Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Author: search.filters.author.Cankal, Yadigar Seyfi

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  • Article
    Citation - WoS: 11
    Citation - Scopus: 12
    The Effect of Starch Types on Extensional, Linear and Nonlinear Rheological Properties of Starch Cracker Dough
    (Elsevier, 2024) Berk, Berkay; Cankal, Yadigar Seyfi; Koroglu, Ebru; Yorulmaz, Hilal; Cavdaroglu, Elif; Unluturk, Sevcan
    Cracker is a popular snack, and their quality depends on the rheological properties of the dough during production. This study focused on the impact of different starch types (tapioca, corn, and potato) used in the same amount (30 g) on the rheology of starch cracker dough. Various rheological tests were conducted to assess the dough's properties. Linear viscoelastic properties were determined using oscillatory frequency and temperature sweep tests, while the nonlinear viscoelastic behavior was characterized through stress relaxation and creep recovery tests. Extensional rheological behavior was also examined. Additionally, the textural and thermal properties of the dough were monitored to understand starch gelatinization and its interactions with other components. In the linear viscoelastic region, no significant differences were found between different dough formulations. However, in the nonlinear viscoelastic region, the potato starch-containing formulation exhibited different viscoelastic and textural properties. Biaxial extensional rheological behaviors showed no significant variations between formulations. The temperature sweep test data from differential scanning calorimetry measurements were consistent with temperature sweep data. In summary, this study provides valuable insights into how different starches influence the rheological behavior of starch cracker dough, considering various degrees of deformation and temperature. These findings have implications for cracker production parameters.
  • Article
    Citation - WoS: 4
    Citation - Scopus: 4
    Fluence (uv Dose) Distribution Assessment of Uv-C Light at 254 Nm on Food Surfaces Using Radiochromic Film Dosimetry Integrated With Image Processing and Convolutional Neural Network (cnn)
    (Elsevier Sci Ltd, 2023) Cankal, Yadigar Seyfi; Ünlütürk, Mehmet S.; Ünlütürk, Sevcan
    Uniform Fluence (UV Dose) distribution on food surfaces is essential for an effective UV process design. In this study, the use of radiochromic films (RCFs) with a computer vision system (CVS) integrating image processing and Convolutional Neural Network (CNN) is proposed as an alternative method to assess Fluence distribution of UV-C light at 254 nm on food surfaces. The color difference of RCFs exposed to different UV irradiance and exposure times was correlated with Fluence. The validity of the developed methodology was proved by applying it to the surface of apple fruits of different shapes and sizes. A linear relationship was found between the color difference of RCF and Fluence. The maximum Fluence to be determined using RCFs was similar to 60 mJ/cm(2). The color of the films after UV irradiation remained stable for up to 15 days in darkness when stored at room and refrigeration temperatures. The results showed that RCF can be used as an alternative UV dosimeter.