ArticleNPJ science of food2026
Generative artificial intelligence creates delicious, sustainable, and nutritious burgers.
Article in NPJ science of food, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
5 citing papers in PubMed.
- The meatball matchup: Plant vs. animal proteins on campus.Food research international (Ottawa, Ont.) · 2026Article
- Open-Source Benchmarking of Plant-Based and Animal Meats.Foods (Basel, Switzerland) · 2026Article
- Texture Independently Drives Liking in AI-Generated Alternative Protein Burgers.Foods (Basel, Switzerland) · 2026Article
- Mechanical, rheological, and sensory characterization of lion's mane mushroom steak.Current research in food science · 2026Article
- Artificial intelligence in child nutrition and eating behavior: from prediction to gastronomic mediation.Frontiers in nutrition · 2026Review
Corrections and comments
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Authors and funding
3 authors.
Funding
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.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.