Characterization of Soil Shrink-Swell Potential Using the
Texas VNIR Diffuse Reflectance Spectroscopy Library
Katrina M. Hutchison, Cristine L.S. Morgan, and C. Tom Hallmark
Texas A&M University, College Station, Texas
Results
Shrink-swell potential of soil natural fabric is quantified by the coefficient of linear
extensibility (COLE). The COLE value is known to be correlated to clay content and
clay mineralogy along with other soil properties (McCormack et al. 1975). Visible near
infrared diffuse reflectance spectroscopy (VNIR-DRS) has been shown to quantify clay
content, clay mineralogy and to be correlated to soil shrink swell potential. (Waiser et
al. 2007, Brown 2005, Goetz et al. 2001). The overall goal of this study was to
determine if VNIR-DRS is an effective tool for directly quantifying COLE. If so, VNIRDRS can be used to scan soils in situ to map soil shrink-swell potential in the field.
Partial Least Squares Regression COLE
0.2
Table 1. Summary statistics for spectral library
Units
COLE
cmcm-1
Clay
%
Cation Exchange Capacity cmol(+)kg-1
pH
Base Saturation
%
CaCO3 Equivalent
%
Organic Carbon
%
Mean
0.049
27.6
16.2
6.5
73.5
19.3
0.52
Median
0.033
24.5
11.2
6.7
96
10.7
0.30
Max
0.24
84.1
105
9.5
100
100
7.66
Min
0.001
0
0
3.3
0
0.1
0
Predicted COLE, cm cm-1
Introduction
N
1296
1295
1294
1295
1271
485
1295
1:1 line
y=0.564+0.017
0.16
0.12
0.08
0.04
0
0
0.04
0.08
0.12
0.16
0.2
Measured COLE, cm cm-1
Objectives
1:1 line
y=0.585x+0.022
Predicted COLE, cm cm-1
2. Create predictor models of COLE, clay content, and CEC that might affect COLE
using the VNIR-DRS spectrometer
3.
Predicted COLE, cm cm-1
1. Provide a summary and descriptive statistics of the soils in the spectral library
0.2
0.16
0.12
0.08
0.04
Methods and Materials
0
0
 2454 soil samples, archived by the Texas Agricultural Experiment Station’s Soil
0.04
0.08
0.12
0.16
100
1:1 line
y= 0.833x + 0.010
0.16
0.12
0.08
60
40
0.04
20
0
0
0
0.2
1:1 line
y=1.038x-0.847
80
Predicted clay,%
0.2
Create a VNIR-DRS spectral library from archived Texas soils
Partial Least Square Regression, clay
Predicting COLE using clay & CEC
Predicting COLE using clay
0.04
0.08
0.12
0.16
0
0.2
Characterization Laboratory, were transferred to 20 ml vials.
40
60
80
100
Measured clay, %
Measured COLE, cm cm-1
Measured COLE, cm cm-1
20
Partial Least Squares Regression CEC
80
PLS of VNIR-DRS
with an AgSpec® Pro (Analytical Spectral Devices, Inc.) that has a spectral range
of 350–2500 nm.
RMSD
COLE
Clay
CEC
0.028
8.6
8.5
-1
Table 2. Summary of Modeling Results
Regression, Pedotransfer
Functions
COLE using
COLE using
clay and CEC
clay
0.019
0.029
r2
0.61
0.83
0.74
0.82
0.57
RPD
1.6
2.4
1.9
2.3
1.5
Predicted CEC, cmol(+)kg
 Each 20 ml sample was transferred into a borosilicate glass puck and scanned
1:1 line
y=1.130x-0.222
60
40
20
0
0
20
40
60
80
Measured CEC, cmol(+)kg-1
Conclusion
 2454 archived soils from Texas are now part of a spectral VNIR library.
 Soil COLE values from the Texas soils are highly correlated to total clay content and CEC.
 The spectral data were treated by splicing, averaging, and taking the first
%
Cla
y
derivative.
 Partial Least Squares (PLS) regression was performed with Unscrambler 9.0 to
create prediction models to convert spectral reflectance to COLE, clay content,
and cation exchange capacity (CEC).
Calibration
100 0
Validation
 To calibrate the prediction model, 70% of the
80
20
soil samples were used and the remaining
samples were used for model validation.
60
40
 To compare VNIR to traditional pedotransfer
40
60
functions, CEC and clay content were used
to predict COLE. Models were built using
20
80
multiple and linear regression, and the same
0
100
70/30 calibration/validation data.
%
t
Sil
100
80
60
40
% Sand
20
0
 Regression using clay content alone and clay content + CEC predict COLE better than using
VNIR-DRS with partial least square regression.
 RPD values show COLE, CEC, and clay content can be predicted effectively using VNIR and
that prediction of clay content is the most stable and effective.
References
 Brown, D.J., K.D. Shepherd, M.G. Walsh, M.D. Mays and T.G. Reinsch. 2005. Global soil characterization with VNIR
diffuse reflectance spectroscopy. Geoderma 132:273-290.
 Goetz, A.F.H., S. Chabrillat and Z. Lu. 2001. Field reflectance spectrometry for detection of swelling clays at
construction sites. Field Analytical Chemistry and Technology 5:143-155.
 McCormack, D.E. and L.P. Wilding. 1975. Soil properties influencing swelling in Canfield and Geeburg soils. Soil Sci.
Soc. Am. J. 39:496-502.
 Waiser, T., C.L.S. Morgan, D.J. Brown and C.T. Hallmark. 2007. In situ characterization of soil clay content with visible
near-infrared diffuse reflectance spectroscopy. Soil Sci. Soc. Am. J. 71:389-396.
Acknowledgements
Thank you to the Texas USDA NRCS Soil Survey for funding this project. Thanks to the Texas Agricultural Experiment
Station’s Soil Characterization Lab, including Donna Prochaska and Morgan Arnette for their assistance with data
management.