Selection index in the study of adaptability and stability in maize

Area of Science:

• Agricultural Science
• Plant Breeding
• Genetics

Background:

• Evaluating maize hybrid stability and adaptability is crucial for successful crop breeding.
• Traditional methods often analyze variables separately, potentially overlooking complex genotype-environment interactions.
• A need exists for integrated methods to assess multiple traits simultaneously for robust hybrid selection.

Purpose of the Study:

• To propose and evaluate the genotype-ideotype distance index (GIDI) as an alternative method for maize hybrid selection.
• To assess the stability and adaptability of 25 maize hybrids across six diverse environments in southern Brazil.
• To compare the predictive accuracy of GIDI with traditional yield analysis for hybrid selection.

Main Methods:

• Collected data on seven variables from 25 maize hybrids evaluated across six trial sites.
• Estimated the genotype-ideotype distance index (GIDI) using the generalized Mahalanobis distance.
• Employed GGE biplot analysis to compare predictive accuracy, group environments, and select superior hybrids.

Main Results:

• Genotype × Environment (G × E) interaction was significant for assessed variables.
• The GGE model demonstrated high predictive accuracy (PRECORR) for GIDI (0.8913) and yield (0.8709).
• GIDI analysis revealed two distinct environmental groups, while yield analysis showed a single group, highlighting differences in selection criteria.

Conclusions:

• The genotype-ideotype distance index (GIDI) effectively identifies maize hybrids combining adaptability and stability across multiple variables.
• GIDI provides a more reliable selection tool compared to analyzing individual variables separately.
• This integrated approach is recommended for optimizing maize breeding programs for diverse agricultural conditions.