Data Management in Multi-disciplinary African RTB Crop Breeding Programs

Abstract

AbstractQuality phenotype and genotype data are important for the success of a breeding program. Like most programs, African breeding programs generate large multi-disciplinary phenotypic and genotypic datasets from several locations, that must be carefully managed through the use of an appropriate database management system (DBMS) in order to generate reliable and accurate information for breeding-decisions. A DBMS is essential in data collection, storage, retrieval, validation, curation and analysis in plant breeding programs to enhance the ultimate goal of increasing genetic gain. The International Institute of Tropical Agriculture (IITA), working on the roots, tubers and banana (RTB) crops like cassava, yam, banana and plantain has deployed a FAIR-compliant (Findable, Accessible, Interoperable, Reusable) database; BREEDBASE. The functionalities of this database in data management and analysis have been instrumental in achieving breeding goals. Standard Operating Procedures (SOP) for each breeding process have been developed to allow a cognitive walkthrough for users. This has further helped to increase the usage and enhance the acceptability of the system. The wide acceptability gained among breeders in global cassava research programs has resulted in improvements in the precision and quality of genotype and phenotype data, and subsequent improvement in achievement of breeding program goals. Several innovative gender responsive approaches and initiatives have identified users and their preferences which have informed improved customer and product profiles. A remaining bottleneck is the effective linking of data on preferences and social information of crop users with technical breeding data to make this process more effective.