Quantification of resveratrol and pyrimethanil in agricultural wastewater by using excitation-emission matrix...

Botrytis cinerea is a common disease in crops such as cucumbers and grapes, and pyrimethanil (PYR) is often used to prevent and control it. Studies have found that resveratrol (RES) and PYR have a synergistic interaction that can prevent botrytis cinerea, but their residues pose a potential threat to the environment. To accurately detect these substances in agricultural wastewater, a new trilinear decomposition algorithm, alternating residual mean trilinear decomposition (ARMTLD), was proposed for second-order calibration of three-way data arrays. The performance of the ARMTLD algorithm was evaluated on a simulated data set and compared with four other iterative trilinear decomposition algorithms. The results show that ARMTLD has a fast convergence speed, strong noise robustness, and low component dependence, and can accurately determine RES and PYR in farmland wastewater under complex conditions. Their average recovery rate exceeded 95 %, and the LOD were 3.0 ng mL^-1 and 9.2 ng mL^-1 (RES) and LOQ were 0.4 ng mL^-1 and 1.3 ng mL^-1 (PYR), respectively. The ARMTLD-assisted excitation-emission matrix (EEM) method provides high-precision decomposition, strong anti-interference capability, and excellent sensitivity, making it particularly well-suited for analytical scenarios with low target concentrations, high noise levels, and complex interferences.