【Objective】Comprehensive evaluation on peanut quality traits of the main can provide the basis for peanut quality breeding and production. 【Method】Principal component analysis and cluster analysis on peanut quality traits such as oil content, protein, oleic acid, linoleic acid, O / L, by using DPSS software.【Result】The result of Principal Component Analysis showed that the 10 traits were consolidated into four principal components independent representing 80.73% of the original information; 51 peanut varieties were divided into six categories through cluster analysis, and there was a wide genetic distance and quality between each categories.【Concussion】It is an effective way to comprehensively evaluate the peanut quality by Principal Component Analysis and Cluster Analysis, which not only could avoid the bias and the instability of single factor analysis, but also explores a practical distinction way for the peanut quality analysis and the quality breeding.