A generative AI model trained on more than 2,200 burger recipes has produced new burger formulations designed to optimize taste, nutrition and environmental impact, according to a study published in npj Science of Food. The researchers say the system could help food developers navigate trade-offs that have long challenged plant-based product development.
Unlike large language models that generate recipes as text, the researchers developed a diffusion-based AI model that learned ingredient combinations and quantities from existing burger recipes before generating one million new formulations. These were then screened for palatability, nutritional quality and environmental performance.
Lower-impact burgers without sacrificing taste
Among the recipes selected for testing was a mushroom-based burger that achieved an environmental impact score more than ten times lower than a conventional Big Mac reference burger. A mushroom and beef hybrid recipe performed similarly to the Big Mac in blind taste tests while reducing environmental impact, suggesting that ingredient combinations, rather than simple substitutions, can improve sustainability.
Photo by Vije Vijendranath on Unsplash
The model also generated a bean-based burger with nearly double the Healthy Eating Index score of the Big Mac and roughly one-sixth of its environmental impact, although participants rated it lower for taste and texture.
Taste remains the biggest challenge
To evaluate whether AI-generated recipes translated into real-world products, the researchers conducted a blind sensory trial involving 101 participants in San Francisco.
Two recipes developed primarily to maximize palatability received flavor or overall liking scores that matched or exceeded those of the Big Mac, while maintaining comparable texture ratings. The findings suggest AI could help identify formulations that improve consumer acceptance, one of the biggest barriers to wider adoption of plant-based foods.
The researchers also demonstrated that the model could generate personalized burger recipes based on age, sex and activity level, suggesting potential applications beyond product development.
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