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Mid infrared spectroscopy and chemometrics as tools for the classification of roasted coffees by cup quality.
Craig, Ana Paula; Botelho, Bruno G; Oliveira, Leandro S; Franca, Adriana S.
Affiliation
  • Craig AP; PPCCA/Universidade Federal de Minas Gerais, Av. Antônio Carlos, 6627, 31270-901 Belo Horizonte, MG, Brazil.
  • Botelho BG; DQ/Universidade Federal de Minas Gerais, Av. Antônio Carlos, 6627, 31270-901 Belo Horizonte, MG, Brazil.
  • Oliveira LS; DEMEC/Universidade Federal de Minas Gerais, Av. Antônio Carlos, 6627, 31270-901 Belo Horizonte, MG, Brazil. Electronic address: leandro@demec.ufmg.br.
  • Franca AS; DEMEC/Universidade Federal de Minas Gerais, Av. Antônio Carlos, 6627, 31270-901 Belo Horizonte, MG, Brazil. Electronic address: adriana@demec.ufmg.br.
Food Chem ; 245: 1052-1061, 2018 Apr 15.
Article in En | MEDLINE | ID: mdl-29287322
Sensory (cup) analysis is a reliable methodology for green coffee quality evaluation, but faces barriers when applied to commercial roasted coffees due to lack of information on roasting conditions. The aim of this study was to examine the potential of mid-infrared spectroscopy for predicting cup quality of arabica coffees of different roasting degrees. PCA analysis showed separation of arabica and robusta. A two-level PLS-DA Hierarchical strategy was employed, with coffee being classified as high or low quality in the first level and then separated according to cup quality in the second level. Validation results showed that the second level models exhibited 100% sensitivity and specificity in the training sets. For the test set, sensitivity ranged from 67% (rio zona) to 100% (soft) while specificity ranged from 71% (rio) to 100% (rioysh, hard). Thus, the proposed method can be used for the quality evaluation of arabica coffees regardless of roasting conditions.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Food Quality / Coffee / Informatics / Food Handling Type of study: Prognostic_studies Language: En Journal: Food Chem Year: 2018 Document type: Article Affiliation country: Brazil Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Food Quality / Coffee / Informatics / Food Handling Type of study: Prognostic_studies Language: En Journal: Food Chem Year: 2018 Document type: Article Affiliation country: Brazil Country of publication: United kingdom