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Artificial Intelligence Reshaping Non-Starch Polysaccharides Research: A Comprehensive Review of Intelligent
Jixiang Zhang1,2, Zhiyuan Xu3, Cheng Zhong2
1College of Food Science and Engineering, Tianjin University of Science and Technology, Tianjin, China.
Comprehensive Reviews in Food Science and Food Safety
|December 29, 2025
Summary
Artificial intelligence (AI) enhances natural polysaccharide research by optimizing extraction and enabling personalized product design. AI integration overcomes traditional limitations, driving innovation in functional foods and biomaterials.
Area of Science:
- Biochemistry and Materials Science
- Biotechnology and Bioinformatics
Background:
- Natural polysaccharides are vital in functional foods, medicines, cosmetics, and biomaterials.
- Traditional research methods face limitations in structure-function elucidation, efficiency, and adaptability.
- Artificial intelligence (AI) offers a transformative approach to overcome these challenges in polysaccharide research.
Purpose of the Study:
- To review recent AI applications in natural polysaccharide research.
- To discuss current challenges and identify future trends in AI-driven polysaccharide innovation.
- To highlight AI's role in optimizing extraction and enabling personalized applications.
Main Methods:
- AI models like artificial neural networks and genetic algorithm-backpropagation are used for optimizing polysaccharide extraction conditions.
- Multi-omics data integration with AI, including graph convolutional networks, correlates polysaccharide structural features with biological activities.
- AI models demonstrate high prediction accuracy (often >0.95) for optimizing processes.
Main Results:
- AI significantly improves prediction accuracy for polysaccharide extraction optimization compared to traditional methods.
- AI facilitates personalized functional product design by linking polysaccharide structures to specific biological activities, such as anti-cancer effects and immune modulation.
- AI-driven approaches show potential for developing novel functional foods, precision medicines, and advanced biomaterials.
Conclusions:
- AI is crucial for advancing natural polysaccharide research, overcoming limitations of traditional methods.
- Addressing challenges like data quality and interpretability will elevate AI's role from supportive to driving innovation.
- AI integration promises significant impacts on personalized medicine, functional foods, and biomaterials development.
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