Enhanced Bayesian model for multienvironmental selection of winter hybrids maize: assessing grain yield using 'ProbBreed'.

ABSTRACT:

Background

Crossover interactions stemming from phenotypic plasticity complicate selection decisions when evaluating hybrid maize with superior grain yield and consistent performance. Consequently, a two-year, region-wide investigation of 45 hybrids maize across Nepal was performed with the aim of disclosing both site and wide adapted hybrids. Utilizing an innovative "ProbBreed" package, based on Bayesian probability analysis of randomized complete block designs with three replicated trials at each station, this study substantively streamlines hybrids maize selection.

Results

This finding revealed substantial genetic, environmental, and interactive influences on grain yield (p < 0.05). Among the hybrids, DKC9149 (8.8 tons/ha) emerged as the elite with probability coefficient

SUBMITTER: Basnet B 

PROVIDER: S-EPMC11776175 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature