山西农业科学2025，Vol.53Issue(5)：1-7,7.DOI:10.26942/j.cnki.issn.1002-2481.2025.05.01
基于全基因组选择预测玉米籽粒含水率
Prediction of Maize Grain Moisture Content Using Genomic Selection
摘要
Abstract
Maize,as an important food crop in China,plays a vital role in ensuring food security.The grain moisture content(GMC)at maturity is a key indicator for mechanical grain harvesting of maize.Breeding maize varieties with low GMC at maturity has become a central focus of current breeding programs.GMC is controlled by complex quantitative traits,and it is inefficient to rely solely on phenotypic selection.Genomic selection(GS)enables rapid screening and improvement of complex quantitative traits.In this study,the GMC of 250 maize hybrid varieties was identified at two locations,Xinzhou and Yuci,genomic selection analysis was conducted in combination with genotype data using 9 GS models.The results showed that an average GMC of maize hybrid varieties tested was 21.51%,with a coefficient of variation of 5.31%,broad-sense heritability of 0.41,and a σ2SCA/σ2GCA ratio of 0.20,indicating that the trait was mainly controlled by additive effects.The GS analysis revealed that the average prediction accuracy of the 9 GS models was 0.592.Among them,four models such as rrBLUP,RKHS,BayesC,and SVM models had higher prediction accuracy,with values of 0.600,while the LASSO model had the lowest prediction accuracy of 0.572.When the marker density was 2 000 and the training population size was 70%,the prediction accuracy reached a higher level.Based on this,using the rrBLUP model,the GMC of 4 700 maize hybrids was predicted.The results showed that the average GMC of the top 100 hybrids was 22.63%,while the bottom 100 hybrids had an average GMC of 18.56%.If breeding were conducted on the bottom 100 hybrids based on GMC predictions,the GMC would decrease by 4.08 compared to the top 100,resulting in a 17.98%gain.关键词
玉米/复杂数量性状/籽粒含水率/全基因组选择分析/标记密度/预测准确度Key words
maize/complex quantitative traits/grain moisture content/genomic selection analysis/marker density/predic-tion accuracy分类
农业科技引用本文复制引用
董春林,张利,李昊洋,宋莹璐,张鹏艳,张正,卜华虎,常建忠..基于全基因组选择预测玉米籽粒含水率[J].山西农业科学,2025,53(5):1-7,7.基金项目
山西农业大学生物育种工程(YZGC146) （YZGC146）
中央引导地方科技发展资金项目(YDZJSX20231C018) （YDZJSX20231C018）
山西省重点研发计划(202302140601018-2) （202302140601018-2）
山西省现代农业产业技术体系建设专项(2025CYJSTX01-09) （2025CYJSTX01-09）
