SASG 3 ESTAB: A SAS Program for Computing Genotype 3 Environment Stability Statistics

SASG 3 ESTAB: A SAS Program for Computing Genotype 3 Environment Stability Statistics,Mohammed Ali Hussein,Asmund Bjornstad,A. H. Aastveit

SASG 3 ESTAB: A SAS Program for Computing Genotype 3 Environment Stability Statistics   (Citations: 11)
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The study of the other two components, the environ- ment and the G 3 E interaction, has lagged behind. We provide a comprehensive SAS program for the computation The G 3 E interaction seems to have gained more of univariate and multivariate stability statistics for balanced data. The program is intended for genotype 3 location 3 year (G 3 L 3 attention in the last few decades. Though not compara- Y) or genotype 3 location (G 3 L) data, averaged over replications ble to the sophisticated biometrical models, various (R). It computes the symmetrical joint linear regression with the right methodologies have been proposed to extract more in- and left solutions and Tukey's 1 df for nonadditivity, the regression formation from this component than analysis of variance coefficients (b -o rb-values), and the deviations from regression (dij ) (ANOVA) alone could give. Various regression models and provides the graphs of the regression lines for both genotypes have been extensively used. Univariate parametric and and locations. Separate regression on the positive and negative sectors nonparametric stability statistics have been proposed of the environmental indices is also conducted. The program calculates to determine the response of genotypes to changing Tai's a and l statistics with graphical presentation of the scatter of environment. Multivariate analytical tools originally de- the genotypes in the a, l space. Other outputs of the program include signed in other fields have been applied to extract more the univariate stability statistics Wricke's ecovalence (Wi 2 ), Shukla's 2 ), Hanson's genotypic stability (Di 2 ), Plaisted pattern from the G 3 E interaction. Most of these stabil- and Peterson's ui, Plaisted's u(i), Francis and Kannenberg's environ- ity statistics have not been extensively used and their mental variance (Si 2 ), and coefficient of variance (CV); and the rank- interrelations have not been investigated thoroughly, based nonparametric stability statistics Si (2) , Si (3) , Si (6) , Kang's rank sum, mainly due to their computational difficulty. Because and the stratified rank analysis of the genotypes. The program also of their recent introduction, the computational algo- computes Type 4 stability, superiority measure (Pi ), the desirability rithms of most of these methodologies are not included index of genotype performance, and the pairwise genotype 3 environ- in the commercial software packages in use today. They ment (G 3 E) interaction of genotypes with checks. It partitions the therefore remain inaccessible to most breeders and G 3 E interaction into that due to heterogeneity of variances and agronomists. Few attempts have been made to produce that due to imperfect correlation between the genotype performance such computational programs (Kang, 1989; Piepho, and performs the singular value decomposition of the G 3 E matrix, plotting the first two interactions' principal components. 1997, 1998, and 1999). Our objective was to produce a unified SAS program that could bridge this gap. We present here an elaborate SAS program for a detailed analysis of G 3 E interac- O f the three components of phenotypic variability tion in balanced data sets using the univariate and multi- (G, E, and G 3 E interaction), the greatest atten- variate stability statistics proposed by various authors tion has been given to genotypic effects. The sciences at different times. We believe that this unifying program of quantitative genetics and biometry have been largely will enable researchers to compute most of the univari- devoted to the study of gene action, with less emphasis ate and multivariate stability statistics and study their on the environment and the G 3 E interaction. Biome- relations under different circumstances.
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