摘要
为研究不同水稻品种综合品质的差异,以来源于黑龙江的11个水稻品种和来源于日本的7个水稻品种为研究对象,以糙米率等作为品质评价指标,在主成分分析基础上,利用隶属函数法对18个水稻品种进行品质评价,同时利用聚类分析法将其归类。结果表明:龙粳39、空育131和牡丹江32三个水稻品种在加工品质方面优于其他品种,爱知旭水稻在外观品质上最好,绥粳18号、松粳9号和早熟青森3个水稻品种在直链淀粉含量和食味评分方面优于其他品种。隶属函数法评价出18个水稻品种品质优劣顺序:龙粳39、牡丹江32、空育131、垦粳8号、早熟青森、龙粳36、爱知旭、绥粳18号、松粳9号、星之梦、垦粳6号、龙庆稻1号、新月光、龙庆稻3号、上育418、龙庆稻2号、龙粳43、富士光。聚类分析结果将18个水稻品种品质聚为3大类,第I类包括龙粳39,其品质最好,第II类包括牡丹江32、空育131、垦粳8号、早熟青森、龙粳36、爱知旭、绥粳18号、松粳9号、星之梦、垦粳6号、龙庆稻1号、新月光、龙庆稻3号、上育418、龙庆稻2号、龙粳43,其品质居中,第Ⅲ类包括富士光,其品质最差。
s: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.
作者
荆瑞勇
卫佳琪
王丽艳
宋维民
郑桂萍
郭永霞
JING Ruiyong;WEI Jiaqi;WANG Liyan;SONG Weimin;ZHENG Guiping;GUO Yongxia(College of Life Science and Technology,Heilongjiang Bayi Agricultural University,Daqing 163319,China;College of Agronomy,Heilongjiang Bayi Agricultural Univeristy,Daqing 163319,China)
出处
《食品科学》
EI
CAS
CSCD
北大核心
2020年第24期179-184,共6页
Food Science
基金
“十三五”国家重点研发计划重点专项(2018YFD0300104)
国家自然科学基金面上项目(31870477)
黑龙江省博士后资助项目(LBH-Z15189)
黑龙江省自然科学基金面上项目(2018046)
校博士启动基金项目(XDB2014-13)。
关键词
水稻
品质评价
主成分分析
隶属函数
聚类分析
rice
quality evaluation
principal component analysis
subordinate function
cluster analysis
