Molecules, Vol. 29, Pages 565: Artificial Intelligence Sensing: Effective Flavor Blueprinting of Tea Infusions for a Quality Control Perspective
Molecules, Vol. 29, Pages 565: Artificial Intelligence Sensing: Effective Flavor Blueprinting of Tea Infusions for a Quality Control Perspective
Molecules doi: 10.3390/molecules29030565
Authors:
Andrea Caratti
Angelica Fina
Fulvia Trapani
Carlo Bicchi
Erica Liberto
Chiara Cordero
Federico Magagna
Tea infusions are the most consumed beverages in the world after water; their pleasant yet peculiar flavor profile drives consumer choice and acceptance and becomes a fundamental benchmark for the industry. Any qualification method capable of objectifying the product’s sensory features effectively supports industrial quality control laboratories in guaranteeing high sample throughputs even without human panel intervention. The current study presents an integrated analytical strategy acting as an Artificial Intelligence decision tool for black tea infusion aroma and taste blueprinting. Key markers validated by sensomics are accurately quantified in a wide dynamic range of concentrations. Thirteen key aromas are quantitatively assessed by standard addition with in-solution solid-phase microextraction sampling followed by GC-MS. On the other hand, nineteen key taste and quality markers are quantified by external standard calibration and LC-UV/DAD. The large dynamic range of concentration for sensory markers is reflected in the selection of seven high-quality teas from different geographical areas (Ceylon, Darjeeling Testa Valley and Castleton, Assam, Yu...
Source: Molecules - Category: Chemistry Authors: Andrea Caratti Angelica Fina Fulvia Trapani Carlo Bicchi Erica Liberto Chiara Cordero Federico Magagna Tags: Article Source Type: research