Application of mid-infrared spectroscopy to the prediction and specification of pesticide sorption: A promising and cost-effective tool

Abstract

The cocktail of pesticides sprayed to protect crops generates a miscellaneous and generalized contamination of water bodies. Sorption, especially on soils, regulates the spreading and persistence of these contaminants. Fine resolution sorption data and knowledge of its drivers are needed to manage this contamination. The aim of this study is to investigate the potential of Mid-Infrared spectroscopy (MIR) to predict and specify the adsorption and desorption of a diversity of pesticides. We constituted a set of 37 soils from French mainland and West Indies covering large ranges of texture, organic carbon, minerals and pH. We measured the adsorption and desorption coefficients of glyphosate, 2,4-dichlorophenoxyacetic acid (2,4-D) and difenoconazole and acquired MIR Lab spectra for these soils. We developed Partial Least Square Regression (PLSR) models for the prediction of the sorption coefficients from the MIR spectra. We further identified the most influencing spectral bands and related these to putative organic and mineral functional groups. The prediction performance of the PLSR models was generally high for the adsorption coefficients Kd_ads (0.4 < R² < 0.9 & RPIQ >1.8). It was contrasted for the desorption coefficients and related to the magnitude of the desorption hysteresis. The most significant spectral bands in the PLSR differ according to the pesticides indicating contrasted interactions with mineral and organic functional groups. Glyphosate interacts primarily with polar mineral groups (OH) and difenoconazole with hydrophobic organic groups (CH₂, CC, COO^-, C-O, C-O-C). 2,4-D has both positive and negative interactions with these groups. Finally, this work suggests that MIR combined with PLSR is a promising and cost-effective tool. It allows both the prediction of adsorption and desorption parameters and the specification of these mechanisms for a diversity of pesticides including polar active ingredients.

Keywords: Adsorption; Desorption; FT-IR; MIR; Partial least square regression; Pesticides; Soil.