adversely affecting yield components, fruit composition, and midwinter primary bud cold hardiness of ‘Vidal blanc’ for commercial production in central Kentucky and the lower midwestern United States. The specific objectives were to determine the effect of
Patsy E. Wilson, Douglas D. Archbold, Joseph G. Masabni, and S. Kaan Kurtural
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
Erik J. Sacks and Douglas V. Shaw
To determine the best sampling strategies, components of variance were estimated for 10 color traits of strawberry (Fragaria × ananassa) fruit. Over three dates in one growing season, 2000+ fruit from 47 genotypes were observed. Within-fruit, among-fruit within genotypes, and harvest date variances were compared. Variances for harvest dates were non-significant or small (0-8% of the total variance). Genotype × date variances were highly significant but small (≤ 6% of the total) for all color traits except internal hue (14% of the total). For external color traits, the within-fruit variance was greater than the among-fruit variance (16-64% and 0-14% of the total, respectively). For internal color traits, the among-fruit variance was greater than the within-fruit variance (20-37% and 9-19% of the total, respectively). Obtaining two observations per fruit for multiple fruit on one harvest date is an efficient strategy for determining a genotype's fruit color. With two observations per fruit, 7 to 22 fruit are needed to estimate a genotype's value within 2 units (CIELAB or degrees) with 95% confidence.
Erik J. Sacks and Douglas V. Shaw
Components of variance were estimated for 10 strawberry (Fragaria ×ananassa) color traits to determine their relative importance and to design optimal sampling strategies. The color attributes of >2000 fruit from 47 genotypes from the Univ. of California Strawberry Improvement Program were evaluated over three harvest dates (HDs) in one growing season. Measurements were obtained for a moderate number of fruit from each genotype on each date, and two measurements were obtained for each trait on all fruit. Variances for HDs were nonsignificant or small (0% to 8% of the total variance). Genotype × date variances were highly significant but small (≤6% of the total) for all color traits except internal hue (14% of the total). For external color traits, the within-fruit variance was greater than the among-fruit variance (16% to 64% and 0% to 14% of the total, respectively). For internal color traits, the among-fruit variance was greater than the within-fruit variance (20% to 37% and 9% to 19% of the total, respectively). Obtaining two measurements per fruit for several fruit on one HD is an efficient strategy for characterizing a genotype's fruit color; seven to 22 fruit are needed to estimate a genotype's fruit color within 2 units (Commission Internationale de L'Eclairage L*a*b* or degrees) with 95% confidence.
Dapeng Zhang, Wanda W. Collins, and Maria Andrade
Two experiments that included 25 sweetpotato [Ipomoea batatas (L.) Lam] genotypes were planted in various environments across North Carolina, and an in vitro screening method was used to investigate genotypic and environmental variance and genotype × environment (G × E) interactions of starch digestibility in sweetpotato. Significant genotypic variation of starch digestibility was found in both experiments. Some clones have starch digestibility equivalent to that of corn. Variance analysis from both experiments indicated that genotypic variance was the dominant component in starch digestibility. G × E interaction only accounted for 6.8% of the phenotypic variance in one experiment and for 5.9% in the other one. These results suggested that starch digestibility of sweetpotato could be improved to a level as that of corn through conventional breeding.
L. León, L.M. Martín, and L. Rallo
Fatty acid composition has been studied in seedlings from a diallel cross (nine families) among `Arbequina', `Frantoio', and `Picual' olive (Olea europaea L.). Variance among samples within genotype, genetic and environmental (yearly) variances, and year-to-year consistency of data were estimated. A correlation analysis of the standardized data for fatty acid composition between first and second year data was also carried out to select the most interesting genotypes as early as possible. The results showed that fatty acid composition exhibit significant differences between genotypes and years. The variance component attributable to differences between genotypes represented >60% of total variance for all the fatty acids evaluated. High correlation coefficients between the first and second year data were found for oleic and linoleic acid percentage; these correlations were slightly poorer for the other fatty acids analyzed. These results may be useful for improving the efficiency of olive breeding programs in first-stage selection on whole progeny populations.
S. Kaan Kurtural, Lydia F. Wessner, and Geoffrey Dervishian
in Region V with a procumbent grape cultivar such as Syrah. Therefore, our study was designed to investigate how the interaction of pruning systems and mechanical shoot removal affected canopy performance, yield components, fruit phenolic composition
Molly Felts, Renee T. Threlfall, and Margaret L. Worthington
component analysis was used to segregate genotypes into different groups ( Fig. 1 ). The perception of physicochemical and descriptive sensory attributes was reduced to two principal components that explained 63.4% of data variance. Principal component 1 (40
Carol A. Bobisud, Susan P. Martin, and Terry T. Sekioka
To estimate the components of variance of a tissue culture experiment, hypocotyl sections of tomato cultivars (C) `Healani,' `Kewalo' and `Anahu' were cultured on modified Murashige and Skoog medium with 10 uM IAA and 10 uM BAP. Three explants were placed in each of 45 flasks per cultivar. This procedure was repeated three times (R) on different dates. Mean values of the number of shoots per explant were 7.0. 8.2 and 9.2 for `Healani', `Kewalo', and `Anahu', respectively. The data were transformed by adding 0.5 and then taking the square root of the sum. Components of variance of the transformed data were σ2 = 0.01, σC2 = -0.02, σRC2 = 0.09, σFC2 = 0.22 and σE2 = 1.68 (error term). The components of variance were used to determine the theoretical variance of the cultivar (treatment) mean. Results indicated that the most efficient method of reducing the error is by increasing the number of explants per flask. Stein's two-stage sample equation determined the number of explants required for a 95% confidence level to be 1613, 807 and 380 to detect differences of 5% 7% and 10%. respectively, of the overall transformed mean.
Stephen J. Tancred, Aldo G. Zeppa, Mark Cooper, and Joanne K. Stringer
A major objective of the apple (Malus domestica Borkh.) breeding program in Stanthorpe, Australia, is to develop early ripening, high-quality cultivars. The heritability and inheritance of ripening date was investigated. Regression of offspring on midparent harvest dates and estimation of best linear unbiased predictions for parents were used to demonstrate that apple harvest date is highly heritable. Predominantly, additive genetic components of variance are responsible for the variation. Despite the existence of some specific combining ability variance and some non-normal family distributions, the best strategy for a breeder to predict the harvest date of progeny is to calculate the mean harvest date of parents.