食品科学2026，Vol.47Issue(3)：1-12,12.DOI:10.7506/spkx1002-6630-20251011-046
大数据与机器学习赋能功能食品稳态增效递送体系的智能化构建前沿进展
Frontiers in the Intelligent Construction of Shelf-Stable and Efficacy-Enhanced Delivery Systems for Functional Foods Empowered by Big Data and Machine Learning
摘要
Abstract
Active ingredients in functional foods often fail to exert their intended efficacy due to poor stability,low solubility,inadequate bioavailability,and limited health effects.Shelf-stable and efficacy-enhanced delivery systems(SSEEDS)have emerged as a pivotal strategy to address these challenges by enabling precise delivery with high loading capacity,stability,and potency through various approaches,including dispersion and solubilization,stabilization and encapsulation,targeted release control,absorption enhancement,and synergistic formulation.However,traditional construction methods,relying on empirical trial-and-error,suffer from low efficiency and poor predictability.This review summarizes recent advances in the application of big data and machine learning(ML)for the intelligent construction of SSEEDS.It systematically explores their roles in functional component screening,carrier structure design,release behavior prediction,and multi-objective process optimization.Special emphasis is placed on case studies involving ML modeling for SSEEDS,prediction of release kinetics,and process regulation via Bayesian optimization.The advantages of ML in improving encapsulation efficiency,prolonging stability,and enhancing bioaccessibility are elucidated.Finally,this paper identifies prevailing challenges including data fragmentation,limited model generalizability,empirical dependence,and the complexity of cross-scale coupling,it also proposes integrating federated learning,transfer learning with few-shot enhancement,explainable AI,and digital twin technologies to address these challenges.This review aims to provide valuable technical insights and methodological guidance for the intelligent construction of SSEEDS for functional foods.关键词
功能食品/稳态增效递送体系/大数据/机器学习/释放行为预测/贝叶斯优化/智能化构建Key words
functional foods/shelf-stable and efficacy-enhanced delivery systems/big data/machine learning/release behavior prediction/Bayesian optimization/intelligent design分类
轻工纺织引用本文复制引用
肖杰,刘俊彬,王玉堂,李云琦,王文博..大数据与机器学习赋能功能食品稳态增效递送体系的智能化构建前沿进展[J].食品科学,2026,47(3):1-12,12.基金项目
国家自然科学基金面上项目(32572495 （）
22173094) （）
新疆维吾尔自治区天山英才项目(2022TSYCJC0015) （2022TSYCJC0015）
丝绸之路经济带创新驱动发展试验区、乌昌石国家自主创新示范区科技发展计划课题(2023LQ02003) （2023LQ02003）
贵州省百千万创新人才团队项目(BQW[2024]006) （BQW[2024]006）
