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Artigo de periodico
How much would irrigation increase maize production in Brazil? (2025)
Antolin, Luís Alberto Silva ; Silva, Evandro Henrique Figueiredo Moura da ; Zanon, Alencar Junior ; Ribeiro, Bruna San Martin Rolim ; Marin, Fabio Ricardo
Fonte: Scientia Agricola. Unidade: ESALQ
Assuntos: MILHO, IRRIGAÇÃO, SIMULAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ANTOLIN, Luís Alberto Silva et al. How much would irrigation increase maize production in Brazil?. Scientia Agricola, v. 82, p. 1-13, 2025Tradução . . Disponível em: https://doi.org/10.1590/1678-992X-2024-0083. Acesso em: 08 out. 2025.
APA
Antolin, L. A. S., Silva, E. H. F. M. da, Zanon, A. J., Ribeiro, B. S. M. R., & Marin, F. R. (2025). How much would irrigation increase maize production in Brazil? Scientia Agricola, 82, 1-13. doi:10.1590/1678-992X-2024-0083
NLM
Antolin LAS, Silva EHFM da, Zanon AJ, Ribeiro BSMR, Marin FR. How much would irrigation increase maize production in Brazil? [Internet]. Scientia Agricola. 2025 ; 82 1-13.[citado 2025 out. 08 ] Available from: https://doi.org/10.1590/1678-992X-2024-0083
Vancouver
Antolin LAS, Silva EHFM da, Zanon AJ, Ribeiro BSMR, Marin FR. How much would irrigation increase maize production in Brazil? [Internet]. Scientia Agricola. 2025 ; 82 1-13.[citado 2025 out. 08 ] Available from: https://doi.org/10.1590/1678-992X-2024-0083
Artigo de periodico
Sample size, range of parameters, and time-dependent effects on global sensitivity analysis in sugarcane modelling (2024)
Pereira, Rodolfo Armando de Almeida ; Vianna, M. S; Marin, Fabio Ricardo
Fonte: Journal of Agricultural Science. Unidade: ESALQ
Assuntos: ANÁLISE ESTATÍSTICA DE DADOS, CANA-DE-AÇÚCAR, CRESCIMENTO VEGETAL, MODELAGEM DE DADOS, SIMULAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PEREIRA, Rodolfo Armando de Almeida e VIANNA, M. S e MARIN, Fabio Ricardo. Sample size, range of parameters, and time-dependent effects on global sensitivity analysis in sugarcane modelling. Journal of Agricultural Science, v. 161, p. 817–834, 2024Tradução . . Disponível em: https://doi.org/10.1017/S0021859624000030. Acesso em: 08 out. 2025.
APA
Pereira, R. A. de A., Vianna, M. S., & Marin, F. R. (2024). Sample size, range of parameters, and time-dependent effects on global sensitivity analysis in sugarcane modelling. Journal of Agricultural Science, 161, 817–834. doi:10.1017/S0021859624000030
NLM
Pereira RA de A, Vianna MS, Marin FR. Sample size, range of parameters, and time-dependent effects on global sensitivity analysis in sugarcane modelling [Internet]. Journal of Agricultural Science. 2024 ; 161 817–834.[citado 2025 out. 08 ] Available from: https://doi.org/10.1017/S0021859624000030
Vancouver
Pereira RA de A, Vianna MS, Marin FR. Sample size, range of parameters, and time-dependent effects on global sensitivity analysis in sugarcane modelling [Internet]. Journal of Agricultural Science. 2024 ; 161 817–834.[citado 2025 out. 08 ] Available from: https://doi.org/10.1017/S0021859624000030
Artigo de periodico
Coupling a dynamic epidemiological model into a process-based crop model to simulate climate change effects on soybean target spot disease in Brazil (2024)
Luca, Gustavo de Angelo ; Fattori Jr, Izael Martins ; Marin, Fabio Ricardo
Fonte: European Journal of Agronomy. Unidade: ESALQ
Assuntos: DOENÇAS DE PLANTAS, FUNGOS FITOPATOGÊNICOS, MODELOS EPIDEMIOLOGICOS, MUDANÇA CLIMÁTICA, SIMULAÇÃO, SOJA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LUCA, Gustavo de Angelo e FATTORI JR, Izael Martins e MARIN, Fabio Ricardo. Coupling a dynamic epidemiological model into a process-based crop model to simulate climate change effects on soybean target spot disease in Brazil. European Journal of Agronomy, v. 161, p. 1-11, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.eja.2024.127361. Acesso em: 08 out. 2025.
APA
Luca, G. de A., Fattori Jr, I. M., & Marin, F. R. (2024). Coupling a dynamic epidemiological model into a process-based crop model to simulate climate change effects on soybean target spot disease in Brazil. European Journal of Agronomy, 161, 1-11. doi:10.1016/j.eja.2024.127361
NLM
Luca G de A, Fattori Jr IM, Marin FR. Coupling a dynamic epidemiological model into a process-based crop model to simulate climate change effects on soybean target spot disease in Brazil [Internet]. European Journal of Agronomy. 2024 ; 161 1-11.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.eja.2024.127361
Vancouver
Luca G de A, Fattori Jr IM, Marin FR. Coupling a dynamic epidemiological model into a process-based crop model to simulate climate change effects on soybean target spot disease in Brazil [Internet]. European Journal of Agronomy. 2024 ; 161 1-11.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.eja.2024.127361
Artigo de periodico
Application of the JULES-crop model and agrometeorological indicators for forecasting off-season maize yield in Brazil (2024)
Prudente Junior, Amauri Cassio ; Vianna, Murilo S; Willians, Karina; Galdos, Marcelo V; Marin, Fabio Ricardo
Fonte: Heliyon. Unidade: ESALQ
Assuntos: AGROMETEOROLOGIA, MILHO, REGRESSÃO LINEAR, SAFRA, SIMULAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PRUDENTE JUNIOR, Amauri Cassio et al. Application of the JULES-crop model and agrometeorological indicators for forecasting off-season maize yield in Brazil. Heliyon, v. 10, p. 1-12, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.heliyon.2024.e29555. Acesso em: 08 out. 2025.
APA
Prudente Junior, A. C., Vianna, M. S., Willians, K., Galdos, M. V., & Marin, F. R. (2024). Application of the JULES-crop model and agrometeorological indicators for forecasting off-season maize yield in Brazil. Heliyon, 10, 1-12. doi:10.1016/j.heliyon.2024.e29555
NLM
Prudente Junior AC, Vianna MS, Willians K, Galdos MV, Marin FR. Application of the JULES-crop model and agrometeorological indicators for forecasting off-season maize yield in Brazil [Internet]. Heliyon. 2024 ; 10 1-12.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.heliyon.2024.e29555
Vancouver
Prudente Junior AC, Vianna MS, Willians K, Galdos MV, Marin FR. Application of the JULES-crop model and agrometeorological indicators for forecasting off-season maize yield in Brazil [Internet]. Heliyon. 2024 ; 10 1-12.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.heliyon.2024.e29555
Artigo de periodico
Predicting soybean evapotranspiration and crop water productivity for a tropical environment using the CSM-CROPGRO-Soybean model (2022)
Silva, Evandro Henrique Figueiredo Moura da ; Hoogenboom, Gerrit; Boote, Kenneth J; Gonçalves, Alexandre Ortega; Marin, Fabio Ricardo
Fonte: Agricultural and Forest Meteorology. Unidade: ESALQ
Assuntos: ÁGUA PARA IRRIGAÇÃO, EVAPOTRANSPIRAÇÃO, SIMULAÇÃO, SOJA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SILVA, Evandro Henrique Figueiredo Moura da et al. Predicting soybean evapotranspiration and crop water productivity for a tropical environment using the CSM-CROPGRO-Soybean model. Agricultural and Forest Meteorology, v. 323, p. 1-12, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.agrformet.2022.109075. Acesso em: 08 out. 2025.
APA
Silva, E. H. F. M. da, Hoogenboom, G., Boote, K. J., Gonçalves, A. O., & Marin, F. R. (2022). Predicting soybean evapotranspiration and crop water productivity for a tropical environment using the CSM-CROPGRO-Soybean model. Agricultural and Forest Meteorology, 323, 1-12. doi:10.1016/j.agrformet.2022.109075
NLM
Silva EHFM da, Hoogenboom G, Boote KJ, Gonçalves AO, Marin FR. Predicting soybean evapotranspiration and crop water productivity for a tropical environment using the CSM-CROPGRO-Soybean model [Internet]. Agricultural and Forest Meteorology. 2022 ; 323 1-12.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.agrformet.2022.109075
Vancouver
Silva EHFM da, Hoogenboom G, Boote KJ, Gonçalves AO, Marin FR. Predicting soybean evapotranspiration and crop water productivity for a tropical environment using the CSM-CROPGRO-Soybean model [Internet]. Agricultural and Forest Meteorology. 2022 ; 323 1-12.[citado 2025 out. 08 ] Available from: https://doi.org/10.1016/j.agrformet.2022.109075

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