A multi-criteria decision making approach for food engineering

The objective of this study was to propose a decision making approach and tools (software packages) to solve the multi-criteria decision making problems arising in the food engineering. The proposed decision making approach is based on a simultaneous utilization for a given set of Pareto-optimal solutions the two following decision making methods: 1) well-known Analytic Hierarchy Process method and 2) Tabular Method. The using of Tabular Method allows utilizing the AHP method in a straightforward manner, which avoids the information overload and makes the decision making process easier. The aggregating functions approach, adaptive random search algorithm coupled with penalty functions approach, and the finite difference method with cubic spline approximation were utilized in this study to compute the initial set of the Pareto-optimal solutions. The decision making software ―MPRIORITY‖ and ―T-CHOICE‖ based on the Analytic Hierarchy Process and Tabular Method methods, respectively, were utilized for choosing the best alternative among the obtained set of Pareto-optimal solutions. The proposed in this study approach and tools was successfully tested on the multi-objective optimization problem of the thermal processing of packaged food. The proposed decision making approach and tools are useful for food scientists (research and education) and engineers (real thermal food process evaluation and optimization)

Thermal food processing computation software

The objective of this research consisted of developing the two following thermal food processing software: “F-CALC” is software developed to carry out thermal process calculations based on the well-known Ball's formula method, and “OPT-PROx” is software for thermal food processing optimization based on variable retort temperature processing and global optimization technique. Time-temperature data loaded from Excel-file is used by “F-CALC” software to evaluate the heat penetration parameters jh and fh, as well as to compute process lethality for given process time or vice versa. The possibility of computing the process time and lethality for broken heating curves is included. The diversity of thermal food processing optimization problems with different objectives and required constraints are solvable by “OPT-PROx” software. The adaptive random search algorithm coupled with penalty functions approach, and the finite difference method with cubic spline approximation are utilized by “OPT-PROx” for simulation and optimization thermal food processes. The possibility of estimating the thermal diffusivity coefficient based on the mean squared error function minimization is included. The “OPT-PROx” software was successfully tested on the real thermal food processing problems, namely in the case of total process time minimization with a constraint for average and surface retentions the “OPT-PROx” demonstrates significant advantage over the traditional constant temperature processes in terms of process time and final product quality. The developed user friendly dialogue and used numerical procedures make the “F-CALC” and “OPT-PROx” software extremely useful for food scientists (research and education) and engineers (real thermal food process evaluation and optimization)

Variable retort temperature optimization benefit in scheduling for retorts of different capacities in food canneries

In the majority of small- to medium-sized canneries, retorting is carried out in a battery of retorts as a batch process. For such canneries, the unloading and reloading operations for each retort are labor-intensive; therefore, a well-designed and well-managed plant should be utilized in order to optimize the whole sterilization process. In other words, it is necessary to develop a suitable mathematical model for the operation of the whole plant and to determine the optimal values of its decision variables. The result of such a model involves the quantities of each product to be loaded onto the retorts for each of the batches, and the optimal solution provides an optimum scheduling. On the other hand, it is well-known that variable retort temperature processing can be used for reducing the sterilization processing time required for sterilization using the traditional constant retort temperature processing. Therefore, the objective of this research consisted of utilizing a variable retort temperature processing in developing a mathematical model for scheduling at food canneries for the case of retorts of different capacities. The developed model was based on mixed-integer linear programming and simultaneous sterilization based on variable retort temperature processing. The adaptive random search algorithm coupled with penalty functions approach, and the finite difference method with cubic spline approximation are utilized in this study to obtain the simultaneous sterilization vectors to be processed under time-variable retort temperature. The proposed in this study methodology can be useful for small- and medium-sized food canneries, which work with many different products simultaneously

Software packages for food engineering needs

The graphic user interface (GUI) software packages “ANNEKs” and “OPT-PROx” are developed to meet food engineering needs. “OPT-RROx” (OPTimal PROfile) is software developed to carry out thermal food processing optimization based on the variable retort temperature processing and global optimization technique. “ANNEKs” (Artificial Neural Network Enzyme Kinetics) is software designed for determining the kinetics of enzyme hydrolysis of protein at different initial reaction parameters based on the Artificial Neural Network’s and adaptive random search algorithm. The “OPT-PROx” software was successfully tested on the real thermal food processing problems, and has demonstrated a significant advantage over the traditionally used constant temperature processes in terms of total processing time and final product quality. The “ANNEKs” software can be effectively used for process design of enzyme hydrolysis of protein. The proposed in this research user friendly dialogue software can be useful for food scientists and engineers

Algorithm and software for modelling of food protein hydrolysis kinetic

The objective of this research was to propose two numerical approaches and based on these approaches user-friendly dialogue software for determining the kinetics of enzyme hydrolysis of protein at different initial reaction parameters, which could be an initial substrate and enzyme concentrations, temperature and pH-value. The proposed approaches mainly are based on the utilization of adaptive random search technique, Artificial Neural Networks (ANNs) and the following well-known exponential kinetic equation presented a relationship between reaction rate and enzymatic reaction parameters dh/dt = aexp(-bh), where coefficients a and b have different expressions according to different reaction mechanism. The first approach consists of using the adaptive random search technique for fitting the kinetic constants of enzymatic reactions to a set of given experimental or time course profiles (TCPs) in the form of degree of hydrolysis over reaction time. Use of this technique can give much greater confidence that if a global optimal solution had existed within the global domain then it would not have been missed by the search routine. The second approach uses ANNs for estimating the values of coefficients a and b of the exponential kinetic equation. In this case each of experimental TCPs is fitted to this equation by using adaptive random search technique. Optimal a and b values obtained for TCPs and initial enzymatic reaction parameters are used as an input data for the ANNs learning process. The user-friendly dialogue software “ANNEKs” (ANN Enzyme Kinetics) realized two mentioned above approaches is developed. Findings from the work reported in this study would suggest that the developed user-friendly interfaces and utilized numerical approaches make the “ANNEKs” software package useful for food scientists and engineers

A multi-criteria optimization and decision-making approach for improvement of food engineering processes.

The objective of this study was to propose a multi-criteria optimization and decision-making technique to solve food engineering problems. This technique was demostrated using experimental data obtained on osmotic dehydratation of carrot cubes in a sodium chloride solution. The Aggregating Functions Approach, the Adaptive Random Search Algorithm, and the Penalty Functions Approach were used in this study to compute the initial set of non-dominated or Pareto-optimal solutions. Multiple non-linear regression analysis was performed on a set of experimental data in order to obtain particular multi-objective functions (responses), namely water loss, solute gain, rehydration ratio, three different colour criteria of rehydrated product, and sensory evaluation (organoleptic quality). Two multi-criteria decision-making approaches, the Analytic Hierarchy Process (AHP) and the Tabular Method (TM), were used simultaneously to choose the best alternative among the set of non-dominated solutions. The multi-criteria optimization and decision-making technique proposed in this study can facilitate the assessment of criteria weights, giving rise to a fairer, more consistent, and adequate final compromised solution or food process. This technique can be useful to food scientists in research and education, as well as to engineers involved in the improvement of a variety of food engineering processes

Control of a solar dryer through using a fuzzy logic and low-cost model-based sensor

Solar drying is one of the important processes used for extending the shelf life of agricultural products. Regarding consumer requirements, solar drying should be more suitable in terms of curtailing total drying time and preserving product quality. Therefore, the objective of this study was to develop a fuzzy logic-based control system, which performs a ?human-operator-like? control approach through using the previously developed low-cost model-based sensors. Fuzzy logic toolbox of MatLab and Borland C++ Builder tool were utilized to develop a required control system. An experimental solar dryer, constructed by CONA SOLAR (Austria) was used during the development of the control system. Sensirion sensors were used to characterize the drying air at different positions in the dryer, and also the smart sensor SMART-1 was applied to be able to include the rate of wood water extraction into the control system (the difference of absolute humidity of the air between the outlet and the inlet of solar dryer is considered by SMART-1 to be the extracted water). A comprehensive test over a 3 week period for different fuzzy control models has been performed, and data, obtained from these experiments, were analyzed. Findings from this study would suggest that the developed fuzzy logic-based control system is able to tackle difficulties, related to the control of solar dryer process

Control of a solar dryer through using a fuzzy logic and low-cost model-based sensor

Abstract Solar drying is one of the important processes used for extending the shelf life of agricultural products. Regarding consumer requirements, solar drying should be more suitable in terms of curtailing total drying time and preserving product quality. Therefore, the objective of this study was to develop a fuzzy logic-based control system, which performs a ''humanoperator-like'' control approach through using the previously developed low-cost modelbased sensors. Fuzzy logic toolbox of MatLab and Borland C++ Builder tool were utilized to develop a required control system. An experimental solar dryer, constructed by CONA SOLAR (Austria) was used during the development of the control system. Sensirion sensors were used to characterize the drying air at different positions in the dryer, and also the smart sensor SMART-1 was applied to be able to include the rate of wood water extraction into the control system (the difference of absolute humidity of the air between the outlet and the inlet of solar dryer is considered by SMART-1 to be the extracted water). A comprehensive test over a 3 week period for different fuzzy control models has been performed, and data, obtained from these experiments, were analyzed. Findings from this study would suggest that the developed fuzzy logic-based control system is able to tackle difficulties, related to the control of solar dryer process