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

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 show...

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Bibliographic Details
Published in:	Remote sensing (Basel, Switzerland) Switzerland), 2021-06, Vol.13 (12), p.2265
Main Authors:	Sanderman, Jonathan, Savage, Kathleen, Dangal, Shree R. S., Duran, Gabriel, Rivard, Charlotte, Cavigelli, Michel A., Gollany, Hero T., Jin, Virginia L., Liebig, Mark A., Omondi, Emmanuel Chiwo, Rui, Yichao, Stewart, Catherine
Format:	Article
Language:	eng
Subjects:	Agricultural management Calibration Carbon Carbon sequestration Cost analysis diffuse reflectance spectroscopy Estimates Experiments Infrared spectra Infrared spectroscopy Laboratories Libraries long term agricultural trials Organic carbon Organic soils Remote sensing Research centers Soil analysis Soil management soil spectroscopy Soil surveys Spectrum analysis Statistical analysis Statistical methods Wheat
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Summary:	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.
ISSN:	2072-4292 2072-4292