Prediction of soil organic carbon using VIS-NIR spectroscopy: Application to Red Mediterranean soils from Croatia
Abstract
The objectives of
this research were: (i) to assess the accuracy of diffuse reflectance
spectroscopy (DRS) in predicting the soil organic
carbon (SOC) content, and (ii) determine the importance of wavelength ranges
and specific wavelengths in
the SOC prediction model. The reflectance spectra of a total
of 424 topsoils (0-25 cm) samples were
measured in a laboratory using a portable Terra Spec 4 Hi-Res
Mineral Spectrometer with a
wavelength range 350-2500 nm. Partial least squares regression (PLSR)
with leave-one-out cross validation was used to develop calibration models for SOC prediction.
The accuracy of the estimate determined by the coefficient of determination (R2),
the concordance correlation coefficient (ρc), the ratio of performance to
deviation (RPD), the range
error ratio (RER) and the root mean square error (RMSE) values of 0.83, 0.90, 2.42, 15.1 and 2.47 g C kg-1
respectively, indicated successful model
for SOC prediction. The near infrared (NIR) and the short-wave infrared (SWIR)
spectrums were more accurate than those in the visible (VIS) and short-wave
near-infrared (SWNIR) spectral regions. The wavelengths contributing most to
the prediction of SOC were at: 1925, 1915, 2170, 2315, 1875, 2260, 1910, 2380, 435,
1960, 2200, 1050, 1420, 1425 and 500 nm.
This study has shown that VIS-NIR
reflectance spectroscopy can be used as a rapid method for determining organic
carbon content in the Red Mediterranean soils that can be sufficient for
a rough screening.
Keywords
References
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Details
Primary Language
English
Subjects
-
Journal Section
Research Article
Authors
Boško Miloš
This is me
Institute for Adriatic Crops and Karst Reclamation, Put Duilova 11, 21 000 Split, Croatia
Croatia
Aleksandra Bensa
This is me
University of Zagreb, Faculty of Agriculture, Soil Science Department, Svetošimunska 25, 10 000 Zagreb, Croatia
Croatia
Publication Date
October 1, 2017
Submission Date
June 5, 2017
Acceptance Date
May 24, 2017
Published in Issue
Year 2017 Volume: 6 Number: 4
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