PREPARATION AND EVALUATION OF TEA CIDER Thesis by VIKAS KUMAR Submitted in partial fulfilment of the requirements for the degree of DOCTOR OF PHILOSOPHY FOOD TECHNOLOGY 1985 COLLEGE OF HORTICULTURE Dr Yashwant Singh Parmar University of Horticulture and Forestry, Nauni, Solan - 173 230 (HP) INDIA 2014
Dr. V K Joshi Professor and Head Department of Food Science and Technology College of Horticulture Dr. Y S Parmar University of Horticulture and Forestry, Nauni, Solan 173 230 CERTIFICATE - I This is to certify that the thesis entitled Preparation and evaluation of tea cider, submitted in partial fulfilment of the requirements for the award of degree of DOCTOR OF PHILOSOPHY FOOD TECHNOLOGY to Dr. Yashwant Singh Parmar University of Horticulture and Forestry, Nauni, Solan (HP ) is a record of bonafide research work carried out by Mr. Vikas Kumar (H-10-11-D) under my guidance and supervision. No part of this thesis has been submitted for any other degree or diploma. The assistance and help received during the course of investigations have been fully acknowledged. Place: Nauni, Solan (Dr. V K Joshi) Dated:, 2014 Chairman Advisory Committee
CERTIFICATE - II This is to certify that the thesis entitled Preparation and evaluation of tea cider, submitted by Mr. Vikas Kumar (H-10-11-D) to Dr. Yashwant Singh Parmar University of Horticulture and Forestry, Nauni, Solan (HP) in partial fulfilment of the requirements for the award of degree of DOCTOR OF PHILOSOPHY FOOD TECHNOLOGY has been approved by the student s advisory committee after an oral examination of the same in collaboration with the external examiner. Dr. V K Joshi (Professor and Head) Chairman, Advisory Committee External Examiner Members of Advisory Committee Dr. N.S. Thakur Sr. Extension Specialist (PHT) Dr. (Mrs) Nivedita Sharma (Professor) Dr. R. K. Gupta (Professor) Professor and Head Department of Food Science and Technology Dean s Nominee Dean College of Horticulture Dr. Y.S. Parmar University of Horticulture and Forestry, Nauni, Solan (H.P.)
CERTIFICATE - III This is to certify that all the mistakes and errors pointed out by the external examiner have been incorporated in the thesis entitled Preparation and evaluation of tea cider, submitted by Mr. Vikas Kumar (H-10-11-D) to Dr. Yashwant Singh Parmar University of Horticulture and Forestry, Nauni, Solan (HP ) in partial fulfilment of the requirements for the award of degree of DOCTOR OF PHILOSOPHY FOOD TECHNOLOGY. (Dr. V K Joshi) Chairman, Advisory Committee (Dr. V K Joshi) Professor and Head Department of Food Science and Technology Dr. Y S Parmar UHF, Nauni, Solan (HP)
Acknowledgements May good befall all, May there be peace for all, May all be fit for perfection, May all experience that which is auspicious. With limitless modesty, I am deeply indebted to God - The Almighty, the creator, the supreme power, the divine light or whatever He is, who bestowed me with good health and courage enough to complete this task. He is the highest of mankind who enlighten and turned the lives of mankind into peace and good practices. Diction is not enough to express my gratitude to my beloved parents (Shri. Prittam Chand Chopra and Smt. Prem Lata) whose filial affection, prudent persuasion, selfless sacrifices, sincere prayers, expectations and heartfelt blessings have always been the most vital source of inspiration and motivation in my life. The success initiates with the role of parents to culture ethics while completes with the guidance of a teacher. I feel fortunate to be associated with my affectionate supervisor Dr. V. K. Joshi (Professor and Head), Department of Food Science & Technology. He guided during the course of this research work with words of wisdom and training for patience. I am indebted for his sympathetic and kind cooperation provided for this research work as a sympathetic and encouraging supervisor. I emphatically owe my sincere thanks and obligations to Dr. N S Thakur (S r. Extension Specialist, Department of Food Science & Technology), Dr. (Mrs) Nivedita Sharma, ( Professor, Microbiology, Department of Basic Science) and Dr. R K Gupta (Professor, Statistics, Department of Basic Science) for providing me necessary facilities, ideological contributions and prized suggestions to complete my research work. I would like to express my deep appreciation to Dr. Devina Vaidya, Mrs. Surekha Attri and Dr. Manisha Kaushal for providing a homely environment and encouragement for stepping ahead. I feel immense pleasure to avail the opportunity to convey my heartfelt thanks to Dr. P.C. Sharma, Dr. K.D. Sharma, Dr. K S Thakur, Dr. Anju Dhiman, Dr. Dev Raj, and Dr. Rakesh Sharma, Dr. Anil Verma and Mr. Anil Gupta for their constant encouragement and invaluable suggestions during my research work. More words cannot substitute my feelings toward my dear brother (Amit Chopra), beloved brothers-in-law (Suresh Jagota, Anil Soni and Vikas Puri), sisters (Sonika, Monika and Sapna) and their kids (Kajal, Divyansh, Abhishek, Akshit, Vanshu and Avani) for their love, affection and moral backup in needful time. I sincerely acknowledge the help and encouragement received from Sandy, Rishu, Tarun, Pankaj, Dev, Prince, Neelu, Rakesh, Rachit, Hukam, Chandresh, Arvind, Ghanshyam Abrol, Vigya Mishra, Surabhi Sharma, Abhishek Walia, Aneesh, Gaurav, Pooja, Anupma, Reena, Vinay, Bera, Suman, Anshu, Anuradha, Pradeep, Ashwani, Sarita, Nilakshi, Satish, Himnshu, Neeraj, Lucky, Naveen and Sangeeta in my needful time. My heartfelt thanks are due to Ms. Gitanjali Vyas for her much needed support always given at the opportune moments. Enthusiastic co-operation of friendly circle of all my seniors and juniors are also acknowledged. Facilities and co-operation provided by Sh. Kuldeep Abrol ji, Sh. Naresh Bhatia Ji, Sh. Kundan Lal Ji, Sh. Tapender Ji, Sh. Manglesh Ji, Sh Khemchand Ji, Sh. Hemchand Ji, Sh. R. L. Junta Ji, Sh. Lekh Ram Ji, Sh. Raj Kumar Ji, Smt. Kaushalya Ji, Sh. Prakash Ji, Sh.Rohit Ji, Sh. Narender Ji, Sh. Ajay Ji and all staff members of Department of Food Science and Technology are thankfully acknowledged. The commendable credit for the highly efficient typing and manuscript preparation goes to Sh Ravikant Sharma and Sh Ajay Ji, Edge computers, Nauni. I solely claim all the responsibilities for the shortcomings and limitations in this work. Thanks to one and all and to those whose names could not appear but who at one stage or the other has helped me in some ways to achieve the goal. Place: Nauni Date:, 2014 (Vikas Kumar )
CONTENTS CHAPTER TITLE PAGE(S) 1. INTRODUCTION 1-4 2. REVIEW OF LITERATURE 5-61 3. MATERIALS AND METHODS 62-89 4. EXPERIMENTAL RESULTS 90-264 5. DISCUSSION 265-292 6. SUMMARY AND CONCLUSIONS 293-299 7. REFERENCES 300-333 ABSTRACT 334 APPENDICES I-X
LIST OF TABLES Table Title Page 2.1 Composition of apple fruit 7 2.2 Present status of Indian tea and global position 9 2.3 The composition of a typical tea beverage (per cent w/w solids) 10 2.4 Composition of fresh tea flush (% dry weight) 11-12 2.5 Microorganisms associated with freshly pressed apple juice 17 2.6 Varieties suitable for apple wine and cider making 40 2.7 Summary of methods used in cider preparation 42 2.8 Microflora associated with Kombucha 45-46 2.9 Physico-chemical characteristics of different fruit wines 53 2.10 Ethyl alcohol content of different alcoholic beverages 54 2.11 Characteristics of different types of wood samples 58 3.1 Different types of tea leaf extracts 64 3.2 Carbohydrates used and their symbols 70 3.3 Detail of treatments used for conducting the preliminary experiment to standardize of type of sugar source, nitrogen sources and microflora 3.4 Range of values for the RSM 74 71-72 3.5 Experimental plan as per the design 74-75 3.6 Different types of wood chips used for the treatment of apple tea wine 78 3.7 Different treatment combinations for preparation of tea cider 78 3.8 Solvent gradient conditions with linear gradient 83 4.1 Chemical, antioxidant and antimicrobial characteristics of fresh apple juice 4.2 Comparison of antimicrobial activity (inhibition zone in mm) of different concentrations of tea, ethyl alcohol, citric acid and caffeine 4.3 Effect of different concentrations and types of tea on protein content, colour and ph of tea leaf extracts with apple juice 4.4 Effect of different concentrations and types of tea on total phenols, epicatechin and quercetin of tea leaf extracts with apple juice 4.5 Effect of different concentrations and types of tea on caffeine and antioxidant activity of tea leaf extracts with apple juice 4.6 Effect of different concentrations and types of tea on TSS, reducing sugars and total sugars of apple tea wine fermented with Saccharomyces cerevisiae var ellipsoideus 4.7 Effect of different concentrations and types of tea on titratable acidity, ph and volatile acidity of apple tea wine fermented with Saccharomyces cerevisiae var ellipsoideus 91 92 94 97 99 104 106
Table Title Page 4.8 Effect of different concentrations and types of tea on ethanol, higher alcohols and colour of apple tea wine fermented with Saccharomyces cerevisiae var ellipsoideus 4.9 Effect of different concentrations and types of tea on total phenols, epicatechin and quercetin of apple tea wine fermented with Saccharomyces cerevisiae var ellipsoideus 4.10 Effect of different concentrations and types of tea on protein content and amino acids of apple tea wine fermented with Saccharomyces cerevisiae var ellipsoideus 4.11 Effect of different concentrations and types of tea on caffeine and antioxidant activity of apple tea wine fermented with Saccharomyces cerevisiae var ellipsoideus 4.12 Effect of different concentrations and types of tea on antimicrobial activity (inhibition zone in mm) of apple tea win e fermented with Saccharomyces cerevisiae var ellipsoideus 4.13 A comparison of sensory scores of different treatments of apple tea wines fermented with Saccharomyces cerevisiae var ellipsoideus 4.14 Effect of different concentrations and types of tea on TSS, reducing sugars and total sugars of apple tea wine fermented by natural fermentation 4.15 Effect of different concentrations and types of tea on titratable acidity, ph and volatile acidity of apple tea wine fermented by natural fermentation 4.16 Effect of different concentrations and types of tea on ethanol, higher alcohols and colour of apple tea wine fermented by natural fermentation 4.17 Effect of different concentrations and types of tea on total phenols, epicatechin and quercetin of apple tea wine fermented by natural fermentation 4.18 Effect of different concentrations and types of tea on protein content and amino acids of apple tea wine fermented by natural fermentation 4.19 Effect of different concentrations and types of tea on caffeine and antioxidant activity of apple tea wine fermented by natural fermentation 4.20 Effect of different concentrations and types of tea on antimicrobial activity (inhibition zone in mm) of apple tea wine fermented by natural fermentation 4.21 A comparison of sensory scores of different treatments of naturally fermented apple tea wines 4.22 Morphological and biochemical characterization of different microbial isolates from natural fermentation 4.23 Physico-chemical characteristics of the musts ameliorated with different sugar sources 109 111 113 115 117 120 127 130 132 134 137 138 140 143 146 152
Table Title Page 4.24 Effect of different types of sugar sources, nitrogen sources and inocula on TSS ( o B) of apple tea wine 4.25 Effect of different types of sugar sources, nitrogen sources and inocula on titratable acidity (% malic acid) of apple tea wine 4.26 Effect of different types of sugar sources, nitrogen sources and inocula on ph of apple tea wine 4.27 Effect of different types of sugar sources, nitrogen sources and inocula on reducing sugars (mg/100 ml) of apple tea wine 4.28 Effect of different types of sugar sources, nitrogen sources and inocula on total Sugars (%) of apple tea wine 4.29 Effect of different types of sugar sources, nitrogen sources and inocula on ethanol (%) of apple tea wine 4.30 Effect of different types of sugar sources, nitrogen sources and inocula on residual sulphur dioxide (ppm) of apple tea wine 4.31 Effect of different types of sugar sources, nitrogen sources and inocula on volatile acidity (% acetic acid) of apple tea wine 4.32 Effect of different types of sugar sources, nitrogen sources and inocula on higher alcohols (mg/l) of apple tea wine 4.33 Effect of different types of sugar sources, nitrogen sources and inocula on colour (OD 440 nm) of apple tea wine 4.34 Effect of different types of sugar sources, nitrogen sources and inocula on total phenols (mg/l) of apple tea wine 4.35 Effect of different types of sugar sources, nitrogen sources and inocula on caffeine (ppm) of apple tea wine 4.36 Effect of different types of sugar sources, nitrogen sources and inocula on antioxidant activity (%) of apple tea wine 4.37 Effect of different types of sugar sources, nitrogen sources and inocula on colour of apple tea wine 4.38 Effect of different types of sugar sources, nitrogen sources and inocula on taste of apple tea wine 4.39 Effect of different types of sugar sources, nitrogen sources and inocula on aroma of apple tea wine 4.40 Effect of different types of sugar sources, nitrogen sources and inocula on bitterness of apple tea wine 4.41 Effect of different types of sugar sources, nitrogen sources and inocula on overall acceptability of apple tea wine 4.42 Experimental results for CCD of RSM 186-187 4.43 ANOVA for TSS 189 4.44 ANOVA for rate of fermentation 191 4.45 ANOVA for fermentation efficiency 193 4.46 ANOVA for ethanol 195 159 160 161 163 164 166 167 169 170 171 173 174 176 179 180 182 183 184
Table Title Page 4.47 ANOVA for titratable acidity 197 4.48 ANOVA for volatile acidity 199 4.49 ANOVA for higher alcohol 201 4.50 ANOVA for colour 203 4.51 ANOVA for ph 205 4.52 ANOVA for reducing sugars 207 4.53 ANOVA for total sugars 209 4.54 ANOVA for residual sulphur dioxide 211 4.55 ANOVA for total phenols 213 4.56 ANOVA for caffeine 215 4.57 ANOVA for antioxidant activity 217 4.58 ANOVA for overall acceptability 219 4.59 Physico-chemical and sensory characteristics of apple tea wine according to tea concentration as prepared by RSM design 4.60 Physico-chemical and sensory characteristics of apple tea wine according to initial sugar concentration as prepared by RSM design 4.61 Physico-chemical and sensory characteristics of apple tea wine according to initial DAHP concentration as prepared by RSM design 4.62 Physico-chemical and sensory characteristics of apple tea wine according to initial sulphur dioxide concentration as prepared by RSM design 4.63 Physico-chemical and sensory characteristics of apple tea wine according to innoculum size as prepared by RSM design 4.64 Effect of different wood chips treatment on TSS, reducing sugars and total sugars during maturation of apple tea wine 4.65 Effect of different wood chips treatment on titratable acidity, ph and volatile acidity during maturation of apple tea wine 4.66 Effect of different wood chips treatment on ethanol, higher alcohols and colour during maturation of apple tea wine 4.67 Effect of different wood chips treatment on total phenols, caffeine and antioxidant activity during maturation of apple tea wine 4.68 Effect of different wood chips treatment on protein content, amino acids and total esters during maturation of apple tea wine 4.69 Effect of different wood chips treatment on antimicrobial activity (inhibition zone in mm) during maturation of apple tea wine 4.70 Effect of different wood chips treatment on sensory characteristics of apple tea wine 4.71 Effect of blending of different concentration of apple juice with matured apple tea wine on TSS ( o B) of tea cider 222 222 223 223 224 226 229 232 236 239 242 245 247
Table Title Page 4.72 Effect of blending of different concentration of apple juice with matured apple tea wine on reducing sugars (mg/100 ml) of tea cider 4.73 Effect of blending of different concentration of apple juice with matured apple tea wine on total sugars (%) of tea cider 4.74 Effect of blending of different concentration of apple juice with matured apple tea wine on titratable acidity (% malic acid) of tea cider 4.75 Effect of blending of different concentration of apple juice with 251 matured apple tea wine on ph of tea cider 4.76 Effect of blending of different concentration of apple juice with 252 matured apple tea wine on ethanol (%) of tea cider 4.77 Effect of blending of different concentration of apple juice with 252 matured apple tea wine on colour (OD 440 nm) of tea cider 4.78 Effect of blending of different concentration of apple juice with 253 matured apple tea wine on total phenols (mg/l) of tea cider 4.79 Effect of blending of different concentration of apple juice with 254 matured apple tea wine on caffeine content (ppm) of tea cider 4.80 Effect of blending of different concentration of apple juice with 255 matured apple tea wine on protein (mg/100 ml) of tea cider 4.81 Effect of blending of different concentration of apple juice with 256 matured apple tea wine on amino acids (mg/100 ml) of tea cider 4.82 Effect of blending of different concentration of apple juice with 257 matured apple tea wine on antioxidant activity (%) of tea cider 4.83 Effect of blending of different concentration of apple juice with 258 matured apple tea wine on antimicrobial activity (inhibition zone in mm) of tea cider 4.84 A comparison of sensory scores of different treatments of tea cider 262 248 249 250
LIST OF PLATES Plate Title Between Page(s) 1. Different types of tea 63-64 2. Different types of wood chips ( Acacia spp., Quercus spp. and Bombax spp.) 3. Apple tea wine prepared from different concentrations and types of tea fermented with Saccharomyces cerevisiae var. ellipsoideus 4. Apple tea wine prepared from different concentrations and types of tea fermented by natural fermentation 5. Apple tea wine prepared from different types of sugar sources (sucrose @ 20 o B, honey 20 @ o B and apple juice concentrate @ 20 o B), nitrogen sources ( DAHP, peptone and ammonium sulphate) and inocula ( Saccharomyces cerevisiae var. ellipsoideus @ 5 %, consortia 1 @ 5 % and consortia 2 @ 5 %) 63-64 67-68 67-68 73-74 6. Optimized method for preparation of apple tea wine 77-78 7. Tea ciders having apple tea wine matured with different wood chips and different concentrations of apple juice 79-80 8. Estimation of caffeine being carried out with HPLC 85-86 9. Antimicrobial activity (inhibition zone in mm) of different concentrations of tea, ethyl alcohol, citric acid and caffeine 10. Antimicrobial activity (inhibition zone in mm) of apple tea wine prepared from different concentrations and types of tea fermented with Saccharomyces cerevisiae var ellipsoideus 11. Antimicrobial activity (inhibition zone in mm) of apple tea wine prepared from different concentrations and types of tea fermented by natural fermentation 12. Microbial isolates isolated from natural fermentation and used for further experiments as consortia 13. Antimicrobial activity (inhibition zone in mm) of apple tea wine matured different wood chips during maturation of apple tea wine 14. Antimicrobial activity (inhibition zone in mm) of different treatments of tea ciders 93-94 117-118 141-142 147-148 243-244 259-260
LIST OF FIGURES Figures Title Page 2.1 Major apple producing countries of the world and their production during 2011 2.2 Major apple producing countries of the world and their production during 2011 2.3 Wine producing countries with their percentage share 16 2.4 Flow diagram to manufacture apple wine 36 2.5 Flow diagram to manufacture apple cider 44 2.6 Schematic description of Kombucha manufacture 48 3.1 Preparation of tea leaf extracts with apple juice 64 3.2 Fermentation of tea leaf extracts with wine yeast ( Saccharomyces cerevisiae var. ellipsoideus) 3.3 Optimized method for preparation of apple tea wine 77 3.4 Chromatographic peaks of the different standards 83 3.5 Chromatographic peaks of different concentrations of caffeine 84 4.1 A comparison of fermentation behaviour of different types of tea musts 4.2 A comparison of rate of fermentation of different types of tea musts 101 4.3 A comparison of titratable acidity (% malic acid) during fermentation of different types of tea musts 4.4 A comparison of fermentation behaviour of different concentrations of tea in apple tea musts 4.5 A comparison of rate of fermentation of different concentrations of tea in apple tea musts 4.6 A comparison of titratable acidity (% malic acid) during fermentation of different concentrations of tea in apple tea musts 4.7 Dendrogram of different treatments of apple tea wine using various physico-chemical characteristics analysed based on rescaled distance 4.8 Spider web diagram of sensory qualities of apple tea wines (fermented with Saccharomyces cerevisiae var ellipsoideus) made from different tea 4.9 Spider web diagram of sensory qualities of apple tea wines (fermented with Saccharomyces cerevisiae var ellipsoideus) having different concentrations of tea 4.10 A comparison of fermentation behaviour of different types of naturally fermented tea musts 6 9 66 100 101 102 102 103 118 121 122 123
Figures Title Page 4.11 A comparison of rate of fermentation of different types of naturally fermented tea musts 4.12 A comparison of titratable acidity (% malic acid) during fermentation of different types of naturally fermented tea musts 4.13 A comparison of fermentation behaviour of different concentrations of naturally fermented tea musts 4.14 A comparison of rate of fermentation of different concentrations of naturally fermented tea musts 4.15 A comparison of titratable acidity (% malic acid) during fermentation of different concentrations of naturally fermented tea musts 4.16 Dendrogram of different treatments of naturally fermented apple tea wine using various physico-chemical characteristics analysed based on rescaled distance 4.17 Spider web diagram of sensory qualities of apple tea wines (naturally fermented) made from different tea 4.18 Spider web diagram of sensory qualities of apple tea wines (naturally fermented) having different concentrations of tea 4.19 A comparison of fermentation behaviour of different types of fermentation 4.20 A comparison of rate of fermentation of different types of fermentation 4.21 A comparison of titratable acidity (% malic acid) during fermentation of different types of fermentation 4.22 Dendrogram of different types of fermentation using various physicochemical characteristics analysed based on rescaled distance 4.23 Spider web diagram of sensory qualities of apple tea wine fermented by different types of fermentations 4.24 A comparison of fermentation behaviour of musts ameliorated with different sugar sources 4.25 A comparison of rate of fermentation of musts ameliorated with different sugar sources 4.26 A comparison of fermentation efficiency of musts ameliorated with different sugar sources 4.27 A comparison of fermentation behaviour of musts with different nitrogen sources 4.28 A comparison of rate of fermentation musts with different nitrogen sources 4.29 A comparison of fermentation efficiency of musts with different nitrogen sources 123 124 125 125 126 141 144 145 148 148 148 150 151 154 154 154 156 156 156
Figures Title Page 4.30 A comparison of fermentation behaviour of musts inoculated with different microorganisms 4.31 A comparison of rate of fermentation of musts inoculated with different microorganisms 4.32 A comparison of fermentation efficiency of musts inoculated with different microorganisms 4.33 Dendrogram of different treatments of apple tea wine using various physico-chemical characteristics analysed based on rescaled distance 4.34 The three dimensional response surface curves for TSS plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate ( o B) (c) CTC tea (g) and inoculums size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 4.35 The three dimensional response surface curves for rate of fermentation plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate ( o B) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 4.36 The three dimensional response surface curves for fermentation efficiency plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate ( o B) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 4.37 The three dimensional response surface curves for ethanol (%) plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate ( o B) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 4.38 The three dimensional response surface curves for titratable Acidity plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate ( o B) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 4.39 The three dimensional response surface curves for volatile acidity plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate ( o B) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 4.40 The three dimensional response surface curves for higher alcohol plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate ( o B) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 4.41 The three dimensional response surface curves for colour plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate ( o B) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 157 157 157 177 188 190 192 194 196 198 200 202
Figures Title Page 4.42 The three dimensional response surface curves for ph plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate ( o B) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 4.43 The three dimensional response surface curves for reducing sugars (mg/ 100g) plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate ( o B) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 4.44 The three dimensional response surface curves for total sugars (%) plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate ( o B) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 4.45 The three dimensional response surface curves for residual SO 2 (ppm) plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate ( o B) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 4.46 The three dimensional response surface curves for total phenols (ppm) plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate ( o B) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 4.47 The three dimensional response surface curves for caffeine (ppm) plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate ( o B) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 4.48 The three dimensional response surface curves for antioxidant activity (%) plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate ( o B) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 4.49 The three dimensional response surface curves for overall acceptability plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate ( o B) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 4.50 Dendrogram of different treatments of apple tea wine using various physico-chemical characteristics analysed based on rescaled distance 4.51 Effect of different wood chips treatment on TSS ( o B) of apple tea wine at different storage intervals of time 4.52 Effect of different wood chips treatment on reducing sugars (mg/100ml) of apple tea wine at different storage intervals of time 4.53 Effect of different wood chips treatment on total sugars (mg/100ml) of apple tea wine at different storage intervals of time 4.54 Effect of different wood chips treatment on titratable acidity (%) of apple tea wine at different storage intervals of time 204 206 208 210 212 214 216 218 220 227 227 228 230
Figures Title Page 4.55 Effect of different wood chips treatment on volatile acidity (%) of apple tea wine at different storage intervals of time 4.56 Effect of different wood chips treatment on ethanol (%) of apple tea wine at different storage intervals of time 4.57 Effect of different wood chips treatment on higher alcohols (mg/l) of apple tea wine at different storage intervals of time 4.58 Effect of different wood chips treatment on colour (OD 440 nm) of apple tea wine at different storage intervals of time 4.59 Effect of different wood chips treatment on total phenols (mg/l) of apple tea wine at different storage intervals of time 4.60 Effect of different wood chips treatment on caffeine (ppm) of apple tea wine at different storage intervals of time 4.61 Effect of different wood chips treatment on antioxidant activity (%) of apple tea wine at different storage intervals of time 4.62 Effect of different wood chips treatment on protein content (mg/100 ml) of apple tea wine at different storage intervals of time 4.63 Effect of different wood chips treatment on amino acid content (mg/100 ml) of apple tea wine at different storage intervals of time 4.64 Effect of different wood chips treatment on total esters (mg/l) of apple tea wine at different storage intervals of time 4.65 Dendrogram of different treatments of apple tea wine matured with different wood chips using various physico-chemical characteristics analysed based on rescaled distance 4.66 Comparison of overall sensory scores of apple tea wines treated different wood chips treatments after 6 month of storage 4.67 Spider web diagram of sensory qualities of 6 month matured apple tea wine with different wood chips 4.68 Dendrogram of different treatments of tea cider using various physico-chemical characteristics analysed based on rescaled distance 4.69 Spider web diagram of sensory qualities of tea ciders having different apple juice concentrations 4.70 Spider web diagram of sensory qualities of tea cider having apple tea wines of different wood chips treatment 231 233 234 234 237 237 237 240 240 241 243 244 246 260 263 264
Chapter-1 INTRODUCTION Wine is perhaps the oldest known beverage and its origin is traced to the region of Udimu in Egypt, some 5000 years back (Petri c, 1923). Wines have always been considered as safe and healthy drinks, besides an important adjunct to the diet (Stockley, 2011). Man s relationship with wine is as old as history and nature. For centuries, wine has been used in religious ceremonies, for recreational and medicinal purposes. It has been a part of the society, meal and social gathering (Joshi and Sharma, 2004). Brewing and consumption of various liquors was developed traditionally into an art in ancient India (Baisya, 2006), every single tribal society had a balanced and beautiful relationship with spirituous stimulants. Recent findings have also indicated that consumption of red wine is perhaps the miracle savior since phenolic compounds in the wine help to combat heart diseases and other ailments (Muller, 1995). Phytoalexins like reservitrol have been found in grapes had cancer chemoperventive activity (Michael et al., 1993; Meshing et al., 1997). Studies have also shown the beneficial effects of wine consumption due to presence of phenolics and alcohol in wine, which protects human body from free radical attack and increase HDL level in the body (Joshi, 1997, Joshi et al., 2011a). Sonia et al. (1992) reported that 8-18% of ethanol (%v/v) can inhibit bacteria, yeast and mould growth but effectiveness depends upon different physical and environmental factors. Wines are made from complete or partial alcoholic fermentation of grape or any other fruit like apple, plum, peach, pear, berries, cherries, currants, apricot (Amerine et al., 1980, Siby and Joshi, 2003; Joshi et al., 2005; Sharma et al., 2009, Joshi and Kumar, 2011). Compared to the quantity of grape wine produced and consumed in the world, the amount of wine produced from non-grape fruits is insignificant, (Amerine et al., 1980) except cider and perry which are produced and consumed in significant amounts throughout the world ( Jarvis et al., 1995; Joshi et al., 2011a).
A large quantity of wines are produced all over the world, the estimated world production of wine during 2012 was 2,63,84,872 tonnes. Italy and France are the leading wine producing countries in the world ( Anonymous, 2012), whereas India stands nowhere in the world map of wine production. For 2008, the estimated Indian wine consumption was approximately 1.1 million liter cases at a value of approximately US$ 60 million with an annual growth rate of 20% to 25% (Anonymous, 2008). On a per capita basis, Indians consumed about 9 milliliters annually (compared to 9000 milliliters in the U.S.) Apple is used for both dessert and processing purposes such as apple juice, concentrate, wine, vinegar, apple sauce, juice, butter, preserve, candy, jam, jellies and canned products. Most of the apple produced is utilized as fresh apples (Sharma and Joshi, 2005), only a small quantity of the fruit is converted into processed apple products. The alcoholic fermentation of apple juice has been used to obtain a pleasant alcoholic beverage in the Eastern Mediterranean areas for more than 2000 years (Laplace et al., 2001). Presently, apple juice is fermented to manufacture the cider, a sparkling and refreshing fruit flavored beverage, consumed in many countries in the world (Alberti et al., 2011, Joshi et al., 2011a) along with wine and brandy. Tea (Camellia sinensis L.) is the most important non-alcoholic beverage consumed worldwide gaining further popularity as an important health drink. It is consumed as morning drink by 2/3 rd of world population. It is mainly consumed in the form of fermented tea or black tea, non-fermented or green tea and semi-fermented or oolong tea are also popular in Japan and China. Tea leaves have more than 700 chemical constituents, among which flavonoids, amino acids, vitamins (C,E,K), caffeine and polysaccharides are important to human health. The stimulative effect of tea is due to caffeine (1.25-45.5%), (Kurian and Peter, 2007). But polyphenolics are most important constituents acting as antioxidant known to play a very significant role in human health. Black tea is produced by a process that oxidized the polyphenols in the leaves to such substances as are characteristics of black tea and responsible for colour, caffeine content and taste of infusion. Black tea has a strong body due to tannins, which are a group of astringent polyphenolic compounds such as 2
flavonoids (theaflavin and thearubigin) and others derivatives of polyphenols. The natural tannins are powerful reducing agents and exhibit a marked tendency to absorb oxygen, thereby, making tea infusions a possible health drink due to its antioxidant property. Not only in tea, tannins impart body to various fermentation products especially in wines and fermented fruit juices, besides enhancing their flavour profile (Fleet, 2001). Black tea can be considered as a good fermentation medium because its infusion contains proteins, aminoacids, volatile compounds, lipids, enzymes and more importantly polyphenols (Martin and Arnold, 1978). The polyphenols of tea can be utilized to improve the phenolics composition of cider. In our earlier attempt, apple wine was supplemented with extract of herbs that increased the polyphenolic content of different wines and also enhanced its antimicrobial activity (Siby and Joshi, 2003). Kombucha (traditional fermented product), is a fermented tea that is often drunk for medicinal purposes. It has been used in Russia for several centuries. The modern form of Russian Kombucha tea is widely popular and is known as tea kvass or simply kvass ( Murugesan et al., 2009). In the literature, Kombucha is also named as tea cider. Though the product is named as tea cider but in its production neither apple juice: the base of cider production nor any fermented wine is used. The natural microflora conducts the fermentation and alcohol is one of the several compounds produced during fermentation (Greenwalt et al., 2000). Mainly it is the acetic acid formed during fermentation of Kombucha, so the trend is to make a product which is consumed more as a medicine than the mild stimulant beverage as cider. Tea cider is a product under focus in this study is based on fermentation of apple juice with added advantage of flavanoids and polyphenols of tea with residuals or caffeine content only. Cider is produced all over the world and consumed throughout the European countries (Alberti et al., 2011). In India, production of cider is in infancy though a considerable research has been carried out on its various aspects especially in context of India scenario as has been documented (Joshi et al., 2011a). An attempt has been made and documented to prepare wine from tea (Jayasundara et al., 2008). But, there is no information available on the preparation of tea cider using apple juice concentrate with respect to size of inoculum, type of inoculum, quantity of tea infusion, quality characteristics of tea cider etc. Thus, present study on the Preparation and Evaluation of Tea Cider 3
was planned. Effect of different wood chips in order to improve the quality of tea cider has also not been documented and was taken up. The product was evaluated for its various physico-chemical and sensory qualities. The following were the broad objectives of this study: 1. To optimize the fermentation conditions and additives for preparation of tea cider. 2. To determine the effect of different wood chips during maturation on quality of tea cider. 3. To evaluate physical, chemical, antimicrobial, antioxidant and sensory quality characteristics of tea cider. 4
Chapter-2 REVIEW OF LITERATURE Apple (Malus X domestica Borkh.) is one of the most important temperate fruit crops of the world. In India, apple is commercially cultivated in the states of Jammu and Kashmir, Himachal Pradesh, Uttrakhand and Arunachal Pradesh. In Himachal Pradesh, apple has become number one commercial fruit crop. Apple is used for both dessert and processing purposes such as apple juice concentrate, vinegar, apple sauce, juice, butter, preserve, candy, jam, jellies, canned and alcoholic (cider, wine) products. Tea (Camellia sinensis L.) is the most important non-alcoholic beverage having worldwide popularity and is the most consumed drink in the world after water. It is a refreshing, thirst-quenching beverage. Tea is a well known source of flavonoids and tannins having a positive influence on the health of consumers. Similarly, apple is also known for its health promoting properties. At present, medicinal values of consumption of wine is being acclaimed as panacea for cure of cardiovascular diseases though it has been associated with treatment of several diseases in the ancient time (Stockley, 2011). So, preparation of alcoholic beverages by blending these two crops is another outlet for their economic utilization especially for healthful benefits, but there is scanty of published information on their utilization for wine preparation. A brief review of the relevant literature on the preparation and evaluation of cider, apple wine, tea wine and tea cider or related fruit wines has been made and discussed hereunder: 2.1 APPLE PRODUCTION, COMPOSITION AND UTILIZATION 2.2 TEA PRODUCTION, COMPOSITION, TYPES AND UTILIZATION 2.3 WINE PRODUCTION TECHNOLOGY 2.4 ROLE OF RESPONSE SURFACE METHODOLOGY IN WINE PRODUCTION 2.5 CIDER PRODUCTION TECHNOLOGY
2.6 KOMBUCHA/TEA CIDER 2.7 COMPOSITION OF WINE 2.8 MATURATION OF WINES WITH WOOD CHIPS AND ASSOCIATED BIOCHEMICAL CHANGES 2.9 MICROBIOLOGICAL AND SENSORY QUALITIES OF WINES 2.1 APPLE PRODUCTION, COMPOSITION AND UTILIZATION 2.1.1 Production in World, India and Himachal Pradesh Apple is one of the important worldwide temperate fruit crop. The major apple producing countries of the world are China, United States of America, India, Turkey, Poland and Italy (Fig. 2.1). The estimated production of apple acorss the world during 2011 was 7,56,35,283 MT, whereas, the estimated production of apple in India has been reported to be 28,91,000 MT (Anonymous, 2011a) and commercially cultivated in the states of Jammu & Kashmir, Himachal Pradesh, Uttrakhand and Arunachal Pradesh (Anonymous, 2011a). In Himachal Pradesh, apple has become number one commercial fruit crop with annual production of 8,92,112 MT (Anonymous, 2010). Fig. 2.1 Major apple producing countries of the world and their production during 2011 (Anonymous, 2011a) 6
2.1.2 Composition and Nutritive Value Composition of fruit is one of the most important factor influencing the quality of wine. Fresh apple is considered a food of moderate energy value, whereas processed apple products are either comparable to fresh apples in energy value or higher because of concentration, dehydration or addition of sugars during processing. Carbohydrates are the principal constituents in apple and account for about 10.65-13.23 % comprising of 7.05%-10.67% reducing sugars and 1.95-5.02% sucrose (Table 2.1). But it has been regarded as a poor source of protein (0.19 %). Pectin, phenolics and vitamin C content of apple juice ranged between 0.32-0.75 %, 0.15-2.4% and 3.15-5.7 mg/100g, respectively as reported by Mitra, (1991); Sharma and Joshi, (2005). Among the minerals potassium, phosphorus and calcium are present in significant amount in apple while other microelements like Fe, Zn, Mn etc. are present in fruit (Joshi et al., 2011a). Large variation in physico-chemical and flavour characteristics amongst the various cultivars of apple that are used to prepare cider have been reported (Jarvis et al., 1995). Table 2.1. Composition of apple fruit Constituents Average range Calories (k cal/100g) 37-46 Water (g) 84.3-85.6 Fiber (g) 2.0-2.4 Total Nitrogen (g/100g) 0.04-0.05 Protein (%) 0.19 Lipid (%) 0.36 Sugar (per 100g flesh) 9.2-11.8 Total sugars (%) 10.65-13.23 Reducing sugars (%) 7.05-10.67 Sucrose (%) 1.95-5.02 Pectin (%) 0.32-0.75 Phenolic compounds (%) 0.15-2.4 Vitamin C (mg/100g) 3.15-5.7 Source: Mitra, 1991; Sharma and Joshi, 2005 7
2.1.3 Utilization Most of the apple produced is utilized as fresh apples and only a small amount of the total production is converted into processed apple products as reported earlier ( Sharma and Joshi, 2005). Apple is used both for dessert and processing purposes. The processed products include juice concentrate, juice, clarified juice, nectar, vinegar, sauce, butter, preserve, candy, jam, jellies, canned apple products, preserve, toffees, pickles and chutney. Among the fermented products; wine, cider, vermouth are made from apple (Joshi, 1997; Joshi et al., 2011a) while apple wine is distilled to make brandy (Dhiman and Attri, 2011). The apple juice after alcoholic fermentation is used as a base to manufacture cider, a refreshing beverage, consumed in many countries in the world (Alberti et al., 2011). 2.2 TEA PRODUCTION, COMPOSITION, TYPES AND UTILIZATION 2.2.1 Production in World and India Tea is one of the most popular low cost beverages in the world that is consumed by a large number of people. Owing to its increasing demand, tea is considered as one of the major components of world beverage market. Globally, tea has been reported to be cultivated in 36,91,938 ha with an annual production of 40,66,596 thousand Kg as documented by Anonymous, (2011a). Amongst tea producing countries, the principal producers are China, India, Sri Lanka, Kenya and Indonesia (Fig. 2.2). These five countries account for 77% of world production and 80% global exports. India is the second largest producer as well as consumer of black tea in the world. Currently, India has been documented to produces 23% of total world production and consumes about 21% of total world consumption of tea - nearly 80% of the tea produced is consumed within India as showed in table: 2.2 (Majumder et al., 2010). The estimated production of tea in India has been reported to be 9,66,733 MT (Anonymous, 2011a). 8
Fig. 2.2 Major tea producing countries of the world and their production during 2011 (Anonymous, 2011a) Table: 2.2 Present status of Indian tea and global position World India Rank Share (%) Area under tea (Million hectares) 3.94 0.58 2nd 15 Production (Million Kg) 4162 966 2nd 23 Yield (Kg/hectare) 1143 1668 - - Export (Million Kg) 1738 193 4th 11 Consumption (Million Kg) 3980 837 2nd 21 Source: Majumder et al., 2010 2.2.2 Composition and Nutritive Value Kurian and Peter (2007) reported that tea leaves have more than 700 chemical constituent, which include flavonoids, amino acids, vitamins (C,E,K), caffeine and polysaccharides which are important to human health. The composition of a typical tea beverage prepared from green and black tea is shown in table 2.3 (Harbowy and Balentine, 1997). Caffeine is a major purine responsible for the taste and briskness, stimulative effect of tea. Balentine et al. (1997) documented that tea leaves contain 30 per cent polyphenols on dry weight basis. Among the polyphenols, flavanols, flavandiols and phenolic acids (gallic, cumaric or caffeic) are present predominantly. These polyphenols 9
are derivatives of catechin and gallic acid. The natural polyphenols of tea include (-) epigallocatechin-3-gallate (EGCG), ( -)-epigallocatechin (EGC), ( -)- epicatechin-3-gallate (ECG) and epicatechin (EC) with highest concentration of EGCG followed by EGC, ECG and EC in decreasing order. Other catechins including (+) gallocateehin (GC), ( -)-gallocatechin gallate (GCG), ( -)-catechin gallate (CG) and (+) catechin are al so present in minor quantities. Black tea has been reported as a good fermentation medium because the infusion contains proteins, amino acids, volatile compounds, lipids, enzymes and polyphenols (Table 2.4) as documented by Hui (1978) and Zhen et al., 2002. Table 2.3: The composition of a typical tea beverage (per cent w/w solids) Green Tea Black Tea Catechins (%) 30 9 Theaflavins (%) - 4 Simple polyphenols (%) 2 3 Flavonols (%) 2 1 Other polyphenols (%) 6 23 Theanine (%) 3 3 Amino acids (%) 3 3 Peptided Protein (%) 6 6 Organic acids (%) 2 2 Sugars (%) 7 7 Other carbohydrates (%) 4 4 Lipids (%) 3 3 Caffeine (%) 3 3 Other methylxanthines (%) <1 <1 Potassium (%) 5 5 Other mineral/ash (%) 5 5 Aroma Trace Trace Source:- Harbowy and Balentine, 1997 10
Caffeine Theobromine Theanine Source:- Harbowy and Balentine, 1997 Table.2.4 Composition of fresh tea flush (% dry weight) Class of component Acids Minerals Saccharides Polyphenols/Flavonoids Name of each component Amino acids 2-4 Organic acids 0.5-2 Insoluble minerals 1.5-3 Soluble minerals 2-4 Carbohydrates 3-5 Cellulose 6-8 Polysaccharides 4-10 (-)-EC 1-3 (-)-ECG 2-4 (-)-EGC 4-7 (-)-EGCG 9-14 (-)-GC 1-2 Dry weight of each component (%) 11
(+)-C 0.5-1 Flavonol glucosides 3-4 Minor Catechins 0.4-1 Proanthocyanindins 2-3 Other Compounds Caffeine 3-4 Pigments, Insoluble pigments 0.5-0.8, 0.5 Lignin 4-6 Lipids 2-4 Saponins 0.04-0.07 Vitamins 0.6-1 Volatiles 0.01-0.02 Source: Hui, 1978; Zhen et al., 2002 2.2.3 Types of tea Different types of tea have been documented by Nagalakshmi (2003) as: conventional tea i.e. (a) totally fermented black tea, (b) raw or unfermented green tea, and (c) partially fermented Oolong (red and yellow) tea, non-conventional tea products are instant tea (cold and hot soluble), flavored tea, and de-caffeinated tea. Canned or bottled tea, soluble tea mixes, tea beverages, frozen tea liquid, and tea tablets are convenience products. Black tea Workhoven (1974) and Nagalakshmi (2003) documented that black tea is made from young leaves and unopened buds of the tea plant. The major steps involved in the manufacture of black tea have been summarized as plucking, withering, leaf distortion, fermentation, firing, grading, packing, and storage. The 12
fresh green tea leaves from rapidly growing shoot tips are usually harvested by hand, at intervals of 7 14 days. Workhoven (1974) reported that withering step made freshly plucked tea leaves undergo certain biochemical changes like increase in amino acid, simple carbohydrate and caffeine levels; maximal activity of polyphenol oxidase; loss of pectinase activity, and breakdown of chlorophyll and physiological changes that assisted the further processing steps, rolling and fermentation. After the withering process, the leaf is distorted by rolling or cutting. Fermentation is most important for the necessary chemical and biochemical changes in black tea processing. The process starts at the onset of leaf maceration at the end of fermentation, leaf color changes from green to coppery red along with development of a pleasant characteristic aroma. The termination point is determined by the skill of the tea maker or by instrumental techniques. Fermentation is terminated by the firing step and can be assessed by measuring the theaflavin and thearubigin content, which are formed in the ratio of 1:10, under ideal conditions of fermentation. Estimation of tannins is another useful method for this purpose. It has been reported that tannin decreased during this period, from 20% in green tea leaf to 10%-12% in fermented tea (Workhoven, 1974; Nagalakshmi, 2003). Green Tea Around 21% of total tea produce is consumed as green tea, which contains larger amounts of catechins and vitamins (Bokuchava and Skobeleva, 1980; Nagalakshmi, 2003). It has a pleasant taste, flowery aroma, and light green colour. Development of the oxidative process has been regarded as an adverse factor due to the non-fermentation of green tea. Various steps in manufacturing of green tea according to Nagalakshmi, (2003) are plucking, steaming/ roasting, primary heating and rolling, rolling, secondary rolling, drying, refining, firing, sorting, and packing. 13
Herbal Teas or Tisanes or Tea Substitutes The herbal teas, tisanes, and substitutes have been reported as fragrant infusions prepared by dried leaves, flowers, roots, or combinations of aromatic/culinary herbs (Nagalakshmi, 2003). They do not contain tea leaves; however, they are popularly called herbal teas. The infusions are prepared in the same way as tea. They vary widely in color and flavor from pale liquids, delicate in taste, to those that are intense in color and robust in flavor. The most popular ones are leaves of boldo (Peumus boldus), camomile herbs and flowers (Anthemis nobilis), elder flower (Sambuscus nigro), hibiscus flower ( Hibuscus sabdariffa), leaves of lemon verbena ( Lippia citriodora), lime blossoms and leaves ( Tilia cordota and Tilia silvestris), orange flowers (Citrus aurantium), peppermint leaf (Mentha piperita), rose hip fruits (Rosa canina), sage leaves (Salvia officinalis), and thyme leaves ( Thymus vulgaris). Some are good as a hot beverage with sugar; others, such as rose hips, lemon verbena, and hibiscus, are good when cold. Lemon juice has been observed to enhance the flavour of tisanes. These are sold by herbalists and chemists and in health food shops and delicatessens (Nagalakshmi, 2003). 2.2.4 Utilization and different products Tea is the most consumed drink in the world after water. It is a refreshing, thirst-quenching beverage. It is a natural product and virtually calorie-free when consumed without milk and sugar. It is served and drunk in a number of different ways across India. Sometimes, it is brewed and served with milk and sugar, or the leaves are boiled with milk, water, spices, and sugar. On railway stations, trains and street corners, sweet milky tea is poured from hot kettles into disposable cups or mugs. Tea is always served to welcome guests in modern homes as a sign of hospitality. Presently, it is considered as one of the most common and cheapest beverages, which is consumed in more than 65 countries of the world where people drink 4 billion cups daily in the morning. There are different value added products which can be prepared from tea such as tea bags, packet tea, instant tea, 14
flavoured tea, decaffeinated tea, fortified tea, tonic tea, tea cider, tea Kombucha, iced tea, herbal tea and tea concentrate. 2.3 WINE PRODUCTION TECHNOLOGY The word wine is derived from the Proto- Germanic winam, an early borrowing from the Latin vinum, wine or (grape) vine, itself derived from the Proto-Indo-European stem win-o-(cf. Ancient Greek oίvog- oίnos. Aeolic Greek Foivog-woinos, Italian Vino, French Vin, Breton Gwin, Gothic Wein), Dutch Wijn. Similar words for wine or grapes are found in the Semitic languages (cf. Arabic Wayn) and in Georgian ( ğvino); some consider the term to be a wanderwort, or wandering word (Jackson, 1994). Theoretically, wine can be prepared from any fruit having fermentable sugars and nutrients required for fermentation (Amerine et al., 1980). Grape has been a fruit of choice for the preparation of wine. Wines are made from complete or partial alcoholic fermentation of grape or any other fruit like apple (Rana et al., 1986; Joshi and Bhutani, 1990; Joshi, 1997), plum (Vyas and Joshi, 1982; Joshi et al., 1991), peach (Joshi and Shah, 1998; Joshi et al., 2001; Joshi et al., 2005), pear, apricot (Joshi and Sharma, 1993), berries, cherries, pomegranate ( Bomble et al., 2001) and currants (Amerine et al., 1980; Joshi et al., 2011b). 2.3.1 Wine production Compared to the quantity of grape wine produced and consumed in the world, the amount of wine produced from non-grape fruits is insignificant (Amerine et al., 1980; Goswell and Kunkee, 1977; Samarajeewa et al., 1985), except cider and perry which are produced and consumed in significant amounts throughout the world (Shah and Joshi, 1999; Joshi et al., 2011a). But, still there is no published information on the preparation of apple tea wine and tea cider. The estimated world production of the wine in 2012 was 2,63,84,872 thousand liters (Anonymous, 2012). Production statistic of wine producing countries has been depicted in Fig.2.3. 15
Fig. 2.3 Wine producing countries with their percentage share (Anonymous, 2011b) 2.3.2 Microbiology of fermentation Natural fermentation It was in 1866, when Louis Pasteur first elucidated the bio-conversion of grape juice into wine, since then, this complex process and the role of the yeast therein has been studied extensively. Yet, there are many areas which are still not well understood (Pretorius, 2000) especially the role of numerous non- Saccharomyces yeasts normally associated with grape must and wine. These yeasts, naturally present in all wine fermentations to a greater or lesser extent, have been found to be metabolically active and their metabolites can impact on wine quality. Rather, non-saccharomyces wine yeasts have been found to influence the fermentation kinetics of fermentations inoculated with starter cultures of S. cerevisiae (Ciani et al., 2006). While, they were originally seen as a source of microbial related problems in wine production, winemakers, especially in Old World countries, saw indigenous yeasts as integral to the authenticity of their wines as these yeasts have been found to impart distinct regional and other desirable characteristics to the wines (Amerine et al., 1980; Jackson, 1994). 16
Traditional type fermentations typically use wooden mills to crush the fruit and batch mechanical presses to extract the juice. Fermentations are then performed in wooden casks with no temperature control. Wild microflora, which typically have been found to originate from the fruit or from the surfaces of the processing equipment, perform the alcoholic fermentations. The natural fermentation of apple juice has been reported to depend upon the ability of naturally occurring yeasts in the juice to convert the fruit sugars to ethyl alcohol. These yeasts have been found to be native to fruit or normal contaminants on the pressing equipment (Beech and Carr, 1977; Joshi et al., 2011a). Different microorganisms associated with freshly pressed apple juice are listed in table 2.5. However, the use of these methods often causes uncontrolled fermentation and subsequent variation in the final quality of the cider (Morrissey et al., 2004). Table 2.5. Microorganisms associated with freshly pressed apple juice Microorganisms type Typical species Yeast Saccharomyces cerevisiae, S. uvarum, Saccharomycodes Bacteria ludwigii, Kloeckera apiculata, Candida pulcheriima, Pichia spp, Torulopsis famata, Aureobasidium pullulans, Rhodotorula spp., Acetobacter xylinum, Pseudomonas spp, Escherichia coli, Salmonella spp, Micrococcus spp., Staphylococcus spp., Bacillus spp., Clostridium spp. Source: Beech and Carr, (1977); Joshi et al. (2011a) It is well established that the industrial wine fermentations are currently conducted by starters of selected wine yeast strains of Saccharomyces cerevisiae in contrast to traditional spontaneous fermentations conducted by the flora that originate from the grapes and winery equipment without deliberate inoculation to start the process (Heard and Fleet, 1985; Maro et al., 2007). Traditionally, wine has been produced by the natural fermentation of grape juice. Apiculate yeasts of the genera with low alcohol toletance capacity like Kloeckera, Hansensiaspora, Candida, Pichia and, sometimes, Hansenula grow during the early stages of 17
fermentation and grow to about 10 6 10 7 CFU ml -1 but by mid-fermentation i.e. after 3-4 days, begin to decline in population and die off, leaving Saccharomyces cerevisiae as the dominant species to complete the fermentation being more tolerant to ethanol and more competitive for growth in media with high sugar concentration (Amerine et al., 1980; Heard and Fleet, 1985; Querol et al., 1990; Longo et al., 1991; Fleet and Heard, 1993; Ciani et al., 2006; Erten et al., 2006). Generally, the species of Hanseniaspora, Candida, Pichia, Kluyveromyces, Metschnikowia and Issatchenkia are not tolerant of ethanol concentrations exceeding 5 7% (Heard and Fleet, 1988). But these yeasts contribute to a more complex aroma and an improved wine quality (Ciani et al., 2006). The fermentation of apple must is a complex microbial reaction involving the sequential development of various species of yeasts and bacteria and among these micro-organisms, yeasts are primarily responsible for alcoholic fermentation as documented by Beech (1972). Heard and Fleet (1985) also reported that S. cerevisiae dominated the wine fermentations but there was significant growth of the natural species Kloeckera apiculata, Candida stellata, Candida colliculosa, Candida pulcherrima and Hansenula anomala. A wide range of yeasts have been found on grapes and in wines due to variations in vine age, variety, and harvest method ( Zoecklein et al., 1997). Frequently isolated native species include Hanseniaspora uvarum, Kloeckera apiculata, Metschnickowa pulcherrima, Candida pulcherrima, Candida stellata, Pichia membranaefaciens, Hansenula anomala, as well as Cryptococcus, Rhodotorula, and Saccharomyces sp. (Reed and Nagodawithana, 1991). Uninoculated fermentations reported to occur as a succession of yeast populations beginning with relatively weak, although numerically superior, species present on the fruit. These strains are susceptible to increasing alcohol levels and are not as alcohol tolerant as strains of S. cerevisiae (Ribereau-Gayon, 1985). Mortimer (1995) reported that over time the activity of native, non - Saccharomyces yeasts declines and indigenous populations of S. cerevisiae are established and finish the fermentation. Wine flavour was influenced by the large 18
number of yeast species present during spontaneous fermentation (Fleet, 2003; Lambrechts and Pretorius, 2000; Combina et al., 2005; DiMaro et al., 2007) including those from the genera Hanseniaspora, Metschnikowia and Candida, and more occasionally Torulaspora and Pichia. A strain of yeast designated ET 99 was isolated from ogol (Ethiopian honey wine) was found to be fermentation yeast. D-Glucose, maltose, D- galactose, and sucrose were fermented, but lactose was not fermented. D-glucose, D-galactose, maltose, and sucrose were assimilated, but glycerol, 2-keto-Dgluconate, L-arabinose, D-xylose, adonitol, xylitol, inositol, D-sorbitol, methyl-α- Dglucoside, N-acetyl-D-glucosamine, D-cellobiose, lactose, D-trehalose, D- melezitose, and D-raffinose were not. According to these and other characteristics, the strain was identified as belonging to the genus Saccharomyces and was considered to closely resemble S. cerevisiae (Teramoto et al., 2005). Spontaneous fermentation Spontaneous fermentation has been defined as a complex process influenced by many factors, including the endogenous microbial flora, the grape variety, climatic conditions, and the winemaking process. Some wine producers and viticulturists have readopted traditional winemaking methods to generate unique attributes that differentiate their products, improve wine quality and increase the variety of complex flavors that characterize regional vineyards (Diaz et al., 2013). Spontaneous alcoholic fermentation of grape must is a complex process characterized by the presence of a large number of different yeast genera and species (Heard and Fleet, 1988) contributing to the flavour of wines (Maro et al., 2007). The traditional Sherry winemaking method includes spontaneous fermentation that produces distinguished wines, but this practice involves certain well-known risks such as irreproducible or undesirable flavors and aromas, uncompleted sugar depletion, slow or stuck fermentations, etc. (Rodriguez-Palero et al. 2013). 19
Fermentation with Saccharomyces cerevisiae Saccharomyces cerevisiae is the traditional yeast used in wine production. When a desirable natural flora is not established in the vineyard and winery, it is difficult to rely on natural fermentation and accordingly selected yeast cultures are inoculated into the grape must to induce fermentation. The main advantages of inoculated wine fermentations have been described as a more rapid and even rate of fermentation and wine of more consistent quality ( Kunkee and Goswell, 1977). Further the inoculated species, generally a single strain of Saccharomyces cerevisiae was observed to dominate the fermentation and rapidly suppress the growth of unwanted natural yeast species (Benda, 1981). Lea (1995) and Cabranes et al. (1997) have reported that the use of selected pure cultures of yeast for fermentation of apple wine as starters, and the technological advances in other parts of the fermented beverage industry have influenced the apple wine making process. However, the available documented information has been reported to be insufficient yet to permit a full understanding and control of the process. At the same time, the advantages of using pure cultures of Saccharomyces cerevisiae with regard to the easy control and homogeneity of fermentations, wine produced with pure yeast monocultures did not possess the complexity of flavour, stylistic distinction and vintage variability caused by indigenous yeasts (Lambrechts and Pretorius, 2000; Romano et al., 2003). Like wine yeast, the primary function of apple wine yeast has been (Saccharomyces cerevisiae is the major industrial strain) reported to catalyze the rapid, efficient and complete conversion of sugars to alcohol without the development of fermentativer off-flavors. However, slow and incomplete alcoholic fermentations of juice (i.e., sluggish or stuck fermentations) have been advocated as a chronic problem for the fruit wine industry ( Bisson, 1999) that could lead to unscheduled loss of tank capacity due to extended processing times and the potential for microbial instability and off-taste of the final product due to residual sugars. 20
Natural fermentation is also practised to make apple wine but pure culture of yeast Saccharomyces cerevisiae is preferable as the final quality of wine is predictable. Moreover, the physico-chemical characteristics of the beverages fermented by the pure yeast culture were found to be desirable from the enological and toxicological angles (Amerine et al., 1980; Joshi and Sandhu, 2000). Many yeast genera and species, including Saccharomyces spp., possess glucosidase activities (Gunata et al., 1994). Laffort et al. (1989) have suggested that the yeast strains can affect wine aroma as a result of the hydrolysis of conjugated aroma precursors, but Delcroix et al. (1994) demonstrated similar and limited glycosidase activity among three unidentified wine yeast strains. Although Saccharomyces cerevisiae produces β-glucosidase, unlike filamentous fungi, little is believed to be excreted into the liquid medium (Leclerc et al., 1987). Therefore, a large percentage of the grape aroma potential was found to remain in the conjugated, non-volatile form (Gunata et al., 1994; Zoecklein et al., 1997). Microorganisms for inoculation The use of mixtures of different species and strains of yeasts as starter culture (multi-starter culture) to induce desirable fermentation of alcoholic beverages has been considered earlier but application of this concept is still relatively new as reported by Fleet (2008). There are a few techniques in the application of multi-starter cultures for fermentation processes. Among them, simultaneous inoculation of the mixture of species has been employed to control the fermentation (Rojas et al., 2003; Moreira et al., 2005; Chanprasartsuk et al., 2012). In recent years, the inclusion of non-saccharomyces wine yeast species as a part of mixed starters together with S. cerevisiae to improve wine quality has been suggested to have the advantage of spontaneous fermentations without running the risks of stuck fermentations or wine spoilage (Jolly et al., 2003; Romano et al., 2003; Rojas et al., 2003; Ciani et al., 2006; Viana et al., 2008). Although non-saccharomyces wine yeast species have traditionally been 21
associated with high volatile acidity, ethyl acetate production, off-flavours and wine spoilage (Ciani and Picciotti, 1995; Viana et al., 2008), the potential positive role they play in the organoleptic characteristics of wine has been emphasized in numerous studies as reviewed (Fleet, 2003). Metabolic interactions between non-saccharomyces wine yeasts and S. cerevisiae during fermentation could positively or negatively interfere with the growth and fermentation behaviour of yeast species, particularly S. cerevisiae. It is also generally assumed that indigenous yeasts are suppressed due to the competition with starter monocultures inoculated at high-density due to the general use of pure yeast cultures (Pretorius, 2000; Rankine, 1977; Hong and Park, 2013). Thus, to produce unique wine using indigenous yeasts, it is useful to emphasize the beneficial functions of these yeasts to understand inhibitory or harmful effects have also been discussed earlier (Ciani et al., 2010). Different studies have shown that in natural fermentations, Saccharomyces and non-saccharomyces yeasts do not passively coexist; instead, they appear to interact. Under these conditions, some enological traits of the non- Saccharomyces yeasts are not expressed, or they could have been modulated by the S. cerevisiae yeast cultures ( Ciani et al., 2006). In this context, the use of controlled mixed fermentations of Saccharomyces and non-saccharomyces yeast species isolated from the wine environment have been proposed (Soden et al., 2000; Ciani et al., 2006; Jolly et al., 2006; Comitini et al., 2011). Indeed, the use of non-saccharomyces wine yeasts together with Saccharomyces strains in mixed fermentations might be recommended as a tool to obtain the advantages of spontaneous fermentation, while avoiding the risks of stuck fermentation (Romano et al., 2003; Rojas et al., 2003; Jolly et al., 2006; Ciani et al., 2010). Furthermore, non-saccharomyces wine yeasts have some specific enological characteristics that are absent in S. cerevisiae species, and these can have additive effects on wine flavour and aroma (Viana et al., 2008; Comitini et al., 2011). Consortium of yeasts and acetic acid bacteria, known as Kombucha cuture, exhibits a metabolic activity on sweetened tea, under the batch conditions, giving a pleasant sour beverage containing useful compounds such as some 22
organic acids and certain number of vitamins. The association between the two types of microorganisms is unique. Yeasts produce ethanol, which stimulates the growth of acetic acid bacteria and production of acetic acid (Liu et al., 1996). The pineapple juice was fermented with a single and mixed starter cultures of Saccharomyces cerevisiae, Saccharomycodes ludwigii and Hanseniaspora isolate I, at 25 o C for 10 days. Based on their fermentation characteristics, the mixed cultures of S. cerevisiae and S codes ludwigii, S. cerevisiae and Hanseniaspora isolate I, and S. cerevisiae, S codes ludwigii and Hanseniaspora isolate I could generate alcohol content in the final day of fermentation to 12.0, 12.0 and 13.0% (v/v), respectively. The mixed cultures of S codes ludwigii and Hanseniaspora isolate I produced the highest alcohol content of 14.0 % (v/v) in the final day of fermentation and their fermentation profiles were similar to those of the batch of single S. cerevisiae and mixed culture of S. cerevisiae and Hanseniaspora isolate I (Chanprasartsuk et al., 2012). 2.3.3 Technology of wine production Basically the production of wine comprises of several steps/unit operations that include microbiological, biochemical and technological operations. The unit operation in general are procurement of apple fruits, removal of unwanted portions of the fruit, washing of fruit in 0.05% HCI solution, grating/crushing, juice extraction, must preparation, yeast starter culture preparation, inoculation, fermentation, siphoning/racking, maturation and bottling. Apple wine is made from apple juice or apple juice concentrate by alcoholic fermentation (alcohol content 11 to 14%). Apple fruit is used to prepare dry, sweet and table wine which is more nutritious than its distilled liquors (Bhutani et al., 1989; Gasteineau et al., 1979; Joshi and Thakur, 1995). The fruits of golden delicious make apple wine of appealing quality as reported by Joshi (1997). 2.3.3.1 Preparation of yeast starter culture A good strain of wine yeast Saccharomyces cerevisiae is a prerequisite and needs to be procured for making quality apple wine. The yeast in the form of slants, tablet or compressed yeast have been employed for this purpose. Before 23
adding the same to the must for fermentation, the yeast culture is activated in the apple juice intended for wine making. The container with the juice is plugged and kept in a warm place (25-30 C) and the culture is ready after 24 hrs (Joshi et al., 2011c). 2.3.3.2 Preparation of must and its inoculation Juice from apple fruits is extracted first by grating followed by pressing in a hydraulic press. Washing and crushing the fruits, adding 50 ppm of sulphur dioxide and 10% water in making apple wine has been recommended (Joshi et al., 2011c). Apple juice or concentrate is no doubt the basic raw material used for the wine preparation, but amelioration with sugar or juice concentrate is essential to maintain the initial TSS 24 o B. To this, SO 2 @ 100 ppm (to enhance the quality of wine), diammonium hydrogen phosphate @ and pectinol enzyme @ 0.5% (added to the must to help clarification of the wine) are added and allowed to withstand for atleast 2 hours to kill the wild microflora. Addition of diammonium hydrogen phosphate improved the fermentability and made most of the physico-chemical characteristics of apple wine desirable (Joshi and Sandhu, 1997). The must so prepared is inoculated after 2 hours with the active starter culture of Saccharomyces cerevisiae @ 5% (Joshi et al., 2011c) 2.3.3.3 Effect of different initial factors on the quality of wine The quality of wine has been reported to be influenced by several factors like initial sugar source and concentration, nitrogen source and its concentration, vinification practices, type of maturation and blending etc. Yeast cells differ in the way in which they respond to stress conditions during wine fermentation. Stress conditions include any change in environmental factor that could have an adverse effect on cell growth and such conditions may lead to sluggish or stuck wine fermentations (Ivorra et al., 1999). Numerous causes of stuck and sluggish wine fermentations have been recorded, including high sugar concentrations, different nutrient concentration and type of microorganism used (Navarro and Navarro, 2011). So, there is a strong need to review the different factors which affect the quality of end products i.e. wine in terms of its physico-chemical as well as sensory characteristics. 24
2.3.3.3.1 Initial TSS concentration with different sugar sources Initial sugar concentration The concentration of initial sugars is an important parameter in the final ethanol production and its sensory quality. In alcoholic beverage production terminology, amendment of raw material to make a product of consistent quality is referred to as amelioration i.e adjustment of the sugar and/or acid content of the juice, as regulated by the respective standards (Joshi et al., 2011a). Controlling the sugar content of apple juice is required to maintain the proper final alcohol content. Gafner and Schutz (1996) reported that the occurrence of stuck and sluggish fermentations was most frequent in vintages of well matured grapes with high sugar concentrations. It has been found that musts containing high sugar levels expose of the yeast to hypertonic conditions as soon as it was inoculated and causing cell shrinkage (Hohmann 1997). High sugar musts could also lead to higher acetic acid production by yeast during fermentation (Monk and Cowley, 1984). Slaninova et al. (2000) showed that yeast cells respond to hyperosmotic shock by modification of the cell wall and the cytoskeleton. Thus, an elevated amount of sugar was observed to hinder the yeast growth and decreased both the maximum population and the ethanol concentration (D Amato et al., 2006). The effect of initial sugar concentration on time of fermentation has also been recorded as higher sugars tended to prolong the fermentation (Borzani et al., 1993). It is likely that the initial concentrations of glucose and fructose (main grape sugars) will selectively influence the species and strains of yeast present during fermentation. Initial concentration of fermentable sugars in grape musts ranged between 125 and 250 g/l (Fleet and Heard, 1993). In fact, the fermentation was slow in a medium containing low sugar, whereas its speed increased in musts which had 15 20 g of sugar per litre and remained stable until about 200 g /L. Above this concentration, fermentation slowed down. Initial sugar concentration (ISC) of must influence d the physico-chemical and sensory characteristics of cider and its value of 20 B was found optimum (Joshi and Sandhu, 1997; Joshi et al., 2011a); for litchi wine, it was 24 o B (Singh and Kaur, 25
2009); for kinnow wine it was 26 Brix (Panesar et al., 2009). Must prepared by the direct dilution of apple juice concentrate reportedly fermented faster than that ameliorated with sugar (Joshi and Sandhu, 1994; Joshi et al., 2011a). Attri (2009) reported that with the increase in initial sugar concentration from 20 o B to 24 o B in cashew apple wine, there was a decrease in fermentation rate which were attributed to the adverse effects of high sugar concentration on the fermentation efficiency. Titratable acidity, volatile acidity, total esters and total phenols increased and aldehyde decreased with higher initial sugar concentration. It was further reported that wine with initial sugar concentration of 22 o B had better acceptability on the basis of sensory evaluation. Soni et al. (2009) studied the effect of different levels of sugar for amla wine production and reported that amongst the various concentrations of sugar in various batches used, the batch with 10% sugar revealed the highest fermentation efficiency of 90% followed by 88% observed in the batch with 15% initial sugar concentration. The efficiency of alcohol production decreased with an increase in initial sugar concentration which was due to increased osmotic pressure of the medium or overloading of the cells because of high concentration of substrate. The maximum alcohol concentration which could be achieved in the amla wine was 12% in the batch having 25% initial sugar concentration. High substrate concentrations inhibited the growth of yeast cells as a result of high osmotic pressure and low water activity leading to the dehydration of the yeast cells. Different sugar sources During wine fermentations, both monosaccharides (glucose and fructose) are co-fermented by yeasts producing diverse compounds such us carbon dioxide, ethanol, glycerol, etc. However, yeasts have reportedly a slightly higher preference for glucose than for fructose during wine fermentations, resulting in a difference between the consumption of both sugars along the fermentative process (Fleet, 1998; Berthels et al., 2004). This differential consumption resulted in a preponderance of fructose during the last phases of fermentation, which must be fermented by yeasts under stress conditions such as nitrogen starvation or high levels of ethanol (Bauer and Pretorius, 2000; Perez et al., 2005). As a consequence, a considerable residual fructose level in fermented 26
musts might be present, with the corresponding risk of microbial spoilage of the finished wine. Moreover, fructose is approximately twice sweeter than glucose, producing undesirable sweetened sensations in dry wines (Boulton et al., 1996; Wang et al., 2004). Therefore, wine yeasts with a higher capability for fructose consumption are of interest to the wine industry. In general, while both glucose and fructose are utilized simultaneously, glucose is utilized faster than fructose by yeast and S. cerevisiae appears to be glucophilic, although some strains have a clear preference for fructose (Wang et al., 2004). Shafaghat et al. (2009) reported that S. cerevisiae showed high growth rate in a glucose-based medium as compared to the medium containing fructose or sucrose. Grapes and consequently musts have been documented to contain equal amounts of fructose and glucose in a range between 160 and 300 g/l of total sugars (Fleet and Heard, 1993). Differences in the glucose and fructose consumption profiles in diverse Saccharomyces wine species and their hybrids during grape juice fermentation was studied by Tronchoni et al. (2009). They reported that all yeasts assayed showed a slightly higher preference for glucose than fructose at both temperatures, confirming the glucophilic character of Saccharomyces wine yeasts. Apple juice contains many sugars, including fructose, glucose, sucrose as well as other carbohydrates, though in varying concentrations. Unlike mash, the sugar in the highest amount in apple juice is fructose, up to 70% of the total fermentable sugar of 100-150 g/l, plus glucose and sucrose (Lea, 1995; Cabranes et al., 1997). 2.3.3.3.2 Initial nitrogen source concentration with different nitrogen sources Yeasts respond metabolically to differences in nitrogen availability so this lack of control of nitrogen leads to differences in wine composition. Nitrogen affects yeast cells in two ways: it increases biomass production and stimulates the rate of sugar utilization. Nitrogen additions during the period of cell growth have resulted in maximum cell populations. But, later additions during the stationary phase have had no effect on the cell population, but had increased the specific 27
fermentation rate, thus reducing the length of the fermentation (Mendes-Ferreira, 2004). A wide range of compounds in grape juice contain nitrogen. Many factors have been documented to have substantial effects on the quantitative and qualitative nitrogen content of musts, including grape variety and maturity, environmental features (such as soil fertility and climatic conditions), and viticultural practices (grape harvesting techniques) (Bell and Henschke, 2005; Callejon et al., 2010; Crepin et al., 2012). The assimilable nitrogen content in grape juice could range from 60 to 2400 mg L -1 (Jackson, 2008); to levels below 120 140 mg L -1, a nitrogen supplementation, usually as diammonium phosphate, is needed to avoid wine fermentation arrest before the complete fermentation of the high sugar concentrations present (Jackson, 2008). But still, the problem of adequate nitrogen levels in grape musts for a good achievement of alcoholic fermentation has not been totally solved because good sources of nitrogen are accumulated more rapidly and are generally utilized earlier in fermentation than poor sources. Factors such as the composition of juice and yeast strain could also affect the assimilation of nitrogenous compounds as metabolism of amino acids can affect the efficiency of the alcoholic fermentation and the quality of the product (Kocher and Pooja, 2011). Supplementation of must with nitrogen source has also been found essential as in its absence, the yeast was found to use the amino acids present in must resulting in the formation of higher alcohols ( Amerine et al., 1980) and affected some byproducts such as production of aromatic compounds as well as the principal products of sugar fermentation, ethanol and glycerol (Albers et al. 1996; Nicolini et al., 2004). Besides, it also affected the production of esters, higher alcohols, volatile fatty acids, thiols and other volatile compounds (Crepin et al., 2012). The available nitrogen content of apple juice, usually ranged from 27 to 574 mg/l, which had been considered as the main limiting factor for the growth of the yeast (Cruz et al., 2002; Alberti et al., 2011). Since the average value i.e. 100mg/l is reportedly enough to drive to an unstable end product with high residual nitrogen content due to the fact that Saccharomyces sp. did not assimilate 28
all the available nitrogen in the growth phase (Nogueira and Wosiacki, 2010). In this case, nitrogen has not been found a nutrient factor for alcoholic fermentation. But at the same time, increase of nitrogen caused some difficulty to control the fermentation speed and the residual content of sugar in the final product, which showed troubles as cloud or haze formation in the stored cider and also microbiological instability, leading to explosions of bottles due to the formation of gases. The nitrogen fraction in apple juice comprehended the presence of various amino acids such as asparagine, glutamine, aspartic acid, glutamic acid and serine, representing together from 86 to 95 % of total amino acids, and they are rapidly assimilated by yeasts (Alberti et al., 2011). It has been reported that exhaustion of assimilable nitrogen could lead to inactivation of the hexose transport system (Salmon, 1996) and the accumulated ethanol produced by yeast became toxic towards the end of fermentation (Casey and Ingledew 1986). The accumulation of inhibitory metabolites during alcoholic fermentation (e.g. ethanol, acetic acid, long chain fatty acids, etc.) and nutritional deficiencies have been considered as the main causes of stuck or sluggish fermentations conducted by Saccharomyces cerevisiae (Bisson, 1999; Varela et al., 2004; Palma et al., 2012; Fairbairn, 2012), an increase of SO 2 -binding fermentation products, an increase of undesirable concentrations of volatile fermentation products like higher alcohols and H 2 S. This deficiency could be ameliorated by supplementation with di-ammonium phosphate (DAP), an ammonium source (Salm on, 1989). The latter was a preferred yeast nitrogen source, and when plentiful, it repressed the expression of catabolic pathways by degrading other nitrogenous compounds (Beltran et al., 2005). A common practice amongst winemakers has been to make a standard addition of DAP to the juice or must (100-300 mg/l) at inoculation without measuring the nitrogen concentration. Once preferred sources became limited, the genes for uptake and utilization of alternative sources are subsequently de-repressed (Deed et al., 2011). On the contrary, if excessive addition of ammonium, there could be a risk of modify characteristics of wine for higher alcohols (Beltran et al. 2005), acetic acid (Bely et al. 2003), ethyl carbamate (Ough et al. 1988) or in some conditions even hydrogen sulphide content (Wang et al. 2013). 29
DAHP @ has been used as a yeast food in alcoholic fermentation and its addition to the musts made from apple juice concentrate and pear for alcoholic fermentation has also been reported (Joshi and Sandhu, 1994; Joshi et al., 2011a). Fortification of apple juice after dilution from its concentrate with diammonium hydrogen phosphate was essential for rapid fermentation. Joshi and Sandhu (1994); Joshi et al. (1991) reported that, the must prepared by direct dilution of the concentrate reportedly fermented faster than that ameliorated with sugar. Joshi et al. (1990a) also reported that, addition of DAHP at the rate of enhanced the rate of fermentation considerably in wild apricot fermentation, regardless of dilution levels. In general, an increase of mineral nutrients with addition of DAHP was observed and the overall quality of wine was not altered by the addition of nitrogen source (Joshi et al., 2011a). Out of two nitrogen sources viz: urea and di-ammonium hydrogen phosphate, urea induced the cell for high rate of sugar utilization and highest yield of ethanol was obtained during the production of palm wine (Ghosh et al., 2010). Soni et al. (2009) studied the effect of nutritional factors by supplementing the production medium for preparation of amla wine, separately, with various nitrogen sources (0.5% w/v) including ammonium sulphate, urea, diammonium hydrogen phosphate, malt extract, yeast extract, soyabean meal, corn steep liquor, peptone, metal salts ( w/v) including magnesium sulphate, calcium chloride, sodium chloride, potassium chloride, zinc sulphate, potassium dihydrogen-orthophosphate, amino acids (0.01% w/v) including alanine, phenyl alanine, tyrosine, tryptophan, ornithine, threonine, aspartic acid, proline, serine, valine, arginine, leucine, lysine, glutamic acid, glycine, methionine, histidine, cystine and vitamins (0.01% w/v) including thiamine, riboflavin, nicotinic acid, pantothenate, biotin, niacin, pyridoxine, folic acid and β-complex. They reported that out of the various nitrogenous compounds evaluated, ammonium sulphate induced the maximum alcohol level which was attributed to the benefits of fermentation with the addition of ammonium salts along with sulphur. It has been found that di-ammonium hydrogen orthophosphate (DAHP) supplementation improved the wine colour, total acids, bouquet, taste, aroma and overall sensory quality of guava wine (Kocher and Pooja, 2011). 30
2.3.3.3.3 Initial sulphur dioxide concentration The antiseptic qualities of sulfur and sulfur dioxide have been known for more than two thousand years. But it wasn't until the mid 1800's, when the association of sulfur compounds and their biological effect on bacteria and yeast began to be understood. Sulfur dioxide (SO 2 ) has been used in wine production since ancient times (Fazio and Warner, 1990; Divol et al., 2012) with the diverse purposes. Sulphur dioxide has been reported as an antioxidant (preventing the oxidation of compounds such as anthocyanins in red wines, reducing the effects of browning in white wines (caused by oxidative enzymes) and protecting both the fruit and the wine against negative changes brought about through contact with oxygen besides serving as a preservative, inhibiting the development of unfavourable microorganisms (Burroughs 1974, Vine et al., 1997; Reddy et al., 2008; Divol et al., 2012; Aberl and Coelhan, 2013). It has also been found to binds with fermentation by-products responsible for off-flavours such as acetaldehyde, thus guaranteeing the desired aroma profile (Schroeter,1966; Gould, 1989; Fazio and Warner, 1990; Russell and Gould 2003; Aberl and Coelhan, 2013). Both free and bound SO 2 is present in wine, however only the free SO 2 provides comprehensive protection to wine (Temperli and Hesford, 2005). The portion of sulfite that is not bound to any food component is called free sulfite (Fazio and Warner, 1990) which exists as SO 2, bisulfite (HSO - 3 ) and sulfite (SO 2-3 ) in a chemical equilibrium depending on ph. Since the ph of wine normally ranges from 3.2-4.0, bisulfite is the predominant form of free SO 2 (Fazio and Warner, 1990). The amount of free SO 2 was found greater in an acidic solution and droped rapidly as the ph was increased (Gould, 1989; Fazio and Warner, 1990; Aberl and Coelhan, 2013). During the initial phase in traditional fermentation using only indigenous microflora, very little sugar was found to be metabolized and only small amounts of alcohol was produced. During this period the number of Saccharomyces yeasts was also low, yet non-saccharomyces yeasts were able to reach very high cell densities and they might have persisted through a large part of the alcoholic 31
fermentation (Heard and Fleet, 1985; Henick-Kling et al., 1998). So, the treatment of juice with SO 2 before fermentation was found as the most common means of controlling undesirable micro-organisms because SO 2 was found highly toxic to the non-saccharomyces yeasts as well as helpful in preventing enzymatic and non-enzymatic browning reactions and is a well established practice in wine making ( Rana et al., 1986). But, if SO 2 is added immediately after pressing, nearly all the colour will be (chemically and visually) reduced because sulphite binds to the quinoidal forms. When, it is added added at the later stage, less reduction in colour will take place-presumably the quinones become more tightly cross linked and less susceptible to nucleophilic addition and reduction. Sulphur dioxide also has a clarifying action, reduces volatile acidity and exerts solvent effect on anthocyanin pigments ( Amerine et al., 1980; Joshi et al., 2011a). The maximum permitted concentration of total SO 2 in wine by law is set in the European Union by Council Directive (European Parliament and Council, 2009). Depending on the sort of wine, as well as the amount of sugar in the wine, the maximum total SO 2 contents have been allowed as 150 mgl -1 for red wine, 200 mgl -1 for white and rose wines and 250-400 mgl -1 for wines containing more than 5 gl -1 sugar (European Parliament and Council, 2009). Kunkee (1967) reported that SO 2 (50 mg/l of total SO 2 ) treatment delayed the beginning of alcoholic fermentation and after SO 2 application, a decrease in the yeast population was observed with respect to the control. Usually, 100-200 ppm SO 2 has been added to the cider and musts. Malo-lactic fermentation reportedly occurred in wines containing SO 2 at concentrations up to 130-160 mg/l. Sugars, aldehydes and anthocyanin pigments were found to bind with SO 2 so that the concentration of free SO 2 in dry red wines is usually less than 4 mg/l (Rankine, 1977). Louisa et al. (1981) reported that in the experimental Cinsaut wine, the lower SO 2 concentration of 34 mg/l was significantly more favourable for the induction of malo-lactic fermentation (MLF) over a range of 30 isolates than the higher SO 2 concentration of 61 mg/l. Ton et al. (2010) reported that when the initial SO 2 content in must was augmented from 12 ppm to 112 ppm, the maximum specific growth rate and maximum cell density of the immobilized and free yeast cultures remained 32
unchanged or increased slightly. On the contrary, when the initial SO 2 content in must increased from 112 ppm to 312 ppm, both maximum specific growth rate and maximum cell density of the immobilized and free yeast cultures decreased sharply. They further reported that the maximum specific growth rate and maximum cell density of the immobilized yeast culture was always higher than those of the free yeast culture except that in medium with 312 ppm sulfur dioxide but these values were insignificantly different. Henick-Kling et al. (1998) observed that in inoculated and uninoculated musts the addition of sulfite (20 and 50 mg l -1 ) did not change the fermentation rate. Both in inoculated and uninoculated musts, the addition of 20 mg l -1 sulfite to the must did not produce a discernible difference in the total cell number of indigenous non-saccharomyces yeasts. However, when 50 mg l -1 sulfite was added, there was significantly less growth and the yeast persisted for a shorter period only. Use of 50 to 100 ppm SO 2 was recommended for preparation of good quality ber wine (Patil et al., 1995), for pear wine it was 100 ppm (Amerine et al., 1980), for mango wine also it was 100 ppm (Kulkarni et al., 1980). 2.3.3.3.4 Inoculum size It is well known that Saccharomyces cerevisiae produces different concentrations of aromatic compounds as a function of fermentation conditions and must treatments. Additionally, sluggish and stuck fermentations often have been related to nitrogen deficiency (Bisson, 1999) and to the small size of the inocula of S. cerevisiae (Cuinier, 1983; Carrau et al., 2010). Inoculum size has been documented as a well known key process parameter in microbial fermentation (Medina et al., 1997; Carrau et al., 2010), paradoxically, its impact in wine quality parameters has been studied in a very limited fashion and in no case the nutrient balance of the grape must utilized has been taken into account (Carrau et al., 2010) and some of these studies showed that a higher level of inoculum resulted in higher fermentation rates, although in sparkling wines this effect was not seen over 4 10 6 cells/ml (Monk and Storer, 1986). Higher inoculum size resulted in higher yields of glycerol and ethyl alcohol (Radler and Schutz, 1982; Carrau et al., 2010). 33
The standardization of inoculum size is important as sugar consumption is a balance between biomass development and ethanol production. A high inoculum size will thus be compromising on amount of ethanol produced. Ethanol production has been found to increase with increase in inoculum concentration up to 9% (v/v) and decreased significantly beyond inoculum level of 9% (v/v) in case of three varieties of guava viz; Punjab pink, Arka amulya and Lucknow-49 (Pooja, 2011), whereas, Singh and Kaur (2009) optimized 10 % (v/v) inoculum for litchi wine production, Panesar et al. (2009) optimized 7.5 % (v/v) inoculum for kinnow wine production, Bomble et al. (2001) optimized 5% inoculum for pomegranate wine production, for preparation of ber wine 2 to 5% yeast inoculum was recommended by Patil et al. (1995). 2.3.3.4 Fermentation The must is allowed to ferment at a suitable temperature (20-25 C) after inoculation with yeast culture. Temperature higher than 26 C has been recommended because it causes loss of volatile components and alcohol. The sugar content or Brix is measured periodically to monitor the progress of fermentation. Normally, fermentation is allowed to proceed till the whole sugar is consumed completely (usually Brix reading of about 8 B). When fermentation is completed, bubbling due to production of CO 2 is stopped (Amerine et al., 1980 and Joshi et al., 2011c) Amerine et al. (1980) documented that natural fermentation is also practised to make apple wine but pure culture of yeast Saccharomyces cerevisiae is preferable as the final quality of wine is predictable. 2.3.3.5 Siphoning/Racking After completion of fermentation, the yeast and other materials that settle at the bottom of container with clear liquid (apple wine) separating out, is siphoned/racked. Two or three racking is usually done after 15-20 days. During inter-racking period, no headspace is kept in the bottle or container which is closed tightly to prevent any acetification (Joshi et al., 2011c). 34
2.3.3.6 Maturation The newly made apple wine is harsh in taste and has yeasty flavour. The process of maturation makes the wine mellow in taste and fruity in flavour besides the clarification. The period may extend up to 6 months to 2-3 years. The process of maturation is complex and the formation of esters takes place thus, improving the flavour of such beverages (Joshi et al., 2011c). 2.3.3.7 Pasteurization Wines being low alcoholic beverages are pasteurized at 62 C for 15-20 min, after keeping some headspace in the bottle and crown corking the same. The wines having higher alcohol contents like fortified wines need no preservative as the alcohol itself acts as a preservative above 15% alcohol (Joshi, 1997). 2.3.4 Optimized technology of apple wine production Based on various functions optimized, Joshi et al. (2011c) had reported a method for preparation of apple wine and various unit operations are depicted in figure 2.4. 2.4 ROLE OF RESPONSE SURFACE METHODOLOGY IN WINE PRODUCTION Optimization of process conditions is one of the most critical stages in the development of an efficient and economic bioprocess. Bas et al. (2007) reported that statistical methodologies involve use of mathematical models for designing fermentation processes and analyzing the process results. RSM is a powerful mathematical model with a collection of statistical techniques by which interaction between multiple processes variables can be identified with fewer experimental trials. Response Surface Methodology (RSM) is a combination of mathematical and statistical techniques that is useful for analysing the effects of several independent variables on the system response as reported by Myers and Montgomery (2002). RSM is a group of statistical techniques for designing experiments, building models, evaluating the effects of factors and searching for the optimum conditions. It has been documented as one of the most efficient tools to optimize parameters in biosystems (Frank, 2001; Seth and Mishra, 2011; Jaiswal et al., 2011; Sevda et al., 2012). 35
Apple Removal of unwanted portions of the fruit Washing of fruit in 0.05% HCI solution Addition of sugar syrup to raise Brix to 24 B Addition of SO 2 (100 ppm) Addition of diammonium hydrogen phosphate @ Grating/Crushing Extraction of juice Extracted juices Apple must Ascorbic acid solution spraying (1%) Apple Pomace Pectinol enzyme @ 0.5% Addition of culture of Saccharomyces cerevisiae @ 3-5% CO 2 gas collection Fermentation (Temp. = 22±1 C Time = 10-12 days) Removal of yeast Addition of aroma, adjustment of TSS and acidity Crown Cork Filtration and storage in tank for aging (time 6-12 months) Filtration and clarification Bottling in sterilized bottle, crowing and pasteurization of Bottles Removal of waste (for BOD reduction) Label Corrugated boxes Labelling and packing Storage Market Fig. 2.4. Flow diagram to manufacture apple wine (Joshi et al., 2011c) 36
It is a statistical approach which uses quantitative data from appropriate experiments to simultaneously determine and solve multivarient equations thus providing an optimum solution as reported by Kalil et al. (2000) and Daramola et al. (2007). Optimization of parameters by the conventional method involves changing one independent variable while unchanging all others at a fixed level. But, is extremely time-consuming and expensive for a large number of variables (Adinarayana et al., 2003) and also might result in wrong conclusions (Oh et al., 1995). Several advantages in using statistical methodologies in terms of rapid and reliable short listing of process conditions, understanding interaction among them and a tremendous reduction in total number of experiments, resulting in saving time, glassware, chemicals and manpower. RSM significantly reduces the number of experiments needed to evaluate multiple parameters and their interactions have been advocated (Montgomery, 2001), thus making it convenient and time-efficient as documented by Myers (1976); Sevda et al. (2012). Particularly, central composite designs with star points have been found very useful because they provide rotatability, high quality predictions over the entire design space and low number of experimental runs (Myers and Montgomery, 2002; Arroyo-Lopez et al., 2009). In RSM, the experimental responses to the design of experiments have been fitted to quadratic function. The numbers of successful applications of RSM have suggested that the second-order relation can reasonably approximate several of the fermentation systems as reported by Popov et al. (2010). In spite of various advantages, statistical designs have been applied in fermentation medium optimization with a large number of variables and there are several reports on the application of RSM for the production of primary and secondary metabolites through microbial fermentation (Karuppaiya et al., 2009). McMeekin et al. (1993) documented that, this methodology has also widely been used in predictive microbiology as a secondary model to predict the microbial response to environmental changes. Kumar et al. (2009) and Wand et al. (2013) reported that this method has been extensively used to optimize chemical and biochemical processes such as alcoholic fermentation and other fermentation media, production of enzymes, composition of cultivation media, conditions of 37
enzymatic hydrolysis, parameters for polymer synthesis and parameters for food processing. Different scientists used RSM in fermentation field such as Hari and Chowdary (2000) used it for optimization of simultaneous saccharification and fermentation for the production of ethanol from lignocellulosic biomass, D'Amato et al. (2006) used it to study the effects of temperature, ammonium and glucose concentrations on yeast growth in a model wine system, Arroyo-Lopez et al. (2009) used RSM to study the effects of temperature, ph and sugar concentration on the growth parameters of Saccharomyces cerevisiae, S. kudriavzevii and their interspecific hybrid, Panesar et al. (2009) used it for optimization of process parameters for production of kinnow wine, Tzeng et al. (2009) used it for optimization of fermenting conditions for sugarcane (Saccharum officinarum l.) wine production, Baladhandayutham et al. (2009) used it for optimization of solid-state fermentative production of pectinase by Aspergillus awamori, Kumar et al. (2009) used it for optimization of fermentation conditions for mango wine production, Popov et al. (2010) used it for bioethanol production from raw juice as intermediate of sugar beet processing, Karuppaiya et al. (2010) used it for optimization of process variables for ethanol production from cashew apple juice by Saccharomyces cerevisiae, Almeida et al. (2010) used it for optimization of processing conditions for wine production from Acerola ( Malpighia glabra L.), Koak et al. (2010) used it for optimization of blending of different domestic grape wines, Duarte et al. (2011) used it for optimization of fermentation conditions for production of the jabuticaba ( Myrciaria cauliflora) spirit, Sevda et al. (2012) used it for optimization of guava juice, Hajar et al. (2012) used it for optimization of ethanol fermentation from pineapple peel extract, Yan et al. (2012) used it for optimization of the alcoholic fermentation of blueberry juice by AS 2.316 Saccharomyces cerevisiae wine yeast, Ghosh et al. (2012) used it for optimizing process conditions for palm ( Borassus flabelliffer) wine fermentation, Wang et al. (2013) used it for optimization of fermentation process for preparation of mulberry fruit wine, Corona-Gonzalez et al. (2013) used it for optimization of fermentation conditions in the production of tepache (a tradition fermented drink 38
of Maxico prepared from pineapple peel, sugar, water and spices like cinnamon and pepper). 2.5 CIDER PRODUCTION TECHNOLOGY Apple fruit is used to prepare mild alcoholic beverages which are more nutritious than distilled liquors. The fruit is more associated with cider than other alcoholic beverages. Cider-a low alcoholic drink, is a popular beverage especially in those countries where grape-vine cultivation is not practised due to agroclimatic conditions. It is produced from apple ( Malus domestica Borkh.) a premier temperate fruit grown extensively throughout the world. The quantity of cider produced is second only to the wine produced from grapes. Out of the two, cider has become an increasingly important commercial product in recent years as documented by Jarvis et al. (1995). France is the world s largest cider producing country. Normandy and Brittany in northern France are the main apple cider-producing region and are famous for their traditional sweet cidre as documented by Joshi et al. (2011a). In Great Britain and France, the term cider (Cider or Cidre) means apple wine, hard cider or fermented apple juice but in U.S.A. it may mean fermented or unfermented apple juice based on the definitions and available products, broadly it can be classified, as follows: Soft Cider : 1-5 % alcohol content, Hard Cider : 5-8 % alcohol content and Apple wine: Above 8% but may go up to 14% (Downing, 1989; Joshi, 1997). Rana et al. (1986) and Joshi (1997) reported that c ider with 5 per cent alcohol, TSS/acid ratio of 25 was found to be the most favoured at laboratory and consumer survey scales. Sparkling sweet cider is produced by fermenting apple juice containing not more than 1% alcohol (v/v) and the natural CO 2 formed during fermentation is retained. Sparkling cider has lower sugar and higher alcohol content of 3.5% but with partial retention of CO 2 formed during fermentation. Carbonated cider is charged with commercial CO 2 to produce effervescent (Joshi et al., 2011a). Recently, low alcoholic beverages have gained importance in preventing cardiovascular diseases. Joshi et al. (1999) reported that consumption of wine prevents the formation of LDL and increases HDL levels (having protective effects against heart diseases). The use of hops and spices in the cider has 39
imparted antimicrobial activity and is considered significant (Joshi and John, 2002). 2.5.1 Cultivars used for cider preparation Downing (1989) has reported that cider can be prepared from any apple but choice of right cultivar is one of the important factor influencing the quality of cider. Different varieties of apple suitable for cider making have been recommended (Table 2.6) especially the four different types i.e. bitter sweet (low in acidity but high in tannin); bitter sharp (high acidity a nd high tannin); sharp varieties (high acidity but low tannin); sweet varieties (low acid and bitter) (Smock and Neubert, 1950; Beech and Carr, 1977; Jarvis et al., 1995; Labelle, 1980; Pourlx and Nicholas, 1980; Rana et al., 1986; Vyas and Kochhar, 1986). However, in India, cider production is in infancy and the suitability of Indian varieties for cider production has not been adequately worked out though Ambri- Kashmiri, Red Delicious, Golden Pippin, Maharaji apples and crab apples, Golden Delicious, Red delicious and Rus Pippin have been found suitable for cider making (Jarvis et al., 1995; Joshi et al., 1991; Joshi et al., 1994). Table 2.6 Varieties suitable for apple wine and cider making Sr. No. Varieties Suitability Quality characteristics 1. Delicious,Cortland, Cider, Rome Beauty Low acid group 2. Jonathan, Winesap, Stayman, Cider Stayman, Northern spy, Rhode Island, Greening Wealthy, Higher acid group Newton, Wayne 3. McIntosh, Gravenstein, Golden Russet, Cox's Orange, Roxbury Russet, Wealthy Aromatic group 4. Dabinett, Michelin, Chisel Jersey, Harry Masters Jersey, Yarlington Mill, Viberie, Bitter sweet Medaille, Bedan, Kermerrein 5. Breakwells seedling, Backwell Red, Brown's Apple, Crimson King, Stoke Red Frederick, Sharp/Bittersharp Kingston Black 6. Sweet Copin, Sweet alford, Northwood Sweet Source: Jarvis et al., 1995; Labelle, 1980; Pourlx and Nicholas, 1980; Rana et al., 1986; Vyas and Kochhar, 1986 40
2.5.2 Methods of cider making Amerine et al. (1980) and Joshi et al. (2011a) reviewed the different methods used to make cider in a systematic way and are summarized in Table 2.7. Kerni and Shant (1984) also documented that there are some reports on the studies of cider preparation from India also. Rana et al. (1986) developed a method for sweet cider preparation and reported that coder having 5 % ethanol with TSS/acid ratio of 25 was found to be the most favoured at laboratory and consumer survey scales. Apple base wine is blended with fresh apple juice and the ratio of base wine to juice is 1:1. The blend is checked for TSS which should give a reading of about 10 o B (Joshi and Sandhu, 2000). 2.5.3 Clarification Joshi et al. (2011a) reported that juice and cider can also be clarified and one of the clarification treatments consists in adding gelatin with tannin solution. This treatment can be used either on the juice before fermentation or on cider before bottling. By removing selectively high DP procyanidins this treatment has been reported to modofied both the total tannin content and the profile of the residual tannins, and thus may change the composition was well as the taste of cider. But the most common clarifying method in French cider making is the keeving process which use endogenous pectin as a clarifying agent: after demethylation of the pectin by an enzyme-the pectinemethyesterase-calcium is added to induce a formation of a calcium pectate gel that includes all particles of the cloudy juice. This gel so made then could be separated by a natural flotation due to CO 2 bubbles of the beginning fermentation. This process produces a pectin-free clarified juice with a reduced nitrogen amount and results in slower fermentation and better stabilization (Quere et al., 2006). Joshi, (1997) reported that cider can also clarified by tannin-gelatin solution or pectolytic enzyme addition. 41
Table 2.7 Summary of methods used in cider preparation Type of method European Method-1 a) Some stored for 3-4 days and others macerated Method -2 Method -3 Fruit Juice Parameters Additive b) -- Lower sugar, higher acidity Sound fruits separated by floation Extracted as usual, cold stabalised at 0-7.8 C Source: Amerine et al., 1980; Joshi et al. (2011a) -- Juice extracted, no. maceration, juice centrifuged for bacteria and yeast removal Juice extracted in hydraulic press SO 2 50-100 mg/1 Pectic enzymes for clarification Lactic acid added to increase acidity, if needed Fermentation Maturation Others Temperature 4.4 to 10 C, Secondary pure yeast in some, mixed fermentation in others in casks for several months Pure yeast such as Steinberg added -- Natural fermentation from 1.008-1.005 sp. gravity Method -4 -- -- -- Fermentation allowed up to specific gravity of 1.025-1.030 (5-7.5 B) filltered or centrifuged American Method -1 a) Sound apples are used for cider making b) Juice extraction istead of apple juice concentrate used Juice is extracted in usual press after crushing in a mill Juice made from concentrate Sulphur dioxide 100-125 ppm added, glucose added to give 13 per cent alcohol Sweetened Spontaneous fermentation may begin during settling Yeast Champagne, 24.4 C temperature was the best Malolactic fermentation, produces CO 2 in bottles -- -- Storage in concreate tanks lined with coatings Stored in wooden casks Before delivery, cider is sweetened with syrup Carbonated and bottled -- Clarified by Bentonite treatment, blended to give 10 B, filtered, bottled and pasteurized -- -- 42
After completion of fermentation, the reported practice is to leave the cider on the lees for a few days to facilitate the yeast to autolyse, thereby adding enzymes and amino acids to the cider. Then, the cider would be separated from the lees and transferred after clarification into the storage vats or storage tanks (Jarvis, 1993). Initial clarification may be performed by the natural settling of well flocculated yeast, by centrifugation, by fining, or by a combination of all the three. Typical fining agents are bentonite, gelatin, isinglass or chitosan. Gelatin has been reported to form a flock with negatively charged tannins in the cider and brings down other suspended materials by entrapment and can also be used together with bentonite for similar effect (Joshi et al., 2011a). 2.5.4 Blending of apple juice in base wine for cider production Blending has been reported as an important step in controlling uniformity of the finished product (Joshi, 1997). Juice from apples in the sweet group is considered good for blending with strong flavoured juices while that in the bittersweet group gives cider a tangy sensation. Juice for making sparkling sweet cider should not be too sweet or too heavy in the body. Astringency is considered less important than the correct sugar/acid ratio but the juice should not have more than tannin as reported by Joshi (1997). Juice used for fully fermented and sparkling ciders should be high in sugar, of moderate acidity and fairly astringent. A method to produce still (non -carbonated) sweet off apple cider from Golden Delicious variety of apple has been shown in figure 2.5 (Joshi, 1997). 2.6 KOMBUCHA/TEA CIDER Tea cider is also known as Kombucha, tea kvass or simply kvass (Murugesan et al., 2009), is a fermented tea that is often drunk for medicinal purposes. Since, neither apple juice (the base of cider production) is used or nor apple wine is employed in its production. So naming it as tea cider is really misnomer. Kombucha tea has been used in Russia for several centuries. This refreshing beverage tasting like sparkling apple cider is often produced at home by fermentation using a tea fungus passed from house to house (Dufresne and Farnworth, 2000). Fermented tea decoctions such as Kombucha have been 43
prepared by co-fermentation with yeast and acetic acid bacteria, and are known to have health benefits (Guttapadu et al., 2000). Apple Removal of unwanted portions of the fruit Addition of sugar syrup to raise Brix to 20 B Addition of SO 2 (100 ppm) Addition of diammonium hydrogen phosphate @ Addition of culture of Saccharomyces cerevisiae @ 3-5% CO 2 gas collection Washing of fruit in 0.05% HCI solution Grating/Crushing Extraction of juice Extracted juices Apple must Fermentation (Temp. = 22±1 C) Siphoning Stock apple wine Sweetening agent apple juice (1:1 ratio) (TSS 7 B) Gelatin @ 0.165% Tannin @ 0.009% solution at 40 o C Sedimentation and filtration Apple cider Ascorbic acid solution spraying (1%) Apple Pomace Pectinol enzyme @ 0.5% Aroma 0.02-0.06 %, adjustment of TSS (10 B) and acidity (0.40%) Caramel colour etc. if needed Bottling Pasteurization 62.5 o C for 20 minutes Fig. 2.5 Flow diagram to manufacture apple cider (Joshi, 1997) 44
2.6.1 MICROBIOLOGY Greenwalt et al. (2000) have reported that the tea fungus is a symbiosis of acetic acid bacteria ( Acetobacter xylinum, Acetobacter aceti, Acetobacter pasteurianus, Gluconobacter oxydans) and yeast ( Saccharomyces sp., Zygosaccharomyces sp., Torulopsis sp., Pichia sp., Brettanomyces sp. The yeasts have been found to ferment sugar in the cultivation medium to ethanol, which is further oxidised by the acetic acid bacteria to produce acetic acid resulting in reduced ph of the medium. Besides acetic acid, the fermented liquid contains gluconic, glucuronic and lactic acids. Glucuronic acid is the main therapeutic agent in Kombucha, as a detoxification agent (Loncar et al., 2000). A culture of Kombucha is a living organism exposed to many influences, which gives the final beverage a different chemical composition and taste (Petrovska and Tozi, 2000). A compact list of bacteria and yeasts associated with fermentation of Kombucha is presented in table 2.8. Table 2.8 Microflora associated with Kombucha Microorganism Bacteria References Acetobacter xylinum Kozaki, 1972; Sievers et al., 1995; Blanc, 1996; Greenwalt et al., 2000; Mrdanovic et al., 2007 Acetobacter aceti Liu et al., 1996; Greenwalt et al., 2000; Mrdanovic et al., 2007 Acetobacter ketogenum Morales and Sanchez, 2003 Acetobacter pasteurianus Liu et al., 1996; Greenwalt et al., 2000, Bacterium gluconicum Morales and Sanchez, 2003; Mrdanovic et al., 2007 Bacterium katogenum Mrdanovic et al., 2007 Bacterium xylinum Morales and Sanchez, 2003; Mrdanovic et al., 2007 Bacterium xylinoides Morales and Sanchez, 2003; Mrdanovic et al., 2007 Gluconobacter oxydans Liu et al., 1996; Greenwalt et al., 2000; Mrdanovic et al., 2007 Yeast Brettanomyces sp. Kozaki, 1972; Mayser et al., 1995 45
Brettanomyces bruxellensis Liu et al., 1996; Mrdanovic et al., 2007 Brettanomyces intermedius Greenwalt et al., 2000, Candida Jankovic and Stojanovic, 1994 Candida guilliermondii Kozaki, 1972; Greenwalt et al., 2000, Candida famata Greenwalt et al., 2000, Candida stellata Mycoderma Jankovic and Stojanovic, 1994 Mycotorula Jankovic and Stojanovic, 1994 Pichia Jankovic and Stojanovic, 1994 Pichia fermentans Pichia membranaefaciens Kozaki, 1972; Greenwalt et al., 2000 Saccharomyces sp. Kozaki, 1972, Saccharomyces cerevisiae subsp. aceti Greenwalt et al., 2000 Saccharomyces cerevisiae subsp. cerevisiae Saccharomycodes ludwigii Liu et al., 1996; Greenwalt et al., 2000 Schizosaccharomyces Jankovic and Stojanovic, 1994 Schizosaccharomyces pombe Torula Jankovic and Stojanovic, 1994 Torulaspora delbrueckii Greenwalt et al., 2000 Torulopsis famata Kozaki, 1972, Zygosaccharomyces sp. Sievers et al., 1995 Zygosaccharomyces bailii Liu et al., 1996; Greenwalt et al., 2000 Zygosaccharomyces rouzii Greenwalt et al., 2000 Zygosaccharomyces rouxii Blanc, 1996 2.6.2 PREPARATION OF KOMBUCHA Raw material Black tea is usually used for Kombucha preparation, green tea and herbs are also used. It has been shown that green tea has a more stimulating effect on the Kombucha fermentation than black tea, fermenting it in a short time frame as 46
reported by Greenwalt et al. (1998). Black tea and white sugar have been found to be best substrates for the preparation of Kombucha, although green tea can also be used (Reiss, 1994). Radomir et al. (2006) conducted research on influence of black tea concentrate on Kombucha fermentation and reported that it was possible to perform Kombucha fermentation in substrates with higher black tea concentration than is the traditional one, but metabolites content in fermentative liquids was not proportional to the amount of used tea and sucrose. Malbasa et al. (2008a) conducted experiment on comparison of Kombucha fermentation on sucrose and molasses as sugar sources and compared the characteristics of the main products of black tea fermentation by Kombucha on pure sucrose and three kinds of molasses. It was reported that the molasses from sugar beet processing could be used as a low-cost carbon source in Kombucha fermentation of black tea. The products obtained on these substrates were rich in lactic acid, which might be considered as an advantage compared to the product on sucrose. 2.6.3 Must preparation Greenwalt et al. (2000) reported that tea leaves were added to boiling water and allowed to infuse for about 10 min after which the leaves are removed and sweetened with sucrose 50 to 150g/ml (5 to 15%). This must was allowed to cool at room temperature. 2.6.4 Inoculation and fermentation Infused tea was poured into a wide-mouthed clean vessel and the microbial mat or colony from previous batch of Kombucha was added to the sweetened tea with about 100 ml of Kombucha from previous fermentation. Markov et al. (2006) reported that isolated strains of yeasts and acetic acid bacteria from tea fungus might be used as a starter culture for Kombucha preparation. They further revealed that, the fermentation was faster in medium inoculated with fermentation broth compared to the fermentation with the starter cultures. The fermentation time was dependent on initial count of yeasts cells. 47
The tea fungus was laid on the tea surface, and the jar was carefully covered with a clean cloth and fastened properly. The preparation was allowed to incubate at room temperature (between 20 0 and 30 0 C) for 7-10 days. If the fermentation was allowed to continue beyond the 10 days, the acidity might rise to levels potentially harmful to consume. During fermentation, a daughter tea fungus was formed at the surface of fermentation medium. The tea fungus was removed from the surface and kept in a small volume of fermented tea. The beverage was then passed through cheese-cloth and stored in capped bottles at 4 0 C. The taste of the Kombucha changes during fermentation from a pleasant fruit sour-like lightly sparkling flavour after a few days, to a mild vinegar-like taste with prolonged incubation (B lanc, 1996; Reiss, 1994; Sievers al., 1995). The Schematic description of Kombucha manufacture is also presented in Figure 2.6. Figure 2.6 Schematic description of Kombucha manufacture Fermentation of 1.5 g/l of Indian black tea, sweetened with adequate quantities of molasses (containing approx. 70 g/l, 50 g/l and 35 g/l of sucrose), was conducted using domestic Kombucha inoculation (Malbasa et al., 2008b). They reported that, inoculation was performed with 10% of fermentation broth 48
from a previous process. They further reported that a product with 70 g/l sucrose from molasses corresponds to an optimal concentration of carbon source, which provided metabolites with high ph, a low content of less desired acetic acid, a high content of highly desired L-lactic acid, an acceptable content of total acids with the highest possible level of utilization of sucrose. 2.6.5 Biochemical changes The tea fungus has been known to produces a cellulosic pellicle or mat, oxidized ethanol, acetic, L(+) lactic acid, gluconic acid and glucuronic acid (Frank, 1991). Fermentative and oxidative processes start, when the tea fungus was placed in a freshly prepared infusion of tea and sugar. When grown in sucrose medium, yeast degraded sucrose in glucose and fructose, than producing carbon dioxide and ethanol, which were further oxidized to acetaldehyde by bacteria. The tea fungus produced many other substances, like gluconic acid and vitamins, which with the supply of tea nutrients, give the drink its unusual flavour and healing properties. It has been reported that, during the process the glucose was polymerized and produces cellulose and hemicelluloses (Greenwalt et al., 1998; Bauer and Petrushevska, 2000). 2.6.6 Components of Kombucha Kombucha is reportedly contains multiple species of yeast and bacteria which produce organic acids, active enzymes, amino acids, and polyphenols. Finished Kombucha might contain acetic acid (mildly antibacterial), Butyric acid, B-vitamins ( Aleksandra et al., 2007), alcohol, gluconic acid, lactic acid, malic acid, oxalic acid and usnic acid. Normally, Kombucha contained less than 0.5% alcohol, which classified Kombucha as a non-alcoholic beverage. Older, more acidic, Kombucha might contain 1.0% or 1.5% alcohol, depending on more anaerobic brewing time and higher proportions of sugar and yeast. 2.6.7 Nutritive and therapeutic value Tea cider ( Kombucha) is associated with many health benefits. It is popular in China, Korea and Japan due to detoxifying and energizing properties as well as curing digestive problems. It contained liver detoxifiers, antioxidants, polyphenols, probiotics and free-form amino acids. As a traditional medicine the 49
Kombucha drink was used as healing liquor in the treatment of many diseases, and at present it is considered to be a folk-remedy as reported by Petrovska and Tozi (2000). Hence, it is used as an alternative therapy (Blanc, 1996). Beneficial effects attributed to consumption of Kombucha mushroom tea have included prevention of a few cancers, relief of arthritis, treatment of insomnia, hemorrhoids, digestive disorders, heart diseases, allergies, asthma, decrease of blood pressure, increase of vitality, increase of T cell count and stimulation of regrowth of hair. It is believed to stimulate the immune system thus, it is popular among elderly persons as reported by Sreeramulu et al. (2000); Cavusoglu and Guler, (2010). Kombucha is a sour, slighty sparkling beverage prepared by fermentation of sweetened black tea with tea fungus. The recommended consumption ranges from 100 to 300 ml per day as documented by Frank (1991). The beverage has been claimed to be a prophylactic agent and is beneficial to human health as a diuretic in edemas, arterosclerosis, gout, sluggish bowels and for stones, etc. Fermentation also induces also biosynthesis of ascorbic acid important natural antioxidant, which serves as human health protector and a drug. Due to the rich biomass in tea fungus ( Medusomyces gisevii), it could be utilized as protein supplement in animal feed (Jayabalan et al., 2010). They further revealed that tea fungus is rich in crude protein, crude fibre, and amino acid lysine. The biochemical characteristics of tea fungus studied were increased throughout the fermentation time during the study of biochemical characteristics of tea fungus produced during Kombucha fermentation. The product has the bacterial β-glucuronidase enzyme that could interfere with proper disposal of a chemotherapeutic agent, and that antibiotics against gut bacteria can prevent toxicity of some chemotherapy drugs as reported by Srinivasan et al. (1997), supporting the idea that glucaric acid is an active component of Kombucha. However, Kombucha consumption has proven to be harmful for individuals with preexisting conditions of illness or if incorrectly prepared (Greenwalt et al., 2000). Some results by researchers revealed that Kombucha 50
can become contaminated with potentially harmful microorganisms, such as mould which may make it harmful for human consumption (Mayser et al., 1995, Cavusoglu and Guler, 2010). Contamination might potentially produce serious adverse effects, and consumption of this may cause several problems such as nausea, jaundice, shortness of breath, throat tightness vomiting, akathasia, headache, xerostomia, dizziness, liver inflammation, chronic liver disease and neck pain (Peron et al., 1995, Jayabalan et al., 2007, Cavusoglu and Guler, 2010). 2.6.8 Antimicrobial activity of Kombucha Application of natural antibacterial agents has been increasingly noticed as a novel trend in biological preservation of foods in recent years (Schillinger et al., 1996). Antimicrobial activities of microbial fermented tea are much less known than its health beneficial properties. These antimicrobial activities are generated in natural microbial fermentation process with tea leaves as substrates. The antimicrobial components produced during the fermentation process have shown inhibitory effects against several food-borne and pathogenic bacteria as reported by Sreeramulu et al. (2001). The acidity and mild alcoholic element of Kombucha resists contamination by most airborne molds or bacterial spores. Kombucha is a home-brewing product which means the preparation conditions are not sterile. Majority of the tests for Kombucha indicated that a low rate of contamination from spoilage and pathogenic microorganisms, suggesting that Kombucha has antimicrobial properties to pathogenic and other bad microorganisms (Mayser et al. 1995). Some studies reported that antimicrobial activity of Kombucha against a range of bacteria, made with a low tea usage level (4.4 g/l), was attributable to the acetic-acid content (Steinkraus et al. 1996, Greenwalt et al. 1998). While Sreeramulu et al. (2001) revealed that the antimicrobial components of Kombucha are compounds other than organic acids, ethanol, proteins or tannins in tea or their derivates after systematic investigation. Rodrigo et al. (2009) conducted research on antimicrobial activity of broth fermented with Kombucha colonies. They reported that the fermented growth was efficient against Microsporum canis (LM-828), Escherichia coli (CCT-0355) and Salmonella typhi (CCT-1511). Guttapadu et al. (2000) 51
investigated antimicrobial activity of Kombucha against a number of pathogenic microorganisms. Staphylococcus aureus, Shigella sonnei, Escherichia coli, Aeromonas hydrophila, Yersinia enterolitica, Pseudomonas aeruginosa, Enterobacter cloacae, Staphylococcus epidermis, Campylobacter jejuni, Salmonella enteritidis, Salmonella typhimurium, Bacillus cereus, Helicobacter pylori, and Listeria monocytogenes were found to be sensitive to Kombucha. Acetic acid is considered to be responsible for the inhibitory effect toward a number of microbes tested. However, Kombucha proved to exert antimicrobial activities against E. coli, Sh. sonnei, Sal. typhimurium, Sal. enteritidis, and Cm. jejuni, even at neutral ph and after thermal denaturation. They also suggests the presence of antimicrobial compounds other than acetic acid and large proteins in Kombucha. Greenwalt et al. (1998) conducted research to determine and characterization of antimicrobial activity of the fermented tea Kombucha. They reported that the fermented samples containing 33g/l total acid (7g/l acetic acid) was significant against the tested gram positive and gram negative pathogenic organisms (Agrobacterium tumefaciens, Bacillus cereus, Salmonella cholerasuis serotype typhimurium, Staphylococcus aureus and Escherichia coli). Candida albicans was not inhibited by Kombucha. Tea, at drinkable levels, demonstrated no antimicrobial properties, even at the highest levels tested; 70 g/l (7%) dry tea. The antimicrobial activity of Kombucha was attributed to its acetic acid content. 2.6.9 Antioxidant activity Antioxidants predominantly include certain secondary metabolites, enzymes and high/low molecular weight proteins which act against the free radicals. Plant phenolics act as a source of natural antioxidants and they have multifaceted functions such as reducing agents, metal chelators and quenchers of oxygen singlet (Heim et.al., 2002) Tea leaves contain 10-30% of polyphenols (earlier known as thea tannins) including catechins, flavonols, phenolic acids, glycosides and plant pigments. Out of three parts of total polyphenols, two parts account to catechins and its relative distribution of green tea catechins varied significantly. Among the catechin fraction EGCG makes up 40% of the total 52
catechin. It had been widely accepted as a major antioxidant ingredient in green tea and its extracts (Shalini and Sudha, 2010). They further reported that black tea samples possessed higher antioxidant potential than that of green tea. Oral administration of Kombucha to rats exposed to pro-oxidation species also indicated the potent antioxidant properties of the fermented drink such as decrease of the degree of lipid oxidation and DNA fragmentation (Dipti et al., 2003). Many claimed beneficial effects of Kombucha such as alleviation of inflammation and arthritis, cancer prevention and immunity enhancement might be associated to its antioxidant activities (Allen, 1998). 2.7 COMPOSITION OF FRUIT WINE Fruit wine have been reported to contain sugars, acids, ethyl alcohol, higher alcohols or fusel oils, tannins, aldehydes, esters, amino acids, minerals, vitamins, anthocyanin, fatty acids, minor constituents like methanol and a number of flavouring compounds etc. (Amerine et al., 1980). Physico-chemical characteristics of some wines is summerised in table 2.9. Table 2.9 Physico-chemical characteristics of different fruit wines Characteristics Range Plum wine a Peach wine b Apple wine c Wild apricot wine d Total soluble solids 8.0-12.0 7.6-9.1 4.6-7.5 6.8 ( B) Titratable acidity(%) 0.62-0.68 0.61-0.80 0.37-0.41 0.75 Volatile acidity (% 0.028-0.040 0.020-0.029 0.021-0.105 0.08 A.A) Ethanol(% v/v) 8.5-11.0 10.6-11.6 10.50-12.8 10.65 Total esters 104-109 90.9-101.5 76-80 --- Total phenols (mg/l) - 206-278 124.50 240 Reference: a Joshi and Bhutani, 1990; Vyas and Joshi, 1982; b Joshi et al. 1999; c Yang and Wiegand, 1949; Joshi, 1997; d Joshi et al.,1990a 2.7.1 Acids Titratable acidity ranged between 0.5-1.0 per cent in different fruit wines (Table 2.9). Acids are reported almost as important to wines as alcohols (Wildenradt and Caputi, 1977). The acidity of fruit wine is dependent upon a 53
number of factors like type of fruit, method of preparation and type of yeast used. It has been found that acids not only produce a refreshing taste, modify the perception of other taste and mouth feel sensation but also stablize the colour of red wine (Jackson, 2004). Acetic acid and lactic acid were produced in a small amount, whereas succinic acid has been thought to be more common by-product during yeast cell fermentation. 2.7.2. Alcohols 2.7.2.1 Ethanol It is the major component on which the type of wine can be characterized. Table wine has been reported to contain 11 to 14 per cent alcohol but may have as low as 7 per cent ( Joshi, 1997). Ethyl alcohol content of different alcoholic beverages is shown in Table 2.10. The ethanol content in wine has been reported to be influenced by method of wine preparation, type of yeast used, initial TSS etc (Joshi and Bhutani, 1990; Joshi and Sharma, 1993; Joshi, 1997). Ethanol acts as an important solvent in the extraction of pigments, tannins and also has multiple effects on taste and mouth feel. Ethanol has been reported to plays an important role in the aging of wine (Amerine et al, 1980). Along with other alcohols, ethanol slowly reacts with organic acids to produce esters (Zoecklein et al., 1995). Ethanol concentration also found to influences the stability of esters. Table 2.10 Ethyl alcohol content of different alcoholic beverages Beverages Ethyl alcohol content (% v/v) Wines 12.2 Table wines 11-14 Dry red wines 12.6 Sweet white wines 19.3 Sweet red wines 19.3 Sparkling wines 13.2 Champagne 11.5-13.0 Fortified wines > 15 Dry white wines 12.4 Distilled beverages 37-42 or more Source: Amerine, 1953; Amerine et al., 1980; Soni et al., 2011 54
2.7.2.2 Methanol Methanol is neither a major constituent, in wine and has been reported to ranged between 0.1-0.2 g/lt nor is found important in flavour development. Methanol in wine is result of enzymatic break down of pectins ( Gnekow and Ough, 1976). 2.7.2.3 Higher alcohols Alcohols with more than two carbon atoms are called as higher or fusel alcohols. Quantitatively, the most important higher alcohols are 1-propanol, 2- methyl-1-propanol (isobutyl alcohol), 2 -methyl-1-butanol (isoamyl alcohol) and 2-phenylethanol (phenethyl alco hol). The formation of higher alcohols is considered to be an important criterion on which the acceptability of wine depends (Amerine et al., 1980). The formation of higher alcohols during fermentation has been closely related with the type of yeast, cultivar of fruits and conditions during fermentation as reported by Amerine et al. (1980); Houtman et al. ( 1980); Ciolfi et al. (1985). Lower content of higher alcohols in wines has been found to be desirable as they contribute to the flavour development (Gayon, 1978; Amerine et al., 1980; Fowles, 1989; Joshi, 1997). Higher alcohols in wines have been formed due to amino acid biosynthesis from carbohydrates or directly from existing amino acids by deamination and decarboxylation (Amerine et al., 1980). Guymon et al. (1961) and Ribereau-Guymon et al. ( 2001) showed that oxidative conditions during fermentation favour production of more quantity of higher alcohols. The presence of pomace, as in red wine production aerates the wine, leading to the formation of greater amount of higher alcohols. The amount of higher alcohols in table wines ranged from about 140 to 240 mg/l and in dessert wines from about 160 to 900 mg/l ( Amerine et al., 1980). Rankie (1967) reported that grape cultivar and climatic variations influenced the fusel oil (higher alcohols) content irrespective of yeast strain, must ph and processing conditions of wine. 2.7.3 Total phenolics Phenols affect the appearance, taste, mouth feel, fragrance and antimicrobial properties of wine (Joshi, 1997; Ribereau-Guymon et al., 2001). 55
Types of wine, yeast, fermentation conditions, containers and the maturation period influenced the total phenols (Amerine et al., 1980; Almela et al., 1991). Amount of tannin in wine varied between 100 to 200 mg/l depending upon the type of wine, yeast fermentation conditions, containers and maturation period (Amerine et al., 1980; Almela et al., 1991). Flavonoids constitute more than 85% of the phenol content ( 1000 mg/l). Tannins strongly react with protein (Yokotsuka and Singleton, 1987) and resulted in dryness and puckering (Singleton, 1992; Serafini et al., 1997). 2.7.4 Total esters Esters in wine have been formed as a result of esterification of alcohols with the respective acids (Amerine et al., 1980). The total esters of various wines reportedly vary between 200 to 400 mg/l as ethyl acetate (Amerine et al., 1980; Joshi, 1997). Over 160 specified esters have been identified and grouped into straight chain or cyclic compounds. Most of esters are reported to be produced by yeasts after cell division has ceased. Subsequently, synthesized and hydrolysed non-enzymetically based on the chemical composition and storage condition of wine (Rapp and Guntert, 1986). Ester formation during fermentation has been influenced by many factors, such as low temperature, high temperature, SO 2 level and absence of oxygen during yeast fermentation. In sound wine ethyl acetate is reported to vary between 50-100mg/l, low level (< 50mg/l), add complexity to the fragrance whereas above 150mg/l, it was reported to produce sour vinegar off-flavour in wine (Amerine and Roessler, 1983). Esters in general, have fruity and floral impact characteristics that are important in sensory (Zoecklein et al., 1995). properties of wine 2.8 BIOCHEMICAL CHANGES DURING MATURATION WITH WOOD CHIPS 2.8.1 Wood chips/barrels Newly fermented wine used to be dull, yeasty and raw in taste. So, aging is necessary to develop good appearance, mouthfeel and flavor. Usage of wood chips for aging belongs to one of the traditional winemaking practices, because of its positive effect on organoleptic and chemical quality of wine. Oak wood is the 56
most frequently used wood for improvement of wine aroma. The role of wood in wine aging is to transfer volatile aromatic compounds and astringency-related phenolics to wine, to improve the intensity and complexity of wine flavour and aroma. Additionally, wine aging in wood barrels leads to gentle oxidation of certain compounds resulting in reduction of astringency and bitterness, colour stabilization, and the disappearance of excessive vegetative-herbaceous aromas (Navojska et al., 2012). Wood of various species of white oak, red wood, Acacia, pine, chestnut and eucalyptus have been frequently used to make barrels (Singleton and Asau, 1969). The woods of Quercus, Albizia, Bombax, Toona, Celtice, and Salix chips have been used successfully in maturation of wines and significant changes in tannins, methanol and sensory quality have been observed (Joshi et al., 1994). 2.8.2 Wood chips Aging wines in wood barrels requires long periods of time and has been found to be very costly. Oak wood chips however have greater and faster effect than oak berrels or other methods of maturation (Gutierrez, 2003). Oak wood chips are small pieces of oak wood which can be obtained from wood scrap wastes produced during barrel manufacturing, and are prepared using traditional methods in cooperage and subjecting them to boiling in water and toasting as documented by Bozalongo et al. (2007). Navojska et al. (2012) reported that chips could be added to the wine fermented in stainless steel tanks, to obtain wines like those fermented in barrels, but with better manipulation conditions (better temperature control, also able for larger amounts, better control of hygiene). Toasting of wood causes, that large polymers lignin or cellulose present in wood are decomposed due to a high temperature forming compounds as aldehydes, phenols, furfural derivatives, lactones, and other as reported by Navojska et al. (2012). In recent years, the use of oak chips as a wood alternative has been proposed ( Wilker and Gallander, 1998; Alamo et al., 2004). Frangipane et al. (2007) observed that geographical origins of wood chips used for maturation of wine also influenced the quality of wine, whereas, Gutierrez (2003) found that 57
the quantity of oak wood chips had a greater effect than the type of oak used for maturation. Characteristics of different types of wood samples are summarized in Table 2.11. Table 2.11 Characteristics of different types of wood samples Wood (species) Humidity (%) Ash (%) ph Surface area (m 2 /g) Lignin content (%) Holm (Quercus 5.3 1.3 5.2 <1 22.6 rotundifolia) Oak (Quercus rubra) 5.9 0.4 4.0 <1 18.2 Beech (Fagus sylvatica) 7.0 0.4 4.9 <1 22.2 Walnut (Juglans nigra) 6.8 0.5 5.2 <1 22.3 Elm (Ulmus minor) 6.5 0.9 6.4 <1 26.9 Pine (Pinus sylvestris) 6.4 0.2 5.0 <1 24.4 Poplar (Populus sp) 6.3 0.2 4.9 <1 22.1 Reference: Rodriguez et al., 2007 2.8.3 Treatment The wine aged in contact with wood oak chips undergoes a quicker aging, their loss of anthocyanins was also faster and suffered a higher number of poymerisation than the wine aged in barrels. Chips with a diameter of 3-5mm favour the extraction process and 5-6 h heat treatment allows an adequate decay of lignin, with the subsequent formation of aromatic aldehydes. Arapitsas et al. (2004) pointed out the influence of chip size on the extraction kinetic. Toasting level had the strongest influence on the volatile composition of chip samples, phenyl ketones, volatile phenols, and some furanic compounds were the most influenced whereas the influence of wood origin was found to be weaker (Nadia et al., 2006). Arapitsas et al. (2004) also studied the effect of the contact time and the size of the chips on red wines. Frangipane et al. (2007) studied four types of chips from four different French forests, added to a red wine stored in 2 year old barrels. Campbell et al. (2005) studied the origin of the wood and the type of heating in model wines also had influence on the quality of wine. 2.8.4 Factors The quantitative and qualitative evolution of the processes related to wood aging have been determined by several factors such as (i) oak origin and species, 58
(ii) length and type of wood seasoning, (iii) degree of stave charring, and (iv) technological parameters (cellar temperature and humidity, contact time between beverage and wood, and age of the barrel) (Mosedale and Ford, 1996; Doussot et al., 2002; Chatonnet, 1999). Compared with the traditional barrel aging, similar aromatic results in shorter contact time were reported (Wilker and Gallander. 1998) when French oak chips were used. Similarly other factors that determine the final characteristics of wines were observed when macerated with chips. Several scientific publications have appeared after studying the effect of wood chips on the phenolic composition of different wines (Del et al., 2004a; Del et al., 2004b; Del and Nevares, 2006; Coninck et al., 2006), whereas others have focused on volatile compounds, mainly on those extracted from wood. Guchu et al. (2006) evaluated the influence of the geographical origin of the oak (American or Hungarian), the toasting degree (toasted and nontoasted), and the time of contact on volatile compounds in a white wine. 2.8.5 Effect on sensory quality Joshi and Shah (1998) observed a remarkable increase in sensory quality of peach wine when aged with wood chips. Non-flavionoid phenols content in presence of oak chips shows a remarkable increase and also for sensory properties of red wine (Coninck et al., 2006). Sensory properties similar to those of wines aged in barrels could be attained through the use of oak chips (Rodriguez-Bencomo et al. 2008), whereas, Ramirez (2001) studied the positive effect on aroma compound sorption by oak wood in a model wine. 2.9 MICROBIOLOGICAL AND SENSORY QUALITIES OF WINES 2.9.1 Microbiological qualities of wines The wine could be spoiled by microorganisms. There are three stages which could contribute to the spoilage of wine by microorganisms. These stages are (1) contamination of raw material with molds, yeasts, acetic acid bacteria or lactic acid bacteria; (2) During fermentation, the wild yeast or microorganisms from the winery equipment may spoil the wine; (3) During storage, when various microorganisms can grow and spoil the wine. The role of film yeasts, which are 59
developed in wine stored in barrels as a result of aerobic growth of Saccharomyces cerevisiae, Pichia, Hansenula and Brettanomyces species has been discussed in detail. Some of the factors that are known to influence the susceptibility of wine to microbial spoilage are summarized as acidity, sugar content, alcohol content, accessory growth elements, tannin concentration, storage temperature, air availability (Joshi et al., 1999). According to Amerine et al. (1980), by taking all the precautions, the microbiological qualities of the wine could effectively be maintained. 2.9.2 Sensory qualities of wines Appearance, colour, aroma, taste and subtle taste factors such as flavour of wine constitute the quality (Amerine et al., 1980). Gayon (1978) observed that aroma and taste of wines was very complex and depended on a number of factors such as cultivars, agricultural land, vinification practices, fermentation and maturation. Sensory qualities particularly flavour sensation by palate is limited to sweetness, sourness, bitterness and astringency together with such taste as metallic and pungency in wine (Piggot et al., 1990). There are certain flavour and quality differences due to holding of grapes under anaerobic conditions (Amerine and Doughlas, 1974). Phenolic compounds are very important for improving the sensory qualities like astringency, bitterness and colour which increased as a linear function of concentration as tannic acid in red wine (Robichaud and Noble, 1991). Sensory evaluation indicated that a wine from highly aerated culture had a lower score, possibly due to products of oxidative metabolism than the wine obtained by addition of ammonium nitrogen (Tzvetanov et al., 1982). Smell is often considered a peculiar sensory modality, as the peripheral olfactory system has a low specificity for substrate. A single receptor recognizes multiple odorants, and a single odorant is recognized by multiple receptors (Malnic et al., 1999). An appraisal of the review of literature showed that virtually there is no information on preparation of tea cider, concentration and types of tea, types of fermentation (inoculated or n atural fermentation), different sugar and nitrogen sources and their respective concentrations, types of microorganisms and 60
consortia,. Similarly, there is information of maturation of fruit wine using wood chips but nothing about tea wine is available in the literature. There is a plenty of literature on type of phenolics, proteins, amino acids etc. attributed to the wine by incorporation of tea leaves. Information about fermentability and sensory quality of the product are also lacking. Hence, the present study was conducted to fill these gaps. 61
Chapter-3 MATERIALS AND METHODS This chapter covers the detailed method and techniques used for the preparation and evaluation of tea cider. The studies were carried out in the Department of Food Science and Technology, Dr Y.S. Parmar University of Horticulture and Forestry, Nauni-Solan during the year 2010-2013. The materials used, experimental methods and analytical techniques employed have been described under the following heads: 3.1 MATERIALS 3.2 EXPERIMENTAL 3.3 ANALYSES 3.1 MATERIALS 3.1.1 Procurement of fruit and different types of tea Apple fruits (Golden variety) were procured from the local market of Solan, whereas, Orthodox tea (Dhauladhar, Natural Organic Orthodox Kangra Tea) was procured from HPKV, Palampur; Herbal Tea (Himalayan Brew, Kangra Special Herbal Tea) was procured from local market of Palampur and CTC tea (Tajmahal) was procured from local market of Solan (Plate 1). 3.1.2 Preparation of apple juice Juice was extracted from apple fruits. The fruits were grated and then juice was extracted by using hydraulic press followed by hot filling, bottling and pasteurization. 3.1.3 Yeast culture The yeast culture viz. Saccharomyces cerevisiae var. ellipsoideus, (UCD 595) used in the study was obtained from Indian Institute of Horticulture Research, Bangalore. It was maintained on yeast malt extract agar (YMEA) medium and recultured after every three months or whenever needed from the stock yeast culture.
3.1.4 Fermentable sugar, apple juice concentrate and honey Sucrose, the common sugar was procured from the local market, apple juice concentrate was procured from HPMC sales outlets Jabli and honey was procured from the Department of Entomology of the University for the preparation of apple tea wine. 3.1.5 Enzyme and chemicals The pectin esterase enzyme used in the studies was manufactured by M/S Triton Chemicals, Mysore, India under the brand name Pectinol. Different nitrogen sources (DAHP, ammonium sulphate and peptone) and chemicals used during the entire study were procured from M/S Loba Chemicals, Solan (HP). 3.1.6 Wood chips Woods of different trees viz. Quercus spp., Bombax spp. and Acacia spp. were collected from the Forest area of University field for the different treatments of apple tea wine. Chips were made of 5 2 cm (l b) and 0.5 cm thickness (Plate 2) and were oven dried at 65ºC, till the constant weight was achieved. 3.2 EXPERIMENTAL Experiment 3.2.1: Standardization of quantity of tea leaves, fermentation behaviour and to determine type of microflora associated with natural fermentation of tea cider 3.2.1.1 Extract of tea leaves and its characterization In this experiment, the study was conducted with the aim of characterization of different tea and their concentrations. For conducting the experiment, different quantities/concentrations (2, 3, 4 and 5 g) of different tea (CTC, orthodox and herbal tea) were used. The infusion/extract of these tea leaves was made with apple juice by boiling for 3 minutes at 100 oc. The resulting infusions were sieve filtered and transferred to sterilized glass bottles (200 ml capacity) and used for further analysis and characterization. The flowsheet of the process is given in figure 3.1 and the complete detail of the experiment is shown in table 3.1. 63
Plate: 1 Different types of tea
Plate: 2 Different types of wood chips (Acacia spp., Quercus spp. and Bombax spp.)
Table 3.1 Different types of tea leaf extracts Treatments Detail T1 Orthodox tea (2 g tea/100ml apple juice) T2 Orthodox tea (3 g tea/100ml apple juice) T3 Orthodox tea (4 g tea/100ml apple juice) T4 Orthodox tea (5 g tea/100ml apple juice) T5 Herbal tea (2 g tea/100ml apple juice) T6 Herbal tea (3 g tea/100ml apple juice) T7 Herbal tea (4 g tea/100ml apple juice) T8 Herbal tea (5 g tea/100ml apple juice) T9 CTC tea (2 g tea/100ml apple juice) T10 CTC tea (3 g tea/100ml apple juice) T11 CTC tea (4 g tea/100ml apple juice) T12 CTC tea (5 g tea/100ml apple juice) Concentrations of tea = 4 (2, 3, 4, 5g tea/100ml apple juice) Types of tea = 3 (Orthodox tea, Herbal tea and CTC tea) Number of treatments = 4X3=12 Number of replications = 3 Statistical design = Completely randomized design (CRD) factorial Orthodox tea or Herbal tea or CTC tea (2, 3, 4, 5g tea/100ml (2, 3, 4, 5g tea/100ml apple (2, 3, 4, 5g tea/100ml apple juice) juice) apple juice) Boiling for 3 minutes at 100 oc Sieving Tea extract Bottling (200 ml capacity) Cooling to 25 oc Tea extract Figure 3.1 Preparation of tea leaf extracts with apple juice 64
3.2.1.2 Fermentation of tea leaf extracts In this experiment, the study was conducted with the aim of standardization of quantity of tea leaves, fermentation behaviour and determination of type of microflora associated with natural fermentation of apple tea wine. A. Fermentation of tea leaf extracts with wine yeast (Saccharomyces cerevisiae var. ellipsoideus) The fermentation was carried out with wine yeast (Saccharomyces cerevisiae var. ellipsoideus) with the aim of standardization of quantity of tea leaves. Preparation of yeast cultures Culture of Saccharomyces cerevisiae var. ellipsoideus, (UCD 595) was made for the preparation of wine. Apple juice was poured into the slant of yeast culture and rolled in-between the hand so that yeast cell got mixed with juice but not medium and then it is transferred back to the flask containing 50ml juice. After 24 hrs, it was inoculated to the 100 ml sterilized juice and kept for 24 hrs at room temperature under aseptic conditions. After 24 hrs, the activated culture was transferred to 500ml and finally to 2 lt, which was used for the inoculation of respective musts. Preparation of must For conducting the experiment, tea leaf extracts with apple juice as prepared in earlier experiment as per the treatments (Experiment 3.2.1.1 and Figure 3.1) were used as fermentation medium. To these extracts diammonium hydrogen phosphate (DAHP) as nitrogen source and 0.5% pectinase enzyme for clarification were added. The TSS was raised with sugar to 20 B and sulphur dioxide (100 ppm) was added to kill the wild microorganisms. After 2 hours, the respective must were inoculated with 5% of activated culture of Saccharomyces cerevisiae var. ellipsoideus. Each treatment study was carried out in 2.5 lt capacity narrow mouth dark glass bottles, filled up to 75% of their capacity. Fermentation Fermentation for all the treatments was carried over at room temperature (2022 oc). When a stable TSS was reached the fermentation was considered complete. Air locks were fitted in the mouth of glass bottles near the end of fermentation. 65
Siphoning/racking When fermentation was complete, siphoning/racking was done after 15 days and then after one month. Bottling Apple tea wines were further filled in 200ml bottled capacity glass bottles and used for further analysis and characterization (Plate 3). The entire procedure is given in Figure 3.2. Orthodox tea or Herbal tea or CTC tea (2, 3, 4, 5g tea/100ml (2, 3, 4, 5g tea/100ml apple (2, 3, 4, 5g tea/100ml apple juice) juice) apple juice) Boiling for 3 minutes at 100 oc Sugar syrup to raise Brix to 20 B Sieving Yeast slant Sterilized apple juice Shifted to sterilized 500 ml apple juice SO2 (100 ppm) Diammonium hydrogen phosphate @ Tea extract Pectin esterase enzyme @ 0.5% Tea extract must Saccharomyces cerevisiae var. ellipsoideus @ 5% (v/v) Fermentation Siphoning/racking (2-3 times) Filtration and bottling (in 200 ml bottles) Storage Figure 3.2 Fermentation of tea leaf extracts with wine yeast (Saccharomyces cerevisiae var. ellipsoideus) B. Natural fermentation of tea leaf extracts In this experiment, natural fermentation was carried out with the aim of standardization of fermentation behaviour and determination of type of microflora 66
associated with natural fermentation of tea cider. Must for this was prepared as discussed earlier. Natural fermentation Natural fermentation for all the treatments was carried over at room temperature. When a stable TSS was reached the fermentation was considered complete. Air locks were fitted in the mouth of glass bottles near the end of fermentation. The apple tea wine so prepared was siphoned/racked and bottled (Plate 4) and used for further analysis and characterization. 3.2.1.3 Isolation, characterization and identification of the microorganism during natural fermentation A. Isolation of microorganism During natural fermentation of tea extract must, after third day of fermentation; isolation of microorganisms was made by standard pour plate technique (Harrigan and McCance, 1966). Stock samples were taken from the must and serial dilution was made with sterilized water in the range of 10-2 to 10-6. The samples (0.1 ml each) from each dilution were inoculated by spread plate method using the solidified selective media (Nutrient Agar) to isolate microbial strain. Inoculated petriplates were incubated for 24 48 hrs at 32oC. Typical microbial colonies were isolated and these were streaked on the same medium to obtain pure microbial culture. B. Tentative identification of the microbial isolates The isolated bacterial strains from different sources were differentiated on the basis of their morphological, cultural and physiological characteristics. Gram staining was carried out with all the isolates and each isolate was subcultured periodically. These were cultured after 30 or 60 days on the agar slants depending on the microorganism. Tentative identification was done from Bergey s manual of Systematic Bacteriology (Buchanan and Gibbons, 1975; Baird-Parker, 1975) and each bacterial isolate was tentatively identified upto genus level under various groups of bacteria on the basis of biochemical and morphological characteristics of every isolate. 67
Plate: 3 Apple tea wine prepared from different concentrations and types of tea fermented with Saccharomyces cerevisiae var. ellipsoideus
Plate: 4 Apple tea wine prepared from different concentrations and types of tea fermented by natural fermentation
C. Morphological and staining characteristics All the cultures were gram stained (Harrigan and McCance, 1966) and were observed under oil-immersion. Their photomicrographs were taken for identification purpose. D. Biochemical characteristics The following biochemical and physiological characteristics of the isolates were studied: i) Catalase test The cultures streaked over dried nutrient agar contained in the petriplates were incubated at 37 oc for 24 hrs to obtain the isolated colonies. Capillary tubes of 1 mm diameter and 67 mm length were placed in 50 ml beaker containing 10 ml of 3 per cent H2O2. A bacterial colony was touched by the capillary tube and the effervescence in the column of H2O2 in tube was observed and accordingly, the colonies were designated as catalase positive or negative (Daniel and Dianae, 1973). ii) Utilization of citrate as a sole source of carbon Simmon s citrate agar slants, containing 0.002 per cent bromothymol blue solution, were inoculated by streaking and incubated at 37oC for 24+2 hrs. The change of green colour to bright blue was inferred as a positive test. There was no change of colour in the control or if the test was negative (Harrigan and McCance, 1966). iii) Starch utilization test On the appropriately centre of starch agar plates single streak inoculation of test microorganisms was made and were incubated for 48 hours at 37 C in an inverted position. After 48 hours, the surfaces of the plates were flooded with iodine solution with a dropper for 30 seconds and excess iodine solution was poured off. The plated were examined for the starch hydrolysis around the line of growth of each organism, i.e. the colour change of the medium (Harrigan and McCance, 1966). 68
iv) Cellulose utilization test On the Czapek-mineral salt agar medium plates inoculation of the test microorganisms was made and were incubated at 35 C in an inverted position for 2-5 days. After 2-5 days, the surfaces of the plates were flooded with 1% aqueous solution of hexadecyltrimethyl ammonium bromide solution. The plated were examined for the formation of a zone around the growth of microorganisms (Harrigan and McCance, 1966). v) Caesin utilization test On the Skim milk agar medium plates inoculation of the test microorganisms as a single line streak was made and were incubated at 37 C in an inverted position for 24-48 hours. After 24-48 hours, the plated were examined for the formation of a zone around the growth of microorganisms (Harrigan and McCance, 1966). vi) Gelatin utilization test On the gelatin-agar medium plates inoculation of the test microorganisms as a single line streak was made and were incubated at 37 C in an inverted position for 4-7 days. After 4-7 days, the surfaces of the plates were flooded with mercuric chloride solution and allowed to stand for 5-10 minutes. The plates were examined for the formation of a clear zone around the growth of microorganisms (Harrigan and McCance, 1966). vii) H2S production test Stab inoculation of the respective test microorganism was done in the SIM agar medium test tubes. The test tubes were incubated at 35-36 C for 48 hours. After 48 hours, the test tubes were examined for the presence or absence of black colouration along the line of stab inoculation (Harrigan and McCance, 1966). viii) Urease utilization test The test was performed as per the detail provided elsewhere (Harrigan and McCance, 1966). On the urea agar medium plates inoculation of the test microorganisms as streak was made and were incubated at 37 C in an inverted position for 24-48 hours. After 24-48 hours, the surfaces of the plates were examined 69
for the colour for the presence of urease utilization (red or cerise colour) and for no urease utilization (yellow colour). ix) Carbohydrate metabolism To the peptone water, 1.0 per cent of the relevant carbohydrate (Table 3.1), Durham s tube and 1.0 per cent solution of Andrade s indicator was added and was inoculated as for broth culture and incubated at 37oC for 24 and 72 hours. The development of pink colour and or gas in Durham s tube constituted a positive reaction (Harrigan and McCance, 1966). Table 3.2. Carbohydrates used and their symbols Sr. No. Name Symbol 1. Maltose Ma 2. Mannitol Mn 3. Dextrose Dx 4. Sucrose Su 5. Glucose Gl 6. Lactose La 7. Fructose F 3.2.2 Preliminary experiment prior to conducting the RSM to standardize the types of sugar sources, nitrogen sources and inocula The experiment was laid out to conduct the preliminary screening of the types of sugar source (sucrose, honey and apple juice concentrate), nitrogen source (DAHP, ammonium sulphate and peptone) and microflora (Saccharomyces cerevisiae var. ellipsoideus; consortia 1 and consortia 2). For all treatments must was prepared by boiling 4 g CTC tea (best concentration of tea from earlier experiments) with apple juice. SO2 (100 ppm) and pectin esterase enzyme (0.5%) were added in must of every treatments. Apple tea wine was prepared as discussed earlier (Plate 5). The main aim of this experiment was to standardize the best sugar source, nitrogen source and microflora. The complete detail of the treatments is given in table 3.3. 70
Table 3.3: Detail of treatments used for conducting the preliminary experiment to standardize of type of sugar source, nitrogen sources and microflora Treatments Treatment Detail T1 Sucrose (20 ob) + DAHP () + Saccharomyces cerevisiae var. ellipsoideus (5% inoculum) T2 Sucrose (20 ob) + DAHP () + Consortia 1 (5% inoculum) T3 Sucrose (20 ob) + DAHP () + Consortia 2 (5% inoculum) T4 Sucrose (20 ob) + peptone () + Saccharomyces cerevisiae var. ellipsoideus (5% inoculum) T5 T6 T7 T8 T9 T10 T11 T12 T13 T14 T15 T16 T17 T18 T19 T20 T21 T22 Sucrose (20 ob) + peptone () + Consortia 1 (5% inoculum) Sucrose (20 ob) + peptone () +Consortia 2 (5% inoculum) Sucrose (20 ob) + ammonium sulphate () + Saccharomyces cerevisiae var. ellipsoideus (5% inoculum) Sucrose (20 ob) + ammonium sulphate () + Consortia 1 (5% inoculum) Sucrose (20 ob) + ammonium sulphate () + Consortia 2 (5% inoculum) Honey (20 ob) + DAHP () + Saccharomyces cerevisiae var. ellipsoideus (5% inoculum) Honey (20 ob) + DAHP () + Consortia 1 (5% inoculum) Honey (20 ob) + DAHP () + Consortia 2 (5% inoculum) Honey (20 ob) + peptone () + Saccharomyces cerevisiae var. ellipsoideus (5% inoculum) Honey (20 ob) + peptone () + Consortia 1 (5% inoculum) Honey (20 ob) + peptone () + Consortia 2 (5% inoculum) Honey (20 ob) + ammonium sulphate () + Saccharomyces cerevisiae var. ellipsoideus (5% inoculum) Honey (20 ob) + ammonium sulphate () + Consortia 1 (5% inoculum) Honey (20 ob) + ammonium sulphate () + Consortia 2 (5% inoculum) Apple juice concentrate (20 ob) + DAHP () + Saccharomyces cerevisiae var. ellipsoideus (5% inoculum) Apple juice concentrate (20 ob) + DAHP () + Consortia 1 (5% inoculum) Apple juice concentrate (20 ob) + DAHP () + Consortia 2 (5% inoculum) Apple juice concentrate (20 ob) + peptone () + Saccharomyces cerevisiae var. ellipsoideus (5% inoculum) 71
T23 T24 T25 T26 T27 Apple juice concentrate (20 ob) + peptone () + Consortia 1 (5% inoculum) Apple juice concentrate (20 ob) + peptone () + Consortia 2 (5% inoculum) Apple juice concentrate (20 ob) + ammonium sulphate () + Saccharomyces cerevisiae var. ellipsoideus (5% inoculum) Apple juice concentrate (20 ob) + ammonium sulphate () + Consortia 1 (5% inoculum) Apple juice concentrate (20 ob) + ammonium sulphate () + Consortia 2 (5% inoculum) Concentration of tea = Best treatment from 1st experiment (CTC 4g) Sugar Source = 3 (Honey, Sucrose, Apple juice concentrate) @ 20 0B each Nitrogen Sources = 3 (DAHP, ammonium sulphate, peptone) @ 0.1 % each Sulphur dioxide concentration = 100 ppm Pectin esterase enzyme = 0.5% Microorganisms = 3 (each) (a.) Saccharomyces cerevisiae var. ellipsoideus (b.) Consortia 1 (Saccharomyces cerevisiae var. ellipsoideus and C3, C41 bacterial isolates*) (c.) Consortia 2 (O31 and H31 yeasts isolates* and C3, C41 bacterial isolates*) *O31, H31 (yeasts) and C3, C41 (bacteria) were isolated from the natural fermentation of apple tea must Inoculum size = 5.0% Number of treatments = 3X3X3= 27 Number of replications = 3 Statistical design = Completely randomized design (CRD) factorial 72
3.2.3 Response surface methodology Standardization of tea concentration, initial TSS, DAHP and sulphur dioxide concentration and inoculum size was done by applying central composite design (CCD) of RSM for preparation of apple tea wine. I. Experimental design The levels of five independent variables i.e. tea concentration (A), initial TSS concentration with apple concentrate of 72 ob as sugar source (B), DAHP as nitrogen source (C), sulphur dioxide (D) and inoculum size (E), chosen for this study were standardized by RSM. The central composite design (CCD) with five factors at five levels was employed to investigate the first and higher-order main effects of each factor and interactions among them. The design involved 8 centre points with an alpha value being ± 2. The five coded levels of alpha, studied in the present study were -2, -1, 0, +1 and +2. The minimum and the maximum ranges of the variables with the coded and actual values are given in Table 3.4.The full experimental plan as per the design is given in Table 3.5. Apple tea wine was prepared as per the process discussed in the earlier experiments (see section 3.2.1) by using minimum and maximum range of variables. The statistical software package Design Expert version 7.0 (Stat Ease, Inc, Minneapolis, USA) was used to generate polynomials and the contour plots. All the experiments were carried out in triplicates. For a fivefactor system, the model equation generated was: Y = β0 + β1a + β2b + β3c + β4d + β5e + β11a² + β22b² + β33c² + β44d² + β55e 2 + β12ab + β13ac + β14ad + β15ae+ β23bc + β24bd + β25be + β34cd +β35ce Where y was response variable, β0 was intercept, β1, β2, β3, β4 and β5 were linear coefficients, β11, β22, β33, β44 and β55 were squared coefficients, β12, β13, β14, β15, β23, β24, β25, β34 and β35 were interaction coefficients and A, B, C, D, E, A², B², C², D², E2, AB, AC, AD, AE, BC, BD, BE, CD and CE were the levels of independent variables. 73
Plate: 5 Apple tea wine prepared from different types of sugar sources (sucrose @ 20 ob, honey 20 @ ob and apple juice concentrate @ 20 ob), nitrogen sources ( DAHP, peptone and ammonium sulphate) and inocula (Saccharomyces cerevisiae var. ellipsoideus @ 5 %, consortia 1 @ 5 % and consortia 2 @ 5 %)
Table 3.4 Range of values for the RSM Independent Variables -2-1 0 +1 +2 CTC tea (g) 2.0 3.0 4.0 5.0 6.0 TSS (ob Apple juice concentrate) 16.0 18.0 20.0 22.0 24.0 DAHP (%) 0.05 0.10 0.20 0.30 0.40 Sulphur dioxide (ppm) 0.00 50 100 150 200 Inoculum Size (%) 0.00 2.50 5.00 7.50 10.00 Table 3.5 Experimental plan as per the design Apple juice Run CTC tea concentrate as (g) sugar source (ob) DAHP as Sulphur nitrogen Dioxide source (%) (ppm) Inoculum size (%) 1 4.00 15.00 0.20 100.00 5.00 2 5.00 18.00 0.10 150.00 7.50 3 1.00 20.00 0.20 100.00 5.00 4 3.00 22.00 0.10 150.00 2.50 5 3.00 18.00 0.30 150.00 7.50 6 5.00 22.00 0.30 150.00 2.50 7 6.00 20.00 0.20 100.00 5.00 8 3.00 22.00 0.30 50.00 2.50 9 3.00 18.00 0.10 50.00 2.50 10 3.00 22.00 0.10 50.00 7.50 11 4.00 24.00 0.20 100.00 5.00 12 4.00 20.00 0.20 100.00 5.00 13 4.00 20.00 0.20 100.00 5.00 14 3.00 22.00 0.10 50.00 2.50 15 3.00 22.00 0.30 150.00 2.50 16 4.00 20.00 0.20 100.00 5.00 17 3.00 18.00 0.30 150.00 2.50 74
18 5.00 22.00 0.10 50.00 2.50 19 4.00 20.00 0.20 100.00 5.00 20 4.00 20.00 0.20 00 5.00 21 5.00 22.00 0.10 50.00 7.50 22 5.00 18.00 0.30 50.00 7.50 23 3.00 22.00 0.30 150.00 7.50 24 5.00 18.00 0.10 150.00 2.50 25 3.00 18.00 0.10 150.00 2.50 26 4.00 20.00 0.20 100.00 10.00 27 3.00 18.00 0.10 50.00 7.50 28 4.00 20.00 0.20 100.00 5.00 29 5.00 22.00 0.30 150.00 7.50 30 5.00 22.00 0.10 150.00 7.50 31 4.00 20.00 0.20 100.00 5.00 32 4.00 20.00 0.20 100.00 00 33 3.00 18.00 0.10 150.00 7.50 34 5.00 22.00 0.10 150.00 2.50 35 3.00 18.00 0.30 50.00 2.50 36 4.00 20.00 0.40 100.00 5.00 37 4.00 20.00 0.00 100.00 5.00 38 5.00 22.00 0.30 50.00 2.50 39 4.00 20.00 0.20 100.00 5.00 40 3.00 22.00 0.30 50.00 7.50 41 4.00 20.00 0.20 100.00 5.00 42 5.00 18.00 0.10 50.00 7.50 43 3.00 22.00 0.10 150.00 7.50 44 5.00 18.00 0.30 50.00 2.50 45 5.00 18.00 0.10 50.00 2.50 46 5.00 18.00 0.30 150.00 7.50 47 4.00 20.00 0.20 218.00 5.00 48 5.00 18.00 0.30 150.00 2.50 49 5.00 22.00 0.30 50.00 7.50 50 3.00 18.00 0.30 50.00 7.50 75
II. Analysis of variance (ANOVA) A second-order polynomial equation was established based on analysis of variance and the optimum ratio of the medium components was found using the Design-Expert 7.1 software optimization toolbox. Standard deviation, PRESS, r² values were also determined. III. Model validation The mathematical model generated during RSM implementation was validated by conducting check point studies. The experimentally obtained data were compared with the predicted one and the prediction error was calculated. Experiment 3.2.4 Experiment 3.2.4.1 Preparation and evaluation of apple tea wine using optimized conditions from response surface methodology experiment In this experiment, the fermentation was carried out by using the standard technology as optimize during the 3.4 and 3.5 experiments as described earlier. Preparation of yeast cultures Yeast cultures were prepared as described earlier in experiment 3.2.1 Preparation of must, fermentation, siphoning/racking and bottling For conducting the experiment, tea extract with apple juice (4 g CTC tea/100 ml apple juice) was extracted and used as fermentation medium. To these extract diamonium hydrogen phosphate (DAHP) as nitrogen source and 0.5% pectinase enzyme for clarification were added. The TSS was raised with apple juice concenrate to 20 B and sulphur dioxide (100 ppm) was added to kill the wild microflora. After 2 hours, the must were inoculated with 5% of activated starter culture of Saccharomyces cerevisiae var. ellipsoideus. The fermentation was carried out at room temperature in 10 l capacity narrow mouth dark carboy, filled up to 75% of their capacity. When a stable TSS was reached, the fermentation was considered completed. Air locks were fitted in the mouth of carboy near the end of fermentation. The apple tea wine so prepared was siphoned/racked and bottled. Optimized method for preparation of apple tea wine is shown in figure 3.3 and plate 6. 76
Apple juice CTC tea @ 4 g tea/100ml apple juice Boiling for 3 minutes at 100 oc Apple juice concentrate as a sugar source to raise Brix to 20 B Sieving Yeast slant Sterilized apple juice Shifted to sterilized 500 ml apple juice SO2 (100 ppm) Tea extract Diammonium hydrogen phosphate @ 0.2% Pectin esterase enzyme @ 0.5% Tea extract must Saccharomyces cerevisiae var. ellipsoideus @ 5% Fermentation Siphoning/racking (2-3 times) Wood chips (Quercus spp., Bombax spp., Acacia spp.) @ 2.5 g/l of apple tea wine Maturation of apple tea wine with different wood chips Filtration Bottling Pasteurization Labeling Figure 3.3 Optimized method for preparation of apple tea wine Experiment 3.2.4.2 Maturation The experiment was laid out to determine, the effect of wood chips on the apple tea wine after the fermentation was over. Apple tea wine as prepared after siphoning was filled in carboys and respective wood chips (2.5 g/l; Joshi and Shah, 1998) were added in each carboy. Maturation was carried out for 6 months. The apple tea wines were analyzed for different physico-chemical, antimicrobial and sensory characteristics during maturation period of six months. The detailed treatments used are shown in Table 3.6. 77
Plate: 6 Optimized method for preparation of apple tea wine
Table 3.6 Different types of wood chips used for the treatment of apple tea wine Treatments Apple tea wine with different wood chips T1 (ATWQ) Quercus spp. (2.5 g/l of apple tea wine) T2 (ATWB) Bombax spp. (2.5 g/l of apple tea wine) T3 (ATWA) Acacia spp. (2.5 g/l of apple tea wine) T4 (ATWC) Control (2.5 g/l of apple tea wine) Maturation periods (in months) = 0, 3, 6 Number of treatments = 4 X 3 = 12 Number of replications = 3 Statistical design = Completely randomized design (CRD) factorial. Experiment 3.2.5 Preparation and evaluation of tea cider by blending apple juice with 6 month matured apple tea wine This experiment was conducted with the objective of preparation and evaluation of cider. The apple tea wine was blended with different proportions of apple juice at the rate of 30, 40 and 50 per cent (Table 3.7). The cider so prepared was clarified using 0.5 % Pectin esterase enzyme, bottled, pasteurized at a temperature of 62 C for 15-20 minutes (Joshi, 1997) and analysed for various physico-chemical, antimicrobial and sensory quality characteristics (Plate 7). Table 3.7 Different treatment combinations for preparation of tea cider Treatments Treatments combinations T1 (TCQ30) Apple tea wine matured with Quercus (wood chips) + 30 % apple juice T2 (TCQ40) Apple tea wine matured with Quercus (wood chips) + 40 % apple juice T3 (TCQ50) Apple tea wine matured with Quercus (wood chips) + 50 % apple juice T4 (TCB30) Apple tea wine matured with Bombax (wood chips) + 30 % apple juice T5 TCB40) Apple tea wine matured with Bombax (wood chips) + 40 % apple juice T6 (TCB50) Apple tea wine matured with Bombax (wood chips) + 50 % apple juice T7 (TCA30) Apple tea wine matured with Acacia (wood chips) + 30 % apple juice T8 (TCA40) Apple tea wine matured with Acacia (wood chips) + 40 % apple juice T9 (TCA50) Apple tea wine matured with Acacia (wood chips) + 50 % apple juice T10 (TCC30) Control Apple tea wine matured without wood chips + 30 % apple juice T11 (TCC40) Control Apple tea wine matured without wood chips + 40 % apple juice T12 (TCC50) Control Apple tea wine matured without wood chips + 50 % apple juice Apple tea wine matured with different wood chips = 4 Different proportions of apple juice = 3 Number of treatments= 4 X 3=12 Number of replications= 3 Statistical design = Completely randomized design (CRD) factorial. 78
3.3 ANALYSES 3.3.1 Analyses of apple juice, apple tea wine and tea cider Apple juice was analyzed for various physico-chemical characteristics viz. TSS, titratable acidity, reducing, total sugars, ph and type of phenols. The apple tea extract was analysed for various physicochemical characteristics viz., caffeine content, total phenols, types of phenols, flavanols, protein content, colour. The must prepared with different sugar sources such as sucrose, apple juice concentrate and honey were analysed for various physico-chemical characteristics viz., TSS, reducing sugars, total sugars, titratable acidity, ph and total phenols. Apple tea wine or tea cider prepared during study was analysed for various physicochemical and sensory characteristics viz. total soluble solids (TSS), rate of fermentation, ethanol, titrable acidity, volatile acidity, higher alcohols, colour, ph, sugars, total phenols, types of phenols, total esters, caffeine content, total amino acids, antimicrobial activity and numerical scoring. During the natural fermentation, the characterization of the microbial isolates and their biochemical identification was also done. During the storage study of apple tea wine, the analyses were performed during and after 6 months of maturation. 3.3.2 Physical parameters Rate of Fermentation (RF) The decrease in TSS during fermentation was noted after every 48 hrs in all the apple tea wine fermentation. The RF values were calculated as: RF = Initial TSS Final TSS Time The trend was also shown graphically Colour Colour of apple tea wine and tea cider was measured with UV-Vis Spectrophotometer at 440 nm in terms of optical density as per the standard procedure described (Ranganna, 1986). 79
Tea cider having apple tea wine matured with Acacia spp. (wood chips) and different concentrations of apple juice Tea cider having apple tea wine matured with Quercus spp. (wood chips) and different concentrations of apple juice Tea cider having apple tea wine matured with Bombax spp. (wood chips) and different concentrations of apple juice Tea cider having control apple tea wine matured without wood chips and different concentrations of apple juice Plate: 7 Tea ciders having apple tea wine matured with different wood chips and different concentrations of apple juice
3.3.3 Chemical characteristics Total soluble solids Total soluble solids (TSS) were measured using an Erma hand refractometer (0 to 32oB) and the results were expressed as degree Brix (ob). The readings were corrected by incorporating the appropriate correction factor for temperature variation (A.O.A.C., 1980). Titratable acidity Titratable acidity was estimated by titrating a known aliquot of the sample against N/10 NaOH solution using phenolphthalein as an indicator. The total titratable acidity was calculated and expressed as per cent malic acid (A.O.A.C., 1980). V x N x 68 x 100 % Titratable acidity (malic acid) = v x 1000 Where V N v = = = Volume of NaOH used for titration Normality of NaOH solution Volume for sample taken for titration ph ph was taken with ELTOP-3030 ph meter. Prior to ph measurement, the instrument was calibrated with the buffer solutions of ph 4 and 7. The ph of the samples was estimated directly. Sugars The total and reducing sugars of fruit, apple tea wine and tea cider were estimated by Lane and Eynon volumetric method (A.O.A.C., 1980) by titrating the sample against Fehlings solutions. A known volume of sample was neutralized with NaOH and to it a known quantity of lead acetate (45%) was added and kept for 10 min. Excess of lead acetate was removed from the sample by using sufficient quantity of potassium oxalate (22%) in a 250 ml volumetric flask. After diluting it upto the mark, the solution was filtered and clear filtrate was taken to estimate 80
reducing sugars by titrating against a known quantity of Fehling s A and Fehling s B solution using metylene blue as an indicator. Total sugars were estimated by adding 5g citric acid to 50 ml clarified sample solution and heating it for 10 minutes for complete inversion of sugars, neutralizing with NaOH and making the volume 250ml in a volumetric flask. Total sugars were estimated as done for reducing sugars. Factor Dilution 100 Reducing sugars (%) = Titre value Weight of sample or volume of sample Factor Dilution 1 Dilution 2 100 % Total sugar as invert sugar = Titre value Volume of Sample (1) Volume of sample (2) % Sucrose = (% total invert sugar % reducing sugar) 0.95 % Total sugar = (% reducing sugar + % Sucrose) Volatile acidity Volatile acidity of apple tea wine was determined by the standard method (Amerine et al., 1980). The distillate was titrated with 0.025 N NaOH and the volatile acidity was expressed as acetic acid (g/100 ml). Acetic acid (g/ 100 ml) = V x N x 60 1000 (v) x 100 Where V N v = = = Volume of NaOH used for titration Normality of NaOH solution Sample volume (ml) Ethanol Ethanol content was determined by spectrophotometric method (Caputi et.al. 1968). One ml of sample and 29 ml of water was taken in distillation flask. Volumetric flask of 50 ml containing 25ml of potassium dichromate beneath the condenser was placed and tightly plugged with cotton. Distillation was carried out and 20ml distillate was collected in receiving end. The content of the flask was 81
heated at 60ºC in a water bath for 20 min and brought up to volume with distilled water. After mixing and cooling, the absorbance was taken at 600 nm in a calorimeter. Ethanol standards were prepared by making ethanol water solutions containing 0, 2, 6, 8% ethanol by volume. Total phenols The total phenols content in apple tea wines and tea ciders were determined by Folin Ciocalteu procedure given by Singleton and Rossi (1965) in which the absorbance was measured at 765 nm in a colourimeter against water blank. A standard calibration curve of gallic acid using its different concentrations was prepared. Total phenols contents were expressed as (mg/100 ml). Stock solution was prepared by dissolving 0.5 g of dry gallic acid in water to make the final volume 100 ml in a volumetric flask. Aliquot 0, 1, 2, 3, 5 and 10 ml gallic acid were taken in separate flasks and then, total volume was raised to 100 ml with distilled water. Pipette 1ml of each from these in separate 100 ml flask. Water (60 ml) and Folin Ciocalteu (5ml) reagent were added to the respective, flasks and mixed well. Then, 15 ml (20g/100ml) sodium carbonate solution was added. The contents were mixed properly and final volume was made to 100 ml with distilled water. After 2 hr, absorbance was recorded at 765nm and a standard curve was prepared and concentration of total phenols in the given sample was calculated. Type of phenols Phenolic compounds were evaluated by reversed phase - high performance liquid chromatography (RP-HPLC) with direct injection without any particular treatment except filtration. Detection and quantification was carried out with a SCL10Avp System controller, a SIL 10AD vp Autosampler, a LC-10AD vp pump, a DGU-14a degasser, a CTO-10 A vp column heater and a diode array detector with wavelengths set at 278 nm. The 250 x 4.6 mm i.d., 5μm column used was filled with Luna Prodigy. The flow rate was 1 ml min-1, injection volume was 10 μl and the column temperature was set at 30 C. Gradient elution of two solvents was used: Solvent A consisted of: acetic acid - water (2:98 v/v), solvent B: methanol and the gradient programme used is given Table 3.8. The data were integrated and analyzed using the Water s Chromatography Laboratory Automated Software system. The tea extract, apple juice and apple tea wine samples, standard solutions and mobile phases 82
were filtered by a 0.45 μm pour size membrane filter. The amount of phenolic compounds in the extracts was calculated as μg/l wine using external calibration curves, which were obtained for each phenolic standard (Ozkan and Baydar, 2006). Standards such as gallic acid, catechin, epicatechin and quercetin were purchased from Sigma-Aldrich (Steinheim, Germany). Stock solutions of all the standards were prepared in methanol and chromatographic peaks of the different standards are shown in the figure 3.4. Table 3.8 Solvent gradient conditions with linear gradient Final Time (Initial) 3 18 20 30 40 50 55 65 Figure 3.4 A% 100 95 80 80 75 70 60 50 0 B% 0 5 20 20 25 30 40 50 100 Chromatographic peaks of the different standards and samples Caffeine content Standard solutions Caffeine stock solution of 1000 ppm was prepared by accurately weighing 100.00 mg of pure caffeine and quantitatively transferring it into 100 ml volumetric flask and making it to the mark with the mobile phase. Working standards of 10, 20, 83
40, 60, 80 ppm were prepared by serial dilution of the stock solution with the mobile phase and chromatographic peaks of these different concentrations of standard are shown in the figure 3.5. The standard curve is shown in the Annexure-III. Figure 3.5 Chromatographic peaks of different concentrations of caffeine Sample preparation and analyte determination The tea extract, apple tea wine, tea cider samples, standard solutions and mobile phases were filtered by a 0.45-μm pour size membrane filter. The standards and the samples were run in the HPLC system (Plate 8). The following were the HPLC conditions: Column, Reverse phase ODS, 250 4.6 mm, flow rate, 1 ml/min, detector, photodiode array set at 278 nm, pressure, 150 khf/cm2, mobile phase, water, acetic acid, methanol (79.9, 0.1 and 20) and sample volume, 10 μl. A calibration curve of peak areas versus concentration of the standards was plotted. The caffeine level of the various samples was calculated using the regression equation of the best line of fit (Wanyika et al., 2010). 84
Total amino acid Total amino acids were estimated by the standard procedure as described by Sadasivam and Manickam (1991). One ml of sample was taken into the test tube and 1.9 ml of Ninhydrin (made in citrate buffer) was added, 1.2 ml of glycerol and 0.2 ml of 0.5M citrate buffer were also added. Mixed thoroughly and heated on water bath for 12 minutes and then the test tubes were cooled. Light violet colour was obtained and optical density of sample was measured at 570 nm with a UV-viz-spectrophotometer. The concentration was determined as per the standard procedure from the standard curve. The standard curve was prepared using different concentrations of glycine using the above procedure. The results were expressed as mg per 100 ml on volume/volume basis and calculated as given below: Total Amino acid (%) = O D of unknown sample Aliquot of sample used x x Amino acid value from standard curve Weight of sample taken x Total x 100 volume of (µg) extract x 1000 x 1000 Total proteins Protein in different wine samples was determined by Lowry s method as described by Sadasivam and Manickam (1991). A known volume of aliquot i.e. apple tea wine/tea cider (0.1 ml) was taken in separate test tubes and volume was made up to 1 ml with distilled water. Then 5 ml of alkaline copper solution was added to each test tube and incubated at room temperature for 10 min. After that 0.5 ml of Folin-Ciocalteu reagent was added to each test tube and again incubated at room temperature in dark for 30 min. Optical density of the sample was measured at 660 nm with a UV-viz-spectro-photometer. The concentration was determined as per the standard procedure from the standard curve which was prepared using different concentrations of bovine serum albumin (BSA; 8-32 µg/ml) using the same procedure. The results were expressed as mg per 100 ml on volume/volume basis and calculated as given below: Protein (%) = O D of unknown sample Aliquot i.e. wine used x x Protein value from standard curve (µg) Weight of sample taken 85 x x Total x 100 volume of extract 1000 x 1000
Plate: 8 Estimation of caffeine being carried out with HPLC
Sulphur dioxide Free SO2 in apple tea wines was measured by Ripper s method as described by Amerine et al. (1980). It was a volumetric method based on direct titration of SO2 in wine after hydrolysis by a strong alkali solution. The results were calculated as total SO2 (mg/l) as given below: Sulphur dioxide (mg/ l) = V x N x 32 x 1000 v x 100 Where V N v = = = Volume of iodine solution used for titration Normality of iodine solution Volume of sample taken Antioxidant activity Antioxidant activity (Free radical scavenging activity) was measured as per the method of Brand-Williams et al. (1995). DPPH (2, 2-diphenyl-1-picrylhydrazyl) was used as a source of free radical. A quantity of 3.9 ml of 6x10-5 mol/l DPPH in methanol was put into a cuvette with 0.1 ml of sample extract and the decrease in absorbance was measured at 515 nm for 30 min or until the absorbance become steady. Methanol was used as a blank. The remaining DPPH concentration was calculated using the following equation: Ab(B) Ab(S) Antioxidant activity (%) = 100 Ab (B) Where, Ab (B) = Absorbance of blank Ab (S) = Absorbance of sample Total Esters Total esters were determined as per the method of liberaty (1961). A standard calibration curve of ethyl acetate using its different concentrations of 2.5, 5, 7.5 and 10ml in 100ml flask was prepared. Final volume was brought to 100ml by using distilled water. Pipette 3ml of each in separate test tubes. Two ml 2M hydroxylamine 86
hydrochloric acid was mixed and allowed to stand for 10 min, then 2ml 4N hydrochloric acid and 2ml ferric chloride was added, mixed and absorbance was recorded at 510 nm and a standard curve was made. The total esters present in apple tea wines were estimated from standard curve after proceeding similarly as for the standard curve preparation. The absorbance of both standards and samples were taken at 510 nm in a colourimeter against a blank. Higher alcohols Higher alcohols in apple tea wine were estimated by the method given by Guymon and Nakagiri (1952). A standard calibration curve of fusel oil standard using its different concentrations was prepared. The quantity of fusel oil contents present in the samples was estimated from the standard curve. The optical density of the samples as well as standards was taken at 530 nm against a blank i.e. concentrated sulfuric acid. The results were expressed as fusel oil mg/l. Antimicrobial activity Antimicrobial activity of apple juice, apple tea wine and tea cider against all the test microorganisms i.e. E. coli, E. faecalis, Listeria monocytogenes, S. aureus and B. subtilis was detected by Well diffusion method (Schillinger and Luke, 1989) under aerobic conditions. a) Test organism A loopful culture of all the test microorganisms i.e. Escherichia coli (IGMC), Enterococcus faecalis (MTCC 2729), Listeria monocytogenes (MTCC 839), Staphylococcus aureus (MRSA 252) and Bacillus cereus (CRI) was innoculated into 100 ml of nutrient broth in 250 ml Erlenmeyer flask. All the cultures were then incubated at 37oC till the time they reached 1.0 O.D. b) Screening of antimicrobial activity with well diffusion assay In Well Diffusion Method (Schillinger and Luke, 1989), the test microorganisms were first grown in nutrient broth for 24-36 hrs at 370C. Wells of 6 mm diameter were cut into prepoured, sterlized nutrient agar petriplates with a sharp and sterile borer. Lawn of respective test microorganism on these petriplates was prepared by pouring 0.1 ml of inoculum and swabbing it properly with the help of 87
sterilized cotton buds in such a way that test microorganism should cover whole of the nutrient agar plate. Lawn of every test organism to be tested against the apple tea wine or tea cider was prepared in the same way. 0.5 ml of apple tea wine/tea cider was placed into each well. Plates were then incubated at 37oC for 24 hrs and results obtained were in the form of zone of inhibition. The diameter of zone formed by apple tea wine/tea cider against the respective test microorganism was measured. In this way, all the samples of apple tea wine/tea cider were tested against each test microorganisms. 3.3.3 Sensory analysis The sensory analysis of different apple tea wines/tea cider was conducted by semi- trained panel of judges by using composite scoring and hedonic rating test. In composite scoring, coded samples were given to 10 judges. They were asked to rinse their mouth before or in between testing the given sample. Each sample was evaluated for overall acceptability on hedonic scale or composite scores using various quality attributes viz. colour and appearance, aroma and bouquet, volatile acidity, total acidity, sweetness, body, flavour, bitterness, astringency and overall impression (Amerine et al., 1980) on a prescribed proforma (Annexure-II). For sensory evaluation, the apple tea wines/tea ciders were served chilled. To draw the spider web diagram, sensory scores were taken for each attributes out of a total score of 10. Nine point Hedonic scale method as given by Amerine et al. (1965) was followed for conducting the sensory evaluation of Apple tea wines (Annexure-III). The panel of 10 judges comprising of semi- trained panel of judges was selected with care to evaluate the different apple tea wines for sensory parameters such as colour, taste, aroma, bitterness and overall acceptability. The samples were presented to judges and plain water was given to them to rinse their mouth in between the evaluation of samples. No discussion during evaluation was allowed. 3.3.4 Statistical analysis Analysis of variance Statistical analysis of the quantitative data of chemical parameters obtained from the experiments was done by Completely Randomized Design (CRD) Factorial. 88
The statistical analysis of the data obtained from sensory evaluation of the apple tea wine and tea cider was done by Randomized Block Design (RBD) as given by Cochran and Cox (1963). Cluster analysis To get an overview, the data of physico-chemical characteristics of the various apple tea wines and tea cider samples were analysed by the use of computer programme SPSS 16.0. The programme took into account the given factors and the parameters and grouped the treatments on cluster based on the extent of similarity and dissimilarity among the treatments. 89
Chapter-4 EXPERIMENTAL RESULTS The present investigations entitled, Preparation and Evaluation of Tea Cider were conducted in the Department of Food Science and Technology, Dr. YS Parmar University of Horticulture and Forestry, Nauni-Solan (HP). The results obtained are discussed in this chapter under the following heads: 4.1 Chemical, antioxidant and antimicrobial characteristics of fresh apple juice 4.2 Antimicrobial activity of different concentrations of tea, ethyl alcohol, citric acid and caffeine 4.3 Physico-chemical analysis of tea leaves extracted in apple juice 4.4 Fermentation behaviour, physico-chemical characteristics, antimicrobial activity, microbial characterization and sensory evaluation of apple tea wine fermented with Saccharomyces cerevisiae var ellipsoideus and natural fermentation 4.5 Effect of various factors on fermentation behavior, physico-chemical characteristics and sensory quality characteristics of apple tea wine 4.6 Effect of different wood chips on the physico-chemical and sensory quality characteristics of apple tea wine during maturation 4.7 Effect of blending of different concentrations of apple juice with matured apple tea wine on the physico-chemical and sensory quality characteristics of tea cider 4.1 CHEMICAL, ANTIOXIDANT AND ANTIMICROBIAL CHARACTERISTICS OF FRESH APPLE JUICE Physico-chemical characteristics of fresh apple juice (Table 4.1) showed that juice is a good source of TSS (10.40±0.12 B), reducing and total sugars (6.25±0.14% and 8.33±0.19%, respectively) and medium acid (0.31±0.01% as malic acid) content. ph value of the juice was recorded to be 4.12±0.02. Total phenols and quercetin content were recorded to be 213±11.56 mg/l and 20.58±0.58 ppm respectively. Antioxidant activity of apple juice was found to be
76.21±0.79 %. It also showed antimicrobial activity against different test microorganisms including microorganisms of pathogenic significance i.e. Staphylococcus aureus (nil), Listeria monocytogenes (nil), Escherichia coli (6.5 mm), Enterococcus faecalis (6.5 mm) and Bacillus cereus (4 mm). Table 4.1 Chemical, antioxidant and antimicrobial characteristics of fresh apple juice Physico-chemical characteristics Mean ± SEM (n=3) TSS ( B) 10.40 ± 0.12 Titratable acidity (% malic acid) 0.31 ± 0.01 ph 4.12 ± 0.02 Reducing sugar (%) 6.25 ± 0.14 Total sugar (%) 8.33 ± 0.19 Phenol (mg/l) 213 ± 11.56 Quercetin (ppm) 20.58 ± 0.58 Antioxidant activity (%) 76.21 ± 0.79 Antimicrobial activity Staphylococcus aureus (mm) 0 Listeria monocytogenes (mm) 0 Escherichia coli (mm) 6.5 Enterococcus faecalis (mm) 6.5 Bacillus cereus (mm) 4.0 SEM: Standard error mean 4.2 ANTIMICROBIAL ACTIVITY OF DIFFERENT CONCENTRATIONS OF TEA, ETHYL ALCOHOL, CITRIC ACID AND CAFFEINE Table 4.2 summarizes the antimicrobial activity of different concentration of tea (CTC), alcohol, citric acid and caffeine (3000 ppm) against the different test microorganisms (Plate 9). With increase in tea concentration (2-5%), a slight increase in antimicrobial activity against all the test microorganisms was observed except Listeria monocytogenes where it was nil. Against the different 91
Table 4.2 Comparison of antimicrobial activity (inhibition zone in mm) of different concentrations of tea, ethyl alcohol, citric acid and caffeine Different concentration of tea Different concentration of Different concentration of citric Caffeine solution (CTC) extract with water Alcohol with water acid with water with water Test microorganisms 2% 3% 4% 5% 5% 10% 15% 20% 0.25% 0.50% 0.75% 1.00% 3000 ppm Staphylococcus aureus 7.0 8.0 8.5 9.0 0 0 0 0 7.0 8.0 9.0 10.0 0 Listeria monocytogenes 0 0 0 0 0 0 0 0 6.0 7.0 8.0 8.5 0 Escherichia coli 7.0 8.0 9.0 9.5 0 0 0 0 8.0 9.0 10.5 11.5 0 Enterococcus faecalis 6.5 7.0 7.5 8.5 0 0 0 0 7.0 9.0 9.5 12.0 0 Bacillus cereus 6.5 7.5 8.0 8.5 0 0 0 0 7.5 8.5 10.0 10.5 0 92
test microorganisms i.e. Staphylococcus aureus, Escherichia coli, Enterococcus faecalis and Bacillus cereus, antimicrobial activity ranged between 7-9 mm, 7-9.5 mm, 6.5-8.5 mm and 6.5-8.5 mm respectively. Table 4.2 further revealed that amongst all the concentrations of ethyl alcohol (5-50%) tested, no antimicrobial activity was detected against any of the test microorganism. Perusal of result (Table 4.2) revealed that with increase in acid concentration (0.25-1.00%), an increase in antimicrobial activity against all the test microorganisms was observed. Against the different test microorganisms i.e. Staphylococcus aureus, Listeria monocytogenes, Escherichia coli, Enterococcus faecalis and Bacillus cereus, antimicrobial activity ranged between 7-10 mm, 68.5 mm, 8-11.5 mm, 7-12 mm and 7.5-10.5 mm, respectively. It is also discernible from the data (Table 4.2) that no antimicrobial activity was observed in caffeine solution (3000 ppm). 4.3 PHYSICO-CHEMICAL ANALYSIS EXTRACTED IN APPLE JUICE OF TEA LEAVES Protein content, colour and ph Table 4.3 summarizes the results of protein content, colour and ph of tea leaves extract in apple juice. It is revealed that irrespective of types of tea, with increase in concentration of tea from 2 g to 5 g there was a significant increase in protein content of tea leaves extract in apple juice. Highest protein content (778 mg/100 ml) was recorded in extract of 5 g tea and the lowest (613 mg/100 ml) was in extract of 2 g tea. Amongst the different types of tea, highest protein content (836 mg/100 ml) was observed in extract of CTC tea and the lowest (652 mg/100 ml) was in extract of orthodox tea. The interaction of concentrations with types of tea was significant. Protein content ranged between 538 to 934 mg/100 ml among the different treatments. The highest protein content was observed in extract of 5 g CTC tea (934 mg/100 ml) and lowest (538 mg/100 ml) in 2 g orthodox tea. This shows that out of different types of tea extracts with apple juice, extract of CTC tea had the highest protein content and it increased with increase in concentration. 93
Different concentrations of alcohol Different concentrations of acid Different concentrations of tea Staphylococcus aureus Listeria monocytogenes Escherichia coli Enterococcus faecalis Bacillus cereus Plate: 9 Antimicrobial activity (inhibition zone in mm) of different concentrations of tea, ethyl alcohol, citric acid and caffeine
Table 4.3 Effect of different concentrations and types of tea on protein content, colour and ph of tea leaf extracts with apple juice Concentrations of tea (per 100ml apple juice) Protein Content (mg/100 ml) Orthodox Herbal CTC tea tea tea 2g tea 538 591 711 3g tea 653 620 4g tea 657 5g tea Mean CD(p=0.05) Colour (OD 440 nm) Mean Orthodox Herbal CTC tea tea tea 613 3.99 2.15 2.94 811 694 4.14 2.88 636 887 727 4.31 759 642 934 778 652 622 836 ph Mean Orthodox Herbal CTC tea tea tea 3.03 4.60 4.55 4.54 4.56 3.24 3.42 4.64 4.65 4.64 4.64 3.77 3.52 3.86 4.67 4.78 4.70 4.72 4.95 5.68 6.02 5.55 4.73 4.80 4.75 4.76 4.35 3.62 3.93 4.66 4.70 4.66 Type of tea (T) 6 Type of tea (T) 0.06 Type of tea (T) NS Concentration (C) 7 Concentration (C) 0.07 Concentration (C) 0.07 TXC 13 TXC 0.12 TXC 0.12 94 Mean
It is discernible from the data that irrespective of types of tea, with increase in concentration of tea from 2 g to 5 g there was a significant increase in colour (OD) of tea leaves extract in apple juice (Table 4.3). Highest optical density for colour (5.55) was observed in extract of 5 g tea and the lowest (3.03) was in extract of 2 g tea. Amongst the different types of tea, lowest OD for colour (3.62) was observed in extract of herbal tea and the highest (4.35) was in extract of orthodox tea. The interaction of concentrations with types of tea was significant. OD for colour value ranged between 2.15 to 6.02 among the different treatments. The highest OD for colour was observed in extract of 5 g CTC tea (6.02) and lowest (2.15) in 2 g herbal tea. Table 4.3 further revealed the results of ph of tea leaves extract in apple juice where it was observed that for various concentrations, the differences for ph were significant. Highest ph (4.76) was observed in extract of 5 g tea which was at par with extract of 4 g tea and the lowest (4.56) was in extract of 2 g tea which was at par with extract of 3 g tea. Amongst the different types of tea, lowest ph (4.66) was recorded in extract of orthodox and CTC tea and the highest (4.70) was in extract of herbal tea. The interaction of concentrations with types of tea was significant and the ph ranged between 4.54 to 4.80 among the different treatments. The highest ph was observed in extract of 5 g herbal tea (4.80) and lowest was (4.55) in 2 g herbal tea. This shows that out of different types of tea extracts with apple juice, extract of herbal tea had the highest ph and it increased with increase in concentration. Total phenols, epicatechin and catechin In table 4.4 the effect of concentrations and types of tea on total phenols, epicatechin and catechin is summarized. Perusal of the results revealed that irrespective of types of tea, with increase in concentration of tea from 2 g to 5 g there was a significant increase in total phenols. The highest (661 mg/l) total phenols were observed in extract of 5 g tea and the lowest (449 mg/l) was in extract of 2 g tea. Amongst the different types of tea, highest total phenols (659 mg/l) were observed in extract of CTC tea and the lowest (492 mg/l) were in extract of orthodox tea which was closely followed by the herbal tea (496 mg/l). 95
The interaction of concentrations with types of tea was significant. Total phenols ranged between 399 to 809 mg/l among the different treatments. The highest total phenols were observed in extract of 5 g CTC tea (809 mg/l) and lowest (399 mg/l) were in 2 g orthodox tea. This shows that out of different types of tea extracts with apple juice, extract of CTC tea had the highest total phenol content and it increased with increase in concentration. The results (Table 4.4) show that there were significant differences among the different concentrations of tea and types of tea for epicatechin. It was observed that with the increase in concentration of tea from 2 g to 5 g, there was a significant increase in epicatechin. The highest (297 ppm) epicatechin was observed in extract of 5 g tea and the lowest (171 ppm) was in extract of 2 g tea. Amongst the different types of tea, highest epicatechin (291 ppm) was observed in extract of CTC tea and the lowest (187 ppm) was in extract of orthodox tea. Among the interaction of concentrations with types of tea, epicatechin ranged between 139 to 362 ppm. The highest epicatechin was observed in extract of 5 g CTC tea (362 ppm) and lowest (139 ppm) was in 2 g orthodox tea. This shows that out of different types of tea extracts with apple juice, extract of CTC tea had the highest epicatechin content and it increased with increase in concentration. The data (Table 4.4) further revealed that there were also significant differences for quercetin among the different treatments. It was evident that with increase in tea concentration there was significant decrease in the quercetin. The highest (14.73 ppm) quercetin was observed in extract of 2 g tea and the lowest (7.95 ppm) was in extract of 5 g tea. Amongst the different types of tea, highest quercetin (14.21 ppm) was observed in extract of orthodox tea and the lowest (7.38 ppm) was in extract of CTC tea. In case of the interaction of concentrations with types of tea, quercetin ranged between 4.85 to 17.24 ppm. The highest quercetin was observed in extract of 2 g orthodox tea (17.24 ppm) and lowest (4.85 ppm) was in 5 g CTC tea. This shows that out of different types of tea extracts with apple juice, extract of orthodox tea had the highest quercetin content and it decreased with increase in concentration. 96
Table 4.4 Effect of different concentrations and types of tea on total phenols, epicatechin and quercetin of tea leaf extracts with apple juice Concentrations of tea (per 100ml apple juice) Total phenols (mg/l) Orthodox Herbal CTC tea tea tea 2g tea 399 444 505 3g tea 457 457 4g tea 513 5g tea Mean CD(p=0.05) Epicatechin (ppm) Mean Orthodox Herbal CTC tea tea tea 449 139 159 216 618 510 170 214 509 705 576 209 600 573 809 661 492 496 659 Quercetin (ppm) Orthodox Herbal CTC tea tea tea 171 17.24 16.57 10.37 14.73 262 215 15.81 12.59 7.93 12.11 263 324 265 12.77 9.71 6.35 9.61 230 300 362 297 11.01 7.99 4.85 7.95 187 234 291 14.21 11.72 7.38 Type of tea (T) 12 Type of tea (T) Concentration (C) 14 Concentration (C) TXC 25 TXC 97 11 12 22 Mean Type of tea (T) 0.83 Concentration (C) 0.96 TXC 1.67 Mean
Caffeine and Antioxidant activity Table 4.5 summarizes the results of caffeine and antioxidant activity of tea leaves extract in apple juice. The data on the caffeine content in different extracts revealed that with increase in tea concentration from 2 g to 5 g, there was significant increase in caffeine content. The highest (756 ppm) caffeine was observed in extract of 5 g tea and the lowest (444 ppm) was in extract of 2 g tea. Amongst the different types of tea, the highest caffeine (738 ppm) was observed in extract of CTC tea and the lowest (527 ppm) was in extract of orthodox tea. Among the interaction of concentrations with types of tea, caffeine ranged between 361 to 881 ppm. The highest caffeine was observed in extract of 5 g CTC tea (881 ppm) and lowest (361 ppm) was in 2 g orthodox tea. This shows that out of different types of tea extracts with apple juice, extract of CTC tea had the highest caffeine content and it increased with increase in concentration. Perusal of Table 4.5 further revealed that the results of antioxidant activity of tea leaves extract in apple juice and it was observed that for various concentrations, types of tea and their interaction, the differences was nonsignificant. The highest (81.47 %) antioxidant activity was observed in extract of 2 g tea and the lowest (79.33 %) was in extract of 5 g tea. Amongst the different types of tea, highest antioxidant activity (81.20 %) was observed in extract of orthodox tea and the lowest (80.80 %) was in extract of CTC tea. In case of the interaction of concentrations with types of tea, antioxidant activity ranged between 78.60 to 81.80 %. The highest antioxidant activity was observed in extract of 2 g CTC tea (81.80 %) and lowest (78.60 %) was in 5 g CTC tea. 4.4 FERMENTATION BEHAVIOUR, CHARACTERISTICS, MICROBIAL PHYSICO-CHEMICAL ANTIMICROBIAL CHARACTERIZATION ACTIVITY, AND SENSORY EVALUATION OF APPLE TEA WINE FERMENTED WITH Saccharomyces cerevisiae var FERMENTATION 98 ellipsoideus AND NATURAL
Table 4.5 Effect of different concentrations and types of tea on caffeine and antioxidant activity of tea leaf extracts with apple juice Concentrations of tea (per 100ml apple juice) Caffeine (ppm) Antioxidant activity (%) Orthodox tea Herbal tea CTC tea Mean Orthodox tea Herbal tea CTC tea Mean 2g tea 361 408 563 444 81.60 81.00 81.80 81.47 3g tea 499 576 702 592 81.40 80.40 81.60 81.13 4g tea 572 588 806 656 81.20 80.00 81.20 80.80 5g tea 674 713 881 756 80.60 78.80 78.60 79.33 Mean CD(p=0.05) 527 571 738 81.20 80.05 80.80 Type of tea (T) 21 Type of tea (T) NS Concentration (C) 24 Concentration (C) NS TXC 43 TXC NS 99
4.4.1 Fermentation with Saccharomyces cerevisiae var ellipsoideus 4.4.1.1 Fermentability of different tea musts The results (Fig. 4.1) depicted the fermentation behaviour of different types of tea musts, irrespective of their concentration. In general, at the initial stages (upto 96 hours), the musts of all the tea treatments witnesses a fast reduction in TSS. Herbal tea must recorded the highest reduction in TSS followed by orthodox tea. Till 240 hours, the pattern remained the same but after this it changed clearly with the flattening of curve at 288 hours, when herbal tea recorded the lowest TSS (6.65 ob) and highest (8.15 ob) TSS in CTC tea was recorded. A comparison of rate of fermentation (Fig. 4.2) also confirmed the trend discussed earlier. Herbal tea must had better fermentation behaviour than other two tea. In confirmation to this, herbal tea had the highest rate of fermentation (1.11) and CTC tea had the lowest (0.99). The change in per cent titratable acidity (as malic acid) of different types of tea musts irrespective of their concentration can be seen in Fig. 4.3. It is clear that CTC tea must recorded the highest increase in titratable acidity followed by herbal tea. Till 240 hours, the pattern remained the same but after this it changed clearly with the flattening of curve at 288 hours, when CTC tea recorded the highest titratable acidity (0.84 %) and lowest (0.72 %) titratable acidity in orthodox tea was recorded. 22 Orthodox tea Herbal tea CTC tea 20 18 TSS OB 16 14 12 10 8 6 0 48 96 144 192 240 288 Fermentation time (hr) Figure 4.1 A comparison of fermentation behaviour of different types of tea musts 100
Figure 4.2 A comparison of rate of fermentation of different types of tea musts (M = Mean fall) 1.0 Orthodox tea Herbal tea CTC tea Titratable Acidity (%) 0.9 0.8 0.7 0.6 0.5 0.4 0 48 96 144 192 240 288 Fermentation time (hr) Figure 4.3 A comparison of titratable acidity (% malic acid) during fermentation of different types of tea musts 4.4.1.2 Fermentability of musts having different concentrations of tea Figure 4.4 depicted the fermentation behaviour of different concentrations of tea musts irrespective of the types of tea. It is visible from the graphs that virtually all the tea concentrations showed the similar fermentation behavior. In general, at the initial stages (upto 96 hours), the musts of all the tea concentrations witnesses a fast reduction in TSS. Must of 5 g tea/100 ml apple juice recorded the highest reduction in TSS followed by 4 g tea/100 ml apple juice. Till 288 hours, the pattern remained the same, when it recorded the lowest TSS (6.80 ob) and highest (8.27 ob) TSS in 2 g tea/100 ml apple juice was recorded. A comparison of rate of fermentation is shown in Fig. 4.5. Must having 101
5 g tea/100 ml apple juice had better fermentation behaviour than other three concentrations. In confirmation to this, must having 5 g tea/100 ml apple juice had the highest rate of fermentation (1.10) and 2 g tea/100 ml apple juice had the lowest (0.98). The change in per cent titratable acidity (as malic acid) of different concentrations of tea musts, irrespective of the types of tea can be seen in Fig. 4.6. It is clear that 5 g tea/100 ml apple juice must recorded the highest increase in titratable acidity followed by 4 g tea/100 ml apple juice. Till 240 hours, the pattern remained the same but after this it changed clearly with the flattening of curve at 288 hours, when 5 g tea/100 ml apple juice must recorded the highest titratable acidity (0.81 %) and lowest (0.73 %) titratable acidity in 2 g tea/100 ml apple juice must was recorded. 22 2 3 4 5 20 18 g g g g tea/100 ml apple juice tea/100ml apple juice tea/100 ml apple juice tea/100 ml apple juice TSS OB 16 14 12 10 8 6 0 48 96 144 192 240 288 Fermentation time (hr) Figure 4.4 A comparison of fermentation behaviour concentrations of tea in apple tea musts of different Figure 4.5 A comparison of rate of fermentation of different concentrations of tea in apple tea musts (M = Mean fall) 102
1.0 2 g tea/100 ml apple juice 3 g tea/100 ml apple juice 4 g tea/100 ml apple juice 5 g tea/100 ml apple juice Titratable Acidity (%) 0.9 0.8 0.7 0.6 0.5 0.4 0 48 96 144 192 240 288 Fermentation time (hr) Figure 4.6 A comparison of titratable acidity (% malic acid) during fermentation of different concentrations of tea in apple tea musts 4.4.1.3 Physico-chemical characteristics of apple tea wines Total soluble solids, reducing sugars and total sugars Table 4.6 summarizes the effect of different concentrations and types of tea on total soluble solids, reducing sugars and total sugars of apple tea wine. It is revealed that the differences for TSS were non-significant among the different concentrations of tea, types of tea and their interaction. However, irrespective of types of tea, highest TSS (7.0 ob) was observed in apple tea wine having 4 g tea and the lowest (6.6 ob) was in apple tea wine having 2 g tea. Amongst the different types of tea, highest TSS (7.05 ob) was observed in apple tea wine having CTC tea and the lowest (6.75 ob) was in apple tea wine having orthodox and herbal tea. The interaction of concentrations with types of tea shows that TSS of apple tea wine ranged between 6.40 to 7.40 ob among the different treatments. The highest TSS was observed in apple tea wine having 4 g CTC tea (7.40 ob) and lowest (6.40 ob) in 2 g orthodox tea. It is discernible from the data that with increase in concentration of tea from 2 g to 4 g, there was a significant increase in reducing sugars content of apple tea wine but in case of 5 g tea, a slight decrease in reducing sugars was observed (Table 4.6). Highest reducing sugars content (352 mg/100 ml) was observed in apple tea wine having 4 g tea and the lowest (275 mg/100 ml) was in apple tea wine having 2 g tea. Amongst the different types of tea, lowest reducing 103
Table 4.6 Effect of different concentrations and types of tea on TSS, reducing sugars and total sugars of apple tea wine fermented with Saccharomyces cerevisiae var ellipsoideus TSS (ob) Concentrations of tea (per 100ml apple juice) Orthodox Herbal CTC tea tea tea 2g tea 6.40 6.60 6.80 3g tea 6.80 6.80 4g tea 7.00 5g tea Reducing sugars (mg/100 ml) Mean Total sugars (%) Orthodox Herbal CTC Orthodox Herbal CTC tea tea tea tea tea tea 6.60 206 260 359 275 1.14 0.93 1.25 1.10 7.00 6.87 240 327 405 324 1.02 1.14 1.22 1.13 6.60 7.40 7.00 321 328 408 352 1.20 1.01 1.20 1.14 6.80 7.00 7.00 6.93 294 326 413 344 1.09 1.17 1.12 1.13 Mean CD(p=0.05) 6.75 6.75 7.05 265 310 396 1.11 1.06 1.20 Type of tea (T) NS Type of tea (T) 12 Type of tea (T) 0.01 Concentration (C) NS Concentration (C) 13 Concentration (C) 0.01 TXC NS TXC 24 TXC 0.02 104 Mean Mean
sugars (265 mg/100 ml) was observed in apple tea wine having orthodox tea and the highest (396 mg/100 ml) was in apple tea wine having CTC tea. The interaction of concentrations with types of tea was significant and reducing sugars content ranged between 206 to 413 mg/100 ml among the different treatments. The highest reducing sugars content was observed in apple tea wine having 5 g CTC tea (413 mg/100 ml) and lowest (206 mg/100 ml) in 2 g orthodox tea. The data (Table 4.6) further revealed in case of total sugars there were also significant differences among the different concentrations, types of tea and their interaction. Highest total sugars content (1.14 %) was observed in apple tea wine having 4 g tea which was at par with the apple tea wine having 3 g and 5 g tea, whereas, the lowest (1.10 %) was in apple tea wine having 2 g tea. Amongst the different types of tea, lowest total sugars (1.06 %) was observed in apple tea wine having herbal tea and the highest (1.20 %) was in apple tea wine having CTC tea. The interaction of concentrations with types of tea was significant and total sugars content ranged between 0.93 to 1.25 % among the different treatments. The highest total sugars content was observed in apple tea wine having 2 g CTC tea (1.25 %) and lowest (0.93 %) in 2 g herbal tea. Titratable acidity, ph and volatile acidity In Table 4.7 the effect of different concentrations and types of tea on titratable acidity, ph and volatile acidity of apple tea wine is summarized. It is revealed from the data that the difference for titratable acidity was non-significant among the different concentrations of tea. However, irrespective of types of tea, highest titratable acidity (0.71 %) was observed in apple tea wine having 2 g and 4 g tea and the lowest (0.69 %) was in apple tea wine having 3 g tea. Amongst the different types of tea, highest titratable acidity (0.75 %) was observed in apple tea wine having CTC tea and the lowest (0.68 %) was in apple tea wine having orthodox which was at par with the herbal tea. The interaction of concentrations with types of tea shows that titratable acidity ranged between 0.66 to 0.76 % among the different treatments. The highest titratable acidity was observed in 105
Table 4.7 Effect of different concentrations and types of tea on titratable acidity, ph and volatile acidity of apple tea wine fermented with Saccharomyces cerevisiae var ellipsoideus Concentrations of tea (per 100ml apple juice) Titratable acidity (% malic acid) Orthodox Herbal CTC tea tea tea 2g tea 0.68 0.70 0.75 3g tea 0.66 0.67 4g tea 0.66 5g tea Mean ph Volatile Acidity (% acetic acid) Orthodox Herbal CTC Orthodox Herbal CTC tea tea tea tea tea tea 0.71 4.60 4.44 4.52 4.52 0.027 0.023 0.028 0.026 0.74 0.69 4.61 4.61 4.56 4.59 0.025 0.023 0.028 0.025 0.71 0.76 0.71 4.60 4.75 4.62 4.66 0.028 0.023 0.030 0.027 0.70 0.67 0.73 0.70 4.71 4.80 4.69 4.73 0.029 0.023 0.031 0.028 Mean CD(p=0.05) 0.68 0.69 0.75 4.63 4.65 4.60 0.027 0.023 0.029 Type of tea (T) 0.03 Type of tea (T) NS Type of tea (T) NS Concentration (C) NS Concentration (C) 0.10 Concentration (C) NS TXC 0.06 TXC 0.17 TXC NS 106 Mean Mean
apple tea wine having 4 g CTC tea (0.76 %) and lowest (0.66 %) in 3 g and 4 g orthodox tea. Table 4.7 further revealed that among the different concentrations of tea, ph ranged between 4.52 to 4.73. Highest ph (4.73) was observed in apple tea wine having 5 g tea which was at par with 4 g tea and the lowest (4.52) was in apple tea wine having 2 g tea which was at par with 3 g tea. In case of different types of tea the difference for ph was non-significant. However, the highest ph (4.65) was found in herbal tea based apple tea wine and lowest (4.60) was in CTC based apple tea wine. The interaction of concentrations with types of tea was significant. The highest ph was observed in apple tea wine having 5 g herbal tea (4.80) and lowest (4.44) in 2 g herbal tea. It is also discernible from the data (Table 4.7) difference for volatile acidity was non-significant among the different concentrations of tea, types of tea and their interaction. However, irrespective of types of tea, highest volatile acidity (0.028 % acetic acid) was observed in apple tea wine having 5 g tea and the lowest (0.025 % acetic acid) was in apple tea wine having 3 g tea. Amongst the different types of tea, highest volatile acidity (0.029 % acetic acid) was observed in apple tea wine having CTC tea and the lowest (0.023 % acetic acid) was in apple tea wine having herbal tea. The interaction of concentrations with types of tea shows that volatile acidity ranged between 0.023 to 0.031% acetic acid among the different treatments. The highest volatile acidity was observed in apple tea wine having 5 g CTC tea (0.031 % acetic acid) and lowest (0.023 % acetic acid) in all the concentrations of herbal tea. Ethanol, higher alcohols and colour Table 4.8 summarizes the results of ethanol, higher alcohols and colour of apple tea wine. It was an observed that with increase in tea concentrations from 2 g to 4 g, there was increase in ethanol content but further increase in tea concentration (5 g) a gradual decrease in ethanol content was observed. Significantly highest (8.82 %) ethanol content was observed in apple tea wine having 4 g tea and lowest (8.36 %) was observed in 5 g tea which was at par with 107
2 g and 3 g tea. Among the different types of tea, highest (8.98 %) ethanol content was observed in apple tea wine having herbal tea and the lowest (8.23 %) was in apple tea wine having orthodox tea which was at par with CTC tea. The interaction of concentrations with types of tea was significant and ethanol content ranged between 7.83 to 9.19 % among the different treatments. The highest ethanol content was observed in apple tea wine having 5 g herbal tea (9.19 %) and lowest (7.83 %) in 3 g orthodox tea. It is discernible from the data that with increase in concentration of tea from 2 g to 5 g, there was a significant increase in higher alcohols of apple tea wine (Table 4.8). Highest higher alcohols (159 mg/l) was observed in apple tea wine having 5 g tea and the lowest (112 mg/l) was in apple tea wine having 2 g tea. Amongst the different types of tea, lowest higher alcohols (125 mg/l) was observed in apple tea wine having orthodox tea and apple tea wine having herbal tea, whereas, the highest (163 mg/l) was in apple tea wine having CTC tea. The interaction of concentrations with types of tea was significant and higher alcohols content ranged between 99 to 182 mg/l among the different treatments. The highest higher alcohols content was observed in apple tea wine having 5 g CTC tea (182 mg/l) and lowest (99 mg/l) in 2 g orthodox tea. This shows that out of different types of apple tea wine, apple tea wine having CTC tea had the highest higher alcohol content and it increased with increase in concentration. In case of colour (440 nm) the data (Table 4.8) further revealed that there were also significant differences among the different concentrations, types of tea and their interaction. Highest OD for colour (2.39) was observed in apple tea wine having 4 g tea, whereas, the lowest (1.78) was in apple tea wine having 2 g tea. Amongst the different types of tea, lowest OD for colour (1.59) was observed in apple tea wine having herbal tea and the highest (2.85) was in apple tea wine having orthodox tea. The interaction of concentrations with types of tea was significant and OD for colour ranged between 1.38 to 3.22 among the different treatments. The lowest OD for colour was observed in apple tea wine having 2 g herbal tea (1.38) and highest (3.22) in 4 g orthodox tea. 108
Table 4.8 Effect of different concentrations and types of tea on ethanol, higher alcohols and colour of apple tea wine fermented with Saccharomyces cerevisiae var ellipsoideus Concentrations of tea (per 100ml apple juice) Ethanol (% v/v) Orthodox Herbal CTC tea tea tea 2g tea 8.50 8.93 7.88 3g tea 7.83 8.90 4g tea 8.60 5g tea Higher alcohols (mg/l) Mean Colour (OD 440 nm) Orthodox Herbal CTC Orthodox Herbal CTC tea tea tea tea tea tea 8.44 99 95 143 112 2.25 1.38 1.70 1.78 8.67 8.47 116 134 159 136 3.14 1.49 1.93 2.19 8.88 8.99 8.82 136 124 167 142 3.22 1.72 2.23 2.39 7.99 9.19 7.90 8.36 147 148 182 159 2.80 1.75 2.50 2.35 Mean CD(p=0.05) 8.23 8.98 8.36 125 125 163 2.85 1.59 2.09 Type of tea (T) 0.23 Type of tea (T) 2 Type of tea (T) 0.12 Concentration (C) 0.26 Concentration (C) 2 Concentration (C) 0.14 TXC 0.45 TXC 5 TXC 0.24 109 Mean Mean
Total phenols, epicatechin and quercetin In Table 4.9 the effect of different concentrations and types of tea on total phenols, epicatechin and quercetin of apple tea wine is summarized. Perusal of the result revealed that the irrespective of types of tea, with increase in concentration of tea from 2 g to 5 g there was a significant increase in total phenols of apple tea wine. The highest (398 mg/l) total phenols were observed in apple tea wine having 5 g tea and the lowest (252 mg/l) was in apple tea wine having 2 g tea. Amongst the different types of tea, highest total phenols (394 mg/l) were observed in CTC tea based apple wine and the lowest (290 mg/l) were in orthodox tea based apple tea wine. The interaction of concentrations with types of tea was significant. Total phenols ranged between 225 to 474 mg/l among the different treatments. The highest total phenols were observed in apple tea wine having 5 g CTC tea (474 mg/l) and lowest (225 mg/l) were in 2 g orthodox tea. This shows that out of different types of apple tea wine, apple tea wine having CTC tea had the highest total phenol content and it increased with increase in concentration. The results (Table 4.9) show that there were significant differences among the different concentrations of tea and types of tea for epicatechin. It was observed that with increase in concentration of tea from 2 g to 5 g there was a significant increase in epicatechin of apple tea wine. The highest (243 ppm) epicatechin was observed in apple tea wine having 5 g tea and the lowest (140 ppm) was apple tea wine having 2 g tea. Amongst the different types of tea, highest epicatechin (236 ppm) was observed in CTC tea based apple tea wine and the lowest (154 ppm) was in orthodox tea based apple tea wine. Among the interaction of concentrations with types of tea, epicatechin ranged between 125 to 294 ppm. The highest epicatechin was observed in apple tea wine having 5 g CTC tea (294 ppm) and lowest (125 ppm) was in 2 g orthodox tea. This shows that out of different types of apple tea wine, apple tea wine having CTC tea had the highest epicatechin content and it increased with increase in concentration. The data (Table 4.9) further revealed that there were also significant differences for quercetin among the different treatments. It was evident from the data that with increase in tea concentration there was decrease in the quercetin. 110
Table 4.9 Effect of different concentrations and types of tea on total phenols, epicatechin and quercetin of apple tea wine fermented with Saccharomyces cerevisiae var ellipsoideus Concentrations of tea (per 100ml apple juice) Total phenols (mg/l) Orthodox Herbal CTC tea tea tea 2g tea 225 226 305 3g tea 258 303 4g tea 320 5g tea Mean CD(p=0.05) Epicatechin (ppm) Mean Orthodox Herbal CTC tea tea tea 252 125 132 164 371 311 158 183 355 425 367 167 358 363 474 398 290 312 394 Quercetin (ppm) Orthodox Herbal CTC tea tea tea 140 11.74 12.02 11.46 11.74 234 191 11.73 12.12 11.30 11.72 232 252 217 11.17 10.60 9.63 10.47 168 268 294 243 6.61 8.55 7.88 7.68 154 204 236 10.32 10.82 10.07 Type of tea (T) 5 Type of tea (T) Concentration (C) 6 Concentration (C) TXC 11 TXC 111 10 12 20 Mean Type of tea (T) 0.38 Concentration (C) 0.44 TXC 0.77 Mean
The highest (11.74 ppm) quercetin was observed in apple tea wine having 2 g tea which was at par with 3 g tea and the lowest (7.68 ppm) was in apple tea wine having 5 g tea. Amongst the different types of tea, highest quercetin (10.82 ppm) was observed in herbal tea based apple tea wine and the lowest (10.07 ppm) was in CTC tea based apple tea wine which was at par with orthodox tea. In case of the interaction of concentrations with types of tea, quercetin ranged between 7.88 to 12.02 ppm. The highest quercetin was observed in apple tea wine having 2 g herbal tea (12.02 ppm) and lowest (7.88 ppm) was in 5 g CTC tea. Protein content and amino acids Table 4.10 summarizes the results of protein content and amino acids of apple tea wine. It is revealed from the data that irrespective of types of tea, with increase in concentration of tea from 2 to 5 g there was a significant increase in protein content of apple tea wine. Highest protein content (825 mg/100 ml) was observed in apple tea wine having 5 g tea and the lowest (541 mg/100 ml) was in apple tea wine having 2 g tea. Amongst the different types of tea, highest protein content (852 mg/100 ml) was observed in CTC tea based apple tea wine and the lowest (608 mg/100 ml) was in orthodox tea based apple tea wine. The interaction of concentrations with types of tea was significant. Protein content ranged between 461 to 1018 mg/100 ml among the different treatments. The highest protein content was observed in apple tea wine having 5 g CTC tea (1018 mg/100 ml) and lowest (461 mg/100 ml) in apple tea wine having 2 g orthodox tea. This shows that out of different types of apple tea wine, apple tea wine having CTC tea had the highest protein content and it increased with increase in concentration. It is discernible from the data that irrespective of types of tea, with increase in concentration of tea from 2 to 5 g there was a significant increase in amino acids content of apple tea wine (Table 4.10). Highest amino acids content (553 mg/100 ml) was observed in apple tea wine having 5 g tea and the lowest (246 mg/100 ml) was in apple tea wine having 2 g tea. Amongst the different types of tea, highest amino acids (454 mg/100 ml) was observed in CTC tea based apple tea wine and the lowest (306 mg/100 ml) was in orthodox tea based 112
Table 4.10 Effect of different concentrations and types of tea on protein content and amino acids of apple tea wine fermented with Saccharomyces cerevisiae var ellipsoideus Concentrations of tea (per 100ml apple juice) Protein content (mg/100 ml) Amino acids (mg/100 ml) Orthodox tea Herbal tea CTC tea Mean Orthodox tea Herbal tea CTC tea Mean 2g tea 461 459 704 541 163 276 299 246 3g tea 590 689 848 709 195 290 417 301 4g tea 674 762 837 758 383 360 474 406 5g tea 708 750 1018 825 483 552 625 553 Mean CD(p=0.05) 608 665 852 306 369 454 Type of tea (T) 5 Type of tea (T) 3 Concentration (C) 6 Concentration (C) 4 TXC 11 TXC 7 113
apple tea wine. The interaction of concentrations with types of tea was significant. Amino acids content ranged between 163 to 625 mg/100 ml among the different treatments. The highest amino acids content was observed in apple tea wine having 5 g CTC tea (625 mg/100 ml) and lowest (163 mg/100 ml) in 2 g orthodox tea. This shows that out of different types of apple tea wine, apple tea wine having CTC tea had the highest aminoacid content and it increased with increase in concentration. Caffeine and Antioxidant activity Table 4.11 summarizes the results of caffeine and antioxidant activity of apple tea wine. The data on the caffeine content in different apple tea wine revealed that with increase in tea concentration from 2 to 5 g there was significant increase in caffeine content. The highest (627 ppm) caffeine was observed in apple tea wine having 5 g tea and the lowest (374 ppm) was in apple tea wine having 2 g tea. Amongst the different types of tea, significantly highest caffeine (647 ppm) was observed in CTC tea based apple tea wine and the lowest (371 ppm) was in orthodox tea based apple tea wine. Among the interaction of concentrations with types of tea, caffeine ranged between 317 to 743 ppm. The highest caffeine was observed in apple tea wine having 5 g CTC tea (743 ppm) and lowest (317 ppm) was in apple tea wine having 2 g orthodox tea. This shows that out of different types of apple tea wine, apple tea wine having CTC tea had the highest caffeine content and it increased with increase in concentration. Perusal of Table 4.11 further revealed that the results of antioxidant activity of apple tea wine and it was observed that for various concentrations, types of tea and their interaction, the differences was non-significant. With increase in concentration from 2 to 5 g, a marginal increase in antioxidant activity was observed. The highest (83.83 %) antioxidant activity was observed in apple tea wine having 5 g tea and the lowest (81.41 %) was in apple tea wine having 2 g tea. Amongst the different types of tea, highest antioxidant activity (83.44 %) was observed in herbal tea based apple tea wine and the lowest (82.04 %) was in CTC tea based apple tea wine. In case of the interaction of concentrations with types of tea, antioxidant activity ranged between 80.60 to 84.14 %. The highest antioxidant activity was observed in extract of 5 g herbal tea (84.14 %) and lowest (80.60 %) was in apple tea wine having 2 g orthodox tea. 114
Table 4.11 Effect of different concentrations and types of tea on caffeine and antioxidant activity of apple tea wine fermented with Saccharomyces cerevisiae var ellipsoideus Concentrations of tea (per 100ml apple juice) Caffeine (ppm) Antioxidant activity (%) Orthodox tea Herbal tea CTC tea Mean Orthodox tea Herbal tea CTC tea Mean 2g tea 317 325 480 374 80.60 82.46 81.16 81.41 3g tea 339 439 647 475 82.28 83.40 81.53 82.40 4g tea 369 538 718 542 83.77 83.77 82.46 83.33 5g tea 460 679 743 627 84.33 84.14 83.02 83.83 Mean CD(p=0.05) 371 495 647 82.74 83.44 82.04 Type of tea (T) 16 Type of tea (T) Concentration (C) 19 Concentration (C) TXC 33 TXC 115 NS NS NS
Antimicrobial activity Table 4.12 summarizes the antimicrobial activity of CTC, herbal and orthodox tea based apple tea wine (Plate 10). It is evident from the data that with increase in concentration of all the types of tea from 2 to 5 g, a slight increase in antimicrobial activity against all the test microorganisms was observed. Against the different test microorganisms i.e. Escherichia coli, Staphylococcus aureus, Bacillus subtilis, Bacillus cereus and Enterococcus faecalis antimicrobial activity ranged between 8.5-10.75 mm, 7-8 mm, 9-9.5 mm, 9-10 mm and 7-9 mm, respectively, in case of the CTC based apple tea wine. Table 4.12 further revealed the antimicrobial activity of herbal tea based apple tea wine and it was observed that against the different test microorganisms i.e. Escherichia coli, Staphylococcus aureus, Bacillus subtilis, Bacillus cereus and Enterococcus faecalis antimicrobial activity ranged between 9-11.25 mm, 89 mm, 9-9.5 mm, 7-9.25 mm and 7-8.5 mm, respectively. Perusal of result (Table 4.12) revealed the antimicrobial activity of orthodox tea based apple tea wine and it was observed that against the different test microorganisms i.e. Escherichia coli, Staphylococcus aureus, Bacillus subtilis, Bacillus cereus and Enterococcus faecalis antimicrobial activity ranged between 8-10.5 mm, 6.5-7.5 mm, 7-9 mm, 7-9 mm and 6-7 mm, respectively. An overview of the antimicrobial activity of different types of tea showed that CTC tea had highest antimicrobial activity against all the test microorganisms. Cluster analysis of the different treatments fermented with Saccharomyces cerevisiae var ellipsoideus The data obtained from physico-chemical analysis of apple tea wine was analysed using cluster analysis with rescaled distance cluster analysis. The dendrogram representation of the different treatments of the apple tea wine using physico-chemical characteristics showed in Fig. 4.7. Cluster analysis grouped various concentrations of tea i.e. 2 and 3 g tea in one cluster and 4 and 5 g tea in another cluster reflecting that the physicochemical characteristics of either 2 or 3 116
Table 4.12 Effect of different concentrations and types of tea on antimicrobial activity (inhibition zone in mm) of apple tea wine fermented with Saccharomyces cerevisiae var ellipsoideus Test microorganisms CTC tea (per 100ml apple juice) Herbal tea (per 100ml apple juice) Orthodox tea (per 100ml apple juice) 2g 3g 4g 5g 2g 3g 4g 5g 2g 3g 4g 5g Escherichia coli 8.50 9.25 10.75 9.00 9.00 9.25 10.00 11.25 8.00 8.50 10.00 10.50 Staphylococcus aureus 7.00 7.75 8.00 8.00 8.00 8.50 8.75 9.00 6.50 7.50 7.00 7.50 Bacillus subtilis 9.00 9.00 9.50 9.50 9.00 9.00 9.50 9.50 7.00 8.50 9.00 6.00 Bacillus cereus 9.00 9.50 10.00 10.00 7.00 8.50 9.00 9.25 7.00 7.50 8.00 9.00 Enterococcus faecalis 7.00 8.00 8.50 9.00 7.00 7.50 7.50 8.50 6.00 6.50 6.75 7.00 117
CTC tea Orthodox tea Herbal Tea Escherichia coli Staphylococcus aureus Bacillus Subitilis Bacillus cereus Enterococcus faecalis Plate: 10 Antimicrobial activity (inhibition zone in mm) of apple tea wine prepared from different concentrations and types of tea fermented with Saccharomyces cerevisiae var. ellipsoideus
g is similar and distinctly different from that of 4 and 5 g which form a separate cluster. The cluster analysis had failed to separate the type of tea into any cluster thus showing that the type of tea did not influence the physico-chemical characteristics of apple tea wine. Figure 4.7 Dendrogram of different treatments of apple tea wine using various physico-chemical characteristics analysed based on rescaled distance Sensory evaluation Table 4.13 summarizes the results of composite scoring of different treatments of apple tea wines fermented with Saccharomyces cerevisiae var ellipsoideus. Apple tea wine made from CTC tea recorded the highest scores for all the sensory attributes followed by orthodox tea. Colour of apple tea wine made from CTC tea scored the highest (1.74), whereas, score for appearance (1.76) was also highest in it than other wines. For aroma, out of three apple tea wines, apple tea wine of CTC was considered the best significantly by the judges. Volatile acidity of apple tea wine made from CTC tea scored better than that of orthodox tea and herbal tea, whereas total acidity, sweetness, body, flavour, bitterness, astringency and overall impression of apple tea wine made from CTC tea was scored better than others by the judges. On the basis of rating, apple tea 118
wines prepared from different tea falls in the standard category. Figure 4.8 shows spider web diagram of sensory qualities of apple tea wines made from different tea. Composite scoring of sensory of apple tea wine made from different concentrations of tea was also studied. Colour, appearance and aroma of the different apple tea wines increased significantly with the increase in the concentrations of tea. Apple tea wine having 5 g tea recorded the highest scores for colour, appearance and aroma which was on par with apple tea wine having 4 g tea. Volatile acidity of all the apple tea wine made from different concentrations of tea was non-significant. For total acidity all the wines were at par with the apple tea wine having 5 g tea except apple tea wine having 3 g tea. Sweetness and flavour of all the apple tea wine made from different concentrations of tea was non-significant, whereas body, bitterness, astringency and overall impression of apple tea wine having 5 g tea was scored better than others by the judges which was on par with apple tea wine having 4 g tea. On the basis of rating, apple tea wines prepared from different tea concentrations falls in the standard category. Figure 4.9 shows the spider web diagram of sensory qualities of apple tea wines having different concentrations of tea. 4.4.2 Natural fermentation 4.4.2.1 Fermentability of different tea musts Figure 4.10 showed the fermentation behaviour of different types of tea musts irrespective of their concentration. In general, at the initial stages (upto 96 hours), the musts of all the tea treatments witnesses a very slow reduction in TSS, whereas, after this a gradual decrease in TSS was observed in orthodox and herbal tea till 288 hours of fermentation and a very slow reduction in TSS was observed in CTC tea treatment till 192 hours of fermentation but after this a gradual decrease was observed upto 288 hours of fermentation. Herbal tea must recorded the highest reduction in TSS followed by orthodox tea. Herbal tea recorded the lowest TSS (6.75 ob) and highest (7.8 ob) TSS was in CTC tea. A comparison of rate of fermentation (Fig. 4.11) also confirmed the trend discussed earlier. Herbal tea must had better fermentation behaviour than other two tea. In confirmation to this, herbal tea had the highest rate of fermentation (1.20) and CTC tea had the lowest (0.79). 119
Table 4.13 Treatments A comparison of sensory scores of different treatments of apple tea wines fermented with Saccharomyces cerevisiae var ellipsoideus Colour Appearance Aroma 2 Max. Score Different types of tea 1.39 Orthodox tea 2 4 Volatile acidity 2 Total acidity 2 Sweetness Body Flavour Bitterness Astringency 1 1 2 1 Total 1 Overall impression 2 1.45 3.03 1.17 1.30 0.61 0.60 1.53 0.64 0.64 1.44 13.79 Herbal tea 1.33 1.37 2.93 1.17 1.29 0.63 0.56 1.48 0.61 0.61 1.40 13.37 CTC tea 1.74 1.76 3.46 1.26 1.34 0.71 0.69 1.65 0.70 0.70 1.61 15.60 0.030 0.040 CD (P=0.05) Different concentrations of tea 1.35 1.47 2g tea 0.061 0.019 0.018 0.016 0.016 0.036 0.047 0.023 0.062 0.371 2.95 1.19 1.31 0.63 0.55 1.50 0.57 0.57 1.41 13.51 20 3g tea 1.46 1.50 3.08 1.19 1.28 0.65 0.60 1.54 0.63 0.64 1.46 14.02 4g tea 1.54 1.56 3.24 1.21 1.31 0.65 0.65 1.57 0.68 0.68 1.51 14.59 5g tea 1.59 1.58 3.29 1.21 1.32 0.65 0.68 1.59 0.71 0.70 1.55 14.88 0.056 0.035 0.055 NS 0.026 NS 0.053 NS 0.044 0.035 0.055 0.312 CD (P=0.05) Ratings: Superior (17-20); standard (13-16); below standard (9-12); unacceptable or spoiled (1-8) 120
Figure 4.8 Spider web diagram of sensory qualities of apple tea wines (fermented with Saccharomyces cerevisiae var ellipsoideus) made from different tea 121
Figure 4.9 Spider web diagram of sensory qualities of apple tea wines (fermented with Saccharomyces cerevisiae var ellipsoideus) having different concentrations of tea 122
The change in per cent titratable acidity (as malic acid) of different types of tea musts irrespective of their concentration can be seen in Fig. 4.12. It is clear that orthodox tea must recorded the highest increase in titratable acidity followed by CTC tea. In orthodox and herbal tea, a gradual increase in titratable acidity was observed till 192 hours of fermentation followed by flattening of the curve upto 288 hours of fermentation, whereas, musts of CTC tea treatment witnesses a very slow increase in titratable acidity upto 96 hours of fermentation but after this a gradual increase in titratable acidity was observed till 192 hours of fermentation followed by flattening of the curve upto 288 hours of fermentation, when orthodox tea recorded the highest titratable acidity (0.91 %) and lowest (0.83 %) titratable acidity in herbal tea was recorded. 22 Orthodox tea Herbal tea CTC tea 20 18 TSS OB 16 14 12 10 8 6 0 48 96 144 192 240 288 Fermentation time (hr) Figure 4.10 A comparison of fermentation behaviour of different types of naturally fermented tea musts Figure 4.11 A comparison of rate of fermentation of different types of naturally fermented tea musts (M = Mean fall) 123
1.0 Orthodox tea Herbal tea CTC tea Titratable Acidity (%) 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0 48 96 144 192 240 288 Fermentation time (hr) Figure 4.12 A comparison of titratable acidity (% malic acid) during fermentation of different types of naturally fermented tea musts 4.4.2.2 Fermentability of musts having different concentrations of tea Figure 4.13 depicted the fermentation behaviour of different concentrations of tea musts irrespective of the types of tea. In general, at the initial stages (upto 240 hours), the musts of all the tea concentrations witnessed a slow reduction in TSS. Must of 5 g tea/100 ml apple juice recorded the highest reduction in TSS followed by 4 g tea/100 ml apple juice. Till 240 hours, the pattern remained the same but after this, it resulted in the similar final TSS of all the concentrations at 288 hours, when 3 g, 4 g and 5 g tea/100ml apple juice recorded the lowest TSS (7.27 ob) and highest (7.33 ob) TSS in 2 g tea/100 ml apple juice was recorded. A comparison of rate of fermentation is shown in Fig. 4.14, where it is evident that with increase in concentration of tea there was increase in rate of fermentation. Must having 5 g tea/100 ml apple juice had better fermentation behaviour which was closely followed by 4 g tea/100 ml apple juice. In confirmation to this, must having 5 g tea/100 ml apple juice had the highest rate of fermentation (1.15) and 2 g tea/100 ml apple juice had the lowest (0.84). The change in per cent titratable acidity (as malic acid) of different concentrations of tea musts irrespective of the types of tea can be seen in Fig. 4.15. It is clear that 5 g tea/100 ml apple juice must recorded the highest increase 124
in titratable acidity followed by 4 g tea/100 ml apple juice. Till 192 hours, the pattern remained the same but after this it changed clearly with the flattening of curve at 288 hours, when 5 g tea/100 ml apple juice must recorded the highest titratable acidity (0.97 %) and lowest (0.77 %) titratable acidity in 2 g tea/100 ml apple juice must was recorded. 22 2 g tea/100 ml apple juice 3 g tea/100 ml apple juice 4 g tea/100 ml apple juice 5 g tea/100 ml apple juice 20 18 TSS OB 16 14 12 10 8 6 0 48 96 144 192 240 288 Fermentation time (hr) Figure 4.13 A comparison of fermentation behaviour of different concentrations of naturally fermented tea musts Figure 4.14 A comparison of rate of fermentation of different concentrationsof naturally fermented tea musts (M = Mean fall) 125
1.1 2 g tea/100ml apple juice 3 g tea/100ml apple juice 4 g tea/100ml apple juice 5 g tea/100ml apple juice Titratable Acidity (%) 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0 48 96 144 192 240 288 Fermentation time (hr) Figure 4.15 A comparison of titratable acidity (% malic acid) during fermentation of different concentrations of naturally fermented tea musts 4.4.2.4 Physico-chemical characteristics of apple tea wines Total soluble solids, reducing sugars and total sugars Table 4.14 summarizes the effect different concentrations and types of tea on total soluble solids, reducing sugars and total sugars of apple tea wine. It is revealed from the data that the difference for TSS was non-significant among the different concentrations of tea. However, irrespective of types of tea, highest TSS (7.47 ob) was observed in apple tea wine having 5 g tea and the lowest (7.27 ob) was in apple tea wine having 3 g and 4 g tea. Amongst the different types of tea, highest TSS (7.80 ob) was observed in apple tea wine having CTC tea and the lowest (6.90 ob) was in apple tea wine having herbal tea. The interaction of concentrations with types of tea was significant and it was observed that TSS ranged between 6.60 to 8.20 ob among the different treatments. The highest TSS was observed in apple tea wine having 5 g CTC tea (8.20 ob) and lowest (6.60 o B) in 4 g herbal tea. 126
Table 4.14 Effect of different concentrations and types of tea on TSS, reducing sugars and total sugars of apple tea wine fermented by natural fermentation TSS (ob) Concentrations of tea (per 100ml apple juice) Orthodox Herbal CTC tea tea tea 2g tea 7.60 7.00 7.40 3g tea 7.00 7.00 4g tea 7.40 5g tea Reducing sugars (mg/100 ml) Mean Orthodox Herbal CTC tea tea tea 7.33 424 135 321 7.80 7.27 209 68 6.60 7.80 7.27 184 7.20 7.00 8.20 7.47 Mean CD(p=0.05) 7.30 6.90 7.80 Type of tea (T) 0.32 Type of tea (T) Concentration (C) NS Concentration (C) TXC 0.64 TXC Total sugars (%) Orthodox Herbal CTC tea tea tea 293 3.32 0.88 1.86 2.02 512 263 1.36 0.82 2.87 1.69 81 265 177 1.47 0.77 1.24 1.16 133 113 370 205 1.60 0.69 1.41 1.24 237 99 367 1.94 0.79 1.85 127 11 12 22 Mean Type of tea (T) 0.02 Concentration (C) 0.02 TXC 0.03 Mean
It is discernible from the data that among the different concentrations of tea from 2 g to 4 g, there was a significant decrease in reducing sugars content of apple tea wine but in case of 5 g tea, a slight increase in reducing sugars was observed (Table 4.14). Highest reducing sugars content (293 mg/100 ml) was observed in apple tea wine having 2 g tea and the lowest (177 mg/100 ml) was in apple tea wine having 4 g tea. Amongst the different types of tea, lowest reducing sugars (99 mg/100 ml) was observed in apple tea wine having herbal tea and the highest (367 mg/100 ml) was in apple tea wine having CTC tea. The interaction of concentrations with types of tea was significant and reducing sugars content ranged between 68 to 512 mg/100 ml among the different treatments. The highest reducing sugars content was observed in apple tea wine having 3 g CTC tea (512 mg/100 ml) and lowest (68 mg/100 ml) in 3 g herbal tea. The data (Table 4.14) further revealed in case of total sugars that there were also significant differences among the different concentrations, types of tea and their interaction. It is also discernible from the data that among the different concentrations of tea from 2 g to 4 g, there was a significant decrease in total sugars content of apple tea wine but in case of 5 g tea, a slight increase in total sugars was observed. Highest total sugars content (2.02 %) was observed in apple tea wine having 2 g tea, whereas, the lowest (1.16 %) was in apple tea wine having 4 g tea. Amongst the different types of tea, lowest total sugars (0.79 %) was observed in apple tea wine having herbal tea and the highest (1.94 %) was in apple tea wine having orthodox tea followed by apple tea wine having CTC tea. The interaction of concentrations with types of tea was significant and total sugars content ranged between 0.69 to 3.32 % among the different treatments. The highest total sugars content was observed in apple tea wine having 2 g orthodox tea (3.32 %) and lowest (0.69 %) in 5 g herbal tea. Titratable acidity, ph and volatile acidity In Table 4.15 the effect of different concentrations and types of tea on titratable acidity, ph and volatile acidity of apple tea wine is summarized. It is revealed from the data that irrespective of types of tea, highest titratable acidity (0.83 %) was observed in apple tea wine having 5 g tea and the lowest (0.77 %) was in apple tea wine having 2 g and 3 g tea. Amongst the different types of tea, 128
highest titratable acidity (0.81 %) was observed in CTC and herbal tea based wine and the lowest (0.76 %) was in apple tea wine having orthodox tea. The interaction of concentrations with types of tea shows that titratable acidity ranged between 0.68 to 0.82 % among the different treatments. The highest titratable acidity was observed in apple tea wine having 4 g CTC tea (0.82 %) and lowest (0.68 %) in 3 g orthodox tea. Table 4.15 further revealed that among the different concentrations of tea, ph ranged between 4.16 to 4.37. Highest ph (4.37) was observed in apple tea wine having 5 g tea which was at par with 3 g and 4 g tea and the lowest (4.16) was in apple tea wine having 2 g tea. In case of different types of tea the difference for ph was non-significant. However, highest ph (4.32) was found in CTC tea based apple tea wine and lowest (4.26) was in herbal tea based apple tea wine. The interaction of concentrations with types of tea was significant. The highest ph was observed in apple tea wine having 5 g CTC tea (4.43) and lowest (4.09) in 2 g herbal tea. It is also discernible from the data (Table 4.15) that difference for volatile acidity was significant among the different concentrations of tea, types of tea and their interaction. However, irrespective of types of tea, highest volatile acidity (0.046 % acetic acid) was observed in apple tea wine having 5 g tea and the lowest (0.031 % acetic acid) was in apple tea wine having 3 g and 4 g tea. Among the different types of tea, highest volatile acidity (0.041 % acetic acid) was observed in apple tea wine having CTC tea and the lowest (0.029 % acetic acid) was in apple tea wine having herbal tea. The interaction of concentrations with types of tea shows that volatile acidity ranged between 0.025 to 0.059% acetic acid among the different treatments. The highest volatile acidity was observed in apple tea wine having 5 g CTC tea (0.059 % acetic acid) and lowest (0.025 % acetic acid) in 4 g herbal tea. Ethanol, higher alcohols and colour Table 4.16 summarizes the results of ethanol, higher alcohols and colour of apple tea wine. It was observed that with increase in tea concentrations from 2 g to 4 g, there was decrease in ethanol content but further increase in tea 129
Table 4.15 Effect of different concentrations and types of tea on titratable acidity, ph and volatile acidity of apple tea wine fermented by natural fermentation Concentrations of tea (per 100ml apple juice) Titratable acidity (% malic acid) Orthodox Herbal CTC tea tea tea 2g tea 0.74 0.78 0.79 3g tea 0.68 0.82 4g tea 0.76 5g tea Mean ph Volatile Acidity (% acetic acid) Orthodox Herbal CTC Orthodox Herbal CTC tea tea tea tea tea tea 0.77 4.18 4.09 4.20 4.16 0.031 0.034 0.031 0.032 0.81 0.77 4.33 4.28 4.28 4.30 0.026 0.031 0.036 0.031 0.81 0.82 0.80 4.31 4.27 4.38 4.32 0.029 0.025 0.037 0.031 0.84 0.82 0.81 0.83 4.30 4.38 4.43 4.37 0.050 0.028 0.059 0.046 Mean CD(p=0.05) 0.76 0.81 0.81 4.28 4.26 4.32 0.034 0.029 0.041 Type of tea (T) NS Type of tea (T) NS Type of tea (T) 0.007 Concentration (C) 0.04 Concentration (C) 0.09 Concentration (C) 0.008 TXC 0.07 TXC 0.15 TXC 0.014 130 Mean Mean
concentration(5 g) a gradual increase in ethanol content was observed. Highest (8.19 %) ethanol content was observed in apple tea wine having 2 g tea which was at par with 3 g tea and lowest (7.61 %) was observed in 4 g tea. Among the different types of tea, highest (8.31 %) ethanol content was observed in apple tea wine having herbal tea and the lowest (7.63 %) was in apple tea wine having orthodox tea. The interaction of concentrations with types of tea was significant and ethanol content ranged between 7.29 to 8.62 % among the different treatments. The highest ethanol content was observed in apple tea wine having 5 g herbal tea (8.62 %) and lowest (7.29 %) in 3 g orthodox tea. It is discernible from the data that with increase in concentration of tea from 2 g to 5 g, there was a significant increase in higher alcohols of apple tea wine (Table 4.16). Highest higher alcohols (277 mg/l) was observed in apple tea wine having 5 g tea and the lowest (190 mg/l) was in apple tea wine having 2 g tea. Amongst the different types of tea, lowest higher alcohols (191 mg/l) was observed in apple tea wine having orthodox tea and the highest (304 mg/l) was in apple tea wine having CTC tea. The interaction of concentrations with types of tea was significant and higher alcohols content ranged between 132 to 347 mg/l among the different treatments. The highest higher alcohols content was observed in apple tea wine having 5 g CTC tea (347 mg/l) and lowest (132 mg/l) in 3g orthodox tea which was closely followed by 2g orthodox tea. This shows that out of different types of apple tea wine, apple tea wine having CTC tea had the highest higher alcohol content and it increased with increase in concentration. The data (Table 4.16) further revealed in case of colour (440 nm) that there were also significant differences among the different concentrations, types of tea and their interaction. Highest OD for colour (5.10) was observed in apple tea wine having 5 g tea, whereas, the lowest (1.89) was in apple tea wine having 2 g tea. Amongst the different types of tea, lowest OD for colour (2.93) was observed in apple tea wine having CTC tea which was at par with apple tea wine having orthodox tea and the highest (3.35) was in apple tea wine having herbal tea. The interaction of concentrations with types of tea was significant and OD for colour ranged between 1.15 to 5.60 among the different treatments. 131
Table 4.16 Effect of different concentrations and types of tea on ethanol, higher alcohols and colour of apple tea wine fermented by natural fermentation Concentrations of tea (per 100ml apple juice) Ethanol (% v/v) Orthodox Herbal CTC tea tea tea 2g tea 8.37 8.47 7.72 3g tea 7.29 8.69 4g tea 7.40 5g tea Higher alcohols (mg/l) Mean Colour (OD 440 nm) Orthodox Herbal CTC Orthodox Herbal CTC tea tea tea tea tea tea 8.19 133 149 287 190 1.15 2.44 2.08 1.89 8.28 8.09 132 215 289 212 1.86 3.31 1.99 2.39 7.46 7.96 7.61 247 199 292 246 3.40 2.87 2.74 3.00 7.46 8.62 7.66 7.91 250 233 347 277 5.60 4.79 4.92 5.10 Mean CD(p=0.05) 7.63 8.31 7.91 191 199 304 3.00 3.35 2.93 Type of tea (T) 0.19 Type of tea (T) 2 Type of tea (T) 0.12 Concentration (C) 0.22 Concentration (C) 3 Concentration (C) 0.14 TXC 0.39 TXC 5 TXC 0.24 132 Mean Mean
The lowest OD for colour was observed in apple tea wine having 2 g orthodox tea (1.15) and highest (5.60) in 5 g orthodox tea. Total phenols, epicatechin and quercetin In Table 4.17 the effect of different concentrations and types of tea on total phenols, epicatechin and quercetin of apple tea wine is summarized. Perusal of the result revealed that the irrespective of types of tea, with increase in concentration of tea from 2 g to 5 g there was a gradual increase in total phenols of apple tea wine. The highest (579 mg/l) total phenols were observed in apple tea wine having 5 g tea and the lowest (415 mg/l) was in apple tea wine having 2 g tea which was at par with apple tea wine having 3 g tea. Amongst the different types of tea, highest total phenols (539 mg/l) were observed in CTC tea based apple wine and the lowest (448 mg/l) were in herbal tea based apple tea wine. The interaction of concentrations with types of tea was significant. Total phenols ranged between 367 to 660 mg/l among the different treatments. The highest total phenols were observed in apple tea wine having 5 g CTC tea (660 mg/l) and lowest (367 mg/l) were in 2 g orthodox tea. This shows that out of different types of apple tea wine, apple tea wine having CTC tea had the highest total phenol content and it increased with increase in concentration. The results (Table 4.17) show that there were significant differences among the different concentrations of tea and types of tea for epicatechin. It was observed that with increase in concentration of tea from 2 g to 5 g there was a significant increase in epicatechin of apple tea wine. The highest (313 ppm) epicatechin was observed in apple tea wine having 5 g tea and the lowest (166 ppm) was apple tea wine having 2 g tea. Amongst the different types of tea, highest epicatechin (279 ppm) was observed in CTC tea based apple tea wine and the lowest (210 ppm) was in herbal tea based apple tea wine which was at par with orthodox tea based apple tea wine. Among the interaction of concentrations with types of tea, epicatechin ranged between 138 to 391 ppm. The highest epicatechin was observed in apple tea wine having 5 g CTC tea (391 ppm) and lowest (138 ppm) was in 2 g orthodox tea. This shows that out of different types of apple tea wine, apple tea wine having CTC tea had the highest epicatechin content and it increased with increase in concentration. 133
Table 4.17 Effect of different concentrations and types of tea on total phenols, epicatechin and quercetin of apple tea wine fermented by natural fermentation Concentrations of tea (per 100ml apple juice) Total phenols (mg/l) Orthodox Herbal CTC tea tea tea 2g tea 367 376 503 3g tea 407 396 4g tea 496 5g tea Mean CD(p=0.05) Epicatechin (ppm) Mean Orthodox Herbal CTC tea tea tea 415 138 145 215 450 418 212 192 509 544 516 240 568 510 660 579 460 448 539 Quercetin (ppm) Orthodox Herbal CTC tea tea tea 166 13.32 12.48 13.60 13.13 217 207 12.19 12.38 11.60 12.06 234 294 256 12.07 11.77 11.06 11.63 278 269 391 313 11.61 11.68 11.21 11.50 217 210 279 12.29 12.08 11.87 Type of tea (T) 5 Type of tea (T) Concentration (C) 6 Concentration (C) TXC 11 TXC 134 10 12 21 Mean Type of tea (T) 0.75 Concentration (C) 0.87 TXC 1.50 Mean
The data (Table 4.17) further revealed that there were also significant differences for quercetin among the different treatments. It was evident that with increase in tea concentration there was decrease in the quercetin. The highest (13.13 ppm) quercetin was observed in apple tea wine having 2 g tea and the lowest (11.50 ppm) was in apple tea wine having 5 g tea which was at par with 4 g tea. Amongst the different types of tea the difference was non-significant. However, highest quercetin (12.29 ppm) was observed in orthodox tea based apple tea wine and the lowest (11.87 ppm) was in CTC tea based apple tea wine. In case of the interaction of concentrations with types of tea, quercetin ranged between 11.06 to 13.32 ppm. The highest quercetin was observed in apple tea wine having 2 g orthodox tea (13.32 ppm) and lowest (11.06 ppm) was in 4 g CTC tea. Protein content and amino acids Table 4.18 summarizes the results of protein content and amino acids of apple tea wine. It is revealed from the data that irrespective of types of tea, with increase in concentration of tea from 2 g to 5 g there was a significant increase in protein content of apple tea wine. Highest protein content (1035 mg/100 ml) was observed in apple tea wine having 5 g tea and the lowest (590 mg/100 ml) was in apple tea wine having 2 g tea. Amongst the different types of tea, highest protein content (975 mg/100 ml) was observed in CTC tea based apple tea wine and the lowest (649 mg/100 ml) was in herbal tea based apple tea wine. The interaction of concentrations with types of tea was significant. Protein content ranged between 476 to 1295 mg/100 ml among the different treatments. The highest protein content was observed in apple tea wine having 5 g CTC tea (1295 mg/100 ml) and lowest (476 mg/100 ml) in apple tea wine having 2 g herbal tea. This shows that out of different types of apple tea wine, apple tea wine having CTC tea had the highest protein content and it increased with increase in concentration. It is discernible from the data that irrespective of types of tea, with increase in concentration of tea from 2 g to 5 g there was a significant increase in amino acids content of apple tea wine (Table 4.18). Highest amino acids content (453 mg/100 ml) was observed in apple tea wine having 5 g tea and the lowest 135
(194 mg/100 ml) was in apple tea wine having 2 g tea. Amongst the different types of tea, highest amino acids (380 mg/100 ml) was observed in CTC tea based apple tea wine and the lowest (204 mg/100 ml) was in herbal tea based apple tea wine. The interaction of concentrations with types of tea was significant. Amino acids content ranged between 146 to 555 mg/100 ml among the different treatments. The highest amino acids content was observed in apple tea wine having 5 g CTC tea (555 mg/100 ml) and lowest (146 mg/100 ml) in 2 g herbal tea. This shows that out of different types of apple tea wine, apple tea wine having CTC tea had the highest amino acid content and it increased with increase in concentration. Caffeine and Antioxidant activity Table 4.19 summarizes the results of caffeine and antioxidant activity of apple tea wine. The data on the caffeine content in different apple tea wine revealed that with increase in tea concentration from 2 g to 5 g there was significant increase in caffeine content. The highest (671 ppm) caffeine was observed in apple tea wine having 5 g tea and the lowest (397 ppm) was in apple tea wine having 2 g tea. Amongst the different types of tea, significantly highest caffeine (626 ppm) was observed in CTC tea based apple tea wine and the lowest (407 ppm) was in orthodox tea based apple tea wine. Among the interaction of concentrations with types of tea, caffeine ranged between 329 to 789 ppm. The highest caffeine was observed in apple tea wine having 5 g CTC tea (789 ppm) and lowest (329 ppm) was in apple tea wine having 2 g orthodox tea. This shows that out of different types of apple tea wine, apple tea wine having CTC tea had the highest caffeine content and it increased with increase in concentration. Perusal of Table 4.19 further revealed that the results of antioxidant activity of apple tea wine and it was observed that for various concentrations, types of tea and their interaction, the differences was non-significant. The highest (82.87 %) antioxidant activity was observed in apple tea wine having 5 g tea and the lowest (81.60 %) was in apple tea wine having 2 g tea. Amongst the different 136
Table 4.18 Effect of different concentrations and types of tea on protein content and amino acids of apple tea wine fermented by natural fermentation Concentrations of tea (per 100ml apple juice) Protein Content (mg/100 ml) Amino acids (mg/100 ml) Orthodox tea Herbal tea CTC tea Mean Orthodox tea Herbal tea CTC tea Mean 2g tea 514 476 779 590 149 146 287 194 3g tea 705 577 794 692 182 158 306 215 4g tea 864 689 1029 861 241 194 370 268 5g tea 953 855 1295 1035 487 317 555 453 Mean CD(p=0.05) 759 649 975 265 204 380 Type of tea (T) 6 Type of tea (T) 4 Concentration (C) 7 Concentration (C) 5 TXC 12 TXC 9 137
Table 4.19 Effect of different concentrations and types of tea on caffeine and antioxidant activity of apple tea wine fermented by natural fermentation Concentrations of tea (per 100ml apple juice) Caffeine (ppm) Antioxidant activity (%) Orthodox tea Herbal tea CTC tea Mean Orthodox tea Herbal tea CTC tea Mean 2g tea 329 381 483 397 82.20 81.20 81.40 81.60 3g tea 366 514 493 458 82.40 81.40 81.80 81.87 4g tea 407 564 740 570 83.00 82.00 82.00 82.33 5g tea 528 698 789 671 83.40 83.00 82.20 82.87 Mean 407 539 626 82.75 81.90 81.85 CD(p=0.05) Type of tea (T) 19 Type of tea (T) NS Concentration (C) 22 Concentration (C) NS TXC 38 TXC NS 138
types of tea, highest antioxidant activity (82.75 %) was observed in orthodox tea based apple tea wine and the lowest (81.85 %) was in CTC tea based apple tea wine. In case of the interaction of concentrations with types of tea, antioxidant activity ranged between 81.20 to 83.40 %. The highest antioxidant activity was observed in extract of 5 g orthodox tea (83.40 %) and lowest (81.20 %) was in apple tea wine having 2 g herbal tea. Antimicrobial activity Table 4.20 summarizes the antimicrobial activity of CTC, herbal and orthodox tea based apple tea wine (Plate 11). It is evident from the data that with increase in concentration of all the types of tea from 2 to 5%, a slight increase in antimicrobial activity against all the test microorganisms was observed. Against the different test microorganisms i.e. Escherichia coli, Staphylococcus aureus, Bacillus subtilis, Bacillus cereus and Enterococcus faecalis antimicrobial activity ranged between 8.5-10 mm, 7.5-8 mm, 7-9 mm, 8.5-9.5 mm and 7-8 mm respectively in case of the CTC based apple tea wine. Table 4.20 further revealed the antimicrobial activity of herbal tea based apple tea wine and it was observed that against the different test microorganisms i.e. Escherichia coli, Staphylococcus aureus, Bacillus subtilis, Bacillus cereus and Enterococcus faecalis antimicrobial activity ranged between 8.25-9.5 mm, 78.5 mm, 7-9 mm, 7-9.5 mm and 6-8.5 mm respectively. Perusal of result (Table 4.20) revealed the antimicrobial activity of orthodox tea based apple tea wine and it was observed that against the different test microorganisms i.e. Escherichia coli, Staphylococcus aureus, Bacillus subtilis, Bacillus cereus and Enterococcus faecalis antimicrobial activity ranged between 5.75-9.5 mm, 6.5-8 mm, 9.5-10 mm, 8.5-11 mm and 7.5-9.5 mm respectively. An overview of the antimicrobial activity of different types of tea showed that CTC tea had highest antimicrobial activity against all the test microorganisms. 139
Table 4.20 Effect of different concentrations and types of tea on antimicrobial activity (inhibition zone in mm) of apple tea wine fermented by natural fermentation Test microorganisms CTC tea (per 100ml apple juice) Herbal tea (per 100ml apple juice) Orthodox tea (per 100ml apple juice) 2g 3g 4g 5g 2g 3g 4g 5g 2g 3g 4g 5g Escherichia coli 8.50 8.50 9.50 10.00 8.25 9.00 9.50 9.50 5.75 7.75 9.25 9.50 Staphylococcus aureus 7.50 8.00 9.50 8.00 7.00 7.50 7.50 8.50 6.50 6.50 7.00 8.00 Bacillus subtilis 7.00 9.50 10.00 9.00 7.00 7.50 8.50 9.00 9.50 8.50 9.50 10.00 Bacillus cereus 8.50 9.00 9.00 9.50 7.00 8.00 9.50 9.50 8.50 8.00 10.50 11.00 Enterococcus faecalis 7.00 7.00 8.00 8.00 6.00 7.00 8.00 8.50 7.50 7.50 8.00 9.50 140
Cluster analysis of the different naturally fermented treatments The data obtained from physico-chemical analysis of apple tea wine was analysed using cluster analysis with rescaled distance cluster analysis. The dendrogram representation of the different treatments of the apple tea wine using physico-chemical characteristics showed in Fig. 4.16. It was observed that the physico-chemical characteristic does not present any classification among all the treatments based on types of tea or their concentrations. Among the different treatments, 5 g tea is outlier. The distinctness of this treatment is a characteristic of difference among the physico-chemical characteristics. Table 4.14 to 4.19 also revealed the same. Figure 4.16 Dendrogram of different treatments of naturally fermented apple tea wine using various physico-chemical characteristics analysed based on rescaled distance 141
CTC tea Orthodox tea Herbal Tea Escherichia coli Staphylococcus aureus Bacillus Subitilis Bacillus cereus Enterococcus faecalis Plate: 11 Antimicrobial activity (inhibition zone in mm) of apple tea wine prepared from different concentrations and types of tea fermented by natural fermentation
Sensory evaluation Table 4.21 summarizes the results of composite scoring of different treatments of different treatments of naturally fermented apple tea wines. Apple tea wine made from CTC tea recorded the highest scores for all the sensory attributes followed by orthodox tea. Colour of apple tea wine made from CTC tea scored the highest (1.64), whereas, score for appearance (1.63) was also highest in it than other wines. For aroma, out of three apple tea wines, apple tea wine of CTC was considered the best significantly by the judges. Volatile acidity of apple tea wine made from CTC tea scored better than that of orthodox tea and herbal tea. Total acidity of all the apple tea wine made from different tea was nonsignificant, whereas sweetness, body, flavour, bitterness and overall impression of apple tea wine made from CTC tea was scored better than others by the judges. Astringency of all the apple tea wine made from different tea was non-significant. On the basis of rating, apple tea wines prepared from different tea falls in the standard category. Figure 4.17 shows spider web diagram of sensory qualities of apple tea wines made from different tea. Composite scoring of sensory of apple tea wine made from different concentrations of tea was also studied. Colour, appearance, aroma and volatile acidity of the different apple tea wines increased significantly with the increase in the concentrations of tea. Apple tea wine having 5 g tea recorded the highest scores for colour, appearance and aroma which was on par with apple tea wine having 4 g tea. Volatile acidity, total acidity and sweetness of all the apple tea wine made from different concentrations of tea was non-significant, whereas body, flavor, bitterness, astringency and overall impression of apple tea wine having 5 g tea was scored better than others by the judges which was on par with apple tea wine having 4 g tea. On the basis of rating, apple tea wines prepared from different tea concentrations falls in the standard category. Figure 4.18 shows the spider web diagram of sensory qualities of apple tea wines having different concentrations of tea. 142
Table 4.21 A comparison of sensory scores of different treatments of naturally fermented apple tea wines Treatments Colour Appearance Aroma 2 Max. Score Different types of tea 1.35 Orthodox tea 2 4 Volatile acidity 2 Total acidity 2 Sweetness Body Flavour Bitterness Astringency 1 1 2 1 Total 1 Overall impression 2 1.42 3.05 1.27 1.38 0.63 0.58 1.41 0.62 0.66 1.26 13.61 Herbal tea 1.28 1.33 2.94 1.27 1.37 0.63 0.55 1.36 0.61 0.63 1.22 13.18 CTC tea 1.64 1.63 3.34 1.35 1.41 0.74 0.65 1.51 0.67 0.71 1.38 15.01 CD (P=0.05) 0.023 0.059 Different concentrations of tea 1.29 1.40 2g tea 0.059 0.023 NS 0.048 0.036 0.036 0.030 NS 0.023 0.712 2.93 1.27 1.37 0.64 0.54 1.36 0.57 0.59 1.22 13.18 20 3g tea 1.40 1.44 3.06 1.28 1.38 0.67 0.57 1.42 0.60 0.66 1.27 13.75 4g tea 1.47 1.48 3.18 1.31 1.39 0.67 0.61 1.44 0.67 0.70 1.31 14.24 5g tea 1.52 1.52 3.26 1.34 1.39 0.68 0.64 1.46 0.70 0.72 1.35 14.58 0.026 0.046 0.093 NS NS NS 0.070 0.053 0.061 0.025 0.053 0.624 CD (P=0.05) Ratings: Superior (17-20); standard (13-16); below standard (9-12); unacceptable or spoiled (1-8) 143
Figure 4.17 Spider web diagram of sensory qualities of apple tea wines (naturally fermented) made from different tea 144
Figure 4.18 Spider web diagram of sensory qualities of apple tea wines (naturally fermented) having different concentrations of tea 145
Table 4.22 Isolated strain Gram staining Surface growth Turbidity Amount of growth Starch Cellulose Caesin Citrate utilization test Gelatin Catalase H 2S production Urease Maltose Manitol Dextrose Glucose Fructose Sucrose Lactose Tentative identified Morphological and biochemical characterization of different microbial isolates from natural fermentation O31 O34 C41 Bacteria H44 + + + + + + + NA NA NA NA NA Present Absent Present Absent Absent Absent Present Present Absent Slightly present Absent Present Absent Uniform Uniform Flocculated Uniform Uniform Flocculated Flocculated Present Flocculated Uniform Slightly Flocculated Moderate Moderate Profuse Moderate Moderate Profuse Profuse Profuse Profuse Profuse Moderate + + + + + + + + Moderat e + + + + + + NA NA NA NA NA - - - - - - - NA NA NA NA NA + + + + + + + + + + + + + NA NA NA NA NA NA NA NA NA NA - + - - - - - NA NA NA NA NA + + + + - + + + + + + + + + + + + + - + + + + + - + + + + + - + + + + + + + + + + + + + NA + + + + - NA + + + + + + - NA + + + + - NA + + + + + + - NA + + + + - O52 C3 C21 H2 Bacillus spp. H42 Yeast H31 O33 O22 Saccharomyces spp. 146
Isolation, identification and characterization of microbial isolates from natural fermentation The biochemical and morphological tests of the isolated microorganism performed are listed in Table 4.22. It is evident from the table that all the bacterial isolates belong to genus Bacillus and all the yeast isolates belong to genus Saccharomyces (Plate 12). 4.4.3 Comparison between different types of fermentation 4.4.3.1 Fermentability of different types of fermentation The results (Fig. 4.19) depicted the fermentation behaviour of two different types of fermentations i.e. fermentation with Saccharomyces cerevisiae var ellipsoideus and natural fermentation. In general, upto 240 hours, there was gradual reduction in TSS, when fermentation with Saccharomyces cerevisiae var ellipsoideus recorded the lower TSS (798 ob) and higher (9.7 ob) TSS in natural fermentation was recorded. A comparison of rate of fermentation (Fig. 4.20) also confirmed the trend discussed earlier. Fermentation with Saccharomyces cerevisiae var ellipsoideus had better fermentation behaviour than natural fermentation. In confirmation to this, fermentation with Saccharomyces cerevisiae var ellipsoideus had the higher rate of fermentation (1.20) and natural fermentation had the lower (1.03). The change in per cent titratable acidity (as malic acid) of two different types of fermentations i.e. fermentation with Saccharomyces cerevisiae var ellipsoideus and natural fermentation can be seen in Fig. 4.21. It is clear that natural fermentation recorded the highest increase in titratable acidity as compared to fermentation with Saccharomyces cerevisiae var ellipsoideus. In natural fermentation, a gradual increase in titratable acidity was observed till 192 hours of fermentation followed by flattening of the curve upto 240 hours of fermentation, whereas, fermentation with Saccharomyces cerevisiae var ellipsoideus witnesses a very slow and gradual increase in titratable acidity upto 240 hours of fermentation, when natural fermentation recorded the highest titratable acidity (0.86 %) and lowest (0.77 %) titratable acidity in fermentation with Saccharomyces cerevisiae var ellipsoideus was recorded. 147
Plate: 12 Microbial isolates isolated from natural fermentation and used for further experiments as consortia
22 Fermentation with Saccharomyces cerevisiae var. ellipsoideus Natural fermentation 20 18 TSS OB 16 14 12 10 8 6 0 48 96 144 192 240 Fermentation time (hr) Figure 4.19 A comparison of fermentation behaviour of different types of fermentation Figure 4.20 A comparison of rate of fermentation of different types of fermentation (M = Mean fall) 1.0 Fermentation with Saccharomyces cerevisiae var. ellipsoideus Natural fermentation Titratable Acidity (%) 0.9 0.8 0.7 0.6 0.5 0.4 0 48 96 144 192 240 Fermentation time (hr) Figure 4.21 A comparison of titratable acidity (% malic acid) during fermentation of different types of fermentation 148
4.4.3.2 Cluster analysis of the different treatments fermented by different types of fermentation The data obtained from physico-chemical analysis of apple tea wines prepared by different types of fermentation was analysed using cluster analysis with rescaled distance cluster analysis. The dendrogram representation of the different types of fermentation using physico-chemical characteristics showed in Fig. 4.22. Cluster analysis grouped different fermentation in separate clusters. One cluster comprises of apple tea wine fermented with with Saccharomyces cerevisiae var ellipsoideus and another cluster comprises of naturally fermented apple tea wine. In Cluster of fermentation with Saccharomyces cerevisiae var ellipsoideus, the treatments were classified according to the tea concentrations i.e. 2 and 3 g tea in one cluster and 4 and 5 g tea in another cluster reflecting that the physicochemical characteristics of either 2 or 3 g is similar and distinctly different from that of 4 and 5 g which form a separate cluster. In natural fermented apple tea wine cluster it was observed that the physico-chemical characteristic does not present any classification among all the treatments based on types of tea or their concentrations. The cluster analysis further revealed that type of fermentation had influenced the physico-chemical characteristics of apple tea wine. 4.4.3.3 Sensory evaluation The results (Fig. 4.23) depicted the sensorial composite scoring comparison between apple tea wine fermented by two different types of fermentations i.e. fermentation with Saccharomyces cerevisiae var ellipsoideus and natural fermentation. For all the sensory attributes, fermentation with Saccharomyces cerevisiae var ellipsoideus recorded the higher scoring than the naturally fermented apple tea wine except volatile acidity, total acidity, sweetness and astringency. On the basis of rating, apple tea wines prepared from different types of fermentation (with Saccharomyces cerevisiae var ellipsoideus and natural fermentation) falls in the standard category. Figure 4.23 shows the spider web diagram of sensory qualities of apple tea wines prepared from different types of fermentation. 149
SC = Fermentation with Saccharomyces cerevisiae var ellipsoideus NF = Natural fermentation Figure 4.22 Dendrogram of different types of fermentation using various physico-chemical characteristics analysed based on rescaled distance 150
Figure 4.23 Spider web diagram of sensory qualities of apple tea wine fermented by different types of fermentations 151
4.5 EFFECT OF VARIOUS FACTORS ON FERMENTATION BEHAVIOR, PHYSICO-CHEMICAL CHARACTERISTICS AND SENSORY QUALITY CHARACTERISTICS OF APPLE TEA WINE 4.5.1 Standardization of types of sugar sources, nitrogen sources and inocula used for inoculation by using factorial design 4.5.1.1 Physico-chemical characteristics of the musts ameliorated with different sugar sources Physico-chemical characteristics of musts ameliorated with different sugar sources shown in Table 4.23. It was observed that the final TSS of all the must was 20 o B. Significantly highest acidity (0.44 %) was recorded in must ameliorated with apple juice concentrate and lowest (0.25 %) was in must ameliorated with honey which was at par with the must ameliorated with sucrose. In case of the ph, highest ph (4.26) was recorded in must ameliorated with sucrose which was at par with must ameliorated with honey and lowest ph (4.16) was in must ameliorated with apple juice concentrate. Table 4.23 Physico-chemical characteristics of the musts ameliorated with different sugar sources Treatments TSS (ob) Titratable acidity (% malic acid) ph Phenols (mg/l) Reducing Sugars (%) Total Sugars (%) Must of 20 ob ameliorated with sucrose having 4 g tea Must of 20 ob ameliorated with honey having 4 g tea Must of 20 ob CD ameliorated (P=0.05) with apple juice concentrate having 4 g tea 20 NS 20 20 0.26 0.25 0.44 0.04 4.26 589 4.24 566 4.16 663 0.05 15 13.51 14.29 15.63 1.25 18.52 18.52 17.73 NS Among the different musts, highest total phenols content (663 mg/l) was observed in must ameliorated with apple juice concentrate and lowest total phenols content (566 mg/l) was observed in must ameliorated with honey which was closely followed by must 152
ameliorated with sucrose (589 mg/l). Table 4.23 further revealed the reducing and total sugar content of different musts. Perusal of results shows that highest reducing sugar content (15.63 %) were recorded in must ameliorated with apple juice concentrate and lowest was in must ameliorated with sucrose (13.51 %) which was at par with must ameliorated with honey. In case of total sugars, there was no significant difference among the different musts. However, highest total sugars (18.52 %) was observed in must ameliorated with sucrose and must ameliorated with honey and lowest (17.73 %) was in must ameliorated with apple juice concentrate. 4.5.1.2 Fermentability of different musts On the basis of sugar sources The results (Fig. 4.24) depicted the fermentation behaviour of musts ameliorated with different sugar sources irrespective of the nitrogen sources and inocula. In general, at the initial stages (upto 96 hours), the musts of all the different sugar sources witnesses a fast reduction in TSS. Must ameliorated with sucrose recorded the highest reduction in TSS followed by must ameliorated with honey. But after this it changed clearly with the flattening of curve followed by stabilization at 192 hours, when must ameliorated with sucrose recorded the lowest TSS (6.31 ob) and highest (7.89 ob) TSS in the must ameliorated with apple juice concentrate was recorded. A comparison of rate of fermentation (Fig. 4.25) also confirmed the trend discussed earlier. Must ameliorated with sucrose had better fermentation behaviour than other two musts. In confirmation to this, must ameliorated with sucrose had the highest rate of fermentation (1.71) and must ameliorated with apple juice concentrate had the lowest (1.51). Fermentation efficiency of must ameliorated with honey was found the highest (85.16 %) and lowest (80.88 %) was in must ameliorated with sucrose (Fig. 4.26). 153
22 Sucrose (20 ob) Honey (20 ob) Apple juice concentrate (20 ob) 20 18 TSS ob 16 14 12 10 8 6 4 0 48 96 144 192 Fermentation time (hr) Figure 4.24 A comparison of fermentation behaviour of musts ameliorated with different sugar sources Figure 4.25 A comparison of rate of fermentation of musts ameliorated with different sugar sources Figure 4.26 A comparison of fermentation efficiency of musts ameliorated with different sugar sources 154
On the basis of nitrogen sources The results (Fig. 4.27) depicted the fermentation behaviour of musts with different nitrogen sources, irrespective of the sugar sources and inocula. At the initial stages (upto 96 hours), the musts of all the different nitrogen sources showed a fast reduction in TSS. Must with DAHP recorded the highest reduction in TSS followed by must with peptone. But after this, it changed clearly with the flattening of curve followed by stabilization at 192 hours, when must with DAHP recorded the lowest TSS (7.16 ob) and the highest (7.31 ob) TSS in the must with ammonium sulphate was recorded. A comparison of rate of fermentation (Fig. 4.28) also confirmed the trend discussed earlier. Must with DAHP have better fermentation behaviour than other two musts. In confirmation to this, must with DAHP had the highest rate of fermentation (1.61) and must ameliorated with ammonium sulphate and peptone had the lowest (1.59). Fermentation efficiency of must with DAHP was found the highest (87.61 %) and lowest (77.57 %) was in must with ammonium sulphate (Fig. 4.29). On the basis of inocula The results (Fig. 4.30) depicted the fermentation behaviour of musts inoculated with different microorganisms, irrespective of the sugar sources and nitrogen sources. Virtually all the sources of fermentation were comparable. At the initial stages (upto 96 hours), the musts inoculated with different microorganisms showed a fast and equal reduction in TSS. Must inoculated with consortia 1 recorded the highest reduction in TSS followed by must inoculated with Consortia 2. But after this it changed clearly with the flattening of curve followed by stabilization at 192 hours, when must with inoculated with consortia 1 recorded the lowest TSS (7.20 ob) and highest (7.29 ob) TSS in the must inoculated with Saccharomyces cerevisiae var. ellipsoideus was recorded. A comparison of rate of fermentation is shown in Fig. 4.31 and it was observed that all the inocula have the same rate of fermentation (1.59). Fermentation efficiency of must inoculated with Saccharomyces cerevisiae var. ellipsoideus was found the highest (86.70 %) and lowest (80.26 %) was in must inoculated with consortia 2 (Fig. 4.32). 155
22 DAHP (0.1 %) Peptone (0.1 %) Ammonium sulphate (0.1 %) 20 18 TSS ob 16 14 12 10 8 6 0 48 96 144 192 Fermentation time (hr) Figure 4.27 A comparison of fermentation behaviour of musts with different nitrogen sources Figure 4.28 A comparison of rate of fermentation musts with different nitrogen sources Figure 4.29 A comparison of fermentation efficiency of musts with different nitrogen sources 156
22 Saccharomyces cerevisiae var. ellipsoideus (5%) Consortia 1 (5%) Consortia 2 (5%) 20 18 TSS ob 16 14 12 10 8 6 0 48 96 144 192 Fermentation time (hr) Figure 4.30 A comparison of fermentation behaviour of musts inoculated with different microorganisms Figure 4.31 A comparison of rate of fermentation of musts inoculated with different microorganisms Figure 4.32 A comparison of fermentation efficiency of musts inoculated with different microorganisms 157
4.5.1.3 Physico-chemical characteristics of apple tea wines TSS Table 4.24 summarizes the effect of type of sugar, nitrogen sources and micro flora on TSS. It was observed that there were non-significant differences among all the factors and their interaction except sugar sources. Among different type of sugar sources, highest TSS (7.89 ob) was observed in apple tea wine having apple juice concentrate as a sugar source and lowest (6.31 ob) was in apple tea wine having sucrose as a sugar source. Among the different nitrogen sources, the highest (7.31 ob) TSS was observed in apple tea wine having ammonium sulphate as a nitrogen source and lowest (7.16 ob) was in apple tea wine having DAHP as nitrogen source. Must inoculated with Saccharomyces cerevisiae var. ellipsoideus for the preparation of apple tea wine recorded the highest (7.29 ob) TSS and the lowest (7.20 ob) was in must inoculated with consortia 1. Titratable acidity Perusal of the result (Table 4.25) revealed that there was non-significant difference among the all factors and their interaction except sugar and nitrogen sources. Among different type of sugar sources highest titratable acidity (0.79 %) was observed in apple tea wine having apple juice concentrate as a sugar source and lowest (0.56 %) was in apple tea wine having sucrose as a sugar source. Among the different nitrogen sources, highest (0.66 %) titratable acidity was observed in apple tea wine having DAHP as a nitrogen source and the lowest (0.62 %) was in apple tea wine having peptone as a nitrogen source. Must inoculated with Saccharomyces cerevisiae var. ellipsoideus and consortia 2 for the preparation of apple tea wine recorded highest (0.65 %) titratable acidity and lowest (0.64 %) was in must inoculated with consortia 1. ph Table 4.26 summarizes the effect of type of sugar, nitrogen sources and micro flora on ph. It was revealed that there was non-significant difference among the all factors and their interaction except sugar and nitrogen sources. Among different type of sugar sources highest ph (4.02) was observed in apple tea wine having apple juice concentrate as a sugar source and lowest (3.83) was in apple tea wine having sucrose as a 158
Table 4.24 Effect of different types of sugar sources, nitrogen sources and inocula on TSS (ob) of apple tea wine Sucrose 20 ob Sugar sources (S) Honey 20 ob Apple juice concentrate 20 ob Nitrogen Sources (N) DAHP Peptone 6.40 6.40 6.40 Consortia 1 (5 %) 6.20 6.20 Consortia 2 (5 %) 6.20 Mean 6.27 Type of DAHP Peptone 6.40 7.40 7.80 7.60 6.20 6.20 7.40 7.60 6.40 6.40 6.33 7.40 6.33 6.33 7.40 Ammoniu Mean m sulphate inocula (M) DAHP Peptone 7.60 7.80 7.80 7.60 7.53 7.80 7.60 7.60 7.53 7.67 7.60 Ammonium Mean sulphate Mean (Type of Mean inocula) 8.00 7.87 7.29 7.80 8.00 7.87 7.20 7.80 8.00 8.00 7.93 7.27 7.80 7.87 8.00 Ammonium sulphate Saccharomyces cerevisiae var. ellipsoideus (5 %) Mean (Sugar 6.31 Sources) 7.56 7.89 Mean (Nitrogen Sources) 7.16 7.29 7.31 Interaction between nitrogen sources and type of inocula Nitrogen Sources (N) DAHP Peptone Ammonium sulphate Mean (Type of inocula) 7.20 7.33 7.33 7.29 Consortia 1 (5 %) 7.13 7.2 7.27 Consortia 2 (5 %) 7.13 7.33 7.33 Mean (Nitrogen Sources) 7.16 7.29 7.31 Type of inocula (M) Saccharomyces cerevisiae var. ellipsoideus (5 %) CD (P=0.05) 7.20 Sugar Source (S) Nitrogen Source (N) Type of inocula (M) SXN SXM 0.18 NS NS NS NS 7.27 NXM NS SXNXM NS 159
Table 4.25 Effect of different types of sugar sources, nitrogen sources and inocula on titratable acidity (% malic acid) of apple tea wine Sucrose 20 ob Sugar sources (S) Honey 20 ob Apple juice concentrate 20 ob Nitrogen Sources (N) DAHP Peptone 0.57 0.55 0.56 Consortia 1 (5 %) 0.56 0.54 Consortia 2 (5 %) 0.56 Mean 0.57 Type of DAHP Peptone 0.56 0.59 0.61 0.58 0.55 0.55 0.62 0.56 0.54 0.56 0.55 0.62 0.54 0.56 0.61 Ammoniu Mean m sulphate inocula (M) DAHP Peptone 0.59 0.80 0.74 0.58 0.59 0.80 0.57 0.60 0.60 0.58 0.59 Ammonium Mean sulphate Mean (Type of Mean inocula) 0.81 0.78 0.65 0.74 0.82 0.79 0.64 0.79 0.76 0.83 0.79 0.65 0.80 0.75 0.82 Ammonium sulphate Saccharomyces cerevisiae var. ellipsoideus (5 %) Mean (Sugar 0.56 Sources) 0.59 0.79 Mean (Nitrogen Sources) 0.66 0.62 0.65 Interaction between nitrogen sources and type of inocula Nitrogen Sources (N) DAHP Peptone Ammonium sulphate Mean (Type of inocula) 0.65 0.63 0.65 0.65 Consortia 1 (5 %) 0.66 0.61 0.65 Consortia 2 (5 %) 0.66 0.62 0.66 Mean (Nitrogen Sources) 0.66 0.62 0.65 Type of inocula (M) Saccharomyces cerevisiae var. ellipsoideus (5 %) CD (P=0.05) 0.64 Sugar Source (S) Nitrogen Source (N) Type of inocula (M) SXN SXM 0.02 0.02 NS NS NS 0.65 NXM NS SXNXM NS 160
Table 4.26 Effect of different types of sugar sources, nitrogen sources and inocula on ph of apple tea wine Sucrose 20 ob Sugar sources (S) Honey 20 ob Apple juice concentrate 20 ob Nitrogen Sources (N) Type of DAHP Peptone inocula (M) Ammoniu Mean m sulphate DAHP Peptone Ammonium Mean sulphate DAHP Peptone Mean (Type of Ammonium Mean inocula) sulphate Saccharomyces cerevisiae var. 3.81 3.92 3.61 3.78 4.28 4.14 3.71 4.04 4.08 4.16 3.87 4.04 3.95 Consortia 1 (5 %) 3.84 3.98 3.73 3.85 4.06 4.08 3.67 3.94 3.98 4.18 3.89 4.02 3.93 Consortia 2 (5 %) 3.85 3.93 3.84 3.87 4.12 4.07 3.72 3.97 3.99 4.15 3.86 4.00 3.95 Mean 3.83 3.94 3.73 4.15 4.10 3.70 4.02 4.16 3.87 ellipsoideus (5 %) Mean (Sugar Sources) 3.83 3.98 4.02 Mean (Nitrogen 4.00 Sources) 4.07 3.77 Interaction between nitrogen sources and type of inocula Nitrogen Sources (N) Type of DAHP Peptone CD (P=0.05) sulphate Mean (Type of inocula) Ammonium inocula (M) Sugar Source (S) 0.14 Nitrogen Source (N) 0.14 Type of inocula (M) NS 4.06 4.07 3.73 3.95 SXN NS Consortia 1 (5 %) 3.96 4.08 3.76 3.93 SXM NS Consortia 2 (5 %) 3.99 4.05 3.81 3.95 NXM NS Mean (Nitrogen Sources) 4.00 4.07 3.77 SXNXM NS Saccharomyces cerevisiae var. ellipsoideus (5 %) 161
sugar source. Among the different nitrogen sources, highest (4.07) ph was observed in apple tea wine having peptone as nitrogen source and lowest (3.77) was in apple tea wine having ammonium sulphate as a nitrogen source. Must inoculated with Saccharomyces cerevisiae var. ellipsoideus and consortia 2 for the preparation of apple tea wine recorded highest (3.95) ph and lowest (3.93) was in must inoculated with consortia 1. Reducing sugars The data on the effect of type of sugar, nitrogen sources and microflora on reducing sugars presented in Table 4.27. It was observed that there was significant difference among the all factors and their interaction except nitrogen sources. Among different type of sugar sources highest reducing sugars (691 mg/100 ml) was observed in apple tea wine having honey as a sugar source and lowest (314 mg/100 ml) was in apple tea wine having sucrose as a sugar source. Among the different nitrogen sources, highest (544 mg/100 ml) reducing sugars was observed in apple tea wine having peptone as nitrogen source and lowest (530 mg/100 ml) was in apple tea wine having ammonium sulphate as a nitrogen source. Must inoculated with Saccharomyces cerevisiae var. ellipsoideus for the preparation of apple tea wine recorded highest (563 mg/100 ml) reducing sugars and lowest (526 mg/100 ml) was in must inoculated with consortia 1 and must inoculated with consortia 2. Total sugars Perusal of the result (Table 4.28) revealed that there was non-significant difference among the nitrogen source and microorganisms except sugar sources which show the significant difference among them. All the interactions of these factors were statistically significant. Among different type of sugar sources highest total sugars (2.78 %) was observed in apple tea wine having honey as a sugar source and lowest (1.27 %) was in apple tea wine having sucrose as a sugar source. Among the different nitrogen sources, highest (2.11 %) total sugars was observed in apple tea wine having DAHP as nitrogen source and lowest (2.09 %) was in apple tea wine having peptone and ammonium sulphate as a nitrogen source. Must inoculated with consortia 2 for the preparation of apple tea wine recorded highest (2.12 %) total sugars and lowest (2.08 %) was in must inoculated with Saccharomyces cerevisiae var. ellipsoideus. 162
Table 4.27 Effect of different types of sugar sources, nitrogen sources and inocula on reducing sugars (mg/100 ml) of apple tea wine Sucrose 20 ob Sugar sources (S) Honey 20 ob Apple juice concentrate 20 ob Nitrogen Sources (N) DAHP Peptone 290 326 332 Consortia 1 (5 %) 282 324 Consortia 2 (5 %) 297 Mean 290 Type of DAHP Peptone 316 734 754 642 319 308 792 670 335 324 319 700 328 325 742 inocula (M) Ammoniu Mean m sulphate DAHP Peptone 710 690 677 591 684 547 620 715 679 682 649 Ammonium Mean sulphate Mean (Type of Mean inocula) 617 661 563 614 599 586 526 537 578 627 580 526 591 623 614 Ammonium sulphate Saccharomyces cerevisiae var. ellipsoideus (5 %) Mean (Sugar 314 Sources) Mean (Nitrogen Sources) 541 544 691 609 530 Interaction between nitrogen sources and type of inocula Nitrogen Sources (N) DAHP Peptone Ammonium sulphate Mean (Type of inocula) 571 586 530 563 Consortia 1 (5 %) 540 536 503 Consortia 2 (5 %) 511 511 555 Mean (Nitrogen Sources) 541 544 529 Type of inocula (M) Saccharomyces cerevisiae var. ellipsoideus (5 %) CD (P=0.05) 526 Sugar Source (S) Nitrogen Source (N) Type of inocula (M) SXN SXM 19 NS 19 33 33 526 NXM 33 SXNXM 58 163
Table 4.28 Effect of different types of sugar sources, nitrogen sources and inocula on total Sugars (%) of apple tea wine Sucrose 20 ob Sugar sources (S) Nitrogen Sources (N) Honey 20 ob Apple juice concentrate 20 ob Mean (Type of inocula) 2.46 2.37 2.08 2.53 2.17 2.22 2.10 1.96 2.23 2.23 2.14 2.12 2.17 2.28 2.29 Peptone Ammoniu m sulphate Mean DAHP Saccharomyces cerevisiae var. ellipsoideus (5 %) 1.14 1.25 1.23 1.21 2.49 2.56 2.96 2.67 2.56 2.09 Consortia 1 (5 %) 1.25 1.21 1.29 1.25 3.05 2.52 2.88 2.82 1.98 Consortia 2 (5 %) 1.40 1.23 1.45 1.36 3.18 3.26 2.12 2.85 Mean Mean (Sugar Sources) Mean (Nitrogen Sources) 1.26 1.23 1.32 2.91 2.78 2.65 Type of inocula (M) 1.27 2.11 2.09 Ammonium Mean Peptone sulphate Mean DAHP DAHP Ammonium Peptone sulphate 2.78 2.25 2.09 Interaction between nitrogen sources and type of inocula Nitrogen Sources (N) DAHP Peptone Ammonium sulphate Mean (Type of inocula) 2.07 1.96 2.22 2.08 Consortia 1 (5 %) 2.09 2.09 2.11 Consortia 2 (5 %) 2.18 2.24 1.94 Mean (Nitrogen Sources) 2.11 2.10 2.09 Type of inocula (M) Saccharomyces cerevisiae var. ellipsoideus (5 %) CD (P=0.05) 2.10 Sugar Source (S) Nitrogen Source (N) Type of inocula (M) SXN SXM 0.05 NS NS 0.08 0.08 2.12 NXM 0.08 SXNXM 0.14 164
Ethanol There was significant difference among the sugar source, nitrogen source, microorganisms and interaction between sugar source and nitrogen source whereas among the other interactions there was non-significant difference (Table 4.29). Among different type of sugar sources significantly highest ethanol (8.93 %) was observed in apple tea wine having sucrose as a sugar source and lowest (8.33 %) was in apple tea wine having apple juice concentrate as a sugar source. Among the different nitrogen sources, significantly highest (9.05 %) ethanol was observed in apple tea wine having DAHP as nitrogen source and lowest (8.02 %) was in apple tea wine having ammonium sulphate as a nitrogen source. Must inoculated with Saccharomyces cerevisiae var. ellipsoideus for the preparation of apple tea wine recorded significantly highest (8.98 %) ethanol and lowest (8.28 %) was in must inoculated with consortia 2. Residual sulphur dioxide Table 4.30 summarizes the effect of type of sugar, nitrogen sources and micro flora on residual sulphur dioxide. It was observed that there was significant difference among all the factors and their interaction except interaction between sugar sources and microorganisms. Among different type of sugar sources highest residual sulphur dioxide (60.62 ppm) was observed in apple tea wine having apple juice concentrate as a sugar source and lowest (37.69 ppm) was in apple tea wine having sucrose as a sugar source. Among the different nitrogen sources, highest (48.71 ppm) residual sulphur dioxide was observed in apple tea wine having ammonium sulphate as a nitrogen source and lowest (44.98 ppm) was in apple tea wine having DAHP as nitrogen source which was at par with apple tea wine having peptone as nitrogen source. Must inoculated with consortia 1 for the preparation of apple tea wine recorded highest (48.18 ppm) residual sulphur dioxide which was at par with must inoculated with consortia 2 for the preparation of apple tea wine and lowest (43.56 ppm) was in must inoculated with Saccharomyces cerevisiae var. ellipsoideus. 165
Table 4.29 Effect of different types of sugar sources, nitrogen sources and inocula on ethanol (%) of apple tea wine Sucrose 20 ob Sugar sources (S) Honey 20 ob Apple juice concentrate 20 ob Nitrogen Sources (N) Mean 8.49 8.66 8.98 8.22 7.99 8.25 8.60 8.28 8.09 7.86 8.08 8.28 8.57 8.30 8.11 Peptone Ammoniu m sulphate Mean DAHP Saccharomyces cerevisiae var. ellipsoideus (5 %) 9.73 9.71 8.50 9.31 9.44 9.26 8.18 8.96 8.89 8.59 Consortia 1 (5 %) 9.55 9.39 8.18 9.04 9.13 8.64 7.73 8.50 8.55 Consortia 2 (5 %) 8.85 8.77 7.70 8.44 9.04 8.39 7.55 8.33 Mean 9.37 9.29 8.13 9.21 8.76 7.82 Type of inocula (M) Mean (Sugar Sources) Mean (Nitrogen Sources) 8.93 9.05 8.78 Ammonium Mean Peptone sulphate Mean (Type of inocula) DAHP DAHP Ammonium Peptone sulphate 8.60 8.33 8.02 Interaction between nitrogen sources and type of inocula Nitrogen Sources (N) DAHP Peptone Ammonium sulphate Mean (Type of inocula) 9.35 9.08 8.73 9.05 Consortia 1 (5 %) 9.19 8.75 8.42 Consortia 2 (5 %) 8.39 7.96 7.70 Mean (Nitrogen Sources) 8.98 8.60 8.28 Type of inocula (M) Saccharomyces cerevisiae var. ellipsoideus (5 %) 166 CD (P=0.05) 8.79 Sugar Source (S) Nitrogen Source (N) Type of inocula (M) SXN SXM 0.27 0.27 0.27 0.47 NS 8.02 NXM NS SXNXM NS
Table 4.30 Effect of different types of sugar sources, nitrogen sources and inocula on residual sulphur dioxide (ppm) of apple tea wine Sucrose 20 ob Sugar sources (S) Nitrogen Sources (N) Type of DAHP Peptone Ammoniu m sulphate Mean DAHP inocula (M) Saccharomyces cerevisiae var. ellipsoideus (5 %) Honey 20 ob Apple juice concentrate 20 ob Ammonium Mean Peptone sulphate DAHP Ammonium Peptone sulphate Mean Mean (Type of inocula) 32.00 35.20 38.40 35.20 38.40 40.00 35.20 37.87 62.40 51.20 59.20 57.60 43.56 Consortia 1 (5 %) 38.40 41.60 40.00 40.00 41.60 36.80 48.00 42.13 54.40 64.00 68.80 62.40 48.18 Consortia 2 (5 %) 40.00 38.40 35.20 37.87 40.00 38.40 46.40 41.60 57.60 60.80 67.20 61.87 47.11 Mean Mean (Sugar Sources) Mean (Nitrogen Sources) 36.80 38.40 37.87 40.00 38.40 43.20 58.13 58.67 65.07 37.69 44.98 45.16 40.53 60.62 48.71 Interaction between nitrogen sources and type of inocula Nitrogen Sources (N) DAHP Peptone Ammonium sulphate Mean (Type of inocula) 44.27 42.13 44.27 43.56 Consortia 1 (5 %) 44.80 47.47 52.27 Consortia 2 (5 %) 45.87 45.87 49.60 Mean (Nitrogen Sources) 44.98 45.16 48.71 Type of inocula (M) Saccharomyces cerevisiae var. ellipsoideus (5 %) CD (P=0.05) 48.18 Sugar Source (S) Nitrogen Source (N) Type of inocula (M) SXN SXM 1.74 1.74 1.74 3.02 NS 47.11 NXM 3.02 SXNXM 5.23 167
Volatile acidity Perusal of the result (Table 4.31) revealed that that there was significant difference among all the factors and their interaction except nitrogen sources and interaction between nitrogen sources and microorganisms. Among different type of sugar sources highest volatile acidity (0.033 %) was observed in apple tea wine having honey as a sugar source and lowest (0.026 %) was in apple tea wine having sucrose as a sugar source. Among the different nitrogen sources, highest (0.031 %) volatile acidity was observed in apple tea wine having ammonium sulphate as a nitrogen source and lowest (0.029 %) was in apple tea wine having DAHP as nitrogen source. Must inoculated with consortia 2 for the preparation of apple tea wine recorded highest (0.033 %) volatile acidity and lowest (0.027 %) was in must inoculated with Saccharomyces cerevisiae var. ellipsoideus. Higher alcohols Table 4.32 summarizes the effect of type of sugar, nitrogen sources and micro flora on higher alcohols. It was observed that there was significant difference among all the factors and their interaction except types of microorganisms used for inoculation. Among different type of sugar sources highest higher alcohols (330 mg/l) was observed in apple tea wine having honey as a sugar source and lowest (171 mg/l) was in apple tea wine having sucrose as a sugar source. Among the different nitrogen sources, highest (284 mg/l) higher alcohols was observed in apple tea wine having ammonium sulphate as a nitrogen source and lowest (241 mg/l) was in apple tea wine having DAHP as nitrogen source and apple tea wine having peptone as nitrogen source. Must inoculated with Saccharomyces cerevisiae var. ellipsoideus for the preparation of apple tea wine recorded highest (257 mg/l) higher alcohols and lowest (253 mg/l) was in must inoculated with consortia 2. Colour Results presented in Table 4.33 revealed that there was significant difference among the sugar source, nitrogen source, microorganisms and interaction between sugar source and nitrogen source whereas among the other interactions there was non- 168
Table 4.31 Effect of different types of sugar sources, nitrogen sources and inocula on volatile acidity (% acetic acid) of apple tea wine Sucrose 20 ob Sugar sources (S) Nitrogen Sources (N) Honey 20 ob Apple juice concentrate 20 ob Mean (Type of inocula) 0.029 0.028 0.027 0.029 0.031 0.032 0.030 0.037 0.031 0.035 0.034 0.033 0.034 0.029 0.032 Peptone Ammoniu m sulphate Mean DAHP Saccharomyces cerevisiae var. ellipsoideus (5 %) 0.018 0.020 0.026 0.021 0.029 0.035 0.027 0.030 0.029 0.026 Consortia 1 (5 %) 0.019 0.025 0.032 0.025 0.034 0.036 0.029 0.033 0.035 Consortia 2 (5 %) 0.022 0.035 0.036 0.031 0.035 0.037 0.031 0.034 Mean Mean (Sugar Sources) Mean (Nitrogen Sources) 0.020 0.027 0.031 0.033 0.036 0.029 Type of inocula (M) 0.026 0.029 0.030 Ammonium Mean Peptone sulphate Mean DAHP DAHP Ammonium Peptone sulphate 0.033 0.031 0.031 Interaction between nitrogen sources and type of inocula Nitrogen Sources (N) DAHP Peptone Ammonium sulphate Mean (Type of inocula) 0.025 0.027 0.027 0.027 Consortia 1 (5 %) 0.029 0.03 0.031 Consortia 2 (5 %) 0.031 0.034 0.034 Mean (Nitrogen Sources) 0.029 0.03 0.031 Type of inocula (M) Saccharomyces cerevisiae var. ellipsoideus (5 %) CD (P=0.05) 0.03 Sugar Source (S) Nitrogen Source (N) Type of inocula (M) SXN SXM 0.001 NS 0.001 0.002 0.002 0.033 NXM NS SXNXM 0.003 169
Table 4.32 Effect of different types of sugar sources, nitrogen sources and inocula on higher alcohols (mg/l) of apple tea wine Sucrose 20 ob Sugar sources (S) Nitrogen Sources (N) Honey 20 ob Apple juice concentrate 20 ob Mean (Type of inocula) 337 263 257 239 354 272 256 224 227 331 261 253 220 235 341 Peptone Ammoniu m sulphate Mean DAHP Saccharomyces cerevisiae var. ellipsoideus (5 %) 172 162 173 169 336 345 334 338 214 239 Consortia 1 (5 %) 173 170 184 176 316 302 345 321 222 Consortia 2 (5 %) 172 166 165 168 338 319 336 331 Mean Mean (Sugar Sources) Mean (Nitrogen Sources) 173 166 174 330 322 338 Type of inocula (M) 171 241 241 Ammonium Mean Peptone sulphate Mean DAHP DAHP Ammonium Peptone sulphate 330 265 284 Interaction between nitrogen sources and type of inocula Nitrogen Sources (N) DAHP Peptone Ammonium sulphate Mean (Type of inocula) 241 249 281 257 Consortia 1 (5 %) 237 237 294 Consortia 2 (5 %) 244 238 277 Mean (Nitrogen Sources) 241 241 284 Type of inocula (M) Saccharomyces cerevisiae var. ellipsoideus (5 %) CD (P=0.05) 2 2 256 Sugar Source (S) Nitrogen Source (N) Type of inocula (M) SXN SXM 253 NXM 4 SXNXM 8 170 NS 4 4
Table 4.33 Effect of different types of sugar sources, nitrogen sources and inocula on colour (OD 440 nm) of apple tea wine Sucrose 20 ob Sugar sources (S) Nitrogen Sources (N) Honey 20 ob Apple juice concentrate 20 ob Mean (Type of inocula) 2.87 3.00 2.90 3.01 2.96 2.99 2.81 3.80 3.14 2.93 3.29 2.89 3.24 3.12 2.92 Peptone Ammoniu m sulphate Mean DAHP Saccharomyces cerevisiae var. ellipsoideus (5 %) 2.87 3.28 2.64 2.93 2.57 2.98 2.73 2.76 2.91 3.22 Consortia 1 (5 %) 2.74 3.01 2.61 2.79 2.70 2.86 2.37 2.64 3.01 Consortia 2 (5 %) 2.77 2.96 2.59 2.77 2.73 2.79 2.34 2.62 Mean Mean (Sugar Sources) Mean (Nitrogen Sources) 2.79 3.09 2.61 2.67 2.87 2.48 Type of inocula (M) 2.83 2.90 3.03 Ammonium Mean Peptone sulphate Mean DAHP DAHP Ammonium Peptone sulphate 2.67 3.09 2.67 Interaction between nitrogen sources and type of inocula Nitrogen Sources (N) DAHP Peptone Ammonium sulphate Mean (Type of inocula) 2.79 3.16 2.75 2.90 Consortia 1 (5 %) 2.82 2.96 2.65 Consortia 2 (5 %) 3.10 2.96 2.62 Mean (Nitrogen Sources) 2.90 3.03 2.67 Type of inocula (M) Saccharomyces cerevisiae var. ellipsoideus (5 %) CD (P=0.05) 2.81 Sugar Source (S) Nitrogen Source (N) Type of inocula (M) SXN SXM 0.02 0.02 0.02 0.03 0.03 2.89 NXM 0.03 SXNXM 0.05 171
significant difference. Among different type of sugar sources significantly highest OD for colour (3.09) was observed in apple tea wine having apple juice concentrate as a sugar source and lowest (2.67) was in apple tea wine having honey as a sugar source. Among the different nitrogen sources, highest (3.03) OD for colour was observed in apple tea wine having peptone as nitrogen source and lowest (2.67) was in apple tea wine having ammonium sulphate as a nitrogen source. Must inoculated with Saccharomyces cerevisiae var. ellipsoideus for the preparation of apple tea wine recorded highest (2.90) OD for colour which was at par with the must inoculated with consortia 2 for the preparation of apple tea wine and lowest (2.81) was in must inoculated with consortia 1. Total phenols Perusal of the result (Table 4.34) revealed that there was non-significant difference among the all factors and their interaction except sugar and nitrogen sources. Among different type of sugar sources highest total phenols (497 mg/l) was observed in apple tea wine having apple juice concentrate as a sugar source and lowest (426 mg/l) was in apple tea wine having sucrose as a sugar source. Among the different nitrogen sources, highest (480 mg/l) total phenols was observed in apple tea wine having peptone as nitrogen source and lowest (446 mg/l) was in apple tea wine having DAHP as a nitrogen source which is at par with apple tea wine having ammonium sulphate as a nitrogen source. Must inoculated with Saccharomyces cerevisiae var. ellipsoideus for the preparation of apple tea wine recorded highest (463 mg/l) total phenols and lowest (451 mg/l) was in must inoculated with consortia 1. Caffeine Table 4.35 summarizes the effect of type of sugar, nitrogen sources and micro flora on caffeine. It was evident that there was non-significant difference among all the factors and their interaction except sugar sources and interaction between sugar sources and nitrogen sources. Among different type of sugar sources highest caffeine (752 ppm) was observed in apple tea wine having apple juice concentrate as a sugar source and lowest (718 ppm) was in apple tea wine having sucrose as a sugar source. Among the different nitrogen sources, highest (738 ppm) caffeine was observed in apple tea wine 172
Table 4.34 Effect of different types of sugar sources, nitrogen sources and inocula on total phenols (mg/l) of apple tea wine Sucrose 20 ob Sugar sources (S) Nitrogen Sources (N) Honey 20 ob Apple juice concentrate 20 ob Mean (Type of inocula) 495 499 463 511 470 485 451 500 545 476 507 461 484 528 480 Peptone Ammoniu m sulphate Mean DAHP Saccharomyces cerevisiae var. ellipsoideus (5 %) 442 434 407 428 419 497 468 462 477 527 Consortia 1 (5 %) 425 435 419 426 441 445 434 440 476 Consortia 2 (5 %) 418 434 423 425 418 493 439 450 Mean Mean (Sugar Sources) Mean (Nitrogen Sources) 428 434 417 426 479 447 inocula (M) 426 446 480 Ammonium Mean Peptone sulphate Mean DAHP Type of DAHP Ammonium Peptone sulphate 450 497 448 Interaction between nitrogen sources and type of inocula Nitrogen Sources (N) DAHP Peptone Ammonium sulphate Mean (Type of inocula) 446 486 457 463 Consortia 1 (5 %) 447 464 441 Consortia 2 (5 %) 445 491 446 Mean (Nitrogen Sources) 446 480 448 Type of inocula (M) Saccharomyces cerevisiae var. ellipsoideus (5 %) CD (P=0.05) 451 Sugar Source (S) Nitrogen Source (N) Type of inocula (M) SXN SXM 17 17 NS NS NS 461 NXM NS SXNXM NS 173
Table 4.35 Effect of different types of sugar sources, nitrogen sources and inocula on caffeine (ppm) of apple tea wine Sucrose 20 ob Sugar sources (S) Nitrogen Sources (N) Honey 20 ob Apple juice concentrate 20 ob Mean (Type of inocula) 749 763 738 742 751 750 730 739 741 749 743 740 768 738 749 Peptone Ammoniu m sulphate Mean DAHP Saccharomyces cerevisiae var. ellipsoideus (5 %) 725 730 711 722 713 737 734 728 807 732 Consortia 1 (5 %) 720 723 663 702 718 734 760 737 757 Consortia 2 (5 %) 721 724 747 731 738 737 760 745 Mean Mean (Sugar Sources) Mean (Nitrogen Sources) 722 726 707 723 736 751 inocula (M) 718 738 733 Ammonium Mean Peptone sulphate Mean DAHP Type of DAHP Ammonium Peptone sulphate 737 752 736 Interaction between nitrogen sources and type of inocula Nitrogen Sources (N) DAHP Peptone Ammonium sulphate Mean (Type of inocula) 749 733 731 738 Consortia 1 (5 %) 732 733 724 Consortia 2 (5 %) 733 734 752 Mean (Nitrogen Sources) 738 733 736 Type of inocula (M) Saccharomyces cerevisiae var. ellipsoideus (5 %) CD (P=0.05) 15 NS NS 730 Sugar Source (S) Nitrogen Source (N) Type of inocula (M) SXN SXM 740 NXM NS SXNXM NS 174 26 NS
having DAHP as a nitrogen source and lowest (733 ppm) was in apple tea wine having peptone as nitrogen source. Must inoculated with consortia 2 for the preparation of apple tea wine recorded highest (740 ppm) caffeine and lowest (730 ppm) was in must inoculated with consortia 1. Antioxidant activity Perusal of the result (Table 4.36) revealed that there was non-significant difference among the all factors and their interaction except sugar and interaction between sugar sources and nitrogen sources. Among different type of sugar sources highest antioxidant activity (81.79 %) was observed in apple tea wine having honey as a sugar source which was at par with apple tea wine having sucrose as a sugar source and lowest (78.31 %) was in apple tea wine having apple juice concentrate as a sugar source. Among the different nitrogen sources, highest (80.61 %) antioxidant activity was observed in apple tea wine having peptone as nitrogen source and lowest (80.31 %) was in apple tea wine having DAHP as a nitrogen source. Must inoculated with consortia 1 for the preparation of apple tea wine recorded highest (80.75 %) antioxidant activity and lowest (80.26 %) was in must inoculated with Saccharomyces cerevisiae var. ellipsoideus. Cluster analysis of the different treatments The data obtained from physico-chemical analysis of apple tea wine was analysed using cluster analysis with rescaled distance cluster analysis. The dendrogram representation of the different treatments of the apple tea wine using physico-chemical characteristics showed in Fig. 4.33. Most of the clustering was on the basis of sugar source but could not classify on the basis of nitrogen source and innocula, which shows that innocula did not produce any characteristics in wine which can be distinguish neither nitrogen source influence the fermentation behavior or characteristics of wine to a distinctiveness. 175
Table 4.36 Effect of different types of sugar sources, nitrogen sources and inocula on antioxidant activity (%) of apple tea wine Sucrose 20 ob Sugar sources (S) Nitrogen Sources (N) Honey 20 ob Apple juice concentrate 20 ob Mean (Type of inocula) 76.62 77.94 80.26 79.12 77.45 78.91 80.75 78.50 78.29 77.45 78.08 80.44 78.92 78.84 77.17 Peptone Ammoniu m sulphate Mean DAHP Saccharomyces cerevisiae var. ellipsoideus (5 %) 79.54 81.42 82.05 81.00 81.42 81.63 82.46 81.84 78.08 79.12 Consortia 1 (5 %) 81.21 81.63 81.84 81.56 81.63 81.42 82.25 81.77 80.17 Consortia 2 (5 %) 80.79 81.42 82.25 81.49 81.42 81.42 82.46 81.77 Mean Mean (Sugar Sources) Mean (Nitrogen Sources) 80.51 81.49 82.05 81.49 81.49 82.39 Type of inocula (M) 81.35 80.31 80.61 Ammonium Mean Peptone sulphate Mean DAHP DAHP Ammonium Peptone sulphate 81.79 78.31 80.54 Interaction between nitrogen sources and type of inocula Nitrogen Sources (N) DAHP Peptone Ammonium sulphate Mean (Type of inocula) 79.68 80.72 80.38 80.26 Consortia 1 (5 %) 81.00 80.72 80.51 Consortia 2 (5 %) 80.24 80.38 80.72 Mean (Nitrogen Sources) 80.31 80.61 80.54 Type of inocula (M) Saccharomyces cerevisiae var. ellipsoideus (5 %) CD (P=0.05) 0.86 NS NS 80.75 Sugar Source (S) Nitrogen Source (N) Type of inocula (M) SXN SXM 80.44 NXM NS SXNXM NS 176 1.48 NS
Figure 4.33 Dendrogram of different treatments of apple tea wine using various physico-chemical characteristics analysed based on rescaled distance 4.5.1.4 Sensory characteristics of apple tea wines Colour Table 4.37 summarizes the effect of type of sugar, nitrogen sources and micro flora on colour. It was observed that there was significant difference 177
among the type of sugar sources and microorganisms, whereas, it was nonsignificant in case of nitrogen sources and interactions. Among different type of sugar sources highest score for colour (7.83) was observed in apple tea wine having apple juice concentrate as a sugar source and lowest (6.94) was in apple tea wine having honey as a sugar source which was at par with apple tea wine having sucrose as a sugar source. Among the different nitrogen sources, highest (7.45) score for colour was observed in apple tea wine having ammonium sulphate as a nitrogen source and lowest (7.06) was in apple tea wine having peptone as nitrogen source. Must inoculated with Saccharomyces cerevisiae var. ellipsoideus for the preparation of apple tea wine recorded highest (7.86) score for colour and lowest (6.99) was in must inoculated with consortia 2 which was at par with must inoculated with consortia 1. Taste Perusal of the result (Table 4.38) revealed that there was non-significant difference among all the factors and their interactions except type of microorganisms which was significant. Among different type of sugar sources highest score for taste (7.39) was observed in apple tea wine having apple juice concentrate as a sugar source and lowest (7.03) was in apple tea wine having honey as a sugar source. Among the different nitrogen sources, highest (7.21) score for taste was observed in apple tea wine having peptone as a nitrogen source and lowest (7.13) was in apple tea wine having ammonium sulphate as nitrogen source. Must inoculated with Saccharomyces cerevisiae var. ellipsoideus for the preparation of apple tea wine recorded highest (7.54) score for taste which was at par with must inoculated with consortia 1 and lowest (6.76) was in must inoculated with consortia 2. Aroma Table 4.39 summarizes the effect of type of sugar, nitrogen sources and micro flora on aroma. It was revealed that there was non-significant difference 178
Table 4.37 Effect of different types of sugar sources, nitrogen sources and inocula on colour of apple tea wine Sucrose 20 ob Sugar sources (S) Nitrogen Sources (N) Honey 20 ob Apple juice concentrate 20 ob Mean (Type of inocula) 8.00 8.44 7.86 7.50 7.67 7.56 7.03 7.83 7.17 7.50 7.50 6.99 8.06 7.72 7.72 Peptone Ammoniu m sulphate Mean DAHP Saccharomyces cerevisiae var. ellipsoideus (5 %) 7.77 7.43 7.43 7.54 7.70 7.70 7.37 7.59 8.83 8.50 Consortia 1 (5 %) 6.43 6.43 7.43 6.77 6.37 6.70 7.20 6.76 7.50 Consortia 2 (5 %) 7.43 6.10 7.43 6.99 6.37 6.03 7.03 6.48 Mean Mean (Sugar Sources) Mean (Nitrogen Sources) 7.21 6.66 7.43 6.81 6.81 7.20 Type of inocula (M) 7.10 7.36 7.06 Ammonium Mean Peptone sulphate Mean DAHP DAHP Ammonium Peptone sulphate 6.94 7.83 7.45 Interaction between nitrogen sources and type of inocula Nitrogen Sources (N) DAHP Peptone Ammonium sulphate Mean (Type of inocula) 8.10 7.88 7.60 7.86 Consortia 1 (5 %) 6.77 6.88 7.43 Consortia 2 (5 %) 7.21 6.43 7.32 Mean (Nitrogen Sources) 7.36 7.06 7.45 Type of inocula (M) Saccharomyces cerevisiae var. ellipsoideus (5 %) CD (P=0.05) 0.45 NS 7.03 Sugar Source (S) Nitrogen Source (N) Type of inocula (M) SXN SXM 6.99 NXM NS SXNXM NS 0.45 NS NS Rating: 9: Like extremely, 8: Like very much, 7: Like moderately, 6: Like slightly, 5: Neither like nor dislike, 4: Dislike slightly, 3: Dislike moderately, 2: Dislike very much, 1: Dislike extremely 179
Table 4.38 Effect of different types of sugar sources, nitrogen sources and inocula on taste of apple tea wine Sucrose 20 ob Sugar sources (S) Nitrogen Sources (N) Honey 20 ob Apple juice concentrate 20 ob Mean 7.17 7.94 7.54 7.50 7.23 7.41 7.22 6.83 6.83 6.73 6.80 6.76 7.61 7.50 7.04 Peptone Ammoniu m sulphate Mean DAHP Saccharomyces cerevisiae var. ellipsoideus (5 %) 6.77 7.43 7.77 7.32 7.37 7.03 7.70 7.37 8.50 8.17 Consortia 1 (5 %) 7.10 7.10 7.10 7.10 7.03 7.37 7.03 7.14 7.50 Consortia 2 (5 %) 7.10 6.77 6.77 6.88 6.37 6.70 6.70 6.59 Mean Mean (Sugar Sources) Mean (Nitrogen Sources) 6.99 7.10 7.21 6.92 7.03 7.14 Type of inocula (M) 7.10 7.17 7.21 Ammonium Mean Peptone sulphate Mean (Type of inocula) DAHP DAHP Ammonium Peptone sulphate 7.03 7.39 7.13 Interaction between nitrogen sources and type of inocula Nitrogen Sources (N) DAHP Peptone Ammonium sulphate Mean (Type of inocula) 7.54 7.54 7.54 7.54 Consortia 1 (5 %) 7.21 7.32 7.12 Consortia 2 (5 %) 6.77 6.77 6.73 Mean (Nitrogen Sources) 7.17 7.21 7.13 Type of inocula (M) Saccharomyces cerevisiae var. ellipsoideus (5 %) CD (P=0.05) NS NS 7.22 Sugar Source (S) Nitrogen Source (N) Type of inocula (M) SXN SXM 6.76 NXM NS SXNXM NS 0.49 NS NS Rating: 9: Like extremely, 8: Like very much, 7: Like moderately, 6: Like slightly, 5: Neither like nor dislike, 4: Dislike slightly, 3: Dislike moderately, 2: Dislike very much, 1: Dislike extremely 180
among the all factors and their interaction except nitrogen sources and types of microorganisms. Among different type of sugar sources highest score for aroma (7.59) was observed in apple tea wine having apple juice concentrate as a sugar source and lowest (7.29) was in apple tea wine having honey as a sugar source. Among the different nitrogen sources, highest (7.69) score for aroma was observed in apple tea wine having DAHP as a nitrogen source which was at par with apple tea wine having peptone as a nitrogen source and lowest (7.12) was in apple tea wine having ammonium sulphate as nitrogen source. Must inoculated with Saccharomyces cerevisiae var. ellipsoideus for the preparation of apple tea wine recorded highest (7.95) score for aroma and lowest (7.01) was in must inoculated with and consortia 2 which was at par with consortia 1. Bitterness The data on the effect of type of sugar, nitrogen sources and micro flora on bitterness is presented in Table 4.40. It was observed that there was nonsignificant difference among all the factors and their interactions except type of microorganisms which was significant. Among different type of sugar sources highest score for bitterness (7.14) was observed in apple tea wine having sucrose as a sugar source and lowest (6.96) was in apple tea wine having honey as a sugar source. Among the different nitrogen sources, highest (7.10) score for bitterness was observed in apple tea wine having DAHP as a nitrogen source and lowest (7.03) was in apple tea wine having peptone as nitrogen source. Must inoculated with Saccharomyces cerevisiae var. ellipsoideus for the preparation of apple tea wine recorded highest (7.58) score for bitterness and lowest (6.51) was in must inoculated with consortia 2. Overall acceptability Perusal of the result (Table 4.41) revealed that there was non-significant difference among all the factors and their interactions except type of microorganisms which was significant. Highest score for overall acceptability (7.44) was observed in apple tea wine having apple juice concentrate as a sugar source and lowest (7.00) was in apple tea wine having honey as a sugar source. 181
Table 4.39 Effect of different types of sugar sources, nitrogen sources and inocula on aroma of apple tea wine Sucrose 20 ob Sugar sources (S) Nitrogen Sources (N) Honey 20 ob Apple juice concentrate 20 ob Mean (Type of inocula) 7.17 8.17 7.95 7.83 7.17 7.61 7.43 7.17 7.17 6.67 7.00 7.01 7.94 7.83 7.00 Peptone Ammoniu m sulphate Mean DAHP Saccharomyces cerevisiae var. ellipsoideus (5 %) 8.10 8.10 7.77 7.99 7.70 7.70 7.70 7.70 8.83 8.50 Consortia 1 (5 %) 7.77 7.43 7.10 7.43 7.37 7.37 7.03 7.26 7.83 Consortia 2 (5 %) 7.43 7.10 6.77 7.10 7.03 7.03 6.70 6.92 Mean Mean (Sugar Sources) Mean (Nitrogen Sources) 7.77 7.54 7.21 7.37 7.37 7.14 Type of inocula (M) 7.51 7.69 7.58 Ammonium Mean Peptone sulphate Mean DAHP DAHP Ammonium Peptone sulphate 7.29 7.59 7.12 Interaction between nitrogen sources and type of inocula Nitrogen Sources (N) DAHP Peptone Ammonium sulphate Mean (Type of inocula) 8.21 8.10 7.54 7.95 Consortia 1 (5 %) 7.66 7.54 7.10 Consortia 2 (5 %) 7.21 7.10 6.71 Type of inocula (M) Saccharomyces cerevisiae var. ellipsoideus (5 %) CD (P=0.05) 7.43 Sugar Source (S) Nitrogen Source (N) Type of inocula (M) SXN SXM NS 0.43 0.43 NS NS 7.01 NXM NS SXNXM NS Mean (Nitrogen Sources) 7.69 7.58 7.12 Rating: 9: Like extremely, 8: Like very much, 7: Like moderately, 6: Like slightly, 5: Neither like nor dislike, 4: Dislike slightly, 3: Dislike moderately, 2: Dislike very much, 1: Dislike extremely 182
Table 4.40 Effect of different types of sugar sources, nitrogen sources and inocula on bitterness of apple tea wine Sucrose 20 ob Sugar sources (S) Nitrogen Sources (N) Honey 20 ob Apple juice concentrate 20 ob Mean (Type of inocula) 7.50 7.72 7.58 7.17 7.17 7.17 7.10 6.17 6.17 6.83 6.39 6.51 7.06 7.06 7.17 Peptone Ammoniu m sulphate Mean DAHP Saccharomyces cerevisiae var. ellipsoideus (5 %) 7.77 7.43 7.77 7.66 7.37 7.03 7.70 7.37 7.83 7.83 Consortia 1 (5 %) 7.43 7.10 6.77 7.10 7.03 7.37 6.70 7.03 7.17 Consortia 2 (5 %) 6.77 6.77 6.43 6.66 6.37 6.70 6.37 6.48 Mean Mean (Sugar Sources) Mean (Nitrogen Sources) 7.32 7.10 6.99 6.92 7.03 6.92 Type of inocula (M) 7.14 7.10 7.06 Ammonium Mean Peptone sulphate Mean DAHP DAHP Ammonium Peptone sulphate 6.96 7.09 7.03 Interaction between nitrogen sources and type of inocula Nitrogen Sources (N) DAHP Peptone Ammonium sulphate Mean (Type of inocula) 7.66 7.43 7.66 7.58 Consortia 1 (5 %) 7.21 7.21 6.88 Consortia 2 (5 %) 6.43 6.54 6.54 Type of inocula (M) Saccharomyces cerevisiae var. ellipsoideus (5 %) CD (P=0.05) NS NS 7.10 Sugar Source (S) Nitrogen Source (N) Type of inocula (M) SXN SXM 6.51 NXM NS 0.40 NS NS SXNXM Mean (Nitrogen Sources) 7.10 7.06 7.03 NS Rating: 9: Like extremely, 8: Like very much, 7: Like moderately, 6: Like slightly, 5: Neither like nor dislike, 4: Dislike slightly, 3: Dislike moderately, 2: Dislike very much, 1: Dislike extremely 183
Table 4.41 Effect of different types of sugar sources, nitrogen sources and inocula on overall acceptability of apple tea wine Sucrose 20 ob Sugar sources (S) Nitrogen Sources (N) Honey 20 ob Apple juice concentrate 20 ob Mean (Type of inocula) 7.17 7.94 7.66 7.50 7.33 7.56 7.27 6.83 6.83 6.83 6.83 6.73 7.72 7.50 7.11 Peptone Ammoniu m sulphate Mean DAHP Saccharomyces cerevisiae var. ellipsoideus (5 %) 7.77 7.43 7.77 7.66 7.37 7.03 7.70 7.37 8.50 8.17 Consortia 1 (5 %) 7.43 7.10 7.10 7.21 7.03 7.03 7.03 7.03 7.83 Consortia 2 (5 %) 6.77 6.77 6.77 6.77 6.37 6.70 6.70 6.59 Mean Mean (Sugar Sources) Mean (Nitrogen Sources) 7.32 7.10 7.21 6.92 6.92 7.14 Type of inocula (M) 7.21 7.32 7.17 Ammonium Mean Peptone sulphate Mean DAHP DAHP Ammonium Peptone sulphate 7.00 7.44 7.16 Interaction between nitrogen sources and type of inocula Nitrogen Sources (N) DAHP Peptone Ammonium sulphate Mean (Type of inocula) 7.88 7.54 7.54 7.66 Consortia 1 (5 %) 7.43 7.21 7.16 Consortia 2 (5 %) 6.66 6.77 6.77 Type of inocula (M) Saccharomyces cerevisiae var. ellipsoideus (5 %) CD (P=0.05) NS NS 7.27 Sugar Source (S) Nitrogen Source (N) Type of inocula (M) SXN SXM 6.73 NXM NS 0.50 NS NS SXNXM Mean (Nitrogen Sources) 7.32 7.17 7.16 NS Rating: 9: Like extremely, 8: Like very much, 7: Like moderately, 6: Like slightly, 5: Neither like nor dislike, 4: Dislike slightly, 3: Dislike moderately, 2: Dislike very much, 1: Dislike extremely 184
Among the different nitrogen sources, highest (7.32) score for overall acceptability was observed in apple tea wine having DAHP as nitrogen source and lowest (7.16) was in apple tea wine having ammonium sulphate. There was significant difference among the different types of microorganisms used for inoculation. Must inoculated with Saccharomyces cerevisiae var. ellipsoideus for the preparation of apple tea wine recorded highest (7.66) score for overall acceptability which was at par with consortia 1 and lowest (6.73) was in must inoculated with consortia 2. 4.5.2 Standardization of tea concentration, initial TSS, DAHP and sulphur dioxide concentration and inoculum size by Response Surface Methodology 4.5.2.1 Experimental design For response surface mapping and standardization of parameters such as CTC tea concentration, initial TSS, initial DAHP and sulphur dioxide concentration and inoculum size, response surface methodology was applied on these factors. Second-order experimental design, i.e., Central Composite Design (CCD) with five factors at five levels was employed to investigate the first- and higher-order main effects of each factor and interactions among them. The design involved 8 center design points with α value being ± 2. The five coded levels investigated in the current study were -2, -1, 0, +1 and +2. The results so obtained for different physico-chemical and sensory characteristics are presented in table 4.42. 4.5.2.2 Physico-chemical and sensory analysis TSS Figure 4.34 depicts the expected response of TSS and correlation between the independent variables in three dimensional plots, with CTC tea at the X-axis. Fig.4.34a shows the curve between CTC tea at X-axis and DAHP concentration at Y- axis while 185
Table 4.42. Experimental results for CCD of RSM Factors Runs Responses Apple juice DAHP concentr as Sulphur CTC ate as nitrogen Dioxide tea (g) sugar source (ppm) source (%) (ob) Inoculum size (%) TSS (ob) Rate of Fermenta fermentat tion ion (M. efficiency fall ob/24 (%) hours) Titratable acidity (% malic acid) Free Sulphur dioxide (ppm) Reducing Sugars (mg/100 ml) Total Sugars (%) ph Colour Phenols (mg/l) Alcohol (%) Volatile acidity (% acetic acid) Higher alcohols (mg/l) Caffeine (ppm) Antioxid Over All ant accepta activity bility (%) 1 4.00 15.24 0.20 100.00 5.00 6.60 1.08 86.27 0.72 64.00 233.60 0.48 3.72 3.05 553.90 7.19 0.046 84.36 759.07 76.75 6.25 2 5.00 18.00 0.10 150.00 7.50 7.80 1.28 82.34 0.76 92.80 493.61 1.43 3.88 3.14 620.60 7.66 0.041 119.46 805.24 78.51 7.10 3 1.62 20.00 0.20 100.00 5.00 7.60 1.55 92.06 0.75 57.60 492.35 1.45 3.66 2.02 381.35 9.59 0.032 69.73 301.60 74.78 7.25 4 3.00 22.00 0.10 150.00 2.50 9.00 1.63 76.07 0.81 83.20 853.34 1.87 3.83 3.07 445.15 8.59 0.029 105.07 699.81 78.29 7.65 5 3.00 18.00 0.30 150.00 7.50 7.60 1.30 97.70 0.88 76.80 499.91 1.63 3.65 2.45 391.50 8.96 0.035 81.43 710.61 78.51 7.25 6 5.00 22.00 0.30 150.00 2.50 9.40 1.58 86.24 1.09 80.00 555.98 1.70 3.77 2.77 546.65 9.82 0.034 111.15 829.18 76.32 7.70 7 6.38 20.00 0.20 100.00 5.00 7.60 1.55 76.11 0.84 54.40 482.90 0.82 3.92 3.22 604.65 8.24 0.026 112.91 910.84 76.97 7.25 8 3.00 22.00 0.30 50.00 2.50 9.20 1.60 84.06 1.03 28.80 724.82 0.79 3.74 3.14 407.45 10.07 0.035 98.40 709.55 78.95 7.85 9 3.00 18.00 0.10 50.00 2.50 7.60 1.30 82.82 0.81 32.00 597.24 0.86 3.84 3.44 450.95 8.00 0.031 88.22 714.71 78.73 7.25 10 3.00 22.00 0.10 50.00 7.50 8.80 1.65 86.20 0.78 35.20 735.21 1.11 3.88 3.07 459.65 10.15 0.027 100.50 736.41 76.10 7.56 11 4.00 24.76 0.20 100.00 5.00 9.40 1.92 76.28 0.91 64.00 640.40 0.93 3.92 2.96 453.85 10.26 0.021 99.68 765.40 77.63 7.32 12 4.00 20.00 0.20 100.00 5.00 7.60 1.55 76.81 0.82 64.00 524.29 0.63 3.79 2.68 452.40 8.40 0.025 91.26 764.26 80.04 8.25 13 4.00 20.00 0.20 100.00 5.00 7.60 1.55 75.22 0.84 67.20 491.72 0.62 3.78 2.68 455.30 8.24 0.028 90.09 778.68 80.70 8.23 14 3.00 22.00 0.10 50.00 2.50 9.00 1.63 75.21 0.81 28.80 843.70 0.94 3.86 3.07 430.65 8.93 0.029 104.83 684.14 78.07 7.65 15 3.00 22.00 0.30 150.00 2.50 9.20 1.60 74.12 1.08 83.20 772.07 0.78 3.74 2.87 433.55 8.88 0.026 99.33 625.81 78.51 7.48 16 4.00 20.00 0.20 100.00 5.00 8.00 1.50 67.80 0.88 60.80 537.71 0.65 3.78 2.59 443.70 7.41 0.022 93.95 740.10 79.82 8.25 17 3.00 18.00 0.30 150.00 2.50 7.80 1.28 76.47 0.86 80.00 607.01 1.37 3.68 2.41 394.40 7.14 0.026 80.73 675.44 78.29 7.16 18 5.00 22.00 0.10 50.00 2.50 9.00 1.63 71.72 0.92 32.00 626.54 1.36 3.95 3.44 506.05 8.33 0.026 121.91 801.14 78.51 7.64 19 4.00 20.00 0.20 100.00 5.00 7.60 1.55 61.29 0.88 57.60 508.41 0.84 3.78 2.64 468.35 6.62 0.022 90.91 747.34 81.14 8.25 20 4.00 20.00 0.20-18.92 5.00 7.60 1.55 62.84 0.84 3.20 549.36 1.45 3.77 2.55 491.55 6.55 0.022 86.70 731.06 81.36 8.01 21 5.00 22.00 0.10 50.00 7.50 8.80 1.65 68.68 0.86 28.80 495.81 0.88 3.95 3.44 562.60 8.19 0.023 118.52 811.41 78.51 7.69 22 5.00 18.00 0.30 50.00 7.50 8.00 1.25 76.77 0.92 32.00 638.51 1.14 3.79 3.07 491.55 7.28 0.022 104.72 821.88 97.65 6.84 186
23 3.00 22.00 0.30 150.00 7.50 8.80 1.65 69.70 1.01 80.00 830.03 0.95 3.74 2.80 390.05 8.28 0.028 90.21 708.67 78.73 7.63 24 5.00 18.00 0.10 150.00 2.50 7.80 1.28 75.66 0.90 80.00 584.64 0.92 3.93 2.59 482.85 7.28 0.025 114.78 838.68 77.85 6.80 25 3.00 18.00 0.10 150.00 2.50 7.60 1.30 74.07 0.88 80.00 823.10 1.00 3.81 2.80 540.85 7.09 0.027 93.02 711.10 78.95 7.10 26 4.00 20.00 0.20 100.00 10.95 7.20 1.60 64.37 0.85 60.80 413.60 0.87 3.80 3.44 475.60 6.95 0.023 75.82 737.94 80.09 8.15 27 3.00 18.00 0.10 50.00 7.50 7.40 1.33 75.92 0.88 35.20 605.43 0.92 3.51 2.80 622.05 7.31 0.022 77.22 710.76 78.73 7.25 28 4.00 20.00 0.20 100.00 5.00 7.60 1.55 69.59 0.88 60.80 530.15 0.86 3.80 2.68 487.20 7.51 0.029 78.39 746.13 81.90 8.25 29 5.00 22.00 0.30 150.00 7.50 9.00 1.63 61.18 1.12 76.80 647.96 1.04 3.78 2.96 537.95 7.23 0.032 101.79 763.48 77.83 7.65 30 5.00 22.00 0.10 150.00 7.50 8.80 1.65 75.15 0.90 80.00 674.73 1.14 3.93 3.31 580.00 8.83 0.028 105.07 835.07 78.05 7.35 31 4.00 20.00 0.20 100.00 5.00 7.60 1.55 76.60 0.88 57.60 538.65 0.74 3.79 2.59 530.70 8.33 0.025 80.85 711.20 81.45 8.25 32 4.00 20.00 0.20 100.00-0.95 8.00 1.50 73.40 0.93 60.80 598.50 0.53 3.80 2.87 568.40 8.08 0.025 90.68 749.78 81.22 8.25 33 3.00 18.00 0.10 150.00 7.50 7.40 1.33 68.29 0.81 73.60 621.81 0.65 3.79 2.87 464.00 6.69 0.023 82.60 702.56 81.00 7.15 34 5.00 22.00 0.10 150.00 2.50 9.20 1.60 77.07 0.97 73.60 742.77 0.89 3.93 3.44 559.70 9.18 0.025 104.13 803.22 79.19 7.38 35 3.00 18.00 0.30 50.00 2.50 7.60 1.30 71.64 0.96 32.00 635.04 0.83 3.64 2.87 414.70 6.93 0.023 75.58 711.29 80.32 7.09 36 4.00 20.00 0.44 100.00 5.00 7.80 1.53 65.58 1.13 60.80 446.99 0.78 3.94 2.50 446.60 7.11 0.022 76.64 761.64 82.13 8.01 37 4.00 20.00-0.04 100.00 5.00 7.60 1.55 73.90 0.75 64.00 584.64 0.59 4.05 3.25 540.85 8.11 0.026 95.00 771.98 81.67 7.96 38 5.00 22.00 0.30 50.00 2.50 9.40 1.58 74.21 1.09 32.00 677.25 1.10 3.79 3.07 569.85 8.74 0.027 106.24 820.99 77.83 7.61 39 4.00 20.00 0.20 100.00 5.00 7.40 1.58 73.52 0.82 64.00 549.36 0.85 3.76 2.59 475.60 7.94 0.025 83.42 756.53 82.13 8.25 40 3.00 22.00 0.30 50.00 7.50 9.20 1.60 73.85 1.14 35.20 845.15 1.17 3.75 2.87 440.80 8.66 0.026 77.81 710.78 80.09 7.62 41 4.00 20.00 0.20 100.00 5.00 8.00 1.50 65.69 0.91 64.00 558.81 0.78 3.79 2.59 498.80 7.13 0.021 80.03 764.06 80.32 8.25 42 5.00 18.00 0.10 50.00 7.50 7.80 1.28 72.95 0.85 28.80 659.61 0.77 3.92 3.22 524.90 7.09 0.025 100.04 771.92 81.00 6.74 43 3.00 22.00 0.10 150.00 7.50 9.00 1.63 66.02 0.87 86.40 845.15 1.08 3.85 2.91 490.10 7.79 0.022 98.87 715.56 78.96 7.62 44 5.00 18.00 0.30 50.00 2.50 8.00 1.25 65.04 0.94 28.80 564.80 0.87 3.81 3.07 542.30 6.28 0.023 93.37 777.91 78.73 6.76 45 5.00 18.00 0.10 50.00 2.50 8.00 1.25 74.31 0.97 32.00 653.63 1.16 3.95 3.22 537.95 7.04 0.023 105.65 786.89 77.60 6.89 46 5.00 18.00 0.30 150.00 7.50 8.00 1.25 70.46 1.14 67.20 517.86 1.04 3.53 2.87 549.55 6.73 0.034 83.54 781.62 78.51 6.84 47 4.00 20.00 0.20 218.92 5.00 7.80 1.53 67.02 0.97 131.20 544.64 0.87 3.64 2.74 516.20 7.23 0.031 84.12 756.39 80.77 7.92 48 5.00 18.00 0.30 150.00 2.50 8.00 1.25 79.22 0.96 83.20 602.60 0.98 3.75 2.83 475.60 7.59 0.025 91.73 793.33 77.15 7.65 49 5.00 22.00 0.30 50.00 7.50 8.80 1.65 58.64 1.00 28.80 735.21 1.37 3.76 3.14 633.65 6.81 0.026 96.76 788.91 74.89 7.61 50 3.00 18.00 0.30 50.00 7.50 7.80 1.28 73.25 1.07 28.80 694.58 0.89 3.66 2.59 403.10 7.06 0.021 72.07 696.31 79.19 7.45 187
keeping all other variables at their O central levels. Similarly, fig. 4.34b, 4.34c and 4.34d shows the curves between CTC tea at X-axis and apple juice concentrate, inoculum size and sulphur dioxide at Y-axis respectively, keeping all other variables at their O central levels. Lower and higher levels of DAHP concentration, inoculum size, sulphur dioxide concentration and CTC tea did not influence TSS. Apple juice concentrate however showed non additive effect in pairs due to significant interaction between them. Maximum TSS of 9.4 ob was observed at 5 g of CTC tea, 22 ob TSS, 0.3% of DAHP, 150 ppm sulphur dioxide and at 2.50 % inoculum. Figure 4.34 a b c d The three dimensional response surface curves for TSS plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate (ob) (c) CTC tea (g) and inoculums size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 188
The regression equation coefficients were calculated and the data was fitted to a second-order polynomial equation. Thus the response (TSS) can be expressed in terms of the following regression equation: 1.0/(TSS) = 0.13-1.137E 003A 9.540E 003B 8.753E 004D + 1.625E 003E -1.712E 003A2-2.369E 003B2 2.998E-003C2-2.133E003D2-1.620E-003E2 +1.290E-003AB + 6.015E-005AC 1.297E-004AD + 2.523E-004AE + 2.082E-00BC 1.791E-004BD+ 5.186E-004BE+ 1.297E004CD 1.058E-004CE +1.828E 004DE Analysis of variance (ANOVA) gave the TSS as a function of the initial values of parameters. The coefficient of determination (R²) was calculated as 0.8604 for TSS, indicating that the statistical model can explain 86.04% of variability in the response. Adequate precision measures signal to noise ratio. For TSS, an adequate precision of 11.489 was recorded (A ratio greater than 4 is desirable), which indicates an adequate signal. This model can thus be used to navigate the design space. The Model F-value of 8.94 implies the model is significant. There is only 0.01% chance that a "Model F-Value" this large could occur due to noise. Values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case B, B2, C2, D2 are significant model terms. Table 4.43 ANOVA for TSS Source Sum of square Degree of freedom Mean square F-value P-value Model 4.696 20 2.348 8.94 0.0001 Total 5.458 49 R²=0.8604 Adequate precision=11.489 Rate of fermentation Figure 4.35 depicts the expected responses for rate of fermentation and correlation between the independent variables in three dimensional plots, with 189
CTC tea at the X-axis. Fig. 4.35a shows the curve between CTC tea at X-axis and DAHP concentration at Y- axis while keeping all other variables at their O central levels. Similarly, Fig. 4.35b, 4.35c and 4.35d shows the curves between CTC tea at X-axis and apple juice concentrate, inoculum size and sulphur dioxide at Y-axis respectively, keeping all other variables at their O central levels. Graphs show that none of the pairs of factors interact effectively to increase the rate of fermentation. Thus the increase in the rate is the outcome of factors contributing independently. Maximum rate of fermentation of 1.92 was observed at 4g CTC concentration, 24 ob TSS, 0.2% of DAHP, 100 ppm sulphur dioxide and at 5 % inoculum. Figure 4.35 a b c d The three dimensional response surface curves for rate of fermentation plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate (ob) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 190
The regression equation coefficients were calculated and the data was fitted to a second-order polynomial equation. Thus the response (rate of fermentation) can be expressed in terms of the following regression equation: Rate of fermentation =1.55-8.750E-003A+ 0.18B-7.727E-003C-1.250E-003D + 0.014E-0.013A2-0.026B2-0.023C2-0.017D2-0.013E2 + 9.375E-003AB + 0.000AC-1.563E-003AD +3.125E-003AE+ 0.000BC-1.563E-003BD +6.250E003BE+ 1.562E-003CD+ 0.000CE + 1.562E-003DE Analysis of variance (ANOVA) gave the rate of fermentation as a function of the initial values of parameters. The coefficient of determination (R²) was calculated as 0.9605 for rate of fermentation, indicating that the statistical model can explain 96.05% of variability in the response. Adequate precision measures signal to noise ratio. For rate of fermentation, an adequate precision of 24.994 was recorded (A ratio greater than 4 is desirable), which indicates an adequate signal. This model can thus be used to navigate the design space. The Model Fvalue of 35.25 implies the model is significant. There is only 0.01% chance that a "Model F-Value" this large could occur due to noise. Values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case B, B2, C2, D2 are significant model terms. Table 4.44 ANOVA for rate of fermentation Source Sum of square Degree of freedom Mean square F-value P-value Model 0.076 20 3.799 35.25 0.0001 Total 0.079 49 R²=0.9605 Adequate precision=24.994 Fermentation efficiency Figure 4.36 depicts the expected response of fermentation efficiency and correlation between the independent variables in three dimensional plots, with CTC tea at the X-axis. Fig.4.36a shows the curve between CTC tea at X-axis and 191
DAHP concentration at Y- axis while keeping all other variables at their O central levels. Similarly, Fig. 4.36b,4.36c and 4.36d shows the curves between CTC tea at X-axis and apple juice concentrate, inoculum size and sulphur dioxide at Y-axis respectively, keeping all other variables at their O central levels. Lower and higher levels of DAHP, inoculum size, sulphur dioxide concentration and CTC tea show increased fermentation efficiency by positively interacting with each other. Sulphur dioxide concentration however, shows additive effect i.e. the effect of one factor on the response does not depend upon the response of other factors. Maximum fermentation efficiency (97.7%) was observed at 3g CTC concentration, 18 ob TSS, 0.3% of DAHP, 150 ppm sulphur dioxide and at 7.5 % inoculum. Figure 4.36 a b c d The three dimensional response surface curves fermentation efficiency plotted between (a) CTC tea (g) DAHP (%), (b) CTC tea (g) and apple juice concentrate (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) sulphur dioxide (ppm) 192 for and (ob) and
The regression equation coefficients were calculated and the data was fitted to a second-order polynomial equation. Thus the response (Fermentation efficiency) can be expressed in terms of the following regression equation: Sqrt (Fermentation efficiency) = 8.41-0.12A - 0.085 B -0.04C + 0.047D-0.091E + 0.19A2 + 0.16 B2-0.021C2-0.083D2-0.023E2-0.021AB - 0.079AC + 0.12AD - 0.060AE - 0.033BC -0.066BD - 0.14BE + 0.089CD - 0.035CE 0.031DE Analysis of variance (ANOVA) gave the fermentation efficiency as a function of the initial values of parameters. The coefficient of determination (R²) was calculated as 0.5667 for fermentation efficiency, indicating that the statistical model can explain 56.67% of variability in the response. Adequate precision measures signal to noise ratio. For fermentation efficiency, an adequate precision of 6.733 was recorded (A ratio greater than 4 is desirable), which indicates an adequate signal. This model can thus be used to navigate the design space. Values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case A, A2, B2,BE are significant model terms. Table 4.45 ANOVA for fermentation efficiency Source Sum of square Degree of freedom Mean square F-value P-value Model 5.53 20 0.28 1.90 0.0001 Total 9.77 49 R²=0.5667 Adequate precision=6.733 Ethanol Figure 4.37 depicts the expected response of ethanol and correlation between the independent variables in three dimensional plots, with CTC tea at the X-axis. Fig. 4.37a shows the curve between CTC tea at X-axis and DAHP concentration at Y- axis while keeping all other variables at their O central levels. Similarly, Fig. 4.37b, 4.37c and 4.37d shows the curves between CTC tea 193
at X-axis and apple juice concentrate, inoculum size and sulphur dioxide at Yaxis respectively, keeping all other variables at their O central levels. With increase in apple juice concentrate concentration and sulphur dioxide concentration, ethanol content has increased, irrespective of the lower CTC tea levels. This means that the pair of factors are additive since there are low interactions between them. Maximum ethanol i.e. 10.26 % was observed at 4g CTC concentration, 24 ob TSS, 0.2% of DAHP, 100 ppm sulphur dioxide and at 5.0 % inoculum. Figure 4.37 a b c d The three dimensional response surface curves for ethanol (%) plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate (ob) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 194
The regression equation coefficients were calculated and the data was fitted to a second-order polynomial equation. Thus the response (Ethanol) can be expressed in terms of the following regression equation: Ethanol = 7.72-0.23A + 0.71B - 0.085C + 0.056D - 0.19E + 0.30A2 + 0.25B2 0.055C2 0.21D2 0.051E2-0.062AB - 0.14AC + 0.26AD - 0.12AE - 0.041BC0.11BD -0.25BE +0.15CD -0.12CE - 0.051DE Analysis of variance (ANOVA) gave the ethanol as a function of the initial values of parameters. The coefficient of determination (R²) was calculated as 0.7510 for ethanol, indicating that the statistical model can explain 75.10% of variability in the response. Adequate precision measures signal to noise ratio. For ethanol, an adequate precision of 9.281 was recorded (A ratio greater than 4 is desirable), which indicates an adequate signal. This model can thus be used to navigate the design space. The Model F-value of 4.37 implies the model is significant. There is only 0.01% chance that a "Model F-Value" this large could occur due to noise.values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case A, B, A2, B2, AD, BE are significant model terms. Table 4.46 ANOVA for ethanol Source Sum of square Degree of freedom Mean square F-value P-value Model 37.57 20 1.88 4.37 0.0001 Total 50.03 49 R²=0.7510 Adequate precision=9.281 Titratable acidity Figure 4.38 depicts the expected response of titratable acidity and correlation between the independent variables in three dimensional plots, with CTC tea at the X-axis. Fig. 4.38a shows the curve between CTC tea at X-axis and DAHP concentration at Y- axis while keeping all other variables at their O central levels. Similarly, Fig. 4.38b, 4.38c and 4.38d shows the curves 195
between CTC tea at X-axis and apple juice concentrate, inoculum size and sulphur dioxide at Y-axis respectively, keeping all other variables at their O central levels. Titratable acidity has shown a consistent decrease with increase in CTC tea concentrations. DAHP concentration and CTC tea has a negative effect on titratable acidity. Other variables such as apple juice concentrate, sulphur dioxide concentration and inoculum size have moderately interacted with the CTC tea concentration for titratable acidity responses. Maximum titratable acidity i.e. 1.29 % was observed at 5g CTC concentration, 22 ob TSS, 0.3% of DAHP, 50 ppm sulphur dioxide and at 2.5 % inoculum. Figure 4.38 a b c d The three dimensional response surface curves for titratable acidity plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate (ob) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 196
The regression equation coefficients were calculated and the data was fitted to a second-order polynomial equation. Thus the response (Titrable acidity) can be expressed in terms of the following regression equation: Titrable acidity = 1.04 + 0.053A + 0.055B +0.066C -2.000E-003D -9.500E-003E -0.017A2 + 0.045B2-6.275E-003C2 + 0.013D2+2.236E-004E2+ 0.020AB 0.010AC - 6.875E-003AD +2.500E-003AE-5.625E-003BC +1.000E-002BD 0.016BE -3.750E-003CD -6.250E-004CE+3.750E-003DE Analysis of variance (ANOVA) gave the titrable acidity as a function of the initial values of parameters. The coefficient of determination (R²) was calculated as 0.8198 for titrable acidity, indicating that the statistical model can explain 81.98% of variability in the response. Adequate precision measures signal to noise ratio. For titrable acidity, an adequate precision of 11.580 was recorded (A ratio greater than 4 is desirable), which indicates an adequate signal. This model can thus be used to navigate the design space. The Model F-value of 6.60 implies the model is significant. There is only 0.01% chance that a "Model F-Value" this large could occur due to noise.values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case A, B, C, B2 are significant model terms. Table 4.47 ANOVA for titratable acidity Source Sum of square Degree of freedom Mean square F-value P-value Model 0.51 20 0.025 6.60 0.0001 Total 0.62 49 R²=0.8198 Adequate precision=11.580 Volatile acidity Figure 4.39 depicts the expected response of titrable acidity and correlation between the independent variables in three dimensional plots, with CTC tea at the X-axis. Fig. 4.39a shows the curve between CTC tea at X-axis and 197
DAHP concentration at Y- axis while keeping all other variables at their O central levels. Similarly, Fig. 4.39b, 4.39c and 4.39d shows the curves between CTC tea at X-axis and apple juice concentrate, inoculum size and sulphur dioxide at Y-axis respectively, keeping all other variables at their O central levels. At higher levels of CTC tea, higher levels of DAHP, apple juice concentrate and inoculum size showed increased volatile acidity. However, with increased levels of sulphur dioxide, there was not a very pronounced increase in volatile acidity with CTC tea. Maximum volatile acidity i.e. 0.046 % was observed at 4g CTC concentration, 16 ob TSS, 0.2% of DAHP, 100 ppm sulphur dioxide and at 5 % inoculum. Figure 4.39 a b c d The three dimensional response surface curves for volatile acidity plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate (ob) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 198
The regression equation coefficients were calculated and the data was fitted to a second-order polynomial equation. Thus the response (volatile acidity) can be expressed in terms of the following regression equation: Volatile acidity = 0.025-7.500E-005A - 8.250-004B + 3.271E-004C + 1.725E003D -7.500E-005E + 9.383E-004A2 + 2.063E-003B2-6.383E-004C2 + 3.133E-004D2-3.117E-004E2-3.438E-004AB -9.375E-005AC + 1.469E003AD + 1.406E-003AE+1.031E-003BC -1.281E-003BD-1.219E-003BE +7.187E-004CD + 2.812E-004CE +1.594E-003DE Analysis of variance (ANOVA) gave the volatile acidity as a function of the initial values of parameters. The coefficient of determination (R²) was calculated as 0.5355 for volatile acidity, indicating that the statistical model can explain 53.55% of variability in the response. Adequate precision measures signal to noise ratio. For volatile acidity, an adequate precision of 5.436 was recorded (A ratio greater than 4 is desirable), which indicates an adequate signal. This model can thus be used to navigate the design space. Values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case B2, D are significant model terms. Table 4.48 ANOVA for volatile acidity Source Sum of square Degree of freedom Mean square F-value P-value Model 6.94 20 3.47 1.67 0.0001 Total 1.29 49 R²=0.5355 Adequate precision=5.436 Higher alcohol Figure 4.40 depicts the expected response for higher alcohols and correlation between the independent variables in three dimensional plots, with CTC tea at the X-axis. Fig. 4.40a shows the curve between CTC tea at X-axis and DAHP concentration at Y- axis while keeping all other variables at their 199
O central levels. Similarly, Fig. 4.40b, 4.40c and 4.40d shows the curves between CTC tea at X-axis and apple juice concentrate, inoculum size and sulphur dioxide at Y-axis respectively, keeping all other variables at their O central levels. From the figures it is seen that there are low interactions among all the factors for higher alcohols, thus the effects of pairs of factors were additive and non significant. Any effect on higher alcohols production was thus the effect of factors acting independently but not in pairs. Maximum higher alcohol i.e. 121.91 mg/l was observed at 5g CTC concentration, 22 ob TSS, of DAHP, 50 ppm sulphur dioxide and at 2.5 % inoculum. Figure 4.40 a b c d The three dimensional response surface curves for higher alcohol plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate (ob) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) 200
The regression equation coefficients were calculated and the data was fitted to a second-order polynomial equation. Thus the response (Higher alcohol) can be expressed in terms of the following regression equation: Higher alcohol = 84.62 + 8.48A+5.18B -5.73C+0.40D-2.83E+2.93A2+3.10B2 +2.76 C2+ 1.45D2+0.91E2-2.24AB- 0.80AC-1.63AD +1.42AE +0.64BC1.24BD-1.24BE+0.28CD-0.40 CE +0.30DE Analysis of variance (ANOVA) gave the higher alcohols as a function of the initial values of parameters. The coefficient of determination (R²) was calculated as 0.8081 for higher alcohols, indicating that the statistical model can explain 80.81% of variability in the response. Adequate precision measures signal to noise ratio. For higher alcohols, an adequate precision of 10.606 was recorded (A ratio greater than 4 is desirable), which indicates an adequate signal. This model can thus be used to navigate the design space. The Model F-value of 6.10 implies the model is significant. There is only 0.01% chance that a "Model F-Value" this large could occur due to noise.values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case A, B, C, E A2, B2 are significant model terms. Table 4.49 ANOVA for higher alcohol Source Sum of square Degree of freedom Mean square F-value P-value Model 6814.79 20 340.74 6.10 0.0001 Total 8433.61 49 R²=0.8081 Adequate precision=10.606 Colour Figure 4.41 depicts the expected response for colour and correlation between the independent variables in three dimensional plots, with CTC tea at the X-axis. Fig. 4.41a shows the curve between CTC tea at X-axis and DAHP concentration at Y- axis while keeping all other variables at their O central levels. Similarly, Fig. 4.41b, 4.41c and 4.41d shows the curves between CTC tea 201
at X-axis and apple juice concentrate, inoculum size and sulphur dioxide at Yaxis respectively, keeping all other variables at their O central levels. There is no effect of pairs of factors on colour. All the factors have acted independently towards colour. Thus the combinations of factors are additive and non significant. Maximum colour intensity of 3.44 was observed at 5g CTC concentration, 22 ob TSS, of DAHP, 150 ppm sulphur dioxide and at 2.5 % inoculum. Figure 4.41 a b c d The three dimensional response surface curves for colour plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate (ob) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) The regression equation coefficients were calculated and the data was fitted to a second-order polynomial equation. Thus the response (colour) can be expressed in terms of the following regression equation: 202
Colour = 2.63 + 0.15A + 0.074B -0.15C -0.076D + 0.014E + 5.917E-003A2 +0.10B2+ 0.087C2 + 0.012D2 + 0.14E2-3.125E- 004AB + 3.125E-004AC2.813E-003AD + 0.063AE -6.562E-003BC + 0.038BD-4.688E-003BE -9.063E003CD + 9.375E-004CE + 0.052DE Analysis of variance (ANOVA) gave the colour as a function of the initial values of parameters. The coefficient of determination (R²) was calculated as 0.7431 for colour, indicating that the statistical model can explain 74.31% of variability in the response. Adequate precision measures signal to noise ratio. For colour, an adequate precision of 8.137 was recorded (A ratio greater than 4 is desirable), which indicates an adequate signal. This model can thus be used to navigate the design space. The Model F-value of 4.19 implies the model is significant. There is only 0.01% chance that a "Model F-Value" this large could occur due to noise.values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case A, B, C, D, B2, E2 are significant model terms. Table 4.50 ANOVA for colour Source Sum of square Degree of freedom Mean square F-value P-value Model 3.57 20 0.18 4.19 0.0001 Total 4.80 49 R²=0.7431 Adequate precision=8.137 ph Figure 4.42 depicts the expected response for ph and correlation between the independent variables in three dimensional plots, with CTC tea at the X-axis. Fig. 4.42a shows the curve between CTC tea at X-axis and DAHP concentration at Yaxis while keeping all other variables at their O central levels. Similarly, Fig. 4.42b, 4.42c and 4.42d shows the curves between CTC tea at X-axis and apple juice concentrate, inoculum size and sulphur dioxide at Y-axis respectively, keeping all other variables at their O central levels. Observation of graphs 203
revealed that the pairs of factors have not interacted in any way to give responses for ph. Thus the pairs of factors are additive, interacting non-significantly. Maximum ph (3.97) was observed at 4g CTC concentration, 20 ob TSS, 0.05% of DAHP, 100 ppm sulphur dioxide and at 5 % inoculum. Figure 4.42 a b c d The three dimensional response surface curves for ph plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate (ob) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) The regression equation coefficients were calculated and the data was fitted to a second-order polynomial equation. Thus the response (ph) can be expressed in terms of the following regression equation: 204
ph =+3.68 + 0.042A+0.017B -0.077C -0.013D + 1.750E-003E-4.180E-003A2 +0.012B2 + 0.055C2-0.027D2-0.012E2-0.025AB -5.938E-003AC - 4.063E003AD-1.563E-003AE +2.812E-003BC -2.813E-003BD +9.375E-004BE + 6.562E-003CD- 5.938E-003CE + 2.187E-003DE Analysis of variance (ANOVA) gave the ph as a function of the initial values of parameters. The coefficient of determination (R²) was calculated as 0.9295 for ph, indicating that the statistical model can explain 92.95% of variability in the response. Adequate precision measures signal to noise ratio. For ph, an adequate precision of 18.012 was recorded (A ratio greater than 4 is desirable), which indicates an adequate signal. This model can thus be used to navigate the design space. The Model F-value of 19.12 implies the model is significant. There is only 0.01% chance that a "Model F-Value" this large could occur due to noise.values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case A, B, C, D, B2, C2, D2, AB are significant model terms. Table 4.51 ANOVA for ph Source Sum of square Degree of freedom Mean square F-value P-value Model 0.40 20 0.020 19.12 0.0001 Total 0.43 49 R²=0.9295 Adequate precision=18.012 Reducing sugars Figure 4.43 depicts the expected response for total sugars and correlation between the independent variables in three dimensional plots, with CTC tea at the X-axis. Fig. 4.43a shows the curve between CTC tea at X-axis and DAHP concentration at Y- axis while keeping all other variables at their O central levels. Similarly, Fig. 4.43b, 4.43c and 4.43d shows the curves between CTC tea at X-axis and apple juice concentrate, inoculum size and sulphur dioxide at Yaxis respectively, keeping all other variables at their O central levels. Maximum 205
reducing sugar i.e. 845.14 mg/100g was observed at 3g CTC concentration, 22 ob TSS, 0.3% of DAHP, 50 ppm sulphur dioxide and at 7.5 % inoculum. a b c d Figure 4.43 The three dimensional response surface curves for reducing sugars (mg/ 100g) plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate (ob) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) The regression equation coefficients were calculated and the data was fitted to a second-order polynomial equation. Thus the response (reducing sugars) can be expressed in terms of the following regression equation: 206
Reducing sugars = 501.26-42.02A+ 65.50B -19.33C-1.74D -17.34E +22.92A2 +10.26B2 + 42.85C2 + 37.76D2 + 27.53E2-28.89AB +10.16AC-12.58AD +1.07AE +7.81BC +16.77BD + 10.92 BE -28.25CD + 26.98CE-15.53DE Analysis of variance (ANOVA) gave the reducing sugars as a function of the initial values of parameters. The coefficient of determination (R²) was calculated as 0.6571 for reducing sugars, indicating that the statistical model can explain 65.71% of variability in the response. Adequate precision measures signal to noise ratio. For reducing sugars, an adequate precision of 7.936 was recorded (A ratio greater than 4 is desirable), which indicates an adequate signal. This model can thus be used to navigate the design space.values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case A, B, C 2, D2 are significant model terms. Table 4.52 ANOVA for reducing sugars Source Sum of square Degree of freedom Mean square F-value P-value Model 5.152 20 25757.83 2.78 0.0001 Total 7.84 49 R²=0.6571 Adequate precision=7.936 Total sugars Figure 4.44 depicts the expected response for total sugars and correlation between the independent variables in three dimensional plots, with CTC tea at the X-axis. Fig. 4.44a shows the curve between CTC tea at X-axis and DAHP concentration at Y- axis while keeping all other variables at their O central levels. Similarly, Fig. 4.44b, 4.44c and 4.44d shows the curves between CTC tea at X-axis and apple juice concentrate, inoculum size and sulphur dioxide at Yaxis respectively, keeping all other variables at their O central levels. It was shown that the effects of pairs of factors were additive and their interactions correspond to the minimal production of total sugars when the factors considered 207
were taken together. Maximum total sugars i.e. 1.87 % was observed at 3g CTC concentration, 22 ob TSS, of DAHP, 150 ppm sulphur dioxide and at 2.5 % inoculum. Figure 4.44 a b c d The three dimensional response surface curves for total sugars (%) plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate (ob) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) The regression equation coefficients were calculated and the data was fitted to a second-order polynomial equation. Thus the response (total sugars) can be expressed in terms of the following regression equation: 208
Sqrt(Total sugars) = 0.84-1.787E-003A+ 0.034B + 0.011C + 0.012D + 9.064E003E + 0.067A2 + 0.010B2 + 0.018C2 + 0.070D2 + 9.861E-003E2 + 8.861E003AB + 9.755E-003AC -0.017AD -2.652E-003AE-0.021BC-0.014BD- 0.013BE + 5.650E-003CD + 0.028CE-0.012DE Analysis of variance (ANOVA) gave the total sugars as a function of the initial values of parameters. The coefficient of determination (R²) was calculated as 0.4258 for total sugars, indicating that the statistical model can explain 42.58% of variability in the response. Adequate precision measures signal to noise ratio. For total sugars, an adequate precision of 3.503 was recorded (A ratio greater than 4 is desirable), which indicates an adequate signal. This model can thus be used to navigate the design space. The Model F-value of 4.37 implies the model is significant. There is only 0.02% chance that a "Model F-Value" this large could occur due to noise.values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case A, B, A2, B2, AD, BE are significant model terms. Table 4.53 ANOVA for total sugars Source Sum of square Degree of freedom Mean square F-value P-value Model 0.46 20 0.023 1.08 0.0001 Total 1.07 49 R²=0.4258 Adequate precision=3.503 Residual sulphur dioxide Figure 4.45 depicts the expected response for total phenols and correlation between the independent variables in three dimensional plots, with CTC tea at the X-axis. Fig. 4.45a shows the curve between CTC tea at X-axis and DAHP concentration at Y- axis while keeping all other variables at their O central levels. Similarly, Fig. 4.45b, 4.45c and 4.45d shows the curves between CTC tea at X-axis and apple juice concentrate, inoculum size and sulphur dioxide at Yaxis respectively, keeping all other variables at their O central levels. Maximum 209
residual sulphur dioxide i.e.131.20 ppm was observed at 4g CTC concentration, 20 ob TSS, 0.2% of DAHP, 200 ppm sulphur dioxide and at 5.00 % inoculum. Figure 4.45 a b c d The three dimensional response surface curves for residual SO2 (ppm) plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate (ob) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) The regression equation coefficients were calculated and the data was fitted to a second-order polynomial equation. Thus the response (residual sulphur dioxide) can be expressed in terms of the following regression equation: 210
Residual sulphur dioxide = +63.16-0.72A+ 0.24B-0.71C + 25.84D-0.080E-2.76 A2-0.76B2-1.67C2 + 0.044D2-1.56E2-1.10AB-0.30AC + 0.100AD- 0.30AE + 0.70BC + 0.30BD + 0.70BE - 0.50CD -1.30CE -0.50DE Analysis of variance (ANOVA) gave residual sulphur dioxide as a function of the initial values of parameters. The coefficient of determination (R²) was calculated as 0.9624 for residual sulphur dioxide, indicating that the statistical model can explain 96.24% of variability in the response. Adequate precision measures signal to noise ratio. For residual sulphur dioxide, an adequate precision of 26.296 was recorded (A ratio greater than 4 is desirable), which indicates an adequate signal. This model can thus be used to navigate the design space. The Model F-value of 37.15 implies the model is significant. There is only 0.01% chance that a "Model F-Value" this large could occur due to noise.values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case D, A2 are significant model terms. Table 4.54 ANOVA for residual sulphur dioxide Source Sum of square Degree of freedom Mean square F-value P-value Model 27335.67 20 1366.78 37.15 0.0001 Total 28402.48 49 R²=0.9624 Adequate precision=26.296 Total phenols Figure 4.46 depicts the expected response for total phenols and correlation between the independent variables in three dimensional plots, with CTC tea at the X-axis. Fig. 4.46a shows the curve between CTC tea at X-axis and DAHP concentration at Y- axis while keeping all other variables at their O central levels. Similarly, Fig. 4.46b, 4.46c and 4.46d shows the curves between CTC tea at X-axis and apple juice concentrate, inoculum size and sulphur dioxide at Yaxis respectively, keeping all other variables at their O central levels. The 211
interactions shown here are non significant as none of the pairs of factors have any effect on total phenols. Maximum total phenols 633.65 mg/l was observed at 5g CTC concentration, 22 ob TSS, 0.3% of DAHP, 50 ppm sulphur dioxide and at 7.5 % inoculum. Figure 4.46 a b c d The three dimensional response surface curves for total phenols (ppm) plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate (ob) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) The regression equation coefficients were calculated and the data was fitted to a second-order polynomial equation. Thus the response (total phenols) can be expressed in terms of the following regression equation: Total phenols = 491.08 + 54.74A + 2.17 B -16.18 C + 3.84D + 0.95E 212
Analysis of variance (ANOVA) gave total phenols as a function of the initial values of parameters. The coefficient of determination (R²) was calculated as 0.6618 for total phenols, indicating that the statistical model can explain 66.18% of variability in the response. Adequate precision measures signal to noise ratio. For total phenols, an adequate precision of 16.224 was recorded (A ratio greater than 4 is desirable), which indicates an adequate signal. This model can thus be used to navigate the design space. The Model F-value of 17.22 implies the model is significant. There is only 0.01% chance that a "Model F-Value" this large could occur due to noise.values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case A, C are significant model terms. Table 4.55 ANOVA for total phenols Source Sum of square Degree of freedom Mean square F-value P-value Model 1.307 20 26133.51 17.22 0.0001 Total 1.974 49 R²=0.6618 Adequate precision=16.224 Caffeine Figure 4.47 depicts the expected responses for caffeine and correlation between the independent variables in three dimensional plots, with CTC tea at the X-axis. Fig. 4.47a shows the curve between CTC tea at X-axis and DAHP concentration at Y- axis while keeping all other variables at their O central levels. Similarly, Fig. 4.47b, 4.47c and 4.47d shows the curves between CTC tea at X-axis and apple juice concentrate, inoculum size and sulphur dioxide at Y-axis respectively, keeping all other variables at their O central levels. The interactions shown here are non significant as none of the pairs of factors have any effect on caffeine production. Maximum caffeine i.e. 838.68 ppm was observed at 5g CTC concentration, 18 ob TSS, of DAHP, 150 ppm sulphur dioxide and at 2.5 % inoculum. 213
Figure 4.47 a b c d The three dimensional response surface curves for caffeine (ppm) plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate (ob) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) The regression equation coefficients were calculated and the data was fitted to a second-order polynomial equation. Thus the response (caffeine) can be expressed in terms of the following regression equation: Caffeine = +746.22 + 70.65A + 1.16B- 5.51C-0.12D + 1.61E Analysis of variance (ANOVA) gave the caffeine as a function of the initial values of parameters. The coefficient of determination (R²) was calculated as 214
0.6123 for caffeine, indicating that the statistical model can explain 61.23% of variability in the response. Adequate precision measures signal to noise ratio. For caffeine, an adequate precision of 15.170 was recorded (A ratio greater than 4 is desirable), which indicates an adequate signal. This model can thus be used to navigate the design space. The Model F-value of 13.90 implies the model is significant. There is only 0.01% chance that a "Model F-Value" this large could occur due to noise.values of "Prob > F" less than 0.0500 indicate model terms are significant. Table 4.56 Source ANOVA for caffeine Sum of Degree of Mean square freedom square Model 2.009 5 40189.81 Total 3.282 49 F-value P-value 13.90 0.0001 R²=0.6123 Adequate precision=15.170 Antioxidant activity Figure 4.48 depicts the expected responses for antioxidant activity and correlation between the independent variables in three dimensional plots, with CTC tea at the X-axis. Fig. 4.48a shows the curve between CTC tea at X-axis and DAHP concentration at Y- axis while keeping all other variables at their O central levels. Similarly, Fig. 4.48b, 4.48c and 4.48d shows the curves between CTC tea at X-axis and apple juice concentrate, inoculum size and sulphur dioxide at Y-axis respectively, keeping all other variables at their O central levels. The interaction of inoculum size and sulphur dioxide with CTC tea has led to an increased level of antioxidants suggesting a significant interaction between them. Maximum antioxidant acidity i.e. 82.12 % was observed at 4g CTC concentration, 20 0B TSS, 0.2% of DAHP, 100 ppm sulphur dioxide and at 5 % inoculum. 215
Figure 4.48 a b c d The three dimensional response surface curves for antioxidant activity (%) plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate (ob) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) The regression equation coefficients were calculated and the data was fitted to a second-order polynomial equation. Thus the response (antioxidant activity) can be expressed in terms of the following regression equation: 1.0/(Antioxidant acitivity) = +0.012-3.055E-005A+ 1.073E-004B - 4.101E-005C + 7.047E-005D - 6.808E-005E+ 2.057E-004A2 + 1.490E-004B2-3.848E-005C2 5.743E-006D2 + 9.982E-006E2 + 8.248E-005A B -9.752E-006AC + 9.399E- 216
005AD -8.526E-005AE + 7.637E-005BC-1.144E-004BD + 1.235E-004BE + 1.192E-004CD -6.085E-005CE + 3.952E-005DE Analysis of variance (ANOVA) gave the antioxidant activity as a function of the initial values of parameters. The coefficient of determination (R²) was calculated as 0.5655 for antioxidant activity, indicating that the statistical model can explain 56.55% of variability in the response. Adequate precision measures signal to noise ratio. For antioxidant activity, an adequate precision of 6.822 was recorded (A ratio greater than 4 is desirable), which indicates an adequate signal. This model can thus be used to navigate the design space. Values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case A2, B2 are significant model terms. Table 4.57 ANOVA for antioxidant activity Source Sum of square Degree of freedom Mean square F-value P-value Model 5.489 20 2.745 1.89 0.0001 Total 9.708 49 R²=0.5655 Adequate precision=6.822 Overall acceptability Figure 4.49 depicts the expected response of TSS and correlation between the independent variables in three dimensional plots, with CTC tea at the X-axis. Fig.16a shows the curve between CTC tea at X-axis and DAHP concentration at Y- axis while keeping all other variables at their O central levels. Similarly, Fig. 4.49b, 4.49c and 4.49d shows the curves between CTC tea at X-axis and apple juice concentrate, inoculum size and sulphur dioxide at Y-axis respectively, keeping all other variables at their O central levels. Lower and higher levels of DAHP, apple juice concentration, inoculum size, sulphur dioxide concentration and CTC tea did not influenced overall acceptability of the product. Thus the factors have been seen interacting additively but independently. Maximum overall acceptability of 8.25 was observed at 4g CTC concentration, 20 ob TSS, 0.2% of DAHP, 100 ppm sulphur dioxide and at 5 % inoculum. 217
Figure 4.49 a b c d The three dimensional response surface curves for overall acceptability plotted between (a) CTC tea (g) and DAHP (%), (b) CTC tea (g) and apple juice concentrate (ob) (c) CTC tea (g) and inoculum size (%), (d) CTC tea (g) and sulphur dioxide (ppm) The regression equation coefficients were calculated and the data was fitted to a second-order polynomial equation. Thus the response (overall acceptability) can be expressed in terms of the following regression equation: Overall acceptability = 8.27-0.063A + 0.26B + 0.049C - 4.250E-003D0.013E-0.27A2-0.39B2-0.12C2-0.093D2-0.034E2 + 0.052AB + 0.024AC + 0.043AD-0.028AE-4.688E-003BC -0.048BD 0.016CE-0.011DE 218-4.688E-003BE +0.033CD -
Analysis of variance (ANOVA) gave the overall acceptability as a function of the initial values of parameters. The coefficient of determination (R²) was calculated as 0.8418 for overall acceptability, indicating that the statistical model can explain 84.18% of variability in the response. Adequate precision measures signal to noise ratio. For overall acceptability, an adequate precision of 13.800 was recorded (A ratio greater than 4 is desirable), which indicates an adequate signal. This model can thus be used to navigate the design space. The Model F-value of 7.72 implies the model is significant. There is only 0.01% chance that a "Model F-Value" this large could occur due to noise.values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case A, B, A2, B2, C2, D2 are significant model terms. Table 4.58 ANOVA for overall acceptability Source Sum of square Degree of freedom Mean square F-value P-value Model 10.24 20 0.51 7.72 0.0001 Total 12.17 49 R²=0.8418 Adequate precision=13.800 4.5.2.3 Cluster analysis of the different runs The data obtained from physico-chemical analysis of apple tea wine was analysed using cluster analysis with rescaled distance cluster analysis. The dendrogram representation of the different runs of the apple tea wine using physico-chemical characteristics showed in Fig. 4.50. Out of the different variables, cluster analysis grouped various concentrations of tea i.e. 1.62 g, 3g, 4g, 5g and 6 g. Main clusters divided in to 2 main clusters. The 1st sub-cluster of it further divided in two another sub-cluster i.e. 1a and 1b. 1a further divided in to two sub-clusters i.e. 1aa and 1ab. Sub-cluster 1aa comprises of the runs having 3 g and 4 g CTC tea, whereas, sub-cluster 1ab comprises of the runs having 5 g CTC tea. Sub-cluster 1b comprises of run having 6.36 g tea. The 2nd sub-cluster comprises of the run having 1.62 g CTC tea. The cluster analysis had failed to separate according to the initial sugar concentration, DAHP concentration, 219
sulphur dioxide concentration and innoculum size into any cluster thus showing that these variables did not influence the physico-chemical characteristics of apple tea wine. Figure 4.50 Dendrogram of different treatments of apple tea wine using various physico-chemical characteristics analysed based on rescaled distance 220
4.5.2.4 Classification concentration, and overview initial of sugar runs according concentration, to tea DAHP concentration, sulphur dioxide concentration and innoculum size Effect of different tea concentration, initial sugar concentration, DAHP concentration, sulphur dioxide concentration and innoculum size on the physicochemical and sensory characteristics of apple tea wine are shown in Table 4.59 to 4.63. It is clearly visible from the Table 4.59 that apple eta wine having 4 g CTC tea had highest rate of fermentation, lowest reducing and total sugar content, comparable total phenols, ethanol content and caffeine content, lowest volatile acidity and higher alcohols, highest antioxidant activity and overall acceptability, whereas, lowest volatile acidity and higher alcohol, highest antioxidant activity and overall acceptability was observed with 20 ob initial sugar concentration (Table 4.60). 0.2 % DAHP had highest rate of fermentation, lowest reducing and total sugar content, comparable total phenols, ethanol content and caffeine content, lowest volatile acidity and higher alcohols and highest antioxidant activity (Table 4.61). Highest rate of fermentation, lowest reducing and total sugar content, comparable total phenols, ethanol content and caffeine content, lowest volatile acidity and higher alcohols and highest antioxidant activity was observed in 100 ppm SO2 (Table 4.62). Similar trend was also observed in case of the 5 % innoculum (Table 4.63). 4.6 EFFECT OF DIFFERENT WOOD CHIPS ON THE PHYSICOCHEMICAL AND SENSORY QUALITY CHARACTERISTICS OF APPLE TEA WINE DURING MATURATION 4.6.1 Physico-chemical changes during maturation Total soluble solids, reducing sugars and total sugars Table 4.64 summarizes the effect different wood chips treatment and maturation period on total soluble solids, reducing sugars and total sugars of apple tea wine. It is revealed from the data that with advancement of maturation period from 0 to 6 month, a significant decrease in TSS was observed from 8.00 221
Table 4.59 Physico-chemical and sensory characteristics of apple tea wine according to tea concentration as prepared by RSM design CTC tea (g) TSS (ob) 3.00 8.31 1.46 76.59 0.92 56.20 4.00 7.71 1.54 71.01 0.88 5.00 8.49 1.44 73.10 0.96 Rate of Fermenta Titratab Free Reducing fermentatio tion le Sulphur Sugars n (M. fall efficiency acidity dioxide (mg/100 o B/24 (%) (% MA) (ppm) ml) hours) Total Sugars (%) ph Colour Phenols (mg/l) Alcohol (%) Volatile acidity (% acetic acid) Higher alcohols (mg/l) Caffeine (ppm) Antioxida Over All nt activity acceptabil (%) ity 720.85 1.05 3.75 2.88 448.68 8.16 0.027 89.12 701.47 78.84 7.42 62.80 515.68 0.78 3.81 2.78 491.19 7.69 0.026 86.37 752.60 80.57 7.99 54.80 616.97 1.11 3.84 3.10 545.11 7.76 0.027 104.93 801.93 79.26 7.27 Table 4.60 Physico-chemical and sensory characteristics of apple tea wine according to initial sugar concentration as prepared by RSM design Apple juice concentrate as sugar source (ob) TSS (ob) Rate of Fermentati Titratable Free fermentatio on acidity Sulphurdiox n (M. fall efficiency (% MA) ide (ppm) o B/24 (%) hours) Reducing Sugars (mg/100 ml) Total Sugars (%) ph Colour Phenols (mg/l) Alcohol (%) Volatile acidity (% acetic acid) Higher alcohols (mg/l) Caffeine (ppm) 18.00 7.76 1.28 76.06 0.91 20.00 7.66 1.54 71.36 22.00 9.04 1.62 73.63 55.20 612.46 1.03 3.76 2.89 494.18 7.26 0.027 91.51 750.64 80.05 7.08 0.87 61.80 522.01 0.83 3.80 2.73 489.83 7.72 0.025 86.28 733.10 80.41 8.05 0.97 55.80 725.36 1.14 3.83 3.09 499.62 8.66 0.028 102.54 752.76 78.05 7.61 222 Antioxida Over All nt activity acceptabil (%) ity
Table 4.61 Physico-chemical and sensory characteristics of apple tea wine according to initial DAHP concentration as prepared by RSM design DAHP as nitrogen source (%) TSS (ob) 0.10 8.31 1.46 75.16 0.86 56.40 0.20 7.70 1.54 72.80 0.86 0.30 8.49 1.44 74.53 1.02 Rate of Fermenta Titratab Free Reducing fermentatio tion le Sulphur Sugars n (M. fall efficiency acidity dioxide (mg/100 o B/24 (%) (% MA) (ppm) ml) hours) Total Sugars (%) ph Colour Phenols (mg/l) Alcohol (%) Volatile acidity (% acetic acid) Higher alcohols (mg/l) Caffeine (ppm) Antioxida Over All nt activity acceptabil (%) ity 678.52 1.06 3.86 3.11 517.38 8.01 0.027 102.49 758.04 78.63 7.30 62.00 512.15 0.84 3.78 2.74 491.10 7.85 0.026 87.06 732.52 79.82 7.90 54.60 659.30 1.10 3.72 2.86 476.42 7.90 0.028 91.55 745.36 79.47 7.39 Table 4.62 Physico-chemical and sensory characteristics of apple tea wine according to initial sulphur dioxide concentration as prepared by RSM design Sulphur Dioxide (ppm) TSS (ob) 50.00 8.40 1.45 74.08 0.94 31.20 100.00 7.70 1.54 73.41 0.86 150.00 8.40 1.45 75.61 0.94 Rate of Fermenta Titratab Free Reducing fermentatio tion le Sulphur Sugars n (M. fall efficiency acidity dioxide (mg/100 o B/24 (%) (% MA) (ppm) ml) hours) Total Sugars (%) ph Colour Phenols (mg/l) Alcohol (%) Volatile acidity (% acetic acid) Higher alcohols (mg/l) Caffeine (ppm) 670.78 1.01 3.80 3.10 499.89 7.93 0.026 96.37 753.44 79.68 7.34 61.40 508.26 0.78 3.82 2.77 489.83 7.94 0.026 87.11 735.41 79.92 7.90 79.80 667.04 1.15 3.79 2.88 493.91 7.98 0.029 97.68 749.96 78.42 7.34 223 Antioxida Over All nt activity acceptabil (%) ity
Table 4.63 Physico-chemical and sensory characteristics of apple tea wine according to innoculum size as prepared by RSM design Inoculumsize TSS (ob) (%) Rate of Fermenta Titratab Free Reducing Total ph fermentatio tion le Sulphur Sugars Sugars n (M. fall efficiency acidity dioxide (mg/100 (%) (%) (% MA) (ppm) ml) o B/24 Colour Phenols Alcohol (mg/l) (%) Volatile Higher Caffeine acidity alcohols (ppm) (% acetic (mg/l) Antioxida Over All nt activity acceptabil (%) ity acid) hours) 2.50 8.49 1.44 76.12 0.94 55.60 679.03 1.09 3.81 3.01 483.67 8.12 0.027 99.63 748.95 78.33 7.35 5.00 7.71 1.54 73.33 0.87 65.80 512.17 0.80 3.81 2.72 487.29 7.93 0.027 86.86 736.33 80.01 7.89 7.50 8.31 1.46 73.57 0.94 55.40 658.79 1.08 3.77 2.97 510.13 7.80 0.027 94.41 754.45 79.77 7.33 224
to 7.65 ob and the trend of change in TSS during maturation is also shown in figure 4.51. Highest TSS (8.00 ob) was observed in apple tea wine at 0 month of storage which was at par with apple tea wine of 3rd month of storage and the lowest (7.65 ob) was recorded on 6th month of storage. There was non-significant difference amongst the different wood chip treatments. However, highest TSS (7.87 ob) was observed in apple tea wine treated with Quercus spp. wood chips and the lowest (7.77 ob) was in control apple tea wine. The interaction of storage intervals and treatments was non-significant and it was revealed that TSS ranged between 7.60 to 8.00 ob among the different treatments. The highest TSS was observed in 0 month wine (8.00 ob) and lowest (7.60 ob) in 6 month matured control apple tea wine and apple tea wine matured with Bombax spp.. It is discernible from the data that with advancement of maturation period from 0 to 6 month, a significant increase in reducing sugars was observed from 502 to 539 mg/100 ml (Table 4.64). The trend of change in reducing sugars during maturation is also shown in figure 4.52. Highest reducing sugars (539 mg/100 ml) was observed in apple tea wine at 6th month of storage which was at par with apple tea wine of 3rd month of storage and the lowest (502 mg/100 ml) was recorded on 0 month of storage. Difference amongst the different wood chip treatments was non-significant for reducing sugars. However, highest reducing sugars (528 mg/100 ml) was observed in apple tea wine treated with Quercus spp. wood chips and the lowest (521 mg/100 ml) was in control apple tea wine. The interaction of storage intervals and treatments was non-significant and it was observed that reducing sugars ranged between 502 mg/100 ml to 545 mg/100 ml among the different treatments. The highest reducing sugars was observed in 6 month matured apple tea with Quercus spp. wood chips (545 mg/100 ml) and lowest (502 mg/100 ml) in apple tea wine at 0 month of storage. The data (Table 4.64) further revealed in case of total sugars there were non-significant differences among the different storage intervals, wood chips treatment and their interaction. However, with advancement of maturation period there was slight decrease in total sugar. Highest total sugars content (0.638 %) was observed on 0 month of storage and the lowest (0.626 %) was recorded in apple tea wine at 6th month of storage. Figure 4.53 also showing the trend of 225
Table 4.64 Effect of different wood chips treatments on TSS, reducing sugars and total sugars during maturation of apple tea wine TSS (ob) Wood chips treatment Reducing sugars (mg/100 ml) Total sugars (%) 0 month 3 month 6 month Mean 0 month 3 month 6 month Mean 0 month 3 month 6 month Mean T1 (Acacia spp.) 8.00 7.80 7.70 7.83 502 535 542 527 0.638 0.632 0.627 0.632 T2 (Quercus spp.) 8.00 7.90 7.70 7.87 502 537 545 528 0.638 0.631 0.626 0.632 T3 (Bombax spp.) 8.00 7.90 7.60 7.83 502 530 537 523 0.638 0.630 0.627 0.632 T4 (Control) 8.00 7.70 7.60 7.77 502 526 533 521 0.638 0.630 0.625 0.631 Mean CD(p=0.05) 8.00 7.83 7.65 502 532 539 0.638 0.631 0.626 Storage Intervals (I) 0.17 Storage Intervals (I) 8 Storage Intervals (I) NS Treatments (T) NS Treatments (T) NS Treatments (T) NS IXT NS IXT NS IXT NS 226
change in total sugars during maturation. All the wood chips treatments recorded similar amount of total sugars (0.632 %) except control apple tea wine (0.631 %). Among the interaction between storage intervals and treatments, highest total sugars (0.638 %) was observed in apple tea wine at 0 month of storage and lowest (0.625 %) in 6 month matured control apple tea wine. 8.1 T1 (Acacia) T2 (Quercus) T3 (Bombax) T4 (Control) 8.0 TSS (ob) 7.9 7.8 7.7 7.6 7.5 0 3 6 Maturation period (months) Figure 4.51 Effect of different wood chips treatment on TSS (ob) of apple tea wine at different storage intervals of time 550 T1 (Acacia) T2 (Quercus) T3 (Bombax) T4 (Control) Reducing Sugars (mg/100ml) 540 530 520 510 500 490 0 3 6 Maturation period (months) Figure 4.52 Effect of different wood chips treatment on reducing sugars (mg/100ml) of apple tea wine at different storage intervals of time 227
0.640 T1 (Acacia) T2 (Quercus) T3 (Bombax) T4 (Control) 0.638 Total sugars (%) 0.636 0.634 0.632 0.630 0.628 0.626 0.624 0 3 6 Maturation period (months) Figure 4.53 Effect of different wood chips treatment on total sugars (mg/100ml) of apple tea wine at different storage intervals of time Titratable acidity, ph and volatile acidity In Table 4.65 the effect of different wood chips treatment and maturation on titratable acidity, ph and volatile acidity of apple tea wine is summarized. It is evident from the data that with passage of maturation period from 0 to 6 month, a significant decrease in titratable acidity was observed from 1.02 to 0.86 %. The trend of change in titratable acidity during maturation is also shown in figure 4.54. Highest titratable acidity (1.02 %) was observed in apple tea wine at 0 month of storage and the lowest (0.86 %) was recorded on 6th month of storage. Among the different wood chips treatments, highest titratable acidity (0.96 %) was observed in apple tea wine treated with Acacia spp. wood chips and the lowest (0.91 %) was in apple tea wine treated with Quercus spp. and Bombax spp. wood chips which was at par with control apple tea wine. The interaction of storage intervals and treatments was non-significant and it was revealed that titratable acidity ranged between 0.83 to 1.02 % among the different treatments. The highest titratable acidity was observed in 0 month wine (1.02 %) and lowest (0.83 %) in 6 month matured apple tea wine with Quercus spp. Table 4.65 further revealed that highest ph (3.89) was observed in apple tea wine at 3rd month of storage and the lowest (3.69) was recorded on 0 and 6th 228
Table 4.65 Effect of different wood chips treatments on titratable acidity, ph and volatile acidity during maturation of apple tea wine Wood chips treatment Titratable acidity (% malic acid) ph Volatile Acidity (% acetic acid) 0 month 3 month 6 month Mean 0 month 3 month 6 month Mean 0 month 3 month 6 month Mean T1 (Acacia spp.) 1.02 0.96 0.89 0.96 3.69 3.98 3.70 3.79 0.028 0.028 0.029 0.028 T2 (Quercus spp.) 1.02 0.89 0.83 0.91 3.69 3.82 3.68 3.73 0.028 0.029 0.030 0.029 T3 (Bombax spp.) 1.02 0.88 0.84 0.91 3.69 3.97 3.71 3.79 0.028 0.030 0.032 0.030 T4 (Control) 1.02 0.94 0.87 0.94 3.69 3.80 3.68 3.72 0.028 0.029 0.030 0.029 Mean CD(p=0.05) 1.02 0.92 0.86 3.69 3.89 3.69 0.028 0.029 0.030 Storage Intervals (I) 0.02 Storage Intervals (I) 0.08 Storage Intervals (I) NS Treatments (T) 0.03 Treatments (T) NS Treatments (T) NS IXT NS IXT NS IXT NS 229
month of storage. Among the different wood chips treatments, highest ph (3.79) was observed in apple tea wine treated with Acacia spp. and Bombax spp. wood chips and the lowest (3.72) was in control apple tea wine. The interaction of storage intervals and treatments was non-significant and it was revealed that ph ranged between 3.68 to 3.98 % among the different treatments. The highest ph was observed in 3 month matured apple tea wine with Acacia spp. (3.98) and lowest (3.68) in 6 month matured control apple wine and apple tea wine with Quercus spp. It is also discernible from the data (Table 4.65) that difference for volatile acidity was non-significant among the different storage intervals, wood chips treatment and their interaction. With the passage of storage interval, there was very slight increase in volatile acidity. Highest volatile acidity (0.030 %) was observed in apple tea wine at 6th month of storage and the lowest (0.028 %) was recorded on 0 month of storage. The trend of change in volaile acidity during maturation is also shown in figure 4.55. Among the different wood chips treatments, highest volatile acidity (0.030 %) was observed in apple tea wine treated with Bombax spp. wood chips and the lowest (0.028 %) was in apple tea wine treated with Acacia spp. wood chips. The interaction of storage intervals and treatments revealed that highest volatile acidity was observed in 6 month matured apple tea wine with Bombax spp. (0.032 %) and lowest (0.029 %) in 6 month matured control apple wine. Titratable acidty (as % MA) 1.05 T1 (Acacia) T2 (Quercus) T3 (Bombax) T4 (Control) 1.00 0.95 0.90 0.85 0.80 0 3 6 Maturation period (months) Figure 4.54 Effect of different wood chips treatment on titratable acidity (%) of apple tea wine at different storage intervals of time 230
Volatile acidity (as % acetic acid) 0.033 T1 (Acacia) T2 (Quercus) T3 (Bombax) T4 (Control) 0.032 0.031 0.030 0.029 0.028 0.027 0 3 6 Maturation period (months) Figure 4.55 Effect of different wood chips treatment on volatile acidity (%) of apple tea wine at different storage intervals of time Ethanol, higher alcohols and colour Table 4.66 summarizes the effect different wood chips treatment and maturation on ethanol, higher alcohols and colour of apple tea wine. It is revealed from the data that with advancement of maturation period from 0 to 6 month, a significant decrease in ethanol was observed from 8.15 to 7.89 %. The trend of change in ethanol during maturation is also shown in figure 4.56. Highest ethanol (8.15 %) was observed in apple tea wine at 0 month of storage and the lowest (7.89 %) was recorded on 6th month of storage. Highest ethanol (8.10 %) was observed in apple tea wine treated with Quercus spp. wood chips and the lowest (7.93 %) was in apple tea wine treated with Acacia spp. wood chips. The interaction of storage intervals and treatments was non-significant and it was revealed that highest ethanol was observed in 0 month wine (8.15 %) and lowest (7.74 %) in 6 month matured apple tea wine matured with Acacia spp. It is discernible from the data that with advancement of maturation period from 0 to 6 month, a significant increase in higher alcohols was observed from 94 to 109 mg/l (Table 4.66). The trend of change in higher alcohols during maturation is also shown in figure 4.57. Highest higher alcohols (109 mg/l) were observed in apple tea wine at 6th month of storage and the lowest (94 mg/l) was recorded on 0 month of storage. There was the significant difference amongst the 231
Table 4.66 Effect of different wood chips treatments on ethanol, higher alcohols and colour during maturation of apple tea wine Wood chips treatment Ethanol (% v/v) Higher alcohols (mg/l) Colour (OD 440 nm) 0 month 3 month 6 month Mean 0 month 3 month 6 month Mean 0 month 3 month 6 month Mean T1 (Acacia spp.) 8.15 7.90 7.74 7.93 94 102 106 101 2.45 2.04 1.62 2.04 T2 (Quercus spp.) 8.15 8.11 8.04 8.10 94 109 114 106 2.45 2.12 1.63 2.07 T3 (Bombax spp.) 8.15 8.01 7.92 8.03 94 106 110 104 2.45 2.19 1.64 2.09 T4 (Control) 8.15 7.95 7.84 7.98 94 98 106 99 2.45 2.24 1.66 2.12 Mean CD(p=0.05) 8.15 7.99 7.89 94 104 109 2.45 2.15 1.64 Storage Intervals (I) 0.10 Storage Intervals (I) 2 Storage Intervals (I) 0.03 Treatments (T) 0.12 Treatments (T) 3 Treatments (T) 0.04 IXT NS IXT NS IXT 0.07 232
different wood chip treatments. Highest higher alcohols (106 mg/l) were observed in apple tea wine treated with Quercus spp. wood chips which was at par with apple tea wine treated with Bombax spp. wood chips and the lowest (99 mg/l) was in control apple tea wine. The interaction of storage intervals and treatments was non-significant and it was observed that higher alcohols ranged between 94 to 114 mg/l among the different treatments. The highest higher alcohols were observed in 6 month matured apple tea with Quercus spp. wood chips (114 mg/l) and lowest (94 mg/l) in apple tea wine at 0 month of storage. The data (Table 4.66) further revealed that in case of colour there were significant differences among the different storage intervals, wood chips treatment and their interaction. With advancement of maturation period there was decrease in colour value (Fig. 4.58). Among the different wood chips treatments, highest OD for colour (2.45) was observed on 0 month of storage and the lowest (1.64) was recorded in apple tea wine at 6th month of storage. Highest OD for colour (2.12) was observed in control apple tea wine and the lowest (2.04) was in apple tea wine treated with Acacia spp. wood chips. Among the interaction between storage intervals and treatments, highest OD for colour (2.45) was observed in apple tea wine at 0 month of storage and lowest (1.62) in 6 month matured apple tea wine matured with Acacia spp. 8.2 Ethanol (% v/v) 8.1 8.0 7.9 T1 (Acacia) T2 (Quercus) T3 (Bombax) T4 (Control) 7.8 7.7 0 3 6 Maturation period (months) Figure 4.56 Effect of different wood chips treatment on ethanol (%) of apple tea wine at different storage intervals of time 233
115 T1 T2 T3 T4 Higher alcohols (mg/l) 110 (Acacia) (Quercus) (Bombax) (Control) 105 100 95 90 0 3 6 Maturation period (months) Figure 4.57 Effect of different wood chips treatment on higher alcohols (mg/l) of apple tea wine at different storage intervals of time 2.6 T1 T2 T3 T4 Colour (440 nm) 2.4 (Acacia) (Quercus) (Bombax) (Control) 2.2 2.0 1.8 1.6 1.4 0 3 6 Maturation period (months) Figure 4.58 Effect of different wood chips treatment on colour (OD 440 nm) of apple tea wine at different storage intervals of time Total phenols, caffeine and antioxidant activity In Table 4.67, the effect of different wood chips treatment and maturation on total phenols, caffeine and antioxidant activity of apple tea wine is summarized. It is evident from the data that with passage of maturation period from 0 to 6 month, a significant decrease in total phenols was observed from 480 to 444 mg/l. The trend of change in total phenols during maturation is also shown in figure 4.59. Highest total phenols (480 mg/l) was observed in apple tea wine at 0 month of storage and the lowest (444 mg/l) was recorded on 6th month of storage. Among the different wood chips treatments, highest total phenols (472 mg/l) was observed in apple tea wine treated with Quercus spp. wood chips 234
which was at par with the apple tea wine treated with Bombax spp. and Acacia spp. and the lowest (441 mg/l) was in control apple tea wine. The interaction of storage intervals and treatments was non-significant and it was revealed that total phenols ranged between 412 to 480 mg/l among the different treatments. The highest total phenols was observed in 0 month wine (480 mg/l) and lowest (412 mg/l) in 6 month matured control apple tea wine. Significantly highest caffeine (824 ppm) was observed in apple tea wine at 0 month of storage and it reduced to 743 ppm on 6th month of storage which was at par with 3rd month of storage (Table 4.67). The trend of change in caffeine content during maturation is also shown in figure 4.60. Among the different wood chips treatments there was non-significant difference. However, highest caffeine (789 ppm) was observed in apple tea wine treated with Quercus spp. and the lowest (768 ppm) was in control apple tea wine. The interaction of storage intervals and treatments was also non-significant and it was observed that caffeine ranged between 727 to 824 ppm among the different treatments. The highest caffeine was observed in 0 month matured apple tea wine (824 ppm) and lowest (727) in 6 month matured control apple tea wine. It is also discernible from the data (Table 4.67) that the difference for antioxidant activity was non-significant among the different storage intervals, wood chips treatment and their interaction. With the passage of storage interval, there was non-significant increase in antioxidant activity. The trend of change in antioxidant activity during maturation is also shown in figure 4.61. Highest antioxidant activity (81.71 %) was observed in apple tea wine at 6th month of storage and the lowest (79.71 %) was recorded on 0 month of storage. Among the different wood chips treatments, highest antioxidant activity (80.80 %) was observed in apple tea wine treated with Quercus spp. wood chips and the lowest (80.53 %) was in apple tea wine treated with Bombax spp. wood chips. The interaction of storage intervals and treatments revealed that highest antioxidant activity was observed in 6 month matured apple tea wine with Quercus spp. (82.17 %) and lowest (79.17 %) in apple tea wine at 0 month of storage. 235
Table 4.67 Effect of different wood chips treatments on total phenols, caffeine and antioxidant activity during maturation of apple tea wine Wood chips treatment Total phenols (mg/l) Caffeine (ppm) Antioxidant activity (%) 0 month 3 month 6 month Mean 0 month 3 month 6 month Mean 0 month 3 month 6 month Mean T1 (Acacia spp.) 480 463 448 464 824 766 741 777 79.71 80.53 81.56 80.60 T2 (Quercus spp.) 480 476 461 472 824 787 756 789 79.71 80.53 82.17 80.80 T3 (Bombax spp.) 480 468 454 468 824 771 749 781 79.71 80.33 81.56 80.53 T4 (Control) 480 432 412 441 824 755 727 768 79.71 80.53 81.56 80.60 Mean CD(p=0.05) 480 460 444 824 770 743 79.71 80.48 81.71 Storage Intervals (I) 17 Storage Intervals (I) 30 Storage Intervals (I) NS Treatments (T) 19 Treatments (T) NS Treatments (T) NS IXT NS IXT NS IXT NS 236
T1 T2 T3 T4 Total phenols (mg/l) 500 (Acacia) (Quercus) (Bombax) (Control) 480 460 440 420 400 0 3 6 Maturation period (months) Figure 4.59 Effect of different wood chips treatment on total phenols (mg/l) of apple tea wine at different storage intervals of time 840 T1 T2 T3 T4 Caffeine (ppm) 820 (Acacia) (Quercus) (Bombax) (Control) 800 780 760 740 720 0 3 6 Maturation period (months) Figure 4.60 Effect of different wood chips treatment on caffeine (ppm) of apple tea wine at different storage intervals of time 82.5 T1 T2 T3 T4 Antioxidant activity (%) 82.0 (Acacia) (Quercus) (Bombax) (Control) 81.5 81.0 80.5 80.0 79.5 0 3 6 Maturation period (months) Figure 4.61 Effect of different wood chips treatment on antioxidant activity (%) of apple tea wine at different storage intervals of time 237
Protein content, amino acids and total esters Table 4.68 summarizes the effect different wood chips treatment and maturation on protein content, amino acids and total esters of apple tea wine. There was significant increase in protein content with advancement of maturation period from 0 to 6 month. The trend of change in protein content during maturation is also shown in figure 4.62. Highest protein content (1291 mg/100 ml) was observed in apple tea wine at 6th month of storage which was at par with the apple tea wine at 3rd month of storage and the lowest (1015 mg/100 ml) was recorded on 0 month of storage. There was non-significant difference among the different wood chips treatments, however, highest protein content (1202 mg/100 ml) was observed in apple tea wine treated with Bombax spp. wood chips and the lowest (1183 mg/100 ml) was in control apple tea. The interaction between storage intervals and treatments was also non-significant and it was revealed that highest protein content was observed in 6th month matured apple tea wine with Bombax spp. (1307 mg/100 ml) and lowest (1015 mg/100 ml) in in apple tea wine at 0 month of storage. It is discernible from the data that with advancement of maturation period from 0 to 6 month, a significant increase in amino acids was observed from 633 to 821 mg/100 ml (Table 4.68). The trend of change in amino acids during maturation is also shown in figure 4.63. Highest amino acids (821 mg/100 ml) was observed in apple tea wine at 6th month of storage which was at par with apple tea wine at 3rd month of storage and the lowest (633 mg/100 ml) was recorded on 0 month of storage. There was the significant difference amongst the different wood chip treatments. Highest amino acids (814 mg/100 ml) was observed in apple tea wine treated with Bombax spp. wood chips and the lowest (711 mg/100 ml) was in apple tea wine treated with Acacia spp. wood chips which was at par with control apple tea wine. The interaction of storage intervals and treatments was also significant and it was observed that amino acids ranged between 633 to 910 mg/100 ml among the different treatments. The highest amino acids was observed in 6 month matured apple tea with Bombax spp. wood chips (910 mg/100 ml) and lowest (633 mg/100 ml) in apple tea wine at 0 month of storage. 238
Table 4.68 Effect of different wood chips treatments on protein content, amino acids and total esters during maturation of apple tea wine Wood chips treatment Protein content (mg/100 ml) Amino acids (mg/100 ml) Total esters (mg/l) 0 month 3 month 6 month Mean 0 month 3 month 6 month Mean 0 month 3 month 6 month Mean T1 (Acacia spp.) 1015 1274 1290 1193 633 743 757 711 114 143 161 139 T2 (Quercus spp.) 1015 1280 1298 1198 633 803 827 755 114 146 163 141 T3 (Bombax spp.) 1015 1285 1307 1202 633 899 910 814 114 144 166 141 T4 (Control) 1015 1262 1272 1183 633 767 790 730 114 135 151 133 Mean CD(p=0.05) 1015 1275 1291 633 803 821 114 142 160 Storage Intervals (I) 82 Storage Intervals (I) 18 Storage Intervals (I) 7 Treatments (T) NS Treatments (T) 20 Treatments (T) NS IXT NS IXT 36 IXT NS 239
With advancement of maturation period there was significant increase in total esters value (Table 4.68). The trend of change in total esters during maturation is also shown in figure 4.64. Highest total esters (160 mg/l) were observed in apple tea wine at 6th month of storage and the lowest (114 mg/l) was recorded on 0 month of storage. There was non-significant difference among the different wood chips treatments. However, highest total esters (141 mg/l) were observed in apple tea wine treated with Bombax spp. and apple tea wine treated with Quercus spp. wood chips and the lowest (133 mg/l) was in control apple tea wine. Among the interaction between storage intervals and treatments, highest total esters (166 mg/l) was observed in 6 month matured apple tea wine treated with Bombax spp. and lowest (114 mg/l) was in apple tea wine at 0 month of storage. 1350 T1 T2 T3 T4 Protein content (mg/100 ml) 1300 (Acacia) (Quercus) (Bombax) (Control) 1250 1200 1150 1100 1050 1000 0 3 6 Maturation period (months) Figure 4.62 Effect of different wood chips treatment on protein content (mg/100 ml) of apple tea wine at different storage intervals of time 950 T1 T2 T3 T4 Amino acid (mg/100 ml) 900 (Acacia) (Quercus) (Bombax) (Control) 850 800 750 700 650 600 0 3 6 Maturation period (months) Figure 4.63 Effect of different wood chips treatment on amino acid content (mg/100 ml) of apple tea wine at different storage intervals of time 240
170 T1 T2 T3 T4 Total esters (mg/l) 160 (Acacia) (Quercus) (Bombax) (Control) 150 140 130 120 110 0 3 6 Maturation period (months) Figure 4.64 Effect of different wood chips treatment on total esters (mg/l) of apple tea wine at different storage intervals of time Antimicrobial activity Table 4.69 summarizes the antimicrobial activity of apple tea wine at 0, 3rd and 6th month of storage (Plate 13). It is evident from the data that with advancement of maturation period from 0 to 6 month, a decrease in antimicrobial activity against all the test microorganisms was observed. On the 0 month of storage, antimicrobial activity of apple tea wine against the different test microorganisms i.e. Staphylococcus aureus, Listeria monocytogenes, Escherichia coli, Enterococcus faecalis and Bacillus cereus was 10 mm, 8 mm, 10 mm, 10.5 mm and 8.5 mm respectively. Table 4.69 further revealed the antimicrobial activity of 3 month matured apple tea wine and it was observed that against the different test microorganisms i.e. Staphylococcus aureus, Listeria monocytogenes, Escherichia coli, Enterococcus faecalis and Bacillus cereus antimicrobial activity ranged between 9.5-10.5 mm, 6-6.5 mm, 9-10 mm, 9-10 mm and 8-9 mm respectively. Perusal of result (Table 4.69) revealed the antimicrobial activity of 6 month matured apple tea wine and it was observed that against the different test microorganisms i.e. Staphylococcus aureus, Listeria monocytogenes, Escherichia coli, Enterococcus faecalis and Bacillus cereus antimicrobial activity ranged between 7-8.5 mm, 3-3.5 mm, 8.5-9.5 mm, 8-9 mm and 7-8 mm respectively. 241
Table 4.69 Effect of different wood chips treatments on antimicrobial activity (inhibition zone in mm) during maturation of apple tea wine Test microorganisms Maturation period (in months) 3 Month 0 Month Staphylococcus aureus Listeria monocytogenes Escherichia coli Enterococcus faecalis Bacillus cereus 6 Month 10.00 Bombax spp. 10.00 Quercus spp. 9.50 Control 10.00 8.00 6.50 6.00 6.00 6.00 3.00 3.50 0 0 10.00 9.50 9.00 9.00 10.00 9.00 8.50 8.50 9.50 10.50 9.00 10.00 9.50 9.00 9.00 8.50 8.00 9.00 8.50 9.00 8.50 8.50 8.00 8.00 8.00 7.50 7.00 242 Acacia spp. 10.50 Bombax spp. 8.50 Quercus spp. 8.00 Control 7.00 Acacia spp. 8.00
Cluster analysis of the different apple tea wines matured with different wood chips The data obtained from physico-chemical analysis of apple tea wine was analysed using cluster analysis with rescaled distance cluster analysis. The dendrogram representation of the different treatments of the apple tea wine matured with different wood chips using physico-chemical characteristics showed in Fig. 4.65 and it was observed that all the wines at 0 month of storage had the same composition so they formed the separate cluster. It was also observed that the physico-chemical characteristic of 3 month and 6 month matured apple tea wines did not present any classification among them, so these grouped in one cluster. Figure 4.65 Dendrogram of different treatments of apple tea wine matured with different wood chips using various physico-chemical characteristics analysed based on rescaled distance 243
0 Month Wine Matured 3 Month Matured Wine 6 Month Matured Wine Staphylococcus aureus Listeria monocytogenes Escherichia coli Enterococcus faecalis Bacillus cereus Plate: 13 Antimicrobial activity (inhibition zone in mm) of apple tea wine matured different wood chips during maturation of apple tea wine
4.6.2 Sensory evaluation of 6 month matured wine Table 4.70 summarizes the results of composite scoring of 6 month matured apple tea wine with different wood chips. Colour of Quercus spp. treated apple tea wine scored the highest which was at par with the apple tea wine treated with Bombax spp. whereas for appearance Quercus spp. treated apple tea wine was preferred to by the judges than other treatments. Aroma of apple tea wine treated with Quercus spp. chips was scored the best. Volatile acidity and total acidity of all the wood chips treated apple tea wines were non-significant. Sweetness of Quercus spp. treated apple tea wine scored better than those by Acacia spp. and Bombax spp.. Body of apple tea wine treated with Acacia spp. was preferred by the most of judges. Flavour and overall acceptability of apple tea wine treated with Bombax spp. was scored highest. For bitterness, Quercus spp. and for astringency Bombax spp. and control treated apple tea wine was scored the best. Total score of all the sensory attribute was the highest in apple tea wine treated with Quercus spp. chips. In most of the attributes, the apple wine treated with Quercus spp. chips scored more than other apple tea wines. Based on this, it can be stated that Quercus spp. chips is the best wood for maturation than Acacia spp. and Bombax spp. (Fig.66). On the basis of rating, apple tea wines matured with different wood chips after 6 month of storage falls in the superior category, whereas, apple tea wine matured without wood chips after 6 month of storage falls in the standard category. Figure 4.67 shows the spider web diagram of sensory qualities of apple tea wines of different wood chips treatment. Figure 4.66 Comparison of overall sensory scores of apple tea wines treated different wood chips treatments after 6 month of storage 244
Table 4.70 Effect of different wood chips treatments on sensory characteristics of apple tea wine Different wood Appearance Colour Aroma chips treatments Max. Score Volatile Total acidity acidity Sweetness Body Flavour Bitterness Astringency Overall Total impression 2 2 4 2 2 1 1 2 1 1 2 20 T1 (Acacia spp.) 1.68 1.66 3.54 1.59 1.56 0.68 0.86 1.81 0.77 0.68 1.71 16.54 T2 (Quercus spp.) 1.79 1.80 3.68 1.51 1.56 0.72 0.84 1.84 0.79 0.67 1.75 16.95 T3 (Bombax spp.) 1.72 1.69 3.63 1.52 1.56 0.63 0.79 1.87 0.76 0.70 1.78 16.65 T4 (Control) 1.62 1.64 3.40 1.51 1.49 0.61 0.76 1.79 0.75 0.70 1.73 16.00 CD (P=0.05) 0.08 NS 0.08 NS NS 0.07 NS NS NS NS NS 0.25 Ratings: Superior (17-20); standard (13-16); below standard (9-12); unacceptable or spoiled (1-8) 245
Figure 4.67 Spider web diagram of sensory qualities of 6 month matured apple tea wine with different wood chips 246
4.7 EFFECT OF BLENDING OF DIFFERENT CONCENTRATION OF APPLE JUICE WITH MATURED APPLE TEA WINE ON THE PHYSICO-CHEMICAL AND SENSORY QUALITY CHARACTERISTICS OF TEA CIDER 4.7.1 Physico-chemical characteristics of tea cider Total soluble solids Table 4.71 revealed the effect of blending of different concentration of apple juice with matured apple tea wine on TSS of tea cider. It was observed that with increase in the concentration of apple juice from 30 to 50 %, a significant increase in TSS was observed from 8.70 to 9.05 ob. Lowest TSS (8.70 ob) was observed in tea cider having 30 % apple juice and the highest (9.05 ob) was recorded in tea cider having 50 % apple juice which was at par with tea cider having 40 % apple juice. Maturation of the apple tea wine with different wood chips did not influence the TSS of tea cider significantly. However, highest TSS (9.07 ob) was observed in tea cider prepared from apple tea wine matured with Acacia spp. wood chips and the lowest (8.80 ob) was in tea cider prepared from control apple tea wine. The interaction of different concentration of apple juice and matured apple tea wine was non-significant and it was revealed that TSS ranged between 8.40 to 9.20 ob among the different treatments. The highest TSS was observed in tea cider having 50 % apple juice and apple tea wine matured with Acacia spp. wood chips (9.20 ob) and lowest (8.40 ob) in tea cider having 30 % apple juice and control apple tea wine. Table: 4.71 Effect of blending of different concentration of apple juice with matured apple tea wine on TSS (ob) of tea cider Wood chips treatment T1 (Acacia spp.) T2 (Quercus spp.) T3 (Bombax spp.) T4 (Control) Mean CD (P=0.05) Treatments (T) Apple juice concentration (C) IXT 30 9.00 8.60 8.80 8.40 8.70 Apple juice concentration (%) 40 50 Mean 9.00 9.20 9.07 9.00 9.00 8.87 9.00 9.00 8.93 9.00 9.00 8.80 9.00 9.05 NS 0.17 NS 247
Reducing sugars It is discernible from the data that with increase in the concentration of apple juice from 30 to 50 %, a significant increase in reducing sugars was observed from 1061 to 1128 mg/100 ml (Table 4.72). Tea cider having 30 % apple juice recorded the lowest reducing sugars (1061 mg/100 ml) which was at par with tea cider having 40 % apple juice and significantly highest (1128 mg/100 ml) was recorded in tea cider having 50 % apple juice. Maturation of the apple tea wine with different wood chips influenced the reducing sugars of tea cider significantly. Highest reducing sugars (1110 mg/100 ml) was observed in tea cider prepared from apple tea wine matured with Quercus spp. wood chips and the lowest (1047 mg/100 ml) was in tea cider prepared from control apple tea wine. The interaction of different concentration of apple juice and matured apple tea wine was also significant and it was revealed that reducing sugars ranged between 1035 to 1162 mg/100 ml among the different treatments. The highest reducing sugars was observed in tea cider having 50 % apple juice and apple tea wine matured with Quercus spp. wood chips (1162 mg/100 ml) and lowest (1035 mg/100 ml) in tea cider having 30 % apple juice and control apple tea wine. Table: 4.72 Effect of blending of different concentration of apple juice with matured apple tea wine on reducing sugars (mg/100 ml) of tea cider Wood chips treatment T1 (Acacia spp.) T2 (Quercus spp.) T3 (Bombax spp.) T4 (Control) Mean CD (P=0.05) Treatments (T) Apple juice concentration (C) IXT Apple juice concentration (mg/100g) 30 40 50 Mean 1068 1074 1152 1098 1081 1088 1162 1110 1062 1068 1143 1091 1035 1050 1056 1047 1061 1070 1128 11 9 19 Total sugars Perusal of data showed that with increase in the concentration of apple juice from 30 to 50 %, a significant increase in total sugars was observed from 2.94 to 4.94 % (Table 4.73). Tea cider having 30 % apple juice recorded the 248
lowest total sugars (2.94 %) and highest (4.94 %) was recorded in tea cider having 50 % apple juice. Maturation of the apple tea wine with different wood chips influenced the total sugars of tea cider significantly. Highest total sugars (3.98 %) was observed in tea cider prepared from apple tea wine matured with Quercus spp. wood chips which was at par with tea cider prepared from apple tea wine matured with Acacia spp. wood chips and the lowest (3.72 %) was in tea cider prepared from control apple tea wine which was at par with tea cider prepared from apple tea wine matured with Bombax spp. wood chips. There was also significant difference among the interaction between different concentration of apple juice and matured apple tea wine and it was observed that total sugars ranged between 2.78 to 5.01 % among the different treatments. The highest total sugars was observed in tea cider having 50 % apple juice and apple tea wine matured with Quercus spp. wood chips (5.01 %) and lowest (2.78 %) in tea cider having 30 % apple juice and control apple tea wine. Table: 4.73 Effect of blending of different concentration of apple juice with matured apple tea wine on total sugars (%) of tea cider Wood chips treatment T1 (Acacia spp.) T2 (Quercus spp.) T3 (Bombax spp.) T4 (Control) Mean CD (P=0.05) Treatments (T) Apple juice concentration (C) IXT 30 3.05 3.01 2.90 2.78 2.94 Apple juice concentration (%) 40 50 3.48 4.96 3.91 5.01 3.58 4.81 3.42 4.97 3.60 4.94 Mean 3.83 3.98 3.76 3.72 0.11 0.09 0.19 Titratable acidity Table 4.74 shows the effect of blending of different concentration of apple juice with matured apple tea wine on titratable acidity of tea cider. It is evident from the data that a decrease in titratable acidity was observed from 0.63 to 0.56 % with increase in the concentration of apple juice from 30 to 50 %. Highest titratable acidity (0.63 %) was observed in tea cider having 30 % apple juice which was at par with tea cider having 40 % apple juice and the lowest (0.56 %) was recorded tea cider having 50 % apple juice. There was non249
significant difference among the tea cider prepared from apple tea wine matured with different wood chips. However, highest titratable acidity (0.61 %) was observed in tea cider prepared from apple tea wine matured with Acacia spp. wood chips and the lowest (0.57 %) was in tea cider prepared from apple tea wine matured with Bombax spp. wood chips. The interaction between different concentration of apple juice and matured apple tea wine was non-significant and it was revealed that titratable acidity ranged between 0.54 to 0.65 % among the different treatments. The highest titratable acidity was observed in tea cider having 30 % apple juice and apple tea wine matured with Acacia spp. wood chips (0.65 %) and lowest (0.54 %) in tea cider having 50 % apple juice and apple tea wine matured with Bombax spp. wood chips. Table: 4.74 Effect of blending of different concentration of apple juice with matured apple tea wine on titratable acidity (% malic acid) of tea cider Wood chips treatment T1 (Acacia spp.) T2 (Quercus spp.) T3 (Bombax spp.) T4 (Control) Mean CD (P=0.05) Treatments (T) Apple juice concentration (C) IXT 30 0.65 0.64 0.60 0.64 0.63 Apple juice concentration (%) 40 50 Mean 0.61 0.57 0.61 0.60 0.55 0.60 0.58 0.54 0.57 0.60 0.57 0.60 0.60 0.56 NS 0.03 NS ph Table 4.75 revealed the effect of blending of different concentration of apple juice with matured apple tea wine on ph of tea cider. It was observed that with increase in the concentration of apple juice from 30 to 50 %, a nonsignificant decrease in ph was observed from 3.79 to 3.74. Highest ph (3.79) was observed in tea cider having 30 % apple juice and the lowest (3.74) was recorded in tea cider having 50 % apple juice. Maturation of the apple tea wine with different wood chips also did not influence the ph of tea cider significantly. However, highest ph (3.78) was observed in tea cider prepared from apple tea wine matured with Acacia spp. wood chips and the lowest (3.75) was in tea cider 250
prepared from apple tea wine matured with Quercus spp. wood chips and tea cider prepared from control apple tea wine. The interaction of different concentration of apple juice and matured apple tea wine was non-significant. The highest ph was observed in tea cider having 30 % apple juice and apple tea wine matured with Acacia spp. wood chips (3.81) and lowest (3.73) in tea cider having 50 % apple juice and apple tea wine matured with Quercus spp. wood chips. Table: 4.75 Effect of blending of different concentration of apple juice with matured apple tea wine on ph of tea cider Wood chips treatment T1 (Acacia spp.) T2 (Quercus spp.) T3 (Bombax spp.) T4 (Control) Mean CD (P=0.05) Treatments (T) Apple juice concentration (C) IXT 30 3.81 3.78 3.79 3.77 3.79 Apple juice concentration (%) 40 50 Mean 3.77 3.75 3.78 3.75 3.73 3.75 3.77 3.75 3.77 3.75 3.74 3.75 3.76 3.74 NS NS NS Ethanol It is discernible from the data that with increase in the concentration of apple juice from 30 to 50 %, a significant decrease in ethanol was observed from 5.69 to 4.13 % (Table 4.76). Tea cider having 30 % apple juice recorded the significantly highest ethanol (5.69 %) and lowest (4.13 %) was recorded in tea cider having 50 % apple juice. Maturation of the apple tea wine with different wood chips influenced the ethanol of tea cider non-significantly. Highest ethanol (4.99 %) was observed in tea cider prepared from apple tea wine matured with Quercus spp. wood chips and the lowest (4.79 %) was in tea cider prepared from apple tea wine matured with Acacia spp. wood chips. The interaction of different concentration of apple juice and matured apple tea wine was also non-significant and it was revealed that ethanol ranged between 4.04 to 5.80 % among the different treatments. The highest ethanol was observed in tea cider having 30 % apple juice and apple tea wine matured with Quercus spp. wood chips (5.80 %) and lowest (4.04 %) in tea cider having 50 % apple juice and apple tea wine matured with Acacia spp. wood chips. 251
Table: 4.76 Effect of blending of different concentration of apple juice with matured apple tea wine on ethanol (%) of tea cider Wood chips treatment T1 (Acacia spp.) T2 (Quercus spp.) T3 (Bombax spp.) T4 (Control) Mean CD (P=0.05) Treatments (T) Apple juice concentration (C) IXT 30 5.59 5.80 5.71 5.66 5.69 Apple juice concentration (%) 40 50 Mean 4.75 4.04 4.79 4.99 4.18 4.99 4.92 4.19 4.94 4.87 4.09 4.87 4.88 4.13 NS 0.18 NS Colour Perusal of data showed that with increase in the concentration of apple juice from 30 to 50 %, a significant decrease in colour value was observed from 1.97 to 1.73 (Table 4.77). Table: 4.77 Effect of blending of different concentration of apple juice with matured apple tea wine on colour (OD 440 nm) of tea cider Wood chips treatment T1 (Acacia spp.) T2 (Quercus spp.) T3 (Bombax spp.) T4 (Control) Mean CD (P=0.05) Treatments (T) Apple juice concentration (C) IXT 30 2.06 1.94 1.96 1.92 1.97 Apple juice concentration (%) 40 50 Mean 1.83 1.78 1.89 1.85 1.82 1.87 1.78 1.68 1.81 1.76 1.64 1.77 1.81 1.73 NS 0.08 NS Tea cider having 30 % apple juice recorded the highest OD for colour (1.97) and lowest (1.73) was recorded in tea cider having 50 % apple juice. Maturation of the apple tea wine with different wood chips influenced the OD for colour of tea cider non-significantly. Highest OD for colour (1.89) was observed in tea cider prepared from apple tea wine matured with Acacia spp. wood chips 252
the lowest (1.77) was in tea cider prepared from control apple tea wine. There was also non-significant difference among the interaction between different concentration of apple juice and matured apple tea wine. The highest OD for colour was observed in tea cider having 30 % apple juice and apple tea wine matured with Acacia spp. wood chips (2.06) and lowest (1.64) in tea cider having 50 % apple juice and control apple tea wine. Total phenols Table 4.78 shows the effect of blending of different concentration of apple juice with matured apple tea wine on total phenols of tea cider. Table: 4.78 Effect of blending of different concentration of apple juice with matured apple tea wine on total phenols (mg/l) of tea cider Wood chips treatment T1 (Acacia spp.) T2 (Quercus spp.) T3 (Bombax spp.) T4 (Control) Mean CD (P=0.05) Treatments (T) Apple juice concentration (C) IXT 30 405 497 434 415 438 Apple juice concentration (%) 40 50 Mean 367 347 373 392 358 416 392 364 396 365 361 380 379 357 9 7 15 It is evident from the data that a significant decrease in total phenols was observed from 438 to 357 mg/l with increase in the concentration of apple juice from 30 to 50 %. Highest total phenols (438 mg/l) were observed in tea cider having 30 % apple juice and the lowest (357 mg/l) were recorded tea cider having 50 % apple juice. There was also a significant difference among the tea cider prepared from apple tea wine matured with different wood chips. However, highest total phenols (416 mg/l) was observed in tea cider prepared from apple tea wine matured with Quercus spp. wood chips and the lowest (373 mg/l) was in tea cider prepared from apple tea wine matured with Acacia spp. wood chips which was at par with tea cider prepared from control apple tea wine. The interaction between different concentration of apple juice and matured apple tea wine was significant and it was revealed that total phenols ranged between 347 to 253
497 mg/l among the different treatments. The highest total phenols was observed in tea cider having 30 % apple juice and apple tea wine matured with Quercus spp. wood chips (497 mg/l) and lowest (347 mg/l) in tea cider having 50 % apple juice and apple tea wine matured with Acacia spp. wood chips. Caffeine Table 4.79 revealed the effect of blending of different concentration of apple juice with matured apple tea wine on caffeine content of tea cider. It was observed that with increase in the concentration of apple juice from 30 to 50 %, a significant decrease in caffeine content was observed from 520 to 392 ppm. Highest caffeine content (520 ppm) was observed in tea cider having 30 % apple juice and the lowest (392 ppm) was recorded in tea cider having 50 % apple juice. Maturation of the apple tea wine with different wood chips also did not influence the caffeine content of tea cider significantly. However, highest caffeine content (463 ppm) was observed in tea cider prepared from apple tea wine matured with Quercus spp. wood chips and the lowest (442 ppm) was in tea cider prepared from control apple tea wine. The interaction of different concentration of apple juice and matured apple tea wine was also non-significant. The highest caffeine content was observed in tea cider having 30 % apple juice and apple tea wine matured with Acacia spp. wood chips (534 ppm) and lowest (382 ppm) in tea cider having 50 % apple juice and control apple tea wine. Table: 4.79 Effect of blending of different concentration of apple juice with matured apple tea wine on caffeine content (ppm) of tea cider Wood chips treatment T1 (Acacia spp.) T2 (Quercus spp.) T3 (Bombax spp.) T4 (Control) Mean CD (P=0.05) Treatments (T) Apple juice concentration (C) IXT 30 534 528 518 501 520 Apple juice concentration (%) 40 50 Mean 457 392 461 461 401 463 458 395 457 441 382 442 454 392 NS 16 NS 254
Protein content It is discernible from the data that with increase in the concentration of apple juice from 30 to 50 %, a significant decrease in protein content was observed from 766 to 668 mg/100 ml (Table 4.80). Tea cider having 30 % apple juice recorded the significantly highest protein content (766 mg/100 ml) and lowest (668 mg/100 ml) was recorded in tea cider having 50 % apple juice. Maturation of the apple tea wine with different wood chips influenced the protein content of tea cider significantly. Highest protein content (832 mg/100 ml) was observed in tea cider prepared from control apple tea wine and the lowest (654 mg/100 ml) was in tea cider prepared from apple tea wine matured with Acacia spp. wood chips. The interaction of different concentration of apple juice and matured apple tea wine was also significant and it was revealed that protein content ranged between 621 to 914 mg/100 ml among the different treatments. The highest protein content was observed in tea cider having 30 % apple juice and control apple tea wine (914 mg/100 ml) and lowest (621 mg/100 ml) in tea cider having 50 % apple juice and apple tea wine matured with Acacia spp. wood chips. Table: 4.80 Effect of blending of different concentration of apple juice with matured apple tea wine on protein content (mg/100 ml) of tea cider Wood chips treatment T1 (Acacia spp.) T2 (Quercus spp.) T3 (Bombax spp.) T4 (Control) Mean CD (P=0.05) Treatments (T) Apple juice concentration (C) IXT 30 675 755 721 914 766 Apple juice concentration (%) 40 50 Mean 664 621 654 706 655 705 698 695 705 880 701 832 737 668 11 9 18 Amino acids Table 4.81shows the effect of blending of different concentration of apple juice with matured apple tea wine on amino acids of tea cider. It is evident from the data that a significant decrease in amino acids was observed from 784 to 705 mg/100 ml with increase in the concentration of apple juice from 30 to 50 %. 255
Highest amino acids (784 mg/100 ml) were observed in tea cider having 30 % apple juice and the lowest (705 mg/100 ml) were recorded tea cider having 50 % apple juice. There was also a significant difference among the tea cider prepared from apple tea wine matured with different wood chips. Highest amino acids (770 mg/100 ml) was observed in tea cider prepared from apple tea wine matured with Bombax spp. wood chips which was at par with tea cider prepared from apple tea wine matured with Quercus spp. wood chips and the lowest (720 mg/100 ml) was in tea cider prepared from apple tea wine matured with Acacia spp. wood chips which was at par with tea cider prepared from control apple tea wine. The interaction between different concentration of apple juice and matured apple tea wine was also significant and it was revealed that amino acids ranged between 691 to 821 mg/100 mg among the different treatments. The highest amino acids was observed in tea cider having 30 % apple juice and apple tea wine matured with Bombax spp. wood chips (821 mg/100 mg) and lowest (691 mg/100 ml) in tea cider having 50 % apple juice and apple tea wine matured with Acacia spp. wood chips. Table: 4.81 Effect of blending of different concentration of apple juice with matured apple tea wine on amino acids (mg/100 ml) of tea cider Wood chips treatment T1 (Acacia spp.) T2 (Quercus spp.) T3 (Bombax spp.) T4 (Control) Mean CD (P=0.05) Treatments (T) Apple juice concentration (C) IXT 30 740 798 821 777 784 Apple juice concentration (%) 40 50 Mean 730 691 720 771 731 767 784 704 770 766 694 746 763 705 6 5 11 Antioxidant activity Perusal of data showed that with increase in the concentration of apple juice from 30 to 50 %, a non-significant increase in antioxidant activity was observed from 81.40 to 82.22 % (Table 4.82). Tea cider having 30 % apple juice recorded the lowest antioxidant activity (81.40 %) and highest (82.22 %) was recorded in tea cider having 50 % apple juice. Maturation of the apple tea wine 256
with different wood chips influenced the antioxidant activity of tea cider nonsignificantly. Highest antioxidant activity (82.03 %) was observed in tea cider prepared from apple tea wine matured with Bombax spp. wood chips and the lowest (81.83 %) was in tea cider prepared from apple tea wine matured with Acacia spp. wood chips and tea cider prepared from apple tea wine matured with Quercus spp. wood chips. The interaction between different concentration of apple juice and matured apple tea wine was also non-significant and it was observed that antioxidant activity ranged between 81.15 to 82.38 % among the different treatments. The highest antioxidant activity was observed in tea cider having 50 % apple juice and apple tea wine matured with Acacia spp. wood chips (82.38 %) and lowest (81.15 %) in tea cider having 30 % apple juice and apple tea wine matured with Acacia spp. wood chips. Table: 4.82 Effect of blending of different concentration of apple juice with matured apple tea wine on antioxidant activity (%) of tea cider Wood chips treatment T1 (Acacia spp.) T2 (Quercus spp.) T3 (Bombax spp.) T4 (Control) Mean CD (P=0.05) Treatments (T) Apple juice concentration (C) IXT 30 81.15 81.35 81.76 81.35 81.40 Apple juice concentration (%) 40 50 81.97 82.38 81.97 82.17 82.17 82.17 82.17 82.17 82.07 82.22 Mean 81.83 81.83 82.03 81.90 NS NS NS Antimicrobial activity Table 4.83 summarizes the antimicrobial activity of tea cider prepared by blending of different concentration of apple juice with matured apple tea wine (Plate 14). It is evident from the data that the antimicrobial activity of tea cider having 30 % apple juice against the different test microorganisms i.e. Staphylococcus aureus, Listeria monocytogenes, Escherichia coli, Enterococcus faecalis and Bacillus cereus was 8.5-10 mm, 7-8 mm, 7.5-9 mm, 7-7.5 mm and 6.5-8 mm respectively. 257
Table 4.83 Effect of blending of different concentration of apple juice with matured apple tea wine on antimicrobial activity (inhibition zone in mm) of tea cider Test microorganisms Apple tea wine and juice ratio 70:30 (30 % Apple juice) Staphylococcus aureus Listeria monocytogenes Escherichia coli Enterococcus faecalis Bacillus cereus Bombax spp. 9.00 Quercus spp. 10.00 0.00 60:40 (40 % Apple juice) 9.50 Acacia spp. 8.50 Bombax spp. 9.00 Quercus spp. 10.00 7.00 7.00 8.00 0.00 9.00 8.00 7.50 8.50 7.50 7.50 7.00 7.00 7.00 6.50 Control 50:50 (50 % Apple juice) 8.50 Acacia spp. 9.00 Bombax spp. 8.50 Quercus spp. 9.00 0.00 0.00 0.00 0.00 8.50 8.00 7.50 8.50 7.50 7.50 7.50 7.50 8.00 8.00 8.00 8.00 258 Control 9.00 Acacia spp. 9.00 0.00 0.00 0.00 7.50 7.00 6.00 7.50 7.00 7.00 7.00 7.00 7.00 7.50 7.50 8.00 7.00 7.00 Control
Table 4.83 further revealed the antimicrobial activity of tea cider having 40 % apple juice against the different test microorganisms i.e. Staphylococcus aureus, Listeria monocytogenes, Escherichia coli, Enterococcus faecalis and Bacillus cereus was 8.5-10 mm, nil, 7.5-8.5 mm, 7-7.5 mm and 7.5-8 mm respectively. Perusal of result (Table 4.83) revealed the antimicrobial activity of tea cider having 50 % apple juice against the different test microorganisms i.e. Staphylococcus aureus, Listeria monocytogenes, Escherichia coli, Enterococcus faecalis and Bacillus cereus was 8.5-9 mm, nil, 6-7.5 mm, 7 mm and 7-8 mm respectively. Cluster analysis of the different tea cider prepared by blending of different concentrations of apple juice with apple tea wine The data obtained from physico-chemical analysis of tea cider was analysed using cluster analysis with rescaled distance cluster analysis. The dendrogram representation of the different treatments of the tea cider using physico-chemical characteristics showed in Fig. 4.68 and it was observed that tea cider having 30 % apple juice and apple tea wine matured with different wood chips and tea cider having 40 % apple juice and apple tea wine matured with different wood chips grouped in one cluster, whereas, tea cider having 50 % apple juice and apple tea wine matured with different wood chips or control apple tea wine grouped in a separate cluster. Tea cider having 30 % apple juice and control apple tea wine and tea cider having 40 % apple juice and control apple tea wine grouped in entirely separate cluster. Clustering was mainly on the basis of percentage of apple juice, whereas, maturation of wine with different wood chips did not show any distinguish character among them. 259
Tea Cider 70:30 (30 % Apple juice) 60:40 (40 % Apple juice) 50:50 (50 % Apple juice) Staphylococcus aureus Listeria monocytogenes Escherichia coli Enterococcus faecalis Bacillus cereus Plate: 14 Antimicrobial activity (inhibition zone in mm) of different treatments of tea ciders