The dataset contains 2D images/photographs of diseased soybean leaves ideal for plant disease identification and visual object recognition research. Images were captured during the 2020 and 2021 soybean seasons using a Canon EOS 7D Mark II Digital SLR Camera and a Motorola Moto Z2 Play Smartphone from fields at the EV Smith Agricultural Research Station (Tallassee, Alabama), the Cullars Rotation (Auburn, Alabama), and the Brewton Agricultural Research Unit (Brewton, Alabama). Across both seasons there are a total of 9,981 original images collected across eight disease/deficiency categories. These include (1) healthy-looking plants, and those displaying the symptoms of (2) bacterial blight, (3) cercospora leaf blight, (4) downey mildew, (5) frogeye leaf spot, (6) soybean rust, (7) target spot, and (8) potassium deficiency. For each disease category, leaves were photographed at various canopy heights while still attached to the plant in the field or they were detached from the plant and then immediately photographed while laid flat on the ground in trimmed grass or on a white surface. Images were collected with the goal of developing a Convolutional Neural Network (CNN)-based automated classifier of digital images of soybean diseases. Dataset is well-suited for classification modeling.

All images in this dataset are the raw images. They are unprocessed, except that for the fact that all images have been oriented horizontally. Soybean leaves were photographed during the 2020 and 2021 Alabama (southeastern USA) growing seasons in the months of August, September, and October. The primary method was to walk through rows of planted soybean fields and capture images of a single soybean leaf showing symptoms of a known disease with the leaf still attached to the plant. The leaves photographed were simply the ones ‘stumbled upon’ in a known diseased area. We attempted to photograph leaves at various heights in the canopy in proportion to how disease symptoms were distributed. Additionally, leaves of each represented disease category were detached from the plant and then immediately photographed while laid flat on the ground in trimmed grass or on a white surface. So there is a mix of attached (in the field) and detached (placed on a white or grass background) soybean leaf images for each of the eight disease categories

All images are formatted as .jpg files. JPG is a commonly used compressed image format for digital images. The categorized images can be used as any other JPG file.