Principal component analysis and fuzzy clustering on drought-tolerance related traits of foxtail millet (Setaria italica).

【Objective】 The main purpose of this paper was to explore the methods of drought tolerance evaluation,and to evaluate the relationships between some agronomic traits and physiological indicators with drought-tolerance in foxtail millet(Setaria italica).【Method】 Principal Component Analysis(PCA) and Fuzzy Clustering(FC) were used to evaluate the drought tolerance of 16 foxtail millet cultivars based on their performance under the conditions of rainfed and water limited cultivation under rainout shelter.【Result】 The result of Principal Component Analysis indicated that 6 principal components could present 90.71% information of the raw data of the traits related to drought tolerance of foxtail millet.The 16 cultivars used in this study could be divided into 3 clusters by Fuzzy Clustering based on their Drought-tolerance Value(DV),which could reflect the drought characteristics of the origins and planting areas of those cultivars.Among those cultivars,the drought tolerance of Jigu18 and Yugu1 were better and more stable.【Concussion】 It is an effective way to comprehensively evaluate the drought tolerance of foxtail millet by Principal Component Analysis and Fuzzy Clustering,which not only could avoid the bias and the instability of single factor analysis,but also reflect the relationship between different drought tolerance related traits and drought tolerance in foxtail millet better.