Evaluation of the Kernel Test Weight and Selection of Identification Indexes of Maize Inbred Lines
Year: 2025
Type: article
Abstract: 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.
Source: Agronomy
Authors: Tao Shen, Jianping Li, Chao Wang, Haihong Fan, Yunxiao Zheng, Yifan Liu, Shuzhen Zhang, Liying Zhu, Xiaoyan Jia, Yongfeng Zhao, Wei Song, Jinjie Guo
Language: English
Topic: Genetics and Plant Breeding
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $3,137
Funder: China Agricultural University
OpenAlex ID: W4412690410
