Abstract
Heritability is a measure of possible genetic advancement under selection. Estimation of variance components could imply partitioning of genetic variability over different sources of variation. This article describes statistical methods applied and some of the observations made on results of heritability and genetic variance analysis of rice yield and related traits of progenies derived from a cross between wild and cultivated rice. A completely random model was used to perform analysis of variances employing PROC GLM. Parent-offspring regression coefficient was calculated using PROC REG. The parent-offspring regression can be greatly influenced by environments resulting in higher or lower trait expression in the offspring relative to the parents. Hence the data was standardized using PROC STANDARD and regression coefficients were recalculated. Variance components for the statistical design were estimated using PROC MIXED. Phenotypic correlations were analyzed by applying PROC CORR. Normal distribution and histograms of various traits were determined using PROC CAPABILITY. The results obtained were highly promising and can be utilized to develop new rice cultivars.
Presented at the 19th SUM forum, Kuala Lumpur Convention Centre, Malaysia
Heritability is a measure of possible genetic advancement under selection. Estimation of variance components could imply partitioning of genetic variability over different sources of variation. This article describes statistical methods applied and some of the observations made on results of heritability and genetic variance analysis of rice yield and related traits of progenies derived from a cross between wild and cultivated rice. A completely random model was used to perform analysis of variances employing PROC GLM. Parent-offspring regression coefficient was calculated using PROC REG. The parent-offspring regression can be greatly influenced by environments resulting in higher or lower trait expression in the offspring relative to the parents. Hence the data was standardized using PROC STANDARD and regression coefficients were recalculated. Variance components for the statistical design were estimated using PROC MIXED. Phenotypic correlations were analyzed by applying PROC CORR. Normal distribution and histograms of various traits were determined using PROC CAPABILITY. The results obtained were highly promising and can be utilized to develop new rice cultivars.
Presented at the 19th SUM forum, Kuala Lumpur Convention Centre, Malaysia
