Comparison of Derivative Preprocessing and Automated Polynomial Baseline Correction Method for Classification and Quantification of Narcotics in Solid Mixtures

This work offers a real-world comparison of derivative preprocessing and a new polynomial method described by Lieber and Mahadevan-Jansen (LMJ) for baseline correction of Raman spectra with widely varying backgrounds. This comparison is based on their outcomes in factor analysis, analyte discrimination, and quantification. Both correction methods are applied to a Raman spectra data set taken from 85 solid samples of illegal narcotics diluted with various materials. It is found that neither approach outperforms the other, as they give similar principal component analysis (PCA) models and quantification errors: cocaine and heroin show cross-validation errors of approximately 8%, while MDMA is quantified to a cross-validation error of approximately 3–4%. The LMJ method does offer several other advantages, the most significant being the retention of original peak shapes after the correction, which simplifies the interpretation of the preprocessed spectra. The LMJ method is therefore recommended for use as a baseline correction method in future research with Raman spectroscopy.

[1]  Alan G. Ryder,et al.  Classification of narcotics in solid mixtures using principal component analysis and Raman spectroscopy. , 2002, Journal of forensic sciences.

[2]  Pavel Matousek,et al.  Fluorescence background suppression in Raman spectroscopy using combined Kerr gated and shifted excitation Raman difference techniques , 2002 .

[3]  A. Mahadevan-Jansen,et al.  Automated Method for Subtraction of Fluorescence from Biological Raman Spectra , 2003, Applied spectroscopy.

[4]  A Jirasek,et al.  Accuracy and Precision of Manual Baseline Determination , 2004, Applied spectroscopy.

[5]  Richard A. Mathies,et al.  Effective Rejection of Fluorescence Interference in Raman Spectroscopy Using a Shifted Excitation Difference Technique , 1992 .

[6]  Ian R Lewis,et al.  Anti-Stokes Raman Spectrometry with 1064-nm Excitation: An Effective Instrumental Approach for Field Detection of Explosives , 2004, Applied spectroscopy.

[7]  William F. Finney,et al.  Subsurface Probing in Diffusely Scattering Media Using Spatially Offset Raman Spectroscopy , 2005, Applied spectroscopy.

[8]  Richard G. Brereton,et al.  Introduction to multivariate calibration in analytical chemistry , 2000 .

[9]  S. Lieberman,et al.  Fluorescence Rejection in Raman Spectroscopy by Shifted-Spectra, Edge Detection, and FFT Filtering Techniques , 1995 .

[10]  Wolfgang Petrich,et al.  Quantitative analysis of serum and serum ultrafiltrate by means of Raman spectroscopy. , 2004, The Analyst.

[11]  P. Geladi,et al.  Linearization and Scatter-Correction for Near-Infrared Reflectance Spectra of Meat , 1985 .

[12]  T. Vickers,et al.  Curve Fitting and Linearity: Data Processing in Raman Spectroscopy , 2001 .

[13]  J. Westerhuis,et al.  Quantitative Raman reaction monitoring using the solvent as internal standard. , 2005, Analytical chemistry.

[14]  Peter D. Wentzell,et al.  Hazards of digital smoothing filters as a preprocessing tool in multivariate calibration , 1999 .

[15]  Age K. Smilde,et al.  Direct orthogonal signal correction , 2001 .

[16]  Vincent Mazet,et al.  Background removal from spectra by designing and minimising a non-quadratic cost function , 2005 .

[17]  S. Bell,et al.  Composition profiling of seized ecstasy tablets by Raman spectroscopy. , 2000, The Analyst.

[18]  Steven D. Brown,et al.  Wavelet analysis applied to removing non‐constant, varying spectroscopic background in multivariate calibration , 2002 .

[19]  Gerard M. O'Connor,et al.  Identifications and quantitative measurements of narcotics in solid mixtures using near-IR Raman spectroscopy and multivariate analysis , 1999 .

[20]  David N. Batchelder,et al.  Use of a Fiber Optic Probe for the Detection and Identification of Explosive Materials by Raman Spectroscopy , 1995 .

[21]  S. Bell,et al.  Quantitative Raman spectroscopy of highly fluorescent samples using pseudosecond derivatives and multivariate analysis. , 2001, Analytical chemistry.

[22]  S. Bell,et al.  Rapid analysis of ecstasy and related phenethylamines in seized tablets by Raman spectroscopy. , 2000, The Analyst.

[23]  Neil J. Everall,et al.  Density Mapping in Poly(Ethylene Terephthalate) Using a Fiber-Coupled Raman Microprobe and Partial Least-Squares Calibration , 1996 .

[24]  E. V. Thomas,et al.  Partial least-squares methods for spectral analyses. 1. Relation to other quantitative calibration methods and the extraction of qualitative information , 1988 .

[25]  Steven E. J. Bell,et al.  Analysis of luminescent samples using subtracted shifted Raman spectroscopy , 1998 .

[26]  Christopher D. Brown,et al.  Derivative Preprocessing and Optimal Corrections for Baseline Drift in Multivariate Calibration , 2000 .

[27]  M. Pelletier,et al.  Quantitative Analysis Using Raman Spectrometry , 2003, Applied spectroscopy.

[28]  Andrew Jirasek,et al.  Investigation of Selected Baseline Removal Techniques as Candidates for Automated Implementation , 2005, Applied spectroscopy.

[29]  S. Bell,et al.  Identification of dyes on ancient Chinese paper samples using the subtracted shifted Raman spectroscopy method. , 2000, Analytical chemistry.