Use of multi-trait evaluation indices to characterise maize (Zea mays) hybrids for enhanced fodder yield and silage quality

Context Maize (Zea mays) is a major source of green fodder and silage for livestock systems, but simultaneous improvement of biomass yield, stability, and feed quality remains challenging due to the complex nature of these traits and their sensitivity to environmental variation. Aims This study aimed to assess genetic variability, trait associations, and silage quality in maize hybrids and to identify superior and stable hybrids using the Factor Analysis and Ideotype Design based on Best Linear Unbiased Prediction (FAI-BLUP) multi-trait ranking index. Methods Twelve maize hybrids were evaluated during two spring seasons for 10 agro-morphological traits and key silage-quality parameters. Statistical analyses included descriptive statistics, ANOVA, correlation analysis, principal component analysis, and a factor analysis and ideotype-design based multi-trait selection index (FAI-BLUP) to rank hybrids for combined performance and consistency across environments. Key results Significant genetic variability was observed for fodder yield, plant architecture, and silage-quality traits. Green fodder yield showed strong positive associations with plant height, leaf length, leaf width, and number of leaves. Principal component analysis revealed that phenology and canopy-related traits accounted for most of the variation among hybrids. The FAI-BLUP multi-trait ranking index identified hybrids JH 17026 and PMH 10 as superior for overall multi-trait performance, while hybrids LH 114 and JH 17011 exhibited high consistency across seasons. Conclusions Integrated multivariate analysis and FAI-BLUP effectively identified and ranked maize hybrids combining high fodder yield, consistency, and improved silage quality. Implications The results provide a robust framework for fodder maize breeding and support the further evaluation of high-performing, stable hybrids to enhance productivity and nutritional quality in livestock production systems.