Evaluation of soybean lines and environmental stratification using the AMMI, GGE biplot, and factor analysis methods

Area of Science:

• Agronomy
• Plant Breeding
• Quantitative Genetics

Background:

• Soybean cultivar development requires evaluating genotypes across diverse environments to identify superior lines for quantitative traits like grain yield.
• Understanding genotype-by-environment (GxE) interactions is crucial for selecting stable and high-yielding soybean varieties.

Purpose of the Study:

• To analyze GxE interactions for grain yield in early-cycle soybean genotypes.
• To assess the adaptability and stability of these genotypes using multiple statistical methods.
• To compare the efficiency of Additive Main Effects and Multiplicative Interaction (AMMI), Genotype Main Effects and Genotype x Environment Interaction (GGE) biplot, and factor analysis.

Main Methods:

• Field experiments conducted across five locations in Mato Grosso over two growing seasons (2011/2012 and 2012/2013).
• Evaluation of 27 early-cycle soybean genotypes, including 22 lines from the Universidade Federal de Uberlândia (UFU) breeding program and 5 control cultivars.
• Statistical analyses using AMMI, GGE biplot, and factor analysis to assess genotype performance, adaptability, and stability.

Main Results:

• Significant and complex GxE interactions were detected for grain yield.
• The AMMI model was most efficient, explaining 61.46% of the variation with its first two principal components, followed by GGE biplot (57.90%) and factor analysis (54.12%).
• Genotype G5 exhibited high grain yield, adaptability, and stability across the evaluated environments.

Conclusions:

• AMMI, GGE biplot, and factor analysis are effective tools for analyzing GxE interactions and identifying stable soybean genotypes.
• Environmental grouping revealed similarities across different seasons at the same location.
• Genotype G5 is a promising candidate for early-cycle soybean breeding programs due to its consistent high performance.