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Development of a Colorimetric Sensing System and Predictive Modeling for Fast Chlorpyrifos Detection
Abstract
For rapid quantitative detection of chlorpyrifos, an enhanced technique integrating colorimetric spectroscopy and chemometrics was created. Based on the molecular structure of chlorpyrifos, palladium chloride and resorcinol were selected as colorimetric reagents, with hydrochloric acid and acetic acid used as solvents for palladium chloride, respectively. Three distinct colorimetric systems were constructed to react with chlorpyrifos at varying concentrations. By comparing the absorbance spectra after the colorimetric reactions, the palladium chloride-acetic acid solution was idjentified as the most effective colorimetric reagent, capable of distinguishing absorbance signals for chlorpyrifos concentrations as low as 0.01 mg/kg. For 50 chlorpyrifos samples (0.01–88 mg/kg), the optimal model was selected by evaluating four key parameters: the determination coefficients of the calibration set (Rc2) and the prediction set (Rp2), together with the root mean square errors of calibration (RMSEC) and prediction (RMSEP). The partial least squares (PLS) regression model achieved Rc2 = 0.9975, RMSEC = 1.3383 mg/kg, Rp2 = 0.9948, and RMSEP = 1.8614 mg/kg. This sensitivity meets the detection limits specified for certain food products in the Chinese National Standard GB 2763-2021. The method is operationally safe, requires only 2 minutes for the colorimetric reaction, and provides a practical basis for developing detection instruments for other sulfur-containing organophosphorus pesticides.
About the Authors
Wen Li
Beijing Key Laboratory of Big Data Technology for Food Safety; School of Computer and Artificial Intelligence, Beijing Technology and Business University
China
China
Beijing
Hongbing Xiao
Beijing Key Laboratory of Big Data Technology for Food Safety; School of Computer and Artificial Intelligence, Beijing Technology and Business University
China
China
Beijing
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Review
For citations:
Li W., Xiao H. Development of a Colorimetric Sensing System and Predictive Modeling for Fast Chlorpyrifos Detection. Zhurnal Prikladnoii Spektroskopii. 2026;93(5):724.
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