Hydroponic Farming Data

Over a three-month period, we conducted three consecutive 30-day experiments to monitor Batavia lettuce growth under varying conditions (water temperature, electrical conductivity, and pH). Each day, a dual-camera system traversed the hydroponic channels, capturing high-resolution images of every plant. In total, the dataset contains over 390,000 images, each annotated with environmental and water-quality metadata, forming a robust resource for machine learning–based growth prediction and anomaly detection in hydroponic farming. This data is provided after segmentation of yolo-v8.