分析化学2025，Vol.53Issue(11)：1797-1807,11.DOI:10.19756/j.issn.0253-3820.251202
机器学习在比色分析中的应用研究进展
Advances in Applications of Machine Learning for Colorimetric Analysis
摘要
Abstract
Colorimetric analysis is a detection and quantification method based on observable color changes in response to analytes,which offers significant advantages including visually detectable signals,straightforward operation,rapid response,and low cost.Consequently,it plays a crucial role in a variety of fields.With increasingly diverse and complex application,colorimetric analysis requires continuous improvement in sensitivity,adaptability to diverse detection environments,and complex data handling capabilities.In recent years,the development of artificial intelligence technology,particularly within its core domain of machine learning(ML),has led to significant advancements in colorimetric analysis.The ML-assisted colorimetric analysis enables high-throughput and high-sensitivity detection,alongside automated analysis,thereby providing novel strategies to overcome the inherent limitations.This review categorized machine learning techniques and summarized their application in colorimetric analysis,introducing two fundamental categories of supervised learning,and unsupervised learning based on the division of core learning paradigms.The research progress of ML-assisted colorimetric analysis in the fields of environmental monitoring,biochemical detection,and food safety were summarized.Finally,the current challenges facing by this research area were analyzed and the research prospect of ML-assisted colorimetric analysis was outlined.关键词
比色分析/机器学习/定量检测/人工智能/评述Key words
Colorimetric analysis/Machine learning/Quantitative detection/Artificial intelligence/Review引用本文复制引用
YAN Yu-Han,WANG Quan-Feng,LAI Yu-Tong,YANG De-Min,XIA Chang..机器学习在比色分析中的应用研究进展[J].分析化学,2025,53(11):1797-1807,11.基金项目
重庆市水利科技项目(No.CQSLK-2023020)、重庆市教委科学技术研究计划项目(No.KJQN202100509)和重庆师范大学博士启动项目(No.21XLB023)资助. Supported by the Science and Technology Project of Chongqing Municipal Bureau of Water Resources(No.CQSLK-2023020),the Science and Technology Research Project of Chongqing Education Commission(No.KJQN202100509)and the Startup Fund of Chongqing Normal University(No.21XLB023). （No.CQSLK-2023020）
