Araújo, Eloá Moura; Lima, Márcio Dias de; Barbosa, Rommel; Alleoni, Luís Reynaldo Ferracciú 
Source: Food Analytical Methods. Unidade: ESALQ
Subjects: APRENDIZADO COMPUTACIONAL, COMPONENTES PRINCIPAIS, COMPOSIÇÃO QUÍMICA, PRODUTOS AGRÍCOLAS ORGÂNICOS
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ARAÚJO, Eloá Moura et al. Using machine learning and multi-element analysis to evaluate the authenticity of organic and conventional vegetables. Food Analytical Methods, v. 12, n. 11, p. 2542-2554, 2019Tradução . . Disponível em: https://doi.org/10.1007/s12161-019-01597-2. Acesso em: 11 nov. 2024.APA
Araújo, E. M., Lima, M. D. de, Barbosa, R., & Alleoni, L. R. F. (2019). Using machine learning and multi-element analysis to evaluate the authenticity of organic and conventional vegetables. Food Analytical Methods, 12( 11), 2542-2554. doi:10.1007/s12161-019-01597-2NLM
Araújo EM, Lima MD de, Barbosa R, Alleoni LRF. Using machine learning and multi-element analysis to evaluate the authenticity of organic and conventional vegetables [Internet]. Food Analytical Methods. 2019 ; 12( 11): 2542-2554.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1007/s12161-019-01597-2Vancouver
Araújo EM, Lima MD de, Barbosa R, Alleoni LRF. Using machine learning and multi-element analysis to evaluate the authenticity of organic and conventional vegetables [Internet]. Food Analytical Methods. 2019 ; 12( 11): 2542-2554.[citado 2024 nov. 11 ] Available from: https://doi.org/10.1007/s12161-019-01597-2
