基于PCA方法的夏玉米穗部性状综合评价  

Application of Principal Component Analysis in Comprehensive Evaluation of Summer Maize Ear Characters

作　　者：赵玉坤[1] 高根来[1] 田玮玮[2] 王向东[1] 甄胜虎[1] 

机构地区：[1]山西省农业科学院小麦研究所,山西临汾041000 [2]安泽县农业局,山西安泽042500

出　　处：《农学学报》2015年第3期20-25,共6页Journal of Agriculture

基　　金：山西省农科院育种工程"优质多抗中早熟玉米新品种选育"(11YZGC055)

摘　　要：为了探究不同年际间夏玉米穗部多性状统计数据的内在关联规律，以晋南地区品比圃鉴定2个玉米对照品种和7个杂交组合为研究对象，调查2011—2013年3年间11个玉米穗部性状因子的数据，通过主成分分析，提取3-4个主成分，评价各杂交组合在穗部性状上的数量差异。结果表明，不同年际间提取的各主成分侧重反应的穗部性状分量各有不同，但在分别构建主成分评价函数后，主成分评价得分表现相似的变化趋势；与对照品种（‘郑单958’、‘先玉335’）相比，杂交组合PB6和PB7综合主成分得分较高，表现出优异的综合穗部性状信息，存在一定的增产潜力。因此，可将主成分分析作为玉米常规育种的辅助数据分析手段，提高育种效率。In order to explore the inner associated rules of maize ear characters’statistical data under different years, eleven ear traits data of two maize breeds and seven maize combinations were surveyed in southern Shanxi from 2011 to 2013, which was for comparing quantity variance in maize hybridized combination. In order to complete data analysis, we extracted 3-4 principal components through principal component analysis. The result showed ear traits vectors reflected by principal components were not alike in different years. The principal component scoring presented a similar trend in different years which was inferred from principal component evaluation function calculation. PB6, PB7 had higher principal component scoring values and better comprehensive ear traits performance in contrast with the control group （‘Zhengdan958’,‘Xianyu335 ’）, it also mean higher yield potentialities. Therefore, principal component analysis （PCA） could serve as an auxiliary data analysis method in maize conventional breeding and improve breeding efficiency.

关 键 词：主成分分析 穗部性状 评价函数 

分 类 号：S513.01[农业科学—作物学]