NaCRRI is one of the breeding programs that the NextGen project supports, so the partnership with NextGen Cassava was fostered under the working relationship that we have established with the cassava program there.ĭo you work with any Master’s/PhD students in the lab? What (generally) is their work focused on?Ĭurrently, we are working on a new task to support Leah Nandudu (PhD student at Cornell University with Jean-Luc Jannink) in using image-based analysis methods for characterizing different expressions of root necrosis caused by cassava brown streak viruses. In the past, we have carried out several research projects jointly with our partners at NaCRRI in Namulonge.

The AIR Lab contributes to this goal by building efficient and accurate phenotyping pipelines that feed into the NextGen Cassava data ecosystem. The NextGen project relies on data to improve the efficiency and effectiveness of breeding cycles in cassava. The AIR Lab’s role in the NextGen Cassava Project is developing imaging technologies for improving the phenotyping pipelines as well as monitoring the usage of PhenoApps to provide quantitative data on their efficacy. Joyce is pictured to the right of the poster.Ĭan you describe how do you see the AIR Lab’s role in the NextGen Cassava project, and how this partnership came to be? The AIR Lab team at the 2019 NextGen Cassava annual meeting in Kampala, Uganda. We spoke to Joyce Nabende, Research Scientist & Lecturer at the AIR Lab, to learn more about this key partnership. By partnering with these groups, the NextGen Cassava project is creating networks necessary for success. These scientists work together to develop smartphone apps, algorithms, and novel techniques to accurately collect and store valuable breeding data.

The Cassavabase team actively collaborates with the PhenoApps team in Jesse Poland’s lab at Kansas State University, and the Artificial Intelligence & Data Research (AIR) Lab at Makerere University in Uganda. An important aspect of the NextGen Cassava project is improving phenotyping techniques in the field for the rapid assessment of cassava roots, leaves, and disease monitoring.

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