scholarly journals COMPARISON OF TWO METHODS OF SOIL ORGANIC CARBON DETERMINATION

2016 ◽  
Vol 48 (1) ◽  
pp. 47 ◽  
Author(s):  
Gabriela Barančíková ◽  
Jarmila Makovníková
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Statistical Processing ◽  
Soil Samples ◽  
Soil Parameters ◽  
Wide Range ◽  
Soil Complex ◽  
Complex Monitoring ◽  
Carbon Determination

<p>Soil organic carbon (SOC) is one of the basic soil parameters which takes part in many biological, chemical and physical soil processes and the SOC is currently considered as a key indicator of soil quality. For this reason determination of the SOC is a part of soil complex monitoring which has been performed in Slovakia since 1993. From 1993 until 2007 the “wet” method of determination of the SOC was used. Since 2008 the “dry” method for determination of the SOC has been applied. The goal of this work has been to evaluate and compare two methods of the SOC determination; the “wet”(Ťiurin method in modification of Nikitin (TN)) and the “dry” determination of the SOC by means of the CN analyser (EA), which was performed on 95 soil samples of topsoil coming from 17 sampling sites with a wide range of the SOC (1–15%). Sampling sites include arable lands and grasslands and represent main soil types and subtypes of Slovakia. On the basis of statistical processing it has been found that in soils with the SOC content up to 3%, differences between two methods are minimal. However, in the case of a higher content of the SOC, the EA method reaches a higher value than the TN method. Obtained data shows that in the case of soil samples with a higher content of the SOC, when changing an analytical method, the PTF function that reduces differences and allows to use all time series monitoring data should be used for the purpose of the tracking trends of the SOC monitoring.</p><p> </p><p>Celem pracy było porównanie wyników oznaczania węgla organicznego (SOC) w próbkach gleb dwoma metodami: spalania „na mokro“ (Tiurina) oraz spalania „na sucho“ w autoanalizatorzee CN. Analizowano 95 próbek gleb z 17 miejsc kompleksowego monitoringu gleb Słowacji, o zwawartości węgla organicznego od 1 do 15%. Analiza statystyczna wykazała, że różnice wyników oznaczania SOC dwoma metodami w próbkach o zawarości węgla do 3% nie były istotne statystycznie. Dla próbek o wyższej zawartości SOC, wyniki uzyskane metodą spalania „na sucho“ były istotnie wyższe niż uzyskane metodą Tiurina, dlatego do celów porównawczych zawartości SOC w tych glebach oznaczonych różnymi metodami należy stosować odpowiednie przeliczniki.</p>

scholarly journals Relationship between the mass of organic matter and carbon in soil

2008 ◽  
Vol 51 (2) ◽  
pp. 263-269 ◽  
Author(s):  
Silmara R. Bianchi ◽  
Mario Miyazawa ◽  
Edson L. de Oliveira ◽  
Marcos Antonio Pavan
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Organic Carbon ◽  
Soil Depth ◽  
Soil Surface ◽  
Soil Samples ◽  
Loss On Ignition ◽  
Oxidation Degree ◽  
Wide Range

The quantity of soil organic matter (SOM) was estimated through the determination of soil organic carbon (SOC) times a factor, which assumes that 58% of the SOM was formed by carbon. A number of soil samples with wide range of SOC content collected in the state of Paraná, Brazil were evaluated in the laboratory. SOC was measured by Walkley-Black method and the total SOM by loss on ignition. The SOC was positively correlated with SOM. The SOM/SOC ratio varied from 1.91 to 5.08 for the soils. It shows that Brazilian SOM has greater oxidation degree. Although, the SOM and SOC decreased with soil depth the SOM/SOC ratio increased. It showed that SOM in the subsoil contained more oxygen but less carbon than the SOM in the upper soil surface. The CEC/SOC also increased with depth indicating that the functional groups of the SOM increased per unity of carbon.

scholarly journals ESTIMATION OF SOIL ORGANIC CARBON PERCENTAGE IN ORGANIC FARMING SOIL SAMPLES OF TANUKU REGION, ANDHRAPRADESH, INDIA BY WALKLEY-BLACK CHROMIC ACID WET OXIDATION METHOD

2020 ◽  
pp. 519-523
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Organic Farming ◽  
Andhra Pradesh ◽  
Chromic Acid ◽  
Soil Samples ◽  
Animal Remains ◽  
Farming Soil

The Estimation of Soil Organic Carbon (SOC) Percentage is done in Organic farming Soil samples from various places in Tanuku Region, Andhra Pradesh, India. It provides all the necessary information about, effect of Organic farming on the concentration of soil organic carbon and also assess the amount of organic matter in soil. The result depends on the quality of soil. The Soil samples were collected systematically from organic farming lands, Sieved the soil samples through 2mm sieves. The determination of SOC is based on the Walkley-Black Chromic acid Wet oxidatiom method. The method measures the amount of carbon in plant and animal remains, including soil humus but not charcoal or coal

scholarly journals A Two-Stage Approach to the Estimation of High-Resolution Soil Organic Carbon Storage with Good Extension Capability

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 517
Author(s):  
Sunwei Wei ◽  
Zhengyong Zhao ◽  
Qi Yang ◽  
Xiaogang Ding
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Storage ◽  
Guangdong Province ◽  
Soil Samples ◽  
Estimation Accuracy ◽  
Ann Model ◽  
Soil Layers ◽  
Second Stage ◽  
Organic Carbon Storage

Soil organic carbon storage (SOCS) estimation is a crucial branch of the atmospheric–vegetation–soil carbon cycle study under the background of global climate change. SOCS research has increased worldwide. The objective of this study is to develop a two-stage approach with good extension capability to estimate SOCS. In the first stage, an artificial neural network (ANN) model is adopted to estimate SOCS based on 255 soil samples with five soil layers (20 cm increments to 100 cm) in Luoding, Guangdong Province, China. This method is compared with three common methods: The soil type method (STM), ordinary kriging (OK), and radial basis function (RBF) interpolation. In the second stage, a linear model is introduced to capture the regional differences and further improve the estimation accuracy of the Luoding-based ANN model when extending it to Xinxing, Guangdong Province. This is done after assessing the generalizability of the above four methods with 120 soil samples from Xinxing. The results for the first stage show that the ANN model has much better estimation accuracy than STM, OK, and RBF, with the average root mean square error (RMSE) of the five soil layers decreasing by 0.62–0.90 kg·m−2, R2 increasing from 0.54 to 0.65, and the mean absolute error decreasing from 0.32 to 0.42. Moreover, the spatial distribution maps produced by the ANN model are more accurate than those of other methods for describing the overall and local SOCS in detail. The results of the second stage indicate that STM, OK, and RBF have poor generalizability (R2 < 0.1), and the R2 value obtained with ANN method is also 43–56% lower for the five soil layers compared with the estimation accuracy achieved in Luoding. However, the R2 of the linear models built with the 20% soil samples from Xinxing are 0.23–0.29 higher for the five soil layers. Thus, the ANN model is an effective method for accurately estimating SOCS on a regional scale with a small number of field samples. The linear model could easily extend the ANN model to outside areas where the ANN model was originally developed with a better level of accuracy.

scholarly journals The use of radiocarbon <sup>14</sup>C to constrain carbon dynamics in the soil module of the land surface model ORCHIDEE (SVN r5165)

2018 ◽  
Author(s):  
Marwa Tifafi ◽  
Marta Camino-Serrano ◽  
Christine Hatté ◽  
Hector Morras ◽  
Lucas Moretti ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Carbon ◽  
Land Surface ◽  
Carbon Stock ◽  
Land Surface Model ◽  
Carbon Dynamics ◽  
Total Carbon ◽  
Soil Parameters ◽  
Surface Model

Abstract. Despite the importance of soil as a large component of the terrestrial ecosystems, the soil compartments are not well represented in the Land Surface Models (LSMs). Indeed, soils in current LSMs are generally represented based on a very simplified schema that can induce a misrepresentation of the deep dynamics of soil carbon. Here, we present a new version of the IPSL-Land Surface Model called ORCHIDEE-SOM, incorporating the 14C dynamic in the soil. ORCHIDEE-SOM, first, simulates soil carbon dynamics for different layers, down to 2 m depth. Second, concentration of dissolved organic carbon (DOC) and its transport are modeled. Finally, soil organic carbon (SOC) decomposition is considered taking into account the priming effect. After implementing the 14C in the soil module of the model, we evaluated model outputs against observations of soil organic carbon and 14C activity (F14C) for different sites with different characteristics. The model managed to reproduce the soil organic carbon stocks and the F14C along the vertical profiles. However, an overestimation of the total carbon stock was noted, but was mostly marked on the surface. Then, thanks to the introduction of 14C, it has been possible to highlight an underestimation of the age of carbon in the soil. Thereafter, two different tests on this new version have been established. The first was to increase carbon residence time of the passive pool and decrease the flux from the slow pool to the passive pool. The second was to establish an equation of diffusion, initially constant throughout the profile, making it vary exponentially as a function of depth. The first modifications did not improve the capacity of the model to reproduce observations whereas the second test showed a decrease of the soil carbon stock overestimation, especially at the surface and an improvement of the estimates of the carbon age. This assumes that we should focus more on vertical variation of soil parameters as a function of depth, mainly for diffusion, in order to upgrade the representation of global carbon cycle in LSMs, thereby helping to improve predictions of the future response of soil organic carbon to global warming.

Matching legacy estimation of soil organic carbon changes from non-paired data with measured values in paired soil samples after two decades: a case study

2021 ◽  
Author(s):  
Calogero Schillaci ◽  
Sergio Saia ◽  
Aldo Lipani ◽  
Alessia Perego ◽  
Claudio Zaccone ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Depth ◽  
Soil Samples ◽  
Wilcoxon Test ◽  
Reliable Estimate ◽  
Model Errors ◽  
Paired Data ◽  
Concentration Changes ◽  
Legacy Data

&lt;p&gt;Legacy data are frequently unique sources of data for the estimation of past soil properties. With the rising concerns about greenhouse gases (GHG) emission and soil degradation due to intensive agriculture and climate change effects, soil organic carbon (SOC) concentration might change heavily over time.&lt;/p&gt;&lt;p&gt;When SOC changes is estimated with legacy data, the use of soil samples collected in different plots (i.e., non-aligned data) may lead to biased results. The sampling schemes adopted to capture SOC variation usually involve the resampling of the original sample using a so called paired-site approach.&lt;/p&gt;&lt;p&gt;In the present work, a regional (Sicily, south of Italy) soil database, consisting of N=302 georeferenced soil samples from arable land collected in 1993 [1], was used to select coinciding sites to test a former temporal variation (1993-2008) obtained by a comparison of models built with data sampled in non-coinciding locations [2]. A specific sampling strategy was developed to spot SOC concentration changes from 1994 to 2017 in the same plots at the 0-30 cm soil depth and tested.&lt;/p&gt;&lt;p&gt;To spot SOC changes the minimum number of samples needed to have a reliable estimate of SOC variation after 23 years has been estimated. By applying an effect size based methodology, 30 out of 302 sites were resampled in 2017 to achieve a power of 80%, and an a=0.05.&lt;/p&gt;&lt;p&gt;After the collection of the 30 samples, SOC concentration in the newly collected samples was determined in lab using the same method&lt;/p&gt;&lt;p&gt;A Wilcoxon test applied to the variation of SOC from 1994 to 2017 suggested that there was not a statistical difference in SOC concentration after 23 years (Z = -0.556; 2-tailed asymptotic significance = 0.578). In particular, only 40% of resampled sites showed a higher (not always significant) SOC concentration than in 2017.&lt;/p&gt;&lt;p&gt;This finding contrasts with a previous SOC concentration increase that was found in 2008 (75.8% increase when estimated as differences of 2 models built with non-aligned data) [2], when compared to 1994 observed data (Z = -9.119; 2-tailed asymptotic significance &lt; 0.001).&lt;/p&gt;&lt;p&gt;Such a result implies that the use of legacy data to estimate SOC concentration changes need soil resampling in the same locations to overcome the stochastic model errors. Further experiment is needed to identify the percentage of the sites to resample in order to align two legacy datasets in the same area.&lt;/p&gt;&lt;p&gt;Bibliography&lt;/p&gt;&lt;p&gt;[1]Schillaci C, et al.,2019. A simple pipeline for the assessment of legacy soil datasets: An example and test with soil organic carbon from a highly variable area. CATENA.&lt;/p&gt;&lt;p&gt;[2]Schillaci C, et al., 2017. Spatio-temporal topsoil organic carbon mapping of a semi-arid Mediterranean region: The role of land use, soil texture, topographic indices and the influence of remote sensing data to modelling. Sci Total Environ.&amp;#160;&lt;/p&gt;

scholarly journals Study on Carbon Stock of Leasehold Forests of Katakuti VDC, Dolakha District

2014 ◽  
Vol 5 ◽  
pp. 63-67
Author(s):  
Tshering Dolma Lama ◽  
Ram Asheshwar Mandal
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Leaf Litter ◽  
Random Sampling ◽  
Carbon Stock ◽  
Carbon Stocks ◽  
Soil Samples ◽  
Total Carbon ◽  
Different Depths ◽  
Total Carbon Stock

A study was carried on ten leasehold forests of Katakuti VDC, Dolakha district to estimate the carbon stock. Random sampling was used to collect the biophysical data of trees/ poles, sapling, root and leaf litter, herb and grass. Then, the biomass was calculated using the respective equation and the calculated biomass stock was converted into carbon stock multiplying with 0.47. Similarly, the soil samples were collectewd from different depths of 0-10 cm, 10-20 cm and 20-30 cm to determine the soil organic carbon. Lastly, all analyzed data were compiled to get total carbon stocks. The result showed that the estimated total carbon stock per ha was found to be highest in Srijana leasehold forest with 125.493 t C/ha. The estimated total carbon stock of 10 leasehold forest was found to be 1439.033 tons. Here, Leasehold forests have been an emerging and successful example in conserving forests in epal. So, it is recommended to extend such studies in other parts of Nepal. DOI: http://dx.doi.org/10.3126/init.v5i0.10255   The Initiation 2013 Vol.5; 63-67

Sign in / Sign up

Export Citation Format

Share Document