Search Results

You are looking at 1 - 10 of 451 items for :

  • phenotypic correlation x
  • All content x
Clear All
Free access

Lorenzo León, Luis M. Martín, and Luis Rallo

Thirteen characters were evaluated over four years in progenies from a diallel cross among the olive (Olea europaea L.) cultivars `Arbequina', `Frantoio', and `Picual' to determine if phenotypic correlations existed between these characters. Yield per tree, ripening date, oil yield components and fatty acid composition were recorded annually once seedlings began to flower and produce fruit. Significant correlations were found between several characters including oil yield components and fatty acids composition. Lower correlation coefficients were obtained between ripening date and oil and oleic acid content. Generally, yield was not correlated with the other characters evaluated. Principal components analysis confirmed the main correlations among characters and showed them to be independent of the parents used.

Free access

Valdomiro A.B. de Souza, David H. Byrne, and Jeremy F. Taylor

Heritability estimates are useful to predict genetic progress among offspring when the parents are selected on their performance, but they also provide information about major changes in the amount and nature of genetic variability through generations. Genetic and phenotypic correlations, on the other hand, are useful for better planning of selection programs. In this research, seedlings of 39 families resulting from crosses among 27 peach [Prunus persica (L.) Batsch] cultivars and selections were evaluated for date of full bloom (DFB), date of ripening (DR), fruit period development (FDP), flower density (FD), node density (ND), fruit density (FRD), fruit weight (WT), soluble solids content (SS), apical protuberance (TIP), red skin color (BLUSH), and shape (SH) in 1993 and 1994. The data were analyzed using the mixed linear model. The best linear unbiased prediction (BLUP) was used to estimate fixed effects and predict breeding values (BV). Restricted maximum likelihood (REML) was used to estimate variance components, and a multiple-trait model to estimate genetic and phenotypic covariances between traits. The data indicates high heritability for DFB, DR, FDP, and BLUSH, intermediate heritability for WT, TIP, and SH, and low heritability for FD, ND, FRD, and SS. They also indicate year effect as a major environmental component affecting seedling performance. High correlation estimates were found between some traits, but further analysis is needed to determine their significance.

Free access

T.E. Thompson and J.F. Baker

Heritability estimates for pecan [Carya illinoinensis (Wangenh.) K. Koch] nut weight, nut buoyancy, nut volume, nut density, kernel weight, and percentage kernel were determined from 8748 nut samples representing 152 families collected during 25 years in the U.S. Dept. of Agriculture (USDA) pecan breeding program at Brownwood, Texas. Measurements were corrected for year-to-year environmental variability using least-squares constants of individual year effects. Adjusted values were then regressed on midparent means. Generally, heritability (h2) estimates were low to moderate: nut weight 0.35, nut buoyancy 0.18, nut volume 0.35, nut density 0.03, kernel weight 0.38, and percentage kernel 0.32. The low values are probably due to the extreme alternate bearing tendency of this species, since crop load affects pecan nut characteristics so directly. Phenotypic correlations among these traits showed that larger or heavier nuts had significantly higher kernel weight, buoyancy, and percentage kernel. Nut density increased with higher nut and kernel weight, but decreased with nut volume.

Free access

John E. Preece, Carl A. Huetteman, W. Clark Ashby, Paul L. Roth, and Richard G. Adams

Sixty clones (four clones from each of 15 provenances) were micropropagated and planted in replicated plots in lowland and upland sites in Carbondale, IL in 1991. Data were collected on tree growth, including basal caliper, height, branching, crown volume, dates of bud break, bud set, and leaf fall. There were significant and strong positive genotypic and phenotypic correlations between tree height and basal caliper throughout the three years of growth. During 1993, bud break was not significantly correlated with any growth parameters. After three years in the field, tree height was significantly negatively correlated with the amount of callus that had formed after one month during the in vitro micropropagation phase. However, all shoots that formed in vitro were of axillary origin.

Free access

Valdomiro A.B. de Souza, David H. Byrne, and Jeremy F. Taylor

Thirteen peach [Prunus persica (L.) Batsch] fruit characteristics were investigated for 3 years, 1993, 1994, and 1995, in College Station, Texas, to determine heritability, genetic and phenotypic correlations, and predicted response to selection. Seedlings of 108 families resulting from crosses among 42 peach cultivars and selections were used in the evaluations. A mixed linear model, with years treated as fixed and additive genotypes as random factors, was employed to analyze the data. Best linear unbiased prediction (BLUP) was used to estimate fixed effects. Restricted maximum likelihood (REML) was used to estimate variance components, and a multiple trait model was used to estimate genetic and phenotypic covariances between traits. Genetic and phenotypic correlations ≥0.65 and <0.30 were considered strong or very strong and weak, respectively. Date of ripening, fruit development period (FDP) and date of full bloom had the highest heritability (h2) estimates, 0.94, 0.91, and 0.78, respectively. Fruit cheek diameter and titratable acidity (h2 = 0.31) were the traits with the lowest estimates. Fruit development period, fruit blush, and date of ripening had the highest predicted selection responses, whereas fruit suture, fruit cheek, L/W12 (ratio fruit length to average fruit diameters), and fruit tip had the lowest values. Most genetic correlations were ≥0.30 and were, in general, much higher than the corresponding phenotypic correlations. All four measures of fruit size were genetically and phenotypically very strongly correlated. Important genetic correlation estimates were also observed for date of ripening with FDP (ra = 0.93), date of ripening and FDP with fruit blush (ra = -0.77, ra = -0.72), SS (percent soluble solids) (ra = 0.63, ra = 0.62) and TA (ra = 0.55, ra = 0.64), and SS with TA (ra = -0.56). Direct selection practiced solely for early ripening and short FDP is expected to have a greater effect on correlated traits than direct selection for early bloom and large fruit mass.

Free access

Valdomiro A.B. de Souza, David H. Byrne, and Jeremy F. Taylor

Seedlings of 108 families from crosses among 42 peach [Prunus persica (L.) Batsch] cultivars and selections were evaluated for six plant characteristics in 1993, 1994, and 1995. The data were analyzed by using a mixed linear model, with years treated as fixed and additive genotypes as random factors. Best linear unbiased prediction (BLUP) was used to estimate fixed effects. Restricted maximum likelihood (REML) was used to estimate variance components, and a multiple trait model was used to estimate genetic and phenotypic covariances among traits. The narrow-sense heritability estimates were 0.41, 0.29, 0.48, 0.47, 0.43, and 0.23 for flower density, flowers per node, node density, fruit density, fruit set, and blind node propensity, respectively. Most genetic correlations among pairs of traits were ≥0.30 and were, in general, much higher than the corresponding phenotypic correlations. Flower density and flowers per node (ra = 0.95), fruit density and fruit set (ra = 0.84) and flower density and fruit density (ra = 0.71) were the combinations of traits that had the highest genetic correlation estimates. Direct selection practiced solely for flower density (either direction) is expected to have a greater effect on fruit density than direct selection for fruit density.

Full access

Zhuping Fan, Yike Gao, Ling Guo, Ying Cao, Rong Liu, and Qixiang Zhang

of direct selection; 3) to estimate the correlations between the tested phenotypic traits, making it possible to forecast the performance of certain traits by observing correlations and simplify the process of breeding; and 4) to analyze the

Open access

Guo-Liang Jiang, Laban K. Rutto, and Shuxin Ren

, and y is the number of years. Coefficients of phenotypic and genotypic correlations were computed using SAS codes described by Holland (2006) , as r_{pij} = σ pij /(σ pi ·σ pj ), and gij = σ gij /(σ gi ·σ gj ) where σ pij and σ gij are the

Free access

Peter J. Zale, Daniel K. Struve, Pablo Jourdan, and David M. Francis

traits. Family variances were estimated using the covariance test option of the MIXED procedure on the sum of traits x and y using Eq. [4] ( Vargas-Hernandez et al., 2003 ): Family mean phenotypic correlations were calculated for all pairwise

Free access

Steven M. Todd, Van-Den Truong, Kenneth V. Pecota, and G. Craig Yencho

significant effect. SCA was considered significant if the parents demonstrated a statistically significant female × male interaction for the trait. Trait correlations were analyzed using the multivariate option in JMP (version 9.0). Phenotypic correlations