Computational gastronomy: capturing culinary creativity by making food computable.

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY NPJ Systems Biology and Applications Pub Date : 2024-07-08 DOI:10.1038/s41540-024-00399-5
Ganesh Bagler, Mansi Goel
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Abstract

Cooking, a quintessential creative pursuit, holds profound significance for individuals, communities, and civilizations. Food and cooking transcend mere sensory pleasure to influence nutrition and public health outcomes. Inextricably linked to culinary and cultural heritage, food systems play a pivotal role in sustainability and the survival of life on our planet. Computational Gastronomy is a novel approach for investigating food through a data-driven paradigm. It offers a systematic, rule-based understanding of culinary arts by scrutinizing recipes for taste, nutritional value, health implications, and environmental sustainability. Probing the art of cooking through the lens of computation will open up a new realm of possibilities for culinary creativity. Amidst the ongoing quest for imitating creativity through artificial intelligence, an interesting question would be, 'Can a machine think like a Chef?' Capturing the experience and creativity of a chef in an AI algorithm presents an exciting opportunity for generating a galaxy of hitherto unseen recipes with desirable culinary, flavor, nutrition, health, and carbon footprint profiles.

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计算美食:通过使食物可计算来捕捉烹饪创意。
烹饪是一种典型的创造性追求,对个人、社区和文明具有深远的意义。食物和烹饪超越了单纯的感官享受,影响着营养和公共卫生成果。食物系统与烹饪和文化遗产密不可分,在可持续发展和地球上的生命存续方面发挥着举足轻重的作用。计算美食学是一种通过数据驱动范式研究食物的新方法。它通过仔细研究食谱的口味、营养价值、健康影响和环境可持续性,对烹饪艺术进行系统的、基于规则的理解。从计算的角度探究烹饪艺术,将为烹饪创意开辟一个新的可能性领域。在通过人工智能模仿创造力的不断探索中,一个有趣的问题是:"机器能像厨师一样思考吗?在人工智能算法中捕捉厨师的经验和创造力,为生成具有理想烹饪、风味、营养、健康和碳足迹特征的前所未见的食谱提供了令人兴奋的机会。
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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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