de Carvalho Couto Cinthia, Freitas-Silva Otniel, Morais Oliveira Edna Maria, Sousa Clara, Casal Susana
Food and Nutrition Graduate Program, Federal University of State of Rio de Janeiro, Av. Pasteur 296, Rio de Janeiro 22290-240, Brazil.
Embrapa Food Agroindustry, Av. das Américas 29501, Rio de Janeiro 23020-470, Brazil.
Foods. 2021 Dec 28;11(1):61. doi: 10.3390/foods11010061.
Roasted coffee has been the target of increasingly complex adulterations. Sensitive, non-destructive, rapid and multicomponent techniques for their detection are sought after. This work proposes the detection of several common adulterants (corn, barley, soybean, rice, coffee husks and robusta coffee) in roasted ground arabica coffee (from different geographic regions), combining near-infrared (NIR) spectroscopy and chemometrics (Principal Component Analysis-PCA). Adulterated samples were composed of one to six adulterants, ranging from 0.25 to 80% (/). The results showed that NIR spectroscopy was able to discriminate pure arabica coffee samples from adulterated ones (for all the concentrations tested), including robusta coffees or coffee husks, and independently of being single or multiple adulterations. The identification of the adulterant in the sample was only feasible for single or double adulterations and in concentrations ≥10%. NIR spectroscopy also showed potential for the geographical discrimination of arabica coffees (South and Central America).
烘焙咖啡一直是日益复杂掺假行为的目标。人们一直在寻找用于检测咖啡的灵敏、无损、快速且能进行多成分分析的技术。这项研究提出,结合近红外(NIR)光谱法和化学计量学(主成分分析-PCA)来检测烘焙磨制的阿拉比卡咖啡(来自不同地理区域)中几种常见的掺假物(玉米、大麦、大豆、大米、咖啡壳和罗布斯塔咖啡)。掺假样品由一至六种掺假物组成,含量范围为0.25%至80%(/)。结果表明,近红外光谱法能够区分纯阿拉比卡咖啡样品和掺假样品(对于所有测试浓度),包括罗布斯塔咖啡或咖啡壳,且无论掺假是单一还是多种情况。仅在单一或双重掺假且浓度≥10%时,才有可能识别样品中的掺假物。近红外光谱法还显示出对阿拉比卡咖啡(南美洲和中美洲)进行产地鉴别的潜力。