In this research, the feasibility of using visible/near-infrared (Vis/NIR) spectroscopy combined with chemometrics was assessed for measurement of pesticide residues in agricultural products (a case study on Diazinon in greenhouse cucumber). Partial least squares (PLS) regression models were developed based on chemical reference measurements and the spectral information of the samples in 450-1000nm after performing different pre-processing methods. Results indicated that Vis/NIR spectroscopy combined with chemometrics have satisfactorily the potential for fast and non-destructive measurement of Diazinon residue in cucumber samples. Best prediction results were achieved with PLS model developed based on the combination of pre-processing methods of multiplicative scatter correction (MSC) and first derivative (D1) (rcv=0.91, SECV=3.22).

Keywords: Visible/Near-Infrared Spectroscopy, Pesticide Residues, Chemometrics, Non-destructive

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