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基于 XGBoost 机器学习算法的人参饮料澄清后沉淀再形成因素分析。

Analysis of sediment re-formation factors after ginseng beverage clarification based on XGBoost machine learning algorithm.

机构信息

Northeast Asia Research Institute of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun 130117, PR China; Key Laboratory of Active Substances and Biological Mechanisms of Ginseng Efficacy, Ministry of Education, Changchun University of Chinese Medicine, Changchun 130117, PR China.

State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, Chinese Academy of Medical Sciences & Peking Union Medical College, Institute of Medicinal Plant Development, Beijing 100193, PR China.

出版信息

Food Chem. 2025 Jan 15;463(Pt 3):141304. doi: 10.1016/j.foodchem.2024.141304. Epub 2024 Sep 17.

DOI:10.1016/j.foodchem.2024.141304
PMID:39321649
Abstract

The aim of this study was to explore the sediment re-formation factors of ginseng beverages subjected to four clarification ways (11 subgroups) including the ethanol precipitation, enzymatic treatment, clarifier clarification, and Hollow Fiber Column (HFC) methods, based on the Extreme Gradient Boosting (XGBoost) model. The results showed that the clarity of the ginseng beverages was significantly improved by all the clarification treatments, but still formed sediment after storage. HFC method exhibited the highest transmittance, the least sediment, and stronger antioxidant activity in the clarification treatment groups. According to the results of chemical composition analyses and partition coefficients, carbohydrates, saponins, proteins and metal elements were involved in varying degrees in the re-formation of the sediments in ginseng beverage after clarification. Based on the above data, the XGBoost model predicted that protein, Rd, Na, K, and total saponins were the five most important chemical components affecting the sediment re-formation in ginseng beverages.

摘要

本研究旨在通过极限梯度提升(XGBoost)模型,探索四种澄清方法(11 个亚组)包括乙醇沉淀、酶处理、澄清剂澄清和中空纤维柱(HFC)方法对人参饮料的沉淀再形成因素。结果表明,所有澄清处理均显著提高了人参饮料的澄清度,但贮藏后仍会形成沉淀。在澄清处理组中,HFC 法表现出最高的透光率、最少的沉淀和最强的抗氧化活性。根据化学成分分析和分配系数的结果,碳水化合物、皂苷、蛋白质和金属元素在不同程度上参与了人参饮料澄清后沉淀的再形成。基于上述数据,XGBoost 模型预测蛋白质、Rd、Na、K 和总皂苷是影响人参饮料沉淀再形成的五个最重要的化学组成部分。

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