“BAU-Insectv2” represents a novel agricultural dataset tailored for deep learning applications and biomedical image analysis focused on plant-insect interactions. This dataset encompasses a diverse collection of high-resolution images capturing intricate details of plant-insect interactions across various agricultural settings. Leveraging deep learning methodologies, this study aims to employ convolutional neural networks (CNN) and advanced image analysis techniques for precise insect detection, classification, and understanding of insect-related patterns within agricultural ecosystems. We mainly focus on addressing insect-related issues in South Asian crop cultivation. The dataset's extensive scope and high-quality imagery provide a robust foundation for developing and validating models capable of accurately identifying and analyzing diverse plant insects. The dataset's utility extends to biomedical image analysis, fostering interdisciplinary research avenues across agriculture and biomedical sciences. This dataset holds significant promise for advancing research in agricultural pest management, ecosystem dynamics, and biomedical image analysis techniques.