HORTSCIENCE 28(7):735–737. 1993. crop that undergoes a marked reduction of vigor and productivity with inbreeding (Huang et al., 1992). The data in this study were Calorimetric Analysis of Gerbera obtained from 437 of generation 14 of the Davis gerbera population. The population was established as a variable gene pool in 1970 by crossing plants from many mixed seed lots Kenneth R. Tourjee1, James Harding2, and Thomas G. Byrne3 (Byrne et al., 1977). Successive generations Environmental Horticulture Department, University of California, Davis, have been grown in the same glasshouse, with »10% of the progeny of each generation (i.e., CA 95616 »40 plants) retained as parents of the next Additional index words. , Composite, reflectance spectrophotometry, generation. Each generation, parents were ran- domly crossed in a factorial mating design (Yu hue, value, chroma, CIELAB et al., 1991). Selection has been applied to Abstract. Ligule color of a Gerbera jamesonii H. Bolus ex Hooker population was analyzed various traits, such as yield and flower with a reflectance spectrophotometer having a spectral capability of 400 to 700 nm and a dry weight (Harding et al., 1991). However, cv <3% for the variables hue, chroma, and value. The observations for each variable had direct selection has not been practiced on hue, a continuous distribution; these broad distributions are possibly bimodal. The repeatabil- chroma, or value. ity of hue, chroma, and value, determined as the correlation between measurements made Individual plants were grown in containers on plants in December and those made on the same plants the following April, are 0.83, of a 1 sand : 1 peat : 1 redwood sawdust (by 0.82, and 0.86, respectively. The phenotypic correlations between value and chroma, value volume) mixture amended with dolomite to and hue, and chroma and hue are -0.35, 0.73, and 0.11, respectively. Some possible »6.5 pH. The plants were irrigated with a biochemical implications concerning the interaction of anthocyanin and carotenoid complete inorganic nutrient solution that in- pigments are discussed. Reflectance spectroscopy and Commission International de cluded all macro- and micronutrients (e.g., + l’Eclairage 1976 (L* a* b*) color space notation provide an objective and precise method and K at 10.64, 182.79, for incorporating color into a recurrent selection program. 42.19, and 219.25 ppm, respectively). Air was maintained at 22 to 25C days and 16 to 19C The study of flower color has played a such as uncontrolled incident light and percep- nights. Seeds were planted singly in 5.0-ml pivotal role in understanding modes of inher- tual differences among observers, reduce the plugs in 135-count plug trays on 6 June 1989, itance throughout the history of genetics ability to discern small differences between transplanted to 1.1-liter pots on 6 July, and (Lawrence, 1950; Lawrence and Price. 1940 classes. Assigning flower color in gerbera to again to 2.0-liter pots on 14 Aug. Final spacing Onslow, 1925). These and more recent inves- discrete classes to determine its mode of inher- was 10.76 plants/m2. Individual plants were tigations (Ennos and Clegg, 1983; Epperson itance has not resulted in Mendelian segrega- evaluated for hue, chroma, and value at the and Clegg, 1988; Ladd et al., 1984; Negi and tion ratios even when chromatographic analy- cut-flower harvest stage (Drennan et al., 1986). Raghaven, 1990) defined flower color as a sis was used to identify pigments (Vandoni, Each was measured in Dec. 1989 and qualitative trait indicative of the presence of 1977). again in Apr. 1990. pigments in a biochemical pathway of a three- Reflectance spectroscopy provides an op- or four-gene system involving dominance and portunity to study gerbera flower color as a Flower color assay continuous variable. This technique analyzes epistasis. However, Nieuwhof et al. (1988) This study’s data were obtained in terms of the spectrum of visible light reflected from a described flower pigmentation in as a hue, chroma, and value according to CIELAB quantitative trait that could be correlated with surface irradiated with a defined incident light, uniform color space (McLaren, 1976). Hue observed color classes. yielding an objective and precise method of and chroma measure the selective absorption Visual matching to a reference standard is color measurement. It has been used success- of visible light. Chroma describes the degree used frequently to specify color. When a match fully in such diverse applications as matching to which selective absorption occurs (i.e., color has been obtained, the sample color is as- soil samples (Fernandez and Schultze, 1987), intensity), and hue describes which wave- measuring the skin color of apples (Malus signed to a class according to one of the many lengths are being absorbed (e.g., reds, yel- current color systems. The Munsell color sys- domestica Borkh.) (Francis, 1952), and as- lows, greens, and blues). Value measures an sessing papaya (Carica papaya L.) fruit matu- tem, for example, defines a three-dimensional achromatic property-the reflectance of total color space based on the attributes hue, chroma, rity (Hayes et al., 1988). Most color data in the food science literature has been reported in the visible light from a surface (i.e., lightness). A and value. Specifying these three attributes thorough treatment of color theory can be results in a color sample that is uniquely lo- Hunter L, a, b color system (Francis, 1980). In vivo reflectance spectroscopy and the Com- found in, for example, Hunter and Harold cated in color space (Agoston, 1979). (1987). mission International de l’Eclairage Unfortunately, visual matching has not Measurements were obtained using the provided the precision necessary to describe (CIELAB) color system are being used to Agtron (Reno, Nev.) Colormet, a portable adequately ligule color variation in Gerbera quantify the color of peaches [Prunus persica reflectance spectrophotometer with a spectral jamesonii (Composite). Interfering factors, (L.) Batsch] (T. Gradziel, personal communi- capability of 400 to 700 nm in 10-nm intervals, cation) and strawberries (Fragaria ×ananassa a 30-mm-diameter viewing area, and output in Duch.) (Shaw, 1991). Received for publication 15 June 1992. Accepted The purpose of this paper is to illustrate the CIELAB notation. CIE illuminant D65 with a 10° observer setting was used throughout the for publication 21 Dec. 1992. Research conducted at use of a portable spectrophotometer to de- Environmental Horticulture Dept., Univ. of Califor- study. Individual measurements were made nia, Davis. Use of trade names does not imply scribe the phenotypic distribution of color attributes—hue, chroma, and value—in the nondestructively. Gerbera flowers were as- endorsement of the products named nor criticism of sayed with the spectrophotometer’s viewing Univ. of California, Davis, gerbera population similar ones not named. The cost of publishing this area aligned on the radial axis of the flower paper was defrayed in part by the payment of page (Harding et al., 1985); provide evidence that flower color can be treated as a quantitative against the ligules of the ray florets. charges. Under postal regulations, this paper there- Before the study, two aspects of assay fore must be hereby marked advertisement solely to trait in this population; and provide data con- validation were examined. First, the cv (SD/ indicate this fact. cerning calorimetric precision. 1Graduate Student. mean) for hue, chroma, and value were estimat- 2Professor. Davis gerbera population ed based on 10 measurements of an individual 3Specialist, Emeritus, Agricultural Experiment Sta- flower. Second, repeatability was estimated tion. Gerbera is a heterozygous cross-pollinated from measurements made on plants in Decem-

HORTSCIENCE, VOL. 28(7), JULY 1993 735 ber and again in April. Repeatabilities for hue, the population tend to be lighter (reflect more segregation provided by the complexity of the chroma, and value are defined as the correla- of the total incident radiation) than reds and flavonoid pathway compared to the carote- tions between these seasonal replicates. Sta- are less abundant. Consequently, it is expected noid pathway (Forkmann, 1991). The contin- tistical analysis was performed using the that the dark or deep values will occur more uous change in the variability for value over CHART and CORR procedures of PC-SAS frequently than the bright or pale values. The the full range of hue may then result from the (SAS, 1985). two-dimensional distributions of color com- relative production of anthocyanins and caro- The cvs for hue, chroma, and value were ponents displayed in Fig. 2 demonstrate the tenoids in common phenotypes. The greater <3% therefore, the instrument introduces little pattern of covariability observed in this popu- value variation in the red hues may result from error into the overall assay. lation. A strong relationship exists between anthocyanin synthesis regulation. For example, The repeatabilities for hue, chroma, and value and hue (r = 0.73) (Fig. 2A), but not in petunia (Petunia hybrida Vilm.), a gene value were 0.83, 0.82, and 0.86, respectively. between chroma and hue (r = 0.11) (Fig. 2b). controls the rate of anthocyanin synthesis, They indicate the constancy of flower color The relationship between chroma and value (r producing either light or dark red flowers over a growing season as well as the heteroge- = –0.35) becomes more apparent when the red (Gerats et al., 1982). When anthocyanin syn- neity for color of particular genotypes. hues (0°–50°) (Fig. 2C) are separated from the thesis is limited, the accumulating precursors yellow hues (50°-100°) (Fig. 2D). or metabolizes (such as dihydroflavonols) are Phenotypic distributions of color An important feature of the data in Fig. 2A colorless, resulting in an increase in the flower components is the substantial variation in value (L*) among color value. Also, for the red hues, value is the red hues. However, the yellow hues have negatively correlated with chroma (Fig. 2C), The population’s color distribution is de- only limited variation for value. This may which is expected if the value component of scribed in terms of CIELAB notation (Fig. 1). reflect the increased opportunity for genetic color were being determined by the rate of Hue, value, and chroma all vary continuously throughout their ranges. They are broadly distributed and may be skewed or bimodal. In the Davis population, hue is art angular measure that ranges from 0 to 100° (viz., purplish red to yellow). The bimodal distri- bution of hue in Fig. 1A may be associated with the presence of two pigment systems: the red hues from anthocyanins and the yellow hues from carotenoids (Asen, 1984; Forkmann, 1991). The red hues represent more than three- fourths of the population, and almost one-third is included within an 8° interval centered at 32°. The yellow hues makeup less than one- fourth of the population. Chroma is a measure of an object’s color intensity. The modifiers bright, strong, or deep indicate colors with high chroma. Pale, weak, or dark colors have low chroma. The distri- bution of chroma in Fig. 1B indicates a high proportion of the plants in this population have intensely colored flowers. This pattern sup- ports the observation that vivid colors are generally considered a characteristic of ger- bera. Value measures the overall lightness of an object’s color. Achromatic colors have neither hue nor chroma; they range through a series of grays from white to black as the proportion of total incident light reflected by a surface is decreased. Chromatic colors corresponding to the same scale of grays range from pale or bright to deep or dark. Interpretation of Fig. 1C suggests a bimodal distribution that may result from the dual action of the anthocyanin and carotenoid pigment systems. The yellows in

736 HORTSCIENCE, VOL. 28(7), JULY 1993 anthocyanin synthesis. Further, flavonols (an Asen, S. 1976. Known factors responsible for infi- nents of variance in gerbera. Theoretical & Ap- alternate pathway of the anthocyanins) often nite flower color variations. Acta Hort. 63:217– plied Genet. 82:756-760. act as copigments with anthocyanins, and to- 223. Hayes, C.F., H.T.G. Chingon, and H.G.C. Young. gether they make anthocyanins appear bluer Asen, S. 1984. High pressure liquid chromatographic 1988. Hunter b color measurements of papaya analysis of flavonoid chemical markers in using a two-filter system. HortScience 23:399. (Asen et al., 1972). The greatest variability for from gerbera flowers as an adjunct for value in Fig. 2A is toward the blue end of the Huang, H., J. Harding, and T. Byrne. 1992. The and germplasm identification. Photochemistry effects of inbreeding on flower yield in gerbera. red range. 23:2523-2526. HortScience 27:586. (Abstr.) A different situation may describe the value Asen, S., R. Stewart, and K. Norris. 1972. Hunter, R.S. and R.W. Harold. 1987. The measure- variation in the yellow hues. They generally Copigmentation of anthocyanins in plant tissues ment of appearance. 2nd ed. Wiley, New York. result from the carotenoid pathway (Griesbach, and its effects on colour. Photochemistry Ladd, D.L., M.L. Albrecht, and C.D. Clayberg. 1984a). The difference in value between yel- 11:1139–1144. 1984. Genetics of flower color in spider flower. low pigments and their precursors or alternate Byrne, T.G., J. Harding, and R.L. Nelson. 1977. J. Amer. Soc. Hort. Sci. 109:759–761. metabolizes may be small, resulting in only Greenhouse gerberas. Calif. Agr. 31(9):21–22. Lawrence, W.J.C. 1950. Genetic control of bio- Drennan, D., J. Harding, and T. Byrne. 1986. Heri- chemical synthesis as exemplified by plant ge- small fluctuations of the flower’s value when tability of inflorescence and floret traits in ger- pigment synthesis rates are varied. This fact is netics—Flower colours, p. 3–9. In: R.T. Wil- bera. Euphytica 35:319-330. liams (ed.). Biochemical aspects of genetics. consistent with the data in Fig. 2D; increasing Ennos, R.A. and M.T. Clegg. 1983. Flower color chroma (i.e., producing more pigment) has no Biochem. Soc. Symp. no. 4, Westminster Medi- variation in the morning glory, Ipomoea cal School Hospital, London, 12 Feb. 1949. effect on value. purpurea. J. Hered. 74:247–250. Cambridge Univ. Press, Cambridge, England. Asen (1976) reviewed the effects of pH, Epperson, B.K. and M.T. Clegg. 1988. Genetics of Lawrence, W.J.C. and J.R. Price. 1940. Genetics anthocyanin concentration, copigment : an- flower color polymorphism in the common morn- ing glory (Ipomoea purpurea). J. Hered. 79:64- and chemistry of flower colour variation. Biol. thocyanin molar ratio, light intensity, tem- Rev. Cambridge Philosophical Soc. 15:35–58. perature, and metals as factors contributing to 68. Fernandez, R.N. and D.G. Schultze. 1987. Calcula- McLaren, K. 1976. The development of the CIE variation in flower color. Griesbach (1984b) tion of soil color from reflectance spectra. Amer. 1976 (L* a* b*) uniform colour space and colour- discussed the creation of novel flower colors J. Soil Sci. 51:1277–1282. difference formula. J. Soc. Dyers & Colourists by combining carotenoids and anthocyanins. Forkmann, G. 1991. Flavonoids as flower pigments: 92:338-341. The plethora of factors involved in determin- The formation of the natural spectrum and its McLaren, K. and B. Rigg. 1976. The SDC recom- ing flower color readily explains why ligule extension by genetic engineering. Plant Breed- mended colour-difference formula Change to color is continuously distributed in the Davis ing 106:1–26. CIELAB. J. Soc. Dyers & Colorists 92:337– population. Francis, F.J. 1952. A method of measuring the skin 338. color of apples. Proc. Amer. Soc. Hort. Sci. Negi, S.S. and S.P.S. Raghaven. 1990. Genetics of Breeding novel flower colors requires that flower color in China aster (Callistepus chinensis the trait be defined so that objective and pre- 81:408–414. Francis, F.J. 1980. Color quality of horticultural (L. Nees)). Euphytica 48(2): 117-122. cise measurements can be obtained. Reflect- crops. HortScience 15:14-15. Nieuwhof, M., J.P. van Eijk, P. Keijzer, and W. ance spectroscopy coupled with CIELAB no- Gerats, A.G.M, R.T.J. Cornelissen, J.M.W. Eikelboom. 1988. Inheritance of flower pig- tation allows the breeder to dissect color into Hogervost, A.W. Schram, and F. Bianchi. 1982. ments in (Tulipa L.). Euphytica 38:49-55. three component traits that can be evaluated A gene controlling rate of anthocyanin synthesis Onslow, M.W. 1925. The anthocyanin pigments of objectively and precisely. CIELAB notation and mutation frequency of the gene Anl in plants. Cambridge Univ. Press, London. defines color in terms that permit data to be Petunia hybrida. Theoretical & Applied Genet. SAS Institute. 1985. SAS user’s guide: Basics, ver- treated as a continuous variable. Applying this 62:199-203. sion 5 edition. SAS Institute, Cary, N.C. technology to the Davis population suggests it Griesbach, R.J. 1984a. Biochemistry of flower color. Shaw, D.V. 1991. Genetic variation for objective may be advantageous to consider gerbera Proc. 11th World Orchid Conf., Miami, Fla. p. and subjective measures of fresh fruit color in 174-176. strawberries. J. Amer. Soc. Hort. Sci. 116:894- flower color as a complex trait that includes Griesbach, R.J. 1984b. Effects of carotenoid-an- 898. polygenic variation as well as the effects of thocyanin combinations on flower color. J. Vandoni, G.C. 1977. Genetic analysis of some phe- major loci. Hered. 75: 145–147. notypes of Gerbera jamesoni. Genet. Agr. Literature Cited Harding, J., J.D. Drennan, and T.G. Byrne. 1985. 31:113–119. Components of genetic variation in the Davis Yu, Y., T. Byrne, and J. Harding. 1991. Quantitative Agoston, G.A. 1979. Color theory and its applica- population of gerbera. Euphytica 34:759–767. genetic analysis of flowering time in the Davis tion in art and design. Springer-Verlag, New Harding, J., H. Huang, and T. Byrne. 1991. Mater- population of gerbera. I. Components of genetic York. nal, paternal, additive, and dominance compo- variance and heritability. Euphytica 53:19–23.

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