Abstract

Despite the fact that a considerable amount of effort has been invested in the development of biosensors for the detection of pesticides, there is still a lack of a simple and low-cost platform that can reliably and sensitively detect their presence in real samples. Herein, an enzyme-based biosensor for the determination of both carbamate and organophosphorus pesticides is presented that is based on acetylcholinesterase (AChE) immobilized on commercially available screen-printed carbon electrodes (SPEs) modified with carbon black (CB), as a means to enhance their conductivity. Most interestingly, two different methodologies to deposit the enzyme onto the sensor surfaces were followed; strikingly different results were obtained depending on the family of pesticides under investigation. Furthermore, and towards the uniform application of the functionalization layer onto the SPEs’ surfaces, the laser induced forward transfer (LIFT) technique was employed in conjunction with CB functionalization, which allowed a considerable improvement of the sensor’s performance. Under the optimized conditions, the fabricated sensors can effectively detect carbofuran in a linear range from 1.1 × 10−9 to 2.3 × 10−8 mol/L, with a limit of detection equal to 0.6 × 10−9 mol/L and chlorpyrifos in a linear range from 0.7 × 10−9 up to 1.4 × 10−8 mol/L and a limit of detection 0.4 × 10−9 mol/L in buffer. The developed biosensor was also interrogated with olive oil samples, and was able to detect both pesticides at concentrations below 10 ppb, which is the maximum residue limit permitted by the European Food Safety Authority.

Highlights

  • Fast and easy analytical tools, that can work alongside confirmatory methods such as chromatography coupled to mass spectrometry, are in high demand

  • A facile and low-cost surface functionalization approach was followed towards the fabrication of an amperometric acetylcholinesterase-based sensor for the detection of organophosphorus

  • The method relies on the use of carbon black (CB) suspended in a CS matrix as a cost-efficient

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Summary

Introduction

Olive oil is one of the primary sources of added fat in the Mediterranean diet, with Spain (66%), Italy (14%) and Greece (14%) being the leading producers of olive oil in the European Union and worldwide. The European Union’s consumption of olive oil is estimated to be around 1.77 million metric tons (for 2019/2020, based on the European Commission data), and there is an increasing demand for high-quality and organic products [1]. In order to secure minimum harvesting losses, olive tree farmers use several agrochemicals, such as organophosphorus and carbamate pesticide, that may contaminate the produced olive oil, raising environmental and food safety concerns. Quantification of pesticides and their residues has become extremely important due to the concerns for public health raised due to their potential bioaccumulation, high toxicity and their long-term risk [2]. The current state-of-the-art methodologies for the determination of contaminants in olive oil are liquid (LC–MS/MS) and gas chromatography (GC–ECD) [3], methods that provide very accurate and reliable data for a large number of contaminants, including pesticide residues, but are costly and time-consuming. Fast and easy analytical tools, that can work alongside confirmatory methods such as chromatography coupled to mass spectrometry, are in high demand

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