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双标图分析在农作物品种多点试验中的应用
引用本文:严威凯.双标图分析在农作物品种多点试验中的应用[J].作物学报,2010,36(11):1805-1819.
作者姓名:严威凯
作者单位:Eastern Cereal and Oilseed Research Centre (ECORC), Agriculture and Agri-Food Canada (AAFC), Neatby Building, 960 Carling Ave., Ottawa, Ontario, Canada, K1A 0C6
摘    要:双标图分析越来越多地被用于直观分析农作物品种多点试验数据和其他类型的两向数据。这种方法深受植物育种家和农业研究人员的推崇, 认为它可以提高研究者理解和驾驭试验数据的能力;但也受到一些学者的批评, 认为它是统计分析方面的旁门左道。事实上,学术界对什么是双标图的认识尚存混乱。一些双标图的使用者并不总能正确地选择和解释双标图。一些双标图的批评者对双标图分析及其研究对象也缺乏深入了解。为使研究者对双标图分析有一个客观全面的认识, 本文就用双标图分析农作物品种多点试验中的几个问题进行阐述:(1) 如何针对特定的研究目的选择适当的双标图; (2) 如何选择适当的GGE双标图来分析多点试验数据; (3) 如何使用GGE双标图的不同功能形态进行品种评价、试验点评价和品种生态区划分; (4) 如何判断双标图是否充分表现试验数据中的规律; (5) 如何检验双标图显示的结果是否显著。

关 键 词:双标图  品种-环境互作  品种评价  试验点评价  品种生态区划分  
收稿时间:2010-03-29

Optimal Use of Biplots in Analysis of Multi-Location Variety Test Data
YAN Wei-Kai.Optimal Use of Biplots in Analysis of Multi-Location Variety Test Data[J].Acta Agronomica Sinica,2010,36(11):1805-1819.
Authors:YAN Wei-Kai
Institution:Eastern Cereal and Oilseed Research Centre (ECORC), Agriculture and Agri-Food Canada (AAFC), Neatby Building, 960 Carling Ave., Ottawa, Ontario, Canada, K1A 0C6 
Abstract:Biplot analysis has been increasingly used in visual analysis of genotype-by-environment data and other types of two-way data. While many plant breeders and agricultural researchers are enthusiastic about the capacity of biplot analysis in helping them to understand their research data, some statisticians consider the use of biplots as a sidetrack to genotype-by-environment interaction analyses. Confusion also exists among statisticians on what is or is not a biplot. Admittedly, some users of biplot analysis are not always clear on how to select a proper type of biplot for a particular research objective and how to interpret a biplot correctly, accurately, and adequately. Some criticisms of biplot analysis may arise from incomplete understanding of the practitioners’ research problems as well as of the biplot methodology. In this review, I summarize the experiences and understanding in biplot analysis of genotype-by-environment data achieved during the last decade and discuss the following issues: (1) how to choose a proper biplot; (2) how to choose a proper GGE (genotype + genotype-by-environment interaction) biplot; (3) how to use the key functions of a GGE biplot for genotype evaluation, test-environment evaluation, and mega-environment delineation; (4) how to judge the adequacy of a 2-D biplot; and (5) how to test the statistical significance of a biplot pattern.
Keywords:Biplot  Genotype-by-environment interaction  Genotype evaluation  Test-environment evaluation  Mega-environment delineation
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