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Artificial Intelligence in Functional Polysaccharides for Food Applications: Process Optimization, Structure-Function
Zhen Cao1, Ting Chen1, Jiayan Xie1
1State Key Laboratory of Food Science and Resources, Nanchang University, Nanchang 330047, China.
Journal of Agricultural and Food Chemistry
|April 10, 2026
Summary
Artificial intelligence (AI) is revolutionizing functional polysaccharide research by optimizing production and uncovering structure-function relationships. AI accelerates the discovery and design of novel food-grade polysaccharides with tailored functionalities.
Area of Science:
- Food Science and Technology
- Biotechnology
- Computational Chemistry
Background:
- Functional polysaccharides are vital food ingredients, but their complex structures and poorly understood relationships between structure and function hinder efficient development.
- Current production methods for functional polysaccharides often rely on inefficient trial-and-error approaches, limiting innovation and scalability.
Purpose of the Study:
- To provide an integrated overview of how artificial intelligence (AI) is transforming the field of functional polysaccharide research for food applications.
- To outline a framework for AI-driven advancements in polysaccharide extraction, analysis, mechanism elucidation, and design for targeted food functionalities.
Main Methods:
- Review and synthesis of recent advances in AI applications for functional polysaccharide research.
- Categorization of AI contributions into efficiency amplification, mechanism-informed hypothesis generation, and design assistance.
- Discussion of AI techniques including machine learning, deep learning (Deep-QSAR), graph-based learning, and interpretable modeling.
Main Results:
- AI enhances efficiency in polysaccharide extraction and fermentation optimization through machine learning models.
- AI facilitates rapid analysis of polysaccharides when coupled with spectroscopic data.
- AI models are beginning to elucidate quantitative structure-function relationships, including microbiome interactions, and aid in precision-guided polysaccharide engineering and formulation.
Conclusions:
- AI offers a transformative roadmap for accelerating the discovery and application of functional polysaccharides in the food industry.
- Addressing challenges such as data scarcity, standardization, model interpretability, and regulatory acceptance is crucial for the successful translation of AI in this field.
- AI-guided strategies are essential for overcoming current limitations and unlocking the full potential of functional polysaccharides.
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