QSAR modelling for predicting a, dsorption of Sulfonylurea herbicides in agricultural volcanic ash-derived soils.

This study developed an OECD-aligned QSAR model with an explicit applicability domain to predict the adsorption of Sulfonylurea (SUs) herbicides and methabenzthiazuron in agricultural volcanic ash-derived soils (VADS), a variable-charge system poorly represented in current pesticide adsorption QSAR models. Twenty-four SUs and methabenzthiazuron were evaluated in ten VADS, generating 250 compound-VADS systems from batch adsorption-desorption experiments. The dataset was complemented by soil physicochemical characterization, adsorption kinetics, and adsorption-desorption analysis, and descriptor-based QSAR modelling using a Lamarckian Genetic Algorithm for variable selection and Ridge regression across interaction, soil-specific, and herbicide-specific edaphic scenarios, with external validation and domain of applicability (DA). Adsorption was consistently nonlinear, and the Freundlich model best described equilibrium behavior. Across the 250 systems, Kfads ranged from 0.04 to 519.50, Kfdes from 0.24 to 229.91, and the hysteresis coefficient (H) from 0.00 to 0.94, indicating strong variability in retention and reversibility. The interaction scenario provided the main predictive result: with 210 training and 40 external observations [Formula: see text] = 0.438, [Formula: see text] = 0.347, RMSEtest = 0.492, and 30/40 (75%) DAcoverage). The final QSAR interaction retained 24 descriptors, indicating that adsorption in VADS is governed by the interplay between herbicide ionisation/polarity and 3D electronic features as well as soil organo-mineral reactive domains (OM, C/N, Fe, Cu, S, and P-Olsen). Accordingly, the predictive signal arose from herbicide-soil coupling rather than from molecular or edaphic properties alone. Within its calibrated chemical and edaphic space, the QSAR model provides a mechanistically interpretable, exploratory screening tool for identifying higher-mobility SUs-VADS combinations.