Literature DB >> 15165326

Fourier transform infrared-attenuated total reflection nitrate determination of soil pastes using principal component regression, partial least squares, and cross-correlation.

Raphael Linker1, Amit Kenny, Avi Shaviv, Liviu Singher, Itzhak Shmulevich.   

Abstract

This paper investigates the use of Fourier transform infrared (FTIR) attenuated total reflectance (ATR) spectroscopy as a fast and simple way for direct determination of nitrate concentration in soil pastes, which would assist precision fertilizer placement and reduce nitrate pollution. Eight types of soils are investigated, with nitrate concentrations ranging from 0 to 1000 ppm-N. The spectral region around the nitrate band (1300-1550 cm(-1)) is analyzed by (1) principal component regression (PCR), (2) partial least squares (PLS), and (3) cross-correlation with reference libraries that include spectra of pure ions and/or soils. The main obstacle to accurate nitrate measurement appears to be an interfering band present in calcareous soils. This band, which may be due to carbonate, is located around 1450 cm(-1) and overlaps with the nitrate band centered around 1370 cm(-1). For non-calcareous soils, and in particular for light sandy agricultural soils, PLS and cross-correlation with a reference library containing only spectra of ions in water give similar results (about 8 ppm-N on dry soil basis), while PCR leads to slightly poorer results. When calcareous soils are included in the analysis, the prediction errors are about twice as large. In this case, the best results are obtained using PLS, followed by PCR, while cross-correlation with reference libraries leads to poorer results.

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Year:  2004        PMID: 15165326     DOI: 10.1366/000370204774103327

Source DB:  PubMed          Journal:  Appl Spectrosc        ISSN: 0003-7028            Impact factor:   2.388


  1 in total

1.  Predictions of soil organic carbon using laboratory-based hyperspectral data in the northern Tianshan mountains, China.

Authors:  Hongfei Yang; Jianlong Li
Journal:  Environ Monit Assess       Date:  2012-09-01       Impact factor: 2.513

  1 in total

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