Application of multivariate curve resolution alternating least square (MCR-ALS) to the study of trikarshika formulation
Abstract
Objective: Multivariate curve resolution method (MCR) is one of the tools designated to unravel the pure component mathematically. The information was extracted through alternative least square algorithm from Trikarshika (TK) formulation. This paper presents the importance of MCR technique in the computation of mathematical component in the form of extract (TKChurna) itself.
Methods: The methanolic macerated extracts of the drugs i.e. Zingiber officinale Rose., Aconitum heterophyllum Wall. and Cyperus rotundas Linn, processed with standard operating procedure and prepared twenty-five mixtures to blend in three concentration levels among the individual simultaneously. The finished mixture annotated with code numbers and considered as an individual sample. The samples were subjected to ultra violet –visible (UV-VIS) UV-VIS spectral detection from 220 to 780 nm at the interval of 10 nm. The data were analyses with the help of The Unscrambler software.
Results: Seven components were computed from TK mixture extracts using concentration as a factor. The correlation between estimated and reference concentration for the Zingiber officinale Rose. was 0.91, this indicates good predictability of Zingiber officinale Rose in comparison to other two ingredients. Several spectral overlap existed only generated the use of absorbance resolved spectra that open up the scope of mixture analysis based on experimental data only.
Conclusion: MCR technique may be a good tool that can be adopted for the discrimination of variables like exposes of discrete light, seasonal differences in the collection, and differences in harvesting schedules. The discrimination of MCR technique is based on ALS algorithm.
Keywords: Trikarshika, Multivariate curve resolution, UV-Vis spectroscopy, Unscrambler Camo Software
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References
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