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Toshihiro Saito, Norio Takada, Hidenori Kato, Shingo Terakami and Sogo Nishio

genetic and environmental variance components to the determination of fruit traits of sweet cherry ( Hansche and Beres, 1966 ; Hansche and Brooks, 1965 ), Japanese pear fruit ( Kozaki, 1975 , 1976 ; Machida and Nishio et al., 2011 ), Japanese persimmon

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Sogo Nishio, Masahiko Yamada, Yutaka Sawamura, Norio Takada and Toshihiro Saito

; Kenis et al., 2008 ; Moriya et al., 2010 ; Quilot et al., 2004 ; Segura et al., 2009 ; Zhang et al., 2010 ). However, phenotypic variance contains both genetic and environmental variance components. The effectiveness of detected QTLs essentially

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Uri Lavi, Emanuel Lahav, Chemda Degani, Shmuel Gazit and Jossi Hillel

Genetic variance components for avocado (Persea americana Mill.) traits were estimated to improve avocado breeding efficiency. The additive and nonadditive genetic variance components were calculated from the variances between and within crosses. In all nine traits examined, i.e.-anise scent, fruit density, flowering intensity, fruit weight, harvest duration, inflorescence length, seed size, softening time, and tree size-a significant nonadditive genetic variance was detected. Additive genetic variance in all traits was lower and nonsignificant. The existence of major nonadditive variance was indicated also by narrow-sense and broad-sense heritability values estimated for each trait. Therefore, parental selection should not be based solely on cultivar performance. Crosses between parents of medium and perhaps even low performance should also be included in the breeding program.

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Qiang Yao and Shawn A. Mehlenbacher

Seventy-seven trees representing 41 hazelnut (Corylus avellana L.) genotypes were to evaluate variance components and broad-sense heritability for 10 nut and kernel traits from 1994 to 1996. All effects in the models were assumed to be random. All traits had extremely high heritability. This indicated that nearly all of the phenotypic variation had a genetic basis. Knowledge of variance components may help us efficiently allocate resources. Broad-sense heritability estimates were larger than those in narrow sense, suggesting the presence of nonadditive genetic variation in the population.

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P.G. Thompson, John C. Schneider and Boyett Graves

Narrow-sense heritability for component traits of freedom from weevil injury and yield of sweetpotato were estimated by parent-offspring regression and variance component analysis. Heritability estimates by variance component analysis based on half-sib families for percent and number of uninjured roots were 0.25 and 0.83, respectively. Individual plant heritability estimates for uninjured root percent and number were 0.03 and 0.13, respectively. Heritability estimates by parent-offspring regression for uninjured root percent and number were 0.35 and 0.52, respectively. Genetic variance was mostly additive for all traits except stem diameter. Genetic correlations between total root number, uninjured root number, and percent uninjured roots ranged from 0.66 to 0.87, indicating that selection for uninjured root number should most effectively increase uninjured root number and percent, as well as total root numbers. Predicted gains in uninjured root percent and number were 8.8% and 0.87 in the progeny derived from intermating the highest four out of 19 families for uninjured root number. The 0.87 gain in uninjured root number equals a 24% increase in one breeding cycle.

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Zhanyong Sun*, Richard L. Lower and Jack E. Staub

The incorporation of genes for parthenocarpy (production of fruit without fertilization) has potential for increasing yield in pickling cucumber (Cucumis sativus L.). The inheritance of parthenocarpy in cucumber is not well understood, and thus a genetic analysis was performed on F3 cross-progeny resulting from a mating between the processing cucumber inbred line 2A (P1, gynoecious, parthenocarpic, indeterminate, normal leaf) and Gy8 (P2, gynoecious, non-parthenocarpic, indeterminate, normal leaf). A variance component analysis was performed to fruit yield data collected at two locations (designated E-block and G-block) at Hancock, WI in 2000. The relative importance of additive genetic variance compared to dominance genetic variance changed across environments. The additive genetic variance was 0.5 and 4.3 times of dominance genetic variance in E-block and G-block, respectively. The estimated environmental variance accounted for ≈90% of the total phenotypic variance on an individual plant basis in both locations. Narrow-sense heritability estimated on an individual plant basis ranged from 0.04 (E-block) to 0.12 (G-block). Broad-sense heritability estimated on an individual plant basis ranged from 0.12 (E-block) to 0.15 (G-block). The minimum number of effective factors controlling parthenocarpy was estimated to range between 5 (G-block) to 13 (E-block). These results suggest that the response to direct selection of individual plants for improving parthenocarpy character will likely be slow and difficult. Experiment procedures that minimize the effect of environment on the expression of parthenocarpy will likely maximize the likelihood of gain from selection.

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Todd C. Wehner, Rachel P. Naegele and Penelope Perkins-Veazie

comparisons were made if F ratio was significant (5% level). Variance components were estimated using PROC VARCOMP implemented within SAS. Phenotypic variance was calculated without environmental variance according to Hallauer and Miranda (1981) . Correlation

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W. Alan Erb and N. Jean Flickinger

Two tomato inbreds (one advanced greenhouse line, P1=Ohio ICR.9 and one frost resistant line, P2=Ohio 4013-3) and F1, BC1, BC2 and F2 progeny were examined for growth and development during December and January to determine inheritance of biomass characters. Two-week-old seedlings from each generation (8 from the P1, P2 and F1; 32 from the BC1 and BC2; and 64 from the F2) developed over a 9-week period at 2 different night temperatures (17 and 12 C) and light levels (natural light and 30% shade, 5 days/week). The F1 generation had the highest leaf area and total dry weight means followed by the BC1 and P1 generations. The variance components for leaf area and total dry weight accumulation were: Ve = 120,300 and 2.63; Vp = 553,618 and 12.46; Va = 127,475 and 3.65; and Vd = 305,843 and 6.18, respectively. Both traits are highly heritable, having a broad sense heritability of 0.78 and 0.79 for leaf area and total dry weight, respectively. However, because narrow sense heritability is low, 0.23 and 0.30, respectively, improvement in biomass accumulation will be more difficult.

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Rolland Agaba, Phinehas Tukamuhabwa, Patrick Rubaihayo, Silver Tumwegamire, Andrew Ssenyonjo, Robert O.M. Mwanga, Jean Ndirigwe and Wolfgang J. Grüneberg

magnitudes of variance components for yield and nutritional quality traits provide information for better understanding of germplasm properties. Similarly, genotypic and phenotypic variation coefficients (GCV and PCV, respectively) give a measure of the

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Heather L. Merk, Shawn C. Yarnes, Allen Van Deynze, Nankui Tong, Naama Menda, Lukas A. Mueller, Martha A. Mutschler, Steven A. Loewen, James R. Myers and David M. Francis

in the lme4 package ( Bates et al., 2011 ) was used to estimate variance components. For each trait except yield, the following linear model was used: where Y ijk is the trait measured, μ is the overall mean, G i is the effect resulting from the ith