Selecting stable rice mutants with linear mixed models (LMM) and stability indexes

Area of Science:

• Agricultural Science
• Genetics and Breeding
• Plant Science

Background:

• Mutation breeding is a key strategy for generating genetic diversity in crop improvement.
• Identifying stable and high-yielding mutant rice lines is crucial for sustainable agriculture.

Purpose of the Study:

• To identify stable rice mutant lines with superior yield and performance across multiple environments.
• To evaluate the genetic diversity and stability of fourteen rice mutant lines compared to conventional cultivars.

Main Methods:

• Multi-environment trials (METs) were conducted across three Iranian locations over two growing seasons.
• Statistical analyses included ANOVA, likelihood ratio tests (LRTs), principal component analysis (PCA), and stability metrics like WAASB, MTSI, and HMRPGV.
• The 'metan' R package was utilized for comprehensive multi-environment trial analysis.

Main Results:

• Significant genotypic, environmental, and genotype-by-environment interaction (GEI) effects were observed for all evaluated traits.
• Principal component analysis indicated that the first three PCs explained substantial variation in GEI.
• Genotypes G3, G9, G6, G12, and G5 were identified as high-yielding and stable using WAASB and heatmap visualization.
• MTSI analysis selected G7, G5, and G1, while HMRPGV ranked G5, G12, G7, G2, and G1 as top performers.

Conclusions:

• Mutation breeding successfully generated significant genetic diversity in rice, leading to promising mutant lines.
• Genotypes G12, G5, and G9 demonstrated notable advantages in yield and stability.
• Genotype G5 emerged as the most robust candidate for selection and potential cultivar release due to its consistent performance across multiple stability indices.