TY  - JA
AU  - Varela,M.
AU  - Crossa,J.
AU  - Raneri,J.
AU  - Joshi,A.K.
AU  - Trethowan,R.M.
TI  - Analysis of a three-way interaction including multi-attributes
SN  - 0004-9409
PY  - 2006///
CY  - Victoria (Australia)
PB  - CSIRO Publishing
KW  - Additive Effect
KW  - AGROVOC
KW  - Genotype environment interaction
KW  - Genotypes
KW  - Irrigation
KW  - Yields
KW  - Statistical methods
N1  - Peer review
N2  - The additive main effect and multiplicative interaction (AMMI) has been widely used for studying and interpreting genotype×environment interaction (GEI) in agricultural experiments using multi-environment trials (METs). When METs are performed across several years the interaction is referred to as a 3-mode (3-way) data array, inwhich the modes are genotypes, environments, and years. The 3-way array can be applied to other conditions or factors artificially created by the researcher, such as different sowing dates or plant densities, etc. Three-way interaction data can be studied using the AMMI analysis. The objective of this study is to apply the 3-mode AMMI to 2 datasets. Dataset 1 comprises genotype (25)×location (4)×sowing time (4) interaction; 8 traits were measured. The structure of dataset 2 is genotype (20)×irrigation regimes (4)×year (3) on grain yield. Results of the 3-way AMMI on dataset 1 show that several important 3-way interactions were not detected when condensing location (4)×sowing time (4) into environments (16). An alternative 3-way array, genotype×attribute×locations for the early sowing date in Year 1, is considered. Results of the 3-way AMMI on dataset 2 show that different patterns of response of genotypes can be found at different irrigation methods and years
UR  - https://hdl.handle.net/20.500.12665/357
DO  - https://doi.org/10.1071/AR06081
T2  - Australian Journal of Agricultural Research
ER  -