FOOD SCIENCE ›› 2020, Vol. 41 ›› Issue (24): 179-184.doi: 10.7506/spkx1002-6630-20191218-198

• Component Analysis • Previous Articles     Next Articles

Comprehensive Quality Evaluation of Different Rice Varieties Based on Principal Component Analysis

JING Ruiyong, WEI Jiaqi, WANG Liyan, SONG Weimin, ZHENG Guiping, GUO Yongxia   

  1. (1. College of Life Science and Technology, Heilongjiang Bayi Agricultural University, Daqing 163319, China; 2. College of Agronomy, Heilongjiang Bayi Agricultural Univeristy, Daqing 163319, China)
  • Online:2020-12-25 Published:2020-12-28

Abstract: In order to explore the difference in the comprehensive quality of different rice varieties, 11 rice varieties from Heilongjiang province, China and 7 rice varieties from Japan were selected for quality evaluation in terms of brown rice rate using subordinate function combined with principle component analysis (PCA). These varieties were classified by cluster analysis. The results showed that among the 18 varieties, Longjing 39, Kongyu 131 and Mudanjiang 32 had the best processing quality, the Japanese rice cultivar Aichiasahi had the best appearance quality, and Suijing 18, Songjing 9 and the Japanese early-maturing cultivar Aomori had the highest amylose content and taste values. According to subordinate function analysis, the quality of the 18 rice varieties could be?ranked?in?decreasing order as follows: Longjing 39, Mudanjiang 32, Kongyu 131, Kenjing 8, early-maturing Aomori, Longjing 36, Aichiasahi, Suijing 18, Songjing 9, Hoshinoyume, Kenjing 6, Longqingdao 1, Xinyueguang, Longqingdao 3, Shangyu 418, Longqingdao 2, Longjing 43, and Fujusu. Cluster analysis showed that these varieties were classified into three groups: Group I, with the best quality, including Longjing 39; Group II including Mudanjiang 32, Kongyu 131, Kenjing 8, early-maturing Aomori, Longjing 36, Aichiasahi, Suijing 18, Songjing 9, Hoshinoyume, Kenjing 6, Longqingdao 1, Xinyueguang, Longqingdao 3, Shangyu 418, Longqingdao 2, and Longjing 43; and Group III, with the worst quality, including Fujusu.

Key words: rice; quality evaluation; principal component analysis; subordinate function; cluster analysis

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