Abstract
Genotype-by-environment (GE) interaction can be analyzed using different approaches. Among these, the additive main effects and multiplicative interaction model yields useful interpretations and can be applied successfully to plant breeding programs. In this paper we review fitting strategies for this model and show how to combine the capabilities of the Mixed and IML procedures in SAS to fit this model. This permits straightforward use of likelihood-based inference in standard and non standard situations like complex experimental designs. The proposed procedures were applied to data from red mottled bean variety trials conducted in the Dominican Republic and Puerto Rico in 9 environments with 30 lines (15 with indeterminate and 15 with determinate growth habit).
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Macchiavelli, Raul E. and Beaver, James S.
(1999).
"ANALYSIS OF GENOTYPE-BY-ENVIRONMENT INTERACTION WITH AMMI MODELS USING SAS PROC MIXED,"
Conference on Applied Statistics in Agriculture.
https://doi.org/10.4148/2475-7772.1268
ANALYSIS OF GENOTYPE-BY-ENVIRONMENT INTERACTION WITH AMMI MODELS USING SAS PROC MIXED
Genotype-by-environment (GE) interaction can be analyzed using different approaches. Among these, the additive main effects and multiplicative interaction model yields useful interpretations and can be applied successfully to plant breeding programs. In this paper we review fitting strategies for this model and show how to combine the capabilities of the Mixed and IML procedures in SAS to fit this model. This permits straightforward use of likelihood-based inference in standard and non standard situations like complex experimental designs. The proposed procedures were applied to data from red mottled bean variety trials conducted in the Dominican Republic and Puerto Rico in 9 environments with 30 lines (15 with indeterminate and 15 with determinate growth habit).
