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Is the estimation of soil organic carbon using the colour space model, based on visible spectroscopy range, a reliable approach?

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00027073%3A_____%2F24%3AN0000089" target="_blank" >RIV/00027073:_____/24:N0000089 - isvavai.cz</a>

  • Result on the web

    <a href="https://bsssjournals.onlinelibrary.wiley.com/doi/epdf/10.1111/sum.13147" target="_blank" >https://bsssjournals.onlinelibrary.wiley.com/doi/epdf/10.1111/sum.13147</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1111/sum.13147" target="_blank" >10.1111/sum.13147</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Is the estimation of soil organic carbon using the colour space model, based on visible spectroscopy range, a reliable approach?

  • Original language description

    Traditionally, soil colour attributes have been determined using the Munsell Colour Chart (MCC). However, the lack of standardization with this method has made it more difficult to assess soil properties, particularly soil organic carbon (SOC). In contrast, reflectance spectroscopy (RS) across the visible (Vis, 400-800 nm), near-infrared (NIR, 800-2500 nm) and Vis-NIR (350-2500 nm) spectral regions has been recognized as a more reliable approach for predicting SOC. As a result, soil scientists have increasingly adopted RS to obtain soil colour parameters, addressing the limitations of the MCC. However, because RS techniques for soil colour analysis is typically limited to the VIS range, key information from the NIR and Vis-NIR regions are often neglected or eliminated. This study examined the effectiveness of the VIS-based colour approach in estimating SOC compared with spectroscopy in the VIS, NIR and Vis-NIR ranges. Fifteen soil colour parameters were derived from the VIS spectrum, and 12 colour indices were calculated from these parameters. Three multivariate models such as random forest (RF), Cubist and support vector machine regression (SVMR) were used for prediction, along with various preprocessing algorithms to remove artefacts. The results indicated that, compared with VIS spectroscopy (R2 = .54) and the VIS-based colour method (R2 = .45), the pre-processed Vis-NIR data produced the most accurate results (R2 = .72). This suggests that the VIS range alone lacks adequate information, likely affecting the accuracy of the VIS-based colour dataset, as it is derived solely from this region. Although the introduction of colour indices slightly improved the VIS-based colour approach (R2 = .47), the results were still less accurate than those obtained using both the Vis-NIR and NIR spectroscopy ranges or even the VIS range alone (R2 = .54). The findings of this study highlight the need for caution when using VIS-based colour methods for SOC estimation, as high SOC levels information is not necessarily restricted to the VIS region.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    40104 - Soil science

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    SOIL USE AND MANAGEMENT

  • ISSN

    0266-0032

  • e-ISSN

    1475-2743

  • Volume of the periodical

    40

  • Issue of the periodical within the volume

    4

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    16

  • Pages from-to

    e13147

  • UT code for WoS article

    001370298300001

  • EID of the result in the Scopus database