IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/3627715.html
   My bibliography  Save this article

Exploring the Food Pairing Hypothesis in Saudi Cuisine Using Genetic Algorithm

Author

Listed:
  • Muna Al-Razgan
  • Shahad Tallab
  • Taha Alfakih

Abstract

Computational gastronomy has emerged as one of the recent hot research topics in the field of food science. It is a field that studies food in the era of data. One of the current research topics in this field is the food pairing hypothesis, which states that food with common flavor compounds tastes good when consumed together. The hypothesis has been studied in Western and European gastronomic societies. However, there are no reported studies conducted in Arab counterparts. In this study, we used genetic algorithms (GAs) to validate this hypothesis in Saudi cuisine. We developed a quantitative model and applied it to a dataset consisting of ingredients compounds found in Saudi cuisine recipes. Our research revealed that the pattern of ingredients occurring in Saudi dishes showed positive food pairing results like western cuisine. Moreover, our research directs the light to new dimensions where GA can be applied to explore the field of food science and computational gastronomy.

Suggested Citation

  • Muna Al-Razgan & Shahad Tallab & Taha Alfakih, 2021. "Exploring the Food Pairing Hypothesis in Saudi Cuisine Using Genetic Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-16, December.
    • Handle: RePEc:hin:jnlmpe:3627715
    DOI: 10.1155/2021/3627715
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2021/3627715.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2021/3627715.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2021/3627715?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:3627715. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.