小麦农艺性状与品质特性的多元分析与评价

估算96个小麦品种(系)的11个农艺性状和10个品质特性参数的主成分,并以主成分和欧氏距离为基础,分别作二维排序分析和聚类分析。农艺性状的前4个主成分反映了85.3450%的原始数据信息量;品质特性的前4个主成分代表了89.1483%的原始数据信息量。以96个材料的主成分得分绘制二维排序图,27个小麦品种(系)表现为矮秆、子粒和旗叶较大,丰产性较好、综合农艺性状优良;32个小麦品种(系)表现为铁、锌含量较高,加工品质较好、综合品质特性优良。在系统聚类图中,农艺性状和品质特性分别被聚成5类。综合农艺性状较好的材料主要集中在第Ⅲ类和第Ⅳ类;综合品质特性较好的材料主要集中在第Ⅰ类和第Ⅱ类。综合分析发现,同时兼顾丰产性较好且子粒铁、锌含量较高,品质特性较好的小麦品种(系)有:泰山9818、西农822、轮选719、杨-31、西安837和中育9383。将聚类分析和二维排序分析结合起来,能较好的对小麦的性状组成做出综合评价,鉴定和评价出优质、高产、综合性状优良的小麦品种(系),为小麦遗传育种提供优良的种质资源,为合理选配亲本提供参考。

Multivariate Analysis and Evaluation of Agronomic and Quality Traits Based on Principal Components in Wheat

The agronomic traits and quality traits of 96 wheat cultivars were investigated, and further principal component analysis (PCA) of those traits were analyzed. The first four components from the 11 studied agronomic traits and 10 quality traits explained 85.35% and 89.15% of total variation, respectively. Based on the scatter plot of largest four principal (PC) , 27 cultivars are dwarf, relative-large grain and flag leaf which characterizes excellent comprehensive agronomic traits, 32 ones with high iron and zinc content show potentiality for excellent processing quality and rheological property. Cluster analysis classified all tested materials into five groups, most cultivars with excellent agronomic traits were mainly concentrated in group III and group IV, those with high quality traits were in Group I and group II. Notably, Taishan9818, Xinong822, Lunxuan719, Yang-31, Xian837 and Zhongyu9383 show either high agronomic or quality characteristics. In general, Cluster analysis and scatter plot based on PCs analysis together can make good comprehensive evaluation on wheat traits. Moreover, possibly identify wheat varieties with potential good comprehensive characters, which provides good theoretical guidance for the reasonable selection of germplasm resources for further wheat breeding.