Banana breeding is a slow and time-consuming process, and it is currently taking almost a decade in Tanzania to develop new varieties due to the crop’s complex genetics, sterility, and long generation cycles. In efforts to improve banana breeding through research, there is a great need for research institutes to increase collaboration with the National Agricultural Research System in data collection and provide feedback to breeders that will facilitate and fast-track the release.
In recognizing the critical role of the NARS in supporting high-quality data in crop improvement, recently, IITA–CGIAR, en collaboration avec le Institut Tanzanien de Recherche Agricole (TARI) et le Tanzania Official Seed Certification Institute (TOSCI), trained the banana breeding staff and researchers on data collection using digital tools. The training was held in four TARI stations in Kagera, Mbeya, and Kilimanjaro regions.
The training objective was to increase efficient, standardized, and quality-controlled data generation across institutions. The training covered data management components, including trait harmonization and fieldbook data collection, uploading and accessing data on Musabase, and preliminary data analysis.
“IITA initiated a regional banana breeding network in East Africa, of which standardization of data collection benefits all partners by facilitating data sharing of common material across different environments,” explained Dr Allan Brown, the IITA Banana Breeder.
Brown noted that digital data collection reduces human errors associated with pen and paper and improves accuracy and efficiency. Moreover, digital tools capture real-time data that enables fast decision-making. Simultaneously, cloud-based storage allows seamless collaboration among researchers across locations and supports long-term data tracking, enabling breeders to analyze trends and refine strategies over time.
Participants engaged in theoretical and hands-on practical sessions to ensure a deep understanding to apply in the field. They learned various components in the data collection process, including basic preliminary analysis on the uploaded data, incorporating covariates such as season and location and identifying any potential outliers for correction, as well as performing preliminary data analysis with a focus on real-time quality checks, such as identifying and correcting outliers, and modeling covariate effects.
“These digital tools make work easier and well-organized,” said Floramanka Ndakidemi, a researcher from TARI. In addition, Emmanuel Mlay, a researcher from TOSCI, applauded the initiative to use digital tools that reduce handwritten notes and lost files while making the data collection faster, more accurate, and easier to share. “Everything can be digital,” he excitedly said.
During the field visits, the participants integrated the digital tools. Each participant successfully created a Musabase account that would enable them to access data across the stations, with follow-up support in progress. IITA also provided 10 data collection devices to stations that conduct banana multi-location trials for efficient data collection activities.
This is part of a greater initiative to strengthen the National Programs, and in this case, TARI, which was recently also trained in using molecular markers to conduct varietal identification in experimental and farmers’ fields. The overall aim is to deliver much faster, high-yielding varieties to farmers. These interventions are now planned to be implemented with other members of the banana-breeding network. The activity is part of the Roots, Tubers, and Bananas breeding program.
Contributed by Hadi Rashid and Gloriana Ndibalema
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