Analyses of replicated spectrophotometric data by using soft computing methods
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ORIGINAL PAPER
Analyses of replicated spectrophotometric data by using soft computing methods Özlem Türkşen1 · Nilüfer Vural2 Received: 28 January 2020 / Accepted: 27 May 2020 © Iranian Chemical Society 2020
Abstract Soft computing based chemometric studies are needed to model and to optimize complex processes, such as the extraction stage. In this study, it was aimed to obtain optimal values of ethanol (EtOH) concentration, extraction time, extraction temperature, solvent/solid ratio for the ultrasound-assisted extraction (UAE) of grape seed polyphenols to maximize the total phenolic content (TPC) and total antioxidant activity (TAA) in multi-objective perspective by using soft computing methods. The experimental data set was composed with replicated response measures to see the behavior of the responses. The replicated response measured (RRM) data was recently modeled by using fuzzy linear regression in which the replicated responses were considered as triangular linear fuzzy numbers (TLFNs). Also, polynomial type fuzzy linear regression model parameters were dealt as TLFNs whereas the experiment conditions were crisp. The predicted fuzzy linear models were obtained by using least square (LS) approach. The predicted fuzzy models were optimized through the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Pareto set was obtained. The obtained Pareto solution set was experimentally verified. A compromise solution was chosen among many non-dominated solutions of experimental conditions by using a distance function based on root mean square of fuzzy errors. According to the results, it is possible to say that the proposed soft computing based modeling and multi-objective optimization (MOO) approaches can be used as flexible analyses tools in chemometry. Keywords Replicated response measures · Triangular linear fuzzy number (TLFN) · Fuzzy linear modeling · NSGA-II · Grape seed polyphenolics Abbreviations CCD Central composite design DPPH 2,2-Diphenyl-2-picryl-hydrazyl EtOH Ethanol GA Genetic Algorithm GAE Gallic acid equivalents H2O Water Inh Inhibition LM Levenberg–Marquardt LS Least square MeOH Methanol MOGAs Multi-objective genetic algorithms MOO Multi-objective optimization * Nilüfer Vural [email protected]; [email protected] 1
Statistics Department, Faculty of Science, Ankara University, Ankara, Turkey
Chemical Engineering Department, Faculty of Engineering, Ankara University, Ankara, Turkey
2
NSGA Non-dominated Sorting Genetic Algorithm NSGA-II Non-dominated Sorting Genetic Algorithm-II RRM Replicated response measured RSM Response surface methodology TAA Total antioxidant activity TLFNs Triangular linear fuzzy numbers TPC Total phenolic content UAE Ultrasound-assisted extraction UV–VIS Ultraviolet–visible Spectrophotometer
Introduction Plants are rich sources of biologically active compounds such as polyphenolics, flavanoids, alkaloids and terpenes. In recent studies, these bioactive compounds appear to be responsible for multifunctional biological effec
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