PDF《双标图分析在农作物品种多点试验中的应用》

作物学报 ACTA AGRONOMICA SINICA 2010, 36(11): 1805?1819 http://www.

chinacrops.org/zwxb/ ISSN 0496-3490;

CODEN TSHPA9 E-mail: xbzw@chinajournal.net.cn 作者联系方式: E-mail: weikai.yan@agr.gc.ca Received(收稿日期): 2010-03-29;

Accepted(接受日期): 2010-08-09. DOI: 10.3724/SP.J.1006.2010.01805 双标图分析在农作物品种多点试验中的应用 严威凯 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 Optimal Use of Biplots in Analysis of Multi-Location Variety Test Data YAN Wei-Kai 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 understand- ing 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 de- lineation;

(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

1 问题的提出 1.1 多点试验数据分析的三大目标 农作物多点试验(或区域试验)是最基础、最常 用的农业试验.每年、每个省区市、每个育种单位 及种子公司都要对各种作物进行品种多点试验, 为 品种的选育、审定和推荐提供依据.多点试验之所 以必要是因为品种与环境之间存在着相互作用(GE), 即品种的排名因环境或试验点的不同而变化.由于 同一原因, 多点试验数据的分析也成为植物育种和 品种推广的重要组成部分.多点试验数据通常包括 多个性状(产量、品质、病虫害抗性、农艺性状等) 的数据, 本文中以产量数据为例.