Assuntos: ALGORITMOS, ANÁLISE MULTIVARIADA, CRESCIMENTO VEGETAL, ESPECTROSCOPIA INFRAVERMELHA, FUMO, MÍNIMOS QUADRADOS, MORFOLOGIA VEGETAL, SENSORIAMENTO REMOTO
ABNT
FALCIONI, Renan et al. Non−invasive assessment, classification, and prediction of biophysical parameters using reflectance hyperspectroscopy. Plants, v. 12, n. 13, p. 1-27, 2023Tradução . . Disponível em: https://doi.org/10.3390/plants12132526. Acesso em: 23 ago. 2024.APA
Falcioni, R., Santos, G. L. A. A. dos, Crusiol, L. G. T., Antunes, W. C., Chicati, M. L., Oliveira, R. B. de, et al. (2023). Non−invasive assessment, classification, and prediction of biophysical parameters using reflectance hyperspectroscopy. Plants, 12( 13), 1-27. doi:10.3390/plants12132526NLM
Falcioni R, Santos GLAA dos, Crusiol LGT, Antunes WC, Chicati ML, Oliveira RB de, Demattê JAM, Nanni MR. Non−invasive assessment, classification, and prediction of biophysical parameters using reflectance hyperspectroscopy [Internet]. Plants. 2023 ; 12( 13): 1-27.[citado 2024 ago. 23 ] Available from: https://doi.org/10.3390/plants12132526Vancouver
Falcioni R, Santos GLAA dos, Crusiol LGT, Antunes WC, Chicati ML, Oliveira RB de, Demattê JAM, Nanni MR. Non−invasive assessment, classification, and prediction of biophysical parameters using reflectance hyperspectroscopy [Internet]. Plants. 2023 ; 12( 13): 1-27.[citado 2024 ago. 23 ] Available from: https://doi.org/10.3390/plants12132526