Fast and Non-Destructive Profiling of Commercial Coffee Aroma under Three Conditions (Beans, Powder, and Brews) Using GC-IMS

• Published in: Molecules (Basel, Switzerland) Vol. 27; no. 19; p. 6262
• Main Authors: Chen, Yanping, Chen, He, Cui, Dandan, Fang, Xiaolei, Gao, Jie, Liu, Yuan
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 23.09.2022; MDPI
• Subjects: Alcohol; Alcohols; Aldehydes; Amino acids; Aroma; Beans; Biomarkers; Chromatography; Coffee; E-nose; Electronic noses; Esters; Factor analysis; Flavor; Flavors; Furans; Gas chromatography; GC-IMS; Ionic mobility; Ketones; Least squares method; Marketing; Mass spectrometry; Odors; Organic compounds; Pesticides; Principal components analysis; Scientific imaging; Spectrometry; Sulfur; VOCs; volatile organic components; Volatile organic compounds; China
• DOI: 10.3390/molecules27196262
• ISSN: 1420-3049

The flavor of coffee can be affected by the preparation parameters. In this investigation, the flavor profiles of three coffee brands under three conditions (bean, powder, and brew) were analyzed by gas chromatography—ion mobility spectrometry (GC-IMS) and the electronic nose (E-nose). The flavor results were further studied using multiple factor analysis (MFA). A total of 117 peaks were identified in all coffee samples by GC-IMS, and the principal component analysis (PCA) showed these coffee samples could be grouped and separated. A total of 37 volatile organic compounds (VOCs) were selected as biomarkers to distinguish coffee samples, including 5 aldehydes, 10 ketones, 8 alcohols, 2 acids, 4 esters, 5 furans, and 3 other compounds. The comparison between E-nose and GC-IMS data using partial least squares regression (PLSR) and MFA showed GC-IMS could present very close sample spaces. Compared with E-nose, GC–IMS could not only be used to classify coffee samples in a very short time but also provide VOC bio-markers to discriminate coffee samples.