基于非线性主成分分析的绿色超级稻品种综合评价
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  • 英文篇名:Comprehensive evaluation of green super rice varieties based on nonlinear principal component analysis
  • 作者:纪龙 ; 申红芳 ; 徐春春 ; 陈中督 ; 方福平
  • 英文作者:JI Long;SHEN Hong-Fang;XU Chun-Chun;CHEN Zhong-Du;FANG Fu-Ping;China National Rice Research Institute;
  • 关键词:绿色超级稻 ; 综合评价 ; 指标体系 ; 非线性主成分分析
  • 英文关键词:green super rice;;comprehensive evaluation;;index system;;nonlinear principal component analysis
  • 中文刊名:XBZW
  • 英文刊名:Acta Agronomica Sinica
  • 机构:中国水稻研究所;
  • 出版日期:2019-04-23 16:15
  • 出版单位:作物学报
  • 年:2019
  • 期:v.45
  • 基金:国家高技术研究发展计划项目(2014AA10A605);; 浙江省自然科学基金青年基金项目(LQ18G030013);; 财政部-农业部基本科研业务费项目(2017RG007)资助~~
  • 语种:中文;
  • 页:XBZW201907003
  • 页数:11
  • CN:07
  • ISSN:11-1809/S
  • 分类号:18-28
摘要
应用绿色超级稻被认为是推动水稻生产可持续发展的重要途径之一,已成为全球水稻育种的主要目标。目前关于绿色超级稻品种综合评价的研究鲜有报道。本文围绕"少打农药、少施化肥、节水抗旱、优质高产"的理念,从技术性、经济性、生态性和社会性4个维度构建了绿色超级稻品种综合评价指标体系,为水稻及其他作物品种的综合评价、品种选育及推广应用提供了有益的研究思路。在此基础上引入一种非线性主成分分析法——对数主成分分析,利用大田试验数据及不同评价方法的对比分析表明,对数主成分分析法符合绿色超级稻的育种理念,具有较强的合理性,可作为一种有效的水稻品种综合评价方法。
        Application of green super rice(GSR) is regarded as one of the important ways to realize sustainable development of rice production, and has become a major goal of the rice breeding around the world. However, there are few literatures on comprehensive evaluation of GSR varieties. The GSR concept is the development of varieties with insect and disease resistance, high N-and P-use efficiency, drought resistance, high grain yield and superior quality. Based on the GSR concept, we establish a comprehensive evaluation index system of GSR varieties in four dimensions, including technical indicators, economic indicators,ecological indicators and social indicators. This index system should shed light on a new perspective for evaluation of crop varieties, variety breeding as well as the application and extension of new crop varieties. Further, a nonlinear principal component analysis, namely logarithmic principal component analysis, was introduced into the comprehensive evaluation of GSR varieties.Based on field experimental data with a comparative analysis by different methods, we revealed that the logarithmic principal component analysis is feasible and reasonable for comprehensive evaluation of GSR varieties.
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