Combining datasets for maize root seedling traits increases the power of GWAS and genomic prediction accuracies
Author:
Affiliation:
1. Corteva Agriscience , Rio Verde, GO , Brazil
2. Department of Agronomy, Universidade Federal de Viçosa , Viçosa, MG , Brazil
3. Department of Agronomy, Iowa State University , Ames, IA , USA
Abstract
Funder
National Institute of Food and Agriculture
Iowa State University
Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior
Publisher
Oxford University Press (OUP)
Subject
Plant Science,Physiology
Link
https://academic.oup.com/jxb/advance-article-pdf/doi/10.1093/jxb/erac236/44646283/erac236.pdf
Reference107 articles.
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2. Genetic diversity and population structure of early-maturing tropical maize inbred lines using SNP markers.;Adu;PLoS One,2019
3. Bayesian analysis and prediction of hybrid performance.;Alves;Plant Methods,2019
4. Technological advances in maize breeding: past, present and future.;Andorf;Theoretical and Applied Genetics,2019
5. Fitting linear mixed-effects models using ‘lme4’.;Bates;Journal of Statistical Software,2015
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Phenotypic and genome-wide association analyses for nitrogen use efficiency related traits in maize (Zea mays L.) exotic introgression lines;Frontiers in Plant Science;2023-10-09
2. Genomic insight into changes of root architecture under drought stress in maize;Plant, Cell & Environment;2023-02-24
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