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 ◽  
...  

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.

Geoderma ◽  
2019 ◽  
Vol 354 ◽  
pp. 113840 ◽  
Author(s):  
Jean-Martial Johnson ◽  
Elke Vandamme ◽  
Kalimuthu Senthilkumar ◽  
Andrew Sila ◽  
Keith D. Shepherd ◽  
...  

2002 ◽  
Vol 66 (2) ◽  
pp. 640-646 ◽  
Author(s):  
G. W. McCarty ◽  
J. B. Reeves ◽  
V. B. Reeves ◽  
R. F. Follett ◽  
J. M. Kimble

1997 ◽  
Vol 51 (8) ◽  
pp. 1200-1204 ◽  
Author(s):  
James B. Reeves ◽  
Stephen R. Delwiche

The objective of this study was to determine whether mid-infrared diffuse reflectance spectroscopy could be used in the same manner as near-infrared diffuse reflectance spectroscopy to quantitatively determine the protein content of ground wheat samples. One hundred and thirty hard red winter wheat samples were assayed for protein by combustion and scanned in the near- and mid-infrared. Samples (UDY ground) were scanned neat in the near-infrared from 1100 nm (9091 cm−1) to 2498 nm (4003 cm−1) on a scanning monochromator and in the mid-infrared from 4000 cm−1 (2500 nm) to 400 cm−1 (25,000 nm) on a Fourier transform spectrometer at 4-and 16-cm−1 resolutions. Protein content varied from a low of 8.98% to a high of 18.70% (average of 12.86% with a standard deviation of 1.66%). Calibrations developed with the use of partial least-squares gave an R2 and bias-corrected standard error of performance of 0.999 and 0.054 for the near-infrared and 0.997 and 0.085 for the mid-infrared (4 cm−1 resolution). Calibration results based on mid-infrared spectra, while not as good as those for near-infrared spectra, were nevertheless quite good. These results demonstrate that it is possible to develop satisfactory calibrations for protein in ground wheat with the use of mid-infrared spectra without the need for sample dilution with KBr.


Soil Research ◽  
2013 ◽  
Vol 51 (8) ◽  
pp. 577 ◽  
Author(s):  
J. A. Baldock ◽  
B. Hawke ◽  
J. Sanderman ◽  
L. M. Macdonald

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.


2002 ◽  
Vol 66 (2) ◽  
pp. 640 ◽  
Author(s):  
G. W. McCarty ◽  
J. B. Reeves ◽  
V. B. Reeves ◽  
R. F. Follett ◽  
J. M. Kimble

Geoderma ◽  
2012 ◽  
Vol 189-190 ◽  
pp. 312-320 ◽  
Author(s):  
Meryl L. McDowell ◽  
Gregory L. Bruland ◽  
Jonathan L. Deenik ◽  
Sabine Grunwald ◽  
Nichola M. Knox

2021 ◽  
Vol 13 (12) ◽  
pp. 2265
Author(s):  
Jonathan Sanderman ◽  
Kathleen Savage ◽  
Shree Dangal ◽  
Gabriel Duran ◽  
Charlotte Rivard ◽  
...  

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.


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