Sharif Digital Repository

The widespread use of pesticides in modern agriculture, despite markedly improving crop productivity, has raised serious concerns regarding public health and food safety. Conventional approaches for detecting pesticide residues, including chromatography-based techniques, although highly accurate and sensitive, face substantial practical limitations due to being time-consuming, costly. Accordingly, the main objective of this research is to develop a rapid, and accurate method based on hyperspectral imaging in the 400-950 nm spectral range, combined with deep learning models built on Convolutional Neural Networks, to detect two widely used pesticides dimethoate and acetamiprid on the surface...