{"title":"Model-based prediction of frost formation inside frozen food packages under temperature fluctuations","authors":"K. Nakagawa, Maya Nakabayashi, Toshiko Yasunobu","doi":"10.1515/ijfe-2023-0222","DOIUrl":null,"url":null,"abstract":"\n Frozen storage of food products is widely accepted not only in the industry but also by households. Frost formation during long-term storage is recognized as a phenomenon that causes changes in product characteristics and quality losses. However, quantitative prediction and control of frost formation remains a challenge. In this study, a mathematical model was developed to predict frost formation inside frozen food products (i.e., frozen minced meat packed in a polyvinylidene chloride (PVDC) film) under fluctuating temperature conditions in a domestic refrigerator. The proposed model is based on heat transfer and energy balance equations, and the amount of frost formation is estimated from the heat generated by condensation. The heat transfer coefficients were experimentally obtained and applied to the developed model. The interactions between the amplitude and frequency of temperature fluctuations and the corresponding amount of frost formation were visualized using contour plots. Both the amplitude and frequency were found to increase frost formation. For the range of fluctuations tested (temperature amplitudes of 0.5–2.5 K and cooling rates of 0.0125–0.2 K/min when connected to the compressor), the simulation predicted that the amount of frost in the packages varied up to approximately 4.5 times (0.48–2.18 g/month for packages containing 300 g of minced meat) depending on the different temperature fluctuation settings.","PeriodicalId":49054,"journal":{"name":"International Journal of Food Engineering","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Food Engineering","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1515/ijfe-2023-0222","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Frozen storage of food products is widely accepted not only in the industry but also by households. Frost formation during long-term storage is recognized as a phenomenon that causes changes in product characteristics and quality losses. However, quantitative prediction and control of frost formation remains a challenge. In this study, a mathematical model was developed to predict frost formation inside frozen food products (i.e., frozen minced meat packed in a polyvinylidene chloride (PVDC) film) under fluctuating temperature conditions in a domestic refrigerator. The proposed model is based on heat transfer and energy balance equations, and the amount of frost formation is estimated from the heat generated by condensation. The heat transfer coefficients were experimentally obtained and applied to the developed model. The interactions between the amplitude and frequency of temperature fluctuations and the corresponding amount of frost formation were visualized using contour plots. Both the amplitude and frequency were found to increase frost formation. For the range of fluctuations tested (temperature amplitudes of 0.5–2.5 K and cooling rates of 0.0125–0.2 K/min when connected to the compressor), the simulation predicted that the amount of frost in the packages varied up to approximately 4.5 times (0.48–2.18 g/month for packages containing 300 g of minced meat) depending on the different temperature fluctuation settings.
期刊介绍:
International Journal of Food Engineering is devoted to engineering disciplines related to processing foods. The areas of interest include heat, mass transfer and fluid flow in food processing; food microstructure development and characterization; application of artificial intelligence in food engineering research and in industry; food biotechnology; and mathematical modeling and software development for food processing purposes. Authors and editors come from top engineering programs around the world: the U.S., Canada, the U.K., and Western Europe, but also South America, Asia, Africa, and the Middle East.