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AI Predicts Consumer Preferences for Insect-Based Foods

Researchers at Korea University and the Rural Development Administration developed an AI-based model to predict consumer acceptance of insect-based foods using sensory data, fuzzy logic, and machine learning. The model achieved over 90% accuracy and showed higher acceptance for mealworm-based noodles and rice snacks, particularly among older consumers.

The technology was tested using four foods containing mealworm powder. Results showed that consumers preferred mealworms in carbohydrate-based foods such as noodles and rice snacks, where high-temperature processing enhanced their characteristic savory flavor. Older consumers also showed higher acceptance of mealworm-based foods than younger consumers. 

The prediction model achieved over 90% accuracy compared with conventional sensory evaluation. By predicting consumer preferences based on target liking, nutritional composition, and processing conditions, this approach could reduce the number of prototypes and sensory tests required, helping shorten product development time and lower costs. 

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