Quantitative Analysis of Generations for Inheritance of Fruit Yield in Watermelon

There is a large genetic diversity for fruit size and yield in watermelon [Citrullus lanatus (Thunb.) Matsum. & Nakai var. lanatus]. Current cultivars have high fruit quality but may not be the highest yielders. This study was designed to estimate variance components and heritability of fruit yield (Mg·ha), fruit count (th·ha), and fruit size (kg/fruit) in a cross involving high-yielding ‘Mountain Hoosier’ with low-yielding ‘Minilee’. Six generations (PaS1, PbS1, F1, F2, BC1Pa, and BC1Pb) were developed and tested in Summer 2008 at two locations in North Carolina. Discrete classes were not observed within the F2 segregating population. The actual distribution of the F2 population for fruit yield, fruit count, and fruit size deviated from the normal distribution. ‘Mountain Hoosier’ had higher parental and backcross variance than ‘Minilee’. High F2 variance for fruit yield indicated large phenotypic variance. There was a larger environmental variance than genetic variance associated with the yield traits. Estimates of broadand narrow-sense heritability were low to medium. A large number of effective factors indicated polygenic inheritance for fruit yield and fruit size. Gain from selection for yield is amendable by selection. As a result of this complex inheritance, selection based on individual plant selection in pedigree method may not be useful for yield improvement in this population. Hence, a selection scheme based on progeny testing using replicated plots, perhaps at multiple locations, is recommended. Watermelon [Citrullus lanatus (Thunb.) Matsum. & Nakai var. lanatus; 2n = 2x = 22] is an economically important, cross-pollinated vegetable crop that is grown throughout the world. Watermelon is grown over 3.5 million ha worldwide with production of 104 million Mg (Food and Agriculture Organization, 2012). The United States is the fourth largest producer after China, Iran, and Turkey (Kumar and Wehner, 2011a). Total area has decreased from 76,000 ha in 1998 to 56,000 ha in 2011 (U.S. Department of Agriculture, 2012). However, production has increased from 1.9 million Mg in 1998 to 2 million Mg in 2011. Over 80% of production is concentrated in the southern United States where temperatures are high: Arizona, California, North Carolina, Florida, Texas, and Georgia. Watermelon has been bred to improved fruit yield, fruit quality, disease resistance, seedlessness, short vine length, and adaptation to production areas around the world. The first genetic studies on watermelon were published in the 1930s and 1940s and involved pure-line cultivars developed in the previous few decades. Those studies focused on traits such as rind pattern, flesh color, seedcoat color, fruit shape, fruit size, and sex expression (Poole, 1944; Poole and Grimball, 1945; Poole et al., 1941; Porter, 1933, 1937; Weetman, 1937). Yield varies among watermelon accessions, old cultivars, and modern elite cultivars (Gusmini and Wehner, 2005). Growers are currently getting !50 Mg·ha of marketable yield (Maynard, 2001). Many have studied the inheritance of qualitative genes in watermelon (Cucurbit Gene List Committee, 1979, 1982, 1987; Guner and Wehner, 2004; Henderson, 1991; Rhodes and Dane, 1999; Rhodes and Zhang, 1995). However, there are few quantitative genetic studies, especially for important traits such as fruit yield and size. Fruit yield was reported to be correlated with component traits such as fruit count and fruit size (Kumar and Wehner, 2011b). Heterosis for watermelon fruit yield and its component traits has been reported (Brar and Sidhu, 1977; Brar and Sukhija, 1977; Chhonkar, 1977; Sidhu and Brar, 1978; Thakur and Nandpuri, 1974). However, fewer studies have examined the inheritance of fruit yield and its component traits in watermelon (Gusmini and Wehner, 2007; Kumar and Wehner, 2011a). Gusmini and Wehner (2005) screened a diverse set of 80 watermelon cultivars for fruit yield, fruit count, and fruit size and reported a large amount of genetic variation. Yield ranged from 114.2 Mg·ha in ‘Mountain Hoosier’ to 36.4 Mg·ha in ‘Minilee’. The highest yielders were the inbreds ‘Legacy’, ‘Mountain Hoosier’, ‘Hopi Red Flesh’, ‘Early Arizona’, ‘Stone Mountain’, ‘AUJubilant’, ‘Sweetheart’, ‘Calhoun Gray’, ‘Big Crimson’, ‘Moon & Stars’, ‘Cole Early’, ‘Yellow Crimson’, and ‘Blacklee’ and the F1 hybrids ‘Starbrite’ and ‘Stars-N-Stripes’. These high yielders included cultivars producing an intermediate number of fruit of medium size (9 to 12 kg/fruit), except ‘Early Arizona’, ‘Stone Mountain’, ‘Sweetheart’, and ‘Cole Early’, which had small (6 to 9 kg/fruit) fruit. ‘Sweet Princess’, ‘Calsweet’, and ‘Minilee’ were the lowest yielders. To improve complex (quantitative) traits like yield, understanding variances and heritability behaviors of yield and its components is paramount. Genetic variance and heritability can be estimated using parent– offspring regression (Holland et al., 2003; Kumar and Wehner, 2011b; Nyquist, 1991), North Carolina Design I, NC Design II (Comstock and Robinson, 1948), and North Carolina Design III (Comstock and Robinson, 1952). Kumar and Wehner (2011b) used parent–offspring regression to measure heritability of yield in watermelon. However, populations that were used to calculate heritability estimates in their study were developed by half-diallel using diverse set of old and new cultivars. Those estimates were low (0.02 to 0.09) and were applicable to those populations. That study indicated that genetic gain will be small and replicated progeny rows were required to select for yield improvement. Among other methods, a design based on the measure of variance from six generations (PaS1, PbS1, F1, F2, BC1Pa, and BC1Pb) can be used to estimate environmental, genetic, additive, dominance, and phenotypic variances and heritability in biparental populations (Lyimo et al., 2011; Zalapa et al., 2006). To improve yield by pedigree selection, biparental populations can be developed by crossing highwith lowyielding cultivars. If the heritability estimates are high for yield, individual plant selection may be practiced in early generations to make genetic gain. If heritability estimates are low, selection for yield should be based on replicated plot trials at multiple locations in more advanced generations. Genetic information related to yield improvement in watermelon is limited. The present study was designed to determine genetic variance and inheritance of fruit yield, fruit count, and fruit size from the cross of highyielding ‘Mountain Hoosier’ with low-yielding ‘Minilee’. Materials and Methods Germplasm development and generation of crosses. The high yielding pure-line watermelon cultivar Mountain Hoosier (114.2 Mg·ha) was crossed to the lowyielding cultivar, Minilee (36.4 Mg·ha) (Gusmini and Wehner, 2005). In addition to fruit yield, difference for fruit size was also Received for publication 25 Mar. 2013. Accepted for publication 26 May 2013. We gratefully acknowledge Ms. Tammy Ellington for assistance with greenhouse pollinations and field tests. To whom reprint requests should be addressed; e-mail [email protected]. 844 HORTSCIENCE VOL. 48(7) JULY 2013 observed in ‘Mountain Hoosier’ (10.2 kg) and ‘Minilee’ (3.6 kg). Total fruit count for ‘Mountain Hoosier’ and ‘Minilee’ was 10.2 and 12.2 th·ha, respectively. The population was intended for yield improvement using pedigree selection. Six generations were developed to estimate the components of variance and heritability for use in designing an optimum breeding strategy. The F1 generation was self-pollinated to produce the F2, and F1 generation was crossed to the high yielding parent (PaS1) and the low-yielding parent (PbS1) to produce BC1Pa (F1 · PaS1) and BC1Pb (F1 · PbS1). The six generations (PaS1, PbS1, F1, F2, BC1Pa, BC1Pb) were produced in the greenhouses at the Horticultural Field Laboratory, North Carolina State University, Raleigh, NC. Parents were selfpollinated to obtain sufficient seeds for making future crosses, so they were noted as PaS1 and PbS1. Cultural practices. Seeds of the six generations were sown in 72-cell polyethylene flats in the greenhouse. The artificial soilless growing medium 4P Fafard soilless mix (Conrad Fafard Incorporated, Agawam, MA) was used. The medium was wetted to capacity after seeding and held in the greenhouse at 25 to 30 !C until full emergence. The transplants were moved to a coldframe at the field site for acclimation 1 week before transplanting. The seedlings were transplanted by hand at the two-true-leaf stage. Missing or damaged transplants were replaced 1 week after transplanting. In the field, raised beds were made up with drip irrigation tubes and covered with black polyethylene mulch. The experiment was conducted using horticultural practices recommended by the North Carolina Extension Service (Sanders, 2004). To keep generations and plants separate for data collection, each plant was manually trained each week into a spiral shape by turning all the vines in a clockwise circle around the crown until fruit set. The vine training allows rapid tracing of the fruit to each plant but affects yield, so heritability estimates apply only to this method of selection (Gusmini and Wehner, 2007). Experiment design. The field tests were conducted at two locations at the Horticultural Crops Research Station in Clinton, NC, in the summer of 2008. Two locations were designated as Clinton (M) and Clinton (P) where M and P represent blocks of the field. All six generations were planted (200 plants) at each location as follows: PaS1 (10 plants), PbS1 (10 plants), BC1Pa (30 plants), BC1Pb (30 plants), F1 (20 plants), and F2 (100 plants). There were four rows at each location with 50 plants per row. The fields had raised shaped beds (rows) on 3.1-m centers with single hills 1.2 m apart. Variances. Distributions of the F2 populations were tested for normality using ShapiroWilk’s statistic (Shapiro and Wilk, 1965) in PROC UNIVARIATE procedure of SASSTAT (SAS Institute, Inc., Cary, NC) for each location. The variance components, phenotypic (P), environmental (E), genotypic (G), and additive (A) variances, in each generation were estimated using Warner (1952) and Wright’s (1968) formulae: s P ð Þ 1⁄4 s F2 ð Þ s G ð Þ 1⁄4 s P ð Þ % s E ð Þ s E ð Þ 1⁄4 s 2 Pa ð Þ þ s2 Pb ð Þ þ 2 s2 F1 ð Þ 1⁄2 (