Volume 15, Issue 83 (2018)                   FSCT 2018, 15(83): 237-250 | Back to browse issues page

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Evaluation and prediction of mechanical properties of potato during storage by laser light backscattering imaging. FSCT 2018; 15 (83) :237-250
URL: http://fsct.modares.ac.ir/article-7-20228-en.html
Abstract:   (4925 Views)
In this research, changes in potato texture during storage were evaluated by laser light backscattering imaging method and using physical and mathematical models according to the results of mechanical destructive tests. Using the characteristics of the images, we tried to develop models for predicting the mechanical properties of potatoes. At first, the backscattering images taken from 594 potatoes. Backscattering profiles obtained for each sample. Cylindrical samples extracted from potatoes and subjected to uniaxial compression test. By fitting the first order Gaussian model to the obtained data from the final image and calculating the frequency of repetition of different intensities in the images, the parameters related to the absorption and scattering of reflected light from the tissue of the tubers obtained at three wavelengths of 650 nm, 780 nm and 980 nm and in six months of the cold storage. The behavior comparison of the mechanical test results and the changes in the Gaussian model fitting estimated parameters and the intensity frequencies during storage showed the effect of mechanical structure changes on the optical properties of the samples. Five models with satisfactory results obtained to predict the tangent modulus of elasticity (R=0.827, 0.815), secant modulus of elasticity (R=0.808), toughness (R=0.874), maximum fracture force (R=0.811) with the fuzzy-neural inference system. The results in this study could mainly useful for understanding the effect of tissue changes during storage on light scattering and absorption. It can be useful to design high-performance sensors and quality determination systems for non-destructive mechanical properties evaluation of potato tubers.
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Article Type: Original paper | Subject: Food quality control
Received: 2017/11/14 | Accepted: 2018/01/20 | Published: 2019/01/15

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