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Research article - Peer-reviewed, 2022

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

Jahangirlou, Maryam Rahimi; Akbari, Gholam Abbas; Alahdadi, Iraj; Soufizadeh, Saeid; Ludemann, Cameron; Parsons, David

Abstract

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 (R-2 = 0.47, P<0.01), stem biomass at flowering (R-2 = 0.74, P<0.001), and year (R-2 = 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 (R-2 = 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.

Keywords

amino acids; corn quality; fatty acids; irrigation; nitrogen; starch

Published in

Journal of Cereal Science
2022, volume: 103, article number: 103388

Authors' information

Jahangirlou, Maryam Rahimi (Jahangirlou, Maryam Rahimi)
University of Tehran
Akbari, Gholam Abbas
University of Tehran
Alahdadi, Iraj
University of Tehran
Soufizadeh, Saeid
Shahid Beheshti University
Ludemann, Cameron
Wageningen University and Research
Swedish University of Agricultural Sciences, Department of Agricultural Research for Northern Sweden

UKÄ Subject classification

Genetics and Breeding
Agricultural Science

Publication Identifiers

DOI: https://doi.org/10.1016/j.jcs.2021.103388

URI (permanent link to this page)

https://res.slu.se/id/publ/114994