A fuzzy logic approach to modeling of the extraction process of bioactive compounds

Abstract

The aim of the present study was to optimize the extraction process of bioactive compounds from berries and wastes from the agro-food industry (grape marc). Mathematical models of the extraction process of biologically active compounds based on algorithms of artificial intelligence: fuzzy logic and neuro-fuzzy algorithms have been established. The mathematical models, which use the experimental average values of uncertain models, as well as of some predictive models, offer values of the sizes with a large prediction horizon. It was established, that mathematical models, which use the experimental average values of uncertain models, the experimental data, as well as of some predictive models offer values of the sizes with a large prediction horizon. The existence of various interactions between the influence factors (ethanol concentration, extraction temperature, pretreatment method) and the measured parameters (total polyphenol index, quantity of tannins extracted and antiradical activity, DPPH) was established. The great diversity of processes at different products and various parameters, as well as the existence of non-linear dependencies between sizes, allow credible extrapolations of the results only within the experimental limits.