Adaptability and phenotypic stability of rice lines in Minas Gerais
DOI:
https://doi.org/10.33448/rsd-v9i9.7857Keywords:
Oryza sativa; Grain yield; GGE Biplot.Abstract
The alternative adopted in the breeding programs to decrease the effect of the genotype x environment interaction (G x E), is through the evaluation of the lineages in a network of experiments, these being conducted in several years and representative environments of the edaphoclimatic regions of cultivation. Therefore, the objective of this work was to evaluate the adaptability and productive stability of upland rice genotypes from the Minas Gerais, using the graphical tool for analysis of data, the GGE biplot. Grain yield data were used, derived from the evaluation of twenty rice lineages from the Cultivation Value and Use test of the Upland Rice Breeding Program at the Federal University of Lavras in partnership with Embrapa and Epamig. The tests were conducted in a complete block design, with three replications in the 2013/2014, 2014/2015 and 2015/2016 agricultural years. The experiments were conducted in a total of nine locations divided into the three agricultural years in the cities of Lambari, Lavras and Patos de Minas, all located in the state of Minas Gerais. It was concluded with this work that the lineages were almost entirely more adapted and stable than the commercial cultivars. The genotypes 10 and 13 were higher than the general average for productivity and showed high stability, being future candidates for launch as new cultivars.
References
Allard, R. W., Bradshaw, A. D. (1964). Implications of genotype x environmental interactions in applied plant breeding. Crop Science, Madison, v.4, n.5, p. 503-508.
Andrade, M. H. M. L. (2016). Adaptabilidade e estabilidade para caracteres agronômicos em clones de batata resistentes ao Potato Virus Y (PVY). Lavras: UFLA, 2016. 77 p.: il. Dissertação (mestrado acadêmico) – Universidade Federal de Lavras, 2016.
Anputhas, M., Samita, S., Abeysiriwardena, D. S. (2011). Stability and adaptability analysis of rice cultivars using environment-centered yield in two-way ANOVA model. Communications in Biometry and Crop Science, v.6, n.2, p. 80-86.
Balestre, M. (2009). Yield stability and adaptability of maize hybrids based on GGE biplot analysis characteristics. Crop Breeding & Applied Biotechnology, v.9, n.3.
Bernardo, R. (2010). Breeding for Quantitative Traits in Plants. 2.ed. Woodbury: Stemma Press, 390 p.
Camargo-Buitrago, I.; Intire, E. M.; Córdon-Mendoza, R. (2011). Identificación de mega-ambientes para potenciar el uso de progênies superiores de arroz em Panamá. Pesquisa Agropecuária Brasileira, Goiânia, v.46, n.9, p.1601-1069.
Companhia Nacional de Abastecimento – Conab. Acompanhamento da safra brasileira de grãos – v.4, n.7 (2016/17) Brasília: Conab, 2017. Disponível em: <http://www.conab.gov.br/OlalaCMS/uploads/arquivos/17_04_17_17_20_55_b. pdf>. Acesso em: 24 de Abril de 2017.
Comstock, R. E., Moll, R. H. (1963). Genotype-environment interactions. Statistical genetics and plant breeding, p. 164-196.
Cruz, C. D., Torres, R A de, Vencovsky, R. (1989). An alternative approach to the stability analysis proposed by Silva and Barreto. Revista Brasileira de Genética, v.12, n.3, p. 567-580.
Cruz, C. D., Regazzi, A. J., Carneiro, P. C. S. (2004). Modelos biométricos aplicados ao melhoramento genético. Viçosa, MG: UFV, v. 1, 480 p.
Ferreira, D. F. (2006). Statistical models in agriculture: biometrical methods for evaluating phenotypic stability in plant breeding. Cerne, v. 12, n. 4, p. 373-388.
Food and Agriculture Organization - FAO. (2016). Rice market monitor. v. 65, April, p.821-822.
Hongyu, K. (2015). Comparação entre os modelos ammi e gge biplot para os dados de ensaios multi-ambientais. Revista Brasileira de Biometria, v. 33, n. 2, p. 139-155.
Pimentel-Gomes, F. (2009). Curso de estatística experimental. 15° edição, Ed. FEALQ, 451 p.
R Core Team. (2015). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
Ramalho, M. A. P., Abreu, A. F. B., Santos, J. B., Nunes, J. A. R. (2012). Aplicações da Genética Quantitativa no Melhoramento de Plantas Autógamas. 1. ed. Lavras: Ed. UFLA, 522p, 2012.
Resende, M. D. V. (2017). Matemática e estatística na análise de experimentos e no melhoramento genético. Colombo: Embrapa Florestas, 362 p.
Resende, M. D. V., Duarte, J. B. (2007). Precisão e controle de qualidade em experimentos de avaliação de cultivares. Pesquisa Agropecuária Tropical, v.37, n.3, p. 182-194.
Storck, L., Filho, A. C., Guadagnin, J. P. (2014). Joint analysis of corn cultivar trials by classes of genotype x environment interaction. Pesquisa Agropecuária Brasileira, v.49, n.3, p. 163-172.
Vencovsky, R., Barriga, P. Genética biométrica no fitomelhoramento. 1992.
Yan, W. (2000). Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Science, v.40, n.3, p. 597-605.
Yan, W. (2001). Two types of GGE biplots for analyzingmulti-environmenttrial data. Crop Science, v.41, n.3, p.656-663.
Yan, W.; Tinker A. (2006). "Biplot analysis of multi-environment trial data: Principles and applications." Canadian Journal of Plant Science, 86.3: 623-645.
Yan, W. (2007). GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop Science, v. 47, n.2, p. 643-653.
Yan, W. (2011). GGE Biplot vs. AMMI graphs for genotype by environment data analysis. Journal of the Indian Society of Agricultural Statistics, v.65, n.2, p. 181-193.
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Copyright (c) 2020 Natália Botega Alves; Antônio Rosário Neto; Douglas Goulart Castro; Camila Soares Cardoso da Silva; Bruno Manoel Rezende de Melo; Flávia Barbosa Silva Botelho
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