Pesticide Biosensors for Multiple Target Detection: Improvement Potential with Advanced Data-processing Methods

Abstract

Pesticides are essential for agriculture, but because of their residues in crops, produce and soil, they have become a major concern. Traditional pesticide detection methods, particularly gas chromatography-mass spectrometry, are expensive and impractical for small-scale farmers. Recognizing the need for robust yet accessible sensing methods, researchers have attempted to develop pesticide sensors that use various mechanisms. Biosensors have made significant progress by utilizing biochemical mechanisms to detect trace amounts of pesticides. However, their limitations to a single pesticide or specific chemical class have driven the exploration of innovative approaches. This review covers a range of biosensor receptor and transducer mechanisms and highlights the recent advancements in biosensor technologies. The focus is on integrating modern data-processing methods, specifically for the biochemical detection of pesticides. Sensor arrays such as electronic noses (e-noses) and electronic tongues (e-tongues) are explored, along with an in-depth analysis of sensor data-processing methods, incorporating machine learning and other techniques. This review explores the potential of advanced data processing methods to effectively analyze raw sensor data from biosensor arrays, ultimately enriching the robust detection of pesticides.