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AI-guided Aspergillus oryzae bioconversion of cucumber-peanut substrates produces an umami-rich,chicken-like flavor for plant-based meat alternatives
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作者 Rodrigo A.Contreras Patricio Caripan +10 位作者 Nicole Ferrada Macarena Cantero Marisol Pizarro Ana Batista-Gonzalez Hector Henríquez matthew sujanto Camila Covarrubias Claudia Vidal Carla Pino Romina Ansaldo Bernardo Moltedo 《Food Bioscience》 2026年第5期2093-2106,共14页
Aspergillus oryzae is widely used in traditional koji production,although its application in targeted savory design in plant-based foods remains limited.Here,we applied an AI-guided bioconversion framework integrating... Aspergillus oryzae is widely used in traditional koji production,although its application in targeted savory design in plant-based foods remains limited.Here,we applied an AI-guided bioconversion framework integrating sensory analysis and metabolomics to derive an umami-rich,chicken-like seasoning from cucumber and peanut.Bayesian optimization was used to refine the substrate ratio and incubation time,identifying 5%cucumber and 5%peanut incubated for 7 days as the optimal conditions.This formulation increased the intensities of umami and chicken-like flavor,reduced off-flavors,and enhanced savory perception when incorporated at 1%(w/w)into a neutral plant-protein nugget model.Untargeted LC-MS and GC-MS analyses identified 52 discriminant metabolites organized into coherent biochemical modules.Integrated chemometrics linked carbohydrate-derived substrates to fungal glutamate,succinate,and 5′-nucleotides,while phenylpropanoid and triterpenoid modules aligned with mushroom notes and the suppression of savory attributes.The results indicate that AI-directed A.oryzae bioconversion provides a basis for the mechanistically informed construction of umami flavor sys-tems from simple botanical substrates. 展开更多
关键词 Artificial intelligence Aspergillus oryzae Bayesian optimization Metabolomics Plant-based meat alternatives
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