Mohammad Reza Amiryousefi; Mohebbat Mohebbi; Faramarz Khodaiyan
Abstract
Analysis of food surfaces is of interest because many processes depend on their complexity. Food surfaces show several textural characteristics related to their nature, composition and processing. Food surface images and their microscopic details need to be translated into numerical data before engineering ...
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Analysis of food surfaces is of interest because many processes depend on their complexity. Food surfaces show several textural characteristics related to their nature, composition and processing. Food surface images and their microscopic details need to be translated into numerical data before engineering analysis. Fractal geometry is a novel concept to describe the complexity of natural shapes. In order to introduce a nondestructive method estimating the effect of process conditions on ostrich meat plates’ surface, in this research an image analysis technique was applied and the concept of fractal dimension was used to quantity the changes. Results show that fractal dimensions of the surfaces decreased with frying. Furthermore, with the increase in frying temperature, frying time and power of microwave pretreatment, a growing procedure in fractal dimension was observed. Fractal dimension as a quantity index could describe the shrinkage of deep-fried ostrich meat as a physical property.
Mohammad Reza Amiryousefi; Mohebbat Mohebbi
Abstract
Osmotic dehydration, as a minimal processing method, has found increasingly wide prospects during the past few decades. This process involves mass transfer which is commonly modeled by applications of different procedures, mostly based on Fick's law. In this research, we approached the modeling process ...
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Osmotic dehydration, as a minimal processing method, has found increasingly wide prospects during the past few decades. This process involves mass transfer which is commonly modeled by applications of different procedures, mostly based on Fick's law. In this research, we approached the modeling process by first obtaining experimental measurement of potato’s solid gain, water loss and moisture content under different conditions of solution concentrations ( 5, 10 and 15% w/w), temperatures (30, 40 and 60oC) , potato to solution ratio (1:6, 1:8 and 1:10) as well as time intervals (1, 2, 3 & 4h). In order to evaluate the effect of changes in operational parameters on mass transfer kinetics, sensitivity analysis was performed. Artificial neural networks (ANN) was applied for modeling. The results exhibited how much powerful the model is in prediction of the system’s outputs, and high sensitiveness of these outputs to the ratio of potato to osmotic solution.
Keywords: Potato, Osmotic dehydration, Sensitivity analysis, Artificial neural networks
