Optimization of fish osmotic treatment applying fuzzy synthetic evaluation method

Abstract

© 2019, Consulting and Training Center - KEY. All rights reserved. Osmotic treatment is used alone or in combination with other drying methods to reduce water content in food and increase its sustainability. Due to the many advantages over traditional drying processes, the osmotic treatment is increasingly being used in the food industry as a preservative method. The complexity of the process causes nonlinear optimization problems and sometimes it is difficult to determine the inter-dependencies between dependent and independent variables. However, by using improved mathematical models and optimization algorithms, it is possible to technologically improve and plan the production process. For this experiment three different osmotic solutions (sugar beet molasses (OS1), aqueous solution of sodium chloride (OS2) and sucrose and the blend of OS1 and OS2 in a 1: 1 ratio (OS3) were used for osmotic drying treatment of fish meat (Carassius gibelio). The treatment was performed for 5 hours, under atmospheric pressure, at four different temperatures. This work is concerned with determination of the optimum drying conditions by using Fuzzy synthetic evaluation-FSE. The optimization of eight response variables (water loss-WL, solid gain-SG, aw, dry matter content-DM and mineral content (K, Na, Ca, Mg) was based on models already developed by second order polynomial-SOP and artificial neural network-ANN. The function maximum F represents the optimal values of the dependent variables and for OS1 was 0.34, 0.36, 0.36, 0.35, for OS2: 0.52, 0.57, 0.60, 0.62 and for OS3: 0.69, 0.74, 0.80 and 0.88. Value of this function that is closer to 1 shows that process parameters are optimal. It can be concluded that by using the FSE method the optimum values of the process parameters for the OS1 were at lower temperatures and at lower concentrations, while for the OS2 and OS3 the optimal values were reached at the maximum observed temperature range and concentrations.Osmotic treatment is used alone or in combination with other drying methods to reduce water content in food and increase its sustainability. Due to the many advantages over traditional drying processes, the osmotic treatment is increasingly being used in the food industry as a preservative method. The complexity of the process causes nonlinear optimization problems and sometimes it is difficult to determine the inter-dependencies between dependent and independent variables. However, by using improved mathematical models and optimization algorithms, it is possible to technologically improve and plan the production process. For this experiment three different osmotic solutions (sugar beet molasses (OS1), aqueous solution of sodium chloride (OS2) and sucrose and the blend of OS1 and OS2 in a 1: 1 ratio (OS3) were used for osmotic drying treatment of fish meat (Carassius gibelio). The treatment was performed for 5 hours, under atmospheric pressure, at four different temperatures. This work is concerned with determination of the optimum drying conditions by using Fuzzy synthetic evaluation-FSE. The optimization of eight response variables (water loss-WL, solid gain-SG, aw, dry matter content-DM and mineral content (K, Na, Ca, Mg) was based on models already developed by second order polynomial-SOP and artificial neural network-ANN. The function maximum F represents the optimal values of the dependent variables and for OS1 was 0.34, 0.36, 0.36, 0.35, for OS2: 0.52, 0.57, 0.60, 0.62 and for OS3: 0.69, 0.74, 0.80 and 0.88. Value of this function that is closer to 1 shows that process parameters are optimal. It can be concluded that by using the FSE method the optimum values of the process parameters for the OS1 were at lower temperatures and at lower concentrations, while for the OS2 and OS3 the optimal values were reached at the maximum observed temperature range and concentrations.