Title: Spectral Fingerprinting and Analysis of Variance-Principal Component Analysis: A Tool for Classifying Variance in Plant Materials Authors
Submitted to: International Conference of Polyphenols
Publication Type: Abstract Only
Publication Acceptance Date: February 5, 2008
Publication Date: July 8, 2008
Citation: Luthria, D.L., Harnly, J.M. 2008. Spectral Fingerprinting and Analysis of Variance-Principal Component Analysis: A Tool for Classifying Variance in Plant Materials. XXIV International Conference on Polyphenols, July 8-11, 2008, Salamanca, Spain. Technical Abstract: Genetics and a variety of environmental factors (such as rainfall, pests, soil, irrigation levels, and fertilization) can lead to chemical differences in the same plant materials. A simple and inexpensive spectral fingerprinting (UV, IR, NIR, and Direct MS) method is described that allows classification of plant material based on the overall chemical composition. Spectral fingerprints (UV, IR, NIR, and Direct MS), 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 or 80% irrigation). Freeze-dried powdered samples were extracted with methanol-water (60:40, v/v) and analyzed with no prior separation. Spectral fingerprints were acquired by UV, IR, NIR, and Direct MS. ANOVA-PCA was used to construct subset matrices that permitted easy testing of the hypothesis 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 percentage of variance due to cultivar, treatment, and analytical repeatability. Fingerprinting will allow 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.