Multi-pesticide Residues Determination in Samples of Fruits and Vegetables Using Chemometrics Approach to QuEChERS-dSPE Coupled with Ionic Liquid-Based DLLME and LC–MS/MS

Pesticides play vital roles in agricultural practices, but the nature and mishandling of the chemicals have led to their accumulation in moist soil, vegetables and fruits. Thus, development of efficient methods for pesticides determination is one of the most important ways to address such challenges...

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Bibliographic Details
Main Authors: Lawal, Abubakar, Wong, Richard Chee Seng, Tan, Guan Huat, Abdulra'uf, Lukman Bola, Alsharif, Ali Mohamed Ali
Format: Article
Published: Springer 2018
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Online Access:http://eprints.um.edu.my/21541/
https://doi.org/10.1007/s10337-018-3511-7
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Summary:Pesticides play vital roles in agricultural practices, but the nature and mishandling of the chemicals have led to their accumulation in moist soil, vegetables and fruits. Thus, development of efficient methods for pesticides determination is one of the most important ways to address such challenges. Multivariate response surface methodology optimisation using Placket–Burman and Box–Behnken designs were respectively used for screening and optimisation of significant factors of quick, easy, cheap, effective, rugged and safe (QuEChERS) with dispersive solid-phase extraction (SPE). Consequently, the optimised QuEChERS-dSPE technique coupled with modified ionic liquid-based (IL-based) dispersive liquid–liquid microextraction was used for sample preparation before LC–MS/MS. The developed method was validated (SANTE 11831-2017) for multi-pesticide residues determination in samples of bananas, cabbages, tomatoes, oranges and onions. The precision results were satisfactory in terms of relative standard deviation (≤ 20%) as recommended. The results of accuracy for relative recoveries (82–137%) were satisfactory because 92.5% of results were within the recommended range (70–120%). The matrix effects in all the samples were very weak (less effective) (≤ − 80%). The linearity of the evaluated results was 5–400 µg kg−1 and regression coefficients (R2) were > 0.99. The resulting limits of detection and quantitation were 0.02–0.32 and 0.07–1.06 µg kg−1, respectively, and therefore satisfactory. Certifiably, the estimated measurement uncertainties range (1–16%) was acceptable (≤ 50%). Thus, the developed method could be reliable and suitable for routine determination of multiple pesticide residues in various vegetable and fruit samples.