Evaluation of the Kernel Test Weight and Selection of Identification Indexes of Maize Inbred Lines
文献类型： 外文期刊
作者： Shen, Tao 1 ; Li, Jianping 1 ; Wang, Chao 2 ; Fan, Haihong 1 ; Zheng, Yunxiao 2 ; Liu, Yifan 1 ; Zhang, Shuzhen 4 ; Zhu, Liying 1 ; Jia, Xiaoyan 1 ; Zhao, Yongfeng 1 ; Song, Wei 6 ; Guo, Jinjie 1 ;
作者机构： 1.Hebei Agr Univ, Hebei Sub Ctr Natl Maize Improvement Ctr China, State Key Lab North China Crop Improvement & Regul, Educ Minist,Coll Agron,North China Key Lab Crop Ge, Baoding 071051, Peoples R China
2.China Agr Univ, Natl Maize Improvement Ctr, Dept Plant Genet & Breeding, State Key Lab Maize Biobreeding, Beijing 100107, Peoples R China
3.Chinese Acad Agr Sci, Inst Crop Sci, Key Lab Crop Physiol & Ecol, Minist Agr & Rural Affairs, Beijing 100081, Peoples R China
4.Hengshui Taocheng Dist Agr Technol Extens Ctr, Hengshui 053000, Peoples R China
5.Hengshui Taocheng Dist Agr & Rural Bur, Hengshui 053000, Peoples R China
6.Hebei Acad Agr & Forestry Sci, Inst Cereal & Oil Crops, Key Lab Crop Genet & Breeding Hebei Prov, Shijiazhuang 050035, Peoples R China
关键词： comprehensive evaluation; PCA; cluster analysis; stepwise regression
期刊名称：AGRONOMY-BASEL （ 影响因子：3.4； 五年影响因子：3.8 ）
ISSN：
年卷期： 2025 年 15 卷 8 期
页码：
收录情况： SCI
摘要： Kernel test weight (KTW) is one of the important assessment indexes of maize quality grade and one of the important influencing factors of yield. This study analyzed 12 traits related to KTW in 321 maize inbred lines using multivariate methods. The principal component analysis (PCA) indicated that the four PCs covered 78.176% of the information of the 12 traits in 321 maize inbred lines. Cluster analysis categorized the maize lines into six groups, identifying 16 elite inbred lines with the highest KTW. A stepwise regression model for KWT evaluation was developed using four PCA traits: starch content, amylopectin content, 100-kernel weight, and kernel circumference. The findings of this study serve as a valuable reference point for the genetic improvement of maize germplasm re-sources in kernel test weight and the creation of high kernel test weight maize resources.
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