Paper Titles

Research on Measurement of Void Fraction for Vertically Rising Pipes by Optical Fiber Probe
p.671

Effect of Air Moisture on Pepper Growth with Different Irrigation Methods in a Greenhouse
p.676

Application of Capillary Zone Electrophoresis in the Separation and Determination of the Tertiary Butylhydroquinone
p.683

A Network Intrusion Detection Model Based on Artificial Immune
p.687

Optimization and Comparison of Three Methods on Anthocyanins Extraction from Blackcurrant (Ribes nigrum L.) Using RSM
p.691

Identiﬁcation and Characteristics of Lactic Acid Bacteria Isolated from Stylosanthes guianensis sw.
p.701

Extraction Mechanism of Total Flavonoids from Red Kidney Bean by Microwave and Light Wave Radiation
p.707

Release of Ferulic Acid from Wheat Bran by Ultrasonic Assisted Alkaline Hydrolysis
p.712

The Research of Ice-Water Phase Change and Heat Transfer in Natural Environment of Northern Winter in China
p.724

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 361-363Optimization and Comparison of Three Methods on...

Optimization and Comparison of Three Methods on Anthocyanins Extraction from Blackcurrant (Ribes nigrum L.) Using RSM

Article Preview

Abstract:

Response surface methodology (RSM) complemented with a central composite design (CCD) was employed to optimize and compare three different anthocyanins extraction methods (solid–liquid extraction(SLE), ultrasonic-assisted extraction (UAE) and microwave-assisted extraction (MAE)) from blackcurrant fruits. The aim was to obtain extracts with high anthocyanins content, which would be potentially interesting for commercial applications as natural colorants. Three major independent variables such as extraction time(min), ethanol concentration (%,v/v), solution to solid ratio (mL/g) were coded at five levels and their actual values were selected on the basis of preliminary experimental results. Results indicated that the yields of anthocyanins varied when extracted with different method, the order of anthocyanins yield from high to low was: MAE (95.77%), UAE (93.65%) and SLE (90.82%). Among three reaction parameters, ethanol concentration consistently tended to significantly affect the anthocyanins yield for above three models (p < 0.0001). MAE was the best of three methods in this study and the optimal values were as follows: extract time controlled at 6.3 min, ethanol concentration maintained at 72.8%, solution to solid ratio equaled to 8.1:1 and working power at 400W. The experimental anthocyanins value under above optimum conditions could reach to 95.77±1.05% that was in perfect agreement with the predicted model 95.52%.

You might also be interested in these eBooks

Natural Resources and Sustainable Development

Info:

Periodical:

Advanced Materials Research (Volumes 361-363)

Pages:

691-700

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.361-363.691

Citation:

Cite this paper

Online since:

October 2011

Authors:

Yu Yang, Sheng Xin Zhao, Ya Qin Xu, Ze Yuan Yu

Keywords:

Anthocyanin, Blackcurrant, Extraction, Optimization, Response Surface Method (RSM)

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] G. J. Mcdougall, S. Gordon & R. Brennan. J.Agric.Food Chem., 2005, 53: 7878–7885.

[2] T. Suzutani, M. Ogasawara, I. Yoshida,et al.. Phytother Res., 2003, 17: 609–613.

[3] H. Matsumoto, E. Takenami, K. Iwasaki-Kurashige, et al.. Eur J Appl Physiol, 2005,94: 36–45.

[4] B. H. Koeppen & K. Herrmann. Z. Lebensm. Unters. Forsch, 1977, 164: 263–268.

[5] T. K. McGhie, G. D. Ainge, L. E. Barnett, et al.. J.Agric.Food Chem., 2003, 51: 4539–4548.

[6] R. Slimestad & H. Solheim. J.Agric.Food Chem., 2002, 50: 3228–3231.

[7] C. A. Nayak, P. Srinivas & N. K. Rastogi. Food Chemistry, 2010, 118: 719–724.

[8] K. Ogawa, H. Sakakibara, R. Iwata, et al.. J.Agric.Food Chem., 2008, 56: 4457–4462.

[9] C. W. Michaela, G. L. Roger, W. R. Gordon, et al.. J.Agric.Food Chem.2006, 54: 7940–7946.

[10] K. Viljanen, R. Kivikari & M. Heinonen. J. Agric.Food Chem., 2004, 52: 7419–7424.

[11] M. P. Kähkönen, J. Heinämäki & V. Ollilainen. J. Sci. Food Agric., 2003, 83: 1403–1411.

[12] K.Viljanen, P. Kylli, E. M. Hubbermann, et al.. J. Agric. Food Chem., 2005, 53 :2022–2027.

[13] T. Lapidot, S. Harel, B. Akiri, et al.. J. Agric. Food Chem., 1999, 47: 67–70.

[14] I. L. Nielsen, L. O. Dragsted, G. Ravn-Haren, et al.. J. Agric. Food Chem., 2003, 51: 2813–2820.

[15] M. P. Kahkonen, A. I. Hopia, & M. Heinonen. J.Agric.Food Chem., 2001, 49: 4076–4082.

[16] A. Amr, & E. Al-Tamimi. Journal of Food Science and Technology, 2007, 42: 985–991.

[17] J. M. Awika, L. W . Rooney, & R. D. Waniska. Food Chemistry, 2005, 90: 293–301.

[18] J. Lee, C. E. Finn, & R. E. Wrolstad. J.Agric.Food Chem., 2004, 52: 7039–7044.

[19] B.L. apornik, M. Prošek, & A. G. Wondra. Journal of Food Engineering, 2005, 71: 214–222.

[20] Fang Chen, Yangzhao Sun, Guanghua Zhao, et al.. Ultrasonics Sonochemistry, 2007, 14: 767–778.

[21] M. D. Luque de Castro, & J. L. Luque García. Acceleration and Automation of Solid Sample Treatment. Amsterdam: Elsevier. 2002, 218.

[22] Zhendong Yang & Weiwei Zhai. Food Science and Emerging Technologies, 2010, 11: 470–476.

[23] L. Holtung, S. Grimmer & K. Aaby. J. Agric. Food Chem., 2011, 59: 3632–3640.

[24] Wenpeng Li, Yan Zhang & Jiamjun Chen. Science and Technology of Food Industry,2008, 6: 220–222. (In China)

[25] T. Yoshida, S. Tsubaki, Y. Teramoto, et al.. Bioresource Technology, 2010, 101: 7820–7826.

[26] Ping Wang,Yu Miao & Ying Wang. Food and Fermentation Industries, 2007, 33: 163–166. (In China)

[27] R. H. Myers, & D. C. Montgomery. Response surface methodology: Process and product optimization using designed experiments (2nd ed.). New York: Wiley. 2002.

[28] A. C. Atkinson & A. N. Doney. Optimum experimental designs. Oxford: Oxford University Press. 1992.