ZHENG Yun-xiao
Department of Agronomy, Agricultural University of Hebei / Hebei Sub-center of National Maize Improvement Center / Key Laboratory for Crop Germplasm of HebeiLIU Wen-si
Department of Agronomy, Agricultural University of Hebei / Hebei Sub-center of National Maize Improvement Center / Key Laboratory for Crop Germplasm of HebeiZHAO Yong-feng
Department of Agronomy, Agricultural University of Hebei / Hebei Sub-center of National Maize Improvement Center / Key Laboratory for Crop Germplasm of HebeiJIA Xiao-yan
Department of Agronomy, Agricultural University of Hebei / Hebei Sub-center of National Maize Improvement Center / Key Laboratory for Crop Germplasm of HebeiZHU Li-ying
Department of Agronomy, Agricultural University of Hebei / Hebei Sub-center of National Maize Improvement Center / Key Laboratory for Crop Germplasm of HebeiHUANG Ya-qun
Department of Agronomy, Agricultural University of Hebei / Hebei Sub-center of National Maize Improvement Center / Key Laboratory for Crop Germplasm of HebeiCHEN Jing-tang
Department of Agronomy, Agricultural University of Hebei / Hebei Sub-center of National Maize Improvement Center / Key Laboratory for Crop Germplasm of HebeiGUO Jin-jie
Department of Agronomy, Agricultural University of Hebei / Hebei Sub-center of National Maize Improvement Center / Key Laboratory for Crop Germplasm of HebeiDepartment of Agronomy, Agricultural University of Hebei / Hebei Sub-center of National Maize Improvement Center / Key Laboratory for Crop Germplasm of Hebei
The National Key Technologies R&D Program of China(2018YFD0300501)
Lodging is one of the main problems affecting the maize production and extension. In this study, 181 maize inbred lines were used for determining 22 characters associating to lodging resistance. Statistical analysis using the correlation analysis, the principal component analysis, the cluster analysis, the stepwise discriminate analysis and the ridge regression analysis was deployed for data interpretation. The results of the correlation analysis showed that 22 characters existed in varying degrees of correlation. The first seven principal components explained 74.460% of the phenotypic variation with the contribution rates of 25.700%, 12.369%, 9.782%, 8.159%, 7.782%, 5.490% and 5.177%. Four categories were clustered in the 181 maize inbred lines at a genetic distance of 3.5. Among them, the first classⅠhas 35 inbred lines, the classⅡhas 47 inbred lines, the class Ⅲ has 49 inbred lines, the class Ⅳ has 50 inbred lines. The result of stepwise discriminant analysis showed that 175 maize inbred lines were correctly discriminated and the identification rate was 96.69%. Six maize inbred lines were incorrectly discriminated and the identification rate was 3.31%, which means that the result of cluster analysis is accurate and reliable. The hemicellulose content, rind penetrometer strength, third internode length, third internode diameter, ear height and area of total vascular bundles were selected and the regression model of lodging resistance of maize inbred line was established by using the ridge regression method. 35 inbred lines, such as AHU 24, e220 and 7026B, showed the highest lodging resistance. Thus, the results provided a reference of the maize lodging resistant germplasm resources, which become valuable in selection of elite germplasm resources in breeding for the lodging resistance hybrids.