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Data management in multi-disciplinary African RTB crop breeding programs

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Title Data management in multi-disciplinary African RTB crop breeding programs
 
Creator Agbona, A .
Peteti, P.
Teeken, Béla
Olaosebikan, O.
Bello, A.A.
Parkes, E.
Rabbi, I.Y.
Mueller, L.
Egesi, Chiedozie N.
Kulakow, Peter
 
Subject genotypes
phenotypes
databases
ontology
data management
 
Description Quality 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 breedingdecisions. 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.
 
Date 2023
2023-01-24T09:25:07Z
2023-01-24T09:25:07Z
 
Type Book Chapter
 
Identifier Agbona, A., Peteti, P., Teeken, B., Olaosebikan, O., Bello, A., Parkes, E., ... & Kulakow, P. (2023). Data management in multi-disciplinary African RTB crop breeding programs. In H.F. Williamson and S. Leonelli, Towards responsible plant data linkage: data challenges for agricultural research and development. Cham, Switzerland: Springer, (p. 85-103).
9783031132759
9783031132766
https://hdl.handle.net/10568/127999
https://doi.org/10.1007/978-3-031-13276-6_5
BIOTECH & PLANT BREEDING
 
Language en
 
Rights CC-BY-4.0
Open Access
 
Format 85-103
application/pdf
 
Publisher Springer International Publishing