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ARS Home » Northeast Area » Beltsville, Maryland (BHNRC) » Beltsville Human Nutrition Research Center » Food Composition and Methods Development Laboratory » Research » Publications at this Location » Publication #226469

Title: UV, IR, NIR, Direct Injection MS Spectral Fingerprinting, and Analysis of Variance-Principal Component Analysis: Tools for Categorization of Food Materials Grown in a Different Environment

item Luthria, Devanand - Dave

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 4/29/2008
Publication Date: 8/9/2008
Citation: Luthria, D.L. 2008. Uv, ir, nir, direct injection ms spectral fingerprinting, and analysis of variance-principal component analysis: tools for categorization of food materials grown in a different environment. University of Delhi, June 2-7, 2008, Mumbai, India, Khon Kaen University, August 9-15, 2008, Khon Kaen, Thailand.

Interpretive Summary:

Technical Abstract: Genetics and environmental conditions (such as rainfall, pests, soil, irrigation levels, and fertilization) will lead to chemical differences in plant materials. Simple and inexpensive spectral fingerprinting (UV, IR, NIR, and Direct MS) methods are described that allow differentiation of plant material based on the overall chemical composition. Spectral fingerprints, in combination with analysis of variance-principal components analysis (ANOVA-PCA), were used to identify sources of variance in seven broccoli samples composed of two cultivars and seven different growing conditions (four levels of selenium irrigation, organic farming, and conventional farming with full and 80% irrigation). Freeze-dried powdered broccoli samples were extracted with methanol-water (60:40, v/v) and the extracts were analyzed by different spectral methods with no prior chromatographic separation. ANOVA-PCA was used to construct subset matrices that permitted easy testing of the hypotheses that cultivar and treatment contributed to a difference in the chemical expression of the broccoli. The sums of the squares of the same matrices were used to show the relative variance due to cultivar, treatment, and analytical repeatability. This method allows the rapid and inexpensive testing of plant materials to determine if there are chemical differences introduced by the cultivar, the growing conditions, or the processing conditions.