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Raman spectroscopy for the differentiation of Arabic coffee genotypes.
Figueiredo, Luisa Pereira; Borém, Flávio Meira; Almeida, Mariana Ramos; Oliveira, Luiz Fernando Cappa de; Alves, Ana Paula de Carvalho; Santos, Cláudia Mendes Dos; Rios, Paula Almeida.
Affiliation
  • Figueiredo LP; Departamento de Ciência dos Alimentos, Universidade Federal de Lavras, P.O. Box: 3037, Lavras, MG 37200-000, Brazil. Electronic address: luisa.figueiredo@ufla.br.
  • Borém FM; Departamento de Engenharia, Universidade Federal de Lavras, P.O. Box: 3037, Lavras, MG 37200-000, Brazil.
  • Almeida MR; Departamento de Química, Universidade Federal de Minas Gerais, Av. Antônio Carlos, n° 6627, Belo Horizonte, MG 31270-901, Brazil.
  • Oliveira LFC; Departamento de Química, Universidade Federal de Juiz de Fora, Rua José Lourenço Kelmer, s/n - Campus Universitário, Juiz de Fora, MG 36036-900, Brazil. Electronic address: luiz.oliveira@ufjf.edu.br.
  • Alves APC; Departamento de Engenharia, Universidade Federal de Lavras, P.O. Box: 3037, Lavras, MG 37200-000, Brazil.
  • Santos CMD; Departamento de Engenharia, Universidade Federal de Lavras, P.O. Box: 3037, Lavras, MG 37200-000, Brazil. Electronic address: claumsantos@yahoo.com.br.
  • Rios PA; Departamento de Engenharia, Universidade Federal de Lavras, P.O. Box: 3037, Lavras, MG 37200-000, Brazil. Electronic address: paulariosagricola@gmail.com.
Food Chem ; 288: 262-267, 2019 Aug 01.
Article in En | MEDLINE | ID: mdl-30902291
The objective of this study was to evaluate the ability of Raman spectroscopy to identify the genotype of green coffee beans. Four genotypes of Arabic coffee: one Mundo Novo line (G1) and three Bourbon lines (G2, G3, and G4). The harvest was selected using a wet processing method. Raman spectra of the samples were obtained using a FT-Raman RFS/100 spectrometer in the spectral range of 3500-400 cm-1. The data were treated using chemometric unsupervised classification tools and supervised analysis. Using the unsupervised analysis (PCA), the apparent tendency of agglomeration between samples G1 and G3 was verified. These differences were present in the spectral bands that are characteristic of fatty acids and kahweol. Based on this information, a classification model to discriminate (PLS-DA) the Mundo Novo and Bourbon samples was utilized. Raman spectroscopy allowed the building of an adequate model to differentiate between coffee genotypes.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Spectrum Analysis, Raman / Coffea Type of study: Prognostic_studies Language: En Journal: Food Chem Year: 2019 Type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Spectrum Analysis, Raman / Coffea Type of study: Prognostic_studies Language: En Journal: Food Chem Year: 2019 Type: Article