Computational gastronomy is an interdisciplinary field combining computational science with culinary studies. It applies data-driven techniques to analyze various aspects of food, including recipes, flavors, nutrition, and sustainability. The field utilizes advancements in data analytics, machine learning, and computational models to systematically study food and optimize culinary practices.[1] Applications of computational gastronomy include recipe optimization, flavor profiling, nutritional analysis, and personalized dietary recommendations.
- ^ Bagler, Ganesh; Goel, Mansi (2024-07-08). "Computational gastronomy: capturing culinary creativity by making food computable". npj Systems Biology and Applications. 10 (1): 72. doi:10.1038/s41540-024-00399-5. ISSN 2056-7189. PMC 11231233. PMID 38977713.