Estimation of Some Chemical Properties of an Agricultural Soil by Spectroradiometric Measurements

Abstract The contents of nitrogen and organic carbon in an agricultural soil were analyzed using reflectance measurements ( n = 52) performed with an ASD FieldSpec-II spectroradiometer. For parameter prediction, empirical models based on partial least squares (PLS) regression were defined from the measured reflectance spectra (0.4 to 2.4 μm). Here, reliable estimates were obtained for nitrogen content, but prediction accuracy was only moderate for organic carbon. For nitrogen, the real spatial pattern of within-field variability was reproduced with high accuracy. The results indicate the potential of this method as a quick screening tool for the spatial assessment of nitrogen and organic carbon, and therefore an appropriate alternative to time- and cost-intensive chemical analysis in the laboratory.

[1]  K. Shepherd,et al.  Development of Reflectance Spectral Libraries for Characterization of Soil Properties , 2002 .

[2]  ANALYSIS OF IRON CONTENTS IN CARBONATE BEDROCK BY SPECTRORADIOMETRIC DETECTION BASED ON EXPERIMENTALLY DESIGNED SUBSTRATES , 1998 .

[3]  U. Schwertmann,et al.  QUANTITATIVE RELATIONSHIPS BETWEEN SOIL COLOR AND HEMATITE CONTENT , 1983 .

[4]  Ewald Schnug,et al.  Sampling and nutrient recommendations ‐ the future , 1998 .

[5]  A. Rencz,et al.  Remote sensing for the earth sciences , 1999 .

[6]  E. Ben-Dor,et al.  NEAR INFRARED ANALYSIS (NIRA) AS A METHOD TO SIMULTANEOUSLY EVALUATE SPECTRAL FEATURELESS CONSTITUENTS IN SOILS , 1995 .

[7]  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.

[8]  J. Schepers,et al.  Precision agriculture—what's in our future , 1998 .

[9]  Randy J. Pell,et al.  Multiple outlier detection for multivariate calibration using robust statistical techniques , 2000 .

[10]  T. Jarmer,et al.  Quantitative analysis of soil chemical properties with diffuse reflectance spectrometry and partial least-square regression: A feasibility study , 2003, Plant and Soil.

[11]  P. Lootens,et al.  Possibilities of near infrared reflectance spectroscopy for the prediction of organic carbon concentrations in grassland soils , 2005, The Journal of Agricultural Science.

[12]  G. McCarty,et al.  The potential of diffuse reflectance spectroscopy for the determination of carbon inventories in soils. , 2002, Environmental pollution.

[13]  E. R. Stoner,et al.  REFLECTANCE PROPERTIES OF SOILS , 1986 .

[14]  B. Frazier,et al.  Relationship between soil organic carbon and Landsat TM data in eastern Washington , 1994 .

[15]  Daniel Schläpfer,et al.  1st EARSEL Workshop on Imaging Spectroscopy , 1998 .

[16]  R. Plant.  Site-specific management: the application of information technology to crop production , 2001 .

[17]  U. Schmidhalter,et al.  High resolution topsoil mapping using hyperspectral image and field data in multivariate regression modeling procedures , 2006 .

[18]  J. Hummel,et al.  Reflectance technique for predicting soil organic matter. , 1980 .

[19]  A. J. Turgeon,et al.  Determination of Soil Separates with near Infrared Reflectance Spectroscopy , 1996 .

[20]  Eyal Ben-Dor,et al.  Near-Infrared Analysis as a Rapid Method to Simultaneously Evaluate Several Soil Properties , 1995 .

[21]  Alex B. McBratney,et al.  Soil chemical analytical accuracy and costs: implications from precision agriculture , 1998 .

[22]  D. P. Franzmeier,et al.  Characterization of Iron Oxide Minerals by Second-Derivative Visible Spectroscopy 1 , 1984 .