Analytical Detection of Insecticide Residues in Bananas: Methods and Implications

Insecticide and pesticide contamination in fruits, poses serious health risks. To address this challenge, Improved-ChemNet, an advanced neural network model designed to classify banana insecticide conditions into six distinct categories such as monohigh, monolow, natural, novahigh, novalow, and rotten are done. ImprovedChemNet integrates multiple deep learning techniques to enhance classification accuracy and robustness. The model is trained with a cyclical learning rate scheduler to ensure efficient convergence. Using these advanced deep learning components, ImprovedChemNet achieved high accuracy in classifying different banana insecticides. Its robustness and effectiveness make it a valuable tool for ensuring fruit quality and food safety in agricultural and commercial settings. The model is specifically trained on banana insecticide conditions. The effectiveness of ImprovedChemNet is highly reliant on the quality and diversity of training data.