IDADP-Corn Disease Image Description Dataset

<p indent="0mm">Corn, as one of the major grain crops in China, faces significant disease issues that severely impact national food security. This study aims to construct a high-quality image description dataset for corn diseases (IDADP-Corn Disease Image Description Dataset). Traditional agricultural disease datasets predominantly exist in the form of ″image data-disease name,″ lacking detailed descriptions of disease symptoms. As agricultural cross-media applications increasingly demand multimodal interactions involving audio, video, images, and text, the utility of these traditional datasets becomes progressively limited. With the support of relevant projects, the authors collected and integrated data from 2018 to 2025 within China to establish an agricultural pest and disease research image library (IDADP). Based on this, they constructed an image description dataset including five types of corn diseases (Northern Corn Leaf Blight, Southern Corn Leaf Blight, Common Rust, Southern Rust, and Ear Rot) along with healthy plants, totaling 600 annotated images and their corresponding descriptive texts. The quality of both image data and textual descriptions was ensured through processes such as original image screening and manual review. This dataset not only provides rich data support for cross-media application tasks such as image generation, text-image contrastive learning, image classification, and visual question answering but also offers valuable input for diagnosing and evaluating agricultural diseases, holding significant application value and importance.