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    Predicting soil permanganate oxidizable carbon (POXC) by coupling DRIFT spectroscopy and artificial neural networks (ANN)

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    Authors
    Margenot, Andrew J.
    O' Neill, Terry
    Sommer, Rolf
    Venkatesh, Akella
    Date Issued
    2020-01
    Language
    en
    Type
    Journal Article
    Review status
    Peer Review
    ISI journal
    Accessibility
    Limited Access
    Usage rights
    Copyrighted; all rights reserved
    Metadata
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    Citation
    Margenot, A.; O' Neill, T.; Sommer, R.; Venkatesh, A. (2020) Predicting soil permanganate oxidizable carbon (POXC) by coupling DRIFT spectroscopy and artificial neural networks (ANN). Computer and Electronics in Agriculture 168:105098 ISSN: 0168-1699
    Permanent link to cite or share this item: https://hdl.handle.net/10568/106801
    DOI: https://doi.org/10.1016/j.compag.2019.105098
    CGIAR Author ORCID iDs
    Rolf Sommerhttps://orcid.org/0000-0001-7599-9056
    AGROVOC Keywords
    spectroscopy; carbon; monitoring; permanganate; espectroscopia; carbono; vigilancia
    Countries
    Kenya
    Regions
    Africa; Eastern Africa
    Organizations Affiliated to the Authors
    Alliance of Bioversity International and CIAT; University of Illinois; University of California
    Investors/sponsors
    Federal Ministry for Economic Cooperation and Development, Germany
    Collections
    • Alliance Bioversity CIAT Journal Articles [1099]
    • CIAT Agroecosystems and Sustainable Landscapes (ASL) [68]
    • CIAT Articles in Journals [2636]

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