| Title: | HS-SPME-MS-Enose Coupled with Chemometrics as an Analytical Decision Maker to Predict In-Cup Coffee Sensory Quality in Routine Controls: Possibilities and Limits |
| Author(s): | Liberto E; Bressanello D; Strocchi G; Cordero C; Ruosi MR; Pellegrino G; Bicchi C; Sgorbini B; |
| Address: | "Dipartimento di Scienza e Tecnologia del Farmaco, Universita degli Studi di Torino, 10125 Turin, Italy. Luigi Lavazza S.p.A, Strada Settimo 410, 10156 Turin, Italy" |
| DOI: | 10.3390/molecules24244515 |
| ISSN/ISBN: | 1420-3049 (Electronic) 1420-3049 (Linking) |
| Abstract: | "The quality assessment of the green coffee that you will go to buy cannot be disregarded from a sensory evaluation, although this practice is time consuming and requires a trained professional panel. This study aims to investigate both the potential and the limits of the direct headspace solid phase microextraction, mass spectrometry electronic nose technique (HS-SPME-MS or MS-EN) combined with chemometrics for use as an objective, diagnostic and high-throughput technique to be used as an analytical decision maker to predict the in-cup coffee sensory quality of incoming raw beans. The challenge of this study lies in the ability of the analytical approach to predict the sensory qualities of very different coffee types, as is usual in industry for the qualification and selection of incoming coffees. Coffees have been analysed using HS-SPME-MS and sensory analyses. The mass spectral fingerprints (MS-EN data) obtained were elaborated using: (i) unsupervised principal component analysis (PCA); (ii) supervised partial least square discriminant analysis (PLS-DA) to select the ions that are most related to the sensory notes investigated; and (iii) cross-validated partial least square regression (PLS), to predict the sensory attribute in new samples. The regression models were built with a training set of 150 coffee samples and an external test set of 34. The most reliable results were obtained with acid, bitter, spicy and aromatic intensity attributes. The mean error in the sensory-score predictions on the test set with the available data always fell within a limit of +/-2. The results show that the combination of HS-SPME-MS fingerprints and chemometrics is an effective approach that can be used as a Total Analysis System (TAS) for the high-throughput definition of in-cup coffee sensory quality. Limitations in the method are found in the compromises that are accepted when applying a screening method, as opposed to human evaluation, in the sensory assessment of incoming raw material. The cost-benefit relationship of this and other screening instrumental approaches must be considered and weighed against the advantages of the potency of human response which could thus be better exploited in modulating blends for sensory experiences outside routine" |
| Keywords: | Biosensing Techniques Coffee/*chemistry *Food Quality *Mass Spectrometry Reproducibility of Results *Solid Phase Microextraction/methods Volatile Organic Compounds/*analysis/*isolation & purification Workflow HS-SPME-MS-enose chemometrics coffee predictio; |
| Notes: | "MedlineLiberto, Erica Bressanello, Davide Strocchi, Giulia Cordero, Chiara Ruosi, Manuela Rosanna Pellegrino, Gloria Bicchi, Carlo Sgorbini, Barbara eng Switzerland 2019/12/15 Molecules. 2019 Dec 10; 24(24):4515. doi: 10.3390/molecules24244515" |
