SYSTEMATIC METHODOLOGY FOR THE DESIGN OF BINARY SOLVENT BLENDS FOR EXTRACTION OF HERBAL PHYTOCHEMICALS WITH COST EVALUATION

Abstract

The trial and error solvent selection method to obtain herbal phytochemicals is time consuming and limited by effort and cost. The combination of property prediction models with computer-assisted search is one way to overcome these drawbacks. Thus, the main objective of this work is to present a computer-aided methodology for the design of solvent blends in extracting herb phytochemicals optimally with cost evaluation. The methodology can be summarised into two main stages, namely, model-based design and experimental-verification stages. The result discussed in this paper is only for the first stage. The extraction of kaempferol from Kacip Fatimah herb is used as a base case study that follows all of the listed tasks. Five optimal binary solvent blends have been identified namely, methanol:isobutyraldehyde (M:IB), methanol:n-propionaldehyde (M:PP), methanol:water (M:W), methanol: ethyl acetate (M:EA) and methanol: acetic acid (M:AA). The M:IB solvent blend is able to extract the highest kaempferol yield while M:PP gives the highest profit.