Elsevier

Advances in Agronomy

Volume 121, 2013, Pages 117-177
Advances in Agronomy

Chapter Three - Characterization of Organic Matter Composition of Soil and Flow Path Surfaces Based on Physicochemical Principles—A Review

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Abstract

Surfaces of macropores in structured soils can made of clay-organic coatings on soil aggregates or linings on worm burrow or root channel walls. The outermost layer of such surfaces is mostly covered by organic matter (OM), which finally controls sorption properties that are relevant for preferential flow and transport. However, the OM properties and local distributions along flow path surfaces are largely unknown, and methods for analyzing intact surfaces are limited. This chapter reviews the principles and applications of Fourier Transform infrared (FTIR) spectroscopy in comparison with complementary nuclear magnetic resonance technique; it describes FTIR techniques for analyzing the composition of bulk soil OM and of OM fractions and of the millimeter-scale spatial distribution at intact surfaces in structured soils for comparing OM composition with cation exchange capacity of OM and soil wettability. Maps of the millimeter-scale heterogeneous spatial distribution of OM composition at aggregate and burrow surfaces could be obtained with diffuse reflectance FTIR (DRIFT) mapping technique. The distribution of OM composition suggests that sorption properties of the OM and wettability of macropore surfaces are also spatially variable at this local scale. DRIFT mapping technique requires relatively smooth and fine-textured intact sample surfaces; further developments need to account for effects of microtopography on the scattering of infrared light. The results indicate yet unknown implications for preferential flow and transport in structured soil, especially for reactive solutes.

Introduction

The global carbon (C) content within organic matter (OM) of mineral soils is estimated to be about 1550 pg in the upper 100 cm layer (e.g., Bavaye et al., 2011, Powlson, 2005), which is about two times the atmospheric C content (e.g., Baveye, 2007). This amount does not consider organic C (Corg) stored in permafrost soils (i.e., 450 pg, Zimov et al., 2006) and peats (i.e., 165 pg, Holmen, 1992). Thus, soil organic matter (SOM) is an important C pool in the global C cycle. The main exchange fluxes for SOM, biomass production and SOM decomposition, are represented by the CO2 exchange between the soil and the atmosphere (e.g., Kuzyakov, 2011). The soil CO2 sequestration depends on soil functioning as a sink or as a source (e.g., Gregorich et al., 2005). The important contribution of microbial SOM decomposition is strongly depending on moisture and temperature (e.g., Conant et al., 2012, Dungait et al., 2012, von Luetzow and Koegel-Knabner, 2009).

However, fluxes of dissolved organic carbon (DOC) in soil solution toward ground and surface waters (e.g., Mei et al., 2012, Wagai and Sollins, 2002) and fluxes of CO2 in the gas phase (e.g., Gregorich et al., 2005, Xu et al., 2008) toward the atmosphere are normally relatively small in relation to the soil C pool (i.e., the SOM content). Smith et al. (2008) found that the rates of soil organic carbon (SOC) stock changes in response to global warming were highly uncertain because of relatively small net changes in soil C-pools as compared to mostly larger biomass and litter C stocks. For improved understanding, Kuzyakov (2011) suggests linking the investigations of pools and fluxes.

Irrespective of global C cycling problems, the SOM content has been used as an indicator for characterizing and understanding soil management- and land use-induced effects on cropping and soil quality (e.g., Hayes and Clapp, 2001, Stevenson, 1994). The term “soil quality” has been defined (e.g., Karlen et al., 1997) as “… the capacity of the soil to perform ecological functions… .” The role of SOM in maintaining soil quality has been emphasized by many authors (e.g., Powlson, 1996, Reeves, 1997, Smith et al., 2008, Sposito, 2008, Stevenson, 1994).

The quality of SOM itself depends on the chemical composition (e.g., Gärdenäs et al., 2011, Kogel-Knabner, 2000; Leifeld and Kogel-Knabner, 2005). Differently soluble SOM fractions (or otherwise physically and chemically separated OM fractions) have been used for characterizing management-induced changes in the SOM composition with direct effect on soil properties (e.g., Ding et al., 2006, He et al., 2009, Munoz Garcia and Faz Cano, 2012, Sequeira and Alley, 2011, Simon et al., 2009). Instead of using the methodologically defined SOM fractions, a model for continuous SOM quality distributions was proposed (Bruun et al., 2010) that characterized all the different SOM particles and fractions with respect to density, particle size, or other properties.

The properties of coarse-textured soils are assumed to be more affected by changes in SOM than those of loamy soils (Stevenson, 1985). While the soil texture practically remains the same, the SOM can be affected by land use and soil management with respect to both the content and the composition (Jenkinson, 1988). The SOM has been reported to affect several important soil functions (Van Lauwe and Giller, 2006) such as aggregate stability and storage capacity for water and nutrients (Baldock and Nelson, 2000), the cation exchange capacity (CEC) (e.g., Celi et al., 1997), and the wettability (Capriel, 1997, Chenu et al., 2000). However, relations between SOC content and soil properties could only in certain cases be explained simply by the SOC content (e.g., Horne and McIntosh, 2000). Negre et al. (2002) suggested considering the macromolecular behavior of SOM that depends on chemical composition and three-dimensional spatial structure of the SOM to explain soil wettability, although the detailed relations are largely unknown (e.g., Bachmann and McHale, 2009, Ellerbrock et al., 2005). The chemical composition of the SOM was found to also control its CEC (e.g., Almendros, 1995, Gressel et al., 1995). In analogy to defined OM (Günzler and Böck, 1990), the negatively charged carboxyl groups in SOM are mainly determining the CEC. Here, the term “SOM composition” describes the type and quantity of functional groups (e.g., carboxyl, alkyl, or hydroxyl groups) and their conformation describing the spatial arrangement at the molecular scale (Morrison and Boyd, 1983). The SOM composition therefore characterizes the functional properties of OM in soil (Stevenson, 1985). Soil type, climatic conditions, land use, crop rotation, and soil management modify the SOM composition indirectly through effects on the water and element balances of the ecosystem (e.g., Antil et al., 2005, Kaiser and Ellerbrock, 2005; Kaiser et al., 2007, von Lützow et al., 2006); the input from crop and root residues (Francioso et al., 2000) and the processes of SOM decomposition (Mathers and Xu, 2003). Such effects on SOM composition can preferably be studied using soils of long-term field experiments (LTFE) (e.g., Quideau et al., 2001) since changes in land use and management will take many years of constant management before a new equilibrium is reached (e.g., Schmidt et al., 2000, West and Post, 2002).

For analyzing OM functional groups, several spectroscopic techniques have been applied, such as infrared (IR), Fourier Transform infrared (FTIR) (e.g., Capriel et al., 1995, Demyan et al., 2012, Gerzabek et al., 1997) or nuclear magnetic resonance (NMR) spectroscopy (e.g., Hayes and Clapp, 2001, Kogel-Knabner, 1997). In the field of organic chemistry, such spectroscopic techniques were used to determine the specific molecular structure of pure, exactly defined organic substances (e.g., Hesse et al., 2005). These techniques are based on the interactions between electromagnetic radiation and the molecular subcomponents (e.g., electrons, magnetic spin of certain isotopes, or molecular bonds) within the functional groups. During the wave–particle interaction, the light transfers a part of its energy on the molecular subcomponents (e.g., Hesse et al., 2005). Such energy transfer will only take place if (Staab, 1964) the energy of the light is proportional to the differences in the energy of the molecular component in the exited minus the basic energy levels (i.e., quantization of energy levels). The energy level of such subcomponents depends on the type of functional groups within the molecule and the possible inter- (i.e., between different molecules) and intra (i.e., within the same molecule) molecular interactions such as hydrogen bonding or complex formation with polyvalent cations (PC) such as Ca2 +, Alx+, Mnx+, or Fex+.

The intensity of the light of a defined wavelength remains unchanged if certain functional groups are absent. In addition, the interaction between a Cdouble bondO group and a cation can cause, for example, shifts in the absorption bands of the Cdouble bondO group in both FTIR and NMR spectra. The information from NMR and FTIR is basically the same, however, due to the different wavelengths; NMR analysis of molecular components is based on the reversal of the orientation of the magnetic spin of certain isotopes, while FTIR is based on the excitation of vibration and rotation of molecular bonds. This overview demonstrates that the spectral techniques have specific challenges and limitation that help to identify and to distinguish SOM functional groups. MacCarthy and Rice (1985) as well as Simpson et al. (1997), among others, used spectral techniques to determine molecular structures for humic acid fractions. In contrast to a defined organic substance, the heterogeneous mixture of operationally defined fractions in SOM is characterized by differing transformation status, degradability, and turnover time (von Lützow et al., 2006) ranging from labile (e.g., microbial biomass) to relatively inert components (Baldock and Nelson, 2000, Stevenson, 1994).

Considering its complex nature, Stevenson (1982) suggested a simplified schematic molecular structure model for SOM that was consisting of different functional groups such as alkyl, carboxyl, and hydroxyl groups (Fig. 3.1). The spectra obtained from analyzing such complex organic substances thus integrate over the spectral properties of all components present in the sample reflecting the OM functional group composition of the mixture.

Note that spectroscopic techniques always provide molecular-level information on the composition of the samples. For analyzing, for instance, the behavior of solutes in a soil profile, upscaling and transformation of molecular information to profile or landscapes scales will become necessary. The use of spectral information involves transformation in effective transport properties (i.e., sorption coefficients) and the consideration of spatial characteristics at the profile scale (e.g., Carter, 2000, Müller et al., 2007); the soil spatial variability in SOM composition is additionally important at the field (e.g., Farenhorst, 2006, Sommer, 2006) and larger scales (e.g., Prechtel et al., 2009, Viaud et al., 2010). For such transformation, it becomes necessary to consider sample preparation and sampling technique, the spatial distribution of SOM composition in soil profile as well as at structural surfaces together with above-mentioned challenges and limitations of the spectroscopic techniques.

In soils, the CEC and chemical sorption reactivity for dissolved substances generally increase with SOM content (Sposito, 2008, Stevenson, 1994), while the wettability of soil decreases with SOM content in many cases (e.g., Chenu et al., 2000, Jaramillo et al., 2000, Mataix-Solera and Doerr, 2004) with some exceptions explained by differences in the composition of SOM (e.g., Horne and McIntosh, 2000). Such results are for (i) homogeneous soils, (ii) assuming water percolation in a uniform wetting or moisture front with (iii) all available pores and particle surfaces uniformly wetted, and (iv) in contact with the soil solution.

In structured soils, preferential flow may occur along earthworm burrows, root channels, or the interaggregate pore space (e.g., Beven and Germann, 1982, Flury et al., 1994, Ghodrati and Jury, 1992, Nieber, 2000). When moving through such pathways, the percolating water is bypassing much of the volume of the porous soil matrix (for details, see reviews of, e.g., Jarvis, 2007, Köhne et al., 2009a). The rapid movement through small fractions of the soil volume strongly limits the soil’s filter and buffer function (e.g., Köhne et al., 2009b). Moreover, any contact and exchange between the preferentially moving water and the surrounding soil matrix is largely restricted to the surface areas of such flow paths. Despite the increasing progress in describing preferential flow processes (e.g., Gärdenäs et al., 2006, Ray et al., 2004, Simunek and van Genuchten, 2008, Simunek et al., 2003), predictions of such processes are limited (Clothier et al., 2008) because it is difficult to determine the soil structural parameters in situ (Köhne et al., 2009b). Additionally, the functional properties (e.g., wettability) of surfaces at preferential flow path are hard to analyze; up to now they were quantified for mixed soil samples or for an aggregate packing (Goebel et al., 2008, Ramírez-Flores et al., 2008).

As for mineral particles, the surfaces of porous soil aggregates are mostly covered by OM. Thus, the OM composition at these surfaces may finally control wettability and sorption and transfer properties of flow pathways. The assumption that the spatial variability of water transfer is caused by local differences in wettability of flow path surfaces (Hallett et al., 2004) could be shown by staining experiments (Kodesova et al., 2012, Lipsius and Mooney, 2006). The small-scale local heterogeneity in SOM distribution seems to be of special importance for pesticide transport and chemical sorption processes in structured soils (e.g., Jury and Flühler, 1992, Kaiser and Zech, 1998, White, 1985). While surfaces of aggregates and pores are intensively studied for the mineralogical properties (e.g., Celis et al., 1997, Jongmans et al., 1998, Kaiser and Wilcke, 1996), there are only a few studies on the effect of SOM composition on preferential flow. When analyzing SOM, we need to consider that the spatial distribution of OM in soil is locally highly variable with consequences for turnover rate processes and transport properties (Fig. 3.2A; Leue et al., 2010).

Such small-scale heterogeneity could not be considered when analyzing mixed soil samples (Fig. 3.2B) because the spatial distribution of SOM at preferential flow paths will be lost when mixing the sample. In addition, the spatial geometry of the patchy-like distribution of SOM at structural surfaces is lost. The transport in pathways is local; therefore, the local distribution of both the solution and the solid phase has to be considered for predictions. Thus, for analyzing the small-scale distribution of SOM at structural surfaces (Fig. 3.2C), it is necessary to investigate intact samples.

Swift (1999) reviewed, for instance, different wet chemical and spectroscopic procedures (FTIR and NMR) for analyzing SOM in bulk soil samples and SOM fractions. However, such investigations were mostly done by different working groups by using either NMR or FTIR except for Inbar et al. (1989) which compared the physical principles of NMR and FTIR for analyzing the same OM fractions from compost samples. The application of the spectroscopic techniques for intact surfaces was yet presented neither in that detail nor in relation to soil physical and chemical properties.

The objective of this review is to discuss the basics of complementary spectroscopic techniques like NMR and FTIR to describe challenges and limitations of spectroscopic techniques and to distinguish between problems caused by soil sample properties, sampling procedure, and basic principles of spectral technique; to describe the application of FTIR techniques for analyzing composition of (i) defined pure organic compounds, (ii) SOM of mixed soil samples, and (iii) for exploring the small-scale spatial variability of SOM composition at intact structural surfaces (preferential flow path).

The information obtained by FTIR spectroscopy may be related to other soil properties and local two-dimensional (2D) distributions of SOM composition compared with water infiltration to indicate possible use of spectral information for describing SOM properties that are relevant for transformation and transport processes in structured soil.

Section snippets

SOM Quantification as SOC

The SOM content makes up about 1–6% of the bulk soil mass of many mineral arable and grassland soils (Stevenson, 1994). Although the fraction is relatively small, SOM is an important component controlling soil physical, chemical, and biological properties. Information on SOM content is usually included in standard soil characterizations together with texture data, among others. The SOM content of soil samples is determined as the content of organic C (Corg). However, Corg is just one component

SOM Separation Methods

SOM can be separated by physical and chemical procedures (Blazejewski et al., 2005, Hayes, 2006, Stewart et al., 2008) into fractions different in composition and stability (e.g., Olk and Gregorich, 2006). The SOM fractions can generally be separated into particulate and soluble OM fractions. The term particulate organic matter (POM) has mostly been used to describe a density fraction obtained from particle-size fractions; the term light fraction (LF) defines a density fraction obtained by

Methods for Determination of OM Composition

In chemistry, spectral techniques like NMR or FTIR spectroscopy are complementary methods to analyze the composition of pure and defined organic components (e.g., Hesse et al., 2005). In general, those techniques act like a question–answer procedure. The question was asked by electromagnetic radiation (light) different in its energy (caused by difference in wavelength). And the answer will be given by the sample: It either interacts with light of certain energy or not, resulting in absorption

Applying FTIR Spectroscopy in Organic Chemistry and in Soil Science

The above-mentioned spectroscopic techniques are generally used in chemistry as complementary methods to analyze the composition of defined OM in terms of the molecular structure. The requirement for analyzing mixtures (e.g., water and oil) for the application of the spectroscopic techniques in chemistry is that spectral signals are known and easily be distinguished, also the mixtures need to consist of maximal two or three well-known components, or the components of the mixture belong to the

Relations Between SOM Composition and Soil Properties

It is well known that content and composition of clay minerals and SOM determine the physicochemical nature of soil (Stevenson, 1994) including wettability (e.g., Dekker and Ritsema, 1994) and CEC (Sposito, 2008). Thus, differences in SOM composition affect soil properties in a similar way as differences in clay mineral composition (e.g., Gerzabek et al., 2001). SOM content and composition are especially important for sandy soils with low clay mineral content, where SOM acts as the major

Modifications by soil sampling of structured soils

The characterization of SOM and OM fractions using FTIR spectra has in the majority of the before-mentioned studies been carried out with homogenized or otherwise intensively mixed samples collected mostly from the topsoil horizon. Mixing of collected soil samples can be useful where local-scale heterogeneity effects are of minor interest. The results obtained from spectroscopic analysis of mixed samples can be used, for example, for comparing long-term mean OM compositions that develop in an

Summary and Conclusions

This overview revealed the importance of characterizing both the content and composition of SOM. The SOM composition could be analyzed by using spectroscopic techniques like NMR and FTIR. Both techniques are in principle complementary and based on the same physicochemical principle, which is the interaction between electromagnetic radiation and submolecular components. The difference in the interactions is caused by the wavelengths of electromagnetic radiation that are used: FTIR spectroscopy

Acknowledgments

We are grateful to the Deutsche Forschungsgemeinschaft, Bonn (DFG), that provided funding for research projects (grants EL 191/5-1, and EL 191/7-1). We thank the former PhD students Dr. Michael Kaiser and Dr. Martin Leue for valuable discussion, Prof. Dr. Radka Kodesova (University of Prague) for support with sampling and thin sections, and our cooperation partners within the DFG priority program SPP 1090: “Soils as sources and sinks for CO2—mechanisms of organic matter stabilization,” in

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