酶制剂在酱香型白酒糟饲料化利用中的研究进展:从结构解构到 AI 赋能

Research progress on enzyme preparations for the feed utilization of Jiang-flavor Baijiu distillers' grains: from structural deconstruction to AI empowerment

摘要

酱香型白酒糟作为“12987”工艺产生的大宗副产物，年产量逾千万吨。因其高纤维、高酸度、蛋白质热变性以及木质素-碳水化合物复合体高度交联的结构特征，直接饲用价值偏低、转化难度突出。当前产业多采用粗放处理，以低值饲喂为主，资源潜力与实际利用水平之间存在显著落差。酶制剂凭借催化专一性、作用条件温和、易与工艺耦合等优势，被视为破解酒糟结构屏障、实现高值化饲料转化的核心技术路径之一。本文系统解析了酱香型白酒糟的理化特性与营养限制因素，归纳了纤维降解酶系、蛋白酶系及酯酶、裂解性多糖单加氧酶等辅助酶系的协同作用机制；从复合酶复配方案、关键工艺参数调控及预处理-酶解-发酵耦合 3 个层面总结了酶解过程的优化规律及产业化适配要点；从理化特性、营养品质、功能活性与动物饲用效果 4 个维度评估了酶解处理对酒糟高值化效果的提升作用。针对当前酶制剂成本偏高、批次适应性不强、工艺集成度低等产业化瓶颈，本文提出了人工智能驱动的新型研发路径:未来应重点发展基于机器学习的酶制剂理性设计，基于深度学习的酶解过程实时优化与调控，以及基于大数据挖掘的功能产物预测与工艺适配模型。本文旨在为酱香型白酒糟的资源化、高值化与绿色化饲料利用提供系统性的理论参考与技术路径支撑。

Abstract

Jiang-flavor Baijiu distillers'grains(JFDG),a major by-product of the “12987” process,are produced at an annual output exceeding ten million metric tons. Owing to their high fiber content,high acidity,thermal denaturation of proteins,and the highly cross-linked lignin-carbohydrate complex,JFDG exhibited low direct feeding value and were difficult to convert efficiently. Current industrial practices remained extensive,mainly utilizing JFDG as low-value feed or discarding them,resulting in a significant gap between resource potential and utilization efficiency. Enzyme preparations,characterized by catalytic specificity,mild reaction conditions,and ease of process integration,were recognized as one of the key technological routes to break down the structural barriers of JFDG and achieve high-value feed conversion. This review systematically analyzed the physicochemical characteristics and nutritional limitations of JFDG,and summarized the synergistic mechanisms of fiber-degrading enzyme systems,protein-modifying enzyme systems,and auxiliary enzyme systems(e.g.,esterases,lytic polysaccharide monooxygenases). Optimization strategies for the enzymatic process and industrial adaptation were discussed from three aspects:multi-enzyme formulation,regulation of key process parameters,and coupling of pretreatment,enzymatic hydrolysis,and fermentation. The effects of enzymatic treatment on enhancing the value of JFDG were evaluated across four dimensions:physicochemical properties,nutritional quality,functional bioactivity,and animal feeding performance. To address current industrial bottlenecks such as high enzyme cost,poor batch-to-batch adaptability,and low process integration,a novel artificial intelligence(AI)-driven R&D paradigm was proposed. Future efforts should focus on machine learning-based rational design of acid-tolerant enzyme systems,deep learning-based real-time optimization and control of enzymatic processes,and big data-driven prediction of functional products and process adaptation models. This review aimed to provide a systematic theoretical reference and technological roadmap for the resourceful,high-value,and environmentally friendly feed utilization of JFDG.

关键词

酱香型白酒糟 / 酶制剂 / 饲料化利用 / 酶解饲料 / 人工智能

Key words

Jiang-flavor Baijiu distillers'grains / enzyme preparations / feed utilization / enzymatically hydrolyzed feed / artificial intelligence

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基金资助

国家自然科学基金项目(U25A20709)