山东农业大学学报（自然科学版）Issue(4)：545-551,558,8.DOI:10.3969/j.issn.1000-2324.2014.04.012
基于主成分和聚类分析的山东省区试小麦品种（系）品质的综合评价
Comprehensive Assessment on Wheat Quality in Regional Test of Shandong Based on Principal Component and Cluster Analysis
摘要
Abstract
Based on the principal component analysis and cluster analysis, we analyzed and comprehensively evaluated the wheat quality of 297 varieties participated in the regional test of Shandong province in 2008-2009 and 2009-2010. Three principal components were extracted for evaluating the overall wheat quality. The first principal component was protein quality factor (gluten index, sedimentation value and formation time, setting time). The second principal component was milling factor (hardness index, flour yield, water absorption, whiteness). The third principal component was protein quantitative factor (moisture content and grain protein content ). The cumulative variance contribution rates of the three principal components were 77%and 82%, respectively. The contribution rate of the first principal component factors were 34.453%and 36.291%in the two years, which indicated gluten index, sedimentation value and formation time, setting time were the main factors affecting the wheat quality. From the evaluation results of 96 varieties in 2009-2010 based on principal component analysis, we found Tainong7058, Tainong05428, Taishan4173, Shannong71 and so on had high quality score, outstanding comprehensive quality traits. While integrated with contribution rates of principal components, the eigenvalues size of different indicators and maneuverability, we proposed that gluten index, sedimentation value and hardness index could evaluate the wheat quality indirectly in the early breeding program. R-type analysis clustered 10 traits into four categories (flour whiteness into a separate category), in which indicators of three traits coincided with indicators of three components in principal components. Q-type analysis clustered 96 varieties in 2009-2010 based on principal component analysis, the indicators of 6 varieties in the group-Ⅲ were high, which agreed with the results of principal component analysis. That further validated the principal component analysis could be used for comprehensive evaluation of wheat varieties (lines) quality.关键词
小麦品质/主成分分析/聚类分析/综合评价Key words
Wheat quality/principal component analysis/cluster analysis/comprehensive assessment分类
农业科技引用本文复制引用
孙彩玲,曲辉英,吕建华,田纪春,张永祥,王守义,宋雪皎..基于主成分和聚类分析的山东省区试小麦品种（系）品质的综合评价[J].山东农业大学学报（自然科学版）,2014,(4):545-551,558,8.基金项目
国家转基因生物新品种培育科技重大专项(2008ZX08002-003、2009ZX08002-017B-03) （2008ZX08002-003、2009ZX08002-017B-03）
