A Comparison of Analytical and Data Preprocessing Methods for Spectral Fingerprinting

被引:17
|
作者
Luthria, Devanand L. [1 ]
Mukhopadhyay, Sudarsan [1 ]
Lin, Long-Ze [1 ]
Harnly, James M. [1 ]
机构
[1] ARS, Food Composit & Methods Dev Lab, Beltsville Human Nutr Res Ctr, USDA, Beltsville, MD 20705 USA
基金
美国国家卫生研究院;
关键词
Spectral fingerprinting; Near-infrared spectroscopy; NIR spectroscopy; Ultraviolet-visible spectroscopy; UV-Vis spectroscopy; Direct mass spectrometry; Classification; Discrimination; Broccoli; Growing conditions; Analysis of variance; ANOVA; Principal component analysis; PCA; ANOVA-PCA; PRINCIPAL COMPONENT ANALYSIS; MASS-SPECTROMETRY; PLANT-EXTRACTS; VARIANCE; BROCCOLI; SELENIUM; TOOL;
D O I
10.1366/10-06109
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
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).
引用
收藏
页码:250 / 259
页数:10
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