Alves, V.C.D.; de Lima, S.F.; Santana, D.C.; Barreto, R.F.; da Cunha, R.A.; da Silva Cândido Seron, A.C.; Teodoro, L.P.R.; Teodoro, P.E.; de Cássia Félix Alvarez, R.; Campos, C.N.S.;
et al. Predicting Pineapple Quality from Hyperspectral Data of Plant Parts Applied to Machine Learning. AgriEngineering 2025, 7, 170.
https://doi.org/10.3390/agriengineering7060170
AMA Style
Alves VCD, de Lima SF, Santana DC, Barreto RF, da Cunha RA, da Silva Cândido Seron AC, Teodoro LPR, Teodoro PE, de Cássia Félix Alvarez R, Campos CNS,
et al. Predicting Pineapple Quality from Hyperspectral Data of Plant Parts Applied to Machine Learning. AgriEngineering. 2025; 7(6):170.
https://doi.org/10.3390/agriengineering7060170
Chicago/Turabian Style
Alves, Vitória Carolina Dantas, Sebastião Ferreira de Lima, Dthenifer Cordeiro Santana, Rafael Ferreira Barreto, Roger Augusto da Cunha, Ana Carina da Silva Cândido Seron, Larissa Pereira Ribeiro Teodoro, Paulo Eduardo Teodoro, Rita de Cássia Félix Alvarez, Cid Naudi Silva Campos,
and et al. 2025. "Predicting Pineapple Quality from Hyperspectral Data of Plant Parts Applied to Machine Learning" AgriEngineering 7, no. 6: 170.
https://doi.org/10.3390/agriengineering7060170
APA Style
Alves, V. C. D., de Lima, S. F., Santana, D. C., Barreto, R. F., da Cunha, R. A., da Silva Cândido Seron, A. C., Teodoro, L. P. R., Teodoro, P. E., de Cássia Félix Alvarez, R., Campos, C. N. S., da Silva Junior, C. A., & Mingotte, F. L. C.
(2025). Predicting Pineapple Quality from Hyperspectral Data of Plant Parts Applied to Machine Learning. AgriEngineering, 7(6), 170.
https://doi.org/10.3390/agriengineering7060170
