Detection of Profenofos in Chinese Kale, Cabbage, and Chili Spur Pepper Using Fourier Transform Near-Infrared and Fourier Transform Mid-Infrared Spectroscopies

Abstract

Different types of quantitative technology based on infrared spectroscopy to detect profenofos were compared based on Fourier transform near-infrared (FT-NIR; 12,500–4000 cm–1) and Fourier transform mid-infrared (FT-MIR; 4000–400 cm–1) spectroscopies. Standard solutions in the range of 0.1–100 mg/L combined with the dry-extract system for infrared (DESIR) technique were analyzed. Based on partial least-squares regression (PLSR) to develop a calibration equation, FT-NIR–PLSR produced the best prediction of profenofos residues based on the values for R 2 (0.87), standard error of prediction or SEP (11.68 mg/L), root-mean-square error of prediction or RMSEP (11.50 mg/L), bias (−0.81 mg/L), and ratio performance to deviation or RPD (2.81). In addition, FT-MIR–PLSR produced the best prediction of profenofos residues based on the values for R 2 (0.83), SEP (13.10 mg/L), RMSEP (13.00 mg/L), bias (1.46 mg/L), and RPD (2.49). Based on the ease of use and appropriate sample preparation, FT-NIR–PLSR combined with DESIR was chosen to detect profenofos in Chinese kale, cabbage, and chili spur pepper at concentrations of 0.53–106.28 mg/kg. The quick, easy, cheap, effective, rugged, and safe technique coupled with gas chromatography–mass spectrometry was used to obtain the actual values. The best FT-NIR–PLSR equation provided good profenofos detection in all vegetables based on values for R 2 (0.88–0.97), SEP (5.27–11.07 mg/kg), RMSEP (5.25–11.00 mg/kg), bias (−1.39 to 1.30 mg/kg), and RPD (2.91–5.22). These statistics revealed no significant differences between the FT-NIR predicted values and actual values at a confidence interval of 95%, with agreeable results presented at pesticide residue levels over 30 mg/kg. FT-NIR spectroscopy combined with DESIR and PLSR should be considered as a promising screening method for pesticide detection in vegetables.

Research Status in the Use of Surface-Enhanced Raman Scattering (SERS) to Detect Pesticide Residues in Foods and Plant-Derived Chinese Herbal Medicines

“…Near-infrared (NIR) spectroscopy is used to analyze information carried by the substance according to the light transmitted or refected by an NIR light source [29]. It is associated with fast detection speeds, high efciency, and low cost, and it can realize the qualitative and quantitative analysis of multiple pesticides, such as profenofos, diazinon, and chlorpyrifos [30][31][32][33]. However, at present, the range of application of NIR spectroscopy technology is limited, because it has low sensitivity in the detection of some trace substances, and its ability to detect analytes in liquid samples is insufcient.…”

Insight into the environmental fate, hazard, detection, and sustainable degradation technologies of chlorpyrifos—an organophosphorus pesticide

“…Modern food safety concerns make the detection of chlorpyrifos residue crucial for preventing the body from absorbing the substance (Sankom et al, 2021). Chlorpyrifos remainder in agricultural samples is typically observed using a variety of sophisticated techniques and tools.…”

A Review of Recent Advances for the Detection of Biological, Chemical, and Physical Hazards in Foodstuffs Using Spectral Imaging Techniques

“…The results based on 1D CNN outperformed those obtained by CNN, PLS-DA, and support vector machine (SVM) models. Moreover, Sankom et al [28] used FT-NIR combined with Fourier transform mid-infrared (FT-MIR) spectroscopy to detect profenofos residues in Chinese kale, cabbage, and chili spur pepper. The original spectral absorbance data were pre-processed via 1st derivative and SNV.…”