Events Diary
The BSF is delighted to welcome prof. Chiara Cordero for her talk: "Artificial Intelligence Smelling: can multidimensional chromatography play a (key) role?"
Abstract:
Multidimensional chromatography has been successfully applied for many years as core technology for odorant patterns characterisation in the flavour and fragrance field. Very recently a sensomics-based expert system (SEBES) [1] capable to predict key-aroma signatures of food without using human olfaction has been implemented in a comprehensive two-dimensional gas chromatography (GC×GC) platform. The strategy, also referred to as Artificial Intelligence Smelling, conceptually opens many opportunities for odorants pattern recognition, accurate quantification avoiding time-consuming sample preparation/extraction steps, and samples sensory qualification/discrimination based on computer vision strategies. Moreover, due to the information density of each analysis, fingerprinting can be extended to different samples features (e.g., origin traceability, shelf-life evolution, processing impact etc.).
The contribution illustrates the potentials of MDGC platforms in the context of Artificial Intelligence Smelling and extended untargeted/targeted fingerprinting through a key-food product for confectionery industry: high-quality hazelnuts (Corylus avellana L.).
Sensory quality of raw and roasted hazelnuts depends to the presence of non-volatile precursors patterns and to (key)-aroma compounds in well-balanced proportions. Moreover, odorants deriving by lipid oxidation processes and/or enzyme-catalysed reactions carried out by bacteria and moulds [2,3] might evoke unpleasant notes with detrimental impact on kernels quality.
Odorant patterns, strongly correlated to sensorial qualities, can be effectively detected by computer vision with composite-class images generated combining 2D chromatographic signals from samples showing specific features (e.g., good reference kernels, spoiled kernels with mould, rancid, stale, solvent-like odors). On the other hand, the comprehensive exploration of the detectable volatilome (including all volatiles) by untargeted/targeted fingerprinting drives machine learning toward samples identification highlighting botanical/geographical signatures [4], shelf-life trajectories, and climate impact on hazelnut metabolome.
The virtuous synergy between Academic research and industry defines new quality concepts, accelerates innovation, and shapes the future of our food. The key is the implementation of modern omics concepts and strategies that bring food analysis closer to flavour characterisation.
The speaker:
Chiara Cordero is Full Professor of Food Chemistry at the University of Turin (Italy).
Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via P. Giuria 9, I-10125 Turin, Italy email:
ORCID ID: https://orcid.org/0000-0003-3201-0775
Scopus ID: 7004576406
Web of Science ResearcherID: I-7858-2012
Research interests focus on: (a) development of innovative and advanced instrumental configurations for detailed chemical characterisation of food (profiling and fingerprinting strategies based on multidimensional platforms); (b) development and application of miniaturized, fully automated and solvent-free sample preparation approaches (Solid Phase Microextraction SPME, Stir Bar Sorptive Extraction SBSE) for sensomic characterisation of food; (c) discovery of food intake markers (low molecular weight metabolites, Advanced Glycation End-products and volatiles in bio-fluids) and metabolic fingerprint after diet induced derangements. In 2008, she was awarded with the "Leslie S. Ettre” Award for “original research in capillary gas chromatography with an emphasis on environmental and food safety" and in 2014 received the “John B. Phillips Award” for her research activity in the field of comprehensive two-dimensional gas chromatography (GC×GC). In 2016 Chiara was included by The Analytical Scientist in the “Women Power List” as one of the 50 most influencing women in the analytical sciences.
References
- Nicolotti, L.; Mall, V.; Schieberle, P. J. Agric. Food Chem., 67 (2019) 4011–4022
- Kiefl, J.; Pollner, G.; Schieberle, P. J. Agric. Food Chem. 61 (2013) 5226–5235.
- Stilo, F.; Liberto, E.; Spigolon, N.; Genova, G.; Rosso, G.; Fontana, M.; Reichenbach, S.E.; Bicchi, C.; Cordero, C. Food Chem. 340 (2021) 128135.
- Stilo, F., Bicchi, C., Jimenez-Carvelo, A.M., Cuadros-Rodriguez, L., Reichenbach, S.E., Cordero, C. TrAC Trends Anal. Chem. 134 (2021) 116133.