Sensomics, like other “omics” fields, cuts across chemistry and biology and so requires holistic strategies capable of comprehensively mapping the set of all potential ligands (e.g., sensometabolome) that trigger the multimodal perception of food flavor. These complex mixtures when directed to odor receptors in the nose, define the so-called Chemical Odor Code. Analytical chemistry is challenged to comprehensively map the complex volatile fractions of real samples, including odorants and interferents, and define univocal odor patterns for correlative studies. This review critically discusses state-of-the-art research in the field of odorants and volatiles characterization in food by comprehensive two-dimensional gas chromatography, illustrating how hyphenation with mass spectrometry and olfactometry, accurate quantitation, suitable sample preparation, and dedicated data mining can capture essential information on odor patterns exploiting the higher level of information on sample sensory features.

Characterization of odorant patterns by comprehensive two-dimensional gas chromatography: a challenge in omic studies

Chiara Cordero
First
;
Carlo Bicchi
Last
2019-01-01

Abstract

Sensomics, like other “omics” fields, cuts across chemistry and biology and so requires holistic strategies capable of comprehensively mapping the set of all potential ligands (e.g., sensometabolome) that trigger the multimodal perception of food flavor. These complex mixtures when directed to odor receptors in the nose, define the so-called Chemical Odor Code. Analytical chemistry is challenged to comprehensively map the complex volatile fractions of real samples, including odorants and interferents, and define univocal odor patterns for correlative studies. This review critically discusses state-of-the-art research in the field of odorants and volatiles characterization in food by comprehensive two-dimensional gas chromatography, illustrating how hyphenation with mass spectrometry and olfactometry, accurate quantitation, suitable sample preparation, and dedicated data mining can capture essential information on odor patterns exploiting the higher level of information on sample sensory features.
2019
113
364
378
comprehensive two-dimensional gas chromatography, sensomics, chemical odor code, multidimensional analytical platforms, data mining, odor fingerprints
Chiara Cordero, Johannes Kiefl, Stephen E. Reichenbach, Carlo Bicchi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1669700
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