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    Proximal soil sensing of soil texture and organic matter with a prototype portable mid-infrared spectrometer

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    Authors
    Dhawale, N.
    Adamchuk, V.
    Prasher, S.
    Viscarra Rossel, Raphael
    Ismail, A.
    Kaur, J.
    Date
    2015
    Type
    Journal Article
    
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    Citation
    Dhawale, N. and Adamchuk, V. and Prasher, S. and Viscarra Rossel, R. and Ismail, A. and Kaur, J. 2015. Proximal soil sensing of soil texture and organic matter with a prototype portable mid-infrared spectrometer. European Journal of Soil Science. 66 (4): pp. 661-669.
    Source Title
    European Journal of Soil Science
    DOI
    10.1111/ejss.12265
    ISSN
    1351-0754
    School
    School of Molecular and Life Sciences (MLS)
    URI
    http://hdl.handle.net/20.500.11937/73694
    Collection
    • Curtin Research Publications
    Abstract

    Recent advances in semiconductor technologies have given rise to the development of mid-infrared (mid-IR) spectrometers that are compact, relatively inexpensive, robust and suitable for in situ proximal soil sensing. The objectives of this research were to evaluate a prototype portable mid-IR spectrometer for direct measurements of soil reflectance and to model the spectra to predict sand, clay and soil organic matter (SOM) contents under a range of field soil water conditions. Soil samples were collected from 23 locations at different depths in four agricultural fields to represent a range of soil textures, from sands to clay loams. The particle size distribution and SOM content of 48 soil samples were measured in the laboratory by conventional analytical methods. In addition to air-dry soil, each sample was wetted with two different amounts of water before the spectroscopic measurements were made. The prototype spectrometer was used to measure reflectance (R) in the range between 1811 and 898cm<sup>-1</sup> (approximately 5522 to 11136nm). The spectroscopic measurements were recorded randomly and in triplicate, resulting in a total of 432 reflectance spectra (48 samples×three soil water contents×three replicates). The spectra were transformed to log<inf>10</inf> (1/R) and mean centred for the multivariate statistical analyses. The 48 samples were split randomly into a calibration set (70%) and a validation set (30%). A partial least squares regression (PLSR) was used to develop spectroscopic calibrations to predict sand, clay and SOM contents. Results show that the portable spectrometer can be used with PLSR to predict clay and sand contents of either wet or dry soil samples with a root mean square error (RMSE) of around 10%. Predictions of SOM content resulted in RMSE values that ranged between 0.76 and 2.24%.

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