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黄淮海夏大豆品种(系)主要农艺性状的综合性分析
引用本文:常世豪,杨青春,舒文涛,李金花,李琼,张保亮,张东辉,耿臻.黄淮海夏大豆品种(系)主要农艺性状的综合性分析[J].作物杂志,2020,36(3):66-6.
作者姓名:常世豪  杨青春  舒文涛  李金花  李琼  张保亮  张东辉  耿臻
作者单位:周口市农业科学院,466001,河南周口
基金项目:国家重点研发计划(2017YFD0101406)
摘    要:以2018年黄淮海区试60个夏大豆参试品种(系)为材料,对12个主要农艺性状进行综合性分析。统计分析结果显示: 中组平均产量最高,南组平均粗蛋白含量最高;有效分枝数的变异系数最高,生育期的变异系数最低。相关性分析结果显示: 产量与单株有效荚数、单株粒数呈显著正相关,与单株粒重呈极显著正相关,与主茎节数呈显著负相关;百粒重与株高、主茎节数呈显著负相关,与单株有效荚数、单株粒数呈极显著负相关;粗蛋白含量与粗脂肪含量呈极显著负相关。主成分分析结果显示: 12个主要农艺性状被提取到4个主成分,累计贡献率达76.78%。聚类分析结果显示: 60个品种(系)被分为2大类,每类又分为2个亚群,但60个品种(系)未按照北组、中组和南组的地域而区分开,说明黄淮海区域大豆品种(系)遗传背景相似。

关 键 词:大豆  农艺性状  主成分分析  聚类分析  
收稿时间:2019-12-13

Comprehensive Analysis of Main Agronomic Traits of Summer Sowing Soybean Varieties(Lines) in Huang-Huai-Hai Region
Chang Shihao,Yang Qingchun,Shu Wentao,Li Jinhua,Li Qiong,Zhang Baoliang,Zhang Donghui,Geng Zhen.Comprehensive Analysis of Main Agronomic Traits of Summer Sowing Soybean Varieties(Lines) in Huang-Huai-Hai Region[J].Crops,2020,36(3):66-6.
Authors:Chang Shihao  Yang Qingchun  Shu Wentao  Li Jinhua  Li Qiong  Zhang Baoliang  Zhang Donghui  Geng Zhen
Institution:Zhoukou Academy of Agricultural Sciences, Zhoukou 466001, Henan, China
Abstract:A total of 12 important agronomic traits from the 60 summer sowing soybean varieties (lines) was tested in Huang-Huai-Hai region. The result of the statistical analysis showed that the average yield and the crude protein content of middle group varieties (lines) was the highest. The coefficient of variation of effective branch number was the highest and the coefficient of variation of growth period was the lowest. The results of the correlation analysis showed that yield had extremely significant positive correlation with effective pod number per plant, seed number per plant and seed weight per plant, but negative correlation with number of the main stem nodes. The 100-seed weight had a negative correlation with plant height, number of the main stem nodes, effective pod number per plant and seed number per plant. The crude protein content was negatively corelated with crude fat content. The result of principal component analysis showed that 12 important agronomic traits were extracted into 4 principal components and their cumulative contribution rate was 76.78%. The result of cluster analysis showed that the 60 varieties (lines) were divided into 2 groups, and each group was divided into 2 subgroups. The 60 varieties (lines) were not distinguishable due to the region of the north, middle and south group, indicated that the genetic backgrounds of soybean varieties (lines) in the Huang-Huai-Hai region were similar.
Keywords:Soybean  Agronomic trait  Principal component analysis  Cluster analysis  
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