Prediction of Soil Organic Matter Content Under Moist Conditions Using VIS-NIR Diffuse Reflectance Spectroscopy

Abstract Soil moisture is known to influence the accuracy of predictions of soil organic matter (SOM) by visible and near-infrared diffuse reflectance spectroscopy. However, the predictions may still be sufficient for analysis under specific moisture conditions with acceptable accuracy. Our study aimed to assess the accuracy of predicting SOM under various moisture conditions and to explore the appropriate soil moistures for reliable predictions. In this study, reflectance spectra (380–2,400 nm) of 62 soil samples were measured in the laboratory under various moisture conditions. Partial least-squares regression was used to build the calibration model between the first-derivative spectra and Log (SOM). The results showed that visible and near-infrared method was capable of predicting SOM content under moist conditions and that the prediction was reliable when soil moisture was less than 22% (wt/wt). The results of this study identify the potential to predict SOM under wet soil conditions in areas with loam soils and should help determine the range of soil moisture appropriate in SOM predictions for future research.

[1]  B. Stenberg.  Effects of soil sample pretreatments and standardised rewetting as interacted with sand classes on Vis-NIR predictions of clay and soil organic carbon , 2010 .

[2]  C. Hurburgh,et al.  INFLUENCE OF SOIL MOISTURE ON NEAR-INFRARED REFLECTANCE SPECTROSCOPIC MEASUREMENT OF SOIL PROPERTIES , 2005 .

[3]  Marvin H. Hall,et al.  Carbon and Nitrogen Analysis of Soil Fractions Using Near-Infrared Reflectance Spectroscopy , 1991 .

[4]  C. Hurburgh,et al.  Near-Infrared Reflectance Spectroscopy–Principal Components Regression Analyses of Soil Properties , 2001 .

[5]  R. Henry,et al.  Simultaneous Determination of Moisture, Organic Carbon, and Total Nitrogen by Near Infrared Reflectance Spectrophotometry , 1986 .

[6]  R. Joergensen,et al.  Usefulness of near-infrared spectroscopy to determine biological and chemical soil properties: Importance of sample pre-treatment , 2008 .

[7]  Dudley A. Williams,et al.  Optical properties of water in the near infrared. , 1974 .

[8]  E. Ben-Dor.  Quantitative remote sensing of soil properties , 2002 .

[9]  E. V. Thomas,et al.  Partial least-squares methods for spectral analyses. 1. Relation to other quantitative calibration methods and the extraction of qualitative information , 1988 .

[10]  Bernard Tychon,et al.  Detection of carbon stock change in agricultural soils using spectroscopic techniques , 2006 .

[11]  G. Fystro.  The prediction of C and N content and their potential mineralisation in heterogeneous soil samples using Vis–NIR spectroscopy and comparative methods , 2002, Plant and Soil.

[12]  S. Wold,et al.  PLS-regression: a basic tool of chemometrics , 2001 .

[13]  W. Hively,et al.  Visible-near infrared reflectance spectroscopy for assessment of soil properties in a semi-arid area of Turkey , 2010 .

[14]  B. Herbert,et al.  A New Spectrophotometric Method for Rapid Semiquantitative Determination of Soil Organic Carbon , 2009 .

[15]  A. Walkley,et al.  AN EXAMINATION OF THE DEGTJAREFF METHOD FOR DETERMINING SOIL ORGANIC MATTER, AND A PROPOSED MODIFICATION OF THE CHROMIC ACID TITRATION METHOD , 1934 .

[16]  Keith D. Shepherd,et al.  Prediction of Soil Fertility Properties from a Globally Distributed Soil Mid-Infrared Spectral Library , 2010 .

[17]  R. V. Rossel,et al.  Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties , 2006 .

[18]  Cristine L. S. Morgan,et al.  Simulated in situ characterization of soil organic and inorganic carbon with visible near-infrared diffuse reflectance spectroscopy , 2009 .

[19]  Haiyan Song,et al.  Evaluating Soil Organic Matter with visible spectroscopy , 2005, 2005 IEEE Instrumentationand Measurement Technology Conference Proceedings.

[20]  N. Tripathi,et al.  Analysis of VNIR (400–1100 nm) spectral signatures for estimation of soil organic matter in tropical soils of Thailand , 2004 .

[21]  S. R. Abella,et al.  Estimating Organic Carbon from Loss-On-Ignition in Northern Arizona Forest Soils , 2007 .