Desenvolvimento e validação de método para determinação de ametryn amostas de águas por quechers-cg-em e posterior aplicação em amostras reais.

Abstract

The present work deals with the development of analytical methods for monitoring pesticide residues in food, which is of paramount importance to ensure compliance with permitted maximum limits and safeguard human health. However, the monitoring of pesticide residues in surface waters has been less explored due to various challenges. The presence of interferents and low analyte concentrations necessitates the development of increasingly sensitive and selective analytical techniques. The QuEChERS method, a solid-phase extraction (s-SPE) technique commonly used for sample preparation, has been extensively applied in food matrices but is less utilized in liquid matrices. The application of methods for analyzing water inputs is crucial for environmental control and human health preservation. This study focuses on optimizing chromatographic conditions for the determination of the pesticide Ametryn by GC- MS in SCAN mode. Initially, the conditions resulted in excessive noise, leading to adjustments that brought about significant improvements. Switching to the SIM mode increased selectivity and sensitivity, highlighting Ametryn. Method validation confirmed linearity, with a calibration curve in both solvent and matrix, demonstrating good linearity. Matrix effects were analyzed, revealing a considerable influence on signal intensity. Statistical tests confirmed the significance of linear regression and calibration parameters. Detection and quantification limits were determined, showing higher sensitivity in the matrix. Precision was assessed through repeatability using the CV%, and accuracy was evaluated through recovery tests, demonstrating results within acceptable limits. The method applied to real water samples did not reveal Ametryn residues but identified the compound 2,4-Di-tert-butylphenol, possibly a byproduct of the degradation of the organochlorine herbicide Pentachlorophenol. This study contributes to the development of efficient analytical methods for pesticide detection, addressing crucial aspects such as selectivity, linearity, and matrix effects, while also providing relevant information on degradation byproducts.