METABOLITE ANALYSIS, ENVIRONMENTAL FACTORS, AND A TRANSGENIC APPROACH TO UNDERSTANDING STRAWBERRY (FRAGARIA X ANANASSA) FLAVOR

Transcription

1 METABOLITE ANALYSIS, ENVIRONMENTAL FACTORS, AND A TRANSGENIC APPROACH TO UNDERSTANDING STRAWBERRY (FRAGARIA X ANANASSA) FLAVOR By MICHAEL LEE SCHWIETERMAN A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA

2 2013 Michael Lee Schwieterman 2

3 To my family, friends, and colleagues 3

4 ACKNOWLEDGMENTS I thank my Ph.D. committee for their patience and guidance. Deepest appreciation to my advisor, Dr. David Clark, for providing direction, encouragement and sound advice when it was needed most, as well as, providing the freedom to pursue research in an unfamiliar system. I recognize Dr. Thomas Colquhoun for his continued dedication to my professional development and positive outlook throughout my Ph.D. education. Portions of this work are supported by grants from USDA Specialty Crop Block Grant. Graduate funding is provided by USDA National Needs Fellowship. Great gratitude is extended to Timothy Johnson, HHMI Undergraduate Scholar, and Yasmin Dweik, for assistance with screening transgenic lines for volatiles and transcript abundance and Elizabeth Jaworski for assistance with Fragaria volatile analysis. 4

5 TABLE OF CONTENTS page ACKNOWLEDGMENTS... 4 LIST OF TABLES... 8 LIST OF FIGURES... 9 LIST OF ABBREVIATIONS ABSTRACT CHAPTER 1 INTRODUCTION AND LITERATURE REVIEW Introduction Fruit Development and Regulation Strawberry Flavor Methyl Anthranilate Biosynthesis Fragaria x ananassa Perception and Integration of Flavor Research Objectives Identifying Flavor-Related Metabolite Targets Using Psychophysics Field and Postharvest Environment Factors Influencing Flavor-Related Metabolites A Transgenic Approach to Introduce F. vesca Volatile Compound in F. x ananassa STRAWBERRY FLAVOR: DIVERSE CHEMICAL COMPOSITIONS, A SEASONAL INFLUENCE, AND EFFECTS ON SENSORY PERCEPTION Background Results Progression of Harvest Season Affects Metabolic Content and Perceived Quality of Strawberry Overall Liking is Subject to Ratings of Sweetness, Flavor, and Texture Texture Liking Correlates to Fruit Firmness Sweetness Intensity is a Result of Sugar Content Sourness Intensity is Partially Explained by Titratable Acidity Flavor Intensity is Influenced by Total and Specific Volatile Content Specific Volatiles Enhance Sweetness Intensity Independent of Sugars Discussion Materials and Methods Plant Material Volatile Analysis

6 Sugars and Acids Quantification Firmness Determination Sensory Analysis Statistical Analysis ENGINEERING OF THE AROMA FLAVOR VOLATILE METHYL ANTHRANILATE IN PETUNIA AND STRAWBERRY Background Results Methyl Anthranilate Content among Fragaria ZmAAMT1.1 Expression Analysis in Transgenic Plants Overexpression construct and plant transformation Petunia expression analysis Strawberry expression analysis ZmAAMT1.1 Volatile Analysis in Transgenic Plants Discussion Future Work Materials and Methods Plant Material Generation of Transgenic ZmAAMT1.1 Plants Overexpression construct Plant transformation and regeneration RNA Isolation Petunia Strawberry Expression Analysis Volatile Analysis Statistical Analysis EFFECTS OF ENHANCED LIGHT ENVIRONMENTS ON POSTHARVEST VOLATILE PROFILES OF STRAWBERRY FESTIVAL Background Results Postharvest Exposure to Narrow-Bandwidth Light Alters Strawberry Volatile Content Red and Black Plastic Mulch Reflective light qualities from red and black mulch Strawberry volatile profiles are not consistently different between red and black mulch treatments Consumers do not distinguish or prefer strawberry from red or black plastic mulch Discussion Materials and Methods Postharvest Narrow-Bandwidth Light Treatment Red and Black Plastic Mulch Field Conditions

7 Flavor Panel Volatile Analysis Statistical Analysis LIST OF REFERENCES BIOGRAPHICAL SKETCH

8 LIST OF TABLES Table page 2-1 Means of consumer, physical, and biochemical measures Standard errors of consumer, physical, and biochemical measures Fruit attribute bivariate fit to harvest week Fruit attribute bivariate fir to consumer measure Multiple regression for identification of sweetness enhancing volatiles Index of CAS registry number, chemical name, and formula Photosynthetically active, red, and far-red radiation reflected by selective reflective mulch Consumer panels do not perceive differences between red and black plastic mulch grown strawberries Volatile analysis does not detect consistent differences between red and black plastic mulch grown strawberries

9 LIST OF FIGURES Figure page 2-1. Cluster analysis of strawberry samples and quantified metabolites Season environmental conditions Individual sugars and total volatiles regressed against season progression Regression of hedonic and sensory measures to physical and chemical fruit attributes Volatile chemical structures Alternative methyl anthranilate biosynthetic pathways in Zea mays and Vitis labrusca Identification of methyl anthranilate in Fragaria Methyl anthranilate content among various lines of Fragaria species Binary vector for stable transformation of petunia and strawberry with ZmAAMT ZmAAMT1.1 transcript abundance in overexpressing Petunia x hybrida cv. Mitchell Diploid ZmAAMT1.1 transcript abundance in overexpressing Petunia x hybrida cv. Mitchell Diploid Emission of methyl anthranilate from petunia flowers over-expressing ZmAAMT Identification of methyl anthranilate in petunia flower over-expressing ZmAAMT ZmAAMT1.1 transcript abundance in overexpressing Fragaria x ananassa cv. Strawberry Festival Spectroradiometer readings of the light qualities used in postharvest treatments Effect of light treatments on selected volatile compounds in Fragaria x. ananassa cv. Strawberry Festival Spectrum of light reflected from red and black plastic mulch

10 LIST OF ABBREVIATIONS CDS CM COA DMF Coding sequence CHORISMATE MUTASE Coenzyme A 3(2H)-furanone, 4-methoxy-2,5-dimethyl- F. Fragaria FID GC GLMS LED MS PNOS NOST NPTII Flame ionization detector Gas chromatograph General labeled magnitude scale Light emitting diode Mass spectrometer NOPALINE SYNTHASE 3 promotor NOPALINE SYNTHASE 3 terminator NEOMYCIN PHOSPHOTRANSFERASE II P. Petunia PAR PFMV 34S QRT-PCR SQRT-PCR SSC TA VLAMAT ZMAAMT Photosynthetic active radiation Figwort mosaic virus 34S promoter Quantitative real time polymerase chain reaction Semi-quantitative polymerase chain reaction Soluble solids content Titratable acidity Vitis labrusca ANTHRANILOYL-CoA:METHANOL ACYLTRANSFERASE Zea mays ANTHRANILIC ACID METHYL TRANSFERASE 10

11 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy METABOLITE ANALYSIS, ENVIRONMENTAL FACTORS, AND A TRANSGENIC APPROACH TO UNDERSTANDING STRAWBERRY (FRAGARIA X ANANASSA) FLAVOR Chair: David G. Clark Major: Plant Molecular and Cellular Biology By Michael Lee Schwieterman August 2013 Fresh strawberries (Fragaria x ananassa) are valued for their red color, juicy texture, distinct aroma, and sweet fruity flavor. To ensure continued consumption, flavor must be high in quality, but defining this complex trait has proven to be difficult. This work presents a metabolite perspective on the perception, variation, and alteration of strawberry fruit flavor to increase consumer acceptability. In the primary study, genetic and environmentally induced variation among strawberry is exploited by simultaneously assaying fruit for: inventories of volatile compounds, sugars, and organic acids; physical measures of titratable acidity, soluble solids content, and firmness; and consumer hedonic and sensory responses. Psychophysics analysis determines seasonal effects and fruit attributes influencing hedonics and sensory perception of strawberry fruit. Seasonal progression negatively influences soluble solids content, primarily through sucrose, leading to decreased volatile content. These alterations are perceivable because sweetness intensity, flavor intensity, and texture liking significantly influence overall liking through variations in sugar concentrations, volatiles, and 11

12 firmness. Specific aroma volatiles make contributions to perceived sweetness independent of fruit sugar concentration. Volatiles that increase perception of sweetness without adding sugar will have far-reaching effects in food chemistry, and also provides targets for future breeding efforts of consumer defined traits. The biosynthesis of an underrepresented volatile in commercial germplasm, methyl anthranilate, is the target of genetically engineering Petunia x hybrida Mitchell Diploid and Strawberry Festival. Expression of Zea mays ANTHRANILIC ACID METHYL TRANSFERASE 1.1 will hypothetically enhance its aroma or flavor. Petunia flowers with expression emit methyl anthranilate at levels similar to Fragaria vesca. Expression is confirmed in over twenty T0 lines of Strawberry Festival. Consumer panels assaying petunia and strawberry with methyl anthranilate phenotype will assist in assaying this volatiles influence on perception. Metabolite inventory of diverse strawberry fruit coupled with consumer panels identifies rare and important compounds associated with strawberry flavor. Transgenic efforts will determine methyl anthranilate influence on consumers. Furthermore, exploration of environmental manipulation provides some prospective technologies for altering strawberry volatile profiles. Whether through breeding, transgenics, or environmental manipulation increasing the flavor of strawberry will ensure the current trend of increasing consumption of this highly nutritious food. 12

13 CHAPTER 1 INTRODUCTION AND LITERATURE REVIEW Introduction Modern strawberry, Fragaria x ananassa, is the product of a recent anthropomorphic botanical hybridization of otherwise geographically isolated species. Hybrids of two octoploid species, male North American F. virginiana and female South American F. chiloensis, began appearing in European gardens during the 18th century (Darrow, 1966). Comparison of genomic microsatellite markers among F. x ananassa cultivars and a geographically diverse collection of progenitors reveals this relatively young crop species is founded on narrow genetic diversity (Chambers et al., 2013), yet is cultivated in most arable regions of the world at a level over 4.3 million metric tons of fruit annually (Hancock, 1999; UN, 2013). The genus Fragaria is distributed globally throughout temperate and tropical zones, with the most widespread distribution belonging to F. vesca. Other Fragaria possess more geographically restricted distributions, most of which are within or bordering that of F. vesca. A specific example is that of South American F. chiloensis. Also, the genus exhibits a natural ploidy diversity ranging from diploid to decaploid (Folta and Davis, 2006; Hancock, 1999). The relatively small stature and herbaceous nature of strawberry strongly contradicts that of typical Rosaceae, but the perennial life cycle is mutual. The morphologically distinct aggregate accessory fruit of strawberry, in which the achenes are exposed on a swollen fleshy receptacle, has been a prize of domestication for over two millennia (Hancock, 1999). Modern fully ripe fruit of F. x ananassa is characterized by its large size, vibrant red color, reduced firmness, distinct aroma, and sweet fruity flavor (Brummell and 13

14 Harpster, 2001; Hong and Wrolstad, 1990; Schieberle and Hofmann, 1997; Ulrich et al., 1997; Whitaker et al., 2011). Strawberry is also a rich source of phenolics, vitamins, and minerals contributing to the nutritional quality of the fruit and promoting human health through antioxidant, anti-inflammatory, antimicrobial, anti-allergy, anti-hypertensive and anticancer properties (Brown et al., 2012; Giampieri et al., 2013; Giampieri et al., 2012; Mikulic-Petkovsek et al., 2012; Tulipani et al., 2008). Ever increasing production and consumption of strawberry (UN, 2013) is driven by demand for high quality fruit, secondarily beneficial to our health, and facilitated by intensive modern horticulture and sophisticated breeding practices. Fruit Development and Regulation Fertilization of the many ovary/ovule inflorescence of strawberry gives rise to the aggregate fruit (Perkins-Veazie, 1995). Here, the achenes (true fruit) are fixed on the epidermis, the outermost layer of the swollen receptacle (false fruit), also consisting of a cortex and internal pith (Suutarinen et al., 1998). Fruit development and ripening is coordinated and regulated with embryo formation and achene maturation most notably through achene localized auxin biosynthesis (Given et al., 1988; Nitsch, 1950). The three stages of non-climacteric, auxin dependent strawberry fruit development; division, expansion and ripening, involve gains in diameter and fresh weight. During this transition color shifts from green to white to dark red in about forty days after anthesis (Zhang et al., 2011a). Increasing auxin during division and expansion stages promotes growth, peaking prior to fruit whitening when achenes mature. Decreased auxin content coincides with fruit maturation and ripening, thus auxin biosynthesis promotes fruit growth but inhibits ripening prior to achene maturation (Fait et al., 2008; Given et al., 1988). 14

15 The dynamic state of fruit ripening is exemplified by the nearly 250 cdnas with significant differential expression (177 up, 70 down) in red compared to green fruit determined using a microarray of 1700 probes (Aharoni et al., 2000). A physical attribute of later ripening stages is the reduction of firmness. Dissolution of middle lamella, which functions in cell-to-cell adhesion, contributes to the melting texture of fruit. Further, a transcript with 200-fold greater expression in ripening fruit compared to green, POLYGALACTURONASE, contributes to fruit softening by aiding in catalytic cell wall disassembly (Brummell and Harpster, 2001; Quesada et al., 2009; Trainotti et al., 1999). Other differentially expressed transcripts are related to primary and secondary metabolism, and transcription of multiple ripening associated genes are initiated by reduced auxin (Aharoni et al., 2002; Aharoni and O'Connell, 2002; Castillejo et al., 2004; Manning, 1994, 1998). Transcriptional reconfiguration coordinates the final shift for strawberry ripening. This highly metabolically active process is visualized by the late accumulation of the predominant red pigment, pelargonidin 3-glucoside (Hoffmann et al., 2006), an anthocyanin synthesized from the primary metabolite phenylalanine (Fait et al., 2008). Of great metabolic interest in the final days of ripening is the accumulation of multiple sugars and organic acids, which culminates with peak volatile emissions (Menager et al., 2004). Strawberry Flavor The sweet fruity flavor and distinct aroma of a ripe strawberry is the result of a multifaceted metabolite mixture of sugars, organic acids and volatile compounds, which are coordinated at ripening through genetic and environmental factors. Early work in tomato correlated fruit acceptability to sweetness and flavor, which were also shown to be the result of sugar and volatile content (Baldwin et al., 1998). Glucose, fructose and 15

16 sucrose accumulate to high levels and account for over 7% of fresh berry weight (Menager et al., 2004). Citric acid and malic acid produce sour sensations at concentrations around two to three micromolar (Settle et al., 1986) and are two of the predominant organic acids in strawberry, in which total content is on the order of 50 millimolar (Mikulic-Petkovsek et al., 2012). The predominant classes of volatile compounds in ripe strawberry are esters, lactones, terpenes, aldehydes and characteristic furanones (Menager et al., 2004; Olbricht et al., 2008) A comparison of strawberry volatile studies underscores the complexity in defining strawberry aroma, as each source considers a highly variable subset of total volatiles (Hakala et al., 2002; Jetti et al., 2007; Olbricht et al., 2008; Schieberle and Hofmann, 1997; Ulrich et al., 1997). Methods such as odor value, aroma extract dilution analysis, and GC-olfactometry have been used to relate concentrations of volatiles in strawberry to perception through direct analysis or threshold determination (Zabetakis and Holden, 1997). These methodologies can be criticized for lack of physiological relevance as complex mixtures of volatiles are perceived entirely different than individual volatiles (Bartoshuk and Klee, 2013). These studies have identified butanoic acid, methyl ester ( ); butanoic acid, ethyl ester ( ); hexanoic acid, methyl ester ( ); hexanoic acid, ethyl ester ( ); 1,6-octadien-3-ol, 3,7-dimethyl- (linalool) ( ); butanoic acid, 2-methyl- ( ); and 2,5-dimethyl- 4-methoxy-2,3-dihydrofuran-3-one (DMF) ( ) as integral to strawberry aroma volatiles (Hakala et al., 2002; Jetti et al., 2007; Olbricht et al., 2008; Schieberle and Hofmann, 1997; Ulrich et al., 1997). Comparisons of consumer preference among a 16

17 variety of fresh strawberries and volatile analysis has described less preferable varieties as possessing less esters, more decalactones and hexanoic acid (Ulrich et al., 1997). During ripening, strawberry fruits become a nutrient sink and facilitate a metabolism resulting in the biochemical constituents of strawberry flavor. In developing strawberry a constant high sucrose sink strength (Basson et al., 2010) results in an active metabolism able to accumulate, synthesize, and spontaneously produce a diversity of primary and secondary metabolites (Fait et al., 2008). Transient transformation of strawberry fruit with a RNA interference construct targeting the predominant sucrose transporter responsible for sucrose accumulation results in arrested ripening. Decreased sucrose and abscisic acid content measured in arrested fruit indicates sucrose as a molecular signal in ripening (Jia et al., 2013). The constant influx of sucrose is primary to all other aspects of fruit metabolism. It is the source for alkanes, alcohols, aldehydes, ketones, esters, sugars, organic acids, fatty acids, furanones, amino acids, and anthocyanins, all of which increase in concentration at one point in development or ripening (Fait et al., 2008; Zhang et al., 2011a). Many of these classes also represent precursors of volatile production, thus facilitating a flux through biosynthetic pathways for the synthesis of some of the 360 identified volatile compounds detected across Fragaria (Du et al., 2011b; Maarse, 1991). Within a single fruit, only a fraction of volatiles are emitted and even fewer contribute to perceived aroma. Functional genomic work has characterized strawberry enzymes responsible for the synthesis of several volatile components of strawberry aroma. QUINONE OXIDOREDUCTASE, an enzyme with highly specialized function, is characterized to be responsible for 3(2H)-furanone, 4-hydroxy-2,5-dimethyl- 17

18 biosynthesis (Raab et al., 2006). This furanone is indicated to be paramount to strawberry aroma, in that six of six panelists detected an orthonasal and retronasal difference when absent in model juice (Schieberle and Hofmann, 1997). Also, this key aroma compound is a substrate of O-METHYLTRANSFERASE activity to produce 3(2H)-furanone, 4-methoxy-2,5-dimethyl- (DMF) (Lavid et al., 2002), which is less defining of strawberry odor (Schieberle and Hofmann, 1997). Two ALCOHOL ACYL TRANSFERASES are characterized in commercial strawberry, which accept a range of alcohols and acyl-coa substrates to produce a great diversity of esters, generally associated with fruit aroma. Also, the transcripts of these enzymes demonstrate fruit specific expression (Aharoni et al., 2000; Cumplido-Laso et al., 2012). Linalool and nerolidol are terpenes associated with many fruits and flowers. Volatile analysis, enzymatic characterization, and molecular markers have confirmed the genetic and biochemical ability to produce these compounds arises from NEROLIDOL SYNTHASE 1 (NES1). Biosynthetic ability is conferred to commercial F. x ananassa and most hybrid progenitors, but not hexaploid, tetraploid, or diploid species (Aharoni et al., 2004; Chambers et al., 2012). Differences in the presence or absence of volatile compounds exist in commercial material compared to wild germplasm. This variation in regards to flavor related metabolites is potentially a result of artificial selection prior or post hybridization. Domestication of F. chiloensis began at least 700 years prior to hybridization with F. virginiana (Finn et al., 2013). All accessions of F. chiloensis (4) and F. x ananassa (112) analyzed contain a linalool producing NES1 allele that is absent in F. vesca materials. Volatile analysis supports the allelic distribution across Fragaria species, particularly in 18

19 commercial material (Chambers et al., 2012; Pyysalo et al., 1979). On the other hand, methyl anthranilate is a common component of F. vesca, but relatively rare in F. x ananassa (Pyysalo et al., 1979; Ulrich et al., 2007). Determination of biochemical differences of strawberry aroma and correlated genetic elements can facilitate targeted approaches to alter flavor of commercial fruit. Methyl Anthranilate Biosynthesis Methyl anthranilate is an aromatic ester that is characteristic of Concord grape, Vitis labrusca. It has been used as a food additive to impart such flavor, for several decades. The compound has been identified in F. x ananassa: Mieze Schindler and F. vesca. However, it is essentially lacking in fruit produced by commercial cultivars (Ulrich et al., 2007). Enzymes of alternative pathways capable of producing methyl anthranilate are characterized in Zea mays (Koellner et al., 2010) and Vitis labrusca (Wang and De Luca, 2005) where volatile biosynthesis arises under herbivory or fruit ripening, respectively. ANTHRANILOYL-CoA:METHANOL ACYLTRANSFERASE of Vitis labrusca (VlAMAT) catalyzes an alcohol acyl-transfer among anthraniloyl-coenzyme A (anthraniloyl-coa) and methanol for methyl anthranilate biosynthesis. This ATP dependent reaction occurs in the grape where protein and methanol concentrations increase to relatively high levels in fruit following the onset of ripening (Wang and De Luca, 2005). Conversely, herbivory induced wound signaling results in up-regulation of ANTHRANILIC ACID METHYL TRNASFERASE 1.1 of Zea mays (ZmAAMT1.1) and anthranilic acid, which serves as the substrate for the S-adenosyl methionine dependent reaction (Koellner et al., 2010). Previously characterized, F. x ananassa STRAWBERRY ALCOHOL ACYLTRANSFERASE (FaSAAT) or a homolog may be 19

20 responsible for the production of methyl anthranilate endogenously as its reactivity with methanol has been confirmed. However, anthraniloyl-coa was not tested as a substrate, thus methyl anthranilate production by FaSAAT cannot be ruled out (Aharoni et al., 2000). A transgenic effort for methyl anthranilate biosynthesis in strawberry is attractive due to deficiency in commercial material, hypothetical lack of specificity for endogenous methyl anthranilate production, and multiple elucidated pathways in other plant species. Also, stable Agrobacterium transformation of strawberry is becoming routine with the first report in 1990 by Nehra (1990), despite long regeneration time and sensitivity to kanamycin antibiotic selection (Folta et al., 2006). Expedited assaying of gene function routinely relies on transient expression via Agrobacterium infiltration of fruit tissue (Hoffmann et al., 2006; Meng et al., 2009; Miyawaki et al., 2012). On the other hand, stable transformation is choice when developing materials tackling commercial interests of disease resistance (Chalavi et al., 2003; Schestibratov and Dolgov, 2005; Vellicce et al., 2006), fruit softening (Lee and Kim, 2011), fruit growth and development (Mezzetti et al., 2004), and aroma enhancement (Lunkenbein et al., 2006). The ease and existing infrastructure of vegetative propagation of strawberry is encouraging for the dissemination of transgenic commercial material. Fragaria x ananassa The allo-octoploid genome of F. x ananassa provides great diversity and adaptability for breeding efforts, but prevents use of lower ploidy material in the development of new cultivars. Inbreeding depression increases with each generation of related cross in strawberry; however with stringent parent selection genetic gains comparable to unrelated crosses are achievable (Shaw, 1997). Introgression of F. 20

21 chiloensis and F. virginiana is increasing and serves as a means of genetic diversity (Hancock et al., 2001; Smith et al., 2003). Nonetheless, commercial cultivars are the result of seedling selection, relying on vegetative propagation of daughter plants due to heterozygosity of seedling progeny (Hancock, 1999; Whitaker et al., 2011). Following initial hybridization events in the 18 th century strawberry breeding remained a personal endeavor, until the United States Department of Agriculture began funding breeding efforts in Oregon. Efforts were initially focused on quality traits for fresh and processed fruit, but disease resistance and abiotic tolerances soon became priorities (Darrow, 1966). Intense breeding of strawberry has resulted in cultivars from a relatively limited group in the United States, including proprietary development by Driscoll s (Watsonville, CA) and publically disseminated cultivars from the University of California at Davis and the University of Florida. Today another shift is occurring as a number of public and private entities, both domestic and abroad, are initiating breeding programs. This expansion is the result of efforts to develop region specific cultivars, as well as expanding targets for breeding including increase shelf-life, mechanical harvestability, nutritional content, and flavor. A highly successful product of the University of Florida s breeding program under Craig Chandler was Strawberry Festival. This cultivar is a first generation seedling selection from a cross between Rosa Linda and Oso Grande. Strawberry Festival was selected for its large, firm, conical shaped fruit of desirable red internal and external color and excellent flavor (Chandler et al., 2000). Currently, Strawberry Festival is the predominant cultivar by acreage in the state of Florida and therefore, an attractive system for fundamental and applied work aimed at understanding flavor in the context 21

22 of the consumer. Furthermore, the commercial relevance of Strawberry Festival in Florida and beyond makes it an attractive candidate for cultural, postharvest and transgenic manipulation to enhance flavor. Perception and Integration of Flavor Flavor is the perceptual and hedonic response to the synthesis of sensory signals of taste, odor, and tactile sensation (Prescott, 2004). In the case of strawberry and other fruits, sensory elicitation is the result of multiple direct interactions between plant and human: sugars and acids, pigments, turgor and structure, and volatile compounds, which elicit the senses of taste, vision, tactile sensation, and olfaction, respectively, in the development of flavor (Causse et al., 2001; Christensen, 1983; Hall, 1968; Stommel et al., 2005). The senses of taste and olfaction directly sample the chemicals present in food, but striking distinctions must be made between the two systems. The basic taste qualities of sweet, sour, salty, and bitter are very limited in diversity compared to innumerable distinct olfactory qualities. Nearly 350 olfactory receptor genes were originally putatively identified following sequencing of the human genome (Breslin, 2001; Zozulya et al., 2001). A more recent study using 1000 Genomes Project identifies over 4,000 protein variants from 413 intact olfactory receptor loci, of which roughly 600 allelic variants per person are estimated (Olender et al., 2012). This person to person genetic variation is suggestive of a highly personalized olfactory system. Most importantly, the distinction is between orthonasal and retronasal olfaction. Orthonasal olfaction is the result of smelling i.e. bringing odor in through the nose, while retronasal olfaction is elicited by odorants traveling from oral cavity or esophagus up to nasal cavity (Pierce and Halpern, 1996). Orthonasal olfaction introduces volatile compounds 22

23 to the nasal epithelium via inhalation, while retronasal olfaction is achieved during exhalation (Masaoka et al., 2010). Specifically, the path of odorants distinguishes the manner of interaction between consumer and potential food, with orthonasal contributing to aroma and retronasal to flavor. Integration of sensory stimuli relies on projection signals to various structures of the brain. Interestingly, portions of orthonasal (smell) and retronasal (flavor) olfaction project to different brain areas for processing (Small and Jones-Gotman, 2001), while taste activation partly overlaps that of retronasal olfaction for integration to produce flavor (Small et al., 2004). Co-activation of taste and retronasal olfaction, but not orthonasal, is shown to elicit responses at otherwise independently sub-threshold levels, exemplifying the ability of multiple sensory integration to intensify one another (Veldhuizen et al., 2010). Mechanical blockage of retronasal olfaction during tasting of solutions significantly reduces the ability to correctly identify solute, including sucrose (Masaoka et al., 2010). Combination of taste and retronasal olfaction results in a sensory system more adapt at analyzing the chemical content of food, but cross communication also facilitates manipulation of the system. The food industry knows of the intensification of volatile sensations by the addition of small amounts of sweeteners to solutions containing volatiles (SjÖStrÖM Loren and Cairncross Stanley, 1955). The ability of volatiles to enhance taste is also a known phenomenon (Lindemann, 2001). Enhancement of perceived sweetness is demonstrated by addition of volatiles amyl acetate (banana) (Burdach et al., 1984) and citral (Murphy and Cain, 1980). Multiple studies show the ability of strawberry aroma to intensify the sweetness of a sugar solution (Frank and Byram, 1988; Stevenson et al., 23

24 1999), as well as pineapple, raspberry, passion fruit, lychee, and peach (Cliff and Noble, 1990; Stevenson et al., 1999). Also, sweetness enhancement has been achieved with vanilla (Lavin and Lawless, 1998), caramel (Prescott, 1999; Stevenson et al., 1999), and chocolate (Masaoka et al., 2010) indicating this phenomena is not only associated with fruit volatiles. Studies to determine perceptional differences when tomato is spiked with sugars, acids, and volatiles indicates cross talk between taste and olfaction, in which volatiles impact perception of sweetness and vice versa (Baldwin et al., 2008). Individual volatile compounds have been implicated in tomato to intensify perceived sweetness independent of sugar content (Bartoshuk and Klee, 2013; Tieman et al., 2012). Diverse retronasal olfaction and fundamental taste sensory systems combine for flavor perception in cortical structures of the brain. Enhanced sensitivity and accuracy in discerning flavors arises from this cooperative effort, facilitating assessment of chemical constituents of food via chemical senses. Multiple roles are potentially served, but foremost survival requires finding and consuming safe food for maintaining metabolism and avoiding the deleterious (Breslin, 2001; Goff and Klee, 2006). Research Objectives The efforts of strawberry breeding, and other fruits and vegetables in general, over the past half century have not been on quality traits such as taste, aroma or texture. Breeder focus has been on visual appeal, firmness for post-harvest, and field traits such as yield and resistance (Ulrich et al., 2007). With flavor associated traits difficult to qualify and flavor as a whole at the discretion of a few breeders, present commercial varieties likely fall short of consumer preference. 24

25 Identifying Flavor-Related Metabolite Targets Using Psychophysics Amassing dense flavor-relevant metabolite data and corresponding consumer hedonic and sensory perceptual information of a diverse set of strawberry fruit allows for clarification of many factors contributing to strawberry flavor and consumer preference, using a psychophysics approach. Statistical analysis of detailed metabolite inventory of 54 unique strawberry samples coupled with consumer data of roughly 100 panelists per sample provides a means to define absolute targets in an otherwise amorphous phenotype. Field and Postharvest Environment Factors Influencing Flavor-Related Metabolites The breadth of genetic diversity assayed for metabolite content is highly complimented by environmentally induced variation in strawberry fruit flavor-related metabolites. Integration of weather data with metabolic profiling allows for elucidating factors that are detrimental to sugar and volatile content, which are positive contributors to flavor. Specific postharvest light treatments indicate a potential to influence volatile content on the shelf, while a pilot field experiment does not produce consistent effects. A Transgenic Approach to Introduce F. vesca Volatile Compound in F. x ananassa An uncommon commercial strawberry volatile compound, methyl anthranilate, is the subject of an applied transgenic effort. Emission of this volatile is known and preferred in many fruit and flowers including F. vesca, therefore heterologous expression of ZmAAMT1.1, which is characterized to be highly specific for methyl anthranilate biosynthesis, in Strawberry Festival is undertaken to enhance the deficient cultivars flavor. 25

26 The defining tenet of consumer-assisted selection is the integration of consumers in the development of new cultivars. With sweetness and complex flavor being high priorities of strawberry consumers (Colquhoun et al., 2012) it is critical to identify metabolites that are significantly impactful upon consumer perception and environmental factors affecting them. This work provides individual targets for breeding, fundamental science, and transgenic efforts to produce more flavorful strawberries using consumer-assisted selection. 26

27 CHAPTER 2 STRAWBERRY FLAVOR: DIVERSE CHEMICAL COMPOSITIONS, A SEASONAL INFLUENCE, AND EFFECTS ON SENSORY PERCEPTION Background Modern fully ripe strawberry (F. x ananassa) fruit is characterized by its large size (MacKenzie et al., 2011), vibrant red color (Hong and Wrolstad, 1990), reduced firmness (Brummell and Harpster, 2001), distinct aroma (Ulrich et al., 1997), and sweet fruity flavor (Schieberle and Hofmann, 1997). The three stages of non-climacteric, auxin dependent strawberry fruit development; division, expansion and ripening, involve gains in diameter and fresh weight; during which color shifts from green to white to dark red in roughly forty days following anthesis (Zhang et al., 2011a). Ripening of strawberry fruit results in the accumulation of multiple sugars and organic acids, culminating with peak volatile emission (Menager et al., 2004). Flavor is the perceptual and hedonic response to the synthesis of sensory signals of taste, odor, and tactile sensation (Prescott, 2004). The senses of taste and olfaction directly sample the chemicals present in food; sugars, acids, and volatiles. These metabolites are primary sensory elicitors of taste and olfaction that attenuate the perception and hedonics of flavor. A consumer based survey indicated sweetness and complex flavor as consistent favorable attributes of the ideal strawberry experience (Colquhoun et al., 2012). Thus a ripe strawberry is metabolically poised to elicit the greatest sensory and hedonic responses from consumers. During strawberry fruit development sucrose is continually imported from photosynthetic tissue. A consistently high sucrose invertase activity contributes to carbon sink strength in all developmental stages of fruit (Basson et al., 2010). Delivered sucrose is hydrolyzed into glucose and fructose and these three carbohydrates 27

28 constitute the major soluble sugars of ripe strawberries, a result of their continual accumulation during fruit development (Fait et al., 2008). In fact, an approximately 150% increase in their sum during ripening has been observed (Basson et al., 2010; Menager et al., 2004). The influx of carbon initiates a complex network of primary and secondary metabolism specific to ripening strawberry fruit (Fait et al., 2008). The metabolic activity of ripening strawberry is visualized by the late accumulation of the predominant red pigment, pelargonidin 3-glucoside (Hoffmann et al., 2006), an anthocyanin derived from the primary metabolite phenylalanine (Fait et al., 2008). The dynamics of fruit development are genetically driven as nearly 15% of cdnas probed using a microarray exhibit significant differential expression in red compared to green fruit (Aharoni et al., 2000). One up regulated gene, POLYGALACTURONASE 1.1, contributes to fruit softening (Quesada et al., 2009) by aiding in catalytic cell wall disassembly (Trainotti et al., 1999). Reduction of firmness is also attributed to dissolution of middle lamella, which functions in cell-to-cell adhesion (Brummell and Harpster, 2001). Active shifts in transcript accumulation throughout ripening result in metabolic network reconfiguration altering the chemical and physical properties. Metabolic profiling indicates an accumulation of sugars, organic acids, and fatty acids as well as the consumption of amino acids during fruit development, which is likely accountable for increases of alkanes, alcohols, aldehydes, anthocyanins, ketones, esters, and furanones during fruit ripening (Zhang et al., 2011a). Many of these chemical classes serve as precursors to volatile synthesis (Perez et al., 2002), thus facilitating a metabolic flux through biosynthetic pathways for increased and diverse 28

29 volatile emissions in ripe strawberry fruit, predominantly furanones, acids, esters, lactones, and terpenes (Menager et al., 2004). Over 350 volatile compounds have been identified across Fragaria (Du et al., 2011b; Maarse, 1991), however within a single fruit, far fewer compounds are detectable and even fewer contribute to aroma or flavor perception. A cross comparison of five previous studies which analyze strawberry volatiles depicts the lack of agreement in defining chemical constituents of strawberry aroma. Each source considers a highly variable subset of total volatiles, which are determined by signal intensity and/or human perception of isolated compounds (Hakala et al., 2002; Jetti et al., 2007; Olbricht et al., 2008; Schieberle and Hofmann, 1997; Ulrich et al., 1997). Mutual volatiles across studies include butanoic acid, methyl ester ( ); butanoic acid, ethyl ester ( ); hexanoic acid, methyl ester ( ); hexanoic acid, ethyl ester ( ); 1,6-octadien-3-ol, 3,7-dimethyl- (linalool) ( ); butanoic acid, 2-methyl- ( ); and DMF( ), the current consensus of integral strawberry aroma compounds. Comparisons of consumer preference among a variety of fresh strawberries and their volatile profiles describes less preferable varieties as possessing fewer esters, more decalactones and hexanoic acid (Ulrich et al., 1997). The breadth of volatile phenotypes previously reported highlights the diversity across strawberry genotypes and underscores the complexity of the aggregate trait of aroma and flavor. Annual horticulture of strawberry in Florida requires continual harvest of ripe fruit from late November through March. The mild winter production environment affects fruit quality as gradually increasing temperatures beginning in mid-january result in a late 29

30 season decline of soluble solids content (SSC) (MacKenzie et al., 2011). In fact, increasing temperature is known to be responsible for increasing fruit maturation rate and decreasing SSC independent of flowering date (MacKenzie and Chandler, 2009). Previous work also identifies variability of SSC, as well as titratable acidity (TA) and multiple classes of volatile compounds across harvest dates (Jouquand et al., 2008). The complex fruit biochemistry, which is variably affected by genetic, environmental, and developmental factors, coupled with individuals perceptional biases has made defining strawberry flavor cumbersome. Here we exploit the genetic and within-season variability of fruit to provide as many unique strawberry experiences as possible to a large sample of consumers. Parallel assays of ripe strawberry samples quantify fruit traits of TA, ph, SSC, and fruit firmness, as well as the content of malic acid, citric acid, glucose, fructose, sucrose, and 81 volatile compounds. The contributions of these attributes to fruit quality was determined by simultaneously evaluating samples for perceived sensory intensities of sourness, sweetness, and strawberry flavor, as well as the hedonic responses of texture and overall liking, i.e. the pleasure derived from consuming a strawberry sample, by consumer panelists during the 2011 and 2012 seasons in Florida. Data analyses determine progression of harvest season effects, gross variation of strawberry experiences, and factors influencing hedonics and sensory perception of strawberry fruit consumption using a psychophysics approach. Results suggestive of specific volatile compounds enhancing perceived sweetness has led to an application for patent (#13/869,132) with the United States Patent and Trademark Office. 30

31 Results The inventory of 54 fully ripe unique strawberry samples (35 cultivars, 12 harvests, two seasons) assayed for TA, ph, SSC, firmness, as well as the concentrations of malic acid, citric acid, glucose, fructose, sucrose, and quantity of 81 volatile compounds is reported (Table 2-1). Cluster analysis of relative chemical composition of all samples and derived hierarchy of both cultivar and metabolite relatedness is displayed (Figure 2-1). The vertical dendrogram (Figure 2-1) demonstrates the lack of relatedness among volatile compound concentration through large distances of initials segments, as well as the high number of clusters. Slightly more structure was observed among the samples, horizontal dendrogram (Figure 2-1), due to genetic or environmental effects. Progression of Harvest Season Affects Metabolic Content and Perceived Quality of Strawberry Ranges of weather parameters are consistent between both 2011 and 2012 seasons, except for slightly more precipitation during late January of 2011 (Figure 2-2 G, H). Solar radiation, minimum and maximum temperature all increased gradually and showed similar trends in both seasons (Figure 2-2 A-D). Relative humidity also, remained constant during and across seasons (Figure 2-2 E, F). One manifestation of these environmental changes over a harvest season was the negative relationship between SSC and harvest week (R 2 = 0.444***) (p < 0.05*, 0.01**, 0.001***) (Table 2-3). The sugars glucose, fructose, and sucrose were quantified, and their sum (total sugar) shows a strong positive correlation to SSC (R 2 = 0.733) (data not shown) and to harvest week (R 2 = 0.287***) (Table 2-3). Biochemical differences as a result of harvest week included a significant reduction in sucrose concentration (R 2 = 0.350***) (Figure 2-31

32 3A). However, glucose (R 2 = 0.064) (Figure 2-3B) and fructose (R 2 = 0.041) (Figure 2-3C) did not show a significant change within-season. Total volatile content decreased as the seasons progressed (R 2 = 0.338***) (Figure 2-3D). Also, a significant correlation was observed among total volatiles and sucrose (R 2 = 0.305***) (Figure 2-3E) but not glucose (R 2 = 0.005) (data not shown) or fructose (R 2 = 0.001) (Figure 2-3F). The simultaneous waning of SSC, predominantly sucrose, and volatiles was perceivable, as overall liking decreases as the season progresses (R 2 = 0.422***) (Figure 2-4E). The hedonic response to strawberry samples was measured as overall liking using the hedonic general labeled magnitude scale (glms) that ranges from -100 to +100, i.e. least to most pleasurable experience (Bartoshuk et al., 2004; Bartoshuk et al., 2003; Bartoshuk et al., 2005; Tieman et al., 2012). The strawberry sample with the highest overall liking was Strawberry Festival from first harvest week in the second season (sn 2, wk 1), which elicited an overall liking of 36.6 (Table 2-1). The lowest, a late season Red Merlin (sn 1, wk 6) scored at 13.3, while the sample set median was 23.5 (Table 2-1). The benchmark Strawberry Festival sample contains 3.5-fold more sucrose and 27% more total volatiles than the least liked fruit (Table 2-1), demonstrating the disparity between early and late harvest week fruit quality and its effect on consumer preference. Overall Liking is Subject to Ratings of Sweetness, Flavor, and Texture In order to elucidate factors contributing to a positive strawberry experience, overall liking of strawberry samples was fit against the hedonic measure of texture liking and the sensory intensities of sweetness, sourness, and strawberry flavor intensity (Figure 2-4A-D). High correlation with significant fit exists for texture liking (R 2 = 0.490***) (Figure 2-4A), sweetness intensity (R 2 = 0.742***) (Figure 2-4B), and 32

33 strawberry flavor intensity (R 2 = 0.604***) (Figure 2-4D). However, sourness intensity showed no correlation to overall liking (R 2 = 0.008) (Figure 2-4C). Texture liking had a significant influence on overall liking, and though increasing firmness contributed to greater texture liking (R 2 = 0.358***) (Figure 2-4I), firmness did not influence overall liking (R 2 = 0.034) (Table 2-4). Sweetness intensity was the strongest driver of overall liking measured in this study. The correlation between total sugar and overall liking (R 2 = 0.488***) (Figure 2-4F) demonstrated the aggregate sugar metabolites effect on hedonic response to strawberry fruit. Total sugar concentration accounted for nearly a majority of the observed overall liking variation but was far from a complete measure. Sourness intensity appears to have no influence on the hedonic response to strawberry fruit. On the other hand, a limited range of perceivable sourness intensity may be underrepresenting the effect as fit of TA to overall liking was significant, even if minor (R 2 = 0.099*) (Figure 2-4G). Total volatiles was the second aggregate metabolite measure having a significant enhancing effect on the overall liking of strawberry (R 2 = 0.179**) (Figure 2-4H). This was not surprising, as strawberry flavor intensity exhibits the second highest correlation to overall liking (Figure 2-4D). Texture Liking Correlates to Fruit Firmness The upper limit for hedonics of texture was comparable to that of overall liking and was observed in Strawberry Festival (sn 1, wk 2) with an average of 35.7, however, the low texture liking value of 5.8 for Mara Des Bois (sn 1, wk 7) indicated a more drastic disliking of off textures than lowest overall liking of fruit in its entirety (Table 2-1). Firmness of samples was assayed by measuring the force required for a set penetration of the fruit, acting as a proxy for texture. The firmness of the fresh strawberry exhibited nearly a five-fold difference in force, 0.2 kg for Mara des Bois (sn 33

34 1, wk 7) and 1.0 kg for Strawberry Festival (sn 1, wk 5) (Table 2-1). Increasing force of penetration, i.e. increasing firmness of berries, was positively correlated with texture liking, indicating a hedonic response to firmer fruit (R 2 = 0.358***) (Figure 2-4I). However, the texture liking rating for the two samples with greatest firmness is less than expected (Figure 2-4I). Sweetness Intensity is a Result of Sugar Content Perceived sweetness intensity was the greatest predictor of overall liking. In fact, the same samples scoring the highest and lowest for overall liking, Strawberry Festival (sn 2, wk 1) and Red Merlin (sn 1, wk 6), elicited the greatest (36.2) and least (14.59) intense sensations of sweetness (Table 2-1). The early and late harvest week samples supported the observed decline in perceived sweetness intensity across harvest weeks (R 2 = 0.471***) (Table 2-3), which was also observable for multiple sugar measures (Figure 2-3A-C). In the 54 samples assayed, the total sugar concentration ranged from %, a 3.5-fold difference (Table 2-1). Glucose and fructose concentrations exhibited highly similar ranges to each other, % and %, respectively (Table 2-1), and near-perfect correlation (R 2 = 0.984***) (data not shown) within a sample. However, the concentration of glucose or fructose was not predictive of sucrose concentration (R 2 = and 0.004, respectively) (data not shown). Sucrose demonstrated a more dynamic state as its concentration dips as low as 0.16% and up to 2.84%, nearly a seventeen-fold difference among all samples. Sucrose was the single metabolite with the most significant contribution to overall liking (R 2 = 0.442***) (Table 2-4). Individually, sucrose (R 2 = 0.445***) (Figure 2-4M), glucose (R 2 = 0.337***) (Figure 2-4N), and fructose (R 2 = 0.300***) (Table 2-4) all 34

35 significantly influenced the variation in sweetness intensity. However, total sugar actually only accounted for slightly more than two-thirds of sweetness intensity variation (R 2 = 0.687***) (Figure 2-4L) likely a result of covariation of glucose and fructose. Interestingly, the total volatile content of a sample correlated positively with sweetness intensity, potentially accounting for up to 13.9%** of variation in sweetness intensity (Figure 2-4O). Sourness Intensity is Partially Explained by Titratable Acidity The sourness intensity of Red Merlin (sn 1, wk 6) led to the lowest maximum consumer response of 24.6 (Table 2-1). This same sample rated as the lowest in terms of overall liking and sweetness (Table 2-1). Acidity of strawberry fruit was assayed using measures of ph, TA, citric acid and malic acid. The ph of strawberry samples ranged from 3.35 to 4.12, while TA ranges from 0.44% to 1.05%. The range of malic acid across samples was 0.078% to 0.338% while citric acid ranged from 0.441% to 1.080% (Table 2-1). TA had the greatest correlation to sourness intensity (R 2 = 0.314***) (Figure 2-4P), even compared to ph (R 2 = 0.118*), malic acid (R 2 = 0.189**) (Figure 2-4Q), or citric acid (R 2 = 0.146**) (Fig.3R) concentration. Citric acid concentration in general is approximately three-fold greater than malic acid and had a significant correlation to TA (R 2 = 0.49***) (data not shown). There was no correlation of malic acid to TA (R 2 = 0.01) (data not shown). Citric acid did not show any significant correlation to overall liking (R 2 = 0.056) (Table 2-4), presumably due to the minimal relationship among sourness intensity and overall liking (R 2 = 0.008) or limited range of sourness intensity ratings (Figure 2-4C). 35

36 Flavor Intensity is Influenced by Total and Specific Volatile Content In this study, strawberry flavor intensity accounts for the retronasal olfaction component of chemical senses, which compliments sourness and sweetness intensities contribution to taste. The overall highest sensory intensity was 37.5 for strawberry flavor of Strawberry Festival (sn 2, wk 1), which also rated highest for overall liking and sweetness intensity. Opposite this, FL (sn 1, wk 6) delivered the least intense strawberry flavor experience with a score of Total volatiles in Strawberry Festival (sn 2, wk 1) was over 50% greater than in FL and seven more volatiles compounds are detected (Table 2-1). Total volatiles within a sample contribute to strawberry flavor intensity (R 2 = 0.167**)(Figure 2-4T), but it was not simply the sum of volatile constituents that explain the effect. For instance, the maximum total volatile content detected within a sample, 27.3 µg 1 gfw -1 hr -1 from Camarosa (sn 1, wk 2), did not result in the greatest flavor intensity (30.5) and the minimum, 8.5 µg 1 gfw -1 hr -1 from Sweet Anne (sn 2, wk 9), did not rate as the least flavorful (25.8) (Table 2-1). The chemical diversity of the resources analyzed allowed for the identification of 81 volatile compounds from fresh strawberry fruit (Figure 2-5). The majority of compounds are lipid derived esters, while lipid derived aldehydes account for the majority of volatile mass. Terpenes, furans, and ketones were also represented in the headspace of strawberry. Forty three of the eighty-one volatile compounds were not detected ( 0.06 ng 1 gfw -1 hr -1 ) in at least one sample i.e. 38 volatiles were measured in all samples and appear to be constant in the genetic resources analyzed (Table 2-1). No cultivar has detectable amounts of all 81 volatiles. Samples of Strawberry Festival, Camino Real, PROPRIETARY 6 (proprietary cultivar of commercial entity, identity withheld), and FL were lacking detectable amounts of just one compound, 36

37 benzoic acid, 2-amino-, methyl ester ( )(methyl anthranilate), which was detectable in only Mara des Bois and Charlotte from the final harvest (wk 7) of season 1 (Table 2-1). Chandler (sn 2, wk 4) was qualitatively the most deficient sample, lacking detectable amounts of 19 of 81 compounds, had the second lowest amount of total volatiles, and a flavor intensity of 24.8 (Table 2-1). One ester deficient in Chandler, butanoic acid, 1-methylbutyl ester ( ), was not detectable in eight samples, and significantly correlated to flavor intensity (R 2 = 0.233***) (Table 2-4), despite maximum mass of only 11.5 ng 1 gfw -1 hr -1 (Table 2-1). Interestingly, the most abundant ester, butanoic acid, methyl ester was measured at over 7 µg 1 gfw -1 hr -1 from PROPRIETARY 2 (sn 1, wk 3) and had less correlation to flavor (R 2 = 0.097*) (Figure 2-4V) than butanoic acid, 1-methylbutyl ester. Hexanoic acid, ethyl ester exhibits over 200-fold difference across samples, had no bearing on sensory perception (Table 2-4). Likewise, hexanal ( ) was the second most abundant individual compound, an aldehyde detected in all samples, exceeded 11 µg 1 gfw -1 hr -1 (Table 2-1), and did not have a significant correlation to flavor intensity (R 2 = 0.016)(Table 2-4). Conversely, two minor level aldehydes demonstrated a disparity in effect: is enhancing toward flavor intensity (R 2 = 0.239**) (Figure 2-4U), while pentanal ( ) was the only compound that negatively correlates to flavor (R 2 = 0.079*) (Figure 2-4W). The significant contribution of the terpenes 1,6,10-dodecatrien-3- ol, 3,7,11-trimethyl-, (6E)- ( ) and 1,6-octadien-3-ol, 3,7-dimethyl- to flavor intensity positively correlated with their increasing concentration (R 2 = 0.112* and R2 = 0.074*, respectively) (Table 2-4), as well as, the level of a characteristic strawberry furan, DMF(R 2 = 0.108*) (Table 2-3). In total, thirty volatiles diverse in structure and 37

38 degree of presence were found to have a positive relationship to flavor intensity (α = 0.05). Specific Volatiles Enhance Sweetness Intensity Independent of Sugars Multiple regressions of individual volatile compounds against perceived intensity of sweetness was performed independent of either glucose, fructose, or sucrose concentration (Table 2-5). Twenty four volatile compounds showed significant correlations (α = 0.05) to perceived sweetness intensity independent of glucose or fructose concentration, twenty-two of which were mutual between the two monosaccharides. Twenty volatiles were found to enhance sweetness intensity independent of sucrose concentration; only six of these volatiles were shared with those independent of glucose and fructose: 1-penten-3-one ( ); 2(3H)-furanone, dihydro-5-octyl- ( ); butanoic acid, pentyl ester ( ); butanoic acid, hexyl ester ( ); acetic acid, hexyl ester ( ); and butanoic acid, 1-methylbutyl ester. Only three compounds were found to be negatively related to sweetness independent of at least one of the sugars: octanoic acid, ethyl ester ( ) exclusively independent of glucose; 2-pentanone, 4-methyl- ( ) mutually independent of glucose and fructose; and 2-buten-1-ol, 3-methyl-, 1-acetate ( ) exclusively independent of sucrose. Discussion Exploitation of genetic diversity and environmental variation allows for a wide range of consumer hedonic and sensory responses. A nearly three-fold difference in overall liking of strawberry is observable within all samples. The highest and lowest rating samples are Strawberry Festival of the first week of season 2 and Red Merlin of week six in the first season; two cultivars that are grown under the same conditions, but 38

39 product of separate breeding programs and from opposite ends of the harvest season. The cultivars in this study represent a large proportion of commercial strawberry acreage in North America, breeding selections, and European cultivars. A genetic collection to enhance the range of diversity for flavors and chemical constituents. Despite the perennial life cycle of strawberry much commercial production uses annual methods, which in sub-tropical Florida allows for continual harvest of ripe fruit from late November through March. In general, progression of harvest of non-determinant, nonclimacteric fruit throughout a season results in decreased overall liking, attributed to perceivable differences in fruit quality (Figure 2-4E). Increasing texture liking, sweetness intensity, and strawberry flavor intensity significantly increase overall liking, while sourness intensity is not clear (Figure 2-4A-D). Therefore, overall liking is the cumulative measure of the experience from eating a strawberry fruit. Integration and synthesis of response to sensory signals of taste, olfaction, and tactile sensation constitute an eating experience (Prescott, 2004) and drive overall liking. The senses of taste and olfaction sample the chemicals present in food like sugars, acids, and volatile chemical compounds. These elicitors attenuate the perception and hedonics of food (Fujimaru and Lim, 2013; Lindemann, 2001). Ratings of strawberry fruit are correlated to specific chemical or physical attributes, especially sweetness and flavor intensity, the two greatest drivers of overall liking. Much work has been done to measure sugars and volatile compounds in strawberry fruit in attempt of understanding sweetness and flavor, and these aims are in line with consumer demand. A consumer survey using 36 attributes of strawberry determined sweetness and complex flavor as consistent favorable characteristics of 39

40 the ideal strawberry experience (Colquhoun et al., 2012). Using the same glms scales employed in the current study, means for ideal strawberry and tomato (Tieman et al., 2012) overall liking, sourness intensity, and flavor intensity are similar. Ideal flavor evoked the highest mean sensory intensity for both, 45 on an intensity scale of 0-100, exemplifying its importance to the consumer. Interestingly, a large disparity for ideal sweetness intensity is found; 42 and 33 for strawberry and tomato, respectively. Ideal sweetness intensity is much greater in strawberry, potentially due to differences in consumption. Strawberry is often consumed fresh and is a delicacy or dessert fruit, while tomato is savory and often an ingredient in complex recipes. Therefore, the desire for sweetness is much greater in strawberry. The overall liking of strawberry fruit is significantly related to texture liking (Figure 2-4A), and increasing fruit firmness accounts for more than a third of increasing texture liking (Figure 2-4I). The five-fold variation in firmness can be attributed to variation in fruit development or softening (Table 2-1). Strawberry fruit development consists of division, expansion, and ripening (Zhang et al., 2011a). Developmentally regulated, ripening associated fruit softening is multifaceted (Quesada et al., 2009), including catalytic cell wall disassembly (Trainotti et al., 1999) and dissolution of cell-to-cell adhesion (Brummell and Harpster, 2001). The relationship between texture liking and firmness does not appear entirely linear, because the two firmest samples are close to average texture liking (Figure 2-4I). Excessively firm fruits may be perceived as under ripe while those with less firmness may be considered over ripe; affecting texture liking. Fruit can progress through ripening, from under to over ripe, in ten days (Zhang et al., 40

41 2011a), exemplifying the narrow window in which multiple facets of fruit quality must synchronize. Despite a moderate range of intensity, perceived sourness has little to no bearing on overall liking (Figure 2-4C). Just over 30% of sourness intensity variation can be accounted for by positive correlation with TA. The concentrations of citric acid and malic acid metabolites are likely additive toward the effect of TA on sourness intensity, and in fact both organic acids have significant correlations to TA (data not shown). Despite a lack of influence by sourness intensity on overall liking, which may be a result of limited intensity range, metabolites of sourness have a critical role in fruit biochemistry, as increased TA shows a significant minor correlation with overall liking (Table 2-4) and correlates significantly with SSC (data not shown). This co-linearity is due to accumulation of sugars and subsequent biosynthesis of organic acids during ripening of fruit (Fait et al., 2008; Menager et al., 2004; Zhang et al., 2011a). Citric acid is the predominant organic acid in ripe fruit (Mikulic-Petkovsek et al., 2012) and its concentration is fairly stable during ripening. Also, it is known to act as an intermediate between imported sucrose and fatty acid biosynthesis (Fait et al., 2008), which may facilitate enhancement of overall liking. The consumer rating of sweetness intensity is the primary factor contributing to overall liking, and sweetness is the component of taste perception facilitating the detection of sugars. Sugars are simple carbohydrates, a readily available form of energy, and the degree of correlation among sweetness and overall liking is due to hedonic effect (Lindemann, 2001). Variation in sweetness intensity is best explained by sugar content (Figure 2-4L) and SSC. More commonly SSC is used to estimate sugar 41

42 concentration, a valid indicator of sweetness in strawberry (Jouquand et al., 2008; Whitaker et al., 2011). Previous quantification of individual sugars within a strawberry identifies sucrose, glucose, and fructose as the predominant soluble solids (Basson et al., 2010; Menager et al., 2004; Mikulic-Petkovsek et al., 2012; Whitaker et al., 2011). Sucrose concentration, more than any other measure, is responsible for the most variation in SSC, sweetness intensity, and overall liking. (Table 2-4). Metabolites contributing to perceived sweetness intensity have the greatest influence on the overall hedonics of strawberry. A significant decrease in sweetness intensity occurs during the seasons, and unfortunately overall liking decreases as well. The extended harvest season of strawberry has an effect on fruit quality (Figure 2-4E) likely due to environmental changes (Figure 2-2) or plant maturity. These factors are likely causative of the observable decrease in sweetness intensity as the season progresses (Table 2-3). SSC, the best predictor of sweetness intensity, decreases during the season as the plant is subjected to increasing temperatures (Table 2-3), which likely alters whole plant physiology and more specifically fruit biochemistry during development and ripening, affecting fruit quality. Development of fruit under elevated temperature increases fruit maturation rate and decreases SSC independent of flowering date i.e. plant maturity (MacKenzie and Chandler, 2009; MacKenzie et al., 2011). A significant and strong decrease in sucrose and a lack of change in glucose and fructose indicates sucrose as the waning constituent of SSC within a season (Figure 2-3A-C). Sucrose concentration has greatest variability among the three sugars and shows no significant relationship to glucose or fructose concentration. However, a near perfect statistical relationship observed between glucose and fructose is likely due to 42

43 their biosynthetic association. During strawberry fruit development sucrose is continually translocated from photosynthetic tissue, while a consistently high sucrose invertase activity in fruit hydrolyzes sucrose into glucose and fructose, maintaining sink strength of fruit (Basson et al., 2010) and in turn feed biosynthetic pathways (Fait et al., 2008). Increased maturation rate hastens fruit development, potentially decreasing cumulative period sucrose is imported to fruit, and inhibiting sucrose accumulation to affect other fruit quality attributes. Total volatile content has an indirect dependence on sucrose concentration (Figure 2-3E), and a decrease in total volatiles is observed as the seasons progress (Figure 2-3D). Generation of glucose and fructose initiates a complex network of primary and secondary metabolism specific to ripening strawberry fruit, in which sucrose is principal and limiting to the strawberry fruit biosynthetic pathways (Fait et al., 2008). The primary metabolite classes of fatty acids and amino acids are derived from sucrose in a fruit specific metabolism and their concentrations decrease in the final stage of ripening (Fait et al., 2008). The culmination of ripening coincides with peak concentration of volatile secondary metabolites (Menager et al., 2004) and upregulation of associated biosynthetic genes (Cumplido-Laso et al., 2012). Influence of harvest date on headspace of fresh strawberry fruit is known (Pelayo-Zaldivar et al., 2005; Watson et al., 2002). One hypothesis, increased volatile content is dependent on more free sucrose, i.e. a larger imported reserve, facilitating greater flux through primary and secondary metabolism. Glucose and fructose concentrations are tightly correlated, show less variation, less seasonal influence, and lack of correlation to sucrose, indicative of tighter biochemical regulation. 43

44 Strawberry flavor intensity is the second greatest determinant of overall liking (Figure 2-4D) and accounts for perception of volatile compounds through retronasal olfaction. A significant positive relationship exists among total volatile content and the flavor intensity for a given sample, however, total volatile content is not entirely explanatory of flavor intensity. The maximum rating for strawberry flavor intensity by Strawberry Festival (sn 2, wk1) is the greatest consumer response evoked within this study (Table 2-1), highlighting the significance of sensory perception of aroma. However, this sample only has slightly more than 60% of total volatile mass of the greatest sample. The extent of volatile phenotype diversity is great enough across strawberry fruit to not only be discerned but be preferred. Within the genetic resources of F. x ananassa analyzed in this study 81 compounds are reproducibly detected, but not one cultivar has detectable amounts of all compounds. Accumulation of sugars, organic acids, and fatty acids, as well as the consumption of amino acids occurs during ripening (Zhang et al., 2011a). Many of these chemical classes serve as precursors to volatile synthesis (Perez et al., 2002), thus facilitating a flux through biosynthetic pathways for increased and diverse volatile emissions in ripe strawberry fruit, characterized by acids, aldehydes, esters, furanones, lactones, and terpenes (Jetti et al., 2007; Menager et al., 2004). Over 350 volatile compounds are identified across Fragaria (Du et al., 2011b; Maarse, 1991). The concentrations of individual volatile compounds within fruit can have a significant influence on flavor intensity, but which volatiles are determinant of flavor has a lack of agreement. 44

45 Previous determination of flavor relevance relied on approaches in which importance of volatiles is based on analytical signal intensity and/or human perception of single isolated volatile compound via orthonasal olfaction (Hakala et al., 2002; Jetti et al., 2007; Olbricht et al., 2008; Schieberle and Hofmann, 1997; Ulrich et al., 1997), negating the complex system of strawberry fruit or actual flavor relevant retronasal olfaction. Of the forty-six volatile compounds cited as relevant to strawberry flavor in five studies (Hakala et al., 2002; Jetti et al., 2007; Olbricht et al., 2008; Schieberle and Hofmann, 1997; Ulrich et al., 1997) only seven are common to at least three of the studies, exemplifying the lack of agreement in defining flavor-relevant constituents. This agreement includes butanoic acid, methyl ester; butanoic acid, ethyl ester; hexanoic acid, methyl ester; hexanoic acid, ethyl ester; 1,6-Octadien-3-ol, 3,7-dimethyl- (linalool); butanoic acid, 2-methyl-; and DMF-, all of which are quantified in this report. These compounds exhibit adequate variability in fruit samples to discern dose dependent effect on flavor intensity. However, only 1,6-Octadien-3-ol (linalool), 3,7-dimethyl-; butanoic acid, ethyl ester; butanoic acid, methyl ester; and DMF show significant positive correlation with flavor intensity (Table 2-4). These compounds that are found to influence flavor intensity represent diverse classes, terpenoid alcohol, two esters, and a furan, respectively, while the three compounds not fitting to flavor are all esters. With esters accounting for the majority of chemical compounds detected in strawberry it is possible that too much emphasis is placed on the chemical class for flavor, or that in a complex mixture less are perceivable than when smelled individually. These volatiles may have no bearing on strawberry flavor, but have been targets due to quantity, threshold ratios, or simply identity. 45

46 Over one third of volatiles in this study significantly correlate with strawberry flavor intensity, potentially enhancing perception of a complex and highly variable volatile mixture (Table 2-4), seventeen of which are not of previous strawberry flavor focus. Two of these unrecognized compounds, 1-hexanol ( ) and butanoic acid, 3-methyl-, butyl ester ( ), are present in the most flavorful strawberry sample but undetected in the least flavorful (Table 2-1). This pair of compounds as well as pentanoic acid, ethyl ester ( ) and butanoic acid, 3-methyl-, octyl ester ( ), also present/absent in the most/least flavorful, have relatively minor amounts but show evidence of enhancing perceived sweetness intensity independent of individual sugars. Volatiles with relatively low concentrations are indicated as new impactful components of strawberry flavor. Thirty-eight volatile compounds are observed to significantly enhance the perceived intensity of sweetness; twenty-two mutually independent of glucose and fructose, fourteen uniquely independent of sucrose, and six compounds mutually independent of all three sugars: 1-penten-3-one; 2(3H)-furanone, dihydro-5-octyl- (γdodecalactone); butanoic acid, pentyl ester; butanoic acid, hexyl ester; acetic acid, hexyl ester; and butanoic acid, 1-methylbutyl ester (Table 2-5). In tomato, similar analysis of a volatile subset identifies three compounds enhancing sweetness intensity independent of fructose: geranial; 1-butanol, 3-methyl- ( ); and butanal, 2- methyl- ( ) (Tieman et al., 2012). These compounds are not identified in the current study, therefore the effect cannot be confirmed in a second system. Botanically, tomato is considered a true fruit and demonstrates climacteric ripening, while strawberry fruit is non-climacteric and considered an aggregate accessory fruit. The developmental 46

47 origin of the flesh that is consumed is divergent, exhibiting unique biochemistries, but the observance of volatile compounds potentially enhancing perceived sweetness appears to be widespread in fruit. Orthonasal (smell) and retronasal (flavor) olfaction each project to different brain areas for processing (Small and Jones-Gotman, 2001), and taste projects to the same brain area as retronasal olfaction for integration to produce flavor (Small et al., 2004). This integration has a remarkable consequence: taste and retronasal olfaction can intensify one another. The food industry knows of the intensification of volatile sensations by the addition of small amounts of sweeteners to solutions containing volatiles (SjÖStrÖM Loren and Cairncross Stanley, 1955). The ability of volatiles to enhance taste is also a phenomena (Burdach et al., 1984; Lindemann, 2001; Murphy et al., 1977), and one study shows the ability of strawberry aroma to intensify the sweetness of a sugar solution (Frank and Byram, 1988). The results here narrow the previous effect of enhanced sweetness by strawberry aroma, a variable mixture, to individual compounds in the fruit. These volatiles are not present at the highest amounts in fruits and most are not targets of flavor analysis. Also, a majority appear to be associated with lipid metabolism, like many other volatiles quantified in this work, yet their presence or increased concentration has an enhancing effect on perceived sweetness independent of sugars. Technically, sweetness is a facet of taste (Lindemann, 2001). Therefore a means to convey sweetness via volatiles can serve as an attractant to seed dispersers of wild strawberry, or perhaps it is a result of artificial selection (Aharoni et al., 2004) to enhance a limited sugar capacity in commercial fruit. 47

48 Strawberry fruit ripening results in softening of flesh, peak volatile emission, and accumulation of sugars. This highly coordinated process results in fruit with strong liking due primarily to texture, flavor, and sweetness. However, cultivar, environmental conditions, and their interactions influence fruit attributes, altering the composition of strawberry. This diversity allows for a gamut of experiences such that the hedonics and intensities of these sensations can vary greatly. The importance of sucrose to sweetness intensity is evident, and the correlation of total volatiles to sucrose highlights the dependence of secondary metabolism to primary metabolism. Individual volatiles correlate to strawberry flavor intensity, helping to better define distinct, perceptually impactful compounds from the larger mixture of the fruit. The dependence of liking on sweetness and strawberry flavor is undermined by environmental pressures that reduce sucrose and total volatile content. A cultivar that exhibits minimal seasonal environmental influence presents itself as a breeding ideotype, as maintenance of sucrose concentration may alleviate loss of overall liking. Selection for increased concentrations of volatile compounds that act independently of sugars to enhance sweetness can serve as an alternate approach. The volatiles described herein are sampled mainly from current commercial cultivars and are therefore feasible targets for varietal improvement in the short-term, whereas future studies will be necessary to identify sweet-enhancing volatiles not already present in elite germplasm. Materials and Methods Plant Material Thirty-five strawberry cultivars and selections were grown during the and winter seasons according to current commercial practices for annual strawberry plasticulture in Florida (MacKenzie et al., 2011; Santos et al., 2012). The 48

49 cultivars were chosen to represent a large proportion of commercial strawberry acreage in North America from both public and private breeding programs. Additional breeding selections and European cultivars were added to enhance the range of diversity for flavors and chemical constituents. Fully-ripe fruit by commercial standards (Strand, 2008) was harvested from three to five cultivars on Monday mornings, delivered to the respective laboratories, and stored at 4 C in the dark overnight for simultaneous analysis of fresh strawberry fruit volatiles, firmness, and sensory analysis on Tuesdays; as well as sample preparation for later sugar and acid measurements. Six harvests in both seasons allows for the complete analysis of fifty-four samples. Weather data was obtained from the Balm, FL station of the Florida Automated Weather Network ( Daily maximum and minimum temperature recording height was 60 cm, and daily average relative humidity, rain, and solar radiation were recording at 2 m. Volatile Analysis At least 100 grams or seven berries of each sample were removed from 4 C dark overnight storage prior to volatile collection. Samples were homogenized in a blender prior to splitting into three 15 gram replicates for immediate capturing of volatile emissions and the remainder frozen in N 2 (l) and stored at -80 C for later sugar and acid quantification. A two hour collection in a dynamic headspace volatile collection system (Underwood et al., 2005) allowed for concentration of emitted volatiles on HaySep porous polymer adsorbent (Hayes Seperations Inc., Bandera, TX, USA). Elution from polymer was described by Schmelz et al. (Schmelz et al., 2003). Quantification of volatiles in an elution was performed on an Agilent 7890A Series gas chromatograph (GC) (carrier gas; He at 3.99 ml min -1 ; splitless injector, 49

50 temperature 220 C, injection volume 2 µl) equipped with a DB-5 column ((5%-Phenyl)- methylpolysiloxane, 30 m length 250 µm i.d. 1 µm film thickness; Agilent Technologies, Santa Clara, CA, USA). Oven temperature was programmed from 40 C (0.5 min hold) at 5 C min -1 to 250 C (4 min hold). Signals were captured with a flame ionization detector (FID) at 280 C. Peaks from FID signal were integrated manually with Chemstation B software (Agilent Technologies, Santa Clara, CA). Volatile emissions (ng 1 gfw -1 h -1 ) were calculated based on individual peak area relative to sample elution standard peak area. GC-Mass Spectrometry (MS) analysis of elutions was performed on an Agilent 6890N GC in tandem with an Agilent 5975 MS (Agilent Technologies, Santa Clara, CA, USA) and retention times were compared with authentic standards (Sigma Aldrich, St Louis, MO, USA) for volatile identification (Schmelz et al., 2001). Chemical Abstract Services (CAS) registry numbers were used to query SciFinder substances database for associated chemical name and molecular formula presented in Table 2-6. Sugars and Acids Quantification Titratable acidity, ph, and SSC were averaged from four replicates of the supernatant of centrifuged thawed homogenates (Whitaker et al., 2011). An appropriate dilution of the supernatant from a separate homogenate (centrifugation of 1.5 ml at 16,000 x g for 20 minutes) was analyzed using biochemical kits (per manufacturer s instructions) for quantification of citric acid, L-malic acid, D-glucose, D-fructose, and sucrose (CAT# , CAT# , and CAT# ; R- Biopharm, Darmstadt, Germany) with absorbance measured at 365 nm on an Epoch Microplate Spectrophotometer (BioTek, Winooksi, VT, USA). Metabolite average concentration (mg 100gFW -1 ) was determined from two to six technical replicates per 50

51 pooled sample. Derived sucrose concentrations via D-glucose and D-fructose were mathematically pooled. Firmness Determination Firmness of the strawberries was determined as the resistance of the fruit to penetration (7 mm depth) at its equator with a TA.XTPlus Texture Analyzer (Texture Technologies Corp., Scarsdale, NY, USA/Stable Micro Systems, Godalming, Surrey, UK). The Texture Analyzer was equipped with a 50 kg load cell and an 8 mm diameter convex tip probe. Whole fruit was punctured on the side to 7 mm down from the epidermis at a test speed of 2 mm/sec; a flap cut off the opposite side provides stability. Maximum force in kg for eight fruit was averaged and reported as a measure of firmness. Sensory Analysis All consumer panels were approved by the University of Florida Institutional Review Board. Over the course of two years, 166 recruited strawberry consumers (58 male, 108 female) evaluated strawberry cultivars. Ages of panelist ranged from 18 to 71, with a median age of 24. Panelists self-classified themselves as 98 White or Caucasian, 11 Black or African-American, 1 Native American, Alaska Native or Aleutian, 41 Asian/Pacific Islander, and 15 Other. An average of 106 (range of ) panelists evaluated between three and five cultivars per session (Tieman et al., 2012). Fresh, fully-ripe strawberry fruit was removed from overnight 4 C dark storage and allowed to warm to room temperature prior to sensory analysis. Each panelist was given one to two whole strawberries for evaluation, depending on cultivar availability. Panelist bit each sample, chewed, and swallowed it. Ratings for overall liking and texture liking were scaled on hedonic glms in the context of all pleasure/displeasure experiences. 51

52 Perceived intensity of sweetness, sourness, and strawberry flavor are scaled in context of all sensory experiences using sensory glms (Bartoshuk et al., 2004; Bartoshuk et al., 2003; Bartoshuk et al., 2005; Tieman et al., 2012). Scales were employed to mediate valid comparisons across subjects and sessions. Statistical Analysis Means and standard errors for consumer, physical, and metabolite measurements were determined from all replicates using JMP (Version 8, SAS Institute Inc., Cary, NC, USA). Bivariate analysis among individual measurements of samples allowed for linear fit, which included summary of fit, analysis of variance, t-test, and correlation analysis for density ellipse. Two-way Ward hierarchical cluster analysis of all metabolite concentrations and strawberry samples was accomplished in JMP. Amounts of individual volatile compounds were regressed using the enter method in SPSS (IBM Corp., Armonk, NY, USA). This is done individually for each of the three sugars: glucose, fructose or sucrose to identify which compounds have an effect on sweetness intensity (positive or negative) independent of each of the sugars. For p-values.05, the volatile makes a contribution to perceived sweetness that is independent of the sugar tested. 52

53 Table 2-1. Means of consumer, physical, and biochemical measures. HIGH LOW MEDIAN FOLD DIFFERENCE HARVEST DATE CULTIVAR HARVEST OVERALL TEXTURE SWEETNESS SOURNESS LIKING LIKING INTENSITY INTENSITY -100 to to to to to +100 PROPRIETARY /24/ CAMAROSA /24/ FESTIVAL /24/ MARA DES BOIS /24/ RADIANCE /24/ PROPRIETARY /31/ CAMAROSA /31/ SWEET CHARLIE /31/ TREASURE /31/ WINTER DAWN /31/ PROPRIETARY /7/ CAMINO REAL /7/ FESTIVAL /7/ WINTERSTAR /14/ FESTIVAL /14/ RADIANCE /14/ PROPRIETARY /14/ FL /21/ ELYANA /21/ FESTIVAL /21/ RED MERLIN /21/ SAN ANDREAS /21/ ALBION /28/ CHARLOTTE /28/ FESTIVAL /28/ MARA DES BOIS /28/ MONTERREY /28/ ALBION /16/ FESTIVAL /16/ MOJAVE /16/ PROPRIETARY /16/ CHANDLER /6/ FESTIVAL /6/ FL /6/ TREASURE /6/ WINTER DAWN /6/ PROPRIETARY /13/ ALBION /13/ FESTIVAL /13/ RUBYGEM /13/ CAMINO REAL /20/ DARSELECT /20/ FESTIVAL /20/ SWEET ANNE /20/ BENICIA /27/ FESTIVAL /27/ FL /27/ PORTOLA /27/ VENTANA /27/ PROPRIETARY /12/ EVIE /12/ FESTIVAL /12/ GALLETA /12/ SWEET ANNE /12/ STRAWBERRY FLAVOR INTENSITY 53

54 Table 2-1. Continued. HIGH LOW MEDIAN FOLD DIFFERENCE CULTIVAR HARVEST FORCE SSC ph TA kg % % PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

55 Table 2-1. Continued. CULTIVAR HIGH LOW MEDIAN FOLD DIFFERENCE HARVEST MALIC CITRIC TOTAL GLUCOSE FRUCTOSE SUCROSE ACID mg 1 100gFW - 1 ACID mg 1 100gFW - 1 SUGAR mg 1 100gFW - 1 mg 1 100gFW - 1 mg 1 100gFW - 1 mg 1 100gFW PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

56 Table 2-1. Continued. HIGH LOW MEDIAN FOLD DIFFERENCE CULTIVAR HARVEST TOTAL VOLATILES ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 alcohol alcohol ketone ketone aldehyde PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

57 Table 2-1. Continued. HIGH LOW MEDIAN FOLD DIFFERENCE CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ketone ester ester ester ketone ketone PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

58 Table 2-1. Continued. HIGH LOW MEDIAN FOLD DIFFERENCE CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 aldehyde ketone ester alcohol alcohol ester PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

59 Table 2-1. Continued. HIGH LOW MEDIAN FOLD DIFFERENCE CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ketone ester aldehyde ester ester ester/alcohol PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

60 Table 2-1. Continued. HIGH LOW MEDIAN FOLD DIFFERENCE CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ketone ester ester ester aldehyde alcohol PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

61 Table 2-1. Continued. HIGH LOW MEDIAN FOLD DIFFERENCE CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 alcohol ester ester ketone ketone ester PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

62 Table 2-1. Continued. HIGH LOW MEDIAN FOLD DIFFERENCE CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ester aldehyde ester ester ester ester PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

63 Table 2-1. Continued. HIGH LOW MEDIAN FOLD DIFFERENCE CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ketone ester ester aldehyde ester ester PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

64 Table 2-1. Continued. HIGH LOW MEDIAN FOLD DIFFERENCE CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ester alcohol ester ester aldehyde ester PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

65 Table 2-1. Continued. HIGH LOW MEDIAN FOLD DIFFERENCE CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 furan aldehyde ketone furan alcohol aldehyde PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

66 Table 2-1. Continued. HIGH LOW MEDIAN FOLD DIFFERENCE CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ester ester ester ester ester ester PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

67 Table 2-1. Continued. HIGH LOW MEDIAN FOLD DIFFERENCE CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 aldehyde aldehyde ester ester ester ester PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

68 Table 2-1. Continued. HIGH LOW MEDIAN FOLD DIFFERENCE CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ester ester furan ester hydrocarbon PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

69 Table 2-1. Continued. HIGH LOW MEDIAN FOLD DIFFERENCE CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 alcohol ester ester furan PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

70 Table 2-2. Standard errors of consumer, physical, and biochemical measures. CULTIVAR HARVEST HARVEST DATE OVERALL LIKING -100 to +100 TEXTURE LIKING -100 to +100 SWEETNESS INTENSITY SOURNESS INTENSITY STRAWBERRY FLAVOR INTENSITY 0 to to to +100 PROPRIETARY /24/ CAMAROSA /24/ FESTIVAL /24/ MARA DES BOIS /24/ RADIANCE /24/ PROPRIETARY /31/ CAMAROSA /31/ SWEET CHARLIE /31/ TREASURE /31/ WINTER DAWN /31/ PROPRIETARY /7/ CAMINO REAL /7/ FESTIVAL /7/ WINTERSTAR /14/ FESTIVAL /14/ RADIANCE /14/ PROPRIETARY /14/ FL /21/ ELYANA /21/ FESTIVAL /21/ RED MERLIN /21/ SAN ANDREAS /21/ ALBION /28/ CHARLOTTE /28/ FESTIVAL /28/ MARA DES BOIS /28/ MONTERREY /28/ ALBION /16/ FESTIVAL /16/ MOJAVE /16/ PROPRIETARY /16/ CHANDLER /6/ FESTIVAL /6/ FL /6/ TREASURE /6/ WINTER DAWN /6/ PROPRIETARY /13/ ALBION /13/ FESTIVAL /13/ RUBYGEM /13/ CAMINO REAL /20/ DARSELECT /20/ FESTIVAL /20/ SWEET ANNE /20/ BENICIA /27/ FESTIVAL /27/ FL /27/ PORTOLA /27/ VENTANA /27/ PROPRIETARY /12/ EVIE /12/ FESTIVAL /12/ GALLETA /12/ SWEET ANNE /12/

71 Table 2-2. Continued. CULTIVAR HARVEST SSC ph TA % % PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

72 Table 2-2. Continued. CULTIVAR HARVEST MALIC ACID mg 1 100gFW - 1 CITRIC ACID mg 1 100gFW - 1 TOTAL SUGAR mg 1 100gFW - 1 GLUCOSE FRUCTOSE SUCROSE mg 1 100gFW - 1 mg 1 100gFW - 1 mg 1 100gFW PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

73 Table 2-2. Continued. CULTIVAR HARVEST TOTAL VOLATILES ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

74 Table 2-2. Continued. CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

75 Table 2-2. Continued. CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

76 Table 2-2. Continued. CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

77 Table 2-2. Continued. CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

78 Table 2-2. Continued. CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

79 Table 2-2. Continued. CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

80 Table 2-2. Continued. CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

81 Table 2-2. Continued. CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

82 Table 2-2. Continued. CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

83 Table 2-2. Continued. CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

84 Table 2-2. Continued. CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

85 Table 2-2. Continued. CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

86 Table 2-2. Continued. CULTIVAR HARVEST ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 ng 1 gfw -1 hr -1 PROPRIETARY CAMAROSA FESTIVAL MARA DES BOIS RADIANCE PROPRIETARY CAMAROSA SWEET CHARLIE TREASURE WINTER DAWN PROPRIETARY CAMINO REAL FESTIVAL WINTERSTAR FESTIVAL RADIANCE PROPRIETARY FL ELYANA FESTIVAL RED MERLIN SAN ANDREAS ALBION CHARLOTTE FESTIVAL MARA DES BOIS MONTERREY ALBION FESTIVAL MOJAVE PROPRIETARY CHANDLER FESTIVAL FL TREASURE WINTER DAWN PROPRIETARY ALBION FESTIVAL RUBYGEM CAMINO REAL DARSELECT FESTIVAL SWEET ANNE BENICIA FESTIVAL FL PORTOLA VENTANA PROPRIETARY EVIE FESTIVAL GALLETA SWEET ANNE

87 Table 2-3. Fruit attribute bivariate fit to harvest week. X Y R 2 CORR COEFF p-value n MEAN X STD DEV X MEAN Y STD DEV Y WEEK WEEK WEEK SWEETNESS INTENSITY WEEK SSC WEEK STRAWBERRY FLAVOR INTENSITY WEEK OVERALL LIKING WEEK WEEK SUCROSE WEEK WEEK TOTAL VOLATILES WEEK WEEK WEEK TOTAL SUGAR WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK TEXTURE LIKING WEEK L* int WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK A* ext WEEK WEEK GLUCOSE WEEK WEEK WEEK WEEK WEEK WEEK WEEK FRUCTOSE WEEK TA WEEK WEEK WEEK WEEK WEEK WEEK WEEK ph WEEK WEEK WEEK L* ext WEEK A* int WEEK WEEK WEEK WEEK FORCE WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK CITRIC ACID WEEK SOURNESS INTENSITY WEEK WEEK WEEK B* int WEEK WEEK WEEK B* ext WEEK WEEK MALIC ACID WEEK WEEK WEEK WEEK WEEK

88 Table 2-3. Continued. X Y R 2 CORR COEFF p-value n MEAN X STD DEV X MEAN Y STD DEV Y WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK WEEK Note: Regression of harvest week during season (X) on panel responses and metabolite concentration (Y). Coefficient of determination (R 2 ), correlation coefficient, p- value, sample size (n), mean and standard deviation of X and Y derived from bivariate fit in JMP 8. 88

89 Table 2-4. Fruit attribute bivariate fir to consumer measure. X Y R 2 CORR COEFF p-value n MEAN X STD DEV X MEAN Y STD DEV Y TOTAL SUGAR OVERALL LIKING SSC OVERALL LIKING SUCROSE OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING TOTAL VOLATILES OVERALL LIKING OVERALL LIKING OVERALL LIKING GLUCOSE OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING L* int OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING FRUCTOSE OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING A* int OVERALL LIKING TA OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING B* int OVERALL LIKING OVERALL LIKING CITRIC ACID OVERALL LIKING ph OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING FORCE OVERALL LIKING OVERALL LIKING A* ext OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING MALIC ACID OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING B* ext OVERALL LIKING OVERALL LIKING OVERALL LIKING

90 Table 2-4. Continued. X Y R 2 CORR COEFF p-value n MEAN X STD DEV X MEAN Y STD DEV Y OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING OVERALL LIKING L* ext OVERALL LIKING FORCE TEXTURE LIKING MALIC ACID TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING SUCROSE TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TOTAL SUGAR TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING ph TEXTURE LIKING SSC TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TA TEXTURE LIKING TEXTURE LIKING TOTAL VOLATILES TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING L* ext TEXTURE LIKING TEXTURE LIKING GLUCOSE TEXTURE LIKING B* ext TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING A* ext TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING

91 Table 2-4. Continued. X Y R 2 CORR COEFF p-value n MEAN X STD DEV X MEAN Y STD DEV Y B* int TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING A* int TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING FRUCTOSE TEXTURE LIKING TEXTURE LIKING CITRIC ACID TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING L* int TEXTURE LIKING TEXTURE LIKING TEXTURE LIKING SSC SWEETNESS INTENSITY TOTAL SUGAR SWEETNESS INTENSITY SUCROSE SWEETNESS INTENSITY SWEETNESS INTENSITY GLUCOSE SWEETNESS INTENSITY FRUCTOSE SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY L* int SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY A* int SWEETNESS INTENSITY TOTAL VOLATILES SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY CITRIC ACID SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY TA SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY B* int SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY ph SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY B* ext SWEETNESS INTENSITY SWEETNESS INTENSITY A* ext SWEETNESS INTENSITY SWEETNESS INTENSITY

92 Table 2-4. Continued. X Y R 2 CORR COEFF p-value n MEAN X STD DEV X MEAN Y STD DEV Y SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY MALIC ACID SWEETNESS INTENSITY FORCE SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY L* ext SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY SWEETNESS INTENSITY TA SOURNESS INTENSITY MALIC ACID SOURNESS INTENSITY CITRIC ACID SOURNESS INTENSITY SOURNESS INTENSITY ph SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY FRUCTOSE SOURNESS INTENSITY GLUCOSE SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY L* ext SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY TOTAL SUGAR SOURNESS INTENSITY L* int SOURNESS INTENSITY SSC SOURNESS INTENSITY SOURNESS INTENSITY B* ext SOURNESS INTENSITY B* int SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SUCROSE SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY A* int SOURNESS INTENSITY

93 Table 2-4. Continued. X Y R 2 CORR COEFF p-value n MEAN X STD DEV X MEAN Y STD DEV Y SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY A* ext SOURNESS INTENSITY SOURNESS INTENSITY TOTAL VOLATILES SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY FORCE SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SOURNESS INTENSITY SSC STRAWBERRY FLAVOR INTENSITY TOTAL SUGAR STRAWBERRY FLAVOR INTENSITY SUCROSE STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY TA STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY CITRIC ACID STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY GLUCOSE STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY TOTAL VOLATILES STRAWBERRY FLAVOR INTENSITY FRUCTOSE STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY L* int STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY A* int STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY

94 Table 2-4. Continued. X Y R 2 CORR COEFF p-value n MEAN X STD DEV X MEAN Y STD DEV Y STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY B* int STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY ph STRAWBERRY FLAVOR INTENSITY B* ext STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY A* ext STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY FORCE STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY L* ext STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY MALIC ACID STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY STRAWBERRY FLAVOR INTENSITY Note: Regression of chemical and physical measures of fruit (X) and panel responses (Y). Coefficient of determination (R 2 ), correlation coefficient, p-value, sample size (n), mean and standard deviation of X and Y derived from bivariate fit in JMP 8. 94

95 Table 2-5. Multiple regression for identification of sweetness enhancing volatiles. CAS # FRUCTOSE FRUCTOSE SUCROSE SUCROSE GLUCOSE GLUCOSE t RATIO p-value t RATIO p-value t RATIO p-value * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *

96 Table 2-5. Continued. CAS # FRUCTOSE t RATIO FRUCTOSE p-value SUCROSE t RATIO SUCROSE p-value GLUCOSE t RATIO GLUCOSE p-value * * * * * * Note: Individual volatile compound concentrations are regressed against perceived sweetness intensity independent of effect from glucose, fructose, or sucrose, separately. Thirty compounds (asterisk) were found to enhance intensity of sweetness independent of at least one of the three sugars. Six compounds were found to significantly enhance intensity of sweetness independent of all three sugars (α = 0.05). Analysis conducted using the enter method in SPSS 96

97 Table 2-6. Index of CAS registry number, chemical name, and formula. CAS Registry Number Chemical Name Formula Butanol, 2-methyl- C 5 H 12 O Penten-3-ol C 5 H 10 O Penten-3-one C 5 H 8 O Pentanone C 5 H 10 O Pentanal C 5 H 10 O Ethanethioic acid, S-methyl ester (9CI) C 3 H 6 O S Propanoic acid, ethyl ester C 5 H 10 O Acetic acid, propyl ester C 5 H 10 O Butanoic acid, methyl ester C 5 H 10 O Hexanone C 6 H 12 O Pentanone, 4-methyl- C 6 H 12 O Pentenal, (2E)- C 5 H 8 O Pentenal, (2Z)- C 5 H 8 O Butenoic acid, methyl ester, (2E)- C 5 H 8 O Pentanol C 5 H 12 O Penten-1-ol, (2Z)- C 5 H 10 O Butanoic acid, 3-methyl-, methyl ester C 6 H 12 O Hexanone C 6 H 12 O Butanoic acid, ethyl ester C 6 H 12 O Hexanal C 6 H 12 O Acetic acid, butyl ester C 6 H 12 O Pentanoic acid, methyl ester C 6 H 12 O Butanoic acid, 2-hydroxy-, methyl ester C 5 H 10 O ,3-Heptanedione C 7 H 12 O Butanoic acid, 1-methylethyl ester C 7 H 14 O Butanoic acid, 2-methyl- C 5 H 10 O Butanoic acid, 2-methyl-, ethyl ester C 7 H 14 O Hexenal, (2E)- C 6 H 10 O Hexen-1-ol, (2E)- C 6 H 12 O Heptanal C 7 H 14 O Butanol, 3-methyl-, 1-acetate C 7 H 14 O Butanol, 2-methyl-, 1-acetate C 7 H 14 O Heptanone C 7 H 14 O Butanethioic acid, S-methyl ester C 5 H 10 O S Butanoic acid, propyl ester C 7 H 14 O Pentanoic acid, ethyl ester C 7 H 14 O Hexanol C 6 H 14 O Acetic acid, pentyl ester C 7 H 14 O Buten-1-ol, 3-methyl-, 1-acetate C 7 H 12 O Hexanoic acid, methyl ester C 7 H 14 O Butenoic acid, 2-methyl-, ethyl ester C 7 H 12 O Hepten-2-one, 6-methyl- C 8 H 14 O Butanoic acid, butyl ester C 8 H 16 O Hexanoic acid, ethyl ester C 8 H 16 O Octanal C 8 H 16 O Acetic acid, hexyl ester C 8 H 16 O Hexen-1-ol, 1-acetate, (2E)- C 8 H 14 O Butanoic acid, 1-methylbutyl ester C 9 H 18 O Hexanol, 2-ethyl- C 8 H 18 O Hexanoic acid, 1-methylethyl ester C 9 H 18 O 2 97

98 Table 2-6. Continued. CAS Registry Number Chemical Name Formula Butanoic acid, 3-methyl-, butyl ester C 9 H 18 O Octenal, (2E)- C 8 H 14 O Butanoic acid, pentyl ester C 9 H 18 O (2H)-Furanone, 4-methoxy-2,5-dimethyl- C 7 H 10 O Octenal, (2Z)- C 8 H 14 O Nonanone C 9 H 18 O Furanmethanol, 5-ethenyltetrahydro-α,α,5-trimethyl-, (2R,5S)-rel- C 10 H 18 O ,6-Octadien-3-ol, 3,7-dimethyl- C 10 H 18 O Nonanal C 9 H 18 O Acetic acid, 2-ethylhexyl ester C 10 H 20 O Acetic acid, phenylmethyl ester C 9 H 10 O Butanoic acid, hexyl ester C 10 H 20 O Butanoic acid, (2E)-2-hexen-1-yl ester C 10 H 18 O Octanoic acid, ethyl ester C 10 H 20 O Acetic acid, octyl ester C 10 H 20 O Bicyclo[3.1.1]hept-2-ene-2-carboxaldehyde, 6,6-dimethyl- C 10 H 14 O Decenal, (2E)- C 10 H 18 O Benzoic acid, 2-amino-, methyl ester C 8 H 9 N O Butanoic acid, octyl ester C 12 H 24 O Decanoic acid, ethyl ester C 12 H 24 O Butanoic acid, 2-methyl-, octyl ester C 13 H 26 O Butanoic acid, 3-methyl-, octyl ester C 13 H 26 O Cyclohexene-1-methanol, 4-(1-methylethenyl)-, 1-acetate C 12 H 18 O (3H)-Furanone, 5-hexyldihydro- C 10 H 18 O Propanoic acid, 2-methyl-, nonyl ester C 13 H 26 O Octane, 3-ethyl- C 10 H Phenol, 2,6-bis(1,1-dimethylethyl)-4-methyl- C 15 H 24 O ,6,10-Dodecatrien-3-ol, 3,7,11-trimethyl-, (6E)- C 15 H 26 O Hexanoic acid, octyl ester C 14 H 28 O Butanoic acid, decyl ester C 14 H 28 O (3H)-Furanone, dihydro-5-octyl- C 12 H 22 O 2 Note: Chemical Abstract Services (CAS) registry numbers were used to query SciFinder substances database for associated chemical name and molecular formula. Listed in order of increasing retention time. 98

99 99 MALIC CITRIC GLUCOSE FRUCTOSE SUCROSE

100 Figure 2-1. Cluster analysis of strawberry samples and quantified metabolites. Twoway Ward cluster analysis of strawberry samples (diagonal bottom) and quantified single metabolites (right) with overall liking score of sample (top) constructed using JMP 8. Standardization of metabolite concentration is by row mean and standard deviation, with high values represented as red, average as green, and low as blue. The hierarchy and distance of segments within the vertical dendrogram indicates relatedness of concentration across samples for single metabolites. Structure of the horizontal dendrogram indicates relatedness of all metabolite concentrations among individual samples. 100

101 27 Dec Jan Jan Jan 2011 WK-2 24 Jan 2011 WK-3 31 Jan 2011 WK-4 07 Feb 2011 WK-5 14 Feb 2011 WK-6 21 Feb 2011 WK-7 28 Feb Mar Mar Dec Jan Jan 2012 WK-1 16 Jan Jan Jan 2012 WK-4 06 Feb 2012 WK-5 13 Feb 2012 WK-6 20 Feb 2012 WK-7 27 Feb Mar 2012 WK-9 12 Mar 2012 TOTAL RAIN (cm) RELATIVE HUMIDITY (%) SOLAR RADIATION (w 1 m -2 ) TEMPERATURE RANGE (C) A R 2 = 0.250, p-value < 0.001* R 2 = 0.068, p-value = B R 2 = 0.227, p-value < 0.001* R 2 = 0.239, p-value < 0.001* C R 2 = 0.177, p-value = 0.001* D R 2 = 0.147, p-value < 0.001* E R 2 < 0.001, p-value = F R 2 = 0.003, p-value = G R 2 = 0.037, p-value = H R 2 = 0.014, p-value = HARVEST WEEK AND DATE 2012 HARVEST WEEK AND DATE 101

102 Figure 2-2. Season Environmental Conditions. Daily maximum and minimum temperatures (A and B), daily average solar radiation (C and D), daily average relative humidity (E and F), and daily total rain fall (G and H) during the 2011 (A, C, E, and G) and 2012 (B, D, F, and H) seasons. Data for Balm, FL obtained from Florida Automated Weather Network ( Data spans three weeks prior to first harvest through last harvest of each season with individual harvests indicated by dotted vertical line and harvest week number. Dashed horizontal lines represent means of environmental measures. Solid lines are the bivariate fit of environmental measure across season. Coefficients of determination (R 2 ) and p-value of fit is listed above individual scatterplots and are calculated using bivariate fit in JMP. 102

103 TOTAL VOLATILES (ng 1 gfw -1 h -1 ) TOTAL VOLATILES (ng 1 gfw -1 h -1 ) TOTAL VOLATILES (ng 1 gfw -1 h -1 ) SUCROSE (mg 1 100gFW -1 ) GLUCOSE (mg 1 100gFW -1 ) FRUCTOSE (mg 1 100gFW -1 ) A R 2 = 0.350, p-value < 0.001* 3000 B R 2 = 0.064, p-value = C R 2 = 0.041, p-value = WEEK WEEK WEEK D R 2 = 0.338, p-value < 0.001* E R 2 = 0.305, p-value < 0.001* F R 2 = 0.001, p-value = WEEK SUCROSE (mg 1 100gFW -1 ) FRUCTOSE (mg 1 100gFW -1 ) Figure 2-3. Individual sugars and total volatiles regressed against season progression. Regression of sucrose (A), glucose (B), fructose (C), and total volatiles (D) by harvest week during the seasons. Total volatile concentration is regressed against sucrose (E) and fructose (F). Sucrose (A) and total volatiles (D) demonstrate a significant negative fit to harvest week, unlike glucose (B) and fructose (C). A strong relationship between total volatile emission and sucrose concentration is found (E) that is not observed between total volatiles and glucose (data not shown) and fructose (F). Coefficient of determination (R 2 ) and p-value of fit is listed above individual scatterplots and is calculated using bivariate fit in JMP 8. Dashed line represents mean of independent variable, solid line represents linear fit, dashed/dotted ellipse indicates 95% confidence range of data, and asterisk denotes significant fit (α = 0.05). 103

104 104

105 Figure 2-4. Regression of hedonic and sensory measures to physical and chemical fruit attributes. Hedonic overall liking is regressed against hedonic texture liking (A), sweetness intensity (B), sourness intensity (C), and strawberry flavor intensity (D). Overall liking is fitted to harvest week (E), total sugars (F), titratable acidity (G), and total volatiles (H). Texture liking is examined against puncture force (I) and harvest week (J), and forces is examined against harvest week (K). Sweetness intensity is regressed against total sugars (L), sucrose (M), glucose (N), and total volatiles (O). Intensity of sourness is fitted to titratable acidity (P), malic acid (Q), citric acid (R), and total sugars (S). Strawberry flavor intensity is regressed by total volatiles (T) and select single volatile compounds (U), (V), and (W).Coefficient of determination (R 2 ) and p-value of fit is listed above individual scatterplots and is calculated using bivariate fit in JMP 8. Dashed line represents mean of independent variable, solid line represents linear fit, dashed/dotted ellipse indicates 95% confidence range of data, and asterisk denotes significant fit (α = 0.05). 105

106

107 Figure 2-5. Volatile Chemical Structure. Chemical structure of volatile compounds quantified in strawberry. Sorted by increasing retention time (left to right, top row to bottom row) and identified by CAS #. 107

108 CHAPTER 3 ENGINEERING OF THE AROMA FLAVOR VOLATILE METHYL ANTHRANILATE IN PETUNIA AND STRAWBERRY Background Methyl anthranilate is a distinguishing constituent of volatile mixtures emitted or synthesized by diverse plant species. Emission of methyl anthranilate originates in multiple plant structures, often alluding to the biological role within that plant species. The biosynthesis in reproductive structures is well known, as methyl anthranilate is a characteristic component of the headspace of Citrus and jasmine flower (Jasminum sambac) (Edris et al., 2008; Najman, 1993), Concord grape (Vitis labrusca) (Massa et al., 2008), wild strawberry (F. vesca) (Ulrich et al., 1997). Its effectiveness as a bee attractant facilitates pollination in floral structures (Najman, 1993), while its potential antimicrobial and antifungal capacities in essential oil of Retama raetam suggest a role in promoting survivability of flowers and fruits (Edziri et al., 2010). Emission from developing fruit may prevent premature foraging, as methyl anthranilate is a potent irritant to starlings (Sturnus vulgaris) and is avoided whether in air or water (Stevens and Clark, 1998). The leaves of Zea mays are known to emit methyl anthranilate upon herbivory (Turlings and Benrey, 1998) and it is shown to be an indirect defense mechanism for attraction of parasitic wasps that require specific herbivores for oviposition (Turlings et al., 2005). With respect to humans, flowers and fruits possessing methyl anthranilate are regarded as having favorable aromas and flavors. Also, it was used as one of the first artificial flavors. As with most plant volatiles, methyl anthranilate presents a means for the plant to interact with other biological entities through chemical emission and sensory mechanisms. 108

109 Methyl anthranilate constitutes nine percent of volatile content in the juice of Concord grapes (Vitis labrusca). This dominance makes these grapes one of the richest biological sources of methyl anthranilate. Acyltransferase activity capable of producing methyl anthranilate was identified in crude protein extracts of ripe grape mesocarp (Figure 3-1). This activity was dependent upon precursor anthaniloyl-coa and methanol. Accumulation of anthranilic acid and methyl anthranilate peaked at approximately 40 µm as grapes reached full maturity, and the concentration of methanol also increased during the ripening of grape further supporting this biosynthesic mechanism (Wang and De Luca, 2005). Purified protein of ANTHRANILOYL-CoA:METHANOL ACYLTRANSFERASE (VlAMAT) was digested, sequenced, and the transcript subsequently cloned (Wang and De Luca, 2005). Characterization of recombinant and native protein indicates a higher affinity and catalytic rate of VlAMAT for anthraniloyl-coa and methanol than structurally similar benzoyl-coa and benzyl alcohol. However, the greatest in vitro activity of recombinant protein is with anthraniloyl-coa and benzyl alcohol as substrates and relatively small amounts of benzyl alcohol is present in grape. VlAMAT transcript abundance increases with the progression of ripening, as does anthranilic acid, VlAMAT protein activity, and thus methyl anthranilate in Concord grape varieties. Conversely, in Vitis vinifera penultimate precursor, protein, and product are not detectable (Wang and De Luca, 2005). This first instance of tissue specific methyl anthranilate biosynthesis is due to a ripening paradigm and enzymatic specificity of VlAMAT. As a result, biosynthesis results in a significant concentration of methyl anthranilate, contributing to Concord grape aroma and flavor. 109

110 A second instance of tissue specific methyl anthranilate biosynthesis is induced in herbivory damaged leaves of Zea mays (Koellner et al., 2010). Three paralogs of ANTHRANILIC ACID METHYL TRANSFERASE (ZmAAMT) were cloned. Within thirty minutes following Spodoptera larvae herbivory, jasmonic acid signaling up regulated ZmAAMT1.1 and ZmAAMT3. Methyl anthranilate is detectable in the leaves after 30 minutes, but emission from the tissue does not occur until two hours after feeding. Crude protein extract from herbivory damaged leaves, but not control leaves, is capable of producing methyl anthranilate. The extract exhibits a methyl transferase activity that is highest with S-adenosyl methionine and anthranilic acid for the synthesis of methyl anthranilate (Figure 3-1). Crude extracts confirm biosynthesis of methyl anthranilate is in response to herbivory. However, that alone does not distinguish which of the two upregulated paralogs is responsible for the majority of methyl anthranilate biosynthesis. Recombinant proteins of ZmAAMT1.1, 1.2, 2, and 3 show the highest relative activity with anthranilic acid. Benzoic acid as substrate reaches a quarter of anthranilic acid activity for ZmAAMT3, while ZmAAMT1.1 has only three percent relative activity. Following herbivory, anthranilic acid increases by 12-fold to a concentration of 0.12 nmol 1 gfw -1. A K m of over 2 mm for anthranilic acid is limiting to the ZmAAMT3 rate of reaction and excludes it as the major contributor to induced methyl anthranilate production. The 641 µm K m of ZmAAMT1.1 is at least three orders of magnitude greater than the whole leaf anthranilic acid levels (Koellner et al., 2010), which is not optimal. Anthranilic acid is an intermediate of tryptophan biosynthesis, which occurs in the chloroplast. Subcellular compartmentalization of anthranilic acid produced by ANTHRANILATE SYNTHASE, which is localized to the chloroplast (Bohlmann et al., 110

111 1996), can provide the enriched environment necessary for efficient methyl anthranilate biosynthesis. Colocalization of protein and substrate is one means of ensuring enzymatic specificity in vivo. Another mechanism of specificity is derived from the protein structure as it can be exclusive to certain substrates. Comparison of homologs in Zea mays and other species as well as site directed mutagenesis indicates substrate specificity for anthranilic acid over salicylic acid is conferred by tyrosine 246 (Tyr-246 to Trp), while benzoic acid is excluded by glutamine 167 (Gln-167 to His) (Koellner et al., 2010). Two specific amino acid residues result in highly specific activity of ZmAAMT1.1 for anthranilic acid compared to benzoic acid or salicylic acid which is preferred by other members of the SABATH gene family (Koo et al., 2007) Methyl anthranilate is absent from a vast majority of commercial cultivars of strawberry. Comparison of whole fruit and GC-olfactometry of methyl anthranilate containing F. vesca to deficient F. x ananassa imparted a heavy sweet and a jasminelike orthonasal and retronasal characteristic (Ulrich et al., 2007). The sole transgenic effort to alter strawberry aroma in literature focused on an endogenous O- METHYLTRANSFERASE responsible for S-adenosyl methionine dependent methylation of 3(2H)-furanone, 4-hydroxy-2,5-dimethyl- to DMF (Lunkenbein et al., 2006). Up and downregulation of volatile synthesis is observed using sense and antisense constructs of O-METHYLTRANSFERASE. This work attempts to introduce methyl anthranilate into the deficient, yet commercially viable cultivar, Strawberry Festival through the overexpression of ZmAAMT1.1. Over-expression of tomato (Solanum lycopersicum) PHENYLACETALDEHYDE REDUCTASE in Petunia x hybrida 111

112 cv. Mitchell Diploid increased 2-phenylethanol floral emission by ten-fold (Tieman et al., 2007). For this reason, ZmAAMT1.1 is also transformed into petunia, as an established pipeline for efficiently generating and analyzing altered volatile phenotypes exists. The methyl transferase of Zea mays is preferred over alcohol acyltranserase mechanism of Vitis labrusca, mainly for its direct methylation of the primary metabolite anthranilic acid, while the ZmAAMT1.1 paralog is selected due to its higher specificity. Results Methyl Anthranilate Content among Fragaria In order to understand the extent of genetic variability for methyl anthranilate synthesis in Fragaria methyl anthranilate had to be identified using a GC coupled to an electron impact mass spectrometer (GC-MS). Fragaria volatile collection samples were run on the GC-MS followed by a dilution of analytical standard methyl anthranilate. Mass spectra corresponding to the retention time of the analytical standard from Fragaria samples were compared to one another, methyl anthranilate standard, and National Institute of Standards and Technology (NIST) mass reference spectra (Figure 3-2). NIST reference (Figure 3-2.A), methyl anthranilate standard (Figure 3-2.B), and F. vesca cv. Fragola Quattro Stagioni mass spectra showed characteristic ions 119, 151, 92, and 65 in decreasing relative abundance. However, none of these particular ions were detected in F. x ananassa cv. Strawberry Festival. The content of methyl anthranilate was quantified in 17 cultivars of four Fragaria species using GC-FID to ascertain the biological variation: nine diploid F. vesca cultivars, two hexaploid F. moschata, one octoploid F. virginiana, and five octoploid F. x ananassa (Figure 3-3). The mean content of each cultivar was from a minimum of five biological replicates from at least two harvest dates. 112

113 Within F. vesca there were eight cultivars with an average content of less than 10 ng 1 gfw -1 hr -1 with Hawaii-4 having the lowest content at 2.65 ng 1 gfw -1 hr -1. Reine des Vallees on the other hand had a mean methyl anthranilate emission of ng 1 gfw -1 hr -1, but large variance of the mean was due to phenotypic variation from harvest to harvest. The cultivars Capron and Profumata di Tortona of F. moschata, a hexaploid species, exhibited the highest mean methyl anthranilate emission quantified in this study at and ng 1 gfw -1 hr -1, respectively. The volatile emission from Capron was nearly two-fold greater than the highest F. vesca accession. F. virginiana was one of the progenitor species to modern F. x ananassa, and the F. virginiana cultivar Intensity did not produce any detectable amounts of methyl anthranilate. The same was observed for four of five F. x ananassa cultivars. In fact, Mara des Bois is the only octoploid in which methyl anthranilate was detected. However, it was not detectable at all points within a season and therefore had the lowest mean content of the twelve cultivars in which methyl anthranilate was measured. A range of methyl anthranilate emission was observed across Fragaria accession with a strong correlation to species. Reliable and appreciable emission in diploid and hexaploid material is for all practical purposes isolated from introgression into octoploid due to genetic architecture. ZmAAMT1.1 Expression Analysis in Transgenic Plants Overexpression construct and plant transformation The coding sequence (CDS) of Zea mays ANTHRANILIC ACID METHYL TRANSFERASE 1.1 (ZmAAMT1.1) was cloned into a Gateway entry vector, pdonr222, and subsequently recombined with a destination vector, phk-dest-oe, which generated a binary plant expression vector, pexp-zmaamt1.1 (Figure 3-4), for transformation of P. x hybrida cv. Mitchell Diploid and F. x ananassa cv. Strawberry 113

114 Festival. The ZmAAMT1.1 CDS is under the control of figwort mosaic virus 34S (pfmv 34S) promoter and Agrobacterium NOPALINE SYNTHASE 3 terminator (NOSt). Also, within the transfer-dna borders of the binary vector is the NEOMYCIN PHOSPOTRANSFERASE II (NPTII) CDS, which confers kanamycin resistance in transformed plants. Following transformation with pexp-zmaamt Mitchell Diploid and 25 Strawberry Festival T0 plantlets were regenerated in the presence of kanamycin. Petunia expression analysis To determine penetrance of the ZmAAMT1.1 transgene in transformed Mitchell Diploid background a one-step semi-quantitative reverse transcription polymerase chain reaction (sqrt-pcr) was used to first generate gene specific complimentary DNA from isolated total RNA of each T0 line which was then amplified in the same reaction. Visualization of ZmAAMT1.1 sqrt-pcr products after thirty cycles of amplification allowed for distinguishing differences in transcript abundance among transgenic lines. Thirty-eight lines were screened for sqrt-pcr transcript abundance of ZmAAMT1.1 and scored by comparing electrophoresis band intensity among one another and referencing sqrt-pcr of endogenous 18S, a consistent control for RNA loading (Figure 3-5). All but three lines exhibited expression of ZmAAMT1.1, (transgenic lines13, 23, and 38) while three lines exhibited very low, three low, twelve average, nine high, and eight very high relative expression. A ZmAAMT1.1 sqrt-pcr product was not visible in the transgenic background P. x hybrida cv. Mitchell Diploid demonstrating the specificity for amplification of the transgene. Six transgenic lines were chosen for quantitative real time PCR (qrt-pcr) to measure relative transcript based off initial semi-quantitative results (Figure 3-6). 114

115 ZmAAMT1.1 transcript was quantified relative to PhFBP7 using comparative Ct method. The greatest expression was found in line 1 and 45, while 7, 13, 16, and 38 exhibited moderate expression, and as expected no amplification was detected in wild-type Mitchell Diploid. Strawberry expression analysis Transcript abundance was also determined in pexp-zmaamt1.1 transformed F. x ananassa Strawberry Festival using sqrt-pcr as in Mitchell Diploid. The RNA loading control sqrt-pcr of endogenous 18S exhibits modest variability from sample to sample and was taken into account when scoring ZmAAMT1.1 expression (Figure 3-9). Two transgenic lines were scored as very low expression, four lines as low, ten as moderate, four as high, and three as very high. The highest expression was likely found in ZmAAMT1.1-OE 3, and therefore the best candidate for emission of greatest amount methyl anthranilate. Purified pexp-zmaamt1.1 was used as a positive amplification control and exhibits very efficient amplification, while the negative amplification control water ddi not amplify, as expected. ZmAAMT1.1 Volatile Analysis in Transgenic Plants Volatile compounds emitted from transgenic ZmAAMT1.1-OE and non-transgenic (wild type) Mitchell Diploid petunia were collected and quantified to determine if methyl anthranilate phenotype was present. Mean methyl anthranilate content from two biological replicates in 24 transgenic lines and Mitchell Diploid is depicted in Figure 3-7. No methyl anthranilate was detected in Mitchell Diploid and six transgenic lines (5, 11, 13, 14, 44, and 45) using GC. Thirteen transgenic lines had detectable amounts less than 10 ng 1 gfw -1 hr -1, while four lines had methyl anthranilate content greater than 10 ng 1 gfw -1 hr -1. The highest content was found in ZmAAMT1.1-OE 1 with a mean of 115

116 41.98 ng 1 gfw -1 hr -1. GC-MS analysis of ZmAAMT1.1-OE, wild type Mitchell Diploid, and analytical standard confirmed introduction of a novel petunia volatile compound, methyl anthranilate, by presence of four predominant ions (119, 151, 92, and 65 determined from analytical standard and NIST) in transgenic lines, but not wild type (Figure 3-8). Volatile analysis of wild type and transgenic lines of Strawberry Festival has yet to be accomplished. Regeneration of F. x ananassa Strawberry Festival is markedly longer than that of P. x hybrida Mitchell Diploid. Also, short-day photoperiod flower induction dependence of Strawberry Festival is limiting to fruit set during long days of summer. Volatile analysis of transgenic strawberry for presence of methyl anthranilate will be conducted as fruit makes itself available. Discussion The emission of methyl anthranilate from various F. vesca and F. moschata accessions is confirmed using MS and analytical standards. Previously, F. moschata cv Cotta exhibited nearly three-fold greater emission of methyl anthranilate than F. vesca ssp. vesca f. alba (Ulrich et al.). Similar results are observed with different F. vesca and F. moschata accessions used in this work. The highest level of methyl anthranilate emission from F. moschata cv. Capron, in excess of 50 ng 1 gfw -1 hr -1, overshadows the majority of F. vesca, approximately 5-10 ng 1 gfw -1 hr -1. The only octoploid accession to emit detectable levels of methyl anthranilate is F. x ananassa cv. Mara des Bois while it is undetected in four commercial cultivars. These results underscore the lack of potential impactful volatile compound in commercial material, but the pervasive emission in lower ploidy material justifies engineering efforts to understand methyl anthranilate effect on aroma and flavor of Petunia and Strawberry Festival. 116

117 The overexpression of heterologous Z. mays ANTHRANILIC ACID METHYL TRANSFERASE is successful at introducing emission into otherwise deficient P. x hybrida cv. Mitchell Diploid. The use of Agrobacterium for the generation of transgenic petunia is an effective method, especially when taking advantage of kanamycin resistance for positive selection during plantlet regeneration (Jorgensen et al., 1996). This is evident in the fact that all but three T0 petunias had detectable levels of expression, while eight lines exhibited very high expression of ZmAAMT1.1 using sqrt- PCR methods. Expression or unspecific amplification is not detected in Mitchell Diploid, which validates the methods of the transgene transcript abundance assay. Greater resolution of transcript level is achieved using qpcr on a subset of transgenic lines. Lines 45 and 1 have high semi-quantitative levels and demonstrate approximately 20- and 30-fold greater expression, respectively, than line 38, all of which is estimated to have low to average expression using semi-quantitative methods. Again, Mitchell Diploid exhibits no expression. The much greater magnitude of expression in line 1 is otherwise under estimated if not for the qrt-pcr methods. Despite detection of expression in 35 of 38 lines, the emission of methyl anthranilate is only detectable in flowers from 18 of 24 lines analyzed. Exclusion of enzyme from substrate or limitations in substrate flux can potentially account for this observed discrepancy. Estimated expression in these deficient lines is far from the highest and more often than not at the lowest end of detection. A caveat however is line 45, which exhibited second highest relative transcript abundance in qrt-pcr analysis, but has no detectable levels of methyl anthranilate. Conversely, line 1 demonstrates the greatest level of methyl anthranilate emission, just under 30 ng 1 gfw -1 hr -1, and the 117

118 greatest relative expression in qrt-pcr. Lines 13 and 16 have similar expression levels; however 13 has no detectable methyl anthranilate while 16 emits over 10 ng 1 gfw -1 hr -1. The efficiency of generating petunia with transgene expression is greater than actual detectable phenotype, and relative expression level does not always coordinate with emission levels of methyl anthranilate. These discrepancies are quite common with petunia transgenics (David G. Clark, personal communication). Transcript and volatile screening of numerous ZmAAMT1.1 overexpressing Mitchell Diploid lines found transgenic line 1 to have the greatest transcript and methyl anthranilate expression, successfully introducing a heterologous enzyme for the production of a novel volatile compound. After normalizing for mass, the headspace emission of flowers from thirteen lines of transgenic petunia is within the range of most F. vesca fruit assayed. Of special interest is transgenic petunia ZmAAMT1.1-OE 1 with emission measured at just under 30 ng 1 gfw -1 hr -1. This quantity is on par with F. vesca Reine des Vallees, which emits roughly three-fold more methyl anthranilate than the rest of F. vesca cultivars. Given the success in petunia, anticipation is high that the to be determined methyl anthranilate content of transgenic Strawberry Festival will be comparable to F. vesca, in which the volatile is believed to impart favorable aroma and flavor (Ulrich et al., 2007). The transformation of strawberry is not as inherently simple as that of petunia, but can be an effective method when taking advantage of kanamycin resistance for positive selection during plantlet regeneration (Folta et al., 2006). A range in relative expression is observed in all regenerated strawberry demonstrated expression of ZmAAMT1.1 using sqrt-pcr. The greatest expression is observed in line 3, while line 118

119 5 has the lowest relative intensity. Observable discrepancies between transcript and volatile emission in petunia requires a volatile screen of transformed Strawberry Festival prior to making assumptions of lines with methyl anthranilate emission, let alone high levels of emission. Successful engineering of methyl anthranilate biosynthesis likely requires appropriate targeting of ZmAAMT1.1 to subcellular compartment containing appropriate substrate, anthranilic acid. Anthranilic acid is the direct product of ANTHRANILATE SYNTHASE which enzymatically cleaves a pyruvate moiety from chorismate (Bohlmann et al., 1996), an intermediate reaction of tryptophan biosynthesis. The entirety of this necessary pathway occurs exclusively in the chloroplast (Mano and Nemoto, 2012), therefore transgenes need to localizes there. Web-based chloroplast transit peptide prediction of ZmAAMT1.1 using ChloroP gives a weak probability of at amino acid residue 56 (Emanuelsson et al., 1999). Also, a small N-terminal helix from residue 24 to 47 is predicted by PredictProtein (Rost et al., 2004) and SWISS-MODEL (Arnold et al., 2006). This is a characteristic motif for some chloroplast transit peptides (Bruce, 2000), however, exact defining constituents are still poorly understood (Li and Chiu, 2010). The detection of methyl anthranilate in transgenic petunia and previously reported compartmentalization of tryptophan biosynthesis, including intermediate anthranilic acid, suggests successful targeting of ZmAAMT1.1 to the plastid. Chemical supplier Material Safety Data Sheet lists physical properties of methyl anthranilate, which are interesting given its role as an emitted volatile. An astonishing low vapor pressure of 3.6 Pascal and a melting point of 24º C are not conducive to high volatility. A lag of over an hour between detection in tissue versus headspace is 119

120 observed in herbivory-damaged Zea mays leaves (Koellner et al., 2010), perhaps requiring concentration to build or requiring extra time for diffusion. The hypothesized chloroplast localized biosynthesis would require at a minimum the volatile compound to traverse three lipid bilayer membranes. Plastid formation occurs early in petunia corolla development, before degrading at anthesis, coinciding with maximum endogenous floral emission (Colquhoun et al., 2010b) possibly freeing otherwise membrane constrained methyl anthranilate. Headspace methyl anthranilate of petunia will contribute directly to the floral fragrance perceived through orthonasal olfaction. Conversely, internal methyl anthranilate could potentially contribute to retronasal olfaction detection while consuming strawberry fruit. Comparison of internal and emitted volatiles will provide insights into the relationship between emitted and pooled methyl anthranilate, which may influence orthonasal and retronasal olfaction perception. Petunia emission of methyl anthranilate at levels comparable to F. vesca is attained by over-expression of ZmAAMT1.1, successfully producing a previously unreported volatile in petunia and potentially altering floral fragrance. Previously, alteration of endogenous petunia volatiles greatly affected pollinator/herbivore interaction (Kessler et al.). Introduction of a novel petunia floral volatile could have similar effects in nature, but human perception is of more immediate interest. The widespread presence of methyl anthranilate in flavoring and aroma of natural and synthetic products suggests a positive response to transgenic petunia would be observed in consumer fragrance panels. These results are also promising for efforts to engineer methyl anthranilate emission in Strawberry Festival. In the event of methyl anthranilate phenotype, multiple 120

121 consequences are possible. The emission of methyl anthranilate may serve as an avian repellent, reducing loss of ripe fruit to birds. Also, the ability to attract parasitic wasps can alleviate herbivory pressure. In regards to postharvest, the presence of methyl anthranilate in fruit may result in less microbial and fungal growth leading to prolonged shelf life. The primary question however, is whether flavor or aroma of Strawberry Festival is enhanced by the presence of methyl anthranilate, a sweet, floral component of F. vesca. Future Work Ultimately, it must be known if consumer perception is altered by the presence of methyl anthranilate in Mitchell Diploid or Strawberry Festival. Seed of T1 ZmAAMT1.1-OE petunia will be sown, an individual of high emission selected, propagated, and grown out in a climate controlled glasshouse. Flowers will be harvested for a consumer panel triangle test to ascertain a difference and/or preference of petunia fragrance with or without methyl anthranilate, and to see if humans perceive them as positive. Screening of T0 ZmAAMT1.1 Strawberry Festival fruit will hopefully identify multiple lines with capabilities of producing methyl anthranilate. Once identified, the appropriate line will need to be propagated and grown out in climate controlled glasshouse for consumer flavor panels. Internal Review Board approval and consumer written consent for the consumption of transgenic material will be obtained. Consumers will directly compare wild-type Strawberry Festival to a methyl anthranilate containing transgenic line to discern any perceptual differences in overall liking, sweetness intensity and flavor intensity. 121

122 More fundamental work could involve crossing homozygous petunia lines of ZmAAMT1.1-OE x CHORISMATE MUTASE-RNAi (CM). CHORISMATE MUTASE competes with ANTHRANILATE SYNTHASE for substrate, diverting it from tryptophan biosynthesis to phenylpropanoid biosynthesis (Colquhoun et al., 2010a). Hypothetically, increased flux through tryptophan biosynthesis will allow greater methyl anthranilate biosynthesis. Metabolite analysis will rely on aqueous supernatant from centrifuged flower tissue. Solid phase extraction will aid in sample preparation prior to analysis on high pressure liquid chromatograph coupled to triple quadrupole MS. Multiple reaction monitoring mode will allow for quantification of MS/MS product ions, particularly of chorismate, anthranilic acid, methyl anthranilate, and tryptophan. Comparison of these compounds in wild type Mitchell Diploid, ZmAAMT1.1-OE, CM-RNAi, and ZmAAMT1.1-OE x CM-RNAi could provide insights on metabolic flux at key nodes of aromatic amino acid synthesis in plants. Materials and Methods Plant Material Inbred P. x hybrida Mitchell Diploid plants were the wild-type control and background for transformation in all petunia experiments (Mitchell et al., 1980), while commercially available F. x ananassa cv. Strawberry Festival was the wild-type control and background for transformation of strawberry experiments. All petunia were grown in glass greenhouses (Dexter et al., 2007). Wild-type and transformed Strawberry Festival were grown in glass greenhouses and watered daily with Verti-Gro hydroponic fertilizer (0.6 grams per liter with trace elements and 2% magnesium) and supplemented with calcium nitrate (0.3 g per liter ). Materials of 122

123 Figure 3-3 were grown in Citra, FL according to current commercial practices for annual strawberry plasticulture in Florida (Whitaker et al., 2011) (Santos et al., 2012). Generation of Transgenic ZmAAMT1.1 Plants Overexpression construct A puc57 vector containing the synthesized CDS of ZmAAMT1.1 (Koellner et al., 2010) was obtained from GenScript. Use of Gateway Cloning (Invitrogen) for the generation of entry vector requires a two-step amplification scheme to incorporate recombination site adapters to CDS of ZmAAMT1.1. The first step used Phusion (Finnzymes) recombinant polymerase to amplify the CDS with partial attb adapters (forward primer 5 AAAAAGCAGGCTTCATGCCGATGAGAATCGAGCGTGAT 3 and reverse primer 5 AGAAAGCTGGGTCTCACACATGAATTATTGCTTTCTC 3 ). The second amplification used the first product as a template and completes the recombination sites using attb primers (forward primer 5 GGGGACAAGTTTGTACAAAAAAGCAGGC 3 and 5 GGGGACCACTTTGTACAAGAAAGCTGGGT 3 ). BP Clonase catalyzed a recombination reaction between polyethylene glycol purified attb PCR product and attp pdonr222 vector for site directed recombination of ZmAAMT1.1 CDS for lethal ccdb CDS to generate pentr ZmAAMT1.1. Mach1 E. coli transformation with BP Clonase reaction was selectively screened for NPTII containing pentr - ZmAAMT on LB agar plates containing kanamycin. Digestion and Sanger sequencing confirmed recombination and identity of ZmAAMT1.1. LR Clonase catalyzed recombination between attl containing pentr ZmAAMT1.1 and attr contain phk-dest OE for site directed recombination of ZmAAMT1.1 CDS for lethal ccdb CDS to generate pexp ZmAAMT

124 The binary expression vector ultimately for plant transformation places ZmAAMT1.1 under the control of pfmv 34S (Richins et al., 1987) and nost. The recombination product was transformed into Mach1 E. coli. ccdb lethality selected against unreacted phk-dest OE and undesired recombination products, while streptomycin LB agar plates selected for pexp-zmaamt1.1-oe, which contains the aada1 resistance gene. Colonies were qualified via digestion of both vector and insert of pexp ZmAAMT1.1, as well as amplifying across recombination site from pfmv 34S into ZmAAMT1.1. Plant transformation and regeneration Fifty independent pexp-zmaamt1.1-oe Mitchell Diploid petunia were generated using Agrobacterium mediated transformation of sterile leaf disc and subsequent plantlet regeneration (Jorgensen et al., 1996). Twenty-five independent pexp-zmaamt1.1-oe Strawberry Festival were generated using Agrobacterium mediated transformation of sterilized leaf and petiole segments and subsequent plantlet regeneration (Folta et al., 2006). Kanamycin resistance conferred by presence of NPTII within T-DNA of pexp ZmAAMT1.1 allows for initial screening of plantlets. T0 petunia were self-pollinated to maintain transgenic events through seed. T0 Strawberry Festival is maintained through propagation of daughter plants due to heterozygosity of octoploid background. RNA Isolation Petunia Developmental stage six petunia flower buds are tagged two days prior to harvest of stage eight fully expanded flowers (Colquhoun et al., 2010b). At 16:00 flowers were excised from the plant at the peduncle and frozen immediately in liquid nitrogen. Whole flower was then ground in liquid nitrogen. Total RNA was extracted 124

125 from approximately 500 mg of tissue according to Verdonk et al., (2003) and reconstituted in 50 µl DEPC treated water. Residual DNA was digested with TURBO DNase (Ambion Inc.) and RNeasy Mini Spin Column (QIAGEN) removes carry-over metabolites prior to downstream applications. Strawberry Young expanding leaf tissue was harvested at 16:00 and frozen immediately in liquid nitrogen. Leaf tissue was then ground in liquid nitrogen. Total RNA was extracted from approximately 100 mg of tissue using 1 ml phenol extraction solution consisting of Tris ph 6.7 +/- 0.2 saturated phenol, 0.1% SDS (w/v), 0.32 M NaOAc, and 0.01M EDTA and 0.4 ml DEPC treated water (Ghawana et al., 2011). Ten seconds of vortex was followed by 5 minute incubation, which was followed by the addition of 0.2 ml chloroform. Five seconds of vortex, 5 minutes of incubation, and centrifugation at 16,000 rcf allowed for the separation of approximately 0.5 ml aqueous phase which was transferred to a new 1.5 ml Eppendorf tube. Nucleic acids were precipitated in 0.3 ml isopropanol and centrifuged for 5 minutes following 5 seconds of vortex and 10 minutes of incubation. Pellet was washed in 70% ethanol, dried and reconstituted in 50 µl DEPC treated water. TURBO DNase (Ambion Inc.) treatment digested residual DNA and RNeasy Mini Spin Column (QIAGEN) removed carry-over metabolites prior to downstream applications. Expression Analysis Abundance of ZmAAMT1.1 transcript in all viable transgenic events of petunia and strawberry was estimated via sqrt-pcr using One-Step RT-PCR kit (QIAGEN Co.) with 50 ng total RNA (ZmAAMT1.1 forward primer 5 AGGCACCAGAGCAACTGAAG 3 and reverse primer 5 125

126 CACCAGACACGAGTTCCTCA 3 ). P. x hybrida and F. x ananassa 18S were amplified (Ph18S forward primer 5 TTAGCAGGCTGAGGTCTCGT 3 and 5 AGCGGATGTTGCTTTTAGGA 3 ; Fa18s 5 ACCGTAGTAATTCTAGAGCT 3 and 5 CCACTATCCTACCATCGAAA 3 ) from all petunia and strawberry samples, respectively, to visualize RNA-loading concentration and to act as a positive control for reverse transcription and amplification. Sub-saturation amplification of 18S was achieved at 22 and 18 cycles, while ZmAAMT1.1 requires 30 and 37 cycles for Petunia and Fragaria, respectively. No template (H 2 O) controls were used in all reactions. Products of sqrt-pcr were analyzed under ultraviolet light following electrophoresis on 1% agarose gel with 0.5 ug 1 ml -1 ethidium bromide. Ct Quantitative qrt-pcr was performed and analyzed using a StepOnePlus real-time PCR system (Applied Biosystems, Foster City, CA). Power SYBR Green PCR (Applied Biosystems, Foster City, CA) was used to amplify and detect the products according to the manufacturer s protocol. Gene specificity is confirmed through analysis of melt curve. Volatile Analysis Developmental stage 8 petunia flowers were excised at the peduncle at 18:00 for an immediate one hour volatile collection. Each sample comprised of two flowers from a single line with at least two biological replicates of each line. Ripe glass greenhouse grown F. x ananassa were harvested at 16:00 and then kept at 4 C until 9:00 the following morning at which time they were prepared for a two hour volatile collection. Each sample comprised of 15 grams of quartered and diced berries from a single line with technical replication as possible. 126

127 Ripe field grown F. vesca were harvested at 9:00 in Citra, FL and kept on ice for transport to Gainesville, FL for immediate two hour volatile collection. Each sample comprised of approximately 15 grams of whole fruit, 5-10 berries from a single genotype with two to three biological replicates per cultivar per harvest. Reported average volatile content was pooled from at least two harvests. Volatile collection apparatus was a dynamic headspace system in which emitted volatiles are concentrated on HaySep porous polymer adsorbent (Hayes Separations Inc.) (Underwood et al., 2005) and then eluted as described by Schmelz (Schmelz et al., 2003). Quantification of volatiles in an elution was performed on an Agilent 7890A Series GC (carrier gas; He at 3.99 ml min -1 ; splitless injector, temperature 220 C, injection volume 2 µl) equipped with a DB-5 column ((5%-Phenyl)-methylpolysiloxane, 30 m length 250 µm i.d. 1 µm film thickness; Agilent Technologies, Santa Clara, CA, USA). Oven temperature was programmed from 40 C (0.5 min hold) at 5 C min -1 to 250 C (4 min hold). Signals were captured with a FID at 280 C. Peaks from FID signal were integrated manually with Chemstation B software (Agilent Technologies, Santa Clara, CA). Volatile emissions (ng 1 gfw -1 h -1 ) were calculated based on individual peak area relative to sample elution standard peak area. GC-Mass Spectrometry (MS) analysis of elutions were performed on an Agilent 6890N GC in tandem with an Agilent 5975 MS (Agilent Technologies, Santa Clara, CA, USA) and retention times were compared with authentic standards (Sigma Aldrich, St Louis, MO, USA) for volatile identification (Schmelz et al., 2001). 127

128 Statistical Analysis Histograms constructed in JMP 8.0 (SAS Institute Inc.) and depict mean volatile content per line/cultivar including standard error bars. 128

129 Figure 3-1. Alternative methyl anthranilate biosynthetic pathways in Zea mays and Vitis labrusca. ATP-dependent ligation of CoA to anthranilic acid provides substrate for Vitis labrusca ANTHRANILOYL-CoA:METHANOL ACYLTRANSFERASE (VlAMAT), which catalyzes the methanol dependent acyl transfer to create methyl anthranilate. Conversely, Zea mays ANTHRANILIC ACID METHYL TRANSFERASE (ZmAAMT) directly synthesizes methyl anthranilate upon methyl donation by S-adenosyl methionine. Chloroplast compartmentalized tryptophan biosynthesis is depicted for relation to primary metabolism. 129

130 Figure 3-2. Identification of methyl anthranilate in Fragaria. GC-MS electron ionization spectra at retention time of 29.2 minutes for methyl anthranilate analytical standard (B), Fragaria vesca cv. Fragola Quattro Stagioni captured volatiles (C), and Fragaria x ananassa cv. Strawberry Festival captured volatiles (D). Presence of ions 119, 151, 92, and 65 (listed in decreasing relative abundance) in National Institute of Standards and Technology mass reference spectra (A), analytical standard (B), and Fragola Quatrol Satgioni (C) confirms the presence of methyl anthranilate, however absence of ions in Strawberry Festival (D) indicates a lack of detectable production. 130

131 Figure 3-3. Methyl anthranilate content among various lines of Fragaria species. Histograms depict average content and standard error of methyl anthranilate from at least five biological replicates across a minimum of two harvests. Diploid (2x) Fragaria vesca cultivars emit approximately 5-10 ng 1 gfw -1 h -1, except for Reine des Vallees, which emits ng 1 gfw -1 h -1. In octoploid (8X) Fragaria x ananassa methyl anthranilate is only detectable in Mara des Bois but not any commercially relevant material. Emissions from both hexaploid (6x) Fragaria moschata cultivars are the highest measured, especially Capron with approximately ten-fold higher content than most Fragaria vesca accessions assayed. Analysis conducted in JMP. 131

132 Figure 3-4. Binary vector for stable transformation of petunia and strawberry with ZmAAMT1.1. T-DNA region within left (LB) and right borders (RB) is stably integrated into host plants. Expression of NPTII confers resistance to kanamycin selection during plantlet regeneration and is regulated by Agrobacterium NOPALINE SYNTHASE 5 promoter (pnos) and 3 terminator (NOSt). Figwort mosaic virus 34S promoter (pfmv 34S) and NOSt constitutively regulate transcription of ZmAAMT1.1 coding sequence. Protein translated from transcript will have enzymatic capability of synthesizing methyl anthranilate from anthranilic acid. Forward and reverse primers 1075 and 1076 are used in expression analysis of transgenic and wild type Petunia x hybrida Mitchell Diploid and Fragaria x ananassa Strawberry Festival. In silico vector constructed in VectorNTI. 132

133 Figure 3-5. ZmAAMT1.1 transcript abundance in overexpressing Petunia x hybrida cv. Mitchell Diploid. Screening of ZmAAMT1.1 transcript abundance in total RNA of T0 stage eight flower tissue to determine high expressing lines. Expected product of 156bp reached sub-saturation and differential amplification across T0 using a one-step RT-PCR at 30 cycles. The transformation plasmid, pexp-zmaamt1.1, is used for an amplification control and no amplification was observed in untransformed Mitchell Diploid. A second one-step RT-PCR of 18S ribosomal RNA is used as a loading control for gene specific reaction. Lines 13, 23, and 38 had no observable expression, while three lines exhibited very low, three low, twelve average, nine high, and eight very high relative expression. 133

134 ND ND Figure 3-6. ZmAAMT1.1 transcript abundance in overexpressing Petunia x hybrida cv. Mitchell Diploid. Quantitative real-time PCR was used determine relative abundance of ZmAAMT1.1 transcript in over-expressing lines using ΔΔCt method relative to line 38. Line 1 exhibits the greatest expression by far, followed by 45. Lines 7, 13, 16, and 38 demonstrate moderate expression, and wild-type Mitchell Diploid (MD) does not express ZmAAMT1.1 (ND not detected). Results compiled using StepOne. 134

135 Figure 3-7. Emission of methyl anthranilate from petunia flowers over-expressing ZmAAMT1.1. Eluents of solid phase captured headspace of T0 ZmAAMT1.1- OE Petunia x hybrida Mitchell Diploid are run on GC-FID for quantification of volatile compounds. Methyl anthranilate, chromatograph signal at minutes, is not detected in wild-type Mitchell Diploid and multiple transgenic lines. A range of emission is quantified in various transgenic events, most notably ZmAAMT1.1-OE 1 with an emission of 29.5 ng 1 gfw -1 h -1. Means and standard errors calculated from two biological replicates of two flowers for each transgenic line and wild-type using JMP

136 Figure 3-8. Identification of methyl anthranilate in petunia flower over-expressing ZmAAMT1.1.GC/MS electron ionization spectra at retention time of 29.2 minutes for methyl anthranilate analytical standard (B), Petunia x hybrida cv. Mitchell Diploid ZmAAMT1.1-OE 1 captured volatiles (C), and nontransgenic Mitchell Diploid captured volatiles (D). Presence of ions 119, 151, 92, and 65 (listed in decreasing relative abundance) in National Institute of Standards and Technology mass reference spectra (A), analytical standard (B), and ZmAAMT1.1-OE 1 (C) confirms the presence of methyl anthranilate, however absence of ions in Mitchell Diploid (D) indicates a lack of detectable production. 136

137 Figure 3-9. ZmAAMT1.1 transcript abundance in overexpressing Fragaria x ananassa cv. Strawberry Festival. Screening of ZmAAMT1.1 transcript abundance in total RNA of T0 leaf tissue to determine high expressing lines. Expected product of 156bp reached sub-saturation and differential amplification across T0 using a one-step RT-PCR at 37 cycles. The transformation plasmid, pexp-zmaamt1.1, is used for an amplification control and no amplification was observed in untransformed Strawberry Festival. A second one-step RT- PCR of 18S ribosomal RNA is used as a loading control for gene specific reaction. All lines display at least minor amplification and highest estimated expression when taking into account 18S control is in line ZmAAMT1.1-OE

138 CHAPTER 4 EFFECTS OF ENHANCED LIGHT ENVIRONMENTS ON POSTHARVEST VOLATILE PROFILES OF STRAWBERRY FESTIVAL Background The development of plants and specific tissues is the result of an interaction among intrinsic genetic potentials and external environmental factors. A particularly important environmental factor to plant development is light. In fact, a suit of photoreceptors exist to sense and transduce information concerning light quality. Characterization of pathways in Arabidopsis describe how signals are transduced to ultimately influence numerous aspects of growth and development (Chen et al., 2004). The susceptibility of strawberry fruit development and ripening to environmental differences has become evident in regard to temperature in chapter 2 of this dissertation as well in other studies (MacKenzie et al., 2011; Watson et al., 2002). The content of specific sugars and general SSC is sensitive to variations in temperature and can affect other metabolites including volatile compounds. Also, variation in light quantity and quality during development has been shown to influence volatile content of ripe strawberry (Kasperbauer et al., 2001; Watson et al., 2002). Previous work in North Carolina comparing the effects of red and black plastic mulch on strawberry fruit indicates significant increases in 12 of 19 aroma compounds, likely due to increased red and far-red light reflected to developing fruit (Kasperbauer et al., 2001). Red mulch work in Egypt using Strawberry Festival indicates increases in fruit weight and total yield compared to black reflective mulch (El-Yazied and Mady, 2012). However, mixed results are observed in regard to yield at multiple locations within Florida using cv. Camarosa (Locascio et al., 2005). The phenomena of volatile profiles changing in response to environmental conditions led to exploring the effect of narrow-bandwidth 138

139 postharvest light and in-field selective reflective mulch to alter volatile content in strawberry. Two pilot experiments were conducted to gain an understanding of the effects of light quality on strawberry volatile synthesis. The use of narrow-bandwidth light in a postharvest system to alter volatile profiles of fruits and flowers is explored in a published work with Postharvest Biology and Technology, Light Modulation of Volatile Organic Compounds from Petunia Flowers and Select Fruits (Colquhoun et al., 2013). Also, an application for patent (#61/794,406) has been submitted to the United States Patent and Trademark Office for technology associated with this work. Within this work light treatments are shown to specifically change the content of individual volatiles but not all volatiles in strawberry. These specific instances and literature support encouraged development of a field scale application to alter light environment through the use of plastic mulches with different reflective properties. Results Postharvest Exposure to Narrow-Bandwidth Light Alters Strawberry Volatile Content Volatile emissions from strawberry fruits contain a large array of compounds (Du et al., 2011a; Maarse, 1991). A focused subset of volatile compounds is presented here, some of which contribute to strawberry sensory perception. These include: 2-hexn-1-ol, (2E)- ( ); hexanoic acid ( ); butanoic acid, 1-methylethyl ester ( ); and linalool ( ). Mature strawberry fruit was harvested in the morning and chilled at 4 C overnight in dark conditions before being exposed to 8 hours of narrowbandwidth light of the blue, red, or far red spectrum (Figure 4-2) as well as controls of white fluorescent light and darkness. Volatile analysis immediately followed treatment to 139

140 identify light conditions capable of altering content of specific volatiles. All forms of light, including white control, decreased the content of 2-hexen-1-ol, (2E)- compared to dark (Figure 4-2A). Far-red light treatment selectively increased hexanoic acid (Figure 4-2B) compared to all other treatments. Blue light decreased butanoic acid, 1-methylethyl ester (Figure 4-2C) while negligibly affected in other treatments. Certain compounds, such as linalool, are not affected by light treatments (Figure 4-2D). The effect of light treatments on these selected volatile compounds in Fragaria x. ananassa cv. Strawberry Festival validates treatment specificity for altering volatile content. Red and Black Plastic Mulch Reflective light qualities from red and black mulch Light reflected from red and black plastic mulch was measured at 15 cm above raised beds, in which Strawberry Festival was growing. New red plastic mulch reflected 8.5% more of direct photosynthetic active radiation (PAR, nm) back up to plant canopy than black mulch (Table 4-1)(Figure 4-3A). The majority of this reflected radiation difference was that of red light ( nm), but also a 7% gain in far-red light ( nm) was observed to be reflected from red mulch (Figure 4-3B). Therefore the ratio of red to far-red light reflected from red mulch is nearly identical to direct sunlight. Black mulch exhibited a variable difference of red: far-red depending on age of mulch, but the reflected radiation was only 1-2% of direct sunlight (Table 4-1)(Figure 4-3C). Therefore, increased radiation was observed over red mulch, but an enhanced spectrum in regard to the red to far-red ratio was not observed. 140

141 Strawberry volatile profiles are not consistently different between red and black mulch treatments Fruit was harvested from three replicated plots of both black and red mulch treatments for simultaneous consumer panel and volatile analysis. Fruit was harvested in the morning and stored at 4 C overnight in the dark. Seventy-two volatile compounds were quantified in Strawberry Festival fruit from the same harvests as consumer panels (Table 4-3). Significant differences in volatile content for nine compounds was determined for January 18 th, 2013, while only three varied significantly on February 13 th, One of the volatiles that varied between treatments in January, hexanoic acid, was shown to be enhanced using postharvest far-red light treatments. However, the field effect was not reproducible, as none of the three volatiles significantly different between mulch treatments in February overlapped with those from January. Therefore, it can be concluded that red plastic mulch does not alter the volatile profile of commercially produced and stored Strawberry Festival fruit as hypothesized or suggested by literature. Consumers do not distinguish or prefer strawberry from red or black plastic mulch The morning following harvest, and simultaneous to volatile collections, approximately 100 panelists consumed and rated multiple berries from each treatment for overall liking, texture liking, sweetness intensity, sourness intensity, and strawberry flavor intensity. The experiment was conducted on January 18 th and February 13 th of No statistically significant differences were determined for any consumer rated measures, except for sourness intensity in February (Table 4-2). Mean sourness intensity of 13.7 and 15.7 for black and red was determined to be statistically significant using Tukey s honestly significant difference test. Despite this one significant difference 141

142 in sourness intensity it was found that red plastic mulch did not impart any difference to overall liking, sweetness intensity, or flavor intensity compared to black mulch as hypothesized. Discussion A variable response of volatile compounds to distinct light treatments is potentially a result of photoreceptor mediated regulation of expression, stability, or activity of enzymes required for volatile synthesis. Hexanoic acid was selectively increased by narrow-bandwidth far-red light compared to all other treatments. This is potentially due to a phytochrome mediated response. On the other hand, butanoic acid, 1-methlethyl ester is decreased by blue light. Therefore, perception of blue light by an appropriate photoreceptor, such as cryptochrome, may down regulate production of this volatile. Butanoic acid, 1-methylethyl ester has been previously reported to be associated with flavor (Hakala et al., 2002) as well as linalool (Jetti et al., 2007; Olbricht et al.; Ulrich et al., 1997). Both of which were found to have significant correlations to flavor intensity in the study conducted in chapter 2 of this dissertation. Knowing the amount of a flavor volatile can be preferentially altered presents the potential to test its effect in an otherwise unaltered whole fruit. Despite first-hand experience of altering volatile profiles of various fruits and flowers, including strawberry, using postharvest light treatments, a similar effect could not be reproducibly measured in a field scale application. Red plastic mulch does exhibit an enhanced reflective spectrum compared to black plastic mulch. The red to far-red ratio reflected from red mulch is similar to that of direct sunlight; therefore, the only difference is a negligible increase in PAR. No detectable or reproducible significant differences are observed in both consumer panels and volatile analysis. 142

143 The effect of colored mulch on volatile content is possibly dependent upon genetic background, as response differences to light quality and quantity are known in strawberry, particularly in flower induction (Hancock, 1999). Previously described reflective mulch induced volatile differences was documented in cultivar Chandler. Also, in that experiment significant gains in glucose, fructose, and sucrose were attributed to red mulch verse black mulch (Kasperbauer et al., 2001). However, in this work the cultivar Strawberry Festival was used. Previous work in Egypt using cultivar Strawberry Festival with red and black plastic mulch describes significant differences in numerous growth parameters including fruit weight and yield. Soluble solid content was not significantly affected by the mulch treatment in Egypt (El-Yazied and Mady, 2012). The previous lack of influence on soluble solid content potentially explains no consistent differences in volatile content measured in this work, as volatile content has been correlated to SSC. Differences in location and season are also potentially explanatory for lack of consistent volatile differences or consumer perception differences. Strawberry production in Florida occurs during the winter months when solar radiation reaching the soil surface has the greatest proportion of red and far red light. This is due to a lower angle of incidence and thus greater atmosphere the radiation must travel through. Egypt and Florida sit at the same latitudes, which may account for the lack of red mulch inducing greater volatile content. North Carolina production occurs in late spring to early summer when the angle of incidence of sunlight is lower, thus a decreased amount of red and far-red light reaches the soil surface. Red mulch reflects more red and far-red light compared to black plastic mulch. Therefore, in a solar environment with less red 143

144 and far-red light, such as May in North Carolina compared to January in Florida, the enhancements by red mulch may elicit a more pronounced effect. The manner in which fruits were assayed for volatile differences in the previous work in North Carolina (Kasperbauer et al., 2001) and this study is potentially explanatory of differences in effects observed. Kasperbauer harvested fruit in the late afternoon, following a full day of exposure to sunlight. Also, the fruit was frozen immediately for later volatile analysis. Conversely, this work in Florida followed an approach more relevant to commercial fresh strawberry. Fruit was harvested in the mornings and stored at 4ºC in the dark overnight. It is possible the cold and/or dark treatment negated any effects of the red mulch on volatile emission. If this is true, red mulch may present itself as a means to enhance flavor of frozen strawberry products, but the effects will not stand up to current postharvest practices of fresh strawberry. Materials and Methods Postharvest Narrow-Bandwidth Light Treatment Fragaria x ananassa cv. Strawberry Festival was grown according to current commercial practices for annual strawberry plasticulture in Florida (MacKenzie et al., 2011; Santos et al., 2012) beginning in the Fall of 2011 and continuing through the Winter of Fully-ripe fruit by commercial standards (Strand, 2008) was harvested at 9:00 in the morning. Fruit was transported from Citra, FL to Gainesville, FL and stored at 4 C in the dark overnight prior to light treatments and subsequent analysis of fresh strawberry fruit volatiles at 9:30 the following morning. Seven berries were selected based on uniformity of appearance per treatment, and were placed into clear plastic containers for each treatment. A dark treatment and four light treatments were tested: white, blue, red, and far-red (Figure 4-1). 144

145 Monochromatic light treatments were generated using a light emitting diode (LED) platform (Zhang et al., 2011b)}. In all cases, light treatments were 50 µmol m-2 s-1 in separate illumination chambers within an environmentally-controlled and actively ventilated area (22 C ± 1.5 C). The light treatments were generated using the Flora Lamp LED arrays (Light Emitting Computers, Victoria, B.C.). The control treatment (white light) was generated by cool white fluorescent bulbs, while the dark treatments were performed in an identical light-tight enclosure under the same ambient conditions. Fruit was treated for eight hours without photoperiod prior to volatile collection. Spectroradiometer readings were obtained with a StellarNet device and visualized on SpectraWiz software (Stellar Net, Tampa, FL). Red and Black Plastic Mulch Field Conditions Two treatments were replicated in three blocks consisting of approximately 150 plants per treatment replicate at the University of Florida and Institute of Food and Agricultural Sciences Plant Science Research and Education Unit in Citra, Florida. Planting of bare root propagules occurred on October 18 th, 2012 and transplant establishment is facilitated by ten days of overhead irrigation. Laying of Black and Red Selective Reflective Mulch (Garden Trends, Inc.) over existing black polyethylene occurred on November 5 th, Spectroradiometer readings were obtained with a StellarNet device and visualized on SpectraWiz software (Stellar Net, Tampa, FL). Reflected light quality was measured at 15 cm above plastic mulch. Harvests were conducted twice per week beginning December 18 th, 2012 through March 14 th, In which, fully-ripe fruit by commercial standards (Strand, 2008) was harvested at 9:00 in the morning, weather permitting. Count and mass (kg) of marketable and cull was recorded for each replicated treatment in the field. Fruit was 145

146 transported from Citra to Gainesville, FL and stored at 4 C in the dark overnight in the event of simultaneous analysis of fresh strawberry fruit volatiles and/or sensory analysis the following morning beginning at 9:30. Flavor Panel All consumer panels were approved by the University of Florida Institutional Review Board. One hundred panelists on January 18 th, 2013 and 88 panelists on February 13 th, 2013 evaluated strawberry fruit grown over red and black plastic mulch raised beds (Tieman et al., 2012). Fresh, fully-ripe strawberry fruit was removed from overnight 4 C dark storage and allowed to warm to room temperature prior to sensory analysis. Each panelist was given two to three whole strawberries for evaluation, depending on cultivar availability. Panelist bit each sample, chewed, and swallowed it. Ratings for overall liking and texture liking were scaled on hedonic glms in the context of all pleasure/displeasure experiences. Perceived intensity of sweetness, sourness, and strawberry flavor are scaled in context of all sensory experiences using sensory glms (Bartoshuk et al., 2004; Bartoshuk et al., 2003; Bartoshuk et al., 2005; Tieman et al., 2012). Scales were employed to mediate valid comparisons across subjects and sessions. Volatile Analysis At least 100 grams or seven berries of each sample were removed from 4 C dark overnight storage or postharvest narrow-bandwidth light treatment prior to volatile collection. A single biological replicate technically replicated three times was used per postharvest light treatment. For plastic mulch experiment volatiles were collected in technical triplicates per three biological replicates of each treatment to achieve precise quantitative measurement of volatile compounds emitted from strawberry fruit. Samples 146

147 were homogenized in a blender prior to splitting into three 15 gram technical replicates for immediate capturing of volatile emissions and the remainder frozen in N 2 (l) and stored at -80 C. A two hour collection in a dynamic headspace volatile collection system (Underwood et al., 2005) allowed for concentration of emitted volatiles on HaySep porous polymer adsorbent (Hayes Seperations Inc., Bandera, TX, USA). Elution from polymer was described by Schmelz et al. (Schmelz et al., 2003). Quantification of volatiles in an elution was performed on an Agilent 7890A Series gas chromatograph (GC) (carrier gas; He at 3.99 ml min -1 ; splitless injector, temperature 220 C, injection volume 2 µl) equipped with a DB-5 column ((5%-Phenyl)- methylpolysiloxane, 30 m length 250 µm i.d. 1 µm film thickness; Agilent Technologies, Santa Clara, CA, USA). Oven temperature was programmed from 40 C (0.5 min hold) at 5 C min -1 to 250 C (4 min hold). Signals were captured with a flame ionization detector (FID) at 280 C. Peaks from FID signal were integrated manually with Chemstation B software (Agilent Technologies, Santa Clara, CA). Volatile emissions (ng 1 gfw -1 h -1 ) were calculated based on individual peak area relative to sample elution standard peak area. GC-Mass Spectrometry (MS) analysis of elutions was performed on an Agilent 6890N GC in tandem with an Agilent 5975 MS (Agilent Technologies, Santa Clara, CA, USA) and retention times were compared with authentic standards (Sigma Aldrich, St Louis, MO, USA) for volatile identification (Schmelz et al., 2001). Chemical Abstract Services (CAS) registry numbers were used to query SciFinder substances database for associated chemical name and molecular formula presented in Table

148 Statistical Analysis One-way ANOVA determined statistically significant differences between volatiles of postharvest narrow-bandwidth light treatments, volatiles of plastic mulch treatments, and consumer ratings of plastic mulch treatments. Tukey s honestly significant difference test was conducted to separate means. All analyses were conducted in JMP

149 Table 4-1. Photosynthetically active, red, and far-red radiation reflected by selective reflective mulch. PAR ( nm) Red ( nm) Far-red ( nm) Red:Far-red Unexposed Exposed Unexposed Exposed Unexposed Exposed Unexposed Exposed Direct Sun µmol 1 m -2 s % Direct PAR Black Reflective µmol 1 m -2 s % Direct PAR Red Reflective µmol 1 m -2 s % Direct PAR Difference µmol 1 m -2 s (red-black) % Direct PAR Note: Radiation measured from unexposed mulch and 4 month exposed mulch on March 14th, Relative value is average of three replicates divided by direct PAR at time of measurement. Absolute value is product of relative and general direct PAR of 2324 µmol 1 m -2 s

150 Table 4-2. Consumer panels do not perceive differences between red and black plastic mulch grown strawberries. n Mean Black Red Black verse Red Ideal Standard Deviation Mean Standard Deviation 1/18/2013 ANOVA p-value Tukey's HSD (α=0.05) Overall Liking a, a Texture Liking a, a Mean Standard Deviation Sweetness Intensity a, a Sourness Intensity a, a Strawberry Flavor Intensity a, a /13/2013 Overall Liking a, a Texture Liking a, a Sweetness Intensity a, a Sourness Intensity b, a Strawberry Flavor Intensity a, a Note: Panels were conducted at two separate points of the season in which consumers rated overall liking, texture liking, sweetness intensity, sourness intensity, and strawberry flavor intensity of strawberries grown over red or black plastic mulch. All attributes were statistically indistinguishable across treatments on both dates, except for sourness intensity being greater in the red treatment on February 13, One-way ANOVA analysis conducted in JMP

151 Table 4-3. Volatile analysis does not detect consistent differences between red and black plastic mulch grown strawberries. 1/18/2013 2/13/2013 Black Red Black Red Volatile CAS # n Mean Std Error Mean Std Error ANOVA p-value Mean Std Error Mean Std Error ANOVA p-value

152 Table 4-3. Continued Volatile CAS # n Mean 1/18/2013 2/13/2013 Black Red Black Red Std Error Mean Std Error ANOVA p-value Mean Std Error Mean Std Error ANOVA p-value TOTAL Note: Volatiles were collected from fresh F. x ananassa cv. Strawberry Festival simultaneously with consumer panels. One-way ANOVA determined statistically significant differences of nine volatiles between treatments on January 18 th, 2013 and three volatiles between treatments on February 13 th, Significant values (α=0.05) are in bold. However, no volatile compounds showed consistent differences on both collections. One-way ANOVA analysis conducted in JMP

153 Figure 4-1. Spectroradiometer readings of the light qualities used in postharvest treatments. All treatments represent the waveform generated at a fluence rate of 50 µmol m -2 s -1. B = blue, R = red, FR = far-red, HBW = half-bandwidth. 153

154 Figure 4-2. Effect of light treatments on selected volatile compounds in Fragaria x. ananassa cv. Strawberry Festival. Light decreases the content of 2-hexen-1- ol, (2E)- ( ) (A) compared to dark. Far-red light treatment selectively increases hexanoic acid ( ) (B) compared to all other treatments. Blue light decreases butanoic acid, 1-methylethyl ester ( ) (C) while negligibly affecting other treatments. Certain compounds, like linalool ( ) are not affected by light treatments (D). Volatile collections were conducted multiple times with similar results observed. Volatile content is the average of three technical replicates. Error bars represent one standard error. Data analysis conducted in JMP

155 A B C D 155