Chemometric Optimization of UHPLC Separation of Multiclass Pesticides of Environmental Interest

Pesticides constitute a critical class of anthropogenic contaminants whose pervasive occurrence in surface waters, groundwater, and drinking water distribution systems poses substantial ecological and public health risks. Their pronounced structural heterogeneity, spanning highly polar herbicides to hydrophobic fungicides, together with their co-occurrence at trace levels, requires analytical methodologies capable of delivering rapid, robust, and high-resolution separations. In this study, a UHPLC-based analytical strategy is presented as a methodological framework for the development and optimization of UHPLC methods targeting multiresidue pesticide mixtures of environmental interest. The framework integrates a two-factor, three-level Design of Experiments, quadratic response surface modeling, and a multicriteria global desirability function to optimize the chromatographic resolution of 27 environmentally relevant pesticides. Statistical modeling revealed significant linear and quadratic effects of flow rate and gradient duration, highlighting the importance of multivariate optimization for complex multiresidue separations. The optimized UHPLC conditions improved simultaneous resolution, particularly for structurally similar analytes prone to coelution under conventional HPLC conditions. Overall, this work provides a statistically supported and transferable methodology for chemometric optimization of UHPLC separations and establishes a basis for extending desirability-driven optimization to additional classes of organic contaminants.