Abstract
Univariate and multivariate statistics were applied to characterize cured bright tobacco samples on the basis of their 13C CPMAS NMR spectra and leaf constituent analysis. NMR spectra were obtained for 55 samples selected from a set of 134 samples of graded bright tobacco leaves from crop year 1999. Historical leaf constituent analyses were available for total alkaloids, reducing sugars, total nitrogen, and insoluble ash. In addition, we applied HPLC to quantify the two abundant plant polyphenols, chlorogenic acid, and rutin. Principal component analysis (PCA) and partial least squares (PLS) of the NMR spectra revealed systematic relationships between groups of samples related to these substances and afforded predictive quantitative models for the analyzed constituents. Analysis of the PLS significant variables showed that leaf polysaccharides, alkaloids, and minerals are major determinants influencing the grading of cured bright tobacco leaves.
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