ABSTRACT: 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. | RESUMO: 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.

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.