Dynamic Modelling and Simulation of Food Systems

Edited by
February 2023
252 pages
  • ISBN978-3-0365-6692-4 (Hardback)
  • ISBN978-3-0365-6693-1 (PDF)

This book is a reprint of the Special Issue Dynamic Modelling and Simulation of Food Systems that was published in

Biology & Life Sciences
Chemistry & Materials Science
Public Health & Healthcare

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.

  • Hardback
© 2022 by the authors; CC BY-NC-ND license
food safety; predictive microbiology; mathematical models; microbial inactivation; sublethal injury; bioprocess engineering; fermentation process; batch bioreactors; dynamical non-linear mathematical model; model identification; particle swarm optimization; simulation; Carnobacterium maltaromaticum; modeling; microbial growth; optimization; fermentation; temperature-dependent thermal properties; scaled sensitivity coefficient; TPCell; parameter estimation; inverse problems; predictive microbiology; food microstructure; food safety; mathematical models; electronic nose; Shewanella putrefaciens; dynamic growth; spoilage prediction; GC-MS; food safety; acrylamide formation; thermal resistance; dynamic models; simulation; predictive microbiology; FSSP; DoE; smoke; fermentation; fish; wine fermentation; nitrogen; mathematical modeling; population model; maintenance; variable yield; underutilized wild species; mathematical modeling; lycopene; viscosity; thermal processing; color; mathematical modelling; fish quality; fish freshness; bibliometric analysis; predictive microbiology; stress variables; quality degradation; parameter estimation; mathematical modeling; beer fermentation; food industry; multi-objective optimization; model-based optimization; equivalent solutions; uncertainty; Monte Carlo; frying operation; acrylamide; quality; n/a