Volume 16, Issue 94 (2019)                   FSCT 2019, 16(94): 91-103 | Back to browse issues page

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Kazemi Karaji F, Abdanan Mehdizadeh S. Determination of Viscoelastic model of sour orange during storage using image processing. FSCT 2019; 16 (94) :91-103
URL: http://fsct.modares.ac.ir/article-7-33054-en.html
1- MSc student of Mechanics of Biosystems Engineering Department, Faculty of Agricultural Engineering andRural Development, Khuzestan Agricultural Sciences and Natural Resources University. Khouzestan,
2- Assistant professor of Mechanics of Biosystems Engineering Department, Faculty of Agricultural Engineering and Rural Development, Khuzestan Agricultural Sciences and Natural Resources University. , saman.abdanan@gmail.com
Abstract:   (4554 Views)
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 changesdemonstraction 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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Article Type: Original Research | Subject: Mechanical properties of food
Received: 2019/05/17 | Accepted: 2019/12/23 | Published: 2019/12/1

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