Comprehensive Image Dataset of Agaricus bisporus Diseases Under Controlled Illumination Conditions

Description This dataset contains annotated images of healthy and diseased Agaricus bisporus mushrooms collected under controlled imaging conditions for deep learning, computer vision, and precision agriculture applications. The dataset was developed to support automated mushroom disease classification and artificial intelligence-based agricultural research. The dataset consists of five classes: Healthy Bacterial Blotch Dry Bubble Cobweb Disease Wet Bubble All images were acquired using a custom-designed portable imaging apparatus specifically developed for standardized agricultural image acquisition. The imaging system provides controlled illumination conditions while minimizing external light interference to ensure image consistency, reproducibility, and high visual quality. The dataset includes images captured under three different illumination environments: White light Ultraviolet (UV) light Mixed illumination (White + UV) Images were collected from mushroom production facilities over an extended acquisition period to ensure diversity in disease progression stages, orientations, and visual characteristics. Expert-supported annotation procedures were applied to improve labeling reliability and overall dataset quality. The dataset is intended for: Deep learning-based classification studies Transfer learning applications Computer vision research Agricultural artificial intelligence systems Precision agriculture applications Benchmarking of pre-trained deep learning architectures Potential applications include automated disease detection systems, smart farming technologies, agricultural monitoring platforms, and AI-assisted decision support systems for sustainable mushroom cultivation. This dataset was used in the following publication: Albayrak, U., Golcuk, A., Aktas, S., Coruh, U., Tasdemir, S., & Baykan, O. K. (2025). Classification and Analysis of Agaricus bisporus Diseases with Pre-Trained Deep Learning Models. Agronomy, 15(1), 226. https://doi.org/10.3390/agronomy15010226 The dataset is publicly released for academic and research purposes. Citation If you use this dataset in your research, please cite both the dataset and the related publication. Dataset Citation Albayrak, U., Golcuk, A., Aktas, S., Coruh, U., Tasdemir, S., & Baykan, O. K. (2026). Comprehensive Agaricus bisporus Disease Image Dataset Captured Under White, UV, and Mixed Illumination Conditions [Data set]. Zenodo. https://doi.org/10.5281/zenodo.20260929 Related Publication Albayrak, U., Golcuk, A., Aktas, S., Coruh, U., Tasdemir, S., & Baykan, O. K. (2025). Classification and Analysis of Agaricus bisporus Diseases with Pre-Trained Deep Learning Models. Agronomy, 15(1), 226. https://doi.org/10.3390/agronomy15010226