|Culman, Steve - The Ohio State University|
|Six, Johan - Swiss Federal Institute Of Technology Zurich|
|Schipanski, Meagan - Colorado State University|
|Beniston, Joshua - Santa Rosa Junior College|
|Grandy, Stuart - University Of New Hampshire|
|Kong, Angela - Columbia University|
Submitted to: Soil Science Society of America Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/1/2016
Publication Date: 4/20/2017
Publication URL: http://handle.nal.usda.gov/10113/5801866
Citation: Calderon, F.J., Culman, S., Six, J., Franzluebbers, A.J., Schipanski, M., Beniston, J., Grandy, S., Kong, A.Y. 2017. Quantification of soil permanganate oxidizable c (poxc) using infrared spectroscopy. Soil Science Society of America Journal. 81:277-288. doi:10.2136/sssaj2016.07.0216.
Interpretive Summary: This study shows that infrared spectroscopy can be used to quickly and accurately predict soil POXC, which represents the soil organic matter that is relatively easy to decompose. This is important, because POXC is one of the soil properties that is most affected by agricultural practices and is also a good indicator of soil fertility and quality. This study also shows that soil organic C and N can also be predicted with infrared spectroscopy, but soils which have received compost or biochar might not calibrate as well.
Technical Abstract: Labile soil carbon is an important component of soil organic matter because it embodies the mineralizable material that is associated with short-term fertility and responds to management practices. Permanganate-oxidizable C (POXC) is a widely used method for the study of labile C dynamics in soils. Rapid methods are needed to measure labile C, and better understand how this pool varies with soil C at regional scales. Infrared spectroscopy is an inexpensive way to quantify SOC and observe fluctuations in C functional groups. Using a sample set that encompassed several soil types and plant communities (seven different research projects, n = 496), soils were analyzed via diffuse reflectance Fourier transformed mid-infrared (MidIR, 4000-400 cm-1) and near-infrared spectroscopy (NIR, 10000-4000 cm-1). Spectral data was used to develop calibrations for POXC, soil organic C (SOC), and total N (TN) using partial least squares (PLS) regression. The MidIR predicted POXC slightly better than the NIR, with calibration/validation R2 values ranging from 0.77-0.81 depending on spectral pretreatments. Predictions for POXC were better than SOC and TN, but we show that site variability influenced the calibration quality for SOC and TN. Using a selected MidIR region, which included bands correlated to POXC (3225-2270 cm-1), reduced the calibration quality, but still gave acceptable R2 values of 0.76-0.77 for the calibration and validation sets. We show that POXC can be predicted using NIR and MidIR spectra. Selecting informative spectral bands offers an alternative to using full spectra for PLS regressions.