Soybean Leaf Image and Greenness Dataset

This dataset contains a collection of soybean leaf images gathered to support research in computer vision and machine learning, particularly in the area of greenness estimation. The images were captured under natural lighting conditions from several soybean varieties, including P, O, F, Anjasmoro, Dega 1, Grobogan, Derap, Devon, Soya USU, and Atelia USU.

The primary research hypothesis is that leaf images can be used as a non-destructive method to predict leaf greenness across different varieties using deep learning and image analysis techniques. The dataset may also serve for studies on leaf segmentation and color feature extraction.

Along with the images, an Excel file is provided containing IDs that correspond directly to the image filenames. This allows researchers to link each image with its associated metadata for further analysis.

The data can be interpreted by analyzing the RGB values and derived color indices from the leaf regions, which can be correlated with physiological measurements or used as input for classification and regression models. Researchers are encouraged to preprocess the images (e.g., segmentation, normalization, augmentation) according to their experimental needs.

This dataset is intended for use in agricultural research, computer vision model development, and educational purposes.