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An Alternate Method for Fourier Transform Infrared (FTIR) Spectroscopic Determination of Soil Nitrate Using Derivative Analysis and Sample Treatments
Authors:Eunyoung Choe  Freek van der Meer  David Rossiter  Caroline van der Salm  Kyoung-Woong Kim
Institution:1. Department of Environmental Science and Engineering, Gwangju Institute of Science and Technology (GIST), 261 Cheomdan-gwagiro, Buk-gu, Gwangju, 500-712, Republic of Korea
2. Soil & Fertilizer Management Division, National Academy of Agricultural Science, RDA, 150 Suin-ro, Gwonseon-gu, Suwon, 441-707, Republic of Korea
3. Department of Earth Systems Analysis, International Institute for Geo-information Science and Earth Observation (ITC), Hengelosestraat 99, 7500 AA, Enschede, The Netherlands
4. Department of Physical Geography, Utrecht University, Heidelberglaan 2, 3508 TA, Utrecht, The Netherlands
5. Alterra, Soil Science Center, Wageningen University and Research Center, P.O. Box 47, NL-6700 AA, Wageningen, The Netherlands
Abstract:This study aimed at examining effective sample treatments and spectral processing for an alternate method of soil nitrate determination using the attenuated total reflectance (ATR) of Fourier transform infrared (FTIR) spectroscopy. Prior to FTIR measurements, soil samples were prepared as paste to enhance adhesion between the ATR crystal and sample. The similar nitrate peak heights of soil pastes and their supernatants indicated that the nitrate in the liquid portion of the soil paste mainly responded to the FTIR signal. Using a 0.01-M CaSO4 solution for the soil paste, which has no interference bands in the characteristic spectra of the analyte, increased the concentration of the nitrates to be measured. Second-order derivatives were used in the prediction model to minimize the interference effects and enhance the performance. The second-order derivative spectra contained a unique nitrate peak in a range of 1,400–1,200 cm?1 without interference of carbonate. A partial least square regression model using second-order derivative spectra performed well (R 2?=?0.995, root mean square error (RMSE)?=?23.5, ratio of prediction to deviation (RPD)?=?13.8) on laboratory samples. Prediction results were also good for a test set of agricultural field soils with a CaCO3 concentration of 6% to 8% (R 2?=?0.97, RMSE?=?18.6, RPD?=?3.5). Application of the prediction model based on soil paste samples to nitrate stock solution resulted in an increased RMSE (62.3); however, validation measures were still satisfactory (R 2?=?0.99, RPD?=?3.0).
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