Predicting contents of carbon and its component fractions in Australian soils from diffuse reflectance mid-infrared spectra

Soil Research ◽  
2013 ◽  
Vol 51 (8) ◽  
pp. 577 ◽  
Author(s):  
J. A. Baldock ◽  
B. Hawke ◽  
J. Sanderman ◽  
L. M. Macdonald
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Carbon ◽  
Total Nitrogen ◽  
Diffuse Reflectance ◽  
Inorganic Carbon ◽  
Soil Samples ◽  
Mid Infrared ◽  
Organic And Inorganic Carbon ◽  
Mir Spectra

Quantifying the content and composition of soil carbon in the laboratory is time-consuming, requires specialised equipment and is therefore expensive. Rapid, simple and low-cost accurate methods of analysis are required to support current interests in carbon accounting. This study was completed to develop national and state-based models capable of predicting soil carbon content and composition by coupling diffuse reflectance mid-infrared (MIR) spectra with partial least-squares regression (PLSR) analyses. Total, organic and inorganic carbon contents were determined and MIR spectra acquired for 20 495 soil samples collected from 4526 locations from soil depths to 1 m within Australia’s agricultural regions. However, all subsequent MIR/PLSR models were developed using soils only collected from the 0–10, 10–20 and 20–30 cm depth layers. The extent of grinding applied to air-dried soil samples was found to be an important determinant of the variability in acquired MIR spectra. After standardisation of the grinding time, national MIR/PLSR models were developed using an independent test-set validation approach to predict the square-root transformed contents of total, organic and inorganic carbon and total nitrogen. Laboratory fractionation of soil organic carbon into particulate, humus and resistant forms was completed on 312 soil samples. Reliable national MIR/PLSR models were developed using cross-validation to predict the contents of these soil organic carbon fractions; however, further work is required to enhance the representation of soils with significant contents of inorganic carbon. Regional MIR/PLSR models developed for total, organic and inorganic carbon and total nitrogen contents were found to produce more reliable and accurate predictions than the national models. The MIR/PLSR approach offers a more rapid and more cost effective method, relative to traditional laboratory methods, to derive estimates of the content and composition of soil carbon and total nitrogen content provided that the soils are well represented by the calibration samples used to build the predictive models.

scholarly journals Can Agricultural Management Induced Changes in Soil Organic Carbon Be Detected Using Mid-Infrared Spectroscopy?

2021 ◽  
Vol 13 (12) ◽  
pp. 2265
Author(s):  
Jonathan Sanderman ◽  
Kathleen Savage ◽  
Shree Dangal ◽  
Gabriel Duran ◽  
Charlotte Rivard ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Carbon ◽  
Diffuse Reflectance Spectroscopy ◽  
Low Cost ◽  
Soil Survey ◽  
Mid Infrared ◽  
Mir Spectroscopy ◽  
Induced Changes ◽  
Carbon Change

A major limitation to building credible soil carbon sequestration programs is the cost of measuring soil carbon change. Diffuse reflectance spectroscopy (DRS) is considered a viable low-cost alternative to traditional laboratory analysis of soil organic carbon (SOC). While numerous studies have shown that DRS can produce accurate and precise estimates of SOC across landscapes, whether DRS can detect subtle management induced changes in SOC at a given site has not been resolved. Here, we leverage archived soil samples from seven long-term research trials in the U.S. to test this question using mid infrared (MIR) spectroscopy coupled with the USDA-NRCS Kellogg Soil Survey Laboratory MIR spectral library. Overall, MIR-based estimates of SOC%, with samples scanned on a secondary instrument, were excellent with the root mean square error ranging from 0.10 to 0.33% across the seven sites. In all but two instances, the same statistically significant (p < 0.10) management effect was found using both the lab-based SOC% and MIR estimated SOC% data. Despite some additional uncertainty, primarily in the form of bias, these results suggest that large existing MIR spectral libraries can be operationalized in other laboratories for successful carbon monitoring.

Carbon storage in cotton soils of northern New South Wales

Soil Research ◽  
2003 ◽  
Vol 41 (5) ◽  
pp. 889 ◽  
Author(s):  
T. A. Knowles ◽  
B. Singh
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Content ◽  
Soil Carbon ◽  
Inorganic Carbon ◽  
Carbon Pool ◽  
Total Carbon ◽  
Soil Types ◽  
Soil Carbon Pool ◽  
Total Soil

Soil carbon is an important component of the global carbon cycle with an estimated pool of soil organic carbon of about 1500 Gt. There are few estimates of the pool of inorganic carbon, but it is thought to be approximately 50% of the organic carbon pool. There is no detailed study on the estimation of the soil carbon pool for Australian soils.In order to quantify the carbon pools and to determine the extent of spatial variability in the organic and inorganic carbon pools, 120 soil cores were taken down to a depth of 0.90 m from a typical cotton field in northern NSW. Three cores were also taken from nearby virgin bushland and these samples were used as paired samples. Each soil core was separated into 4 samples, i.e. 0–0.15, 0.15–0.30, 0.30–0.60, and 0.60–0.90 m. Soil organic carbon was determined by wet oxidation and inorganic carbon content was determined using the difference between total carbon and organic carbon, and confirmed by the acid dissolution method. Total carbon was measured using a LECO CHN analyser. Soil organic carbon of the field constituted 62% (0–0.15 m), 58% (0.15–0.30 m), 60% (0.30–0.60 m), and 67% (0.60–0.90 m) of the total soil carbon. The proportion of inorganic carbon in total carbon is higher than the global average of 32%. Organic carbon content was relatively higher in the deeper layers (>0.30�m) of the studied soils (Vertosols) compared with other soil types of Australia. The carbon content varied across the field, however, there was little correlation between the soil types (grey, red, or intergrade colour) and carbon content. The total soil carbon pool of the studied field was estimated to be about 78 t/ha for 0–0.90 m layer, which was approximately 58% of the total soil carbon in the soil under nearby remnant bushland (136 t/ha). The total pool of carbon in the cotton soils of NSW was estimated to be 44.8 Mt C, where organic carbon and inorganic carbon constitute 34.9 Mt C and 9.9 Mt C, respectively. Based on the results of a limited number of paired sites under remnant vegetation, it was estimated that about 18.9 Mt of C has been lost from Vertosols by cotton cropping in NSW. With more sustainable management practices such as conservation tillage and green manuring, some of the lost carbon can be resequestered, which will help to mitigate the greenhouse effect, improve soil quality and may increase crop yield.

Generic Prediction of Soil Organic Carbon in Alfisols Using Diffuse Reflectance Fourier-Transform Mid-Infrared Spectroscopy

2011 ◽  
Vol 75 (6) ◽  
pp. 2358-2360 ◽  
Author(s):  
Mercy Kamau-Rewe ◽  
Frank Rasche ◽  
Juan Guillermo Cobo ◽  
Gerd Dercon ◽  
Keith D. Shepherd ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Diffuse Reflectance ◽  
Mid Infrared ◽  
Mid Infrared Spectroscopy

Spatial variability of organic and inorganic carbon stocks in Hungry Steppe (Uzbekistan)

2020 ◽  
Author(s):  
Sophia Demina ◽  
Viacheslav Vasenev ◽  
Kristina Ivashchenko ◽  
Inna Brianskaia ◽  
Bakhtiyor Pulatov ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Carbon ◽  
Soil Salinity ◽  
Inorganic Carbon ◽  
Carbon Stocks ◽  
Total Carbon ◽  
Soil Inorganic Carbon ◽  
Organic And Inorganic Carbon ◽  
Soil Carbon Stocks ◽  
Soil Inorganic

&lt;p&gt;Desertification is an important soil treat, affecting soil functions and ecosystem services&amp;#160;&amp;#160; in arid and semiarid climate zones. Salinization is one of the principal processes which follows desertification and has a negative impact on soil properties and functions. Carbon sequestration is considered a principle soil function and the decline in soil carbon stocks in one of the main negative consequences of soil degradation. Soil salinization is caused by combination of natural factors (e.g. dry climate condition and high table of mineralized ground waters) and human activities such as improper water management. Globally, soils of the areas affected by salinization are considered to be poor in organic carbon due to low biomass and hampered microbiological activity. However, the contribution of inorganic carbon to the total carbon stocks in these areas can be comparable. Considering that soil inorganic carbon is more stable to mineralization compared to organic carbon, soil carbon stocks in saline landscape shall not be neglected.&lt;/p&gt;&lt;p&gt;Central Asian regions and especially the Aral Sea basin have been historically affected by desertification enhancing soil salinity. Hungry Steppe (Mirzachul) is an area of historical desertification and salinization, covering around 10000 km&lt;sup&gt;2&lt;/sup&gt; at the territories of Uzbekistan, South Kazakhstan and Tajikistan. The region has a sharp continental climate with large seasonal fluctuations. Dry and semidesertic steppe vegetation dominates the natural areas (mainly coincided with high soil salinity), whereas most of the areas is managed to produce cotton, perennial grasses, melons and gourds. Soils are dominated by serozems corresponding to Calcisols in WRB soil classification. The research aimed to analyze the effect of salinization on carbon stocks in Hungry Steppe. To achieve this aim, soil carbon stocks were estimated at the four collective farms, referred as Water Consumer Assiociations (WCAs) or &amp;#8216;shirkats&amp;#8217; in Syrdarya province: Khavast district in Yangier WCA, Mirzaobod district in Beruniy WCA&amp;#160; Oq Oltin district in Andijan WCA and Syrdarya district in Sobir&amp;#160; Rakhimov WCA. The selected sites belonged to different in land quality classes, based on the land evaluation survey carried out by the melioration expedition of the Ministry of Agriculture and Water Resources of Uzbekistan in 201,&amp;#160; from the lowest (Mirzaobod) to the highest (S. Rahimov). Soil pH, electroconductivity, chlorides, organic and inorganic carbon stocks and total nitrogen stocks were estimated for each of the areas. Although the internal variability in the analyzed parameters was high we clearly showed the highest stocks of soil inorganic carbon in the most salinized area, whereas the highest stocks of organic carbon were shown for the most fertile lands. However, we didn&amp;#8217;t ding significant difference in the total carbon stocks between the sites. It can be concluded that desertification has more effect on the redistribution of organic and inorganic forms of carbon, rather than on the total carbon stocks.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Acknowledgements &lt;/strong&gt;The experimental research was performed with the support of the Russian Foundation for Basic Research, Project # 18-54-41004 and Ministry of Innovation development of the Republic of Uzbekistan, Project # MRU-SQV 86/2017. Data analysis and mapping was supported by the RUDN project &amp;#8220;5-100&amp;#8221;.&lt;/p&gt;

scholarly journals Spatial Variability of Soil Organic Carbon and Total Nitrogen in Desert Steppes of China’s Hexi Corridor

2021 ◽  
Vol 9 ◽  
Author(s):  
Xuyang Wang ◽  
Yuqiang Li ◽  
Yulong Duan ◽  
Lilong Wang ◽  
Yayi Niu ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Carbon ◽  
Total Nitrogen ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Elevation Gradient ◽  
Dominant Factor ◽  
Desert Steppe ◽  
Carbon And Nitrogen

Stock estimates are critical to quantifying carbon and nitrogen sequestration, quantifying greenhouse gas emissions, and understanding key biogeochemical processes (i.e., soil carbon and nutrient cycling). Many studies have assessed soil organic matter and nutrients in different ecosystems. However, the spatial distribution of carbon and nitrogen and the key influencing factors in arid desert steppe remain unclear. Here, we investigated the soil organic carbon (SOC) and soil total nitrogen (STN) to a depth of 100 cm at 126 sites in a desert steppe in northwestern China. SOC and STN contents decreased with increasing depth; the highest average SOC and STN contents were 12.70 and 0.65 g kg−1 in the surface 5 cm, and the lowest were from 80 to 100 cm (4.49 and 0.16 g kg−1, respectively). SOC density (SOCD) and STN density (STND) to a depth of 100 cm averaged 8.94 and 0.45 kg m−2, respectively. The top 1 m of the soils stored approximately 1,041 Tg SOC and 52 Tg STN in the study area. Geostatistical analysis showed strong and moderate spatial autocorrelation for SOCD in different soil layers, but the autocorrelation for STND gradually weakened with increasing depth. SOCD and STND decreased from southwest to northeast in the study area, along an elevation gradient. Both were significantly positively correlated with topographic variables, precipitation, and the normalized-difference vegetation index, but negatively correlated with temperature and aridity. More than 40% of the SOCD and STND spatial variation was explained by elevation, which was the dominant factor. The data and high-resolution maps from this study will support future soil carbon and nitrogen analyses.

How does grinding affect the mid-infrared spectra of soil and their multivariate calibrations to texture and organic carbon?

Soil Research ◽  
2015 ◽  
Vol 53 (8) ◽  
pp. 913 ◽  
Author(s):  
F. Le Guillou ◽  
W. Wetterlind ◽  
R. A. Viscarra Rossel ◽  
W. Hicks ◽  
M. Grundy ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Ir Spectra ◽  
Soil Sample ◽  
Diffuse Reflectance ◽  
Near Infrared ◽  
Diffuse Reflectance Spectroscopy ◽  
Soil Samples ◽  
Particle Sizes ◽  
Mid Infrared ◽  
Specular Reflections

Mid-infrared (mid-IR) diffuse reflectance spectroscopy can be used to effectively analyse soil, but the preparation of soil samples by grinding is time consuming. Soil samples are usually finely ground to a particle size of less than 0.250 mm because the spectrometer’s beam aperture is approximately 1–2 mm in diameter. Larger particles can generate specular reflections and spectra that do not adequately represent the soil sample. Grinding soil to small particle sizes enables the diffuse reflectance of light and more representative sample measurements. Here, we report on research that investigates the effect that grinding to different particle sizes have on soil mid-IR spectra. Our aims were to compare the effect of grinding soil to different particle sizes (2.000 mm, 1.000 mm, 0.500 mm, 0.250 mm and 0.106 mm) on the frequencies of mid-IR spectra, and compare the effect of these particle sizes on the accuracy of spectroscopic calibrations to predict organic carbon, sand, silt and clay contents. Using the Commonwealth Scientific and Industrial Research Organisation’s (CSIRO) National visible–near infrared database, we selected 227 soil samples from the National Soil Archive for our experiments, and designed an experiment whereby each soil sample was ground in triplicate to the different particle sizes. These ground samples were measured using an FT-IR spectrometer with a spectral range of 4000–600 cm–1. Grinding to particle sizes that are ≤2.000 mm reduces subsample variability. Smaller particle sizes produce finer and sharper absorption features, which are related to organic carbon, and clay and sand mineralogies. Generally, better predictions for clay, sand and soil organic carbon contents were achieved using soil that is more finely ground, but there were no statistically significant differences between predictions that use soil ground to 1 mm, 0.5 mm, 0.25 mm. Grinding did not affect predictions of silt content. Recommendations on how much grinding is required for mid-IR analysis should also consider the time, cost and effort needed to prepare the soil samples as well as the purpose of the analysis.

scholarly journals Comparison of soil organic carbon and total nitrogen stocks between farmland treated with three and six years level soil bund and adjacent farmland without conservation measure: In the case of southwestern Ethiopia

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0252123
Author(s):  
Leta Hailu ◽  
Mulugeta Betemariyam
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Total Nitrogen ◽  
Block Design ◽  
Critical Role ◽  
Soil Samples ◽  
Conservation Measure ◽  
Southwestern Ethiopia ◽  
The Status ◽  
And Control

This study was conducted to examine and compare the status of soil organic carbon (SOC) and total nitrogen (TN) stocks between farmlands treated with level soil bund (LSB) of three and six years and adjacent farmland without conservation measure (control) at Somodo Watershed. Soil samples were collected from farmland treated with LSB-3 years, LSB-6 years and control using randomized complete block design. A total of 108 composite soil samples (3 treatments * 6 replications * 3 bund zones * 2 depths (0–20 and 20–40 cm) were collected for analysis and determination of the Organic Carbon fraction (OC) and Nitrogen fraction (N). OC was determined using Walkley and Black method while N was determined using the Kjeldahl digestion, distillation and titration method. The result indicated that farmland treated with LSB-6 years has insignificantly higher SOC (98.43±11.55 Mg ha-1) and TN (9.37±1.10 Mg ha-1) stock than control SOC (93.01±13.51 Mg ha-1) and TN (9.28±1.60 Mg ha-1) stock. Likely, farmland treated with LSB-6 years has insignificantly higher SOC and TN stock than farmland treated with LSB-3 years SOC (96.61±11.45 Mg ha-1) stock. With respect to the age of LSB, farmland treated with LSB-6 years accumulated more SOC stock (5.83%) than control. This study revealed that the age of LSB conservation measures has a critical role in enhancing soil fertility through maintaining and sequestering SOC and TN.

Sign in / Sign up

Export Citation Format

Share Document