npj Science of Food: Machine learning for understanding food as a complex system

A collaborative review by our research group and colleagues from Shanghai Institute of Technology has been published in npj Science of Food. The article surveys recent advances in applying machine learning to food science and introduces a conceptual framework describing three layers of food complexity: molecular composition, component interactions, and human perception.

The review highlights machine learning as a unifying tool for linking data across scales, enabling improved understanding of food chemical space, nonlinear interaction effects, and sensory perception. This work provides conceptual guidance for interdisciplinary research at the interface of food science, artificial intelligence, and sensory science.

https://www.nature.com/articles/s41538-026-00730-w