Comparison of Principal Component Analysis and Generalized Two-Dimensional Correlation Spectroscopy: Spectral Analysis of Synthetic Model System and Near-Infrared Spectra of Milk

Principal component analysis (PCA) and generalized two-dimensional (2D) correlation spectroscopy have been applied to a two-component spectral model made up of highly overlapped bands and to near-infrared (NIR) spectra of milk. The analyses were made on mean-normalized and mean-centered data of the model. The dynamic loading of PCA is expanded into 2D contour by calculating a variance-covariance matrix. This 2D pattern is compared with a synchronous 2D spectrum calculated by generalized 2D correlation spectroscopy, and a high degree of similarity is discernible between the two kinds of 2D spectra. The one-dimensional (1D) features of the synchronous 2D map, slice spectra, are identical to the dynamic loading as well. We show that, for noncentered data of the model system, only in limited cases can the correlation between the first loadings and synchronous map be established. PCA of the milk spectra yields two factors. The 2D representation of the most important loading is significantly different from the synchronous spectrum calculated by the generalized 2D approach. The slice spectra from which the synchronous spectrum is made are found to be mutually different as one moves along the variable axis. A synchronous 2D map emphasizes only variables with the highest correlation of the spectral intensity changes. On the other hand, PCA is geometrically oriented; thus, as the complexity of the data increases, the differences between PCA and generalized 2D correlation spectroscopy become striking. The selectivity of the asynchronous 2D map is demonstrated for the bands due to milk fat.

[1]  H. Siesler,et al.  2D FT-NIR and FT-IR correlation analysis of temperature-induced changes of nylon12 , 1998 .

[2]  Y. Ozaki,et al.  Two-Dimensional Fourier Transform Raman Correlation Spectroscopy Studies of Polymer Blends: Conformational Changes and Specific Interactions in Blends of Atactic Polystyrene and Poly(2,6-dimethyl-1,4-phenylene ether) , 1999 .

[3]  Isao Noda,et al.  Two-Dimensional Infrared (2D IR) Spectroscopy: Theory and Applications , 1990 .

[4]  Yukihiro Ozaki,et al.  Analysis of Near-Infrared Spectra of Complicated Biological Fluids by Two-Dimensional Correlation Spectroscopy: Protein and Fat Concentration-Dependent Spectral Changes of Milk , 1999 .

[5]  B. Eichinger,et al.  Determination of Crystallinity and Morphology of Fibrous and Bulk Poly(ethylene terephthalate) by Near-Infrared Diffuse Reflectance Spectroscopy , 1990 .

[6]  A. Boskey,et al.  Two‐dimensional infrared correlation spectroscopy of synthetic and biological apatites , 1998 .

[7]  J. J. Andrew,et al.  Rapid Analysis of Raman Image Data Using Two-Way Multivariate Curve Resolution , 1998 .

[8]  Paul Geladi,et al.  Principal Component Analysis , 1987, Comprehensive Chemometrics.

[9]  H. Mantsch,et al.  Two-dimensional mid-IR and near-IR correlation spectra of ribonuclease A: using overtones and combination modes to monitor changes in secondary structure. , 1998, Biospectroscopy.

[10]  Yizeng Liang,et al.  Associative Behavior of Benzyl Alcohol in Carbon Tetrachloride Solutions , 1997 .

[11]  M. A. Czarnecki.  Two-Dimensional Correlation Spectroscopy: Effect of Normalization of the Dynamic Spectra , 1999 .

[12]  O. M. Kvalheim.  Interpretation of direct latent-variable projection methods and their aims and use in the analysis of multicomponent spectroscopic and chromatographic data , 1988 .

[13]  K. Heremans,et al.  2D FT-IR spectroscopy analysis of the pressure-induced changes in proteins , 1999 .

[14]  Y. Ozaki,et al.  Comparison between Conventional Spectral Analysis Methods, Chemometrics, and Two-Dimensional Correlation Spectroscopy in the Analysis of Near-Infrared Spectra of Protein , 2000 .

[15]  M. Pézolet,et al.  Two-Dimensional FT-IR Spectroscopy: A Powerful Method to Study the Secondary Structure of Proteins Using H-D Exchange , 1997 .

[16]  Chris W. Brown,et al.  Chemical information based on neural network processing of near-IR spectra , 1998 .

[17]  H. Richardson,et al.  Two-Dimensional FT-IR Correlation Analysis of the Chemisorption of Nitric Oxide on Pt(100) , 1999 .

[18]  Yukihiro Ozaki,et al.  Band Assignment of Near-Infrared Spectra of Milk by Use of Partial Least-Squares Regression , 2000 .

[19]  I. Noda.  Generalized Two-Dimensional Correlation Method Applicable to Infrared, Raman, and other Types of Spectroscopy , 1993 .

[20]  S. Šašić,et al.  RAMAN SPECTROSCOPIC STUDY OF ACETONE-PHENOL MIXTURES , 1998 .

[21]  Y. Ozaki,et al.  Two-Dimensional Correlation Spectroscopy Study of Temperature-Dependent Spectral Variations of N-Methylacetamide in the Pure Liquid State. 1. Two-Dimensional Infrared Analysis , 1996 .

[22]  T. Hasegawa.  Detection of minute chemical species by principal-component analysis. , 1999, Analytical chemistry.

[23]  Y. Ozaki,et al.  Two-Dimensional Fourier Transform Near-Infrared Spectroscopy Study of Heat Denaturation of Ovalbumin in Aqueous Solutions , 1998 .

[24]  Evaluation techniques for two-way data from in situ fourier transform mid-infrared reaction monitoring in aqueous solution. , 1998, Analytical chemistry.

[25]  M. Masson.  Factor Analysis in Chemistry : E. R. Malinowski and D. G. Howery, Wiley-Interscience, New York, 1980. Pp. ix + 251. £19.35. , 1981 .

[26]  Y. Ozaki,et al.  Two-Dimensional Fourier Transform Near-Infrared Correlation Spectroscopy Studies of Temperature-Dependent Spectral Variations of Oleyl Alcohol , 1995 .

[27]  I. Noda,et al.  Determination of Two-Dimensional Correlation Spectra Using the Hilbert Transform , 2000 .

[28]  M. Watari,et al.  Fourier Transform Raman Spectra of Linear Low-Density Polyethylene and Prediction of Their Density by Multivariate Data Analysis , 1999 .