Cassava root cross-section images

Published: 19 June 2020| Version 1 | DOI: 10.17632/gvp7vshvnh.1
Joyce Nakatumba-Nabende,
Ernest Mwebaze,
Robert Kawuki,
Heneriko Kulembeka,
Solomon Nsumba,
Jeremy Tusubira,
Samiiha Nalwooga,
Benjamin Akera,
Ruhinda Kabonire,
Daniel Ssendiwala,
Paul Mugisha


This dataset contains images of cassava root cross-sections captured by the Makerere University Artificial Intelligence Lab in conjunction with the National Crop Resources Research Institute in Uganda and the Tanzania Agricultural Research Institute in Tanzania. The images were captured during harvests conducted by cassava breeders to assess and score root necrosis for different varieties of cassava. The dataset contains 9843 images from five field trials. The images can be used to develop deep learning algorithms that can help to automate the scoring of root necrosis and to study other aspects of necrosis expression on cassava roots..



Makerere University College of Computing and Information Sciences


Agricultural Science, Computer Vision, Image Segmentation, Cassava