Selection for yield in elephant-grass forage genotypes using GGE Biplot analysis
Seleção para produtividade em genótipos forrageiros de capim-elefante utilizando análise de GGE Biplot
Palavras-chave:
Cenchrus purpureus (Schumach.) Morrone, Dry matter yield, Genotype × Environment interaction, Stability, YieldResumo
Elephant grass is among the most used forages in intensive animal production systems due to its high productive potential, carrying capacity and nutritional quality. Because of the existing interaction between genotypes and environments, it is essential to select and develop materials that are not only high-yielding but also adaptable and stable. In this context, this study was developed to analyze the performance and select genotypes of elephant grass simultaneously for dry matter yield, performance stability and adaptability. Fifty-three elephant grass genotypes with forage potential were evaluated in four environments (rainy and dry seasons in years 1 and 2), defined according to the time at which the harvests occurred. A randomized-block design with two replicates was adopted. Dry matter yield (t.ha-1) was measured at each assessment (harvest). Adaptability and genotypic stability were evaluated using the GGE biplot methodology and R software. In the overall classification, genotypes 53, 22, 29, 17 and 33 showed the best average performance. Regarding dry matter yield, adaptability and phenotypic stability, genotype 53 was classified as the ideotype.
Downloads
Referências
BHERING, M. et al. Características agronômicas do capim-elefante roxo em diferentes idades de corte na Depressão Cuiabana. Revista Brasileira de Saúde e Produção Animal, v. 9, n. 3, p.384-396, 2008.
CAVALCANTE, M.; LIRA, M.A. Variabilidade genética em Pennisetum purpureum Schumacher. Revista Caatinga, v. 23, n. 2, p.153-163, 2010.
CRUZ, C.D.; REGAZZI, A.J. Modelos biométricos aplicados ao melhoramento genético. 2.ed.rev. Viçosa, Editora UFV, 2001.
CRUZ, C.D. Genes: a software package for analysis in experimental statistics and quantitative genetics. Acta Scientiarum. Agronomy, 35(3): 271-276, 2013.
CRUZ, C. D.; REGAZZI, A. J.; CARNEIRO, P. C. Métodos biométricos aplicados ao melhoramento genético 4a ed. Viçosa, UFV. 414p, 2012.
CUNHA, M. V. et al. Adaptabilidade e estabilidade da produção de forragem por meio de diferentes metodologias na seleção de clones de Pennisetum spp. Agrária, v. 8, n. 4, p. 681–686, 2013. https://doi.org/10.5039/agraria.v8i4a3280
DAHER, R. F. et al. Variação sazonal na produção de forragem de clones intra e interespecíficos de capim-elefante. Agrarian, v. 10, n. 38, p. 294, 2017. https://doi.org/10.30612/agrarian.v10i38.4072
DAHER, R. F. et al. Correlations Between Stability Statistics of Forage Production in Elephant Grass. Journal of agricultural science, v. 12, n. 1, p. 118–118, 2019. https://doi.org/ 10.5539/jas.v12n1p118
FONSECA, J.S. DE ; MARTINS, G. DE A. Curso de Estatística. 6 ed. São Paulo: Atlas, 1996.
FREIRE, L.R.; FREIRE, L.R. Manual de calagem e adubação do Estado do Rio de Janeiro, 2013.
FREITAS, R. S. et al. Dry Matter Yield and Nutritional Characteristics of Elephant-Grass Genotypes. Journal of experimental agriculture international, p. 1–8, 2019. http://doi.org/ 10.9734/jeai/2019/v35i530216
Gauch Jr, H.G.; Piepho, H.P.; Annicchiarico, P. 2008. Statistical analysis of yield trials by AMMI and GGE: Further considerations. Crop science 48(3):866-889. https://doi.org/10.2135/cropsci2007.09.0513
GRAVINA, L.M et al. Multivariate analysis in the selection of elephant grass genotypes for biomass production. Renewable Energy, v. 160, p. 1265–1268, 2020. https://doi.org/10.1016/j.renene.2020.06.094
KARIMIZADEH, R. et al. GGE Biplot Analysis of Yield Stability in Multi-environment Trials of Lentil Genotypes under Rainfed Condition. Notulae Scientia Biologicae, v. 5, n. 2, p. 256–262, 2013. https://doi.org/10.15835/nsb529067
HASSANPANAH, D. Evaluation of Potato Cultivars for Resistance Against Water Deficit Stress Under In Vivo Conditions. Potato Research, v. 53, n. 4, p. 383–392, 2010. https://doi.org/10.1007/s11540-010-9179-5
HONGYU, K. et al. 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, 2015.
LIMA, E. DA S. et al. Produção de matéria seca e proteína bruta e relação folha/colmo de genótipos de capim-elefante aos 56 dias de rebrota. Revista Brasileira de Zootecnia, v. 36, n. 5, p. 1518–1523, 2007. https://doi.org/10.1590/S1516-35982007000700009
MENEZES, B. R. D. S. et al. Comportamento Per se de híbridos de capim-elefante para fins energéticos. Comunicata Scientiae, v. 7, n. 1, p. 73, 2016. https://doi.org/ 10.14295/CS.v7i1.946
OLIVEIRA, T. N. et al. Estabilidade e adaptabilidade de clones de Pennisetum sp. sob pastejo: Mancha ocular. Archivos de zootecnia, v. 60, n. 231, p. 725–732, 2011. https://doi.org/10.4321/S0004-05922011000300060
OLIVEIRA, T. R. A. DE et al. The GT biplot analysis of green bean traits. Ciência Rural, v. 48, n. 6, 2018. https://doi.org/10.1590/0103-8478cr20170757
PIMENTEL-GOMES, F; GARCIA, C.H. Estatística aplicada a experimentos agronômicos e florestais: exposição com exemplo e orientações para uso. Piracicaba: FEALQ, 2002.
R DEVELOPMENT CORE TEAM. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing, Vienna, 2014.
RAMALHO, M.A.P.; FERREIRA, D.F.; OLIVEIRA, A.C. Experimentação em genética e melhoramento de plantas. Lavras: UFLA, 2005.
ROCHA, R.S. et al. Comparison of stability methods in elephant-grass genotypes for energy purposes. African Journal of Agricultural Research, v. 10, n. 47, p. 4283–4294, 2015. https://doi.org/ 10.21475/ajcs.20.14.02.p2121
RODRIGUES, E. V. et al. Repeatability estimates and minimum number of evaluations for selection of elephant-grass genotypes for herbage production. Bioscience journal, v. 36, n. 1, 2020. https://doi.org/10.14393/BJ-v36n1a2020-42075
SANTANA, J. G. S. et al. Genotype analysis by trait is a practical and efficient approach on discrimination of inbred lines and identification of papaya (Carica papaya L.) ideotypes for fruit quality. Euphytica, v. 217, n. 6, 2021. https://doi.org/ 10.1007/s10681-021-02850-8
SANTOS, A DOS et al. Adaptability and stability of erect cowpea genotypes via REML/BLUP and GGE Biplot. Bragantia, v. 75, n. 3, p. 299–306, 2016.https://doi.org/10.1590/1678-4499.280
SANTOS, A. DOS et al. GGE Biplot projection in discriminating the efficiency of popcorn lines to use nitrogen. Ciência e Agrotecnologia, v. 41, n. 1, p. 22–31, 2017. https://doi.org/10.1590/1413-70542017411030816
BRITO, V. et al. DIFFERENT STABILITY METHODS FOR CULTIVAR RECOMMENDATION IN ELEPHANT-GRASS FOR ENERGY PURPOSES IN BRAZIL. Cerne, v. 23, n. 4, p. 507–515, 2017. https://doi.org/10.1590/01047760201723042292
SINGH, C. et al. Genotype x environment interaction analysis of multi-environment wheat trials in India using AMMI and GGE biplot models. Crop Breeding and Applied Biotechnology, v. 19, n. 3, p. 309–318, 2019. https://doi.org/10.1590/1984-70332019v19n3a43
STIDA, W. F. et al. Estimation of genetic parameters and selection of elephant-grass ( Pennisetum purpureum Schumach.) for forage production using mixed models. Chilean journal of agricultural research, v. 78, n. 2, p. 198–204, 2018. 78(2):198-204. http://dx.doi.org/10.4067/S0718-58392018000200198
TRETHOWAN, R.M. Defining a genetic ideotype for crop improvement. In Crop Breeding. Humana Press, New York, NY, 2014.
YAN, W. et al. Cultivar Evaluation and Mega-Environment Investigation Based on the GGE Biplot. Crop Science, v. 40, n. 3, p. 597–605, 2000. https://doi.org/10.2135/cropsci2000.403597x
YAN, W.; RAJCAN, I. Biplot Analysis of Test Sites and Trait Relations of Soybean in Ontario. Crop Science, v. 42, n. 1, p. 11–20, 2002. https://doi.org/ 10.2135/cropsci2002.1100
YAN, W.; KANG, M.S. GGE biplot analysis: a graphical tool for breeders, geneticists and agronomists. Flórida: Boca Raton, 2003.
YAN, W.; TINKER, N. A. Biplot analysis of multi-environment trial data: Principles and applications. Canadian Journal of Plant Science, v. 86, n. 3, p. 623–645, 2006. https://doi.org/10.4141/P05-169
YAN, W.; HOLLAND, J.B. A heritability-adjusted GGE biplot for test environment evaluation. Euphytica, v. 171, n. 3, p.355-369, 2010.
YAN, W. et al. GGE Biplot vs. AMMI Analysis of Genotype-by-Environment Data. Crop Science, v. 47, n. 2, p. 643–653, 2007. https://doi.org/10.2135/cropsci2006.06.0374