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Title: NEAR-INFRARED REFLECTANCE SPECTROSCOPY-PRINCIPAL COMPONENT REGRESSION ANALYSIS OF SOIL PROPERTIES

Author
item CHANG, CHENG - IOWA STATE UNIVERSITY
item Laird, David
item MAUSBACH, MAURICE - USDA, NRCS, SSRA
item HURBURGH, CHARLES - IOWA STATE UNIVERSITY

Submitted to: Soil Science Society of America Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/12/2000
Publication Date: N/A
Citation: N/A

Interpretive Summary: Current use of soil analysis for managing soils and assessing soil quality is limited by the expense and complicated nature of the analysis. We found that Near-Infrared Reflectance Spectroscopy (NIRS) can be used to simultaneously estimate more than 14 soil properties with acceptable accuracy in less than one minute. The results demonstrate that NIRS has the potential to be used as a rapid analytical tool for measuring soil properties in the field thus avoiding the need to collect soil samples and take them to a laboratory for analysis. This research will benefit farmers and land managers by furthering development of a faster and less expensive tool for analyzing soils and will benefit the NRCS and other governmental agencies by furthering development of a faster and less expensive tool for assessing soil quality.

Technical Abstract: A fast and convenient soil analytical technique is needed for soil quality assessment and precision soil management. The main objective of this study was to evaluate the ability of Near-Infrared Reflectance Spectroscopy (NIRS) to predict diverse soil properties. Near-infrared reflectance spectra of 33 chemical, physical, and biochemical properties were studied for 802 soil samples collected from four Major Land Resource Areas (MLRAs). Calibrations were based on locally weighted principal component regression (PCR) using first derivatives of spectral reflectance (log(1/R)) for the 1300-2498 nm spectral range. Total C, total N, moisture, CEC, and 15 bar water were successfully predicted by NIRS (r2 greater than 0.80). Extractable and/or exchangeable cations (Ca, Mg, MN, K, and Fe), particle size distribution, respiration rate, and total mineralizable N were also estimated by NIRS but with less accuracy (r2 0.85-0.65). Predicted values for aggregation, pH, and biomass-C were not very reliable (r2 0.64-0.55); and extractable and/or exchangeable Cu, P, Zn, and Na could not be predicted using the NIRS-PCR technique. The results show that NIRS can be used to simultaneously estimate more than 14 soil properties with acceptable accuracy in less than one minute. Therefore, NIRS has the potential to be used as a rapid analytical technique for measuring soil properties in the field.