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上海软米品种品质性状分析与评价
引用本文:李茂柏,王萃,顾玉龙,李刚,王冬兰,余飞宇.上海软米品种品质性状分析与评价[J].中国稻米,2021,27(2):77-79.
作者姓名:李茂柏  王萃  顾玉龙  李刚  王冬兰  余飞宇
作者单位:1.上海市种子管理总站,上海 201103;2.光明米业(集团)有限公司农业技术中心,上海202171;3.上海市农业技术推广服务中心,上海 201103
基金项目:上海市水稻产业技术体系建设[沪农科产字(2019)第3号]
摘    要:以上海近年推广种植的8个软米品种为试验材料,对稻米品质进行了相关性分析和主成分分析。结果表明,8个软米品种均未达到部颁优质稻米标准,主要是因为透明度、胶稠度、直链淀粉含量3项指标未达到部颁优质米标准。各性状相关性分析复杂,整精米率与粒长呈极显著负相关,糙米率和碱消值呈显著负相关,胶稠度与蛋白质含量成显著负相关。主成分分析发现,前3个主成分累计贡献率达82.795%,整精米率、糙米率、垩白度、胶稠度、碱消值为最有代表性的品质指标。

关 键 词:软米  品质  相关分析  主成分分析  
收稿时间:2020-11-17

Analysis and Evaluation of Quality Characters of Soft Rice in Shanghai
Maobai LI,Cui WANG,Yulong GU,Gang LI,Donglan WANG,Feiyu YU.Analysis and Evaluation of Quality Characters of Soft Rice in Shanghai[J].China Rice,2021,27(2):77-79.
Authors:Maobai LI  Cui WANG  Yulong GU  Gang LI  Donglan WANG  Feiyu YU
Institution:1.Shanghai Seed Management Station, Shanghai 201103, China;2.Agricultural Technology Center of Bright Rice(Group)Limited Company, Shanghai 202171, China;3.Shanghai Agricultural Technology Extension and Service Center, Shanghai 201103, China
Abstract:Through principle component analysis and correlation analysis, the quality characters of eight soft rice varieties popularized in Shanghai in recent years were tested and analyzed. The results showed that none of the eight soft rice varieties reaching the standards of fine quality rice issued by the Ministry of Agriculture and Rural Affairs of China, mainly because the three indicators of the improper transparency, gel consistency and amylose content failed to meet the high-quality rice standards. There were complicated correlations between grain quality traits. There was a very significant negative correlation between the head rice rate and grain length. There was significant negative correlation between brown rice rate and alkali spreading value, gel consistency and protein content. It was found that the cumulative contribution rate of the first three principal components reached 82.795%, and the whole rice rate, brown rice rate, chalkiness degree, gel consistency and alkali spreading value were the most representative quality indicators by principal component analysis.
Keywords:soft rice  quality  correlation analysis  principle component analysis  
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