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Computational Gastronomy is an emerging interdisciplinary field that merges the principles of computational science with the art of cooking, utilizing data-driven techniques to analyze food from multiple perspectives, including recipes, flavors, nutrition, and sustainability. A significant challenge in computational gastronomy is the need for high-quality, well-structured data on food, particularly concerning traditional recipes from around the world. Due to food's subjective nature and complexity, quantifying sensory experiences like taste remains difficult[1].
Researchers use mathematical models, algorithms, and software to navigate this complexity, studying the intricate relationships between food, health, and the gut microbiome.[2]. The field holds the potential to transform culinary practices through innovations in recipe generation, food design, and customized nutrition, with applications extending beyond individual dietary practices to broader implications for public health, sustainability, and the global food industry[3]
References
edit- ^ Mwaura, Ngugi (September 2024). "The Role of Artificial Intelligence in Personalized Nutrition".
- ^ Eetemadi, Ameen; Rai, Navneet; Pereira, Beatriz Merchel Piovesan; Kim, Minseung; Schmitz, Harold; Tagkopoulos, Ilias (2020-04-03). "The Computational Diet: A Review of Computational Methods Across Diet, Microbiome, and Health". Frontiers in Microbiology. 11. doi:10.3389/fmicb.2020.00393. ISSN 1664-302X.
- ^ Ascorbe Landa, Cristina (2018-06-12). "[Nearby food and gastronomy: a rising value?]". Nutricion Hospitalaria. 35 (Spec No4): 44–48. doi:10.20960/nh.2124 (inactive 1 November 2024). ISSN 1699-5198. PMID 30070121.
{{cite journal}}: CS1 maint: DOI inactive as of November 2024 (link)