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A Brief Understanding of Process Optimisation in Microwave‐assisted Extraction of Botanical Materials: Options and Opportunities with Chemometric Tools
Author(s) -
Das Anup Kumar,
Mandal Vivekananda,
Mandal Subhash C.
Publication year - 2013
Publication title -
phytochemical analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 72
eISSN - 1099-1565
pISSN - 0958-0344
DOI - 10.1002/pca.2465
Subject(s) - chemometrics , extraction (chemistry) , process (computing) , biochemical engineering , data extraction , management science , computer science , process engineering , chemistry , machine learning , chromatography , engineering , biochemistry , medline , operating system
ABSTRACT Introduction Extraction forms the very basic step in research on natural products for drug discovery. A poorly optimised and planned extraction methodology can jeopardise the entire mission. Objective To provide a vivid picture of different chemometric tools and planning for process optimisation and method development in extraction of botanical material, with emphasis on microwave‐assisted extraction (MAE) of botanical material. Methods A review of studies involving the application of chemometric tools in combination with MAE of botanical materials was undertaken in order to discover what the significant extraction factors were. Optimising a response by fine‐tuning those factors, experimental design or statistical design of experiment (DoE), which is a core area of study in chemometrics, was then used for statistical analysis and interpretations. Results In this review a brief explanation of the different aspects and methodologies related to MAE of botanical materials that were subjected to experimental design, along with some general chemometric tools and the steps involved in the practice of MAE, are presented. A detailed study on various factors and responses involved in the optimisation is also presented. Conclusion This article will assist in obtaining a better insight into the chemometric strategies of process optimisation and method development, which will in turn improve the decision‐making process in selecting influential extraction parameters. Copyright © 2013 John Wiley & Sons, Ltd.