TECHNICAL ARTICLESCOMPARISON OF NEAR INFRARED AND MID INFRARED DIFFUSE REFLECTANCE SPECTROSCOPY FOR FIELD-SCALE MEASUREMENT OF SOIL FERTILITY PARAMETERSMcCarty, Gregory W.1; Reeves, James B. III2Author Information 1USDA Environmental Quality Laboratory, Beltsville, MD. Dr. Gregory W. McCarty is corresponding author. E-mail: [email protected] 2USDA Animal Manure and Byproducts Laboratory, Beltsville, MD. Received Dec. 30, 2004; accepted Sept. 1, 2005. Soil Science: February 2006 - Volume 171 - Issue 2 - p 94-102 doi: 10.1097/01.ss.0000187377.84391.54 Buy Metrics Abstract Data-intensive technologies such as precision agriculture require new approaches for acquisition of soil data on landscapes. We compared the ability of near infrared (NIR; 400-2500 nm) and mid infrared (MIR; 2,500-25,000 nm) spectroscopy for field-scale acquisition of soil fertility parameters. Samples were obtained in a grid pattern (25 m spacing) from the surface (0-10 cm) and sub-surface (10-30 cm) samples collected at 272 locations. Samples were analyzed for organic C and total N, texture (clay, silt, and sand), soil pH, and Mehlich I extractable Ca, K, Mg, and P. We found that chemometric analyses NIR and MIR provided good calibrations for organic carbon, total N, and soil texture. To varying degrees of precision, these regions also calibrated for pH and exchangeable Ca, Mg, and K. Exchangeable P did not form useful calibrations in either spectral region. In all cases, MIR calibrations were better than those formed in the NIR region. Test of calibrations based on one-third of the samples was used to predict the remaining samples. This demonstrated the strategy of developing field-scale calibrations for the spectral regions by chemical analysis of a small sub-set of samples for the prediction of large numbers of samples. This approach can be used to accurately map the spatial distribution of soil properties within agricultural landscapes. These studies demonstrate the utility of infrared spectral approaches for generating the spatial soil properties data needed to implement precision agriculture technology. © 2006 Lippincott Williams & Wilkins, Inc.