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    Predictive characterization methods for accessing and using CWR diversity

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    Authors
    Thormann, I.
    Parra-Quijano, M.
    Rubio-Teso, M.L.
    Endersen, D.T.F.
    Dias, S.
    Iriondo, Jose Maria
    Maxted, Nigel
    Date Issued
    2016
    Language
    en
    Type
    Book Chapter
    Review status
    Peer Review
    Accessibility
    Limited Access
    Metadata
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    Citation
    Thormann, I.; Parra-Quijano, M.; Rubio-Teso, M.L.; Endersen, D.T.F.; Dias, S.; Iriondo, J.M.; Maxted, N. (2016) Predictive characterization methods for accessing and using CWR diversity. In: Maxted, N. (et al. (eds.)) Enhancing crop genepool use: capturing wild relative and landrace diversity for crop improvement. CABI p. 64-77 ISBN: 978-1-78064-613-8
    Permanent link to cite or share this item: https://hdl.handle.net/10568/75709
    External link to download this item: https://www.cabi.org/bookshop/book/9781780646138
    AGROVOC Keywords
    wild plants; crops; geographic information systems; application methods; biodiversity
    Subjects
    GEOGRAPHIC INFORMATION SYSTEMS; APPLICATION METHODS; BIODIVERSITY;
    Organizations Affiliated to the Authors
    Bioversity International; International Treaty on Plant Genetic Resources for Food and Agriculture; Universidad Rey Juan Carlos; University of Oslo; University of Birmingham
    Related material
    Related reference: https://hdl.handle.net/10568/75694
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    • Bioversity Book Chapters [206]

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