Testing multiplicative terms in AMMI and GGE models for multienvironment trials with replicates

Area of Science:

• Agricultural Science
• Biometrics
• Plant Breeding

Background:

• Additive Main Effects and Multiplicative Interaction (AMMI) and Genotype Main Effects and Genotype-by-Environment Interaction (GGE) models are standard for analyzing multienvironment trial data.
• Agronomists and plant breeders utilize these models for cultivar trials across diverse environments and years.
• Determining the number of significant multiplicative interaction terms is critical in these analyses.

Purpose of the Study:

• To propose a resampling-based method for testing the significance of multiplicative interaction terms in AMMI and GGE models.
• To offer a robust alternative to existing parametric tests that assume normality and homogeneous variance.
• To evaluate the performance of the proposed method against competing tests.

Main Methods:

• Development of resampling-based methods for analyzing multienvironment trial data with replicates.
• Comparison of proposed methods with existing parametric tests.
• Extensive simulation study using data from two multienvironment trials.

Main Results:

• The proposed resampling methods demonstrate robust performance in terms of Type-I error rates, irrespective of error distribution.
• The methods are superior to contending methods in robustness to heterogeneity of variance.
• The proposed method outperforms the robust t-test when normality and homogeneity of variance assumptions are violated.

Conclusions:

• Resampling-based methods provide a reliable approach for analyzing multienvironment trials with replicates.
• These methods offer improved robustness, particularly when standard statistical assumptions are not met.
• The findings support the adoption of resampling techniques for more accurate significance testing in plant breeding and agronomy.