Dynamic Modelling and Simulation of Food Systems

Several factors influence consumers' choices of food products. While price remains the main criterion, quality, pleasure, convenience, and health are also important driving factors in food market evolution. Food enterprises are making significant efforts to manufacture products that meet consu...

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Bibliographic Details
Other Authors: Vilas, Carlos (Editor), García, Míriam R. (Editor), Egea, Jose A. (Editor)
Format: Electronic Book Chapter
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
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Online Access:DOAB: download the publication
DOAB: description of the publication
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100 1 |a Vilas, Carlos  |4 edt 
700 1 |a García, Míriam R.  |4 edt 
700 1 |a Egea, Jose A.  |4 edt 
700 1 |a Vilas, Carlos  |4 oth 
700 1 |a García, Míriam R.  |4 oth 
700 1 |a Egea, Jose A.  |4 oth 
245 1 0 |a Dynamic Modelling and Simulation of Food Systems 
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520 |a Several factors influence consumers' choices of food products. While price remains the main criterion, quality, pleasure, convenience, and health are also important driving factors in food market evolution. Food enterprises are making significant efforts to manufacture products that meet consumers' demands without compromising on safety standards. Additionally, the food industry also aims to improve the efficiency of transformation and conservation processes by minimizing energy consumption, process duration, and waste generation. However, foods are highly complex systems in which: (i) Non-linear dynamics and interactions among different temporal and spatial scales must be considered; (ii) A wide range of physical phenomena occur; (iii) Different food matrices, with different microstructures and properties are involved; and (iv) The number of quality and safety indicators (such as bacteria, total volatile basic nitrogen, color, texture, odor, and sensory characteristics) is substantial. Mathematical modeling and simulation are key elements that allow us to gain a deeper understanding of food processes and enable the use of tools such as optimization and real-time control to improve their efficiency. This Special Issue gathers research on the development of dynamic mathematical models that describe the relevant factors in food processes, and model-based tools to improve such processes. The contributions published in this Special Issue can be grouped into two categories: the evolution of safety and quality indicators in unprocessed food systems, and transformation and preservation processes. 
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546 |a English 
650 7 |a Technology: general issues  |2 bicssc 
650 7 |a History of engineering & technology  |2 bicssc 
653 |a food safety 
653 |a predictive microbiology 
653 |a mathematical models 
653 |a microbial inactivation 
653 |a sublethal injury 
653 |a bioprocess engineering 
653 |a fermentation process 
653 |a batch bioreactors 
653 |a dynamical non-linear mathematical model 
653 |a model identification 
653 |a particle swarm optimization 
653 |a simulation 
653 |a Carnobacterium maltaromaticum 
653 |a modeling 
653 |a microbial growth 
653 |a optimization 
653 |a fermentation 
653 |a temperature-dependent thermal properties 
653 |a scaled sensitivity coefficient 
653 |a TPCell 
653 |a parameter estimation 
653 |a inverse problems 
653 |a food microstructure 
653 |a electronic nose 
653 |a Shewanella putrefaciens 
653 |a dynamic growth 
653 |a spoilage prediction 
653 |a GC-MS 
653 |a acrylamide formation 
653 |a thermal resistance 
653 |a dynamic models 
653 |a FSSP 
653 |a DoE 
653 |a smoke 
653 |a fish 
653 |a wine fermentation 
653 |a nitrogen 
653 |a mathematical modeling 
653 |a population model 
653 |a maintenance 
653 |a variable yield 
653 |a underutilized wild species 
653 |a lycopene 
653 |a viscosity 
653 |a thermal processing 
653 |a color 
653 |a mathematical modelling 
653 |a fish quality 
653 |a fish freshness 
653 |a bibliometric analysis 
653 |a stress variables 
653 |a quality degradation 
653 |a beer fermentation 
653 |a food industry 
653 |a multi-objective optimization 
653 |a model-based optimization 
653 |a equivalent solutions 
653 |a uncertainty 
653 |a Monte Carlo 
653 |a frying operation 
653 |a acrylamide 
653 |a quality 
653 |a n/a 
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856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/98844  |7 0  |z DOAB: description of the publication