مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

video

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

sound

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Version

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

View:

832
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Download:

0
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Cites:

Information Journal Paper

Title

OPTIMIZATION OF ORANGE OSMOTIC DEHYDRATION PROCESS USING RESPONSE SURFACE METHOD AND ESTIMATION OF DEHYDRATION PARAMETERS BY ARTIFICIAL NEURAL NETWORK

Pages

  202-214

Keywords

RESPONSE SURFACE METHODOLOGY (RSM)Q1

Abstract

 In this study, Response Surface Methodology (RSM) was used to optimize osmo-dehydration of orange slice. Effect of osmotic solution temperature in the range of 30 to 60oC, immersion time from 0 to 300 min and sucrose concentration from 35 to 65 brix degree on water loss, solid gain, moisture content, water loss to solid gain ratio and brix change were investigated by Central Composite Design (CCD). Applying response surface and contour plots optimum for OSMOTIC DEHYDRATION were found to be at temperature of 30oC, immersion time of 229.2 minute and sucrose concentration of 65%. At this optimum point, water loss, solid gain, WL/SG ratio, moisture content (dry base) and brix difference were found to be 30.316 (g/100 g initial sample), 13.51 (g/100 g initial sample), 2.45, 2.77 % and 15.79, respectively. The result of ARTIFICIAL NEURAL NETWORK indicated that the perceptron neural network with one hidden layer is able to anticipate the dehydration characteristics. This network predicted solid gain and moisture content with 5 neuron per hidden layers with R2 values of 0.937 and 0.959, respectively and brix difference and water loss with 30 neuron per hidden layer with R2 values of 0.961 and 0.942, respectively.

Cites

  • No record.
  • References

    Cite

    APA: Copy

    AYDANI, E., KASHANINEJAD, M., MOKHTARIAN, M., & BAKHSHABADI, H.. (2013). OPTIMIZATION OF ORANGE OSMOTIC DEHYDRATION PROCESS USING RESPONSE SURFACE METHOD AND ESTIMATION OF DEHYDRATION PARAMETERS BY ARTIFICIAL NEURAL NETWORK. IRANIAN FOOD SCIENCE AND TECHNOLOGY RESEARCH JOURNAL, 9(3), 202-214. SID. https://sid.ir/paper/143614/en

    Vancouver: Copy

    AYDANI E., KASHANINEJAD M., MOKHTARIAN M., BAKHSHABADI H.. OPTIMIZATION OF ORANGE OSMOTIC DEHYDRATION PROCESS USING RESPONSE SURFACE METHOD AND ESTIMATION OF DEHYDRATION PARAMETERS BY ARTIFICIAL NEURAL NETWORK. IRANIAN FOOD SCIENCE AND TECHNOLOGY RESEARCH JOURNAL[Internet]. 2013;9(3):202-214. Available from: https://sid.ir/paper/143614/en

    IEEE: Copy

    E. AYDANI, M. KASHANINEJAD, M. MOKHTARIAN, and H. BAKHSHABADI, “OPTIMIZATION OF ORANGE OSMOTIC DEHYDRATION PROCESS USING RESPONSE SURFACE METHOD AND ESTIMATION OF DEHYDRATION PARAMETERS BY ARTIFICIAL NEURAL NETWORK,” IRANIAN FOOD SCIENCE AND TECHNOLOGY RESEARCH JOURNAL, vol. 9, no. 3, pp. 202–214, 2013, [Online]. Available: https://sid.ir/paper/143614/en

    Related Journal Papers

    Related Seminar Papers

  • No record.
  • Related Plans

  • No record.
  • Recommended Workshops






    Move to top