A pilot study of NMR-based sensory prediction of roasted coffee bean extracts

• Published in: Food chemistry 2014-06, Vol.152, p.363-369
• Main Authors: Wei, Feifei, Furihata, Kazuo, Miyakawa, Takuya, Tanokura, Masaru
• Format: Article
• Language: English
• Subjects: Beans; Biological and medical sciences; Coffea - chemistry; Coffee; Cooking; Food toxicology; Foods; Forecasting; Hot Temperature; Humans; Magnetic Resonance Spectroscopy - methods; Mathematical models; Medical sciences; Multivariate analysis; NMR; Nuclear magnetic resonance; OPLS; Pilot Projects; Plant Extracts - chemistry; Projection; Roasted coffee beans; Seeds - chemistry; Sensory analysis; Sensory prediction; Taste; Toxicology
• ISSN: 0308-8146; 1873-7072
• DOI: 10.1016/j.foodchem.2013.11.161

•We investigated the utility of NMR as a potential tool to analyse the taste of coffee.•Chemical substances that could distinguish the different sensations were identified.•We successfully predicted the tastes of commercial coffee beans based on NMR.•NMR with OPLS is convenient and accurate for the sensory evaluation of coffee. Nuclear magnetic resonance (NMR) spectroscopy can be considered a kind of “magnetic tongue” for the characterisation and prediction of the tastes of foods, since it provides a wealth of information in a nondestructive and nontargeted manner. In the present study, the chemical substances in roasted coffee bean extracts that could distinguish and predict the different sensations of coffee taste were identified by the combination of NMR-based metabolomics and human sensory test and the application of the multivariate projection method of orthogonal projection to latent structures (OPLS). In addition, the tastes of commercial coffee beans were successfully predicted based on their NMR metabolite profiles using our OPLS model, suggesting that NMR-based metabolomics accompanied with multiple statistical models is convenient, fast and accurate for the sensory evaluation of coffee.