This data contains 4015 root images, splitted into 4 datasets, acquired using two minirhizotron (MR) system types - manual (Dataset 1 & Dataset 4) and automated (Dataset 2 & Dataset 3). It includes four crop species (corn, pepper, melon, and tomato) grown under various abiotic stresses. The data was acquired by researchers from Ben-Gurion University of the Negev, Beer Sheva, Israel, and used for research of automated TRL estimation with Convolutional Neural Networks. The annotations were conducted manually using the Rootfly software (Wells and Birchfield, Clemson University, South Carolina, USA), and data were transformed as CSV formats. In this software, the annotator must draw a root by marking points along the selected root. These points usually correspond to the coordinates at the start and the end of the root, and curving points along the root. These points are then connected in a line, the length of which reflects the real length of the selected root. The annotations has been done for all roots within an image, and for all images in the provided dataset. The provided annotations include the total root length (TRL) per image (mm) and the coordinates of annotated points. The annotations are given in two types of files: "TRL.csv" files: contain the image names and corresponding TRL values (mm). "pointsOutput.csv" files: contain the annotated image names and the coordinates of the points of the roots in the image (if the image contains roots) in the form of x1, y1, x2, y2, x3, y3, etc. It the image doesn't have roots, the file contains only its name.

This research was supported by the Israeli Ministry of Agriculture and Rural Development (Eugene Kandel Knowledge Centers) as part of the Root of the Matter—The Root Zone Knowledge Center for Leveraging Modern Agriculture (grant number 16-38-0044) of the Israeli Ministry of Agriculture and Rural Development, and the European Union's Horizon 2020 Research and Innovation Program (grant agreement no. 777222) (ATTRACT project "NextMR-IAA"). Partial support was provided by the Ben-Gurion University of the Negev W. Gunther Plaut Chair of Manufacturing Engineering.