R. Bras. Zootec.13/Nov/2026;55:e20250253.
Variability and prediction of energy nutritional traits in grains from maize genetic basis and their relationships with meteorological variables
Murilo Vieira Loro
, Alberto Cargnelutti Filho
ABSTRACT
The purpose of this study was to evaluate whether there is variability in the energy and nutritional composition of maize grains among different genetic backgrounds and sowing dates and to determine whether there are relationships between energy nutritional traits and meteorological variables. In total, 773 grain samples from four maize genetic backgrounds, cultivated across ten sowing dates in the years 2021, 2022, and 2023, were evaluated. Descriptive statistics were calculated, and the principal component, correlation, multiple linear regression, and random forest analyses were performed. The contents of ash, ether extract, crude fiber, starch, amylose, and apparent metabolizable energy corrected for nitrogen balance varied among maize genetic backgrounds and sowing dates. At the study site, maize sown in January and February had the highest levels of starch, amylose, and apparent metabolizable energy corrected for nitrogen balance, and the lowest levels of ash, ether extract, and crude fiber. Single-, triple-, and double-cross hybrids had the highest contents of starch, amylose, and apparent metabolizable energy corrected for nitrogen balance, whereas open-pollinated varieties had the highest contents of ash, ether extract, and crude fiber. The contents of crude fiber, starch, amylose, and apparent metabolizable energy corrected for nitrogen balance in maize grains could be predicted using meteorological variables across all maize genetic backgrounds. Random forest models exhibited high predictive accuracy (R2 ≥ 0.78), with precipitation between female flowering and harvest emerging as the main meteorological variable associated with the contents of crude fiber, starch, amylose, and apparent metabolizable energy corrected for nitrogen balance (IncMSE ≥ 23.83%).
