Yield potential and selection of off-season maize for silage and grain using GT Biplot under limited water and frost





Forage, Multivariate, Yield, Zea mays.


Maize silage has been used as a forage reserve strategy for critical periods or continuous use in animal feed. However, new genotypes and their potential must be identified. Thus, this study aimed to evaluate the potential of maize genotypes for silage and grain in one off-season in the midwest region of Brazil, under limited water and frost, and select them for this dual purpose (silage and grain) using the GT Biplot tool. The experiment was performed at Embrapa Western Agriculture in the autumn-winter season of 2021 in Dourados, Mato Grosso do Sul, Brazil. The experimental design consisted of randomized blocks of six maize genotypes (BRS1010, KWS9606, 1P2224, 1Q2383, BRS3046, and CAPO) with five replications under no-tillage. Silage points were evaluated at harvest when the grain milk line was at ¾ and maize grains at the maturation stage (dry plant). The 1P2224 and 1Q2383 maize genotypes present silage (high green and dry biomass) and grain yield potential. The GT Biplot tool identified the 1P2224 genotype as superior and suitable for cultivation or as a parent in a breeding program in the midwest region of Brazil for silage and grain yield evaluations of one off-season under limited water and frost.


Download data is not yet available.


CONAB - Companhia Nacional de Abastecimento. Série histórica das safras: Milho 1ª Safra, Milho 2ª Safra. 2021a. Available from: https://www.conab.gov.br/info-agro/safras/serie-historica-das-safras?start=20

CONAB - Companhia Nacional de Abastecimento. Acompanhamento da safra brasileira de grãos: safra 2020/2021- 11º Levantamento. 2021b. Available from: https://www.conab.gov.br/info-agro/safras

CORREA, C.E.S., et al. Relationship Between Corn Vitreousness and Ruminal In Situ Starch Degradability. Journal of Dairy Science. 2002, 85(11), 3008–3012. https://doi.org/10.3168/jds.S0022-0302(02)74386-5

CREVELARI, J.A.A., et al. Correlations between agronomic traits and path analysis for silage production in maize hybrids. Bragantia. 2018, 77(2), 1-10, 2018. https://doi.org/10.1590/1678-4499.2016512

CRUZ, J.C., et al. A cultura do milho. Sete Lagoas: Embrapa Maize e Sorghum, 2008.

CRUZ, C.D. Genes Software-extended and integrated with the R, Matlab and Selegen. Acta Scientiarum Agronomy. 2016, 38(4), 547-552. https://doi.org/10.4025/actasciagron.v38i4.32629

DOLATABAD, S.S., et al. Multienvironment analysis of traits relation and hybrids comparison of maize based on the genotype by trait Biplot. American Journal of Agricultural and Biological Sciences. 2010, 5(1), 107-113.

DUARTE, A.P., SAWAZAKI, E. and PAZIANI, S.F. 2014. Milho para Silagem. In: A.T. AGUIAR, et al. eds. Instruções agrícolas para as principais culturas econômicas. Campinas: Instituto Agronômico, pp. 276-279.

FIETZ, R.C., et al. O clima da região de Dourados, MS. Dourados: Embrapa Western Agriculture, 2017 Available from: https://www.infoteca.cnptia.embrapa.br/infoteca/bitstream/doc/1079733/1/DOC2017138FIETZ.pdf

GUIA CLIMA. Boletem Agrometeorológico. 2020. Available from: https://clima.cpao.embrapa.br/?lc=site/boletins/boletins

GUIA CLIMA. Dados Meterológicos de Dourados. 2021. Available from: https://clima.cpao.embrapa.br/?lc=site/banco-dados/base_dados

KAPLAN, M., et al. GT biplot analysis for silage potential, nutritive value, gas and methane production of stay-green grain sorghum shoots. Ciencia e investigación agraria: revista latinoamericana de ciencias de la agricultura. 2017, 44(3), 230-238. http://dx.doi.org/10.7764/rcia.v44i3.1802

MAGALHÃES, P.C. and DURÃES, F.O. Fisiologia da produção de milho. Sete Lagoas: Embrapa Maize and Sorghum, 2006. Available from: https://www.infoteca.cnptia.embrapa.br/bitstream/doc/490408/1/Circ76.pdf

MEDEIROS, S.R. and MARINO, C.T. 2015. Valor nutricional dos alimentos na nutrição de ruminantes e sua determinação. In: S.R. MEDEIROS, R.C. GOMES and D. J. BUNGENSTAB, eds. Nutrição de bovinos de corte: fundamentos e aplicações. Campo Grande: Embrapa Beef Cattle, pp. 1-6.

MOHAMMADI, R. and AMRI, A. Genotype × environment interaction and genetic improvement for yield and yield stability of rainfed durum wheat in Iran. Euphytica. 2013, 192(2), 227-249. https://doi.org/10.1007/s10681-012-0839-1

NEGRÃO, F.M., et al. Perdas, perfil fermentativo e composição química das silagens de capim Brachiaria decumbens com inclusão de farelo de arroz. Revista Brasileira de Saúde e Produção Animal. 2016, 17(1), 13-25. https://doi.org/10.1590/S1519-99402016000100002

NEUMANN, M., et al. Aditivos químicos utilizados em silagens. Pesquisa Aplicada & Agrotecnologia. 2010, 3(2), 187-195. ISSN 1984-7548

OLIVEIRA, T.R.A., et al. The GT biplot analysis of green bean traits. Ciência Rural. 2018, 48(6), 1-6. https://doi.org/10.1590/0103-8478cr20170757

PEREIRA, V.R.F., et al. Critical variables for estimating productivity in maize as a function of plant population and spacing. African Journal of Agricultural Research. 2018a, 13(35), 1828-1836. https://doi.org/10.5897/AJAR2018.13273

PEREIRA, L.B., et al. Características agronômicas da planta e produtividade da silagem de milho submetido a diferentes arranjos populacionais. Magistra. 2018b, 29(1), 18-27. ISSN 2236-4420.

PEREIRA, M.G., et al. UENF MSV2210 and UENF MS2208: Silage and green maize hybrids for Rio de Janeiro State, Brazil. Crop Breeding and Applied Biotechnology. 2020, 20(3), e309320310. https://doi.org/10.1590/1984-70332020v20n3c44

R CORE TEAM. 2020. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available from: https://www.r-project.org/

SABAGHNIA, N. and JANMOHAMMADI, M. Interrelationships among some morphological traits of wheat (Triticum aestivum L.) cultivars using biplot. Botanica Lithuanica. 2014, 20(1), 19-26. https://doi.org/10.2478/botlit-2014-0003

SABAGHNIA, N., et al. Graphic analysis of trait relations of spinach (Spinacia oleracea L.) landraces using the biplot method. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis. 2015, 63(4), 1187-1194. https://doi.org/10.11118/actaun201563041187

SANTOS, H.G., et al. Sistema Brasileiro de Classificação de Solos. Rio de Janeiro: Embrapa, 2018. Available from: https://www.infoteca.cnptia.embrapa.br/infoteca/handle/doc/1094003

SHARIFI, P. and EBADI, A.A. Relationships of rice yield and quality based on genotype by trait (GT) biplot. Anais da Academia Brasileira de Ciências. 2018, 90(1), 343-356. https://doi.org/10.1590/0001-3765201820150852

YAN, W. and TINKER, N.A. Biplot analysis of multi-environment trial data: Principles and applications. Canadian Journal of Plant Science. 2006, 86(3), 623-645. https://doi.org/10.4141/P05-169

YAN, W., et al. GGE biplot vs, AMMI Analysis of Genotype-by-Environment Data. Crop Science. 2007, 47(2), 643-653. https://doi.org/10.2135/cropsci2006.06.0374

YAN, W. and FRÉGEAU-REID, J. Genotype by yield* trait (GYT) biplot: a novel approach for genotype selection based on multiple traits. Scientific Reports. 2018, 8(1), 1-10. https://doi.org/10.1038/s41598-018-26688-8




How to Cite

GUIMARÃES, A.G., CECCON, G., CAPRISTO, D.P., OLIVEIRA, O.H. de, RETORE, M. and SANTOS, A. dos, 2023. Yield potential and selection of off-season maize for silage and grain using GT Biplot under limited water and frost. Bioscience Journal [online], vol. 39, pp. e39032. [Accessed16 April 2024]. DOI 10.14393/BJ-v39n0a2023-65597. Available from: https://seer.ufu.br/index.php/biosciencejournal/article/view/65597.



Agricultural Sciences