Extract-Template Modeling and Pattern Recognition in the Assessment of (Cymbopogon Proximus)
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Abstract
Comprehensive analytical methodologies are exceedingly needed in order to evaluate product quality and raw material specifications especially for botanical preparations. Advances in teaming up statistical (PCA, CA & pattern recognition techniques) and spectroscopic (UV, IR, MS & NMR) methods of analysis have generated a substantial impact on how to use spectroscopic instruments as intelligent modules capable of identifying and classifying the composition of a variety of natural products. Cymbopogon proximus, a traditionally used medicinal herb claimed to be an effective remedy for renal spasms, lacks appropriate evaluation procedures. UV assisted-PCA and PLS analysis were exercised herein to maximize the usefulness and applicability of some previously established analytical specifications for herbal materials (e.g. solvent extractive values). Hierarchical cluster analysis was also attempted to categorize and associate the generated solvent-extracts. In addition, DE-TLC and GC were used to examine the different plant fractions in a qualitative and quantitative manner.
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