{"title":"Generative artificial intelligence creates delicious, sustainable, and nutritious burgers.","authors":"Vahidullah Tac, Christopher D Gardner, Ellen Kuhl","doi":"10.1038/s41538-026-00953-x","DOIUrl":null,"url":null,"abstract":"<p><p>Food choices shape both human and planetary health; yet, designing foods that are delicious, nutritious, and sustainable remains challenging. Here we show that generative artificial intelligence can learn the structure of the human palate directly from large-scale, human-generated recipe data to create novel foods within a structured design space. Using burgers as a model system, the generative AI rediscovers the classic Big Mac without explicit supervision and generates novel burgers optimized for deliciousness, sustainability, or nutrition. Compared to the Big Mac, its delicious burgers score the same or better in overall liking, flavor, and texture in a blinded sensory evaluation conducted in a restaurant setting with 101 participants; its mushroom burger achieves an environmental impact score more than an order of magnitude lower; and its bean burger attains nearly twice the nutritional score. Together, these results establish generative AI as a quantitative framework for learning human taste and navigating complex trade-offs in principled food design.</p>","PeriodicalId":19367,"journal":{"name":"NPJ Science of Food","volume":"10 1","pages":""},"PeriodicalIF":9.7000,"publicationDate":"2026-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13309617/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"NPJ Science of Food","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1038/s41538-026-00953-x","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Food choices shape both human and planetary health; yet, designing foods that are delicious, nutritious, and sustainable remains challenging. Here we show that generative artificial intelligence can learn the structure of the human palate directly from large-scale, human-generated recipe data to create novel foods within a structured design space. Using burgers as a model system, the generative AI rediscovers the classic Big Mac without explicit supervision and generates novel burgers optimized for deliciousness, sustainability, or nutrition. Compared to the Big Mac, its delicious burgers score the same or better in overall liking, flavor, and texture in a blinded sensory evaluation conducted in a restaurant setting with 101 participants; its mushroom burger achieves an environmental impact score more than an order of magnitude lower; and its bean burger attains nearly twice the nutritional score. Together, these results establish generative AI as a quantitative framework for learning human taste and navigating complex trade-offs in principled food design.
期刊介绍:
npj Science of Food is an online-only and open access journal publishes high-quality, high-impact papers related to food safety, security, integrated production, processing and packaging, the changes and interactions of food components, and the influence on health and wellness properties of food. The journal will support fundamental studies that advance the science of food beyond the classic focus on processing, thereby addressing basic inquiries around food from the public and industry. It will also support research that might result in innovation of technologies and products that are public-friendly while promoting the United Nations sustainable development goals.