Harnessing artificial intelligence for the analysis of complex chemical combinations, paving the way for novel flavors in food manufacturing: A comprehensive review
Year: 2025
Type: article
Abstract: • AI enables novel flavor creation through chemical and sensory data analysis. • Machine learning personalizes taste prediction beyond traditional methods. • Case studies reveal AI’s power to reshape flavor innovation in food design. • Ethical limits and data diversity remain major challenges for AI in food. The integration of artificial intelligence (AI) into flavor development is reshaping the food industry by enhancing precision, efficiency, and innovation. This review synthesizes the current advancements in AI-driven flavor creation, from chemical analysis to sensory optimization and market alignment. Traditional flavor development methods rooted in empirical knowledge and sensory panels are increasingly limited by subjectivity, scalability, and reproducibility. AI overcomes these limitations by leveraging machine learning algorithms to analyze complex chemical interactions, predict consumer preferences, and generate novel flavor profiles. Drawing from an extensive literature search across ScienceDirect, PubMed, Web of Science, and Scopus (2015–2025), we analyzed empirical studies, review articles, and industrial case reports selected for relevance. A thematic synthesis shows key trends, including the application of deep learning for unstructured sensory data, the use of odor activity values (OAVs) and electronic noses in quantitative olfactory modelling, and successful industrial implementations in product innovation. Challenges related to model interpretability, data bias, and regulatory acceptance are critically discussed. Future directions emphasize the need for culturally inclusive datasets, interdisciplinary collaboration, and integration of sensory neuroscience. This review underscores the transformative potential of AI as a strategic tool in flavor science, bridging molecular data, human perception, and consumer demands to foster next-generation food design.
Source: Food Chemistry Advances
Language: English
Subfield: Food Science
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,080
OpenAlex ID: W4416415385