Approaches to Mapping Loci That Influence Flavor Quality in

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Approaches to Mapping Loci That Influence Flavor Quality in Raspberries Alistair Paterson, John R. Piggott, and Jianping Jiang Food Science Laboratories, Department of Bioscience and Biotechnology, University of Strathclyde, 131 Albion Street, Glasgow G1 1SD, Scotland

Flavour quality is important in the raspberry and related soft fruits. Using multivariate statistics, it has been possible to resolve varietal and seasonal differences and processing effects in raspberry flavour into variations in fruit composition. Such approaches transform varietal flavour variation into quantitive traits that can be mapped genetically to chromosomal loci (qtls). Physical mapping of plant genomes has been facilitated by new polymerase chain reaction technologies that use oligonucleotide primers of arbitrary sequence. With such techniques, the presence of physical genetic markers in parental and progeny strains can be screened using rapid automated protocols. Such approaches can readily be used in diploid raspberries and related berry crops with simple genomes. In varieties with more complicated cytogenetics, genetic mapping of both phenotypic and physical markers is more complex.

Molecular biology is a reductionist science that has dominated modern genetics. In the past decade, molecular genetics has reached maturity and strategies developed to explore how molecules interact can now be employed to elucidate the genetic basis of variation in plants. Quantitive variations in certain compositional characters infruitare perceived by the human observer in an integrative manner as taste and aroma. The genetic coding of such variation can be localised on plant chromosomes to quantitive trait loci (qtl) that have major influences upon fruit character, notably flavour and composition (7). These loci must also, in principle, be present in animal genomes, although, in domesticated animals, choice of feed, growth conditions, and slaughter conditions are likely to have the dominant influence. A prerequisite for using such strategies to analyze the regulation offlavourin fruits and vegetables, is an understanding of which variations in a complex mixture of organic compounds are important to the human observer. Use of multivariate statistics allows the analyst to identify single or multiple compounds with a strong influence on varietal character, or producing flavour changes following processing, against a background of others that contribute to overall flavour, but are not central to varietal character (2). Mapping complex genomes has been invigorated by the development of rapid molecular genetic techniques. The presence of individual plant genes can now be 0097-6156/93/0528-0109$06.00/0 © 1993 American Chemical Society

Spanier et al.; Food Flavor and Safety ACS Symposium Series; American Chemical Society: Washington, DC, 1993.

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determined, and subsequent inheritance followed, using a physical "tag" in the form of a restriction fragment length polymorphisms (3). Developments in polymerase chain reaction (PCR) technology have also facilitated such approaches: using short DNA primers, of arbitrary sequence, populations of DNA fragments similar to RFLPs can be generated in rapid and reproducible protocols (4, 5). The Raspberry and Related Hybrid Fruits Raspberry species were widely distributed through Northern Europe and the Americas, Asia, and East and Southern Africa, and belong to the subgenus Idaeobatus of the genus Rubus. They are closely related to, but differentiated from, the blackberries (Eubatus), cloudberries (Chamaemorus), and various arctic berries (Cylactis) (6). Each produces distinctive fruits, appreciated by consumers, and a tremendous range of hybrid cultivars has been generated for evaluation and growth by horticulturalists. Rubus genomes are relatively simple and contain seven chromosomes present in ploidies (n) ranging from two to twelve (6). Crossing between members of the genus has proven relatively straightforward and a number of progeny have achieved success, notably the loganberry. This was thought to arise from an accidental crossing between the European raspberry "Red Antwerp" (R. idaeus) and the Western American blackberry "Auginbaugh" (R. ursinus), discovered in the garden of a Judge Logan, at Santa Cruz, California in 1881. Crane and Thomas (7, 8) showed that this fruit was a hexaploid (6n), with 42 chromosomes, subsequently shown to be an allopolyploid with two different pairs of genomes (4ri) from R. ursinus and a pair of identical genomes (2n) from R. idaeus. Other important North American crosses include the Young- and Boysenberries (7n) (9) and in Scotland crossings between the Oregon blackberry "Aurora" (8n) and tetraploid raspberries (4n) have generated the important Tay- and Tummelberries (hexaploid; 6n) (6). In Finland, the arctic raspberry (R. arcticus) has been crossed into R. idaeus and the diploid "Heija" has enabled commercial exploitation of the special aroma character of this fruit (10). Analyses of Raspberry Flavour To achieve widespread success, the raspberry and related fruits have required major breeding programmes, in Scotland carried out at the Scottish Crops Research Institute at Invergowrie. Major research targets in recent years have included developing berries suitable for machine-harvesting and freezing. Flavour has, to an extent, been a secondary selection character in breeding being largely related to acceptability with expert assessments of quality based upon rejection of defects. The "impact compound' that provides the primary stimulus forfruitcharacter in the raspberry is the ketone, l-(p-hydroxphenyl)-3-butanone (77). Other important flavour contributors are os-3-hexen-l-ol, α - and β - ionones, and α - irone (72, 13). In R. arcticus the characteristic aroma is considered to be from mesifurane (70). It has, however, been reported that steam distillates of raspberries can be assessed for aroma content using a colorimetric procedure and 80% of aroma is accounted for by geraniol, nerol, linalool, α - terpineol and the ionones (13). Despite this detailed knowledge of raspberry aroma compounds, major flavour problems still emerge in commercial production. For many years the Scottish crop was dominated by Glen Clova, released in the early 1970s, which produced a good yield, and had good disease resistance, but gave fruit subject to deleterious flavour and colour changes associated with chilled storage and thermal processing. Such flavour faults can prove a major handicap in the current retail market. Moreover, the aroma of modern raspberries is notably sensitive to heat, andfreezingand thawing, yet to satisfy consumer demand for premium fruit, and successfully compete against reduced labour costs in Eastern European fruit, character must be retained.


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Matching of Compositional and Sensory Data on Flavour Determining compounds responsible for varietal character and flavour changes is thus of more than passing interest. Use of multivariate statistics has made it possible to discern relationships between instrumental quantifications of individual fruit flavour compounds and sensory data, obtained from panels of experienced observers. A decade ago such strategies were the realm of the specialist, but with the appearance of suitable statistical packages for the microcomputer, such techniques are more approachable. Principal component analysis (PCA) (14), partial least square regression (PLS) (15) and redundancy analysis (RA) (16) have proven of particular value in allowing the experimenter to determine which of many compounds, have a major influence on an individual varietal character or flavour changes from processing. Principal component analysis calculates linear combinations of variables that explain the maximum possible proportion of variance in data and generates orthogonal latent variables describing relationships among variables and between objects. This yields relationships among groups of variables in data sets and shows relationships between samples (14). Partial least square regression, commercially available in an accessible form, searches for a small number of orthogonal latent factors that describe the interrelationships between two blocks of variables. Factors that are extractedfromthe regressor matrix (X) are relevant to prediction of the regressand (Y) and factors in one matrix not relevant to the other are eliminated. Redundancy analysis, not previously extensively used in food science, projects Y (sensory) variables on to X (compositional) variables, and performs principal component analyses on the totality of y-variables. Elucidation of Important Features in Raspberry Taste Flavour is of increasing importance when food is sufficiently abundant for consumers to exert choice. Sensory analysis, using trained laboratory panels, has been developed to profile fruit flavours, and describe relationships between products with a marked degree of confidence but is time-consuming, requiring dedicated observers who appreciate the nuances of individual character. Many, if not most, consumers, however, do not discriminate betweenfruitflavours. In dried orange juices, sweetness has been shown to be the major factor determining preference; in canned juices, sourness; and infrozenjuices the interaction between sweetness and sourness is the significant factor (17). Three major sugars (% w/v) contribute to sweet taste in the raspberry:fructose(17 - 40 ), glucose (14.5 - 33) and sucrose (0 - 10.8) giving total contents of 31.5 - 73.0 g I" . Raspberry juices are, unfortunately, remarkably sour in taste, through the presence of 10.5 - 26.7 g 1 citric and malic acids. In a recent study of varietal and seasonal influences on raspberry taste, in this laboratory (18), it was concluded that 26 growth trial cultivars fell into three classes with respect to acidity: low (10.5 13.5); intermediate (15 - 30) and high (20.1 - 26.7 g 1 '). Principal component analysis of 14 compositional variables and 6 sensoiy attributes gave indicated the relationships between compositional and sensory variables (Figure la) and cultivars studied (Figure lb) which allowed conclusions to be drawn with respect to flavour characters, their compositional origin, and influence on fruits. Although the three statistical techniques PCA, PLS, and RA gave different sets of information, it was clear that sweetness and sourness and related compositional factors were of central importance in flavour. Contents of total sugars, sweet taste, sugar/acid ratio gave positive loadings and high negative loadings were obtained for sour taste, citric and total acid content, indicating malic acid had little influence on flavour as concluded previously (79). Utilizing PLS and RA, 55% and 77%, respectively, of total variance of sensory variables was explained by compositional variables. The correlation between such results and those of earlier studies give confidence in this methodology. 1

1


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FOOD FLAVOR A N D SAFETY

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o

a

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Figure 1. Analysis of the relationships between (a) compositional and sensory variables and (b) cultivars in terms of these variables, (a) Loadings of the 6 sensory and 14 compositional variables (Table I) onfirst(horizontal) and second (vertical) principal components, (b) Sample scores of the first (horizontal) and second (vertical) principal components of raspberry cultivars (Table II).


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Table I. Compositional and sensory variables in principal component analysis of flavour in raspberry cultivars Composition

Symbol

Composition

Symbol

Fructose Glucose Sucrose Total sugars

Fru Glu Sue Tos

Sugar/acid ratio

S/A

Malic acid Citric acid Total acids

Mai Cit Toa

Cyanidin-3-sophoroside Cyanidin-3-glucosylrutinoside Cyanidin-3-glucoside Cyanidin-3-rutinoside Pelargonidin-3-sophoroside Total pigments

Csop Cglr Cglu Crut Psop Top

Sensory attributes

Sweet taste Sour taste Bitter taste

Swt Sot Bit

Table II. Raspberry cultivars in study Named varieties Comox GlenClova Glen Garry Glen Lyon GlenMoy GlenProsen Mailing Joy Mailing Jewel Mailing Landmark Mailing Leo

Symbol Co GC GG GL GM GP Jo MJ La Le

Cultivars M30 14/106 16A10 16C6 19B11 31/7 32RG3 54/39 55/15 55/46 55/47 55/48 789C1

Symbol Syn MS 14 Al C6 Bl 31 RG 34 15 46 47 48 Cl


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FOOD FLAVOR AND SAFETY

Important Features in Raspberry Flavour Compositional analyses of flavour compounds in fresh and processed fruits are often of limited value because it is clear that compounds with very low aroma thresholds can have dominant effects upon fruit flavour. Moreover after processing, the compounds with the primary influence on flavour may change. Quantification of individual aroma compounds is also problematic requiring high resolution gas chromatographs linked to ion-trap or related detectors (HRGC/MS) although flame-ionisation detection is often more convenient. Nearly 200 aroma compounds have been identified in fresh raspberries, many in trace quantities (20, 21), although Jiang (18) quantified only 62 compounds. Principal component analysis of volatile compound data showed that the first component was dominated by nine compounds, and the second by eight. Incorporating sensory data showed that grassy, correlated withris-3-hexen-l-ol,had a high negative loading and fruity (citric) was associated with three compounds. In contrast, Williams (22) reported that apple flavour notes could be related to many compounds. Redundancy analysis was able to explain 47% of total variance in flavour in relation to the 62 aroma compounds in the first two components; PLS explained only 36%. Neither method, however, correlated either raspberry ketone or linalool with important aroma notes, suggesting concentrations of these impact compounds are not important in determining varietal character. Definition of taste and aroma character in sensory terms, and assigning this to precise variation in fruit composition, allows experiments with sensory panels to be limited to defining compositional components correlated with character changes perceived important by observers. Subsequent experimentation can then be effected by automated chromatography. Quantitive Trait Loci Studies of raspberry flavour have centered on understanding how quantitive variation in individual volatile and non-volatile compounds influence perceived quality. Such variation can be seasonal, environmental, or of genetic origin; both seasonal and varietal influences are important. Interaction between sources of variation is also observed. Seasonal effects in raspberry aroma volatiles appears to be primarily associated with variation in ds-3-hexenol content (grassy note), whereas genetic variation is stable. In strawberries, genotype determines ratios of individual sugars and organic acids in fruits (23). A number of aspects of genetic variation in tomato flavour have been shown by Tanksley and his colleagues (/) to originate from regulation of levels of phenotype expression by quantitive trait loci. These can be mapped in the diploid genome by physical methods such as restriction fragment length polymorphism (RFLP) analysis. This has been carried out using random genomic DNA clones, isolated from the organism being studied, in hybridizations utilizing radiolabelled DNA (24). While inexpensive for a small number of samples, such strategies are tedious when monitoring the progeny of crosses is required. Thus attention has turned to use of new approaches, made feasible by development of polymerase chain reaction (PCR) technology, which does not require radioisotopes, and can be routinely performed by affordable automated equipment to yield data that can be digitized. Polymerase chain reactions are initiated by binding oligonucleotide primers to opposing strands of the DNA and synthesizing the intervening sequence using a thermostable DNA polymerase. This effects an amplification of a predefined sequence, generating significant quantities of duplex DNA in experiments lasting a few hours. Random primers (typically decamers), not corresponding to any known sequence, have also been utilized to generate physical genetic maps, and alternate mixtures of primers generates complementary data. Moreover as organisms diverge, the similarities


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between PCR product patterns is reduced, indicating changes in genomic sequence. Analyses using Random Amplified Polymorphic D N A (RAPD markers) (4) have been of value in genetic fingerprinting in cultivated sub-populations of cocoa (Theobroma), generating certain fragments that are shared between and others that differentiate varieties (25). Physical Mapping of Quantitive Trait L o c i in Raspberries Mapping qtte in raspberries is an exciting concept. It is clear that compositional factors determining fruit character can be identified, utilizing sensory analysis and multivariate statistics. It is also clear that the cytogenetics of the Rubus genus may be varied and complex, as in many fruit. The strategy of Tanksley and his coworkers (7) in mapping qtte in the tomato was dependent upon backcrossing progeny obtained from a cross between a modern cultivar and a wild-type tomato, and is dependent upon progeny being diploid. In the raspberry, crosses between diploid cultivars are possible and a wide range of genes have already been identified (6). This fruit may thus prove a valuable model system in developing research in an area that has proven recalcitrant. Acknowledgments The authors are very grateful to the Director, and staff of the Scottish Crops Research Institute for provision of fruit and helpful discussions, and the University of Strathclyde Research and Development Fund, Agricultural and Food Research Council and Chivas Bros (Keith) Ltd for support. Literature Cited 1 Paterson, A.H.; Lander, E.S.; Hewitt, J.D.; Peterson, S.; Lincoln, S.E.; Tanksley, S.D. Nature 1988, 335, 721-726. 2 Piggott, J.R. J. Sensory Stud. 1990, 4, 261-272. 3 Prince, J.D.; Tanksley, S.D. Proc. Roy. Soc. Edin. 1992, 99B, 23-29. 4 Williams, J.G.K.; Kubelik, A.R.; Livak, K.L.; Rafalski, J.A.; Tingey, S.V. Nucleic Acids Research 1991, 18, 6531-6535. 5 Welsh, J.; McClelland, M. Nucleic Acids Research 1991, 18, 7213-7218. 6 Jennings, D.L. Raspberries and Blackberries: Their Breeding Diseases and Growth; Academic Press: New York, 1988. 7 Crane, M.B.J. Genet. 1940, 40, 109-118. 8 Thomas, P.T.J. Genet. 1940, 40, 119-128. 9 Thompson, M.M. Amer. J. Botany 1961, 48, 667-673. 10 Hiirsalmi, H.; Sako, J. Acta Horticult. 1976, 60, 151-157. 11 Nursten, H.E. In The Biochemistry of Fruits and their Products; Hulme, A.C., Ed.; Academic Press: London, 1970;p253. 12 Kallio, H.J. Food. Sci. 1976, 41, 563-566. 13 Latrasse, Α.; Lantin, B.; Mussillon, P.; Sanis, J.L. Lebensmittel Wissensch. Technol. 1982, 15, 19-21. 14 Piggott, J.R.; Sharman, K. In Statistical Procedures in Food Research; Piggott, J.R., Ed.; Elsevier Applied Science: London, 1986; pp 181-232. 15 Martens, M.; van der Berg, E. In Progress in Flavour Research 1984; Adda, J., Ed.; Elsevier Science Publishers BV: Amsterdam, 1985; pp 131-148. 16 Liu, Y. Multivariate Methods for Relating Different Sets of Variables with Applications in Food Research. PhD Thesis, University of Bristol, UK, 1990. 17 Ennis, D.M.; Keeping, L.; Chin-Ting, J.; Ross, N.J. Food Sci. 1979, 44, 1011-1016. 18 Jiang, J. Variation in Raspberry Composition and Sensory Qualities as Influenced by Variety, Season and Processing. PhD Thesis, University of Strathclyde, UK, 1991.


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19 Green, A. In The Biochemistry of Fruits and their Products; Hulme, A.C., Ed.; Academic Press: London, 1971. 20 Nursten, H.E.; Williams, A.A. Chem. Indust. 1967, 12, 486-497. 21 de Vincenzi, M.; Badellino, E.; Di Folco, S.; Dracos, Α.; Magliola, M.; Stacchini, Α.; Stachinin, P.; Silano, V. Food Additives and Contaminants 1989, 6, 235-267. 22 Williams, A.A. In Geruch- und Geshmackstoffe; Drawert, F., Ed.; Verlag Hans Carl: Nurnberg, 1975; pp 141-151. 23 Shaw, D.V.J. Amer. Soc. Hort. Sci. 1988, 113, 770-774. 24 Bonierbale, M.W.; Plaisted, R.L.; Tanksley S.D. Genet. 1988, 120, 1095-1103. 25 Wilde, J.; Waugh, R.; Powell, W. Theor. Appl. Genet. 1992, 83, 871-877. Received December 30, 1992


Approaches to Mapping Loci That Influence Flavor Quality in

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