Determination of organic carbon and nitrogen in particulate organic matter and particle size fractions of Brookston clay loam soil using infrared spectroscopy
ABSTRACT The objective of this study was to determine whether models developed from infrared spectroscopy could be used to estimate organic carbon (C) content, total nitrogen (N) content and the C:N ratio in the particulate organic matter (POM) and particle size fraction samples of Brookston clay loam. The POM model was developed with 165 samples, and the particle size fraction models were developed using 221 samples. Soil organic C and total N contents in the POM and particle size fractions (sand, 2000-53 micro m; silt, 53-2 micro m; clay, <2 micro m) were determined by using dry combustion techniques. The bulk soil samples were scanned from 4000 to 400 cm-1 for mid-infrared (MIR) spectra and from 8000 to 4000 cm-1 for near-infrared (NIR) spectra. Partial least squares regression (PLSR) analysis and the 'leave-one-out' cross-validation procedure were used for the model calibration and validation. Organic C and N content and C:N ratio in the POM were well predicted with both MIR- and NIR-PLSR models ( R cal2=0.84-0.92; R val2=0.78-0.87). The predictions of organic C content in soil particle size fractions were also very good for the model calibration ( R cal2=0.84-0.94 for MIR and R cal2=0.86-0.92 for NIR) and model validation ( R val2=0.79-0.94 for MIR and R cal2=0.84-0.91 for NIR). The prediction of MIR- and NIR-PLSR models for the N content and the C:N ratio in the sand and clay fractions was also satisfactory ( R cal2=0.73-0.88; R val2=0.67-0.85). However, the predictions for the N content and C:N ratio in the silt fraction were poor ( R cal2=0.23-0.55; R cal2=0.20-0.40). The results indicate that both MIR and NIR methods can be used as alternative methods for estimating organic C and total N in the POM and particle size fractions of soil samples. However, the NIR model is better for estimating organic C and N in POM and sand fractions than the MIR model, whereas the MIR model is superior to the NIR model for estimating organic C in silt and clay fractions and N in clay fractions.
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ABSTRACT: The usefulness of the C/N ratio as an indicator of the decomposability of organic matter in forest soil was assessed. The assessment was based on the relationship between the C/N ratio and the contents of soil organic carbon (SOC), soil nitrogen (total N), dissolved total organic carbon (DTOC) and dissolved inorganic nitrogen (DIN). SOC, total N, DTOC and DIN were determined in soils sampled in coniferous and coniferous–deciduous forest sites from genetic horizons of 48 soil profiles. The variability of the above soil parameters was determined and the correlation between these parameters and the C/N values were calculated. It was found that the C/N ratio in soil was shaped by the difference in the mobility of both elements, whereas the decrease in the C content in subsequent horizons was mostly higher than the decrease in the N content, which means that the C/N value decreased with the depth of a soil profile. When the loss of SOC and total N contents occurs at a similar rate, the C/N ratio is maintained at a more or less stable level despite the advancing SOM mineralization. When the rate of the carbon release from SOM differs from that of nitrogen or when there is an N input from external sources, the C/N ratio does not adequately describe the process of SOM mineralization as well. The correlation coefficients between the C/N ratio and other parameters indicate that the relationships between them are not significant or that there is no correlation at all. It was found that the percentage of DTOC in SOC seemed to be a better indicator of SOM mineralization than the C/N ratio.Ecological Indicators 10/2014; · 3.23 Impact Factor
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ABSTRACT: Assessment and monitoring of soil organic matter (SOM) quality are important for determining and developing management practices that will enhance and maintain the productivity of agricultural soils. This requires routine analysis of multiple soil parameters, which can be time-consuming and expensive. Research has suggested that visible near infrared reflectance spectroscopy (VNIRS) may be used as a rapid and cost-efficient tool for SOM quality assessment. In this study, VNIRS (400–2498 nm)was used for the first time to simultaneously predict microbial biomass nitrogen (MBN),water-extractable organic N (WEON), light fraction organic matter N (LFOMN), particulate organic matter N (POMN), soil total N (TN), soil organic carbon (SOC) and soil C/N ratio as soil SOM quality indicators in Chernozemic soils of western Canada. The soil samples (n = 200) were collected at the 0–15 cm depth from a crop rotation experiment conducted at 6 sites in 2010 and 2011. After removal of outliers (five samples) identified by principal components analysis (PCA), 75% of the sample set was randomly selected for calibration (n=146) and the remainder used for validation (n=49).Modified partial least squares regression with cross-validation was used to develop prediction models. The reliability of the models was assessed using the coefficient of determination in validation (R2V) and the ratio of standard deviation of the reference data in the validation set to the standard error of prediction (RPDV). The VNIRS predictions were considered reliable for LFOMN, POMN, TN, and SOC (R2V N 0.80, RPDV N 2.4), aswell as forMBN (R2V= 0.74, RPDV= 1.93),but less reliable for WEON (R2V = 0.67, RPDV = 1.70) and soil C/N ratio (R2V = 0.54, RPDV = 1.45). This study showed that VNIRS has the potential as a non-destructive and cost-efficient tool for rapid determination of SOM quality indicators.Geoderma 11/2014; 232-234:449-458. · 2.51 Impact Factor
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ABSTRACT: The distribution of extracellular enzyme activities in particle-size fractions of sediments was investigated in a subtropical mangrove ecosystem. Five enzymes involved in carbon (C), nitrogen (N), and phosphorus (P) cycling were analyzed in the sand, silt, and clay of sediments. Among these fractions, the highest activities of phenol oxidase (PHO), β-D glucosidase (GLU), and N-acetyl-glucosiminidase (NAG) were found in sand, and greater than bulk sediments of both intertidal zone (IZ) and mangrove forest (MG). This result implied that sand fractions might protect selective enzymes through the adsorption without affecting their activities. Additionally, the enzyme-based resource allocation in various particle-size fractions demonstrated that nutirents availability varied with different particle-size fractions and only sand fraction of MG with highest total C showed high N and P availability among fractions. Besides, the analysis between elemental contents and enzymes activities in particle-size fractions suggested that enzymes could monitor the changes of nutrients availability and be good indicators of ecosystem responses to environmental changes. Thus, these results provided a means to assess the availability of different nutrients (C, N, and P) during decomposition of sediment organic matter (SOM), and thus helping to better manage the subtropical mangrove ecosystems to sequester C into SOM.Global Journal of Environmental Science and Management. 01/2015; 1(1):15-26.