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Information Journal Paper

Title

Determination of Viscoelastic model of sour orange during storage using image processing

Pages

  91-103

Abstract

 The mechanical properties of fruit are one of the most important determinants of standards for designing, transforming, processing, and packaging systems. One of the methods for changes demonstraction in the internal structure of fruits during Storage is to perform stress relaxation tests in different predetermined strains. Therefore, the purpose of this study was to investigate the orange compression behavior in quasi-static mechanical loadings by performing stress-relaxation tests of samples at predetermined levels of strain and modeling the Maxwell and Peleg method and comparing it with image processing method. In addition, in this study, cross-sectional area changes were measured during loading by image processing. The modulus of elasticity in the image processing method, the Maxwell model and the Peleg model on days 0 to 9 increased from 3. 91 to 4. 5, 3. 6 to 4. 53 and 2. 7 to 3. 45, respectively. which in spite of increasing trend there was no significant difference between them. Since, no significant difference in the output of these two models (Maxwell and Peleg) was observed Peleg with the less number of elements (only two constants) was preferred compared to Maxwell method.

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  • Cite

    APA: Copy

    Kazemi Karaji, F., & ABDANAN MEHDIZADEH, S.. (2019). Determination of Viscoelastic model of sour orange during storage using image processing. IRANIAN JOURNAL OF FOOD SCIENCE AND TECHNOLOGY, 16(94 ), 91-103. SID. https://sid.ir/paper/72702/en

    Vancouver: Copy

    Kazemi Karaji F., ABDANAN MEHDIZADEH S.. Determination of Viscoelastic model of sour orange during storage using image processing. IRANIAN JOURNAL OF FOOD SCIENCE AND TECHNOLOGY[Internet]. 2019;16(94 ):91-103. Available from: https://sid.ir/paper/72702/en

    IEEE: Copy

    F. Kazemi Karaji, and S. ABDANAN MEHDIZADEH, “Determination of Viscoelastic model of sour orange during storage using image processing,” IRANIAN JOURNAL OF FOOD SCIENCE AND TECHNOLOGY, vol. 16, no. 94 , pp. 91–103, 2019, [Online]. Available: https://sid.ir/paper/72702/en

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