Detection of Low Volatility Organic Analytes on Soils Using Infrared Reflection Spectroscopy

Abstract

Previous work on the detection of low-volatility liquid organic (and organophosphorus) analytes on soil indicated a strong signal in Fourier transform infrared spectra in the 2966–2855 cm−1 range attributed to C-H vibrational stretching modes. This range is the focus of detection strategies examined here as an anticipated prelude to subsequent detection and classification approaches utilising additional spectral bands. This laboratory study is being used to test detection algorithms that may be useful for rapid stand-off detection of organic compounds on soil. Six signal processing methods (designed to minimise irrelevant variability in the recorded soil reflection spectra while enhancing signal from analyte compounds possibly present on soil) were studied. These included Savitzky-Golay second derivatives, extended multiplicative scatter correction (EMSC) and a novel alternative to piece-wise EMSC. The pre-processed signal was then used for detection. Previous work utilised principal components analysis (PCA)-based multivariate statistical process control methodologies for detection. Six alternative anomaly detection statistics were examined here that were based on the pre-processed signal, weighted signal and generalised weighted signal. The latter statistic can be considered easier than PCA with many of the same benefits. Two tests corresponding to different monitoring strategies were examined: test data “local” and “non-local” to the calibration data. Although the results are expected to be optimistic, the generalised weighted approach worked extremely well for the “local” detection test, but was less successful for the “non-local” test. Results suggest that good characterisation of analyte-free soil prior to monitoring will lead to the best detection performance. Second derivative pre-processing showed the best results on receiver operator characteristic curves and its ease of application is a distinct advantage. However, it may not be universally successful for all bands to be considered in the future. Both EMSC and the novel “piece-wise” EMSC methodology showed promise, but some improvements may be necessary.