Multivariate optimization and validation of 200 pesticide residues in the banana matrix by GC-MS/MS

Abstract

GC-MS/MS has been observed from past studies to be an appropriate choice for designing a simple, efficient and sensitive analytical technique. Accordingly, the linearity and working range, Method Limit of Detection (MLOD), Method Limit of Quantification (MLOQ), accuracy, precision (intra-day and inter-day), Matrix Effect (ME) and selectivity were analyzed for the assessment of 200 pesticide residues [organophosphorus pesticides (OPP), organochlorine pesticides (OCP), organonitrogen pesticides (ONP), synthetic pyrethroid pesticides (SPP), and herbicide methyl esters (HME)] in the banana matrix. The procedure involved QuEChERS (quick, easy, cheap, effective, rugged, and safe) extraction and clean-up with Multi-Walled Carbon Nanotubes (MWCNTs) and Primary Secondary Amine (PSA) wherein the factors were optimized using the Plackett–Burman and central composite designs. The performance of the method in order to quantitate 200 pesticides at trace levels was evaluated by matrix-matched calibration. The linearity was observed to range from 1 to 100 μg L⁻¹ with determination coefficient (r²) > 0.99. Recovery studies were conducted at 2 levels, 10 μg kg⁻¹ and 25 μg kg⁻¹, and the values obtained were in the range of 71–116% and 72–119%, respectively. The Relative Standard Deviation (RSD) was observed to be less than 20% in line with the recommended guidelines (SANTE/11312/2021). The MLOD and MLOQ were found to be in the range of 0.45–6.33 μg kg⁻¹ and 1.44–9.59 μg kg⁻¹ respectively. The developed method was applied satisfactorily to analyse banana samples cultivated in different regions of Gujarat, India.