Application of multispectral imaging combined with machine learning models to discriminate special and traditional green coffee (2022)
- Authors:
- USP affiliated authors: MATTOS, WANESSA MELCHERT - ESALQ ; SILVA, CLÍSSIA BARBOZA DA - CENA ; GOMES, WINSTON PINHEIRO CLARO - CENA
- Unidades: ESALQ; CENA
- DOI: 10.1016/j.compag.2022.107097
- Subjects: ANÁLISE DE ALIMENTOS; APRENDIZADO COMPUTACIONAL; CAFÉ; ESPECTROSCOPIA; QUÍMICA DE ALIMENTOS; QUIMIOMETRIA
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Computers and Electronics in Agriculture
- ISSN: 0168-1699
- Volume/Número/Paginação/Ano: v. 198, art. 107097, p. 1-9, June 2022
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
GOMES, Winston Pinheiro Claro et al. Application of multispectral imaging combined with machine learning models to discriminate special and traditional green coffee. Computers and Electronics in Agriculture, v. 198, p. 1-9, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2022.107097. Acesso em: 09 fev. 2026. -
APA
Gomes, W. P. C., Gonçalves, L., Silva, C. B. da, & Melchert, W. R. (2022). Application of multispectral imaging combined with machine learning models to discriminate special and traditional green coffee. Computers and Electronics in Agriculture, 198, 1-9. doi:10.1016/j.compag.2022.107097 -
NLM
Gomes WPC, Gonçalves L, Silva CB da, Melchert WR. Application of multispectral imaging combined with machine learning models to discriminate special and traditional green coffee [Internet]. Computers and Electronics in Agriculture. 2022 ; 198 1-9.[citado 2026 fev. 09 ] Available from: https://doi.org/10.1016/j.compag.2022.107097 -
Vancouver
Gomes WPC, Gonçalves L, Silva CB da, Melchert WR. Application of multispectral imaging combined with machine learning models to discriminate special and traditional green coffee [Internet]. Computers and Electronics in Agriculture. 2022 ; 198 1-9.[citado 2026 fev. 09 ] Available from: https://doi.org/10.1016/j.compag.2022.107097 - Digital images and chemometric tools for predicting physicochemical parameters of beers
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Informações sobre o DOI: 10.1016/j.compag.2022.107097 (Fonte: oaDOI API)
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