Optimization of microwave-assisted extraction of total polyphenolic compounds from chokeberries by response surface methodology and artificial neural network

Abstract Response surface methodology (RSM) and artificial neural network (ANN) were used for modeling and optimizing microwave-assisted extraction (MAE) of total polyphenolic content (TPC) from chokeberries ( Aronia melanocarpa ) as a function of microwave power (300, 450 and 600 W), ethanol concentration (25%, 50% and 75%) and extraction time (5, 10 and 15 min). The set of the optimal operational conditions, as well as the conditions which gave the maximum yield of TPC while minimizing extraction time, solvent and energy consumption, (economic conditions), were proposed. Statistical indicators such as the coefficient of determination ( R 2 ), root-mean-square error (RMSE) and mean absolute error (MAE) demonstrated the superiority of the ANN. In order to scale-up a MAE procedure of chokeberries TPC from the laboratory to the industrial scale, the following set of conditions was proposed: an ethanol concentration of 53.6%, the microwave power of 300 W and the extraction time of 5 min corresponded to a TPC yield of 420.1 mg gallic acid equivalents (GAE)/100 g of fresh plant material.

[1]  Olivera S. Stamenković,et al.  Kinetic modeling and optimization of maceration and ultrasound-extraction of resinoid from the aerial parts of white lady's bedstraw (Galium mollugo L.). , 2013, Ultrasonics sonochemistry.

[2]  Parameswarakumar Mallikarjunan,et al.  Microwave-assisted extraction of phenolic antioxidant compounds from peanut skins , 2010 .

[3]  R. Chi,et al.  Optimization of ionic liquid-based microwave-assisted extraction of isoflavones from Radix puerariae by response surface methodology , 2014 .

[4]  S. Šiler-Marinković,et al.  Optimization of microwave-assisted extraction of natural antioxidants from spent espresso coffee grounds by response surface methodology , 2014 .

[5]  A. Kokotkiewicz,et al.  Aronia plants: a review of traditional use, biological activities, and perspectives for modern medicine. , 2010, Journal of medicinal food.

[6]  Jing Zhang,et al.  Study on the PEG-based microwave-assisted extraction of flavonoid compounds from persimmon leaves. , 2012, Journal of separation science.

[7]  Siddhartha Datta,et al.  Response surface optimization and artificial neural network modeling of microwave assisted natural dye extraction from pomegranate rind , 2012 .

[8]  M. Palma,et al.  Evaluation of various extraction techniques for obtaining bioactive extracts from pine seeds , 2010 .

[9]  Y. Ju,et al.  Effect of extraction solvent on total phenol content, total flavonoid content, and antioxidant activity of Limnophila aromatica , 2013, Journal of food and drug analysis.

[10]  Dennis K. Taylor,et al.  Microwave-assistance provides very rapid and efficient extraction of grape seed polyphenols. , 2011, Food chemistry.

[11]  S. Jafari,et al.  Microwave-assisted extraction of phenolic compounds from olive leaves; a comparison with maceration. , 2011 .

[12]  I. Nikov,et al.  Kinetics of ultrasound assisted extraction of anthocyanins from Aronia melanocarpa (black chokeberry) wastes , 2014 .

[13]  Olivera S. Stamenković,et al.  Optimization of hempseed oil extraction by n-hexane , 2013 .

[14]  J. Pincemail,et al.  Optimisation of extraction of phenolics and antioxidants from black currant leaves and buds and of stability during storage , 2007 .

[15]  G. Mazza,et al.  Optimisation of antioxidant activity of grape cane extracts using response surface methodology , 2010 .

[16]  M. D. Luque de Castro,et al.  Microwave-assisted extraction of phenolic compounds from wine lees and spray-drying of the extract , 2011 .

[17]  Khodir Madani,et al.  Optimization of microwave-assisted extraction of polyphenols from Myrtus communis L. leaves. , 2015, Food chemistry.

[18]  K. E. Malterud,et al.  Anthocyanins, proanthocyanidins and total phenolics in four cultivars of aronia: Antioxidant and enzyme inhibitory effects , 2014 .

[19]  P. Denev,et al.  Bioavailability and Antioxidant Activity of Black Chokeberry (Aronia melanocarpa) Polyphenols: in vitro and in vivo Evidences and Possible Mechanisms of Action: A Review , 2012 .

[20]  U. Farooq,et al.  Optimized microwave-assisted extraction of phenolic acids from citrus mandarin peels and evaluation of antioxidant activity in vitro , 2009 .

[21]  E. Mayer-Miebach,et al.  Stability of Chokeberry Bioactive Polyphenols during Juice Processing and Stabilization of a Polyphenol-Rich Material from the By-Product , 2012 .

[22]  Giorgia Spigno,et al.  Microwave-assisted extraction of tea phenols: A phenomenological study , 2009 .

[23]  Katarina M. Rajković,et al.  Optimization of ultrasound-assisted base-catalyzed methanolysis of sunflower oil using response surface and artifical neural network methodologies , 2013 .

[24]  Ajit Kumar Kolar,et al.  ANN-GA based optimization of a high ash coal-fired supercritical power plant , 2011 .

[25]  Eriola Betiku,et al.  Modeling and optimization of Thevetia peruviana (yellow oleander) oil biodiesel synthesis via Musa paradisiacal (plantain) peels as heterogeneous base catalyst: a case of artificial neural network vs. response surface methodology. , 2014 .

[26]  P. Denev,et al.  Solid-phase extraction of berries’ anthocyanins and evaluation of their antioxidative properties , 2010 .

[27]  Siddhartha Datta,et al.  Modeling of microwave-assisted extraction of natural dye from seeds of Bixa orellana (Annatto) using response surface methodology (RSM) and artificial neural network (ANN) , 2013 .

[28]  I. Nikov,et al.  Ultrasound assisted extraction of polyphenols from black chokeberry , 2012 .

[29]  Yun‐Hi Kim,et al.  Determination of chokeberry (Aronia melanocarpa) polyphenol components using liquid chromatography-tandem mass spectrometry: Overall contribution to antioxidant activity. , 2014, Food chemistry.

[30]  Yahong Yuan,et al.  Optimization of microwave-assisted extraction of polyphenols from apple pomace using response surface methodology and HPLC analysis. , 2010, Journal of separation science.

[31]  K. Rezaei,et al.  Solvent and solvent to sample ratio as main parameters in the microwave-assisted extraction of polyphenolic compounds from apple pomace , 2013, Food Science and Biotechnology.

[32]  Limin Li,et al.  Microwave-assisted extraction and antioxidant activity of total phenolic compounds from pomegranate peel , 2011 .

[33]  Hongyan Li,et al.  microwave-assisted extraction of phenolics with maximal antioxidant activities in tomatoes , 2012 .

[34]  A. Miron,et al.  The Involvement of a Polyphenol-Rich Extract of Black Chokeberry in Oxidative Stress on Experimental Arterial Hypertension , 2013, Evidence-based complementary and alternative medicine : eCAM.

[35]  V. L. Singleton,et al.  Colorimetry of Total Phenolics with Phosphomolybdic-Phosphotungstic Acid Reagents , 1965, American Journal of Enology and Viticulture.

[36]  V. Orsat,et al.  MAE of phenolic compounds from blueberry leaves and comparison with other extraction methods , 2014 .

[37]  M. Lazić,et al.  Optimization of microwave-assisted extraction and characterization of phenolic compounds in cherry laurel (Prunus laurocerasus) leaves , 2013 .

[38]  S. Kulling,et al.  Chokeberry (Aronia melanocarpa) – A Review on the Characteristic Components and Potential Health Effects , 2008, Planta medica.

[39]  C. Che,et al.  Microwave-assisted extraction of bioactive alkaloids from Stephania sinica , 2014 .

[40]  J. Kwon,et al.  Effect of ethanol concentration on the efficiency of extraction of ginseng saponins when using a microwave-assisted process (MAP™) , 2003 .

[41]  M. Šeruga,et al.  Phenolic acids, flavonols, anthocyanins and antiradical activity of „Nero“, „Viking“, „Galicianka“ and wild chokeberries , 2012 .

[42]  C. Cojocaru,et al.  Modeling and optimization of tartaric acid reactive extraction from aqueous solutions: A comparison between response surface methodology and artificial neural network , 2010 .

[43]  G. Mazza,et al.  Optimization of Extraction of Anthocyanins from Black Currants with Aqueous Ethanol , 2003 .

[44]  Ying Wang,et al.  Microwave assisted extraction of secondary metabolites from plants: Current status and future directions , 2011 .

[45]  O. Lee,et al.  Radical-scavenging-linked antioxidant activities of extracts from black chokeberry and blueberry cultivated in Korea. , 2014, Food chemistry.

[46]  M. Heinonen,et al.  Antioxidant activity of plant extracts containing phenolic compounds. , 1999, Journal of agricultural and food chemistry.

[47]  S. Valcheva-Kuzmanova,et al.  Current knowledge of Aronia melanocarpa as a medicinal plant. , 2006, Folia medica.

[48]  S. Benvenuti,et al.  Polyphenols, Anthocyanins, Ascorbic Acid, and Radical Scavenging Activity of Rubus, Ribes, and Aronia , 2006 .

[49]  Katarina M. Rajković,et al.  Optimization of base-catalyzed ethanolysis of sunflower oil by regression and artificial neural network models , 2013 .

[50]  Nyuk Ling Chin,et al.  Optimization of total phenolic content extracted from Garcinia mangostana Linn. hull using response surface methodology versus artificial neural network , 2012 .

[51]  T. Langrish,et al.  Optimisation of total phenolic acids extraction from mandarin peels using microwave energy: The importance of the Maillard reaction , 2012 .

[52]  T. Zou,et al.  Comparison of microwave-assisted and conventional extraction of mangiferin from mango (Mangifera indica L.) leaves. , 2013, Journal of separation science.

[53]  H. Raheman,et al.  Prediction of optimized pretreatment process parameters for biodiesel production using ANN and GA , 2009 .

[54]  Li Yang,et al.  Optimum extraction process of polyphenols from the bark of Phyllanthus emblica L. based on the response surface methodology. , 2009, Journal of separation science.