Statistical modeling and optimization of classical and ultrasound-assisted extraction of the minerals fromGalium mollugoL. by response surface methodology and genetic algorithm

Abstract

Ultrasound-assisted and classical extractions of the minerals from Galium mollugo L. by an aqueous ethanol solution at different temperatures were investigated. The study was aimed at examining the effects of extraction temperature and time on both extraction yield and selectivity of K, Ca, and Mg and determining the best extraction conditions using response surface methodology alone and coupled with genetic algorithm. Both extraction temperature and time affect the extraction yield significantly. Lower maximum mineral yields were obtained by classical extraction within longer time and at higher temperatures, compared to ultrasound-assisted extraction. Ultrasound and temperature increased the mineral yield but reduced the mineral extraction selectivity. Practical applications The optimization of extraction processes is commonly connected to organic compounds and very rarely to mineral matters despite their important role in many reactions in living organisms. The use of extracts with their augmented contents of minerals can be more effective in many cases, compared to the use of the origin plant material. White lady's bedstraw (Galium mollugo) has already proved to contain several minerals like K, Ca, and Mg. Since ultrasound and temperature increased the mineral yield but reduced the mineral extraction selectivity, the optimization of the extractions of the minerals will improve the techno-economics of the potential commercial preparation from this plant.