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ARS Home » Plains Area » El Reno, Oklahoma » Grazinglands Research Laboratory » Forage and Livestock Production Research » Research » Publications at this Location » Publication #167966


item Northup, Brian
item Daniel, John
item Carson, Lesley

Submitted to: Society for Range Management Meeting Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: 1/10/2005
Publication Date: 2/5/2005
Citation: Northup, B.K., Daniel, J.A., Carson, L.B. 2005. Predicting soil characteristics of Oklahoma pasture with near infrared reflectance spectroscopy (NIRS) [abstract]. Society for Range Management, 58th Annual Meeting and Trade Show, February 5-11, 2005, Fort Worth, Texas. 2005 CDROM.

Interpretive Summary: Abstract Only

Technical Abstract: Soil characteristics are important to pasture productivity in central Oklahoma. Rapid, accurate estimates would be useful in improving management. However, traditional laboratory techniques require significant amounts of time, equipment and manpower. This study examined whether useful predictive relationships could be developed between results of traditional laboratory analyses and near infrared reflectance spectroscopy (NIRS). Soil samples (n=300) were collected from each of four, 1.6 ha experimental paddocks in November 2003, after 27 years of sustained management (three levels of grazing on upland tallgrass prairie and conservation-tilled and grazed winter wheat). Samples were ground to 2.0 mm particle size, sieved to remove roots and litter, scanned by NIRS, and analyzed (n=165) for total nitrogen, total carbon (high temperature induction), organic matter (loss on ignition [400oC]) and bulk density. Relationships between peaks of reflected wavelengths from NIRS (750-2500 nm range) and levels of the characteristics defined by laboratory procedures were developed by partial least squares regression. Strong relationships were noted between results of laboratory analyses and NIRS for C and N (R^2 >0.97; P<0.01). The equation defining relationships for organic matter was less precise but still significant (R^2=0.87; P<0.01), and bulk density had the least precise equation (R^2=0.72; P<0.05). Results indicate NIRS could be used to quickly estimate (with relative accuracy) some important soil characteristics. Such assessments could be useful in quickly defining nutrient concentrations and management responses. Data from additional sites and forms of management are required to fully test the ability of NIRS to estimate soil characteristics.