Phenotypic predictors of dent maize grain quality based on different genetics and management practices

Rahimi Jahangirlou, M.; Akbari, G.A.; Alahdadi, I.; Soufizadeh, S.; Ludemann, C.I.; Parsons, D.


Attempts to determine phenotypic predictors to identify high quality maize grain for different uses are noteworthy. This study aimed to assess the relationships among maize grain quality and some phenotypic characteristics of dent maize cultivars in response to various irrigation regimes (6-day and 12-day intervals), planting dates (20 June and 21 July), and nitrogen rates (0 and 184 kg ha−1), in a two-year experiment. Principal component analysis suggested that grain yield, hundred-grain weight and stem biomass were highly correlated with starch, oil and most fatty acid concentration variables. Grains per ear was the only variable correlated with amylose, protein and amino acids. Using regression tree analysis, stover yield (R2 = 0.47, P˂0.01), stem biomass at flowering (R2 = 0.74, P˂0.001), and year (R2 = 0.74, P˂0.001), were the most important variables predicting starch, oil and protein concentrations of maize grain, respectively. Data from 2019, a warmer and drier year, and high nitrogen rate were associated with higher protein and amino acids. There was a negative relationship between protein and plant height (R2 = 0.44; P˂0.001). The relationships determined in this study can give an insight to breeders and farmers for specialized farming and selecting specific quality characteristics through phenotypic predictors.