Development of field techniques to predict soil carbon, soil nitrogen and root density from soil spectral reflectance : a thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Soil Science at Massey University, Palmerston North, New Zealand
Loading...
Date
2009
DOI
Open Access Location
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Massey University
Rights
The Author
Abstract
The objectives of this research were to develop and evaluate a field method for in
situ measurement of soil properties using visible near-infrared reflectance spectroscopy
(Vis-NIRS). A probe with an independent light source for acquiring soil reflectance
spectra from soil cores was developed around an existing portable field spectrometer
(ASD FieldSpecPro, Boulder, CO, USA; 350-2500 nm).
Initial experiments tested the ability of the acquired spectra to predict plant root
density, an important property in soil carbon dynamics. Reflectance spectra were
acquired from soil containing ryegrass roots (Lolium multiflorum) grown in Allophanic
and Fluvial Recent soils in a glasshouse pot trial. Differences in root density were
created by differential nitrogen and phosphorus fertilization. Partial least squares
regression (PLSR) was used to calibrate spectral data (pre-processed by smoothing and
transforming spectra to the first derivative) against laboratory-measured root density
data (wet-sieve technique). The calibration model successfully predicted root densities
(r2 = 0.85, RPD = 2.63, RMSECV = 0.47 mg cm-3) observed in the pots to a moderate
level of accuracy. This soil reflectance probe was then tested using a soil coring system
to acquire reflectance spectra from two soils under pasture (0-60 mm soil depths) that
had contrasting root densities. The PLSR calibration models for predicting root density
were more accurate when soil samples from the two soils were separated rather than
grouped. A more accurate prediction was found in Allophanic soils (r2 = 0.83, RPD =
2.44, RMSECV = 1.96 mg g-1) than in Fluvial Recent soils (r2 = 0.75, RPD = 1.98,
RMSECV = 5.11 mg g-1). The Vis-NIRS technique was then modified slightly to work
on a soil corer that could be used to measure root contents from deeper soil profiles (15-
600 mm depth) in arable land (90-day-old maize crop grown in Fluvial Recent soils).
PLSR calibration models were constructed to predict the full range of maize root
densities (r2 = 0.83, RPD = 2.42, RMSECV = 1.21 mg cm-3) and also soil carbon (C)
and nitrogen (N) concentrations that had been determined in the laboratory (LECO FP-
2000 CNS Analyser; Leco Corp., St Joseph, MI, USA).
Further studies concentrated on improving the Vis-NIRS technique for prediction of
total C and N concentrations in differing soil types within different soil orders in the
field. The soil coring method used in the maize studies was evaluated in permanent and
recent pastoral soils (Pumice, Allophanic and Tephric Recent in the Taupo-Rotorua
Volcanic Zone, North Island) with a wide range of soil organic matter contents resulting
from different times (1-5 years) since conversion from forest soils. Without any sample
preparation, other than the soil surface left after coring, it was possible to predict soil C
and N concentrations with moderate success (C prediction r2 = 0.75, RMSEP = 1.23%,
RPD = 1.97; N prediction r2 = 0.80, RMSEP = 0.10%, RPD = 2.15) using a technique
of acquiring soil reflectance spectra from the horizontal cross-section of a soil core (H
method).
The soil probe was then modified to acquire spectra from the curved vertical wall of
a soil core (V method), allowing the spectrometer’s field of view to increase to record
the reflectance features of the whole soil sample taken for laboratory analysis. Improved
predictions of soil C and N concentrations were achieved with the V method of spectral
acquisition (C prediction r2 = 0.97, RMSECV = 0.21%, RPD = 5.80; N prediction r2 =
0.96, RMSECV = 0.02%, RPD = 5.17) compared to the H method (C prediction r2 =
0.95, RMSECV = 0.27%, RPD = 4.45; N prediction r2 = 0.94, RMSECV = 0.03%, RPD
= 4.25).
The V method was tested for temporal robustness by assessing its ability to predict
soil C and N concentrations of Fluvial Recent soils under permanent pasture in different
seasons. When principal component analysis (PCA) was used to ensure that the spectral
dimensions (which were responsive to water content) of the data set used for developing
the PLSR calibration model embraced those of the “unknown” soil samples, it was
possible to predict soil C and N concentrations in “unknown” samples of widely
different water contents (in May and November), with a high level of accuracy (C
prediction r2 = 0.97, RMSEP = 0.36%, RPD = 3.43; N prediction r2 = 0.95, RMSEP =
0.03%, RPD = 3.44).
This study indicates that Vis-NIRS has considerable potential for rapid in situ
assessment of soil C, N and root density. The results demonstrate that field root
densities in pastoral and arable soil can be predicted independently from total soil C,
which will allow researchers to predict C sequestration from root production. The
recommended “V” technique can be used to assess spatial and temporal variability of
soil carbon and nitrogen within soil profiles and across the landscape. It can also be
used to assess the rate of C sequestration and organic matter synthesis via root density
prediction. It reduces the time, labour and cost of conventional soil analysis and root
density measurement.
Description
Keywords
Soil properties, Soil carbon, Root density, in-situ assessment