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    Improving root characterisation for genomic prediction in cassava

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    Journal Article (2.735Mb)
    Date
    2020-05-14
    Author
    Yonis, B.O.
    del Carpio, D.P.
    Wolfe, M.
    Jannink, J.L.
    Kulakow, P.
    Rabbi, I.
    Type
    Journal Article
    Review Status
    Peer Review
    Target Audience
    Scientists
    Metadata
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    Abstract/Description
    Cassava is cultivated due to its drought tolerance and high carbohydrate-containing storage roots. The lack of uniformity and irregular shape of storage roots poses constraints on harvesting and post-harvest processing. Here, we phenotyped the Genetic gain and offspring (C1) populations from the International Institute of Tropical Agriculture (IITA) breeding program using image analysis of storage root photographs taken in the field. In the genome-wide association analysis (GWAS), we detected for most shape and size-related traits, QTL on chromosomes 1 and 12. In a previous study, we found the QTL on chromosome 12 to be associated with cassava mosaic disease (CMD) resistance. Because the root uniformity is important for breeding, we calculated the standard deviation (SD) of individual root measurements per clone. With SD measurements we identified new significant QTL for Perimeter, Feret and Aspect Ratio on chromosomes 6, 9 and 16. Predictive accuracies of root size and shape image-extracted traits were mostly higher than yield trait prediction accuracies. This study aimed to evaluate the feasibility of the image phenotyping protocol and assess GWAS and genomic prediction for size and shape image-extracted traits. The methodology described and the results are promising and open up the opportunity to apply high-throughput methods in cassava.
    https://dx.doi.org/10.1038/s41598-020-64963-9
    Multi standard citation
    Permanent link to this item
    https://hdl.handle.net/20.500.12478/7646
    IITA Authors ORCID
    Jean-Luc Janninkhttps://orcid.org/0000-0003-4849-628X
    Peter Kulakowhttps://orcid.org/0000-0002-7574-2645
    Ismail Rabbihttps://orcid.org/0000-0001-9966-2941
    Digital Object Identifier (DOI)
    https://dx.doi.org/10.1038/s41598-020-64963-9
    Research Themes
    Biotech and Plant Breeding
    IITA Subjects
    Agronomy; Cassava; Disease Control; Food Security; Plant Breeding; Plant Diseases; Plant Production
    Agrovoc Terms
    Cassava; African Cassava Mosaic Virus; Processing; Plant Diseases; Nigeria
    Regions
    Africa; West Africa
    Countries
    Nigeria
    Hubs
    Headquarters and Western Africa Hub
    Journals
    Scientific Reports
    Collections
    • Journal and Journal Articles4835
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