Near‐infrared spectroscopy can predict the composition of organic matter in soil and litter

The usefulness and limitations of near‐infrared reflectance spectroscopy (NIRS) for the assessment of several soil characteristics are still not sufficiently explored. The objective of this study was to evaluate the ability of visible and near‐infrared reflectance (VIS‐NIR) spectroscopy to predict the composition of organic matter in soils and litter. Reflectance spectra of the VIS‐NIR region (400–2500 nm) were recorded for 56 soil and litter samples from agricultural and forest sites. Spectra were used to predict general and biological characteristics of the samples as well as the C composition which was measured by ¹³C‐CPMAS‐NMR spectroscopy. A modified partial least‐square method and cross‐validation were used to develop equations for the different constituents over the whole spectrum (1st to 3rd derivation). Near‐infrared spectroscopy predicted well the C : N ratios, the percentages of O‐alkyl C and alkyl C, the ratio of alkyl C to O‐alkyl C, and the sum of phenolic oxidation products: the ratios of standard deviation of the laboratory results to standard error of cross‐validation (RSC) were greater than 2, the regression coefficients (a) of a linear regression (measured against predicted values) ranged from 0.9 to 1.1, and the correlation coefficients (r) were greater than 0.9. Satisfactorily (0.8 ≤ a ≤ 1.2, r ≥ 0.8, and 1.4 ≤ RSC ≤ 2.0) assessed were the contents of C, N, and production of DOC, the percentages of carbonyl C and aromatic C and the ratio of alkyl C to aromatic C. However, the N‐mineralization rate and the microbial biomass were predicted unsatisfactorily (RSC < 1.4). The good and satisfactory predictions reported above indicate a marked usefulness of NIRS in the assessment of biological and chemical characteristics of soils and litter.     

Use of near‐ and mid‐infrared spectroscopy to distinguish carbon and nitrogen originating from char and forest‐floor material in soils

The presence of relatively inert organic materials such as char has to be considered in calibrations of soil C models or when calculating C‐turnover times in soils. Rapid and cheap spectroscopic techniques such as near‐infrared (NIRS) or mid‐infrared spectroscopy (MIRS) may be useful for the determination of the contents of char‐derived C in soils. To test the suitability of both spectroscopic techniques for this purpose, artificial mixtures of C‐free soil, char (lignite, anthracite, charcoal, or a mixture of the three coals) and forest‐floor Oa material were produced. The total C content of these mixtures (432 samples) ranged from 0.5% to 6% with a proportion of char‐derived C amounting to 0%, 20%, 40%, 50%, 60%, or 80%. All samples were scanned in the visible and near‐IR region (400–2500 nm). Cross‐validation equations for total C and N, C and N derived from char (C_char, N_char) and Oa material were developed using the whole spectrum (first and second derivative) and a modified partial least‐square regression method. Thirty‐six samples were additionally scanned in the middle‐IR and parts of the near‐IR region (7000–400 cm^–1 which is 1430–25,000 nm) in the diffuse‐reflectance mode. All properties investigated were successfully predicted by NIRS as reflected by RSC values (ratio of standard deviation of the laboratory results to standard error of cross‐validation) > 4.3 and modeling efficiencies (EF) ≥ 0.98. Near‐infrared spectroscopy was also able to differentiate between the different coals. This was probably due to structural differences as suggested by wavelength assignment. Mid‐IR spectroscopy in the diffuse‐reflectance mode was also capable to successfully predict the parameters investigated. The EF values were > 0.9 for all constituents. Our results indicated that both spectroscopic techniques applied, NIRS and MIRS, are able to predict C and N derived from different sources in soil, if closed populations are considered.     

Rapid determination of lime requirement by mid‐infrared spectroscopy: A promising approach for precision agriculture

Mid‐infrared spectroscopy (MIRS) has proven to be a cost‐effective, high throughput measurement technique for soil analysis. After multivariate calibration mid‐infrared spectra can be used to predict various soil properties, some of which are related to lime requirement (LR). The objective of this study was to test the performance of MIRS for recommending variable rate liming on typical Central European soils in view of precision agriculture applications. In Germany, LR of arable topsoils is commonly derived from the parameters organic matter content (SOM), clay content, and soil pH (CaCl₂) as recommended by the Association of German Agricultural Analytical and Research Institutes (VDLUFA). We analysed a total of 458 samples from six locations across Germany, which all revealed large within‐field soil heterogeneity. Calcareous topsoils were observed at some positions of three locations (79 samples). To exclude such samples from LR determination, peak height at 2513 cm^?1 of the MIR spectrum was used for identification. Spectra‐based identification was accurate for carbonate contents > 0.5%. Subsequent LR derivation (LR_SPP) from MIRS‐PLSR predictions of SOM, clay, and pH (CaCl₂) for non‐calcareous soil samples using the VDLUFA look‐up tables was successful for all locations (R² = 0.54–0.82; RMSE = 857–1414 kg CaO ha^?1). Alternatively, we tested direct LR prediction (LR_DP) by MIRS‐PLSR and also achieved satisfactory performance (R² = 0.52–0.77; RMSE = 811–1420 kg CaO ha^?1; RPD = 1.44–2.08). Further improvement was achieved by refining the VDLUFA tables towards a stepless algorithm. It can be concluded that MIRS provides a promising approach for precise LR estimation on heterogeneous arable fields. Large sample numbers can be processed with low effort which is an essential prerequisite for variable rate liming in precision agriculture.     

Prediction of model pools for a long‐term experiment using near‐infrared spectroscopy

Fourty‐one soil samples from the “Eternal Rye” long‐term experiment in Halle, Germany, were used to test the usefulness of near‐infrared spectroscopy (NIRS) to differentiate between C derived from C₃ and C₄ plants by using the isotopic signature (δ¹³C) and to predict the pools considered in the Rothamsted Carbon (RothC) model, i.e., decomposable plant material, resistant plant material, microbial biomass, humified organic matter, and inert organic matter. All samples were scanned in the visible‐light and near‐infrared region (400–2500 nm). Cross‐validation equations were developed using the whole spectrum (first to third derivative) and a modified partial least‐square regression method. δ¹³C values and all pools of the RothC model were successfully predicted by NIRS as reflected by RSC values (ratio between standard deviation of the laboratory results and standard error of cross‐validation) ranging from 3.2 to 3.4. Correlations analysis indicated that organic C can be excluded as basis for the successful predictions by NIRS in most cases, i.e., 11 out of 16.     

Rainforest litter quality and chemical controls on leaf decomposition with near‐infrared spectrometry

Plant‐litter chemical quality is an important driver of many ecosystem processes, however, what actually constitutes high‐ or low‐quality litter (chemical potential for fast and slow decomposition, respectively) is often interpreted by the indices available. Here, near‐infrared spectroscopy (NIRS) was used to explore leaf‐litter chemical quality and the controls on decomposition in the tropical rainforest region of north Queensland Australia. Leaf‐litter samples from litterfall collections and litterbag studies were used. NIRS was used to calibrate the chemical compositions of the material (N, P, C, Mg, Ca, acid detergent fiber, acid detergent lignin, α‐cellulose, and total phenolics) from a smaller sample set covering the spectral range in the full set of samples. Calibrations were compared for both separate (local) and combined models, for litterbags, and litterfall. Coefficients of determination (r²) in the local models ranged from 0.88 (litterbag Mg) to 0.99 (litterfall N), with residual prediction deviation ratios > 3 for all constituents except Mg (≈ 2.5). Mass loss in the litterbags was strongly related to the NIR spectra, with model r²'s of 0.75 (in situ leaves) and 0.76 (common control leaf). In situ decomposability was determined from modeling the initial NIR spectra prior to decomposition with litterbag exponential‐decay rates (model r² of 0.81, n = 85 initial samples). A best subset model including litter‐quality, climate, and soil variables predicted decay better than the NIR decomposability model (r² = 0.87). For litter quality alone the NIR model predicted decay rate better than all of the best predictive litter–chemical quality indices. The decomposability model was used to predict in situ decomposability in the litterfall samples. The chemical variables explaining NIR decomposability for litterfall were initial P, C, and phenolics (linear model r² = 0.80, n = 2471). NIRS is a holistic technique that is just as, if not more accurate, than litter–chemical quality indices, when predicting decomposition and decomposability, shown here in a regional field study.     

Use of Near Infrared Reflectance Spectroscopy (NIRS) for Predicting Soil Fertility and Historical Management

This study tests the potential of near infrared reflectance spectroscopy (NIRS) for predicting soil fertility and management history from topsoil (0–10 cm deep) spectra. Soil fertility was assessed by measuring the growth of a test plant, and soil management history was determined through inquiries with farmers. Moreover, NIRS predictive value was compared with that of a group of topsoil parameters: total carbon and nitrogen, nitrate, potential respiration and denitrification, and microbial biomass. Modelling used partial and modified partial least square regressions to ensure comparisons between predictions by NIRS versus by soil parameters. Soil fertility and management history were well predicted by NIRS (Q² = 0.78 and R² = 0.89 both; Q² and R² are cross-validation and calibration coefficients of determination, respectively), as were the soil parameters (Q² = 0.79–0.92 and R² = 0.86–0.98). Soil fertility and management history were more accurately predicted by NIRS than by the set of soil parameters.     

The Effect of Severe Drought on the Evolution of Urban and Manure Wastes in an Agricultural Soil in Mediterranean Ecosystems

In semi‐arid Mediterranean soils, water availability is the most limiting factor, negatively affecting the organic matter (OM) degradation. The aim of this work is to study under controlled laboratory conditions how three sources of OM [municipal solid waste (MSW), sheep manure (SM) and cow manure (CM)] behave when they are applied to an agricultural soil subjected to a severe year‐long drought. In order to apply the same concentration of OM to the soil (16·92 Mg OM ha⁻¹), 2 kg of soil was mixed with 30, 67·41 and 55·25 Mg ha⁻¹ (dry matter) of MSW, CM and SM, respectively. Two levels of irrigation were employed: (i) watered soils and (ii) non‐watered soils. Soil's chemical properties [water soluble carbon (WSC), humic acids, fulvic acids and protein mass distribution], biological properties (soil microbial biomass carbon and o‐diphenoloxidase activity) and solid‐state ¹³C cross‐polarisation magic angle spinning nuclear magnetic resonance spectroscopy were determined. In watered soils, the soil microbial biomass carbon was higher in the SM than in CM and MSW treatments (9·9% and 23·1%, respectively). The WSC was significantly higher in SM than in CM (55·7%) and MSW (78·7%) treatments. A decrease in the content of O‐alkyl C and an increase in alkyl C, aromatic C and carboxyl C were observed. In non‐watered soils, the biochemical properties and alkyl C and alkyl/O‐alkyl ratio decreased, whereas WSC content and O‐alkyl C increased. These results indicated that the evolution of OM and the activity of the microbial community in non‐watered soils were very different to those in the watered soils. Copyright © 2016 John Wiley & Sons, Ltd.     

Dynamics of 13C‐labeled mustard litter (Sinapis alba) in particle‐size and aggregate fractions in an agricultural cropland with high‐ and low‐yield areas

The application of ¹³C‐labeled litter enables to study decomposition processes as well as the allocation of litter‐derived carbon to different soil C pools. ¹³Carbon‐labeled mustard litter was used in order to compare decomposition processes in an agricultural cropland with high‐yield (HY) and low‐yield (LY) areas, the latter being characterized by a finer texture and a lower organic‐C (OC) content. After tracer application, ¹³C concentrations were monitored in topsoil samples in particulate organic matter (POM) and in fine mineral fractions (silt‐ and clay‐sized fractions). After 568 d, approximately 5% and 10% of the initial ¹³C amount were found in POM fractions of LY and HY areas, respectively. Higher amounts were found in POM occluded in aggregates than in free POM. Medium‐term (0.5–2 y) storage of the initial ¹³C in fine silt‐ and clay‐sized fractions amounts to 10% in HY and LY soils, with faster enrichment but also faster disappearance of the ¹³C signal from LY soils. Amounts of 80%–90% of the added ¹³C were mineralized or leached in the observed period. Decomposition of free POM was faster in HY than in LY areas during the first year, but the remaining ¹³C amounts in occluded‐POM fractions were higher in HY soils after 568 d. High‐yield and low‐yield areas showed different ¹³C dynamics in fine mineral fractions. In LY soils, ¹³C amounts and concentrations in mineral‐associated fractions increased within 160 d after application and decreased in the following time period. In HY areas, a significant increase in ¹³C amounts did not occur until after 568 d. The results indicate initially faster decomposition processes in HY than in LY areas due to different soil conditions, such as soil texture and water regime. The higher silt and clay contents of LY areas seem to promote a faster aggregate formation and turnover, leading to a closer contact between POM and mineral surfaces in this area. This favors the OC storage in fine mineral fractions in the medium term. Lower aggregate formation and turnover in the coarser textured HY soil leads to a delayed C stabilization in silt‐ and clay‐sized fractions.     

Can Near or Mid‐Infrared Diffuse Reflectance Spectroscopy Be Used to Determine Soil Carbon Pools?

Abstract

The objective of this study was to compare mid‐infrared (MIR) an near‐infrared (NIR) spectroscopy (MIRS and NIRS, respectively) not only to measure soil carbon content, but also to measure key soil organic C (SOC) fractions and the δ¹³C in a highly diverse set of soils while also assessing the feasibility of establishing regional diffuse reflectance calibrations for these fractions. Two hundred and thirty‐seven soil samples were collected from 14 sites in 10 western states (CO, IA, MN, MO, MT, ND, NE, NM, OK, TX). Two subsets of these were examined for a variety of C measures by conventional assays and NIRS and MIRS. Biomass C and N, soil inorganic C (SIC), SOC, total C, identifiable plant material (IPM) (20× magnifying glass), the ratio of SOC to the silt+clay content, and total N were available for 185 samples. Mineral‐associated C fraction, δ¹³C of the mineral associated C, δ¹³C of SOC, percentage C in the mineral‐associated C fraction, particulate organic matter, and percentage C in the particulate organic matter were available for 114 samples. NIR spectra (64 co‐added scans) from 400 to 2498 nm (10‐nm resolution with data collected every 2 nm) were obtained using a rotating sample cup and an NIRSystems model 6500 scanning monochromator. MIR diffuse reflectance spectra from 4000 to 400 cm^?1 (2500 to 25,000 nm) were obtained on non‐KBr diluted samples using a custom‐made sample transport and a Digilab FTS‐60 Fourier transform spectrometer (4‐cm^?1 resolution with 64 co‐added scans). Partial least squares regression was used with a one‐out cross validation to develop calibrations for the various analytes using NIR and MIR spectra. Results demonstrated that accurate calibrations for a wide variety of soil C measures, including measures of δ¹³C, are feasible using MIR spectra. Similar efforts using NIR spectra indicated that although NIR spectrometers may be capable of scanning larger amounts of samples, the results are generally not as good as achieved using MIR spectra.     

Structural changes in humic substances after long-term fertilization of a calcareous soil with pig slurries

Pig slurries are widely used on calcareous soils in European rainfed systems. Here we assess their impact on the amount of soil organic carbon (SOC) and on the composition of humic-type substances (HTS). Seven doses of slurry (five from fattening pigs and two from sows) ranging from 1.0 to 4.8 Mg ha⁻¹ yr⁻¹ of organic matter were evaluated after a period of 12 years and compared with mineral fertilizer treatment. At the end of the last annual cropping season (September), SOC was quantified, and HTS were isolated by alkaline extraction followed by acid precipitation, and studied by visible spectroscopy (800–400 nm) and Fourier-transformed infrared spectroscopy (4000–400 cm⁻¹). Following the trend in the slurry organic matter applied rates, SOC increased from 9.5 g C kg⁻¹ (mineral treatment) to 13.8 g C kg⁻¹. This SOC increase was equivalent to c. 25.4% of the slurry organic carbon applied. The incorporation of aliphatic structures, mainly polyalkyl, from slurries into the HTS tends to modify the composition of the soil organic matter (SOM), which is reflected in a decrease in the intensity of FT-IR peaks related to aromatic structures. Despite the trend of significant increase in SOC with fattening slurries, mainly from the organic matter rate of 1.6 Mg ha⁻¹ yr⁻¹ (c. 185 kg N ha⁻¹), the composition of the HTS showed an important aliphatic enhancement. The FTIR results showed that using exclusively the relative intensities of specific peaks (alkyl, carboxyl, aromatic and amide groups) as variables for the discriminant analysis, it is possible to identify HA between different groups of soils treated with progressive levels of slurry. Although the new aliphatic components could be considered important to improve soil physical quality, after the incorporation of additional SOM, the spectroscopic characteristics of HTS in soils treated with slurries suggested a weak effect in long-term C sequestration, as the newly incorporated OC forms are not qualitatively similar to the presumably stable native SOM. These potential changes in SOC and SOM composition at field level are constrained by the maximum allowed N rates from organic origin in some agricultural systems.     

Use of near‐infrared spectroscopy to distinguish carbon and nitrogen originating from char and forest‐floor material in soils: usefulness of a genetic algorithm

Several algorithms exist for the calibration procedures of near‐infrared spectra in soil‐scientific studies, but the potential of a genetic algorithm (GA) for spectral feature selection and interpretation has not yet been sufficiently explored. Objectives were (1) to test the usefulness of near‐infrared spectroscopy (NIRS) for a prediction of C and N from char and forest‐floor Oa material in soils using either a partial least squares (PLS) method or a GA‐PLS approach and (2) to discuss the mechanisms of GA feature selection for the examined constituents. Calibration and validation were carried out for measured reflectance spectra in the visible and near‐IR region (400–2500 nm) on an existing set of 432 artificial mixtures of C‐free soil, char (lignite, anthracite, charcoal, or a mixture of the three coals), and forest‐floor Oa material. For all constituents (total C and N, C and N from all coals and from the Oa material, C derived from mixed coal, charcoal, lignite, and anthracite), the GA‐PLS approach was superior over the full‐spectrum PLS method. The RPD values (ratio of standard deviation of the laboratory results to standard error of prediction) ranged from 2.4 to 5.1 in the validation and indicated a better category of prediction for three constituents: “approximate quantitative” instead of a “distinction between high and low” for C derived from mixed coal and “good” instead of “approximate quantitative” for C and N derived from all coals. Overall, this study indicates that the approach using GA may have a greater potential than the PLS method in NIRS.     

Cold and hot water–extractable organic matter as indicators of litter decomposition in forest soils

Mild extractions were used as indicators of easily decomposable organic matter (OM). However, the chemical composition of extracted OM often remained unclear. Therefore, the composition of cold and hot water–extractable OM was investigated in the O horizons (Oi, Oe, Oa) of a 170 y old beech stand (Fagus sylvatica) in the Ore Mtns., SE Germany. To simulate litter decomposition, the O horizon samples were incubated for 1 week under defined conditions. Cold‐ and hot‐water extracts were analyzed and chemically characterized by pyrolysis–field ionization mass spectrometry (Py‐FIMS). The C and N concentrations were always lower in the cold‐(C: 2.69 to 3.95 g kg^–1; N: 0.14 to 0.29 g kg^–1) than in the hot‐water extracts (C: 13.77 to 15.51 g kg^–1; N: 0.34 to 0.83 g kg^–1). The C : N ratios of both extracts increased with increasing depth. Incubation increased the concentrations of C and N in all water extracts, while C : N ratios of extracts decreased. The molecular‐chemical composition of cold and hot water–extracted OM revealed distinct differences. Generally, cold water–extracted OM was thermally more stable than hot water–extracted OM. The mass spectra of the hot water–extracted organic matter revealed more intensive signals of carbohydrates, phenols, and lignin monomers. Additionally, the n‐C₂₈ fatty acid and the n‐C₃₈–to–n‐C₅₂ alkyl monoesters clearly distinguished the hot‐ from the cold‐water extract. A principle‐component analysis visualized (1) alterations in the molecular‐chemical composition of cold‐ and hot‐water extracts due to previous incubation of the solid O horizon samples and (2) a decomposition from the Oi to the Oh horizon. This provides evidence that the macromorphological litter decomposition was reflected by the chemical composition of water extracts, and that Py‐FIMS is well‐suited to explain at the molecular level why OM decomposability is correlated with water‐extracted C.     

Analyzing organic matter composition at intact biopore and crack surfaces by combining DRIFT spectroscopy and Pyrolysis‐Field Ionization Mass Spectrometry#

In the clay‐illuvial horizons (Bt) of Luvisols, surfaces of biopores and aggregates can be enriched in clay and organic matter (OM), relative to the bulk of the soil matrix. The OM composition of these coatings determines their bio‐physico‐chemical properties and is relevant for transport and transformation processes but is largely unknown at the molecular scale. The objective of this study was to improve the interpretation of spectra from Fourier transform infrared spectroscopy in diffuse reflectance mode (DRIFT) by using thermograms and released ion intensities obtained with pyrolysis‐field ionization mass spectrometry (Py‐FIMS) for a more detailed analysis of the mm‐scale spatial distribution of OM components at intact structural surfaces. Samples were separated from earthworm burrow walls, crack coatings, uncoated cracks, root channels, and pinhole fillings of the Bt‐horizons of Luvisols. The information from Py‐FI mass spectra enabled the assignment of OM functional groups also from spectral regions of overlapping DRIFT signal intensities to specific OM compound classes. In particular, bands from C=O and C=C bonds in the infrared range of wave numbers between 1,641 and 1,605 cm^?1 were related to heterocyclic N‐compounds, benzonitrile, and naphthalene. The OM at earthworm burrow walls was composed of chemically labile aliphatic C‐rich and rather stable lignin and alkylaromatic compounds whereas the OM of thick crack coatings and pinholes was dominated by heterocyclic N and nitriles and high‐molecular compounds, likely originating from combustion residues. In combination with Py‐FIMS, DRIFT applications to intact samples seem promising for generating a more detailed mm‐scale spatial distribution of OM‐related sorption and wettability properties of crack and biopore surfaces that may serve as preferential flow paths in structured soils.     

Sorption of HOC in soils with carbonaceous contamination: Influence of organic‐matter composition

Detailed information about structure and composition of organic sorbents is required to understand their impact on sorption capacity and sorption kinetic of organic pollutants. Therefore, the chemical composition of organic material from 18 geosorbents was investigated by solid‐state ¹³C nuclear‐magnetic‐resonance (NMR) spectroscopy. Structural parameters such as aromaticity, polarity, and alkyl‐C content were related to the Freundlich sorption exponent (1/n) and the sorption coefficient . The geosorbents included three natural and four combusted coals (carbonaceous material), three Histosols, five mineral soils from Germany containing inputs of technogenic carbonaceous material, derived from industrial activities, and four non‐contaminated mineral soils from Germany. Equilibrium sorption was measured for five hydrophobic organic compounds and analyzed with the solubility‐normalized Freundlich sorption isotherm. With increasing maturation degree, the proportion of polar constituents decreases from the natural soils to the coals. In contrast to the non‐polluted mineral soils, the soils with technogenic input are characterized by high aromaticity and low polarity. A positive correlation between sorption coefficient and aromaticity was found. The Freundlich exponent (1/n) is negatively correlated with the aromaticity, denoting an increase of adsorption processes with increasing aromaticity. Likewise, the contribution of partitioning decreases. This sorption mechanism predominates only if the organic matter in the samples contains a high proportion of polar compounds.     

Long‐term effects of fertilization on some soil properties under rainfed soybean‐wheat cropping in the Indian Himalayas

This study aims to examine the effects of long‐term fertilization and cropping on some chemical and microbiological properties of the soil in a 32 y old long‐term fertility experiment at Almora (Himalayan region, India) under rainfed soybean‐wheat rotation. Continuous annual application of recommended doses of chemical fertilizer and 10 Mg ha^–1 FYM on fresh‐weight basis (NPK + FYM) to soybean (Glycine max L.) sustained not only higher productivity of soybean and residual wheat (Triticum aestivum L.) crop, but also resulted in build‐up of total soil organic C (SOC), total soil N, P, and K. Concentration of SOC increased by 40% and 70% in the NPK + FYM–treated plots as compared to NPK (43.1 Mg C ha^–1) and unfertilized control plots (35.5 Mg C ha^–1), respectively. Average annual contribution of C input from soybean was 29% and that from wheat was 24% of the harvestable aboveground biomass yield. Annual gross C input and annual rate of total SOC enrichment from initial soil in the 0–15 cm layer were 4362 and 333 kg C ha^–1, respectively, for the plots under NPK + FYM. It was observed that the soils under the unfertilized control, NK and N + FYM treatments, suffered a net annual loss of 5.1, 5.2, and 15.8 kg P ha^–1, respectively, whereas the soils under NP, NPK, and NPK + FYM had net annual gains of 25.3, 18.8, and 16.4 kg P ha^–1, respectively. There was net negative K balance in all the treatments ranging from 6.9 kg ha^–1 y^–1 in NK to 82.4 kg ha^–1 y^–1 in N + FYM–treated plots. The application of NPK + FYM also recorded the highest levels of soil microbial‐biomass C, soil microbial‐biomass N, populations of viable and culturable soil microbes.     

Quantitative Analysis of Chlorophyll and Protein in Alfalfa Leaves Using Fiber‐Optic Near‐Infrared Spectroscopy

The performance of near‐infrared (NIR) spectroscopy as a rapid technique for the estimation of chlorophyll and protein contents in alfalfa (Medicago sativa L.) was investigated. A fiber‐optic probe was employed directly on a total of 198 fresh leaves to measure spectra between 1100 and 2200 nm. Partial least squares (PLS) regression models were developed with a calibration set of 120 samples spanning a concentration range of 5.20–158.5 for the chlorophyll content index (CCI), 0.39–4.60 mg g^?1 (fresh weight) for the chlorophyll extracted with dimethylsulfoxide (DMSO), and 9.92–45.32% (dry matter) for protein content. The models obtained were validated with 78 independent samples. Standard errors of prediction of 12.49 were obtained for the CCI, 0.24 mg g^?1 for DMSO‐extracted chlorophyll, and 3.27% for the protein content. These results support the use of NIRS equipped with a fiber‐optic probe to monitor and assess the composition and quality of forages in a nondestructive way.     

Use of near infrared spectroscopy to determine biological and chemical characteristics of organic layers under spruce and beech stands

The chemical composition of organic layers of forest soils shows a high spatial variability and fast methods may be required for its study at a landscape level. The objective was to assess the applicability of near infrared spectroscopy (NIRS) to measure several chemical and biological properties of organic layers in spruce, beech, and mixed spruce‐beech stands. Spectra in the VIS‐NIR region (400—2500 nm) were recorded for 406 samples representing Oi, Oe, and Oa layers of forest soils from Solling (Germany), 195 of them were used for calibration and 211 for validation. The calibration equations for each constituent were developed using the whole spectrum (0^th to 3^rd derivative). Humus samples were analyzed for contents of C and N and contents of P, S, Na, K, Ca, Mg, Mn, Fe, and Al after pressure digestion in HNO₃. Additionally, basal respiration and microbial C (C_mic) were measured. NIRS predicted well the contents of C, N, P, S, Ca, Na, K, Fe, and Al and C/N and C/P ratios: the regression coefficients (a) of a linear regression (measured against predicted values) ranged from 0.9 to 1.1, and the correlation coefficients (r) were greater or equal 0.9. C_mic (a = 0.87, r = 0.83) was predicted satisfactorily, whereas the prediction of the basal respiration (a = 0.74, r = 0.87) was less satisfactory. Due to liming of some of the plots NIRS failed to predict contents of Mg (a = 1.27, r = 0.68). For all chemical and biological characteristics the best prediction performances were achieved using the whole sample population. Splitting the samples into smaller groups according to a dominant tree species or an organic layer did not improve the predictions.<?show $6#>     

Acidity,nutrient stocks,and organic‐matter content in soils of a temperate deciduous forest with different abundance of European beech (Fagus sylvatica L.)

The production and composition of leaf litter, soil acidity, exchangeable nutrients, and the amount and distribution of soil organic matter were analyzed in a broad‐leaved mixed forest on loess over limestone in Central Germany. The study aimed at determining the current variability of surface‐soil acidification and nutrient status, and at identifying and evaluating the main factors that contributed to the variability of these soil properties along a gradient of decreasing predominance of European beech (Fagus sylvatica L.) and increasing tree‐species diversity. Analyses were carried out in (1) mature monospecific stands with a predominance of beech (DL 1), (2) mature stands dominated by three deciduous‐tree species (DL 2: beech, ash [Fraxinus excelsior L.], lime [Tilia cordata Mill. and/or T. platyphyllos Scop.]), and (3) mature stands dominated by five deciduous‐tree species (DL 3: beech, ash, lime, hornbeam [Carpinus betulus L.], maple [Acer pseudoplatanus L. and/or A. platanoides L.]). The production of leaf litter was similar in all stands (3.2 to 3.9 Mg dry matter ha^–1 y^–1) but the total quantity of Ca and Mg deposited on the soil surface by leaf litter increased with increasing tree‐species diversity and decreasing abundance of beech (47 to 88 kg Ca ha^–1 y^–1; 3.8 to 7.9 kg Mg ha^–1 y^–1). The soil pH_(H2O) and base saturation (BS) measured at three soil depths down to 30 cm (0–10 cm, 10–20 cm, 20–30 cm) were lower in stands dominated by beech (pH = 4.2 to 4.4, BS = 15% to 20%) than in mixed stands (pH = 5.1 to 6.5, BS = 80% to 100%). The quantities of exchangeable Al and Mn increased with decreasing pH and were highest beneath beech. Total stocks of exchangeable Ca (0–30 cm) were 12 to 15 times larger in mixed stands (6660 to 9650 kg ha^–1) than in beech stands (620 kg ha^–1). Similar results were found for stocks of exchangeable Mg that were 4 to 13 times larger in mixed stands (270 to 864 kg ha^–1) than in beech stands (66 kg ha^–1). Subsoil clay content and differences in litter composition were identified as important factors that contributed to the observed variability of soil acidification and stocks of exchangeable Ca and Mg. Organic‐C accumulation in the humus layer was highest in beech stands (0.81 kg m^–2) and lowest in stands with the highest level of tree‐species diversity and the lowest abundance of beech (0.27 kg m^–2). The results suggest that redistribution of nutrients via leaf litter has a high potential to increase BS in these loess‐derived surface soils that are underlain by limestone. Species‐related differences of the intensity of soil–tree cation cycling can thus influence the rate of soil acidification and the stocks and distribution of nutrients.     

Prediction of soil organic and inorganic carbon contents at a national scale (France) using mid‐infrared reflectance spectroscopy (MIRS)

This work aimed to evaluate the potential of mid‐infrared reflectance spectroscopy (MIRS) to predict soil organic and inorganic carbon contents with a 2086‐sample set representative of French topsoils (0–30 cm). Ground air‐dried samples collected regularly using a 16 × 16‐km grid were analysed for total (dry combustion) and inorganic (calcimeter) carbon; organic carbon was calculated by difference. Calibrations of MIR spectra with partial least square regressions were developed with 10–80% of the set and five random selections of samples. Comparisons between samples with contrasting organic or inorganic carbon content and regression coefficients of calibration equations both showed that organic carbon was firstly associated with a wide spectral region around 2500–3500 cm^?1 (which was a reflection of its complex nature), and inorganic carbon with narrow spectral bands, especially around 2520 cm^?1. Optimal calibrations for both organic and inorganic carbon were achieved by using 20% of the total set: predictions were not improved much by including more of the set and were less stable, probably because of atypical samples. At the 20% rate, organic carbon predictions over the validation set (80% of the total) yielded mean R², standard error of prediction (SEP) and RPD (ratio of standard deviation to SEP) of 0.89, 6.7 g kg^?1 and 3.0, respectively; inorganic carbon predictions yielded 0.97, 2.8 g kg^?1 and 5.6, respectively. This seemed appropriate for large‐scale soil inventories and mapping studies but not for accurate carbon monitoring, possibly because carbonate soils were included. More work is needed on organic carbon calibrations for large‐scale soil libraries.     

Application of Near‐Infrared Reflectance Spectroscopy to Estimate Chemical Constituents in Broiler Litter

Abstract

Near‐infrared reflectance spectroscopy (NIRS) has potential to provide rapid estimates of phosphorus (P) and nitrogen (N) concentrations in broiler litter to assist managers in establishing application rates of litter to grazing lands that fall within productive and environmentally safe levels. An experiment was conducted to determine accuracy of NIRS estimates of moisture, P, N, and acid detergent fiber (ADF) concentrations in broiler litter. Broiler litter samples were collected from various farms to develop sample sets that were either with or without bedding material, and each sample set was subdivided into processed (i.e., dried and ground) and unprocessed samples to develop local equations for each constituent. Equations were developed by using all samples from each set and using samples following random removal of 20% of total for equation validation. Moisture was determined to be accurately measured by using NIRS based on a high R² (≥0.96), low SEC (<10 g kg^?1), and high s_x/SECV (>5.0). ADF also had a high R² (0.96), but the S_x/SEC (3.00) value was too low for the equation to be considered truly accurate. Estimations of P and N by calibrations that included all samples had a moderate to high R² values, but estimations for the validation set were relatively low in R² (≤0.78) and S_x/SEC (≤2.00). Concentrations of P and N were not estimated by NIRS with a high degree of accuracy, but other methodologies could enhance the usefulness of this technology to rapidly provide these nutrient measures.