A novel, green ultrasound-assisted dispersive liquid–liquid microextraction (UA-DLLME) method combined with solidification of floating organic droplets (SFO) and a menthol–decanoic acid deep eutectic solvent (DES) was developed for the analysis of pesticide residues in agricultural water. The method was optimized using experimental design techniques (DoE), achieving limits of detection between 0.2 and 0.8 ng/mL, and recovery rates ranging from 83 % to 115 %. Precision, as measured by relative standard deviations, was below 15 %, and enrichment factors ranged from 74 to 193. Analysis was performed using gas chromatography coupled with mass spectrometry (GC–MS). Environmental sustainability was assessed using the AGREE-prep tool, yielding a balanced score of 0.5, emphasizing both efficiency and environmental impact. This optimized method was successfully applied to the analysis of real water samples from agricultural areas, demonstrating its robustness and applicability for environmental monitoring of pesticide contamination.
Development of ultrasound-assisted dispersive liquid–liquid microextraction based on solidification of floating organic droplets and deep eutectic solvents for multi-class pesticide analysis in agricultural waters
Naccarato A.
2025-01-01
Abstract
A novel, green ultrasound-assisted dispersive liquid–liquid microextraction (UA-DLLME) method combined with solidification of floating organic droplets (SFO) and a menthol–decanoic acid deep eutectic solvent (DES) was developed for the analysis of pesticide residues in agricultural water. The method was optimized using experimental design techniques (DoE), achieving limits of detection between 0.2 and 0.8 ng/mL, and recovery rates ranging from 83 % to 115 %. Precision, as measured by relative standard deviations, was below 15 %, and enrichment factors ranged from 74 to 193. Analysis was performed using gas chromatography coupled with mass spectrometry (GC–MS). Environmental sustainability was assessed using the AGREE-prep tool, yielding a balanced score of 0.5, emphasizing both efficiency and environmental impact. This optimized method was successfully applied to the analysis of real water samples from agricultural areas, demonstrating its robustness and applicability for environmental monitoring of pesticide contamination.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
