APSIM - Tropical Pasture parameterization for biomass production, light and water competition in a silvopastoral system with B. brizantha cv. Piatã and E. urograndis

Detalhes bibliográficos
Ano de defesa: 2021
Autor(a) principal: Balcão, Lucas Fillietaz
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: https://www.teses.usp.br/teses/disponiveis/11/11139/tde-13092021-085434/
Resumo: The SSP are characterised by associating trees with herbaceous forages in the same area with the presence of animals. In general, the prognosis about productivity is correlated with meteorological variables, such as air temperature and precipitation. To estimate the productive capacity of agricultural systems, mathematical modelling can be used. The present work aims to parameterise the APSIM model (Agricultural Production Systems sIMulator) to estimate the production of forage biomass in a SSP, as well as the competition for light and water. In the first stage, a field experiment was carried out in a silvopastoral system, where microclimate data were collected, of forage production and soil moisture. The experimental design was completely randomised with repeated measures over time. Forage production was analysed in relation to microclimate variables. A multiple factor analysis (AFM) was performed to verify which micro- meteorological variables have a greater participation in the variability of the results. Based on this information, the APSIM model was parameterized in relation to the growth of forage plants. To evaluate the efficiency of the model, multiple linear regression analyses and coefficient of determination (R2), Nash-Sutclif Efficience (NSE), mean error (EM) and mean absolute error (EAM) were used. The APSIM-Slurp model simulated well the light interception (R2 = 0.64 NSE = 0.60). APSIM-Tropical Pasture model showed a good performance to simulate pasture biomass (R2 = 0.90 NSE = 0.72), leaf (R2 = 0.82 NSE = 0.44), stem (R2 = 0.82 NSE = 0.75) and an acceptable performance for pasture leaf area index (R2 = 0.76 NSE = 0.58).