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 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 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 Effect of Different Tillage Systems on Soil Organic Carbon and Enzymatic Activity

Agronomy ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 208
Author(s):  
Małgorzata Szostek ◽  
Ewa Szpunar-Krok ◽  
Renata Pawlak ◽  
Jadwiga Stanek-Tarkowska ◽  
Anna Ilek
Keyword(s):  
Organic Matter ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Organic Farming ◽  
Total Nitrogen ◽  
Farming Systems ◽  
Conventional Tillage ◽  
Tillage Systems ◽  
Organic Farming Systems ◽  
Organic Matter Fractions

The aim of the study was to compare the effect of conventional, simplified, and organic farming systems on changes in the content of soil organic carbon, organic matter fractions, total nitrogen, and the enzymatic activity. The research was conducted from 2016–2018 on arable land in the south-eastern part of Poland. The selected soils were cultivated in conventional tillage (C_Ts), simplified tillage (S_Ts), and organic farming (O_Fs) systems. The analyses were performed in soil from the soil surface layers (up to 25 cm depth) of the experimental plots. The highest mean contents of soil organic carbon, total nitrogen, and organic matter fractions were determined in soils subjected to the simplified tillage system throughout the experimental period. During the study period, organic carbon concentration on surface soil layers under simplified tillage systems was 31 and 127% higher than the soil under conventional tillage systems and organic farming systems, respectively. Also, the total nitrogen concentration in those soils was more than 40% and 120% higher than conventional tillage systems and organic farming systems, respectively. Moreover, these soils were characterised by a progressive decline in SOC and Nt resources over the study years. There was no significant effect of the analysed tillage systems on the C:N ratio. The tillage systems induced significant differences in the activity of the analysed soil enzymes, i.e., dehydrogenase (DH) and catalase (CAT). The highest DH activity throughout the experiment was recorded in the O_Fs soils, and the mean value of this parameter was in the range of 6.01–6.11 μmol TPF·kg−1·h−1. There were no significant differences in the CAT values between the variants of the experiment. The results confirm that, regardless of other treatments, such as the use of organic fertilisers, tillage has a negative impact on the content of SOC and organic matter fractions in the O_Fs system. All simplifications in tillage reducing the interference with the soil surface layer and the use of organic fertilisers contribute to improvement of soil properties and enhancement of biological activity, which helps to maintain its productivity and fertility.

scholarly journals Properties of Humic Acids in Meadow Soils Irrigated With the Slope-And Flooding System

2021 ◽  
Author(s):  
Magdalena Banach-Szott ◽  
Andrzej Dziamski
Keyword(s):  
Particle Size ◽  
Organic Matter ◽  
Organic Carbon ◽  
Humic Acids ◽  
Soil Samples ◽  
Hydrophobic Properties ◽  
Irrigation Ditch ◽  
Ft Ir ◽  
Degree Of Maturity

Abstract The aim of the research has been to determine the effect of many-year irrigation of unique grasslands on the properties of humic acids defining the quality of organic matter. The research was performed based on the soil (Albic Brunic Arenosol, the A, AE and Bsv horizons) sampled from Europe’s unique complex of permanent grasslands irrigated continuously for 150 years, applying the slope-and-flooding system; the Czerskie Meadows. The soil samples were assayed for the content of total organic carbon (TOC) and the particle size distribution. HAs were extracted with the Schnitzer method and analysed for the elemental composition, spectrometric parameters in the UV-VIS range, hydrophilic and hydrophobic properties and the infrared spectra were produced. The research results have shown that the HAs properties depended on the depth and the distance from the irrigation ditch. The HAs of the A horizon of the soils were identified with a lower “degree of maturity”, as reflected by the values of atomic ratios (H/C, O/C, O/H), absorbance coefficients, and the FT-IR spectra, as compared with the HAs of the Bsv horizon. The HAs molecules of the soils sampled furthest from the irrigation ditch were identified with a higher degree of humification, as compared with the HAs of the soils sampled within the closest distance. The results have demonstrated that many-year grassland irrigation affected the structure and the properties of humic acids.

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

scholarly journals Determining the Distribution and Interaction of Soil Organic Carbon, Nitrogen, pH and Texture in Soil Profiles: A Case Study in the Lancangjiang River Basin, Southwest China

Forests ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 532 ◽  
Author(s):  
Wenxiang Zhou ◽  
Guilin Han ◽  
Man Liu ◽  
Jie Zeng ◽  
Bin Liang ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
River Basin ◽  
Soil Ph ◽  
Soil Texture ◽  
Soil Depth ◽  
Soil Samples ◽  
Soil Profiles ◽  
Soil Organic Nitrogen ◽  
Silty Loam

The profile distributions of soil organic carbon (SOC), soil organic nitrogen (SON), soil pH and soil texture were rarely investigated in the Lancangjiang River Basin. This study aims to present the vertical distributions of these soil properties and provide some insights about how they interact with each other in the two typical soil profiles. A total of 56 soil samples were collected from two soil profiles (LCJ S-1, LCJ S-2) in the Lancangjiang River Basin to analyze the profile distributions of SOC and SON and to determine the effects of soil pH and soil texture. Generally, the contents of SOC and SON decreased with increasing soil depth and SOC contents were higher than SON contents (average SOC vs. SON content: 3.87 g kg−1 vs. 1.92 g kg−1 in LCJ S-1 and 5.19 g kg−1 vs. 0.96 g kg−1 in LCJ S-2). Soil pH ranged from 4.50 to 5.74 in the two soil profiles and generally increased with increasing soil depth. According to the percentages of clay, silt, and sand, most soil samples can be categorized as silty loam. Soil pH values were negatively correlated with C/N ratios (r = −0.66, p < 0.01) and SOC contents (r = −0.52, p < 0.01). Clay contents were positively correlated with C/N ratios (r = 0.43, p < 0.05) and SOC contents (r = 0.42, p < 0.01). The results indicate that soil pH and clay are essential factors influencing the SOC spatial distributions in the two soil profiles.

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