The contribution illustrates the potentials of GC×GC-MS/FID platforms in the context of Artificial Intelligence Smelling and computer vision tools for extra-virgin olive oils characterization and identitation. By accurate quantification of key-aromas and odorants strongly correlated to sensory defects, samples’ aroma blueprint is captured and used to discriminate oils based on peculiar hedonic features.
Artificial Intelligence strategies based on GC×GC-MS/FID patterns capture extra-virgin olive oil aroma blueprint and unique identity
Chiara Cordero;Simone Squara;Federico Stilo;Andrea Caratti;Erica Liberto;Carlo Bicchi;
2022-01-01
Abstract
The contribution illustrates the potentials of GC×GC-MS/FID platforms in the context of Artificial Intelligence Smelling and computer vision tools for extra-virgin olive oils characterization and identitation. By accurate quantification of key-aromas and odorants strongly correlated to sensory defects, samples’ aroma blueprint is captured and used to discriminate oils based on peculiar hedonic features.
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