Sensory quality prediction of coffee assessed by physicochemical parameters and Multivariate model

• Autor(a) principal: Domingues, Laricia Oliveira Cardoso; et. al.
• Data de Publicação: 2020
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório do Instituto de Tecnologia de Alimentos
• Texto Completo: http://repositorio.ital.sp.gov.br/jspui/handle/123456789/186
• topic: Coffee quality; Sensory; Chemometrics; OCC

Beverages from roasted coffee can be classified according to their sensory quality into Gourmet, Superior, Traditional, and not recommended for supply coffees. However, the sensory evaluation of coffee has been questioned as it can induce a subjective bias, since the assessors may be influenced by psychological, physiological, and/or emotional factors. Therefore, the aim of this study was to develop multivariate models for predicting the overall quality of Gourmet, Superior, and Traditional coffees, based on the physical and physicochemical parameters. One hundred and eight ground roasted coffee samples were evaluated for particle size, degree of roasting, histological identification, moisture, ash, aqueous extract, soluble solids (Brix), pH, and sensory profiling. All categories presented fine grinding. No significant differences were observed in the moisture content and soluble solids (Brix) of Gourmet, Superior, Traditional, not recommended for supply coffee samples. The Traditional and not recommended for supply presented higher levels of aqueous extract, ash, and pH. Light degree of roast and higher acidity values were observed with the increase in coffee quality grades. The results of the physical and physicochemical parameters and the principal component analysis allowed the separation of coffees into only two classes: high-quality (Gourmet and Superior) and low-quality (Traditional and not recommended). Furthermore, the one-class classification (OCC) method showed good sensitivity and was able to satisfactorily distinguish the Gourmet coffee samples from the other samples, in this way, this model can be used to corroborate but not replace the sensory analysis.