Prediction of juice quality from fruit analysis Mabel Martínez Vega PhD Student Supervisors: Brian Grout Torben Toldam-Andersen Dvoralai Wulfsohn Slide 1
Fruit Material Cultivars Measurement Dates Levels Quality traits Aroma Rajka Holsteiner Cox Ingrid Marie 1 2 1 2 1 Sugar Firmness Acidity Sug/acid Starch Color Aroma sensory 2 Slide 2
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Variability Apple orchard The Pometum, Taastrup- Denmark Slide 4
Sugar content, 10 trees (Pometum) Variety: 'Aroma'. Date 1 Variety: 'Rajka'. Date 1 18 18 16 16 Sugar SSC Content (%Brix) (%Brix) 14 12 10 8 6 4 2 0 0 1 2 3 4 5 6 7 8 9 10 11 Tree Sugar SSC Content (%Brix) (%Brix) 14 12 10 8 6 4 2 0 0 1 2 3 4 5 6 7 8 9 10 11 Tree Slide 5
Science and Variability Author/s Method Area of study Barrit et al. 1987, Krishnaprakash et al. 1983 De Silva et al. 2000, Kainer et al. 2001, Skrede et al. 2011, Woodward et al. 2011), Gutrie and Walsh 1999, McGlone et al. 2002, Hernández et al. 2003, Chauchard et al. 2004, Qing and Zude 2007, Mendoza et al. 2012 Random sampling Random sampling Random sampling Effects of fruit position and light Fruit variation Fruit quality prediction H.J. Gundersen, 1987 The fractionator, systematic sampling Medicine Gardi et al. 2006, 2007; Dorph- Petersen et al. 2000, Different uses of Systematic Uniform Random sampling Medicine, Slide 6
What is sampling about? Sample Population Slide 7
Applications of SUR sampling: The fractionator Number of flowers in a tree, fruit yield Source: (Maletti et al. 2004, Wulfsohn et al. 2011) Slide 8
Objectives 1. To obtain representative samples in order to study the quality variability of early and late season apple varieties 2. To explore relationships between fruit and juice quality 3. To evaluate feasibility of non-destructive methods to predict fruit and juice quality Slide 9
Sugar content, 10 trees (Pometum) Variety: 'Aroma'. Date 1 Variety: 'Rajka'. Date 1 18 18 16 16 Sugar SSC Content (%Brix) (%Brix) 14 12 10 8 6 4 2 0 0 1 2 3 4 5 6 7 8 9 10 11 Tree Sugar SSC Content (%Brix) (%Brix) 14 12 10 8 6 4 2 0 0 1 2 3 4 5 6 7 8 9 10 11 Tree Slide 10
Sugar Content and fruit position on the tree Variety: 'Aroma'. Date 1 Variety: Rajka D1 18 18 16 16 14 14 SSC (%Brix) 12 10 8 6 SSC (%Brix) 12 10 8 6 4 4 2 2 0 low high 0 low high Low = apples under 1.56 m High = apples over 1.56 m (In agreement with: Barritt et al. 1987, Volz et al. 1995, Warrington et al. 1996) Slide 11
An example of skin color and sugar content 9,2 11 11,1 11,3 11,4 11,5 11,7 11,9 12,1 12,3 12,4 12,5 12,7 13,3 13,5 14,1 15,1 Slide 12 Aroma 2010
Commercial Orchard: Fuji Chile (7.6ha) Frequency 30% 25% 20% 15% 10% 5% Distribution of of Caliber fruit (18.2 size kg class box) Sample Packing Export 0% 135 120 110 100 90 80 70 60 50 40 Size class Caliber (mm) N= 70 apples Parameter Standard Range in sample % of export quality Firmness (kg) 6.4-9-1 5.9-10-4 86% Sugar content (%Brix) > 12% 12.1 18.6 100% Starch Æble temadag index (10 Taastrup, 14-11-2012 5-7 4-10 43% Slide scale) 13
The Samples who showed extreme values of sugar seem to come from the upper part of the trees No clear relationships between internal quality and skin color were found It was possible to produce an early fruit quality evaluation for a commercial apple plantation Slide 14
Objectives 1. To obtain representative samples in order to study the quality variability of early and late season apple varieties 2. To explore relationships between fruit and juice quality 3. To evaluate feasibility of non-destructive methods to predict fruit and juice quality Slide 15
Quality Fruit Quality Aroma Rajka Holsteiner Cox Ingrid Marie 5 days 10 Days 5 days 10 Days 5 days 10 Days 5 days 10 Days No. 102 94 96 90 111 115 105 76 Sugar/acid 15.8 16.9 21.9 24.5 17.7 19.7 18.2 20.7 Streif 0.13 0.04 0.07 0.06 0.08 0.06 0.18 0.08 Quality Juice Quality Aroma Rajka Holsteiner Cox Ingrid Marie 5 days 10 Days 5 days 10 Days 5 days 10 Days 5 days 10 Days Sugar/acid 14.3 17.1 20.3 23.8 17.8 20.5 18.5 25.76 Slide 16
Juice quality Slide 17
Aroma Rajka H. Cox Ingrid Marie normal apple smell fresh apple flavor Complex apple smell complex fruit tones Date 1 Cis-3-hexenol Ethyl-2- methylpropanoate Date 2 2-propanone Butyl 2 methyl butanoate Ethyl-2-butenoate Date 1 Methyl propanoate Ethyl-2- methylpropanoate Date 2 Cis-3-hexenol Date 1 1-pentanol Hexanol 2-methyl-1-propanol 2-methyl-1-propanol Pentanal 2- pentanone 2-nonanone 2-heptanone Methyl acetate* Ethyl acetate* Date 2 Propanol 2-butanol 2-methyl butanal 2-butanone Propyl acetate Butyl propanoate Date 1 Butanal Hexanal* t-2-hexenal pentil acetate methyl butanoate ethyl butanoate propyl butanoate butyl butanoate methyl hexanoate Date 1 1-pentanol Hexanol 2-methyl-1-propanol 2-methyl-1-propanol Pentanal 2- pentanone 2-nonanone 2-heptanone Methyl acetate* Ethyl acetate* Harvest date Slide 18
Apple varieties collected at the end of the harvest season developed more complex and appealing aroma taste after a postharvest period sugar/acidity ratio between fruit and their juice was similar Slide 19
Objectives 1. To obtain representative samples in order to study the quality variability of early and late season apple varieties 2. To explore relationships between fruit and juice quality 3. To evaluate feasibility of non-destructive methods to predict fruit and juice quality Slide 20
VIS/NIR spectroscopy?? Slide 21
VIS/NIR Spectroscopy Slide 22
Variety Aroma 5 days 10 days Slide 23
Fruit sugar content calibration model (%Brix) Variety Aroma Predicted (%Brix) R=0.78 SEC=0.66 (%Brix) Actual (%Brix) Slide 24
Fruit sugar content bands of interest (%Brix) Predictive spectral regions for sugar content. Variety Aroma Slide 25
The juice calibration model for sugar content obtained from fruit spectra 14 13 R = 0.92 SEC= 0.95 Hcox B-1 B-2 Ingrid B Predicted Brix (%) 12 11 10 9 8 7 Hcox A-2 Rajka B-1 Rajka Rajka B-2 Hcox A-1 A-1 Aroma Aroma B-1 B-2 Rajka A-2 Aroma A-2 Aroma A-1 Ingrid A-1 Ingrid A-2 6 5 5 6 7 8 9 10 11 12 13 14 Actual Brix (%) Slide 26
Conclusions It was possible to model fruit quality from sets of representative samples Postharvest results in juice quality enhancement but better quality control of quality in the field is necesary to avoid post harvest fruit disorders (e.g. Patulin) Slide 27
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