Quantification of soil carbon from bulk soil samples to predict the aggregate-carbon fractions within using near- and mid-infrared spectroscopic techniques

Geoderma ◽  
2016 ◽  
Vol 267 ◽  
pp. 207-214 ◽  
Author(s):  
M.P.N.K. Henaka Arachchi ◽  
D.J. Field ◽  
A.B. McBratney
Keyword(s):  
Soil Carbon ◽  
Soil Samples ◽  
Bulk Soil ◽  
Spectroscopic Techniques ◽  
Mid Infrared ◽  
Carbon Fractions ◽  
Infrared Spectroscopic

Near-infrared and Mid-infrared Spectroscopic Techniques for a Fast and Nondestructive Quality Control of Thymi herba

Planta Medica ◽  
2017 ◽  
Vol 84 (06/07) ◽  
pp. 420-427 ◽  
Author(s):  
Cornelia Pezzei ◽  
Stefan Schönbichler ◽  
Shah Hussain ◽  
Christian Kirchler ◽  
Verena Huck-Pezzei ◽  
...  
Keyword(s):  
Antioxidant Capacity ◽  
Rosmarinic Acid ◽  
Near Infrared ◽  
Coefficient Of Determination ◽  
Attenuated Total Reflectance ◽  
Spectroscopic Techniques ◽  
Test Set ◽  
Mid Infrared ◽  
Capacity Coefficient ◽  
Infrared Spectroscopic

AbstractIn this study, novel near-infrared and attenuated total reflectance mid-infrared spectroscopic methods coupled with multivariate data analysis were established enabling the determination of thymol, rosmarinic acid, and the antioxidant capacity of Thymi herba. A new high-performance liquid chromatography method and UV-Vis spectroscopy were applied as reference methods. Partial least squares regressions were carried out as cross and test set validations. To reduce systematic errors, different data pretreatments, such as multiplicative scatter correction, 1st derivative, or 2nd derivative, were applied on the spectra. The performances of the two infrared spectroscopic techniques were evaluated and compared. In general, attenuated total reflectance mid-infrared spectroscopy demonstrated a slightly better predictive power (thymol: coefficient of determination = 0.93, factors = 3, ratio of performance to deviation = 3.94; rosmarinic acid: coefficient of determination = 0.91, factors = 3, ratio of performance to deviation = 3.35, antioxidant capacity: coefficient of determination = 0.87, factors = 2, ratio of performance to deviation = 2.80; test set validation) than near-infrared spectroscopy (thymol: coefficient of determination = 0.90, factors = 6, ratio of performance to deviation = 3.10; rosmarinic acid: coefficient of determination = 0.92, factors = 6, ratio of performance to deviation = 3.61, antioxidant capacity: coefficient of determination = 0.91, factors = 6, ratio of performance to deviation = 3.42; test set validation). The capability of infrared vibrational spectroscopy as a quick and simple analytical tool to replace conventional time and chemical consuming analyses for the quality control of T. herba could be demonstrated.

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.

Modelling soil carbon fractions with visible near-infrared (VNIR) and mid-infrared (MIR) spectroscopy

Geoderma ◽  
2015 ◽  
Vol 239-240 ◽  
pp. 229-239 ◽  
Author(s):  
N.M. Knox ◽  
S. Grunwald ◽  
M.L. McDowell ◽  
G.L. Bruland ◽  
D.B. Myers ◽  
...  
Keyword(s):  
Soil Carbon ◽  
Near Infrared ◽  
Mid Infrared ◽  
Carbon Fractions ◽  
Mir Spectroscopy ◽  
Soil Carbon Fractions

Soil organic carbon dynamics jointly controlled by climate, carbon inputs, soil properties and soil carbon fractions

2017 ◽  
Vol 23 (10) ◽  
pp. 4430-4439 ◽  
Author(s):  
Zhongkui Luo ◽  
Wenting Feng ◽  
Yiqi Luo ◽  
Jeff Baldock ◽  
Enli Wang
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Properties ◽  
Soil Carbon ◽  
Carbon Dynamics ◽  
Carbon Fractions ◽  
Soil Organic Carbon Dynamics ◽  
Soil Carbon Fractions

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.

scholarly journals Robustness of visible near‐infrared and mid‐infrared spectroscopic models to changes in the quantity and quality of crop residues in soil

2020 ◽  
Vol 84 (3) ◽  
pp. 963-977
Author(s):  
Isabel Greenberg ◽  
Deborah Linsler ◽  
Michael Vohland ◽  
Bernard Ludwig
Keyword(s):  
Near Infrared ◽  
Crop Residues ◽  
Mid Infrared ◽  
Infrared Spectroscopic
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