Methods development for determination of neonicotinoid pesticides from selected vegetable oils using hplc-dad

Abstract

The neonicotinoid pesticides (NEOs) have been used over the years for plant protection. The use of these NEOs on crops and oil seed plants has led to vegetable oil and crop produce contamination. The four selected NEOs for this study are acetamiprid, imidacloprid, thiacloprid and thiamethoxam. Their accumulation in oil crops is through absorption via roots and plant leaves. The presence of NEOs in the vegetable oils results in human health problems, hence there is a need for monitoring and control of their concentration levels present in agricultural products. Different organisations like World Health Organization (WHO), Codex Alimentarius Commission (CAC) and European Union (EU) have maximum residue limits set for NEOs in countries like Japan, China and US at less than 0.5 mg.kg-1. Different chromatographic techniques have been used for determination of NEOs in various sample matrices. The high-performance liquid chromatography with diode-array detection (HPLC-DAD) was among the most reported chromatographic techniques for detection of NEOs. However, due to the complexity of vegetable oils and the trace concentration levels of NEOs, sample preparation step is required prior to chromatographic detection. The solid phase extraction (SPE) and liquid-liquid extraction (LLE) methods are popular for extraction of various targeted analytes. However, these two extraction methods suffer from different limitations like use of large amount of organic solvents, tediousness, costly adsorbents and production of hazardous waste. Therefore, the aim of the study was to develop rapid, greener, and efficient extraction methods followed by HPLC-DAD analysis for determination NEOs in selected vegetable oils. The magnetic solid phase microextraction (MSPME) was the first extraction method to be investigated. A novel magnetic adsorbent (Fe3O4@Al2O3/AC) was synthesized using maize waste material and characterized using various techniques such Fourier transform infrared spectrometry (FTIR), Powdered X-ray diffraction (PXRD), Scanning electron microscope coupled to energy dispersive X-ray spectroscopy (SEM-EDS), Thermogravimetric analysis (TGA), Transmission electron microscopy (TEM), and Ultraviolet visible spectroscopy (UV-Vis) to confirm the formation of the adsorbent material. The proposed MSPME method achieved high accuracy (80-119.21 %) and precision (≤10 %) for all the investigated NEOs. Furthermore, the obtained limit of detection (LOD) ranged from 0.5-1.76 ng.μL-1, limit of quantification (LOQ) ranged from 1.87-6.62 ng.μL-1, with satisfactory high 9 preconcentration factors (73.02-407) were comparable with literature reported studies. The Analytical GREEness calculator (AGREE) analysis confirmed the 0.54 greenness scale, suggesting that the MSPME was environmentally friendly. Deep eutectic solvent- dispersive liquid-liquid microextraction (DES-DLLME) was the second examined extraction method prior to chromatographic determination of NEOs in vegetable oils. The GREEness of the proposed DES-DLLME was attributed using “greener” more environmentally friendly solvent known as deep eutectic solvents. The method achieved good limit of detection (LOD) ranging from 0.4 to 4.95 ng. μL-1 and limit of quantification (LOQ) ranging from 1.43 to 9.7 ng.μL-1. The method also showed good accuracy (79-119.6 %) and precision (0.1 to 0.9 %). Method greenness was studied using the Analytical GREEness calculator (AGREE) in full tool and the greenness was 0.67 scale. The DLLME method has proved to be greener compared to the AGREE calculator as reported above. The method detection limits for MSPME were lower compared to that for DES-DLLME. The MSPME also shows the high preconcentration factors than the DES-DLLME. The accuracy for the DES-DLLME was good and higher compared to that for MSPME. Both the methods were conducted under room temperature. The precision for DES-DLLME was lower compared to that of MSPME which shows that DES-DLLME is more sensitive than the MSPME.