Abstract
The use of multiple calibration sets in partial least squares (PLS) regression
was proposed to improve the quantitative determination of NH<sub>3</sub> over wide
concentration ranges from open-path Fourier transform infrared (OP/FT-IR) spectra.
The spectra were measured near animal farms, where the path-integrated concentration
of NH<sub>3</sub> can fluctuate from nearly zero to as high as approximately 1000
ppm-m. PLS regression with a single calibration set did not cover such a large
concentration range effectively, and the quantitative accuracy was degraded due to
the nonlinear relationship between concentration and absorbance for spectra measured
at low resolution (1 cm<sup>–1</sup> and poorer.) In PLS regression with multiple
calibration sets, each calibration set covers a part of the entire concentration
range, which significantly decreases the serious nonlinearity problem in PLS
regression occurring when only a single calibration set is used. The relative error
was reduced from approximately 6% to below 2%, and the best results were obtained
with four calibration sets, each covering one quarter of the entire concentration
range. It was also found that it was possible to build the multiple calibration sets
easily and efficiently without extra measurements.
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