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A Comparison of Analytical and Data Preprocessing Methods for Spectral Fingerprinting

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Abstract:

Spectral fingerprinting, as a method of discriminating between plant cultivars and growing treatments for a common set of broccoli samples, was compared for six analytical instruments. Spectra were acquired for finely powdered solid samples using Fourier transform infrared (FT-IR) and Fourier transform near-infrared (NIR) spectrometry. Spectra were also acquired for unfractionated aqueous methanol extracts of the powders using molecular absorption in the ultraviolet (UV) and visible (VIS) regions and mass spectrometry with negative (MS−) and positive (MS+) ionization. The spectra were analyzed using nested one-way analysis of variance (ANOVA) and principal component analysis (PCA) to statistically evaluate the quality of discrimination. All six methods showed statistically significant differences between the cultivars and treatments. The significance of the statistical tests was improved by the judicious selection of spectral regions (IR and NIR), masses (MS+ and MS−), and derivatives (IR, NIR, UV, and VIS).

Keywords: ANALYSIS OF VARIANCE; ANOVA; ANOVA-PCA; BROCCOLI; CLASSIFICATION; DIRECT MASS SPECTROMETRY; DISCRIMINATION; GROWING CONDITIONS; NEAR-INFRARED SPECTROSCOPY; NIR SPECTROSCOPY; PCA; PRINCIPAL COMPONENT ANALYSIS; SPECTRAL FINGERPRINTING; ULTRAVIOLET-VISIBLE SPECTROSCOPY; UV-VIS SPECTROSCOPY

Document Type: Research Article

DOI: http://dx.doi.org/10.1366/10-06109

Affiliations: Food Composition and Methods Development Laboratory, Beltsville Human Nutrition Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, Maryland 20705-3000, USA

Publication date: March 1, 2011

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