Regional model to predict sugarcane yield usingsentinel-2 imagery in São Paulo State, Brazil (2025)
Source: Sugar Tech. Unidade: ESALQ
Subjects: ALGORITMOS PARA IMAGENS, CANA-DE-AÇÚCAR, ESPECTROSCOPIA INFRAVERMELHA, IMAGEAMENTO DE SATÉLITE, MODELOS MATEMÁTICOS
ABNT
AMARO, Rafaella Pironato et al. Regional model to predict sugarcane yield usingsentinel-2 imagery in São Paulo State, Brazil. Sugar Tech, v. 27, n. 1, p. 108–118, 2025Tradução . . Disponível em: https://doi.org/10.1007/s12355-024-01468-z. Acesso em: 17 abr. 2026.APA
Amaro, R. P., Christina, M., Todoroff, P., Le Maire, G., Fiorio, P. R., Pereira, E. de C., & Luciano, A. C. dos S. (2025). Regional model to predict sugarcane yield usingsentinel-2 imagery in São Paulo State, Brazil. Sugar Tech, 27( 1), 108–118. doi:10.1007/s12355-024-01468-zNLM
Amaro RP, Christina M, Todoroff P, Le Maire G, Fiorio PR, Pereira E de C, Luciano AC dos S. Regional model to predict sugarcane yield usingsentinel-2 imagery in São Paulo State, Brazil [Internet]. Sugar Tech. 2025 ; 27( 1): 108–118.[citado 2026 abr. 17 ] Available from: https://doi.org/10.1007/s12355-024-01468-zVancouver
Amaro RP, Christina M, Todoroff P, Le Maire G, Fiorio PR, Pereira E de C, Luciano AC dos S. Regional model to predict sugarcane yield usingsentinel-2 imagery in São Paulo State, Brazil [Internet]. Sugar Tech. 2025 ; 27( 1): 108–118.[citado 2026 abr. 17 ] Available from: https://doi.org/10.1007/s12355-024-01468-z
