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Tea prepared by infusion of dried leaves of Camellia sinensis (L.) Kuntze, is the second world's most popular beverage, after water. Its consumption is associated with its chemical composition: it influences its sensory and nutritional quality addressing consumer preferences, and potential health benefits. This study aims to obtain an informative chemical signature of the volatile fraction of black tea samples from Ceylon by applying the principles of sensomics. In particular, several high concentration capacity (HCC) sample preparation techniques were tested in combination with GC×GC-MS to investigate chemical signatures of black tea volatiles. This platform, using headspace solid phase microextraction (HS-SPME) with multicomponent fiber as sampling technique, recovers 95% of the key-odorants in a fully automated work-flow. A group 123 components, including key-odorants, technological and botanical tracers, were mapped. The resulting 2D fingerprints were interpreted by pattern recognition tools (i.e. template matching fingerprinting and scripting) providing highly informative chemical signatures for quality assessment., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

The volatile fractions of six Italian high-quality rice cultivars were investigated by HS-SPME-GC-MS to define fingerprinting and identify chemical markers and/or indices of ageing and aroma quality. In particular, four non-aromatic (Carnaroli, Carnise, Cerere and Antares) and two aromatic (Apollo and Venere) rices, harvested in 2010 and 2011, were monitored over 12months. Twenty-five aroma components were considered and, despite considerable inter-annual variability, some of them showed similar trends over time, including 2-(E)-octenal as a marker of ageing for all cultivars, and heptanal, octanal and 2-ethyl hexanol as cultivar-specific indicators. The area ratios 2-acetyl-1-pyrroline/1-octen-3-ol, for Venere, and 3-methyl-1-butanol/2-methyl-1-butanol, for Apollo, were also found to act as ageing indices. Additional information on release of key-aroma compounds was also obtained from quantitation and its dependence on grain shape and chemical composition. Heptanal/1-octen-3-ol and heptanal/octanal ratios were also defined as characterising the aroma quality indices of the six Italian rice cultivars investigated., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

The study proposes an investigation strategy to identify sensitive, robust and reliable chemical markers of hazelnut roasting. A fully-automated and validated analytical method, based on Headspace Solid Phase Microextraction (HS-SPME) coupled with Gas Chromatography-Mass Spectrometric detection (GC-MS), for effective off-line monitoring of changes in the volatile profile of high-quality hazelnuts was developed. Samples from two different harvests were submitted to roasting, following different time/temperature protocols and different technologies, enabling chemical changes to be correlated with technological processing and sensory quality. Chemical indices, expressed as analyte response ratio, were defined and their trend observed across roasting profiles. Reliability and robustness of chemical indices were also evaluated, in view of their application to on-line monitoring with Mass Spectrometry-based electronic nose technology (MS-nose). Experiments, simulating on-line chemical characterisation of the volatile fraction, were performed through a fully-automated system. The results confirmed: (a) the effectiveness of single process indicators of roasting selected by the separative method (5-methylfurfural, 1(H)-pyrrole, furfuryl alcohol, 1(H)-pyrrole-2-carboxaldehyde, 1-hydroxy-2-propanone, dihydro-2(3H)-furanone, 5-methyl-(E)-2-hepten-4-one, acetic acid, pyridine, furfural, pyrazine, and several alkyl-pyrazines); and, (b) the reliability of proposed chemical indices: 5-methylfurfural/2,5-dimethylpyrazine, 5-methylfurfural/2-methylpyrazine, 2,5-dimethylpyrazine/2,3-dimethylpyrazine; these maintained a consistent trend versus harvest and sampling/analysis technology., (Copyright © 2012 Elsevier Ltd. All rights reserved.)