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2013, vol. 67, br. 2, str. 249-259
Optimizacija ekstrakcije ukupnih flavonoida iz Camellia sinensis primenom veštačke neuronske mreže i metodologije površinskog odgovora
aUniverzitet u Nišu, Tehnološki fakultet, Leskovac
bUniversity of Natural Resources and Life Sciences, Institute of Applied Statistics and Computing, Center of Experimental Design, Vienna, Austria

e-adresaici_teh@yahoo.com
Projekat:
Biljni i sintetički bioaktivni proizvodi novije generacije (MPNTR - 34012)

Ključne reči: Veštačka neuronska mreža; Metodologija površine odgovora; Ekstrakcija; Ukupni flavonoidi; Camelia sinensis
Sažetak
Poznato je da slobodni radikali deluju vrlo nepovoljno na čovekov organizam, oštećujući ćelije tkiva i organa dovodeći do degenerativnih oboljenja i raznih oblika raka. Utvrđeno je da su polifenoli nekih biljaka jaki antioksidansi, a za zeleni čaj potvrđeno je da ima najveću količinu polifenola (300-400 mg). Zbog visoke koncentracije polifenola i flavonoida (5-27%), zeleni čaj se koristi kod infekcija, prehlada smanjujući oštećenja ćelija pod dejstvom virusa. Upotrebom zelenog čaja sprečava se razvoj malignih ćelija, a redovno konzumiranje je povezano sa smanjenom incidencom razvoja raka jajnika, jednjaka, mokraćne bešike, pluća, pankreasa, prostate i kože. Takođe, sprečava razvoj ateroskleroze i srčanih oboljenja, ubrzava metabolizam i sagorevanje masti. Snižava nivo holesterola, pa se primenjuje i kod povećanog nivoa holesterola u krvi. Cilj ovog rada bio je modelovanje i optimizacija procesa ekstrakcije ukupnih flavonoida iz zelenog čaja (Camellia sinensis) primenom veštačke neuronske mreže (eng. artificial neural network, ANN) i metodologije površine odgovora (eng. response surface methodology, RSM), kao i poređenje ovih optimizacionih tehnika. Vreme ekstrakcije, koncentracija etanola i solvomodul posmatrani su kao nezavisno promenljive, dok je prinos ukupnih flavonoida odabran kao zavisno promenljiva. Centralni kompozitni dizajn (eng. central composite design, CCD), primenom polinomnog modela drugog reda i višeslojni perceptron korišćeni su za fitovanje dobijenih eksperimentalnih podataka. Vrednosti RMS, Q2 i r2 za optimizacione modele ukazuju da je model "višeslojnog filtiriranja" (eng. multilayer perceptron, MLP) bolji za predviđanje prinosa ukupnih flavonoida od CCD modela. Kod CCD modela, primenom "poželjne" (eng. desirability) funkcije, optimalni uslovi ekstrakcije ukupnih flavonoida postignuti su pri vremenu ekstrakcije od 32,5 min, koncentraciji etanola od 100% (v/v) i solvomodulu od 1:32,5 (m/v). Pri datim uslovima, predviđeni prinos ukupnih flavonoida je 2,11 g/100 g suvog ostatka (s.o.), dok je eksperimentalno dobijena vrednost od 2,39 g/100 g s.o. Proces ekstrakcije optimizovan je primenom simpleks algoritma kod MLP modela. Po ovom modelu optimalni uslovi ekstrakcije ukupnih flavonoida iz zelenog čaja postižu se za vreme ekstrakcije od 27,2 min, pri koncentraciji etanola od 100% (v/v) i solvomodulu od 1:20,7 (m/v). Pri ovim optimalnim uslovima ekstrakcije, predviđena vrednost prinosa ukupnih flavonoida (2,80 g/100 g s.o.) potvrđena je eksperimentalno (2,71 g/100 g s.o.).
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O članku

jezik rada: engleski
vrsta rada: naučni članak
DOI: 10.2298/HEMIND120313066S
objavljen u SCIndeksu: 02.09.2013.