A rapid pesticide detection approach in food forensics using hyphenated technology of TLC-electronic nose

Abstract

Pesticides are a commonly employed means for improving agri-yield but have grave forensic implications in cases of accidental or deliberate pesticide poisoning. There is a need of devising a rapid, portable, and accurate in-situ technique to detect pesticides in food samples encountered at the scene of crime. The technology Electronic Nose (E-nose) has the potential to detect pesticides rapidly by identifying the volatile constituent compounds in tested samples and generating corresponding "smell prints." The aim of this study was to determine a combined multiclass/multiresidue analytical approach using Thin Layer Chromatography (TLC) and E-nose to be employed as a reliable, rapid and cost-effective method for detecting pesticides in different food samples at crime scene in cases of pesticide poisoning. Five food matrices were spiked with eight pesticides of standard concentration. TLC was used for a preliminary separation of pesticides in each of the food matrices spiked with the eight pesticides individually. Further, E-nose was employed to build a prediction model using two specific pesticides, atrazine and diafenthiuron. The data obtained was analyzed using built-in principal component analysis (PCA) and the spiked samples showed congruence to the prediction model. The results demonstrate the E-nose’s efficiency of detecting the presence of pesticide-contaminated food matrices as it responded well to the volatile pesticide components with good linearity (R2>9.998) as per the developed protocol. We advocate this combined approach to be utilized for on-field rapid and reliable qualitative forensic testing for pesticide contamination in food matrices with minimal sample preparation.