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The Optimization Method by Using the Transformation of Two Variable Dependent Experiment Results into Image Data and Its Usability in the Food Engineering Applications

Year 2017, Volume: 1 Issue: 1, 58 - 65, 30.08.2017

Abstract

In this study, it is aimed to
determine the variable values which should be selected to produce the optimal
experiment results in the field of Food Engineering by using image processing
methods. In the study, the matrix of experiment results dependent on two
variable values is transformed into the gray-scale image matrix, then the cells
with the darkest color values (cells with black color is the least-valued) in
the image matrix were identified. Finally, the variable limits (coordinate
limits) of the black color cells have been determined. Determined limits were
considered to be variable limits which will produce the optimal result of the
experiment. The method proposed in the study has been tested in an exemplary
experiment in which the antimicrobial effect of the Lactobacillus casei Shirota against the Staphylococcus aureus is determined by in-vitro. According to the obtained findings, it was confirmed that
the proposed method can be used to determine the optimum variable limits in
similar Food Engineering analyzes. Also which of the image processing methods
would be useful in such optimizations were proposed
.

References

  • Aksay S. & Mazza G. 2007. Optimization of protein recovery by foam separation using response surface methodology. Journal of food engineering, 79(2), 598-606.
  • Burger W.& Burge M. J. 2016. Digital image processing: an algorithmic introduction using Java. Springer.
  • Buzrul S., Cevik M. & Alpas H. 2008. Comparison of response surface methodology and the proposed Weibull model for inactivation of Listeria innocua by high hydrostatic pressure. Journal of food safety,28(1), 142-156.
  • Cordova C., Heidenreich B., Popolitov A. & Shakirov S. 2016. Orbifolds and Exact Solutions of Strongly-Coupled Matrix Models. arXiv preprint arXiv:1611.03142.
  • GoksungurY., Mantzouridou F., Roukas T. & Kotzekidou P. 2004. Production of β-carotene from beetmolases by Blake sleatrispora in stirred-tank and bubble column reactors. Applied biochemistry and biotechnology, 112(1), 37-54.
  • Ibanoglu S. & Ainsworth P. 2004. Application of response surface methodology for studying the viscosity changes during canning of tarhana, a cereal-based food. Journal of food engineering 64(3): 273-275.
  • Kılıç K., Köksel H. &Boyacı İ. H. 2006. Görüntü İşleme Tekniği ve Gıda Teknolojisi Alanında Kullanımı: Deneysel Uygulamalar, Türkiye 9. Gıda Kongresi, İzzet Baysal Kültür Merkezi (pp. 39-40), Bolu.
  • KoçB. & Kaymak-Ertekin F. 2009. Yanıt yüzey yöntemi ve gıda işleme uygulamaları, Gıda, 1-8 p.
  • Lau T. K. & Lin K. W. 2016. U.S. Patent No. 9,307,133. Washington, DC: U.S. Patent and Trademark Office
  • Russ J. C., Matey J. R., Mallinckrodt A. J.& McKay S. 1994. The image processing handbook. Computers in Physics, 8(2), 177-178.
  • Saklar S., Katnas S.&Ungan S. 2001. Determination of optimum hazelnut roasting conditions. International journal of food science & technology, 36(3), 271-281.
  • Samtaş G.& Gülesin M. 2012. Sayısal Görüntü İşleme ve Farklı Alanlardaki Uygulamaları. EJOVOC: Electronic Journal of Vocational Colleges, 2(1).
  • Sofu M. M., Er O., Kayacan M. C.&Cetişli B. 2013. Elmaların görüntü işleme yöntemi ile sınıflandırılması ve leke tespiti. Gıda Teknolojileri Elektronik Dergisi, 8(1), 12-25.
  • Ürküt Z., Daǧbaǧlı S.&Göksungur Y. 2007. Optimization of pullulan production using Ca‐alginate‐immobilized Aureobasidium pullulans by response surface methodology. Journal of chemical technology and biotechnology, 82(9), 837-846.
Year 2017, Volume: 1 Issue: 1, 58 - 65, 30.08.2017

Abstract

References

  • Aksay S. & Mazza G. 2007. Optimization of protein recovery by foam separation using response surface methodology. Journal of food engineering, 79(2), 598-606.
  • Burger W.& Burge M. J. 2016. Digital image processing: an algorithmic introduction using Java. Springer.
  • Buzrul S., Cevik M. & Alpas H. 2008. Comparison of response surface methodology and the proposed Weibull model for inactivation of Listeria innocua by high hydrostatic pressure. Journal of food safety,28(1), 142-156.
  • Cordova C., Heidenreich B., Popolitov A. & Shakirov S. 2016. Orbifolds and Exact Solutions of Strongly-Coupled Matrix Models. arXiv preprint arXiv:1611.03142.
  • GoksungurY., Mantzouridou F., Roukas T. & Kotzekidou P. 2004. Production of β-carotene from beetmolases by Blake sleatrispora in stirred-tank and bubble column reactors. Applied biochemistry and biotechnology, 112(1), 37-54.
  • Ibanoglu S. & Ainsworth P. 2004. Application of response surface methodology for studying the viscosity changes during canning of tarhana, a cereal-based food. Journal of food engineering 64(3): 273-275.
  • Kılıç K., Köksel H. &Boyacı İ. H. 2006. Görüntü İşleme Tekniği ve Gıda Teknolojisi Alanında Kullanımı: Deneysel Uygulamalar, Türkiye 9. Gıda Kongresi, İzzet Baysal Kültür Merkezi (pp. 39-40), Bolu.
  • KoçB. & Kaymak-Ertekin F. 2009. Yanıt yüzey yöntemi ve gıda işleme uygulamaları, Gıda, 1-8 p.
  • Lau T. K. & Lin K. W. 2016. U.S. Patent No. 9,307,133. Washington, DC: U.S. Patent and Trademark Office
  • Russ J. C., Matey J. R., Mallinckrodt A. J.& McKay S. 1994. The image processing handbook. Computers in Physics, 8(2), 177-178.
  • Saklar S., Katnas S.&Ungan S. 2001. Determination of optimum hazelnut roasting conditions. International journal of food science & technology, 36(3), 271-281.
  • Samtaş G.& Gülesin M. 2012. Sayısal Görüntü İşleme ve Farklı Alanlardaki Uygulamaları. EJOVOC: Electronic Journal of Vocational Colleges, 2(1).
  • Sofu M. M., Er O., Kayacan M. C.&Cetişli B. 2013. Elmaların görüntü işleme yöntemi ile sınıflandırılması ve leke tespiti. Gıda Teknolojileri Elektronik Dergisi, 8(1), 12-25.
  • Ürküt Z., Daǧbaǧlı S.&Göksungur Y. 2007. Optimization of pullulan production using Ca‐alginate‐immobilized Aureobasidium pullulans by response surface methodology. Journal of chemical technology and biotechnology, 82(9), 837-846.
There are 14 citations in total.

Details

Primary Language English
Journal Section Article
Authors

Selahaddin Batuhan Akben This is me

Selin Kalkan

Demet Çanga This is me

Publication Date August 30, 2017
Published in Issue Year 2017 Volume: 1 Issue: 1

Cite

APA Akben, S. B., Kalkan, S., & Çanga, D. (2017). The Optimization Method by Using the Transformation of Two Variable Dependent Experiment Results into Image Data and Its Usability in the Food Engineering Applications. Eurasian Journal of Food Science and Technology, 1(1), 58-65.
AMA Akben SB, Kalkan S, Çanga D. The Optimization Method by Using the Transformation of Two Variable Dependent Experiment Results into Image Data and Its Usability in the Food Engineering Applications. EJFST. August 2017;1(1):58-65.
Chicago Akben, Selahaddin Batuhan, Selin Kalkan, and Demet Çanga. “The Optimization Method by Using the Transformation of Two Variable Dependent Experiment Results into Image Data and Its Usability in the Food Engineering Applications”. Eurasian Journal of Food Science and Technology 1, no. 1 (August 2017): 58-65.
EndNote Akben SB, Kalkan S, Çanga D (August 1, 2017) The Optimization Method by Using the Transformation of Two Variable Dependent Experiment Results into Image Data and Its Usability in the Food Engineering Applications. Eurasian Journal of Food Science and Technology 1 1 58–65.
IEEE S. B. Akben, S. Kalkan, and D. Çanga, “The Optimization Method by Using the Transformation of Two Variable Dependent Experiment Results into Image Data and Its Usability in the Food Engineering Applications”, EJFST, vol. 1, no. 1, pp. 58–65, 2017.
ISNAD Akben, Selahaddin Batuhan et al. “The Optimization Method by Using the Transformation of Two Variable Dependent Experiment Results into Image Data and Its Usability in the Food Engineering Applications”. Eurasian Journal of Food Science and Technology 1/1 (August 2017), 58-65.
JAMA Akben SB, Kalkan S, Çanga D. The Optimization Method by Using the Transformation of Two Variable Dependent Experiment Results into Image Data and Its Usability in the Food Engineering Applications. EJFST. 2017;1:58–65.
MLA Akben, Selahaddin Batuhan et al. “The Optimization Method by Using the Transformation of Two Variable Dependent Experiment Results into Image Data and Its Usability in the Food Engineering Applications”. Eurasian Journal of Food Science and Technology, vol. 1, no. 1, 2017, pp. 58-65.
Vancouver Akben SB, Kalkan S, Çanga D. The Optimization Method by Using the Transformation of Two Variable Dependent Experiment Results into Image Data and Its Usability in the Food Engineering Applications. EJFST. 2017;1(1):58-65.

Eurasian Journal of Food Science and Technology (EJFST)   e-ISSN: 2667-4890   Web: https://dergipark.org.tr/en/pub/ejfst   e-mail: foodsciencejournal@gmail.com