PLDPNet: End-to-end hybrid deep learning framework for potato leaf disease prediction

•We propose a novel hybrid deep learning model, PLDPNet, for automatic segmentation and classification of potato leaf diseases.•The PLDPNet utilizes auto-segmentation and deep feature ensemble fusion modules to enhance disease prediction accuracy.•The end-to-end performance of the proposed PLDPNet achieves a recorded accuracy of 98.66%.•A comprehensive ablation study is conducted using two additional plant leaf diseases: Apple (4 classes) and Tomato datasets (10 classes).