| Title: | Rum classification using fingerprinting analysis of volatile fraction by headspace solid phase microextraction coupled to gas chromatography-mass spectrometry |
| Author(s): | Belmonte-Sanchez JR; Gherghel S; Arrebola-Liebanas J; Romero Gonzalez R; Martinez Vidal JL; Parkin I; Garrido Frenich A; |
| Address: | "Research Group 'Analytical Chemistry of Contaminants', Department of Chemistry and Physics, Research Centre for Agricultural and Food Biotechnology (BITAL), University of Almeria, Agrifood Campus of International Excellence, ceiA3, E-04120 Almeria, Spain. Research Group 'Analytical Chemistry of Contaminants', Department of Chemistry and Physics, Research Centre for Agricultural and Food Biotechnology (BITAL), University of Almeria, Agrifood Campus of International Excellence, ceiA3, E-04120 Almeria, Spain; UCL Department of Security and Crime Science, 35 Tavistock Square, London WC1H 9EZ, United Kingdom; UCL Department of Chemistry, 20 Gordon Street, London WC1H 0AJ, United Kingdom. UCL Department of Chemistry, 20 Gordon Street, London WC1H 0AJ, United Kingdom. Research Group 'Analytical Chemistry of Contaminants', Department of Chemistry and Physics, Research Centre for Agricultural and Food Biotechnology (BITAL), University of Almeria, Agrifood Campus of International Excellence, ceiA3, E-04120 Almeria, Spain. Electronic address: agarrido@ual.es" |
| DOI: | 10.1016/j.talanta.2018.05.025 |
| ISSN/ISBN: | 1873-3573 (Electronic) 0039-9140 (Linking) |
| Abstract: | "In this study, targeted and untargeted analyses based on headspace solid phase microextraction coupled to gas chromatography-mass spectrometry (HS-SPME-GC-MS) method were developed for classifying 33 different commercial rums. Targeted analysis showed correlation of ethyl acetate and ethyl esters of carboxylic acids with aging when rums of the same brand were studied, but presented certain limitations when the comparison was carried out between different brands. To overcome these limitations, untargeted strategies based on unsupervised treatments, such as hierarchical cluster analysis (HCA) and principal component analysis (PCA), as well as supervised methods, such as linear discriminant analysis (LDA) were applied. HCA allowed distinguishing main groups (with and without additives), while the PCA method indicated 40?ª+ions corresponding to 13 discriminant compounds as relevant chemical descriptors for the correct rum classification (PCA variance of 88%). The compounds were confirmed based on the combination of retention indexes and low and high-resolution mass spectrometry (HRMS). Using the obtained results, LDA was carried out for the analytical discrimination of the remaining rums based on manufacturing country, raw material type, distillation method, wood barrel type and aging period and 94%, 91%, 92%, 95% and 94% of rums, respectively, were correctly classified. The proposed methodology has led to a robust analytical strategy for the classification of rums as a function of different parameters depending on the rum production process" |
| Keywords: | Classification Multivariate analysis Rum Spme-gc-ms Volatile organic compounds; |
| Notes: | "PubMed-not-MEDLINEBelmonte-Sanchez, Jose Raul Gherghel, Simona Arrebola-Liebanas, Javier Romero Gonzalez, Roberto Martinez Vidal, Jose Luis Parkin, Ivan Garrido Frenich, Antonia eng Netherlands 2018/06/02 Talanta. 2018 Sep 1; 187:348-356. doi: 10.1016/j.talanta.2018.05.025. Epub 2018 May 8" |
