Personalized diets based on multi-objective optimization of nutrition and sensory characteristics: A digital strategy for enhancing food quality

Abstract

Background

Personalized diets aim at designing dietary interventions for individuals and satisfying sensory preferences. An increasing interest is how to balance the deliciousness and nutrition rather than focus on one side of them. With the development of technology and interdisciplinary integration, a review of the current situation and future trends is necessary.

Scope and approach

In this paper, we introduced the food nutrition and sensory digitization, respectively. The computational methods and food technologies in multi-objective optimization (MOO) of nutrition and sensory characteristics were reviewed comprehensively. The application of food technology in improving the nutrition and sensory quality of food was summarized as well.

Key findings and conclusions: This review indicated the methods of digital representation in precision nutrition, food perception science, and MOO. We highlighted the fact that the MOO would improve nutrition and sensory qualities simultaneously in personalized dietary design. The application of MOO emphasized the importance of diversified demands with higher food quality. Advances in big data and machine learning promoted the development of personalized diets with sensory enjoyment and health benefits. This review focused on assisting the field of precision nutrition more scientifically, intelligently, and characteristically. The personalized strategy based on MOO will provide guidance for the development of healthy food. It is believed that the personalized strategy of nutrition and sensory MOO driven by artificial intelligence will be a popular trend in future food.