In-situ quantitative prediction of pesticide residues on plant surface by ATR-FTIR technique coupled with chemometrics

Abstract

Pesticide residues on plant surfaces pose a severe threat to food security, yet most research has focused on monitoring the liquid matrix, with few reports conducting in-situ analysis of the residues. This study was the first to attempt to utilize portable attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) for in-situ characterization of broad-spectrum fungicide boscalid residues on plant surfaces. ATR-FTIR scanning of tomato fruits with pre-determined concentrations of boscalid residues was conducted without any pre-treatment, and the obtained spectra were then processed using chemometrics methods. The results demonstrated a negative correlation between the residual concentrations and their corresponding absorption intensities of several well-resolved peaks from the spectra, resulting in a high accuracy of 93.33% for the classification model created by probabilistic neural network (PNN) coupled with principal component analysis (PCA). By employing correlation analysis and the interval partial least squares method (iPLS), quantitative analysis was conducted on the wavenumber ranges of 1000–1800 cm−1 and 2700–2900 cm−1 from the spectra. The regression model, established through partial least squares regression (PLSR), demonstrated exceptional performance with an R2 value of 0.80, RMSE of 1.02 μg/cm2, RPD of 2.0, and RPIQ of 2.1 for validation. Meanwhile, the detection limit (LOD) of the model was calculated as 3.06 μg/cm2. This report highlights the potential of using portable ATR-FTIR for conducting qualitative and quantitative monitoring of pesticide residues both in-situ and on-site. It also provides references for other measuring techniques.