Fadiji Tobi, Ashtiani Seyed-Hassan Miraei, Onwude Daniel I, Li Zhiguo, Opara Umezuruike Linus
Africa Institute for Postharvest Technology, South African Research Chair in Postharvest Technology, Postharvest Technology Research Laboratory, Faculty of AgriSciences, Stellenbosch University, Stellenbosch 7602, South Africa.
Department of Biosystems Engineering, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad 91779-48974, Iran.
Foods. 2021 Apr 16;10(4):869. doi: 10.3390/foods10040869.
Freezing is a well-established preservation method used to maintain the freshness of perishable food products during storage, transportation and retail distribution; however, food freezing is a complex process involving simultaneous heat and mass transfer and a progression of physical and chemical changes. This could affect the quality of the frozen product and increase the percentage of drip loss (loss in flavor and sensory properties) during thawing. Numerical modeling can be used to monitor and control quality changes during the freezing and thawing processes. This technique provides accurate predictions and visual information that could greatly improve quality control and be used to develop advanced cold storage and transport technologies. Finite element modeling (FEM) has become a widely applied numerical tool in industrial food applications, particularly in freezing and thawing processes. We review the recent studies on applying FEM in the food industry, emphasizing the freezing and thawing processes. Challenges and problems in these two main parts of the food industry are also discussed. To control ice crystallization and avoid cellular structure damage during freezing, including physicochemical and microbiological changes occurring during thawing, both traditional and novel technologies applied to freezing and thawing need to be optimized. Mere experimental designs cannot elucidate the optimum freezing, frozen storage, and thawing conditions. Moreover, these experimental procedures can be expensive and time-consuming. This review demonstrates that the FEM technique helps solve mass and heat transfer equations for any geometry and boundary conditions. This study offers promising insight into the use of FEM for the accurate prediction of key information pertaining to food processes.
冷冻是一种成熟的保存方法，用于在储存、运输和零售分销过程中保持易腐食品的新鲜度；然而，食品冷冻是一个复杂的过程，涉及同时进行的传热和传质以及一系列物理和化学变化。这可能会影响冷冻产品的质量，并增加解冻过程中的滴水损失百分比（风味和感官特性的损失）。数值建模可用于监测和控制冷冻和解冻过程中的质量变化。该技术提供准确的预测和可视化信息，可大大改善质量控制，并用于开发先进的冷藏和运输技术。有限元建模（FEM）已成为工业食品应用中广泛应用的数值工具，特别是在冷冻和解冻过程中。我们回顾了最近在食品工业中应用有限元建模的研究，重点是冷冻和解冻过程。还讨论了食品工业这两个主要部分中的挑战和问题。为了在冷冻过程中控制冰晶形成并避免细胞结构受损，包括解冻过程中发生的物理化学和微生物变化，应用于冷冻和解冻的传统技术和新技术都需要优化。单纯的实验设计无法阐明最佳的冷冻、冷冻储存和解冻条件。此外，这些实验程序可能既昂贵又耗时。这篇综述表明，有限元建模技术有助于求解任何几何形状和边界条件下的质量和传热方程。这项研究为使用有限元建模准确预测与食品加工相关的关键信息提供了有前景的见解。
