Sudki, Julia Marconato 
; Oliveira, Gustavo Roberto Fonseca de ; de Medeiros, André Dantas ; Mastrangelo, Thiago de Araújo ; Arthur, Valter ; Silva, Edvaldo Aparecido Amaral da ; Mastrangelo, Clíssia Barboza
Fonte: Frontiers in Plant Science. Unidade: CENA
Assuntos: QUALIDADE DOS ALIMENTOS, COMPUTAÇÃO GRÁFICA, FUNGOS FITOPATOGÊNICOS, ALGORITMOS GRÁFICOS
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SUDKI, Julia Marconato et al. Fungal identification in peanuts seeds through multispectral images: Technological advances to enhance sanitary quality. Frontiers in Plant Science, v. 14, 2023Tradução . . Disponível em: https://doi.org/10.3389/fpls.2023.1112916. Acesso em: 02 nov. 2024.APA
Sudki, J. M., Oliveira, G. R. F. de, de Medeiros, A. D., Mastrangelo, T. de A., Arthur, V., Silva, E. A. A. da, & Mastrangelo, C. B. (2023). Fungal identification in peanuts seeds through multispectral images: Technological advances to enhance sanitary quality. Frontiers in Plant Science, 14. doi:10.3389/fpls.2023.1112916NLM
Sudki JM, Oliveira GRF de, de Medeiros AD, Mastrangelo T de A, Arthur V, Silva EAA da, Mastrangelo CB. Fungal identification in peanuts seeds through multispectral images: Technological advances to enhance sanitary quality [Internet]. Frontiers in Plant Science. 2023 ; 14[citado 2024 nov. 02 ] Available from: https://doi.org/10.3389/fpls.2023.1112916Vancouver
Sudki JM, Oliveira GRF de, de Medeiros AD, Mastrangelo T de A, Arthur V, Silva EAA da, Mastrangelo CB. Fungal identification in peanuts seeds through multispectral images: Technological advances to enhance sanitary quality [Internet]. Frontiers in Plant Science. 2023 ; 14[citado 2024 nov. 02 ] Available from: https://doi.org/10.3389/fpls.2023.1112916
