Year 2019, Volume 44, Issue 3, Pages 396 - 408 2019-05-15

MARMARA BÖLGESİNDE YENİ BİR TATLI TARİFİ İÇİN LEZZET BİLEŞİKLERİ AĞ ANALİZİNİN KULLANIMI
UTILIZATION OF FLAVOR NETWORK ANALYSIS FOR A NEW RECIPE IN MARMARA REGION

Bengu Ozturk [1] , Burcak Zeyrekce [2]

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Doğal lezzet bileşikleri gıda malzemelerine karakteristik tat ve koku özelliklerini vermektedir. Gıda eşleştirme teorisine göre, yüksek sayıda ortak lezzet bileşiği içeren gıda malzemeleri birbiriyle uyum içerisinde güzel tat veren bir yemek oluşturabilir. Bu çalışmada, Marmara Bölgesi’nde yeni bir tarif oluşturmak için, malzemeler içerdikleri ortak bileşik sayısına göre değerlendirilip tat bileşikleri ağ analizi metodu kullanıldı. Yüksek sayıda ortak bileşik içeren eşleştirmelerden pirinç, süt, kuru fasulye ve incir malzemelerini ihtiva eden yeni bir tatlı geliştirildi. Ortak bileşiklerden sekiz tanesinin dört malzemede de bulunduğu ve şaşırtıcı bir şekilde birbiriyle benzer tat ve koku maddeleri içerdiği görüldü ki bu da lezzet eşleştirme teorisinin bu bölgedeki yeni bir tarif için kullanılabildiğini göstermektedir. 9-noktalı hedonik skala testine göre, 20 panelistin %80’i ‘Fevkalade beğendim’ seçeneğini işaretlemiştir. Lezzet bilimi ve gıda eşleştirme teorisinin bilinmesi, tüketimi çok tercih edilen yeni gıda formülasyonlarının geliştirilmesi imkânını bize verebilecektir.

Natural flavor compounds give natural taste and odor characteristics to the food ingredients. According to food pairing theory, ingredients that contain higher number of shared flavor compounds go well together in a dish. In this study, flavor network analysis was used to create a new food in Marmara Region by evaluating the ingredient pairs based on number of shared compounds. A new dessert with four main ingredients, rice, milk, bean and figs that shared higher number of flavor compounds was formulated. Among the flavour compounds, eight of them were common in all four ingredients and they interestingly had similar taste and odor characteristics which showed how flavor pairing worked well in design of new dish. According to 9-point hedonic scale of consumer preference test, 80% of 20 panelists extremely liked the dish. Knowledge on flavour science and food pairing theory will pave the way to create highly preferable food formulations.

  • Ahn, Y., Ahnert, S. E., Bagrow, J. P., Barabâsi, A. (2011). Flavor network and the principles of food pairing. Sci Rep, 1(196): 1-7.
  • Ahnert, S.E. (2013). Network analysis and data mining in food science: the emergence of computational gastronomy. Flavour, 2(4): 1-3.
  • Akkor, M. Ö. (2009). Bursa Mutfagi, Türkiye İş Bankasi Yayinlari, Istanbul.
  • Barabási, A., Gulbahce, N., Loscalzo, J. (2011). Network medicine: A network-based approach to human disease. Nat Rev Genet, 12(1): 56–68.
  • Bayrak, M. F. (2015). Soframda Anadolu Marmara Yemekleri. Alfa Basim Yayim Dağitim San. ve Tic. Ltd. Sti., Istanbul.
  • Blumenthal, H. (2009). The Fat Duck Cookbook, UK Ed. Bloomsbury Publishing PLC, London, United Kingdom.
  • Bogojeska A., Kalajdziski S., Kocarev L. (2016). Processing and analysis of Macedonian cuisine and its flavours by using online recipes. In: Loshkovska S., Koceski S. (Eds), ICT Innovations 2015. Advances in Intelligent Systems and Computing, vol 399, (pp 143-152). Springer, Cham, Switzerland.
  • Borgatti, S.P, Mehra, A., Brass, D.J., Labianca, G. (2009). Network analysis in the social sciences. Science, 323(5916): 892-895.
  • Bozis, S. (2002). Istanbul lezzeti. (2nd Ed.). Tarih Vakfi Yurt Yayinlari, Istanbul.
  • Burdock, G.A. (2009). Fenaroli’s handbook of flavor ingredients. (6th Ed.). CRC Press, Bosa Roca, United States.
  • Dornenburg, A. and Page, K. (2008). The Flavor Bible. (2nd Ed.). Litte, Brown and Company, Hachette Book Group, New York.
  • Dunne, J. A., Williams, R. J., Martinez, N. D. (2002). Network structure and biodiversity loss in food webs: robustness increases with connectance. Ecol Lett, 5(4): 558–567.
  • Ergün Öztürk, Ö. and Öztürk, B. (2018). An ontology based Semantic Representation for Turkish Cuisine.26th IEEE Signal Processing and Communications Applications Conference, 1-5 May, Cesme- Izmir, Turkey.
  • Geissbauer, R., Vedso, J., Schrauf, S. (2016). Industry 4.0: Building the digital enterprise. PWC. 2016 Global Industry 4.0 Survey.
  • Ghaswala, D., Kundalia, H., Shah, N. (2018). Bon vivant: an artificial intelligence cooking app. Int J of Sci Eng, 3(1): 170-174.
  • Habibi, I., Emamian, E. S., Abdi, A. (2014). Quantitative analysis of intracellular communication and signaling errors in signaling networks. BMC Syst Biol, 8(89): 1-15. Halici, N. (1990). Türk Mutfagi, Güven Matbaasi, Ankara.
  • Higgins, K.T. (2017). Artificial intelligence and other advances in industrial baking. Food Processing, https://www.foodprocessing.com/articles/2017/artificial-intelligence-industrial-baking/Accessed 20 July 2018.
  • Jain, A., Rakhi N. K., Bagler, G. (2015). Analysis of food pairing in regional cuisines of India. PLoS ONE, 10(10): 1-17.
  • Kort, M., Nijssen, B., van Ingen-Visscher, K., Donders, J. (2010). Food pairing from the perspective of the ‘volatile compounds in food’ database. I.Blank, M.Wüst, C.Yeretzian (Eds.), Expression of Multidisciplinary Flavour Science: Proceedings of the 12th Weurman Symposium, Interlaken, Switzerland, Institut of Chemistry and Biological Chemistry,Winterthur, pp.589-592.
  • Kutup, N. (2017). Network science, flavor ingredient compounds network and the birth of digital gastronomy. Apelasyon, 43: 1-14.
  • McNamara, C. (2017). Digitalization: The future of food and beverage. Food Processing. https://www.foodprocessing.com/articles/2017/digitalization-the-future-of-food-and-beverage/Accessed 20 July 2018.
  • Mizrahi, M., Gruber, R., Golan, A., Lachnish, A.Z., Mizrahi, A.B., Zoran, A. (2016, October). Digital gastronomy: methods & recipes for hybrid cooking. 29th Annual Symposium on User Interface Software and Technology, 16-19 October, Tokyo, Japan, pp. 541-552.
  • Mouritsen, O. G., Edwards-Stuart, R., Ahn, Y-Y., Ahnert, S. E. (2017). Data-driven methods for the study of food perception, preparation, consumption, and culture. Frontiers ICT 4:15.
  • Pimentel, T.C., Gomes da Cruz, A., Deliza, R. (2016). Sensory evaluation: sensory rating and scoring methods. The Encyclopedia of Food and Health, 4: 744-749.
  • Pinel F., Varshney L.R.,Bhattacharjya D. (2015). A Culinary Computational Creativity System. In: Besold T., Schorlemmer M., Smaill A. (Eds), Computational Creativity Research: Towards Creative Machines. Atlantis Thinking Machines, (pp 327-346). Atlantis Press, Paris.
  • Prescott, J. (2015). Multisensory processes in flavour perception and their influence on food choice. Curr Opin Food Sci, 3: 47-52.
  • Reineccius, G. (2006). Flavor chemistry and technology, (2nd Ed.). Taylor & Francis Group, LLC, Boca Raton, FL, USA.
  • Shrinivas, S.G., Vetrivel, S., Elango, N.M. (2010). Applications of graph theory in computer science an overview. Int J Eng Sci Technol, 2(9): 4610-4621.
  • Şengül, S., Çakir, A., Çakir, G. (2015). Yöresel Mutfaklar. Beta Basim Yayim Dağitim A.Ş. Ankara.
  • Taylor, A. and Hort, J. (2007). Modifying flavor in food. CRC Press LLC, Boca Raton, FL, USA.
  • Toroa, C., Barandiarana, I., Posada, J. (2015). A perspective on knowledge based and intelligent systems implementation in Industrie 4.0. Procedia Comput Sci, 60: 362-370.
Primary Language en
Subjects Science
Published Date 2019
Journal Section Articles
Authors

Orcid: 0000-0002-4925-6678
Author: Bengu Ozturk (Primary Author)
Institution: YEDITEPE UNIVERSITY, FACULTY OF ENGINEERING, DEPARTMENT OF FOOD ENGINEERING
Country: Turkey


Author: Burcak Zeyrekce
Institution: YEDITEPE UNIVERSITY, FACULTY OF FINE ARTS, DEPARTMENT OF GASTRONOMY AND CULINARY ARTS
Country: Turkey


Dates

Publication Date: May 15, 2019

Bibtex @research article { gida505496, journal = {GIDA}, issn = {1300-3070}, eissn = {1309-6273}, address = {Gıda Teknolojisi Derneği}, year = {2019}, volume = {44}, pages = {396 - 408}, doi = {10.15237/gida.GD19012}, title = {UTILIZATION OF FLAVOR NETWORK ANALYSIS FOR A NEW RECIPE IN MARMARA REGION}, key = {cite}, author = {Ozturk, Bengu and Zeyrekce, Burcak} }
APA Ozturk, B , Zeyrekce, B . (2019). UTILIZATION OF FLAVOR NETWORK ANALYSIS FOR A NEW RECIPE IN MARMARA REGION. GIDA, 44 (3), 396-408. DOI: 10.15237/gida.GD19012
MLA Ozturk, B , Zeyrekce, B . "UTILIZATION OF FLAVOR NETWORK ANALYSIS FOR A NEW RECIPE IN MARMARA REGION". GIDA 44 (2019): 396-408 <http://dergipark.org.tr/gida/issue/44377/505496>
Chicago Ozturk, B , Zeyrekce, B . "UTILIZATION OF FLAVOR NETWORK ANALYSIS FOR A NEW RECIPE IN MARMARA REGION". GIDA 44 (2019): 396-408
RIS TY - JOUR T1 - UTILIZATION OF FLAVOR NETWORK ANALYSIS FOR A NEW RECIPE IN MARMARA REGION AU - Bengu Ozturk , Burcak Zeyrekce Y1 - 2019 PY - 2019 N1 - doi: 10.15237/gida.GD19012 DO - 10.15237/gida.GD19012 T2 - GIDA JF - Journal JO - JOR SP - 396 EP - 408 VL - 44 IS - 3 SN - 1300-3070-1309-6273 M3 - doi: 10.15237/gida.GD19012 UR - https://doi.org/10.15237/gida.GD19012 Y2 - 2019 ER -
EndNote %0 THE JOURNAL OF FOOD UTILIZATION OF FLAVOR NETWORK ANALYSIS FOR A NEW RECIPE IN MARMARA REGION %A Bengu Ozturk , Burcak Zeyrekce %T UTILIZATION OF FLAVOR NETWORK ANALYSIS FOR A NEW RECIPE IN MARMARA REGION %D 2019 %J GIDA %P 1300-3070-1309-6273 %V 44 %N 3 %R doi: 10.15237/gida.GD19012 %U 10.15237/gida.GD19012
ISNAD Ozturk, Bengu , Zeyrekce, Burcak . "UTILIZATION OF FLAVOR NETWORK ANALYSIS FOR A NEW RECIPE IN MARMARA REGION". GIDA 44 / 3 (May 2019): 396-408. https://doi.org/10.15237/gida.GD19012
AMA Ozturk B , Zeyrekce B . UTILIZATION OF FLAVOR NETWORK ANALYSIS FOR A NEW RECIPE IN MARMARA REGION. GIDA. 2019; 44(3): 396-408.
Vancouver Ozturk B , Zeyrekce B . UTILIZATION OF FLAVOR NETWORK ANALYSIS FOR A NEW RECIPE IN MARMARA REGION. GIDA. 2019; 44(3): 408-396.