Can Agricultural Management Induced Changes in Soil Organic Carbon Be Detected Using Mid-Infrared Spectroscopy?
Autor: | Kathleen Savage, Shree R. S. Dangal, Jonathan Sanderman, Yichao Rui, Hero T. Gollany, Charlotte Rivard, Emmanuel Chiwo Omondi, Virginia L. Jin, Mark A. Liebig, Michel A. Cavigelli, Catherine E. Stewart, Gabriel Duran |
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Rok vydání: | 2021 |
Předmět: |
long term agricultural trials
Diffuse reflectance infrared fourier transform Soil test Science Agricultural management chemistry.chemical_element Soil science 04 agricultural and veterinary sciences Soil carbon 010501 environmental sciences 01 natural sciences Mid infrared spectroscopy diffuse reflectance spectroscopy Soil survey chemistry 040103 agronomy & agriculture 0401 agriculture forestry and fisheries General Earth and Planetary Sciences Environmental science Spectroscopy soil spectroscopy Carbon 0105 earth and related environmental sciences |
Zdroj: | Remote Sensing; Volume 13; Issue 12; Pages: 2265 Remote Sensing, Vol 13, Iss 2265, p 2265 (2021) |
ISSN: | 2072-4292 |
Popis: | 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. |
Databáze: | OpenAIRE |
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