Process Description

GxE Interaction

This process analyzes the genotype-by-environment interaction component of a multi-environment trial (MET) by displaying stability measures such as Wricke's W_i (1962)1Wricke, G. 1962. Uber enie methode zur erfasssung der okologischen streubreite in feldversuchen. Z. Pflanzen. 47: 92-96. , Beta_i, MSD_i, and S2d_i (Eberhart and Russell 1966)2Eberhart S A and Russell W A. 1966. Stability parameters for comparing varieties. Crop Sci. 6: 36-40., and alpha_i and Lambda_i from Tai (1971)3Tai GCC, 1971. Genotypic stability analysis and its application to potato regional trials. Crop Sci 11: 184-190..

Genotype and GxE least square (LS) means are plotted as well.

A linear-bilinear model such as AMMI or GGE can be fit, with 2-D and 3-D biplots of the principal components and PC1 x mean trait all shown to convey the genotype performances in various environments.

Heritability is calculated on a plot-mean basis.4Hanson, C.H., H.F. Robinson, and R.E. Comstock.1956. Biometrical studies of yield in segregating populations of Korean Lespedeza. Agronomy Journal 48: 268-272.

SAS data sets containing the analysis of variance for these models are also included in the output. Heritability is displayed on the SAS Output tab or, when multiple traits are selected, the results journal.

What do I need?

One Input Data Set is required. This data set must contain columns identifying the genotype, environment, and replicate, along with one or more quantitative variables.

The peanut.sas7bdat data set shown above is included in the Sample Data folder.

For detailed information about the files and data sets used or created by JMP Genomics software, see Files and Data Sets.

Output/Results

The output generated by this process is summarized in a Tabbed report. Refer to the GxE Interaction output documentation for detailed descriptions and guides to interpreting your results.