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    Do we really need large spectral libraries for local scale SOC assessment with NIR spectroscopy?

    Access Status
    Fulltext not available
    Authors
    Guerrero, C.
    Wetterlind, J.
    Stenberg, B.
    Mouazen, A.
    Gabarrón-Galeote, M.
    Ruiz-Sinoga, J.
    Zornoza, R.
    Viscarra Rossel, Raphael
    Date
    2016
    Type
    Journal Article
    
    Metadata
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    Citation
    Guerrero, C. and Wetterlind, J. and Stenberg, B. and Mouazen, A. and Gabarrón-Galeote, M. and Ruiz-Sinoga, J. and Zornoza, R. et al. 2016. Do we really need large spectral libraries for local scale SOC assessment with NIR spectroscopy?. Soil and Tillage Research. 155: pp. 501-509.
    Source Title
    Soil and Tillage Research
    DOI
    10.1016/j.still.2015.07.008
    ISSN
    0167-1987
    School
    School of Molecular and Life Sciences (MLS)
    URI
    http://hdl.handle.net/20.500.11937/74023
    Collection
    • Curtin Research Publications
    Abstract

    Near infrared (NIR) spectroscopy was used to predict the soil organic carbon (SOC) contents at local scale in eleven target sites. For that, eight spectral libraries of different sizes (ranging from 3482 to 36 samples) were used to construct national, provincial and local scale models. Inaccurate predictions were obtained except when the largest national library was used to construct the model. We also obtained SOC predictions once the models were adapted to target sites characteristics. For the models' adaptation, we used a two-step approach consisting on spiking (as first step) and extra-weighting (as second step). The effect of spiking was small in larger-sized models and high in smaller-sized models, whereas the effect of extra-weighting was small in smaller-sized models and large in larger-sized models. The very high accuracy obtained after models' adaptation (R2>0.95; RPIQ>5.48), regardless of the size of the spectral library, suggests that large spectral libraries are not needed for local scale SOC assessment. These results have important implications regarding the way that NIR spectroscopy can result highly effective for land management and how users can focus and organize the analytical efforts.

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