Construction of an Electronic Nose for Disinfectant Concentration Detection in Cold Chain Environment

Rapid detection of whether the disinfectant concentration in the cold chain transportation environment meets the disinfection standards plays an important role in epidemic prevention and control. To meet this requirement, this paper studies the detection method of different concentrations of four commonly used disinfectants. Based on an electronic nose platform developed in our laboratory, an optimized regression model is developed integrating the Principal Component Analysis (PCA), Gray Wolf Optimization algorithm (GWO) and the Support Vector Regression (SVR) for the fast evaluation of the concentration of disinfectants. Compared to conventional processing techniques, the proposed electronic nose system shows high accuracy and broad application prospect in the concentration detection of environmental disinfectants for cold chain.