Exploration of Pesticide Residue Detection Methods

Pesticide residues in chillis present significant health concerns due to their widespread consumption in India. This study provides a range of methods for residual detection, such as mass spectrometry and gas chromatography, which are precise but expensive and time-consuming. We also explore advanced spectroscopic approach like Hyperspectral imaging that provides faster results compared to traditional methods, although it faces sensitivity issues, various machine learning and deep learning techniques which are claimed to function superiorly well in image analysis tasks. The Study reveals that hyperspectral imaging combined with Deep learning methods significantly enhances detection accuracy and reduces processing time compared to traditional approaches. As part of continuous efforts to increase food safety and public health, future research aims to refine these methodologies for enhanced sensitivity and real-time detection of pesticide residues in chilies.