Busca avançada
Ano de início
Entree


Texto completo
Autor(es):
de Moraes-Neto, Venancio Ferreira ; Baqueta, Michel Rocha ; Teixeira, Alexsandro Lara ; Carames, Elem Tamirys dos Santos ; Pallone, Juliana Azevedo Lima
Número total de Autores: 5
Tipo de documento: Artigo Científico
Fonte: Food Research International; v. 220, p. 10-pg., 2025-11-01.
Resumo

There is a need to develop efficient analytical methods to recognize the origins of coffee beans, especially from large producers such as Brazil, which offers high value-added Geographical Indication (GI) coffees. However, the challenge is not only the need for fast and clean techniques but also understanding how sample preparation and data treatments directly affect the performance of the applied technique. In this study, Near Infrared (NIR) Spectroscopy was combined with Partial Least Squares Discriminant Analysis (PLS-DA) to assess the ability to discriminate green coffee samples with recognized GI (Robusta Amazonico from Rondonia and Conilon from Espirito Santo), examining the influence of sample presentation (ground or whole bean) and spectral preprocessing. The results demonstrated that NIR performed with high efficiency for both whole beans and ground green coffee, achieving 100 % correct prediction. The most effective pre-processing was the combination of the 1st derivative of Savitzky-Golay and Multiplicative Scatter Correction (MSC). This suggests that the technique can be used for rapid discrimination in green coffee trading, with the direct analysis of natural whole beans being much more advantageous, as it avoids milling, which requires liquid nitrogen and a specific mill. Thus, NIR coupled with PLS-DA is a non-invasive, easy-to-operate, low-cost, and sensitive technique that can be applied directly to intact canephora coffee samples. (AU)

Processo FAPESP: 22/03268-3 - Técnicas analíticas alternativas e ensaios de digestão in vitro para alimentos especiais
Beneficiário:Juliana Azevedo Lima Pallone
Modalidade de apoio: Auxílio à Pesquisa - Regular
Processo FAPESP: 21/14060-1 - Foodomics e análise multivariada no controle de micotoxinas em cevada
Beneficiário:Elem Tamirys dos Santos Caramês
Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado