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The Application of GGE Biplot Analysis for Evaluating Test Locations and Mega-Environment Investigation of Cotton Regional Trials
  • ISSN号:1001-9332
  • 期刊名称:《应用生态学报》
  • 时间:0
  • 分类:S512.12[农业科学—作物学] X837[环境科学与工程—环境工程]
  • 作者机构:[1]Key Laboratory of Corp Growth Regulation, Ministry of Agriculture/Nanjing Agricultural University, Nanjing 210095, P.R. China, [2]Key Laboratory of Cotton and Rapeseed, Ministry of Agriculture~Institute of Industrial Crops, Jiangsu Academy of Agriculture Sciences, Nanjing 210014, P.R.China, [3]Center of International Cooperation on Agronomic Research for Development (CIRAD), TA B102/02, 34398 Montpellier Cedex 5, France
  • 相关基金:funded by the Jiangsu Agriculture Science and Technology Innovation Fund,China(CX(12)5035); the National Natural Science Foundation of China(30971735); the China Agriculture Research System(CARS-18-20); the Special Fund for Agro-Scientific Research in the Public Interest of China(Impact of Climate Change on Agriculture Production of China,200903003)
中文摘要:

In the process to the marketing of cultivars, identification of superior test locations within multi-environment variety trial schemes is of critical relevance. It is relevant to breeding organizations as well as to governmental organizations in charge of cultivar registration. Where competition among breeding companies exists, effective and fair multi-environment variety trials are of utmost importance to motivate investment in breeding. The objective of this study was to use genotype main effect plus genotype by environment interaction(GGE) biplot analysis to evaluate test locations in terms of discrimination ability, representativeness and desirability, and to investigate the presence of multiple mega-environments in cotton production in the Yangtze River Valley(YaRV), China. Four traits(cotton lint yield, fiber length, lint breaking tenacity, micronaire) and two composite selection indices were considered. It was found that the assumption of a single mega-environment in the YaRV for cotton production does not hold. The YaRV consists of three cotton mega-environments: a main one represented by 11 locations and two minor ones represented by two test locations each. This demands that the strategy of cotton variety registration or recommendation must be adjusted. GGE biplot analysis has also led to the identification of test location superior for cotton variety evaluation. Although test location desirable for selecting different traits varied greatly, Jinzhou, Hubei Province, China, was found to be desirable for selecting for all traits considered while Jianyang, Sichuan Province, China, was found to be desirable for none.

英文摘要:

In the process to the marketing of cultivars, identification of superior test locations within multi-environment variety trial schemes is of critical relevance. It is relevant to breeding organizations as well as to governmental organizations in charge of cultivar registration. Where competition among breeding companies exists, effective and fair multi-environment variety trials are of utmost importance to motivate investment in breeding. The objective of this study was to use genotype main effect plus genotype by environment interaction(GGE) biplot analysis to evaluate test locations in terms of discrimination ability, representativeness and desirability, and to investigate the presence of multiple mega-environments in cotton production in the Yangtze River Valley(YaRV), China. Four traits(cotton lint yield, fiber length, lint breaking tenacity, micronaire) and two composite selection indices were considered. It was found that the assumption of a single mega-environment in the YaRV for cotton production does not hold. The YaRV consists of three cotton mega-environments: a main one represented by 11 locations and two minor ones represented by two test locations each. This demands that the strategy of cotton variety registration or recommendation must be adjusted. GGE biplot analysis has also led to the identification of test location superior for cotton variety evaluation. Although test location desirable for selecting different traits varied greatly, Jinzhou, Hubei Province, China, was found to be desirable for selecting for all traits considered while Jianyang, Sichuan Province, China, was found to be desirable for none.

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期刊信息
  • 《应用生态学报》
  • 北大核心期刊(2011版)
  • 主管单位:中国科学院
  • 主办单位:中国生态学学会 中国科学院沈阳应用生态研究所
  • 主编:沈善敏
  • 地址:沈阳市文化路72号
  • 邮编:110016
  • 邮箱:
  • 电话:024-83970393
  • 国际标准刊号:ISSN:1001-9332
  • 国内统一刊号:ISSN:21-1253/Q
  • 邮发代号:8-98
  • 获奖情况:
  • 中国自然科学核心期刊,中国科学院优秀期刊,中国期刊方阵“双效”期刊
  • 国内外数据库收录:
  • 俄罗斯文摘杂志,美国化学文摘(网络版),荷兰地学数据库,荷兰文摘与引文数据库,美国生物医学检索系统,美国生物科学数据库,英国动物学记录,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊(2004版),中国北大核心期刊(2008版),中国北大核心期刊(2011版),中国北大核心期刊(2014版)
  • 被引量:98742