GENOTYPE BY ENVIRONMENT INTERACTION IN COWPEA LINES USING GGE BIPLOT METHOD
DOI:
https://doi.org/10.1590/1983-21252018v31n108rcKeywords:
Vigna unguiculata. Grain yield. Adaptability and stability.Abstract
The GGE Biplot method is efficien to identify favorable genotypes and ideal environments for evaluation. Therefore, the objective of this work was to evaluate the genotype by environment interaction (G×E) and select elite lines of cowpea from genotypes, which are part of the cultivation and use value tests of the Embrapa Meio-Norte Breeding Program, for regions of the Brazilian Cerrado, by the GGE-Biplot method. The grain yield of 40 cowpea genotypes, 30 lines and 10 cultivars, was evaluated during three years (2010, 2011 and 2012) in three locations: Balsas (BAL), São Raimundo das Mangabeiras (SRM) and Primavera do Leste (PRL). The data were subjected to analysis of variance, and adjusted means were obtained to perform the GGE-Biplot analysis. The graphic results showed variation in the performance of the genotypes in the locations evaluated over the years. The performance of the lines MNC02-675F-4-9 and MNC02-675F-4-10 were considered ideal, with maximum yield and good stability in the locations evaluated. There mega-environments were formed, encompassing environments correlated positively. The lines MNC02-675F-4-9, MNC02-675F-9-3 and MNC02-701F-2 had the best performance within each mega-environment. The environment PRL10 and lines near this environment, such as MNC02-677F-2, MNC02-677F-5 and the control cultivar (BRS-Marataoã) could be classified as those of greater reliability, determined basically by the genotypic effects, with reduced G×E. Most of the environments evaluated were ideal for evaluation of G×E, since the genotypes were well discriminated on them. Therefore, the selection of genotypes with adaptability and superior performance for specific environments through the GGE-Biplot analysis was possible.Downloads
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References
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BARROS, M. A. et al. Adaptabilidade e estabilidade produtiva de feijão-caupi de porte semiprostrado. Pesquisa Agropecuária Brasileira, Brasília, v. 48, n. 4, p. 403-410, 2013.
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FRUTOS, E.; GALINDO, M. P.; LEIVA, V. An interactive biplot implementation in R for modeling genotype-by-environment interaction. Stochastic Environmental Research and Risk Assessment, v. 28, n. 7, p. 1629-1641, 2014.
GAUCH, H. G. Model selection and validation for yield trials with interaction. Biometrics, Arlington, v. 44, n. 3, p. 705-715, 1988.
GAUCH, H. G. Statistical analysis of regional yield trials: AMMI analysis of factorial designs. 1. ed. Amsterdam: Elsevier, 1992. 278 p.
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HONGYU, K. et al. Comparação entre os modelos AMMI e GGE-Biplot para os dados de ensaios multi-ambientais. Revista Brasileira de Biometria, São Paulo, v. 33, n. 2, p. 139-155, 2015.
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KEMPTON, R. A. The use of biplots in interpreting variety by environment interactions. The Journal of Agricultural Science, Cambridge, v. 103, n. 1, p. 123–135, 1984.
MATTOS, P. H. C. et al. Evaluation of sugarcane genotypes and production environments in Paraná by GGE-Biplot and AMMI analysis. Crop Breeding and Applied Biotechnology, Viçosa, v. 13, n. 1, p. 83-90, 2013.
MEHARI, M. et al. GGE-Biplot analysis of genotype-by-environment interaction and grain yield stability of bread wheat genotypes in South Tigray, Ethiopia. Communications in Biometry and Crop Science, Warsaw, v. 10, n. 1, p. 17–26, 2015.
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PAGLIOSA, E. S. et al. Análise GGE-Biplot de genótipos de milho sob diferentes formas de adubação em sistema de agricultura familiar. Semina: Ciências Agrárias, Londrina, v. 36, n. 5, p. 2965-2976, 2015.
R CORE TEAM. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2015. Disponível em: <http://www.R-project.org/>. Acesso em: 14 jun. 2016.
RESENDE, M. D. V.; DUARTE, J. B. Precisão e controle de qualidade em experimentos de avaliação de cultivares. Pesquisa Agropecuária Tropical, Goiânia, v. 37, n. 3, p. 182-194, 2007.
ROCHA, M. M. et al. Adaptabilidade e estabilidade produtiva de genótipos de feijão-caupi de porte semi-ereto na região Nordeste do Brasil. Pesquisa Agropecuária Brasileira, Brasília, v. 42, n. 9, p. 1283-1289, 2007.
SANTOS, et al. Adaptability and stability of erect cowpea genotypes via REML/BLUP and GGE-Biplot. Bragantia, São Paulo, v. 75. n. 3, p. 299-306, 2016.
SHIRINGANI, R. P.; SHIMELIS, H. A. Yield response and stability among cowpea genotypes at three planting dates and test environment. African Journal of Agricultural Research, Nairobi, v. 6, n. 4, p. 3259-3263, 2011.
SILVA, R. R.; BENIN, G. Análises Biplot: conceitos, interpretações e aplicações. Ciência Rural, Santa Maria, v. 42, n. 8, p. 1404-1412, 2012.
WESTCOFF, B. A method of analysis of the yield stability of crops. Journal of Agricultural Science, Toronto, v. 108, n. 1, p. 267–274, 1987.
YAN, W. et al. Cultivar evaluation and mega environment investigation based on GGE-Biplot. Crop Science, Madison, v. 40, n. 3, p. 597-605, 2000.
YAN, W. GGE-Biplot vs. AMMI Graphs for Genotype-by-Environment Data Analysis. Journal of the India Society of Agricultural Statistics, New Delhi, v. 65, n. 2, p. 181-193, 2011.
YAN, W.; TINKER, N. A. Biplot analysis of multienvironment trial data: Principles and applications. Canadian Journal of Plant Science, Ottawa, v. 83, n. 6, p. 623-645, 2006.
YANG, R. C. et al. Biplot analysis of genotype × environment interaction: proceed with caution. Crop Science, Madison, v. 49, n. 5, p. 1564-1576, 2009.
ALWALA, S. et al. A comprehensive comparison between Eberhart and Russel joint regression and GGE-Biplot analyses to identify stable and high yielding maize hybrids. Field Crops Research, Amsterdam, v. 119, n. 2-3, p. 225-230, 2010.
BARROS, M. A. et al. Adaptabilidade e estabilidade produtiva de feijão-caupi de porte semiprostrado. Pesquisa Agropecuária Brasileira, Brasília, v. 48, n. 4, p. 403-410, 2013.
CRUZ, C. D. Princípios de Genética Quantitativa. 1. ed. Viçosa, MG: UFV, 2010. 394 p.
FREIRE FILHO, F. R. et al. Feijão-caupi: produção, melhoramento genético, avanços e desafios. Brasília, DF: Embrapa Informação Tecnológica, 2011. 81 p.
FRUTOS, E.; GALINDO, M. P.; LEIVA, V. An interactive biplot implementation in R for modeling genotype-by-environment interaction. Stochastic Environmental Research and Risk Assessment, v. 28, n. 7, p. 1629-1641, 2014.
GAUCH, H. G. Model selection and validation for yield trials with interaction. Biometrics, Arlington, v. 44, n. 3, p. 705-715, 1988.
GAUCH, H. G. Statistical analysis of regional yield trials: AMMI analysis of factorial designs. 1. ed. Amsterdam: Elsevier, 1992. 278 p.
GAUCH, H. G.; PIEPHO, H. P.; ANNICCHIARICO, P. Statistical analysis of yield trials by AMMI and GGE: Further considerations. Crop Science, Madison, v. 48, n. 3, p. 866-889, 2008.
HONGYU, K. et al. Comparação entre os modelos AMMI e GGE-Biplot para os dados de ensaios multi-ambientais. Revista Brasileira de Biometria, São Paulo, v. 33, n. 2, p. 139-155, 2015.
KAYA, Y. M.; AKÇURA, T. S. GGE-Biplot analysis of multienvironment yield trials in bread wheat. Turkish Journal of Agriculture and Forestry, Tübitak, v. 30, n. 5, p. 325-337, 2006.
KEMPTON, R. A. The use of biplots in interpreting variety by environment interactions. The Journal of Agricultural Science, Cambridge, v. 103, n. 1, p. 123–135, 1984.
MATTOS, P. H. C. et al. Evaluation of sugarcane genotypes and production environments in Paraná by GGE-Biplot and AMMI analysis. Crop Breeding and Applied Biotechnology, Viçosa, v. 13, n. 1, p. 83-90, 2013.
MEHARI, M. et al. GGE-Biplot analysis of genotype-by-environment interaction and grain yield stability of bread wheat genotypes in South Tigray, Ethiopia. Communications in Biometry and Crop Science, Warsaw, v. 10, n. 1, p. 17–26, 2015.
MOHAMMADI, R.; AMRI, A. Genotype×environment interaction and genetic improvement for yield and yield stability of rainfed durum wheat in Iran. Euphytica, Wageningen, v. 192, n. 3, p. 227–249, 2013.
NUNES, H. F. et al. Grain yield adaptability and stability of blackeyed cowpea genotypes under rainfed agriculture in Brazil. African Journal of Agricultural Research, Nairobi, v. 9, n. 2, p. 255-261, 2014.
OLAYIWOLA, M. O.; SOREMI, P. A. S.; OKELEYE, K. A. Evaluation of some cowpea [Vigna unguiculata (L.) Walp.] genotypes for stability of performance over 4 years. Current Research in Agricultural Sciences, v. 2, n. 1, p. 22- 30, 2015.
PAGLIOSA, E. S. et al. Análise GGE-Biplot de genótipos de milho sob diferentes formas de adubação em sistema de agricultura familiar. Semina: Ciências Agrárias, Londrina, v. 36, n. 5, p. 2965-2976, 2015.
R CORE TEAM. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2015. Disponível em: <http://www.R-project.org/>. Acesso em: 14 jun. 2016.
RESENDE, M. D. V.; DUARTE, J. B. Precisão e controle de qualidade em experimentos de avaliação de cultivares. Pesquisa Agropecuária Tropical, Goiânia, v. 37, n. 3, p. 182-194, 2007.
ROCHA, M. M. et al. Adaptabilidade e estabilidade produtiva de genótipos de feijão-caupi de porte semi-ereto na região Nordeste do Brasil. Pesquisa Agropecuária Brasileira, Brasília, v. 42, n. 9, p. 1283-1289, 2007.
SANTOS, et al. Adaptability and stability of erect cowpea genotypes via REML/BLUP and GGE-Biplot. Bragantia, São Paulo, v. 75. n. 3, p. 299-306, 2016.
SHIRINGANI, R. P.; SHIMELIS, H. A. Yield response and stability among cowpea genotypes at three planting dates and test environment. African Journal of Agricultural Research, Nairobi, v. 6, n. 4, p. 3259-3263, 2011.
SILVA, R. R.; BENIN, G. Análises Biplot: conceitos, interpretações e aplicações. Ciência Rural, Santa Maria, v. 42, n. 8, p. 1404-1412, 2012.
WESTCOFF, B. A method of analysis of the yield stability of crops. Journal of Agricultural Science, Toronto, v. 108, n. 1, p. 267–274, 1987.
YAN, W. et al. Cultivar evaluation and mega environment investigation based on GGE-Biplot. Crop Science, Madison, v. 40, n. 3, p. 597-605, 2000.
YAN, W. GGE-Biplot vs. AMMI Graphs for Genotype-by-Environment Data Analysis. Journal of the India Society of Agricultural Statistics, New Delhi, v. 65, n. 2, p. 181-193, 2011.
YAN, W.; TINKER, N. A. Biplot analysis of multienvironment trial data: Principles and applications. Canadian Journal of Plant Science, Ottawa, v. 83, n. 6, p. 623-645, 2006.
YANG, R. C. et al. Biplot analysis of genotype × environment interaction: proceed with caution. Crop Science, Madison, v. 49, n. 5, p. 1564-1576, 2009.
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11-12-2017
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