ESTIMATING THE NEED FOR NITROGEN IN THE PRODUCTION OF GRAIN AND SILAGE

Detalhes bibliográficos
Autor(a) principal: Silva, Marciela Rodrigues
Data de Publicação: 2015
Outros Autores: Martin, Thomas Newton, Pavinato, Paulo Sergio, Brum, Marcos da Silva
Tipo de documento: Artigo
Idioma: por
Título da fonte: Revista Caatinga
Texto Completo: https://periodicos.ufersa.edu.br/caatinga/article/view/3629
Resumo: The modeling for agriculture is a mathematical tool that allows us to weigh the effects of factors, environmental or management on crop productivity. Therefore, the aim of this study was to evaluate the efficiency of mathematical models, in the estimation of the productivity of maize over the need for nitrogen fertilization. Estimates of nitrogen fertilization were performed to obtain the potential productivity and depleted grain yield and silage corn genotypes. The Model 1 was based on estimates obtained in the literature and Model 2 on estimates generated by the proposed alternative model, calibrated with data observed in the experiment. To evaluate the performance of the models we used statistical indicators, such as Pearson correlation coefficient, Willmott agreement index, the performance index of Camargo, percentage deviation and medium square error. Recommendations of nitrogen generated by the models for the potential productivity and depleted much grain as silage were higher compared with the recommendations of the culture ways. The AG30A91 genotype had a higher leaf area index, reflecting higher estimates of potential productivity and depleted grain and silage. The model 2 can be used to estimate the yield of grain and silage and the need for simulation of nitrogen for grain production, however, requires adjustments to estimate nitrogen needs for the production of silage. Both models are efficient in simulating the crop cycle.
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spelling ESTIMATING THE NEED FOR NITROGEN IN THE PRODUCTION OF GRAIN AND SILAGEESTIMATIVAS DA NECESSIDADE DE NITROGÊNIO PARA PRODUÇÃO DE GRÃOS E SILAGEM DE MILHONitrogen fertilization. Modeling. Simulation. Zea mays L.Adubação nitrogenada. Modelagem. Simulação. Zea mays L.The modeling for agriculture is a mathematical tool that allows us to weigh the effects of factors, environmental or management on crop productivity. Therefore, the aim of this study was to evaluate the efficiency of mathematical models, in the estimation of the productivity of maize over the need for nitrogen fertilization. Estimates of nitrogen fertilization were performed to obtain the potential productivity and depleted grain yield and silage corn genotypes. The Model 1 was based on estimates obtained in the literature and Model 2 on estimates generated by the proposed alternative model, calibrated with data observed in the experiment. To evaluate the performance of the models we used statistical indicators, such as Pearson correlation coefficient, Willmott agreement index, the performance index of Camargo, percentage deviation and medium square error. Recommendations of nitrogen generated by the models for the potential productivity and depleted much grain as silage were higher compared with the recommendations of the culture ways. The AG30A91 genotype had a higher leaf area index, reflecting higher estimates of potential productivity and depleted grain and silage. The model 2 can be used to estimate the yield of grain and silage and the need for simulation of nitrogen for grain production, however, requires adjustments to estimate nitrogen needs for the production of silage. Both models are efficient in simulating the crop cycle.A modelagem para a agricultura é uma ferramenta matemática que permite ponderar os efeitos de fatores ambientais ou de manejo sobre a produtividade das culturas. Nessa ótica, objetivou-se com o presente trabalho avaliar a eficiência de modelos matemáticos na estimação da produtividade da cultura do milho em relação a necessidade de adubação nitrogenada. As estimativas da adubação nitrogenada foram realizadas para se obter as produtividades potencial e deplecionada de grãos e silagem de genótipos de milho. O Modelo 1 foi baseado em estimativas obtidas em dados da literatura e o Modelo 2 em estimativas geradas pelo modelo alternativo proposto, calibrado com dados observados no experimento. Para avaliar o desempenho dos modelos foram utilizados indicadores estatísticos tais como: coeficiente de correlação de Pearson; índice de concordância de Willmott; índice de desempenho de Camargo; porcentagem de desvio; e quadrado médio do erro. Recomendações de nitrogênio geradas pelos modelos para as produtividades potenciais e deplecionadas tanto de grãos quanto de silagem foram elevadas em comparação com os aplicados atualmente pelas recomendações da cultura. O genótipo AG30A91 obteve maior índice de área foliar, refletindo em maiores estimativas de produtividades potencial e deplecionada de grãos e silagem. O modelo 2 pode ser utilizado na estimativa da produtividade de grãos e silagem e na simulação da necessidade de nitrogênio para produção de grãos, porém necessita de ajustes para estimar as necessidades de nitrogênio para a produção de silagem. Ambos os modelos são eficientes na simulação do ciclo da cultura.Universidade Federal Rural do Semi-Árido2015-08-27info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufersa.edu.br/caatinga/article/view/362910.1590/1983-21252015v28n302rcREVISTA CAATINGA; Vol. 28 No. 3 (2015); 12-24Revista Caatinga; v. 28 n. 3 (2015); 12-241983-21250100-316Xreponame:Revista Caatingainstname:Universidade Federal Rural do Semi-Árido (UFERSA)instacron:UFERSAporhttps://periodicos.ufersa.edu.br/caatinga/article/view/3629/pdf_271Copyright (c) 2023 Revista Caatingainfo:eu-repo/semantics/openAccessSilva, Marciela RodriguesMartin, Thomas NewtonPavinato, Paulo SergioBrum, Marcos da Silva2023-07-27T12:49:32Zoai:ojs.periodicos.ufersa.edu.br:article/3629Revistahttps://periodicos.ufersa.edu.br/index.php/caatinga/indexPUBhttps://periodicos.ufersa.edu.br/index.php/caatinga/oaipatricio@ufersa.edu.br|| caatinga@ufersa.edu.br1983-21250100-316Xopendoar:2024-04-29T09:46:07.244004Revista Caatinga - Universidade Federal Rural do Semi-Árido (UFERSA)true
dc.title.none.fl_str_mv ESTIMATING THE NEED FOR NITROGEN IN THE PRODUCTION OF GRAIN AND SILAGE
ESTIMATIVAS DA NECESSIDADE DE NITROGÊNIO PARA PRODUÇÃO DE GRÃOS E SILAGEM DE MILHO
title ESTIMATING THE NEED FOR NITROGEN IN THE PRODUCTION OF GRAIN AND SILAGE
spellingShingle ESTIMATING THE NEED FOR NITROGEN IN THE PRODUCTION OF GRAIN AND SILAGE
Silva, Marciela Rodrigues
Nitrogen fertilization. Modeling. Simulation. Zea mays L.
Adubação nitrogenada. Modelagem. Simulação. Zea mays L.
title_short ESTIMATING THE NEED FOR NITROGEN IN THE PRODUCTION OF GRAIN AND SILAGE
title_full ESTIMATING THE NEED FOR NITROGEN IN THE PRODUCTION OF GRAIN AND SILAGE
title_fullStr ESTIMATING THE NEED FOR NITROGEN IN THE PRODUCTION OF GRAIN AND SILAGE
title_full_unstemmed ESTIMATING THE NEED FOR NITROGEN IN THE PRODUCTION OF GRAIN AND SILAGE
title_sort ESTIMATING THE NEED FOR NITROGEN IN THE PRODUCTION OF GRAIN AND SILAGE
author Silva, Marciela Rodrigues
author_facet Silva, Marciela Rodrigues
Martin, Thomas Newton
Pavinato, Paulo Sergio
Brum, Marcos da Silva
author_role author
author2 Martin, Thomas Newton
Pavinato, Paulo Sergio
Brum, Marcos da Silva
author2_role author
author
author
dc.contributor.author.fl_str_mv Silva, Marciela Rodrigues
Martin, Thomas Newton
Pavinato, Paulo Sergio
Brum, Marcos da Silva
dc.subject.por.fl_str_mv Nitrogen fertilization. Modeling. Simulation. Zea mays L.
Adubação nitrogenada. Modelagem. Simulação. Zea mays L.
topic Nitrogen fertilization. Modeling. Simulation. Zea mays L.
Adubação nitrogenada. Modelagem. Simulação. Zea mays L.
description The modeling for agriculture is a mathematical tool that allows us to weigh the effects of factors, environmental or management on crop productivity. Therefore, the aim of this study was to evaluate the efficiency of mathematical models, in the estimation of the productivity of maize over the need for nitrogen fertilization. Estimates of nitrogen fertilization were performed to obtain the potential productivity and depleted grain yield and silage corn genotypes. The Model 1 was based on estimates obtained in the literature and Model 2 on estimates generated by the proposed alternative model, calibrated with data observed in the experiment. To evaluate the performance of the models we used statistical indicators, such as Pearson correlation coefficient, Willmott agreement index, the performance index of Camargo, percentage deviation and medium square error. Recommendations of nitrogen generated by the models for the potential productivity and depleted much grain as silage were higher compared with the recommendations of the culture ways. The AG30A91 genotype had a higher leaf area index, reflecting higher estimates of potential productivity and depleted grain and silage. The model 2 can be used to estimate the yield of grain and silage and the need for simulation of nitrogen for grain production, however, requires adjustments to estimate nitrogen needs for the production of silage. Both models are efficient in simulating the crop cycle.
publishDate 2015
dc.date.none.fl_str_mv 2015-08-27
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
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dc.identifier.uri.fl_str_mv https://periodicos.ufersa.edu.br/caatinga/article/view/3629
10.1590/1983-21252015v28n302rc
url https://periodicos.ufersa.edu.br/caatinga/article/view/3629
identifier_str_mv 10.1590/1983-21252015v28n302rc
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://periodicos.ufersa.edu.br/caatinga/article/view/3629/pdf_271
dc.rights.driver.fl_str_mv Copyright (c) 2023 Revista Caatinga
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2023 Revista Caatinga
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal Rural do Semi-Árido
publisher.none.fl_str_mv Universidade Federal Rural do Semi-Árido
dc.source.none.fl_str_mv REVISTA CAATINGA; Vol. 28 No. 3 (2015); 12-24
Revista Caatinga; v. 28 n. 3 (2015); 12-24
1983-2125
0100-316X
reponame:Revista Caatinga
instname:Universidade Federal Rural do Semi-Árido (UFERSA)
instacron:UFERSA
instname_str Universidade Federal Rural do Semi-Árido (UFERSA)
instacron_str UFERSA
institution UFERSA
reponame_str Revista Caatinga
collection Revista Caatinga
repository.name.fl_str_mv Revista Caatinga - Universidade Federal Rural do Semi-Árido (UFERSA)
repository.mail.fl_str_mv patricio@ufersa.edu.br|| caatinga@ufersa.edu.br
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