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Evaluation of the lodging resistance and the selection of identification indexes of maize inbred lines

文献类型： 外文期刊

作者： Zheng, Yunxiao 1 ; Hou, Peng 3 ; Jia, Xiaoyan 1 ; Zhu, Liying 1 ; Zhao, Yongfeng 1 ; Song, Weibin 2 ; Song, Wei 4 ; Guo, Jinjie 1 ;

作者机构： 1.Hebei Agr Univ, Natl Maize Improvement Ctr China, North China Key Lab Crop Germplasm Resources Educ, Hebei Subctr,Coll Agron,State Key Lab North China, Baoding 071001, Hebei, Peoples R China

2.China Agr Univ, Natl Maize Improvement Ctr, Dept Plant Genet & Breeding, State Key Lab Maize Biobreeding, Beijing, Peoples R China

3.Chinese Acad Agr Sci, Key Lab Crop Physiol & Ecol, Minist Agr & Rural Affairs, Inst Crop Sci, Beijing, Peoples R China

4.Hebei Acad Agr & Forestry Sci, Inst Cereal & Oil Crops, Key Lab Crop Genet & Breeding Hebei Prov, Shijiazhuang 050035, Hebei, Peoples R China

关键词： cluster analysis; comprehensive evaluation; lodging resistance; maize; principal component analysis

期刊名称：FOOD AND ENERGY SECURITY （ 影响因子：4.5； 五年影响因子：5.4 ）

ISSN： 2048-3694

年卷期： 2023 年 12 卷 5 期

页码：

收录情况： SCI

摘要： Lodging is one of the main problems affecting the maize production. In this study, 220 maize inbred lines were used for determining the lodging resistance. Analysis methods such as the correlation analysis, the principal component analysis, the cluster analysis, the stepwise discriminate analysis, and the ridge regression analysis were deployed for data interpretation. The results of the correlation analysis showed that 17 characters were correlated with varying degrees. Strong and positive correlations between TID and FID (r=0.910), TIL and FIL (r=0.898), NSVB and NLVB (r=0.775), ASVB and ALVB (r=0.746), and LC and HC (r=0.656) were observed. The first six principal components explained 79.13% of the phenotypic variation of the 17 characters, with the contribution rates being 20.77%, 18.12%, 14.09%, 11.17%, 8.66%, and 6.32%, respectively. Five categories were clustered in the 220 inbred lines. The result of stepwise discriminate analysis showed that 211 inbred lines were correctly discriminated and the identification rate was 95.91%, and 9 inbred lines were incorrectly discriminated and the identification rate was 4.09%, which meant that the result of cluster analysis was accurate and reliable. The stalk bending strength, ear height, cellulose content, number of small vascular bundles, and cross-sectional area were selected, and the regression model of lodging resistance of inbred lines was established by using the ridge regression method. Thirty of the 220 inbred lines, including R1656, 4003, and LD61, showed the highest lodging resistance. The results provide a reference for the selection of lodging-resistant germplasm resources in breeding for the lodging resistance hybrids.

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