Ultrasound assisted extraction of phenolic compounds from P. lentiscus L. leaves: Comparative study of artificial neural network (ANN) versus degree of experiment for prediction ability of phenolic compounds recovery

Industrial Crops and Products

Volumn 77, Issue , 2015, Pages 251-261

  Dahmoune, Farid ^a,b   Remini, Hocine ^a   Dairi, Sofiane ^a   Aoun, Omar ^a,c   Moussi, Kamal ^a   Bouaoudia Madi, Nadia ^a   Adjeroud, Nawel ^a   Kadri, Nabil ^b   Lefsih, Khalef ^a   Boughani, Lhadi ^a,b   Mouni, Lotfi ^b   Nayak, Balunkeswar ^d   Madani, Khodir ^a  

^a UNIVERSITY OF BEJAIA   (Algeria)

^b UNIVERSITY OF BOUIRA   (Algeria)

^c UNIVERSITY OF KHEMIS MILIANA   (Algeria)

^d UNIVERSITY OF MAINE   (United States)

Author keywords

Antioxidant activity; Artificial neural networks; DOE; Phenolic compounds; Pistacia leaves; Ultrasound extraction

Indexed keywords

COMPUTER SYSTEM RECOVERY; DESIGN OF EXPERIMENTS; MEAN SQUARE ERROR; NEURAL NETWORKS; PHENOLS; PYRENE; ULTRASONICS;

ANTI-OXIDANT ACTIVITIES; DOE; PHENOLIC COMPOUNDS; PISTACIA LEAVES; ULTRASOUND EXTRACTIONS;

EXTRACTION;

ANTIOXIDANT; ARTIFICIAL NEURAL NETWORK; COMPARATIVE STUDY; ENZYME ACTIVITY; ERROR ANALYSIS; EVERGREEN TREE; EXPERIMENTAL DESIGN; EXTRACTION METHOD; LEAF; MODEL TEST; OPTIMIZATION; PHENOLIC COMPOUND; PREDICTION; ULTRASONICS;

PISTACIA; PISTACIA LENTISCUS;

EID: 84941271061     PISSN: 09266690     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.indcrop.2015.08.062     Document Type: Article

References (32)

1. Bampouli A., Kyriakopoulou K., Papaefstathiou G., Louli V., Aligiannis N., Magoulas K., Krokida M. Evaluation of total antioxidant potential of Pistacia lentiscus var. chia leaves extracts using UHPLC-HRMS. J. Food Eng. 2014, 10.1016/j.jfoodeng.2014.10.021.
2. Chemat F., Vian M.A., Cravotto G. Green extraction of natural products: concept and principles. Int. J. Mol. Sci. 2012, 13:8615-8627.
3. Cheok C.Y., Chin N.L., Yusof Y.A., Talib R.A., Law C.L. Optimization of total phenolic content extracted from Garcinia mangostana Linn hull using response surface methodology versus artificial neural network. Ind. Crops Prod. 2012, 40:247-253.
4. Dahmoune F., Boulekbache L., Moussi K., Aoun O., Spigno G., Madani K. Valorization of Citrus limon residues for the recovery of antioxidants: evaluation and optimization of microwave and ultrasound application to solvent extraction. Ind. Crops Prod. 2013, 50:77-87.
5. Dahmoune F., Moussi K., Remini H., Belbahi A., Aoun O., Spigno G., Madani K. Optimization of ultrasound-assisted extraction of phenolic compounds from Citrus sinensis L peels using response surface methodology. Chem. Eng. 2014, 37:889-894.
6. Dahmoune F., Nayak B., Moussi K., Remini H., Madani K. Optimization of microwave-assisted extraction of polyphenols from Myrtus communis L. leaves. Food Chem. 2015, 166:585-595.
7. Dawidowicz A.L., Olszowy M., Jóźwik-Doleba M. Antagonistic antioxidant effect in butylated hydroxytoluene/butylated hydroxyanisole mixture. J. Food Process. Preserv. 2015, (In press). 10.1111/jfpp.12469.
8. Delpino-Rius A., Eras J., Vilaró F., Cubero M.Á., Balcells M., Canela-Garayoa R. Characterisation of phenolic compounds in processed fibres from the juice industry. Food Chem. 2015, 172:575-584.
9. Geyikçi F., Kiliç E., Çoruh S., Elevli S. Modelling of lead adsorption from industrial sludge leachate on red mud by using RSM and ANN. Chem. Eng. J. 2012, 183:53-59.
10. Ghoreishi S.M., Heidari E. Extraction of Epigallocatechin-3-gallate from green tea via supercritical fluid technology: neural network modeling and response surface optimization. J. Supercrit. Fluids 2013, 74:128-136.
11. Gong Y., Hou Z., Gao Y., Xue Y., Liu X., Liu G. Optimization of extraction parameters of bioactive components from defatted marigold (Tagetes erecta L.) residue using response surface methodology. Food Bioprod. Process. 2012, 90:9-16.
12. Gruenwald J. Novel botanical ingredients for beverages. Clin. Dermatol. 2009, 27:210-216.
13. Hafizi A., Ahmadpour A., Koolivand-Salooki M., Heravi M., Bamoharram F. Comparison of RSM and ANN for the investigation of linear alkylbenzene synthesis over H 14 [NaP 5W 30 O 110]/SiO 2 catalyst. J. Ind. Eng. Chem. 2013, 19:1981-1989.
14. Hafizi A., Ahmadpour A., Koolivand-Salooki M., Heravi M.M., Bamoharram F.F. Comparison of RSM and ANN for the investigation of linear alkylbenzene synthesis over H14[NaP5W30O110]/SiO2 catalyst. J. Ind. Eng. Chem. 2013, 19:1981-1989.
15. Huang D., Ou B., Hampsch-Woodill M., Flanagan J.A., Prior R.L. High-throughput assay of oxygen radical absorbance capacity (ORAC) using a multichannel liquid handling system coupled with a microplate fluorescence reader in 96-well format. J. Agric. Food Chem. 2002, 50:4437-4444.
16. Jaramillo-Flores M.E., González-Cruz L., Cornejo-Mazón M., Dorantes-Alvarez L., Gutiérrez-López G.F., Hernández-Sánchez H. Effect of thermal treatment on the antioxidant activity and content of carotenoids and phenolic compounds of cactus pear cladodes (Opuntia ficus-indica). Food Sci. Technol. Int. 2003, 9:271-278.
17. Jerman T., Trebše P., Mozetič Vodopivec B. Ultrasound-assisted solid liquid extraction (USLE) of olive fruit (Olea europaea) phenolic compounds. Food Chem. 2010, 123:175-182.
18. Kadam S.U., Tiwari B.K., Smyth T.J., O'Donnell C.P. Optimization of ultrasound assisted extraction of bioactive components from brown seaweed Ascophyllum nodosum using response surface methodology. Ultrason. Sonochem. 2015, 23:308-316.
19. Kumar R., Chauhan S. Study on surface roughness measurement for turning of Al 7075/10/SiCp and Al 7075 hybrid composites by using response surface methodology (RSM) and artificial neural networking (ANN). Measurement 2015, 65:166-180.
20. Lupien J.R. Implications for food regulations of novel food: Safety and labeling. Asia Pac. J. Clin. Nutr. 2002, 11:S224-S229.
21. Machado A.P.D.F., Pasquel-Reátegui J.L., Barbero G.F., Martínez J. Pressurized liquid extraction of bioactive compounds from blackberry (rubus fruticosus l.) residues. a comparison with conventional methods. Food Res. Int. 2015, (In press). 10.1016/j.foodres.2014.12.042.
22. Molyneux P. The use of the stable free radical diphenylpicrylhydrazyl (DPPH) for estimating antioxidant activity. Songklanakarin J. Sci. Technol. 2004, 26:211-219.
23. Pilkington J.L., Preston C., Gomes R.L. Comparison of response surface methodology (RSM) and artificial neural networks (ANN) towards efficient extraction of artemisinin from Artemisia annua. Ind. Crops Prod. 2014, 58:15-24.
24. Rafigh S.M., Yazdi A.V., Vossoughi M., Safekordi A.A., Ardjmand M. Optimization of culture medium and modeling of curdlan production from Paenibacillus polymyxa by RSM and ANN. Int. J. Biol. Macromol. 2014, 70:463-473.
25. Ramić M., Vidović S., Zeković Z., Vladić J., Cvejin A., Pavlić B. Modeling and optimization of ultrasound-assisted extraction of polyphenolic compounds from Aronia melanocarpa by-products from filter-tea factory. Ultrason. Sonochem. 2015, 23:360-368.
26. Rodrigues S., Fernandes F.A.N., de Brito E.S., Sousa A.D., Narain N. Ultrasound extraction of phenolics and anthocyanins from jabuticaba peel. Ind. Crops Prod. 2015, 69:400-407.
27. Sarve A., Sonawane S.S., Varma M.N. Ultrasound assisted biodiesel production from sesame (Sesamum indicum L.) oil using barium hydroxide as a heterogeneous catalyst: comparative assessment of prediction abilities between response surface methodology (RSM) and artificial neural network (ANN). Ultrason. Sonochem. 2015, 26:218-228.
28. Shojaeimehr T., Rahimpour F., Khadivi M.A., Sadeghi M. A modeling study by response surface methodology (RSM) and artificial neural network (ANN) on Cu2+ adsorption optimization using light expended clay aggregate (LECA). J. Ind. Eng. Chem. 2014, 20:870-880.
29. Spigno G., Tramelli L., De Faveri D.M. Effects of extraction time, temperature and solvent on concentration and antioxidant activity of grape marc phenolics. J. Food Eng. 2007, 81:200-208.
30. Thabit R.A., Cheng X.-R., A.L-Hajj N., Rahman M.R.T., Le G. Antioxidant and Conyza bonariensis: a Review. Eur. Acad. Res. 2015, 2(6):8454-8474.
31. Vázquez C.V., Rojas M.G.V., Ramírez C.A., Chávez-Servín J.L., García-Gasca T., Ferriz Martínez R.A., García O.P., Rosado J.L., López-Sabater C.M., Castellote A.I., Montemayor H.M.A., de la Torre Carbot K. Total phenolic compounds in milk from different species design of an extraction technique for quantification using the Folin-Ciocalteu method. Food Chem. 2015, 176:480-486.
32. Veggi P.C., Prado J.M., Bataglion G.A., Eberlin M.N., Meireles M.A.A. Obtaining phenolic compounds from jatoba (Hymenaea courbaril L.) bark by supercritical fluid extraction. J. Supercrit. Fluids 2014, 89:68-77.