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J Chromatogr A

Title:		Artificial Intelligence decision-making tools based on comprehensive two-dimensional gas chromatography data: the challenge of quantitative volatilomics in food quality assessment
Author(s):		Squara S; Caratti A; Fina A; Liberto E; Spigolon N; Genova G; Castello G; Cincera I; Bicchi C; Cordero C;
Address:		"Dipartimento di Scienza e Tecnologia del Farmaco, Universita degli Studi di Torino, Via Pietro Giuria 9, Torino 10125, Italy. Soremartec Italia Srl, Piazzale Ferrero 1, Alba, Cuneo 12051, Italy. Dipartimento di Scienza e Tecnologia del Farmaco, Universita degli Studi di Torino, Via Pietro Giuria 9, Torino 10125, Italy. Electronic address: chiara.cordero@unito.it"
Journal Title:		J Chromatogr A
Year:		2023
Volume:		20230429
Issue:
Page Number:		464041 -
DOI:		10.1016/j.chroma.2023.464041
ISSN/ISBN:		1873-3778 (Electronic) 0021-9673 (Linking)
Abstract:		"Effective investigation of food volatilome by comprehensive two-dimensional gas chromatography with parallel detection by mass spectrometry and flame ionization detector (GCxGC-MS/FID) gives access to valuable information related to industrial quality. However, without accurate quantitative data, results transferability over time and across laboratories is prevented. The study applies quantitative volatilomics by multiple headspace solid phase microextraction (MHS-SPME) to a large selection of hazelnut samples (Corylus avellana L. n = 207) representing the top-quality selection of interest for the confectionery industry. By untargeted and targeted fingerprinting, performant classification models validate the role of chemical patterns strongly correlated to quality parameters (i.e., botanical/geographical origin, post-harvest practices, storage time and conditions). By quantification of marker analytes, Artificial Intelligence (AI) tools are derived: the augmented smelling based on sensomics with blueprint related to key-aroma compounds and spoilage odorant; decision-makers for rancidity level and storage quality; origin tracers. By reliable quantification AI can be applied with confidence and could be the driver for industrial strategies"
Keywords:		*Volatile Organic Compounds/analysis Artificial Intelligence Gas Chromatography-Mass Spectrometry/methods Food Quality Mass Spectrometry Odorants/analysis *Corylus/chemistry Solid Phase Microextraction Accurate odorants quantitation Aroma blueprint Artifi;
Notes:		"MedlineSquara, Simone Caratti, Andrea Fina, Angelica Liberto, Erica Spigolon, Nicola Genova, Giuseppe Castello, Giuseppe Cincera, Irene Bicchi, Carlo Cordero, Chiara eng Netherlands 2023/05/08 J Chromatogr A. 2023 Jul 5; 1700:464041. doi: 10.1016/j.chroma.2023.464041. Epub 2023 Apr 29"