Authentication of roasted and ground coffee samples containing multiple adulterants using NMR and a chemometric approach. (June 2020)

• Record Type: Journal Article
• Authors: Milani, Maria Izabel; Rossini, Eduardo Luiz; Catelani, Tiago Augusto; Pezza, Leonardo; Toci, Aline Theodoro; Pezza, Helena Redigolo
• Is Part Of: Food control. Volume 112(2020)
• Publication Date: 2020-06
• Subjects: Coffee authentication -- Quality control -- Nuclear magnetic resonance -- Chemometrics -- SIMCA; Food -- Quality -- Periodicals; Food -- Analysis -- Periodicals; Food handling -- Periodicals; Food industry and trade -- Quality control -- Periodicals; Aliments -- Industrie et commerce -- Qualité -- Contrôle -- Périodiques; Aliments -- Qualité -- Périodiques; Aliments -- Analyse -- Périodiques; Hygiène alimentaire -- Périodiques; Food -- Analysis; Food handling; Food -- Quality; Periodicals; Electronic journals; 664.07
• DOI: 10.1016/j.foodcont.2020.107104
• Languages: English
• ISSNs: 0956-7135

Abstract

Abstract: Brazil is still the world's largest producer and exporter of coffee. In order to maximize profits, some producers may add lower cost materials (such as corn, barley, or even coffee husks) to commercial coffee. In view of the growing market for coffee products and the importance of coffee for the Brazilian economy, it is necessary to have a rapid, simple, and reliable methodology to identify and quantify coffee adulterants. NMR has proved to be a versatile and robust tool for the identification of adulterants in foods and beverages. Here, we explore the versatility of 1 H NMR assisted with chemometric tools, avoiding laborious data analysis, for the quantification of coffee adulteration. Six different adulterants were considered: barley, corn, coffee husks, soybean, rice, and wheat. The NMR-based methodology described here provided satisfactory LOD values (0.31–0.86%) for adulterants in medium and dark roast coffees. The statistical techniques PCA and SIMCA were employed for pattern recognition and the identification of pure and adulterated samples. Use of the SIMCA model enabled 100% correct classification for both training and prediction sets, ensuring the accuracy, traceability, and reliability of the results. Highlights: A fast, eco-friendly, and easy method for determination of coffee adulterants. Quantification of six different adulterants in roasted coffee using 1 H NMR. Chemometric tools assist in identifying adulterated coffee samples. PCA differentiation between pure and adulterated roasted coffee samples.