This is an author produced version of a paper published in Advances in Agronomy.
This paper has been peer-reviewed. It does not include the final journal pagination.
Citation for the published paper:
Bo Stenberg, Raphael A. Viscarra Rossel, Abdul Mounem Mouazen, and Johanna
Wetterlind, Visible and Near Infrared Spectroscopy in Soil Science. In Donald L.
Sparks, editor: Advances in Agronomy, Vol. 107, Burlington: Academic Press,
2010, pp. 163-215. http://dx.doi.org/10.1016/S0065-2113(10)07005-7
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1
Visible and near infrared spectroscopy in soil science
Bo Stenberg
a*
, Raphael A. Viscarra Rossel
b
, Abdul Mounem Mouazen
c
, Johanna Wetterlind
d
a*
Department of Soil and Environment, Swedish University of Agricultural Sciences, PO Box 234, SE-532
23 Skara, Sweden Tel: +46 511 67276, Fax: +46 511 67134, E-mail: bo.stenberg@mark.slu.se
(Corresponding author)
b
CSIRO Land & Water, Bruce E. Butler Laboratory, GPO Box 1666 Canberra ACT 2601, Australia, E-
mail: raphael.viscarra-rossel@csiro.au
c
Natural Resources Department, Cranfield University, MK43 0AL, United Kingdom, E-mail:
a.mouazen@cranfield.ac.uk
d
Department of Soil and Environment, Swedish University of Agricultural Sciences, PO Box 234, SE-532
23 Skara, Sweden, E-mail: Johanna.wetterlind@mark.slu.se
Abstract
This chapter provides a review on the state of soil visible–near infrared (vis–NIR) spectroscopy. Our
intention is for the review to serve as a source of up-to date information on the past and current role of
vis–NIR spectroscopy in soil science. It should also provide critical discussion on issues surrounding the
use of vis–NIR for soil analysis and on future directions. To this end, we describe the fundamentals of
visible and infrared diffuse reflectance spectroscopy and spectroscopic multivariate calibrations. A review
of the past and current role of vis–NIR spectroscopy in soil analysis is provided, focusing on important
soil attributes such as soil organic matter (SOM), minerals, texture, nutrients, water, pH, and heavy
metals. We then discuss the performance and generalization capacity of vis–NIR calibrations, with
particular attention on sample pre-tratments, co-variations in data sets, and mathematical data
preprocessing. Field analyses and strategies for the practical use of vis–NIR are considered. We
conclude that the technique is useful to measure soil water and mineral composition and to derive robust
calibrations for SOM and clay content. Many studies show that we also can predict properties such as pH
and nutrients, although their robustness may be questioned. For future work we recommend that research
should focus on: (i) moving forward with more theoretical calibrations, (ii) better understanding of the
complexity of soil and the physical basis for soil reflection, and (iii) applications and the use of spectra for
soil mapping and monitoring, and for making inferences about soils quality, fertility and function. To do
this, research in soil spectroscopy needs to be more collaborative and strategic. The development of the
Global Soil Spectral Library might be a step in the right direction.
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Contents
Abstract .................................................................................................................................. 2
1. Introduction ........................................................................................................................ 3
1.1. Fundamentals of soil visible and infrared diffuse reflectance spectroscopy............... 4
1.2. Spectroscopic multivariate calibrations ...................................................................... 5
1.3. Considerations for developing spectroscopic calibrations .......................................... 6
2. Past and current role of vis–NIR in soil analysis ............................................................... 6
2.1. Soil organic matter (SOM).......................................................................................... 7
2.2. Soil mineralogy ......................................................................................................... 14
2.3. Soil texture ................................................................................................................ 16
2.4. Plant nutrients............................................................................................................ 19
2.5. pH and lime requirement........................................................................................... 20
2.6. Organic matter quality and microbial processes ....................................................... 20
2.7. Heavy metals and other soil contaminants................................................................ 22
2.8 Soil moisture .............................................................................................................. 23
3. Factors influencing the performance and generality of vis–NIR calibrations.................. 25
3.1. Sample pre-treatment ................................................................................................ 25
3.2. Data pre-treatment..................................................................................................... 26
4 Field analyses .................................................................................................................... 27
5. Strategies for practical use of vis–NIR spectroscopy for soil analysis ............................ 28
5.1. Local influence of target area.................................................................................... 30
5.2 Screening and mapping of overall soil variability ..................................................... 31
5.3. Soil quality and fertility assessment.......................................................................... 32
6. General and future aspects ............................................................................................... 32
References ............................................................................................................................ 32
1. Introduction
Soil is a fundamental natural resource which people rely on for the production of food, fiber, and energy.
Soil is a regulator of water movement in the landscape, it is an environmental filter for metals, nutrients,
and other contaminants that may leach into the environment, it is a biological habitat and gene reserve and
is the foundation for buildings and other constructions. Soil is also regarded as a potential sink for carbon
to mitigate global warming. The ability of a soil to support any of these functions depends on its structure;
composition; and chemical, biological, and physical properties, all of which are both spatially and
temporally variable (Blum, 1993; Bouma, 1997; Harris et al., 1996; Jenny, 1980; Karlen et al., 1997).
Fundamentally, soil is a complex matrix that consists of organic and inorganic mineral matter, water, and
air. The organic material in soils ranges from decomposed and stable humus to fresh, particulate residues
of various origins. The distribution of these different organic pools in soil influences biological activity,
nutrient availability and dynamics, soil structure and aggregation, and water-holding capacity (Skjemstad
et al., 1997). The inorganic mineral fraction is often described by its particle size distribution (proportions
of sand, silt, and clay) and also by additional subclasses in various classification systems (Hillel and
Hillel, 1998). Coarse sand particles typically consist of resistant minerals such as quartz and feldspars,
while fine particles consist of various clay minerals that have undergone various degrees of weathering.
Thus, the mineral fraction can be defined by the parent material, soil age, climate, relief, and position in
the landscape ( Jenny, 1980). Different clay minerals have different properties, for example, some are able
to hold water in their lattices, giving them their shrink–swell behavior, while others are important as a
source of potassium on weathering (Andrist-Rangel et al., 2006). Clay particles are characterized by
negatively charged surfaces and some clay minerals have more negatively charged surfaces than others.
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This is important in terms of the physics and chemistry of the soil as these charged surfaces regulate
aggregation processes and the cat ion exchange capacity (CEC) of the soil, which affects the release and
retention of nutrients as well its buffering capacity (Hillel and Hillel, 1998).
No two soils are exactly alike and variations occur over short distances, vertically and horizontally. Given
the importance of soils, there is a need for regular monitoring to detect changes in its status so as to
implement appropriate management in the event of degradation. Soil surveying may be performed at
national levels for the inventory of soil resources, or for agriculture at regional, farm or field scales, for
example, to monitor carbon, nutrient status, pH, and salinity.
Recognition by farmers of the high variability of soils, even within fields, and the advent of global
positioning systems (GPS) facilitating real time positions have led to the development of the concept of
precision agriculture (PA) or site-specific agriculture. PA aims to improve resource use efficiency by
variable rate applications to supply a crop with precisely what it requires at a high spatial resolution
(Robert et al., 1991).
As a consequence of global warming, there is also much focus on developing soil management practices
supporting carbon sequestration in soils to reduce atmospheric carbon dioxide. Intensive and reliable
mapping is required to monitor changes in soil organic pools (Bricklemyer et al., 2005; Mooney et al.,
2004). All these aspects require accurate inexpensive soil analysis.
Over the past two decades, research on the use of visible–near infrared (vis–NIR) diffuse reflectance
spectroscopy in soil science has increased rapidly (Ben-Dor and Banin, 1995a; Bowers and Hanks, 1965;
Brown et al., 2006; Shepherd and Walsh, 2002; Stenberg et al., 1995; Sudduth et al., 1989; Viscarra
Rossel and McBratney, 1998; Wetterlind et al., 2008b). The main focus has been on basic soil
composition, particularly soil organic matter (SOM), texture, and clay mineralogy, but also nutrient
availability and properties such as fertility, structure, and microbial activity. There are many reasons for
the interest in vis–NIR. For example, sample preparation involves only drying and crushing, the sample is
not affected by the analysis in any way, no (hazardous) chemicals are required, measurement takes a few
seconds, several soil properties can be estimated from a single scan, and the technique can be used both in
the laboratory and in situ (Viscarra Rossel et al., 2006c).
The aim of this chapter is to provide a review on the current state of vis–NIR spectroscopy in soil science.
We begin by describing some of the fundamentals of soil diffuse reflectance spectroscopy, as well as the
spectroscopic calibrations needed to estimate soil properties. We then review and discuss the use of vis–
NIR for estimating important soil properties and examine the influence of external factors, such as
experimental design and sample and spectral pretreatments, on the calibrations. We then consider the
potential for field vis–NIR measurements and strategies for its practical implementation, and
finish by providing a synthesis and discuss the future of vis–NIR spectroscopy.
1.1. Fundamentals of soil visible and infrared diffuse reflectance spectroscopy
To generate a soil spectrum, radiation containing all relevant frequencies in the particular range is directed
to the sample. Depending on the constituents present in the soil the radiation will cause individual
molecular bonds to vibrate, either by bending or stretching, and they will absorb light, to various degrees,
with a specific energy quantum corresponding to the difference between two energy levels. As the energy
quantum is directly related to frequency (and inversely related to wavelength), the resulting absorption
spectrum produces a characteristic shape that can be used for analytical purposes (Miller, 2001). The
frequencies at which light is absorbed appear as a reduced signal of reflected radiation and are displayed
in % reflectance (R), which can then be transformed to apparent absorbance: A = log(1/R) (Fig. 1). The
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wavelength at which the absorption takes place (i.e., the size of the energy quantum) depends also on the
chemical matrix and environmental factors such as neighboring functional groups and temperature,
allowing for the detection of a range of molecules which may contain the same type of bonds.
When NIR radiation interacts with a soil sample, it is the overtones and combinations of fundamental
vibrations in the mid-infrared (mid-IR) region that are detected. Molecular functional groups can absorb in
themid-IR, with a range of progressively weaker orders of overtones detected in both the mid-IR and NIR
regions. General ly, the NIR region is characterized by broad, superimposed, and weak vibrational modes,
giving soilNIRspectra few, broad absorption features (Fig. 1). In the visible region, electronic excitations
are the main processes as the energy of the radiation is high.
Due to the broad and overlapping bands, vis–NIR spectra contain fewer absorptions than the mid-IR and
can be more difficult to interpret (Fig. 1). Nevertheless, this region contains useful information on organic
and inorganic materials in the soil. Absorptions in the visible region (400–780 nm) are primarily
associated with minerals that contain iron (e.g., haematite, goethite) (Mortimore et al., 2004; Sherman and
Waite, 1985). SOM can also have broad absorption bands in the visible region that are dominated by
chromophores and the darkness of organic matter. Absorptions in the NIR region (780–2500 nm) result
from the overtones of OH, SO4, and CO3 groups, as well as combinations of fundamental features of H2O
and CO2 (e.g., Clark, 1999). Clay minerals can show absorption in the vis–NIR region due to metal-OH
bend plus O–H stretch combinations (Viscarra Rossel et al., 2006a). Carbonates also have weak
absorption peaks in the near infrared (Hunt and Salisbury, 1970). Water has a strong influence on vis–NIR
spectra of soils. The dominant absorption bands of water around 1400–1900 nm are characteristic of soil
spectra (Fig. 1), but there are weaker bands in other parts of the vis–NIR range (Liu et al. 2002).
400 800 1200 1600 2000 2400
Log 1/R
Wavelength /nm
Combination
1
st
OT 2
nd
OT 3
rd
OT
vis
Figure 1. Soil vis–NIR 400–2500 nm spectra showing approximately where the combination, first, second,
and third overtone (OT) vibrations occur, as well as the visible (vis) range.
1.2. Spectroscopic multivariate calibrations
Diffuse reflectance spectra of soil in the vis–NIR are largely nonspecific due to the overlapping absorption
of soil constituents. This characteristic lack of specificity is compounded by scatter effects caused by soil
structure or specific constituents such as quartz. All of these factors result in complex absorption patterns
that need to be mathematically extracted from the spectra and correlated with soil properties. Hence, the
analyses of soil diffuse reflectance spectra require the use of multivariate calibrations (Martens and Naes,
1989). The most common calibration methods for soil applications are based on linear regressions, namely
stepwise multiple linear regression (SMLR) (Ben-Dor and Banin, 1995a; Dalal and Henry, 1986),
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