Multivariate Analysis and Evaluation of Agronomic and Quality Traits Based on Principal Components in Wheat
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National Natural Science Foundation of China(31101138);Special Funds for Basic Research(QN2012003);Special Funds for Talents in Northwest A&F University(2010BSJJ033);Modern Agro-industry Technology Research System(CARS-3-2-47)

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    Abstract:

    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.

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History
  • Received:April 26,2013
  • Revised:July 22,2013
  • Adopted:November 13,2013
  • Online: December 26,2013
  • Published:
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