Journal of Biosystems Engineering

Korean Society for Agricultural Machinery (한국농업기계학회)
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Preprocessing and Calibration of Optical Diffuse Reflectance Signal for Estimation of Soil Physical and Chemical Properties in the Central USA

미국 중부 토양의 이화학적 특성 추정을 위한 광 확산 반사 신호 전처리 및 캘리브레이션

  • La, Woo-Jung (Dept. of Bioindustrial Machinery Engineering and Institute of Agriculture & Life Sciences Gyeongsang National University) ;
  • Sudduth, Kenneth A. (Agriculture Engineer, Cropping Systems and Water Quality Research Unit, USDA-ARS) ;
  • Chung, Sun-Ok (Dept. of Bioindustrial Machinery Engineering, Chungnam National University) ;
  • Kim, Hak-Jin (School of Biosystems Engineering, Pusan National University)
  • Published : 2008.12.25
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Abstract

Optical diffuse reflectance sensing in visible and near-infrared wavelength ranges is one approach to rapidly quantify soil properties for site-specific management. The objectives of this study were to investigate effects of preprocessing of reflectance data and determine the accuracy of the reflectance approach for estimating physical and chemical properties of selected Missouri and Illinois, USA surface soils encompassing a wide range of soil types and textures. Diffuse reflectance spectra of air-dried, sieved samples were obtained in the laboratory. Calibrations relating spectra to soil properties determined by standard methods were developed using partial least squares (PLS) regression. The best data preprocessing, consisting of absorbance transformation and mean centering, reduced estimation errors by up to 20% compared to raw reflectance data. Good estimates ($R^2=0.83$ to 0.92) were obtained using spectral data for soil texture fractions, organic matter, and CEC. Estimates of pH, P, and K were not good ($R^2$ < 0.7), and other approaches to estimating these soil chemical properties should be investigated. Overall, the ability of diffuse reflectance spectroscopy to accurately estimate multiple soil properties across a wide range of soils makes it a good candidate technology for providing at least a portion of the data needed in site-specific management of agriculture.

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