Soil Organic Matter Parameters Research Articles

Carbon Stock and Chemical Fractionation of Organic Matter in Different Soil Management Systems in the Bahian Cerrado

ABSTRACT Determining total organic carbon and its stock and quantifying the chemical fractions of soil organic matter can be used as indicators of the quality of the soil management used in a cropping area. This study aimed to quantify soil organic matter’s carbon stock and chemical fractions in different soil management systems used in the western Bahian Cerrado, Brazil, and compare them to a native Cerrado area. Ten microregions (Alto Horizonte, Anel da Soja, Bela Vista, Cascudeiro, Coaceral, Novo Paraná, Panambi, Placas, Roda Velha, Roda Velha de Baixo), three soil management systems [tillage system (TS), no-tillage systems (nTS), native Cerrado (NC)], and two soil layers (0–0.1 and 0.1–0.2 m) were studied. Soil bulk density (Sd), soil organic matter (SOM), total organic carbon (TOC), SOM quantification (qSOM), equivalent carbon stock (EqCs), humin (HF), humic acid (HAF) and fulvic acid (FAF) fractions from SOM were evaluated. The results indicated that Sd in all evaluated microregions was below the critical upper limit that would restrict plant root development. SOM, TOC, EqCs, and qSOM revealed increasing results following the TS, nTS, and NC order. The NC area presented the highest soil organic fraction contents (HF, HAF, and FAF). The microregions with better soil quality for all evaluated parameters were Coaceral and Cascudeiro; the lowest soil quality was observed in Alto Horizonte. The present study indicates that conservation agricultural management, such as the no-tillage system, improves the structure and composition of SOM parameters over time.

Qualitative and Quantitative Changes in Soil Organic Compounds in Central European Oak Forests with Different Annual Average Precipitation

The various climate scenarios consistently predict warming and drying of forests in Hungary. Soils play a significant role in the long-term sequestration of atmospheric CO2, while in other cases they can also become net carbon emitters. Therefore, it is important to know what can be expected regarding future changes in the carbon storage capacity of soils in forests. We used precipitation gradient studies to solve this problem, using a type of “space–time” substitution. In this research, we primarily examined the quality parameters of soil organic matter (SOM) to investigate how climate change transforms the ratio of the main SOM compound groups in soils. For our studies, we applied elemental and 13C and 15N isotopic ratio analysis, NMR analysis, FT-IR spectra analysis, thermogravimetric and differential thermal analyses to measure SOM chemistry in samples from different oak forests with contrasting mean annual precipitation from Central Europe. Our results showed that soil organic carbon (SOC) was lower in soils of humid forests due to the enhanced decomposition processes and the leaching of Ca, which stabilizes SOM; however, in particular, the amount of easily degradable SOM compounds (e.g., thermolabile SOM, O-alkyl carbon, carboxylic and carbonyl carbon) decreased. In dry forest soils, the amount of recalcitrant SOM (e.g., thermostable SOM, alkyl carbon, aromatic and phenolic carbon and organo–mineral complexes stabilized by Ca increased, but the amount of easily degradable SOM increased further. The main conclusion of our study is that SOC can increase in forests that become drier, compensating somewhat for the decrease in forest plant biomass.

Optimizing the Dryland Sheet Erosion equation in South China

Optimisation of models applied in sheet erosion equations could facilitate effective management of sheet erosion in the field, and sustainable agricultural production. To optimise the characterisation of sheet erosion on slope farmland in South China, the present study conducted field simulation rainfall experiments with vegetated and fallow soils. According to the results, sheet erosion rate first increased with an increase in rainfall duration and then stabilised. Exclusive P. vulgaris planting and P. vulgaris in combination with earthworms could reduce sheet erosion by 10–60%, and the combined method could better control sheet erosion. There were significant differences in erosion rate between mild and steep slopes, and light and heavy rain conditions. The influence of rain intensity on sheet erosion was greater than that of slope. Soil organic matter (SOM), rain intensity, and slope can be used to optimise sheet erosion equations of exposed slopes, and SOM and hydraulic parameters can be used to optimise sheet erosion equations in vegetated slopes. The results of the present study could facilitate the reduction of the time and space variability errors in the establishment of sheet erosion models for vegetated slopes.

Predicting soil organic matter and soil moisture content from digital camera images: comparison of regression and machine learning approaches

Appropriate soil management maintains and improves the health of the entire ecosystem. Soil appropriate administration necessitates proper characterization of its properties including soil organic matter (SOM) and soil moisture content (SMC). Image-based soil characterization has shown strong potential in comparison with traditional methods. This study compared the performance of 22 different supervised regression and machine learning algorithms, including support vector machines (SVMs), Gaussian process regression (GPR) models, ensembles of trees, and artificial neural network (ANN), in predicting SOM and SMC from soil images taken with a digital camera in the laboratory setting. A total of 22 image parameters were extracted and used as predictor variables in the models in two steps. First models were developed using all 22 extracted features and then using a subset of six best features for both SOM and SMC. Saturation index (redness index) was the most important variable for SOM prediction, and contrast (median S) for SMC prediction, respectively. The color and textural parameters demonstrated a high correlation with both SOM and SMC. Results revealed a satisfactory agreement between the image parameters and the laboratory-measured SOM ( R2 and root mean square error (RMSE) of 0.74 and 9.80% using cubist) and SMC ( R2 and RMSE of 0.86 and 8.79% using random forest) for the validation data set using six predictor variables. Overall, GPR models and tree models (cubist, RF, and boosted trees) best captured and explained the nonlinear relationships between SOM, SMC, and image parameters for this study.

Sampling representativeness of soil carbon and physiological parameters of marandu palisadegrass in a tropical silvopastoral system

The sampling methods for soil and plant evaluation in integrated production systems need to be refined for their use in experiments. This study purposed a sampling representativeness model to evaluate soil carbon and physiological parameters of marandu palisadegrass intercropped with double rows of eucalyptus in a silvopastoral system in southeastern Brazil. Four transects were delimited within the silvopastoral system and the soil was sampled at 0-5, 5-10, and 10- 20 cm depths to evaluate two parameters of soil organic matter: total organic carbon (TOC) and soil microbial carbon (Cmic). We also evaluated three physiological parameters of marandu palisadegrass: stomatal conductance, transpiration rate, and photosynthetic rate. The sampling strategy was evaluated by the Hatheway and Modified Maximum Curvature (MMC) methods. We found that cultivation of the alley with forage grass and double rows of eucalyptus must be considered to ensure sampling representativeness in a silvopastoral system, once TOC and Cmic and physiological parameters showed variation within the integrated production system. The MMC method could be useful to evaluate silvopastoral systems for experiments and characterization of agricultural areas, as 11 soil samples are representative to evaluate Cmic and TOC, and 13 samples are enough to evaluate the physiological parameters in marandu palisadegrass. The Hatheway method could be applied to experiments that need higher accuracy with a reduction in the minimum difference to be detected between the treatments and a consequent increase in the number of samples to be collected.

Using catchment characteristics to model seasonality of dissolved organic carbon fluxes in semi-arid mountainous headwaters.

Prediction of dissolved organic carbon (DOC) based on catchment characteristics is a useful tool for efficient and effective water management, but in the case of arid and semi-arid regions, such predictive capacity is scarce. Accordingly, the main objective of this study was to evaluate the significance of principal components for predicting DOC concentrations and fluxes in nine headwater catchments of the Hiv catchment located in the Southern Alborz Mountains in the west of Tehran, Iran. To achieve this aim, data were assembled on 24 headwater catchment characteristics comprising soil properties, physiography, seasonal rainfall, and flow attributes, as well as estimates of DOC concentrations and fluxes across four seasons. The results revealed a major positive correlation between DOC and soil organic matter parameters related to soil biological processes. Using general linear modelling, an organic matter component related to soil biology, a seasonal component related to the dummy effect of sampling seasons, and a soil physical component related to soil texture were found to be the best predictors for DOC responses in the study area.

Adsorption of epoxiconazole and tebuconazole in twenty different agricultural soils in relation to their properties

Conazole fungicides are currently used pesticides with considerable chronic toxicity and ecotoxicity that are also on EU list for substitution. They enter the soil forming short- or long-term residues. In this study two of their representatives, epoxiconazole (EPC) and tebuconazole (TBC), have been tested with 20 soils from the Czech Republic for their adsorption. Adsorption, by means of Kd coefficients, was compared to “basic” (TOC, pH, clay …) and “advanced” (surface area, minerals ..) soil properties. After doing multivariate analysis of the variables it was apparent that adsorption of both pesticides was highly associated with pH (negatively correlated), and less associated with soil organo-mineral complex (TOC, clay and surface area) and C and N in soil organic matter (OM). Particle sizes or cation exchange capacity (CEC) did not show correlation with adsorption, but showed an association in multidimensional space in factor analysis (FA). Some correlations were revealed between EPC adsorption and soil organic matter parameters. Recalculating Kd to Koc and to Gibb’s free energy (ΔG) and its values indicated that the adsorption of EPC and TBC is mainly weak physical adsorption – partitioning. Also, ΔG values gave better correlation with pH(H2O) than Kd. Surface area impacted EPC adsorption. From the several soil minerals, kaolinite showed EPC and TBC adsorption. EPC adsorption was not highly influenced with pH changes compared to TBC. The number and types of H-bonds with molecular geometry govern the sorption, which might crucially affect leachibility in soil, and this may indicate that TBC is more leachable than EPC for the same soil.

The variation in soil water retention of alpine shrub meadow under different degrees of degradation on northeastern Qinghai-Tibetan plateau

In recent decades, an increasing proportion of alpine shrub meadow has become severely degraded owing to the combined effects of global climate warming and rodent infestation, with significant impacts on soil water retention. The present paper investigates the patterns and controlling factors of soil water retention of alpine shrub meadow under different degrees of degradation, to help inform decisions on the management of degraded alpine shrub meadow. Four degradation stages were defined: non-degradation (ND); light degradation (LD); moderate degradation (MD) and higher degradation (HD). Pearson correlation and redundancy analysis were used to examine the relationships between soil physical properties and soil hydraulic properties. Sand content increased while clay content decreased with increasing degree of degradation. In HD treatment, the available nitrogen and soil bulk density of surface soil layer was significantly lower than that in the other three stages, whereas the soil organic matter content and soil total porosity of surface soil layer was increased significantly, the soil compaction of 0–10 cm soil depth in HD was reduced significantly. The soil water retention of 0–60 cm soil depth first decreased and then increased with increasing degradation, with the maximum values occurring in HD, and the soil organic matter has an overwhelming effect on soil water retention than soil texture. As the degree of degradation increased, the surface soil structure deteriorated, and available nitrogen reduced while soil organic matter increased sharply in higher degradation, which leads to the highest soil water retention in higher degradation. Our results suggested that the soil water retention in degraded alpine grassland was largely determined by soil organic matter, and the soil organic matter parameters should be incorporated in hydrological models of degraded alpine ecosystem.

Productivity and Topsoil Quality of Young and Old Permanent Grassland: An On-Farm Comparison

Renewing agricultural grasslands for improved yields and forage quality generally involves eliminating standing vegetation with herbicides, ploughing and reseeding. However, grassland renewal may negatively affect soil quality and related ecosystem services. On clay soil in the north of the Netherlands, we measured grass productivity and soil chemical parameters of ‘young’ (5–15 years since last grassland renewal) and ‘old’ (>20 years since last grassland renewal) permanent grasslands, located as pairs at 10 different dairy farms. We found no significant difference with old permanent grassland in herbage dry matter yield and fertilizer nitrogen (N) response, whereas herbage N yield was lower in young permanent grassland. Moreover, the young grassland soil contained less soil organic matter (SOM), soil organic carbon (C) and soil organic N compared to the old grassland soil. Grass productivity was positively correlated with SOM and related parameters such as soil organic C, soil organic N and potentially mineralizable N. We conclude that on clay soils with 70% desirable grasses (i.e., Lolium perenne and Phleum pratense) or more, the presumed yield benefit of grassland renewal is offset by a loss of soil quality (SOM and N-total). The current practice of renewing grassland after 10 years without considering the botanical composition, is counter-productive and not sustainable.

Thermal stability of organic matter of typical chernozems under different land uses

Soil organic matter of bulk samples and size fractions (by dry sieving) of chernozems with a rather with different history of use (from intact steppe to permanent bare fallow) was studied by TGA under pyrolysis conditions in an inert atmosphere to approach its transformation depending on the type of use. For the first time, thermal properties of samples of Kursk chernozem (Kursk Research Institute of Agricultural Production and V.V. Alekhin Tsentralno-Chernozemny Nature Reserve of Russia) were studied for a continuous 55-year field experiment with a well-documented history of use and showed that long-term agricultural use significantly changes the thermal parameters of soil organic matter, and this is manifested for aggregates of various sizes. The minimum representative weight for the thermal analysis of bulk soils is ca. 1 g (when grinding samples to 100 μm). The paper proposes a new parameter to assess the degree of organic matter degradation, the ratio of the mass loss in the 380–600 to 170–380 °C temperature ranges that is referred to as two-range thermal stability ratio. It is shown that this relative index discriminates soil samples depending on the land use type and does not require the knowledge on carbon content.

Predicting soil organic matter from cellular phone images under varying soil moisture

Soil organic matter (SOM) is considered as the backbone of soil health and soil quality. Thus, its’ estimation is critical to support the development of management decision including precision agriculture. To overcome challenges of laborious, rather expensive and time-consuming laboratory measurements, recent advances in image acquisition systems provided a new dimension of image-based SOM prediction. However, challenges remain in using soil images taken directly in the field due to variable soil surface conditions including vegetation cover, illumination, and soil moisture. Soil moisture can significantly influence soil color and thus confounds the relationship between SOM and soil color. This study quantifies the effects of soil moisture on the relationship between SOM and color parameters derived from cell phone images and establishes suitable SOM prediction models under varying conditions of soil moisture contents (SMCs). To simulate the continuous variation of soil moisture in the field, air-dried ground soil samples were saturated and allowed to dry naturally. Images were captured with a cellular phone over time representing various SMCs (set of images). Final set of images were captured on oven-dried samples. Images were preprocessed using illumination normalization to avoid illumination inconsistencies and segmentation technique to remove non-soil parts of the images including black cracks, leaf residues and specular reflection before modelling. Five color space models including RGB, HIS, CIELa*b*, CIELc*h* and CIELu*v* were used to quantify soil color parameters. Univariate linear regression models were developed between SOM and color parameters and an optimal set of color parameters that are capable of resisting variation in SMC was determined. It was observed that SMC exerted a considerable influence on SOM prediction accuracy when its value reached > 10%. The threshold of 10% SMC was considered as the critical SMC. Consequently, stepwise multiple linear regression (SMLR) models were developed for soil samples with SMC below and above the critical SMC. For the soil samples at below the critical SMC, the color parameter R based model produced satisfactory prediction accuracy for SOM with R2cv, RMSEcv, and RPDcv values of 0.936, 4.44% and 3.926, respectively. For the soil samples at above the critical SMC, the SOM predictive model including SMC as a predictor variable showed better accuracy (R2cv = 0.819, RMSEcv = 7.747%, RPDcv = 2.328) than that without including SMC (R2cv = 0.741, RMSEcv = 9.382%, RPDcv = 1.922). This study showed potential of cellular phone to be used as a proximal soil sensor fast, accurate and non-destructive estimation of SOM both in the laboratory and field conditions.

How relationships between soil organic matter parameters and soil structure characteristics are affected by the long-term fertilization of a sandy soil

Refining our understanding of how soil structure develops is important because soil structure has a major influence on plant growth. Recent studies show positive correlations between soil organic matter and soil structure. However, the question remains: how are the relationships between soil organic matter (SOM) parameters and soil structure characteristics affected by the long-term fertilization of a sandy soil? In contrast to most other studies on SOM vs. soil structure, the present study is composed of long-term field experiments (a total of 3 experiments) with durations of 25, 41 and 94 years. In this paper, the impact of the long-term application of mineral fertilizers and manure on the SOM and soil structure of a sandy soil is quantified, and the relationships between the SOM and soil structure of a sandy soil with a dependence on the length of fertilizer application are determined. Soil samples were collected from all three long-term field experiments in central Poland, which were located at Skierniewice experimental station including a 94-year-old experiment with mineral fertilization, a 41-year-old experiment with mineral fertilization and a 25-year-old experiment with mineral fertilization + farmyard manure (FYM) in a 4-year cycle. In the spring of 2017, soil samples were collected (Co – no fertilizers, NPK – NPK fertilizers, CaNPK – CaNPK fertilizers). In the 94-year-old experiment, the content of soil organic carbon (SOC) in Co, NPK and CaNPK was 4.07, 5.89 and 5.99 g kg−1, respectively. An increase in the SOC content under fertilization was also found in the other two experiments. In the 25-year-old experiment, the SOC contents in FYM, FYM + NPK and FYM + CaNPK were 6.07, 8.36 and 7.63 g kg−1, respectively, and in the 41-year-old experiment, the SOC contents in Co, NPK and CaNPK were 6.38, 10.1 and 7.80 g kg−1, respectively. The content of labile carbon (CL) increased significantly in the fertilized treatments only in the 94-year-old experiment. The contents of humic substances significantly increased in the soil of fertilized treatments in the 25- and 41-year-old experiments. In all fertilized treatments, the humus quality significantly decreased. After 94 years of mineral fertilization, the content of water-stable macroaggregates (WSAma) in size fractions > 5 and 5–2 mm was significantly higher in the NPK than in the Co and CaNPK treatments. After 94 years of mineral fertilization, the mean weight diameter of aggregates for dry sieving (MWDd) differed between Co (0.41) and both treatments of mineral fertilization (NPK: 0.88; CaNPK: 1.70). The application of FYM with CaNPK resulted in a statistically significant decrease in aggregate stability (Sw) in the 25-year-old experiment. For Co and NPK treatments in the 41-year-old experiment, the contents of WSAma > 5 mm were 41% and 51% lower, respectively, whereas the content of WSAma 5–3 mm was lower by 40% and 50%, respectively, which was higher than that for the CaNPK treatment. The aggregate stability significantly decreased due to NPK application in the soil of the 41-year-old experiment. The number of correlations between SOM parameters and the soil structure decreased in the following order: 94-year-old experiment with mineral fertilization > 41-year-old experiment with mineral fertilization > 25-year-old experiment with mineral fertilization + FYM.

Enzymatic activity and culturable bacteria diversity in rhizosphere of amaranth, as indicators of crop phenological changes

Background: Amaranth is a plant of interest in farming due to its ability to adapt into arid and semi-arid climates. Biological activity by microorganisms in rhizosphere determines plant performance and quality.Hypothesis: The enzymatic activity is different in two types of soil, rhizosheath soil (adhered by roots) and loose soil (non-adhered by roots), in four cropping periods of amaranth.Species study: Amaranthus hypochondriacus L.Methods: Parameters of soil organic matter and several enzyme activities in the amaranth rhizosphere were assessed. Two types of soil, rhizosheath soil and loose soil, and four cropping periods were compared. Thirty-seven culturable bacterial isolates obtained from rhizosheath soil were molecularly identified.Results: Rhizosheath soil had higher content of carbon and total nitrogen compared with loose soil; however, potential enzyme activity in both soil types was similar. Dehydrogenase and acid phosphatase activities were very sensitive to the crops phenological stages. Acid and alkaline phosphatases, cellulase and protease activities correlated to changes in soil moisture. The greatest diversity of culturable bacteria was found during the flowering stage.Conclusions: In the rhizosphere of A. hypochondriacus grown in a pumiceous sandy soil, enzymatic activities in the rhizosheath and loose soils were similar, which must be considered a unique rhizosphere environment. Dehydrogenase and acid phosphatase activities were highly sensitive to changes in the crop phenology. The behavior of phosphatases and dehydrogenase activities suggests an increased dynamic soil organic matter (SOM) during the post-harvest period. In the amaranth rhizosphere, native culturable bacteria are involved in the breakdown of SOM.

Application of microwave-pretreated cephalosporin mycelial dreg (CMD) as soil amendment: Temporal changes in chemical and fluorescent parameters of soil organic matter

Land application of treated cephalosporin mycelial dreg (CMD) as a soil amendment is an alternative to its disposal in landfills and incineration because it has environmental and agronomic benefits. This study validated the efficacy of using the dewatered, microwave-pretreated CMD as a soil amendment. Pot experiments were conducted to assess the temporal changes in soil organic matter (SOM) profiles via chemical and fluorescent parameters. During the ageing period, the CMD-treated soil experienced a sudden rise in soil pH and soil electrical conductivity, along with a rapid decline in soil organic carbon and soil organic nitrogen content. The specific Ex/Em peak related to protein-like substances gradually disappeared, while those related to humic acid-like substances continued to increase thereafter. Fluorescence regional integration (FRI) results showed an ascended PV,n/PIII,n index (1.94) and significant correlations with chemical data (M2=0.2875, r=0.8441, P<0.001, 999 permutations for Procrustes analysis). Taken together, despite the temporal changes in chemical and fluorescent data after soil conditioning, the increased content of SOM containing humic acid-like substances was observed at the end of the incubation period compared with control soil samples, indicating that the microwave-pretreated CMD might be applied as a soil amendment.

The influence of soil organic matter fractions on aggregates stabilization in agricultural and forest soils of selected Slovak and Czech hilly lands

Because the stability of soil aggregates is affected by many factors, we studied aggregates formed in forest and agricultural soils in different soil types (Cambisols, Luvisols, Chernozems). We evaluated: (1) the differences in water-stable aggregates (WSA) as related to soil type and land management and (2) the relationships between quantitative and qualitative parameters of soil organic matter (SOM), particle-size distribution and individual size classes of WSA. Soil samples were taken from three localities (Soběsice, Bab, Vieska nad Žitavou). Each study locality included both a forest and an agricultural soil-sampling area. We found that in forest soils, the proportion of water-stable macroaggregates (WSAma) relative to water-stable microaggregates (WSAmi) was greater than in agricultural soils. When all soils were assessed together, positive statistically significant correlations were observed between the size classes WSAma > 1 mm and organic carbon (Corg) content; however, the WSAmi content was negatively correlated with Corg content. Favorable humus quality positively influenced the stabilization of WSAma > 5 mm; however, we found it had a negative statistically significant effect on stabilization of WSAma 1–0.25 mm. In agricultural soils, the stabilization of WSAma was associated with humified, i.e., stable SOM. The WSAma content was highly positively influenced mainly by fulvic acids bound with clay and sesquioxides; therefore, we consider this humus fraction to be a key to macroaggregate stability in the studied agricultural soils. On the other side, all fractions of humic and fulvic acids participated on the formation of WSAma in forest soil, which is a major difference in organic stabilization agents of macroaggregates between studied forest and agricultural soils. Another considerable difference is that WSAmi in agricultural soils were stabilized primarily with humic acids and in forest soils by fulvic acids. Moreover, in forest soils, a higher content of labile carbon in WSA had a positive effect on formation of WSAmi. The observed changes in individual size classes of WSA and interactions between SOM, particle-size distribution, and WSA have a negative impact on soil fertility and thereby endanger agricultural sustainability.

The long-term changes in soil organic matter contents and quality in Chernozems

For the purposes of assessment of long-term changes, two sets of Chernozems soil samples were analysed and compared in parallel: ‘old’ file samples obtained during the Soil Survey 1960–1970 in the former Czechoslovakia and a ‘present’ (2013) set of samples from exactly the same sites as the archive samples. The recently collected samples revealed worse qualitative parameters (lower humic acid to fulvic acid (HA/FA) ratios and higher colour quotient Q4/6 values) than the file samples, for all the localities. On the other side, the quantitative soil organic matter (SOM) parameters (oxidizable carbon (C&lt;sub&gt;ox&lt;/sub&gt;) and all its determined components) showed contrary results. The amount of total SOM at the same sites is higher now than it was about 50 years ago. It can be concluded that the current decline in SOM quality in Chernozems is partly compensated for by higher accumulation of SOM in the soils. All the analysed Chernozem samples were found to have much worse qualitative SOM parameters than the values mentioned for this soil type in the older literature. However, a comparison of the current data and the file data of Chernozem SOM quality can still be considered an open issue and require more complex research.

Changes in Soil Organic Matter Parameters during the Period of 18 Years Under Different Soil Management Practices

Abstract Quantity and quality of soil organic matter (SOM) is very important from view point of sustainable agriculture; therefore, during the years 1994–2011, the influence of different soil management practices on changes in SOM parameters in loamy Haplic Luvisol was evaluated in a field experiment in the locality of Dolná Malanta. The field experiment included two types of soil tillage – (1) conventional tillage (CT) and (2) reduced tillage (RT) – and also two treatments of fertilisation – (1) crop residues together with added NPK (nitrogen, phosphorus and potassium) fertilisers (CR + NPK) and (2) added NPK fertilisers. Contents of humic substances (HS) and fulvic acids (FA) under RT increased by 1.6% and 4.4%, respectively, compared to CT during the years 1994–2011. On the other hand, contents of humic acids (HA), HA-to-FA ratios, colour quotient of HS and colour quotient of HA under CT increased by 2.0%, 2.5%, 1.8% and 2.3%, respectively, compared to RT. In CT and RT, HS declined at an average speed of 0.33% and 0.53% per year, respectively. In CR + NPK treatments and application, only NPK fertiliser caused a decline of HS at an average speed of 0.52% and 0.33 % per year, respectively. In CT, RT and CR + NPK treatments, the linear trends (statistical significant) in decline of FA were observed. All in all, the CT had a slightly better effect on the quality of SOM, whilst the stability of SOM was improved by RT. Applications of mineral fertilisers along with crop residues resulted in better quality but lower stability of SOM.

How dose of biochar and biochar with nitrogen can improve the parameters of soil organic matter and soil structure?

AbstractBiochar application to agricultural soils has a significant potential to influence soil resource availability and thus crop performance. A factorial experiment investigating effects of different biochar application rates combined with nitrogen fertilizer was conducted in field conditions on a Haplic Luvisol. The aim of this study was to evaluate the effects of biochar and biochar combined with fertilization on soil organic matter and soil structure parameters. The treatments comprised combinations of biochar application of 0, 10 and 20 t ha

Use of Spectral Character to Evaluate Soil Organic Matter

Core Ideas Reflectance spectroscopy was used to characterize soil properties. Continuum‐removed processing was utilized to achieve absorbed peaks and absorbed characters. Multiple liner regression and PLS methods were also applied and compared for assessment. Variable importance in projection was used for evaluation. To estimate soil organic matter (SOM) and evaluate the performance of a SOM prediction model with two different soil particle sizes (sieved soil and nonsieved soil), multivariate statistical analysis is applied to construct an SOM model with absorption peak parameters derived from the continuum‐removed (CR) method. In this study, 107 samples from Exp. 1 were randomly categorized into 86 samples as a calibration set and 21 samples as a validation set to construct the SOM models. The second field experiment, which included 47 samples, was also implemented to validate the spectral absorption peak parameters of SOM. The results indicated that the SOM models based on the nonsieved soil (R2 &gt; 0.692; RMSE &lt; 6.018) had better performance than the sieved soil (R2 &lt; 0.627; RMSE &gt; 6.732). The most accurate SOM model was based on the multiple liner regression (MLR) method. The SOM models constructed with the partial least squares regression (PLSR) method were stable and also showed a moderate prediction for both nonsieved soil and sieved soil. Moreover, the important absorption peak parameters (trend slopes [TS] at 2410 nm, spectral absorption index [SAI] at 1320 nm, and TS at 662 nm for nonsieved; SAI at 892 nm, TS at 2345 nm, and absorption depth [H] at 669 nm for sieved soil) were determined to be related to SOM by using the PLSR method. Therefore, the combination of multivariate statistical methods (MLR and PLSR) provides a foundation to estimate SOM.

Rapid assessment of soil organic matter: Soil color analysis and Fourier transform infrared spectroscopy

Soil organic matter (SOM) content and composition may be affected by geographic region, land use (grassland vs. forest) and management intensity (intensive vs. extensive). To asses these effects SOM of 300 German soils was characterized using soil color analyses (L*,a*,b*-values) and Fourier transform infrared (FTIR) spectroscopy. Soil lightness (L*-value) was strongly negatively correlated with the soil organic carbon content and this relationship was stronger when the previously sieved soils were ground. Using the band at wavenumber 1634cm−1 (as determined by FTIR) as a proxy for aromaticity of SOM the L*-value was negatively correlated with aromaticity. Geographic region as well as land use affected L*-, a*- and b*-values. FTIR results suggested that particularly amides and polysaccharides were affected by geographic region, while mainly polysaccharides were affected by land use. We conclude that soil color analysis can provide additional information on environmental circumstances/site effects which may affect SOM composition. A few only weak correlations of soil color/SOM composition parameters with management intensity indicate that either changes in SOM parameters were too small or that the applied management indices were not sensitive enough to management effects.