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Citation: Shitong Wang, Yangyang He, Xihong Xiong, Wei Zhang, Meilin Xia, Fenglin Tang. 基于手机RGB图像-微信小程序的化学需氧量(COD)实时可视化快速分析[J]. University Chemistry, ;2026, 41(1): 394-405. doi: 10.12461/PKU.DXHX202506011 shu

基于手机RGB图像-微信小程序的化学需氧量(COD)实时可视化快速分析

1.
College of Chemistry and Chemical Engineering, China West Normal University, Nanchong 637000, Sichuan Province, China;
2.
College of Mathematics and Information, China West Normal University, Nanchong 637000, Sichuan Province, China;
3.
College of Computer Science, China West Normal University, Nanchong 637000, Sichuan Province, China

Corresponding author: Fenglin Tang, tfl06180205@cwnu.edu.cn
Received Date: 3 June 2025
Revised Date: 23 September 2025

Chemical oxygen demand (COD) serves as a crucial parameter for assessing organic pollution in water and represents a routine analytical requirement. Building upon the standard method HJ/T399-2007 (“Water Quality-Determination of Chemical Oxygen Demand-Rapid Digestion Spectrophotometric Method”), this study innovatively developed a smartphone-based real-time visual detection system for COD analysis. The system utilizes smartphone color recognition to extract RGB values from digested water samples and establishes a ternary multiple regression model based on these values. A dedicated WeChat mini-program was developed to enable online visualization and analysis of COD, facilitating rapid on-site measurement of multiple water samples. This approach demonstrates advantages including operational simplicity, cost-effectiveness, and rapid analysis. Educational practice has shown that this technology not only finds application in environmental monitoring but also effectively enhances analytical chemistry pedagogy. It promotes outdoor teaching activities for undergraduates, stimulates students’ interest in chemistry, fosters scientific thinking and innovation awareness, and cultivates rigorous scientific attitudes.
- Chemical oxygen demand (COD),
- RGB value,
- Smartphone,
- WeChat mini-program development
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