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| The Application of GGE Biplot Analysis for Evaluat ng Test Locations and Mega-Environment Investigation of Cotton Regional Trials |
| XU Nai-yin, Fok Michel, ZHANG Guo-wei, LI Jian , ZHOU Zhi-guo |
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 |
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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.
Abstract 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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Received: 02 August 2013
Accepted:
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| Fund: This work was 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), and the Special Fund for Agro-Scientific Research in the Public Interest of China (Impact of Climate Change on Agriculture Production of China, 200903003). |
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Corresponding Authors:
ZHOU Zhi-guo, Tel/Fax: +86-25-84396813, E-mail: giscott@njau.edu.cn
E-mail: giscott@njau.edu.cn
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| About author: XU Nai-yin, E-mail: naiyin@126.com |
Cite this article:
XU Nai-yin, Fok Michel, ZHANG Guo-wei, LI Jian , ZHOU Zhi-guo.
2014.
The Application of GGE Biplot Analysis for Evaluat ng Test Locations and Mega-Environment Investigation of Cotton Regional Trials. Journal of Integrative Agriculture, 13(9): 1921-1933.
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