Technical Abstract: Diffuse reflectance spectroscopy based on near-infrared radiation (NIRS) has become an important method for analyzing agricultural products where large numbers of measurements are needed to detect variations in product composition that impact market value (i.e., protein in grains and food/feed composition) or to monitor and measure spatial and temporal variation in environmental parameters (i.e., soil carbon and other soil properties). More recently, diffuse reflectance spectroscopy using Fourier transform mid-infrared (DRIFTS) has also been shown to be capable of rapid quantitative analysis of agricultural products and environmental samples. Through the process termed chemometrics, information contained in the entire spectrum is related to the property of interest by use of multivariate statistical techniques such as stepwise regression, principle component analysis or, more recently, partial squares regression. Mathematical models produced by these techniques form the calibration models used to predict properties of unknown samples. With the development of robust calibrations, NIRS and DRIFTS have the ability to analyze samples rapidly and simultaneously for multiple properties with virtually no consumables and minimal sample preparation.