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用于监测食品质量的保质期预测模型的最新进展。

Recent advances in shelf life prediction models for monitoring food quality.

作者信息

Cui Fangchao, Zheng Shiwei, Wang Dangfeng, Tan Xiqian, Li Qiuying, Li Jianrong, Li Tingting

机构信息

College of Food Science and Technology, Bohai University; National & Local Joint Engineering Research Center of Storage, Processing and Safety Control Technology for Fresh Agricultural and Aquatic Products, Jinzhou, China.

College of Food Science and Technology, Jiangnan University, Wuxi, China.

出版信息

Compr Rev Food Sci Food Saf. 2023 Mar;22(2):1257-1284. doi: 10.1111/1541-4337.13110. Epub 2023 Jan 30.

Abstract

Each year, 1.3 billion tons of food is lost due to spoilage or loss in the supply chain, accounting for approximately one third of global food production. This requires a manufacturer to provide accurate information on the shelf life of the food in each stage. Various models for monitoring food quality have been developed and applied to predict food shelf life. This review classified shelf life models and detailed the application background and characteristics of commonly used models to better understand the different uses and aspects of the commonly used models. In particular, the structural framework, application mechanisms, and numerical relationships of commonly used models were elaborated. In addition, the study focused on the application of commonly used models in the food field. Besides predicting the freshness index and remaining shelf life of food, the study addressed aspects such as food classification (maturity and damage) and content prediction. Finally, further promotion of shelf life models in the food field, use of multivariate analysis methods, and development of new models were foreseen. More reliable transportation, processing, and packaging methods could be screened out based on real-time food quality monitoring.

摘要

每年,有13亿吨食物因供应链中的变质或损耗而损失,约占全球粮食产量的三分之一。这就要求制造商提供每个阶段食品保质期的准确信息。已经开发并应用了各种监测食品质量的模型来预测食品保质期。本综述对保质期模型进行了分类,并详细介绍了常用模型的应用背景和特点,以便更好地理解常用模型的不同用途和方面。特别是,阐述了常用模型的结构框架、应用机制和数值关系。此外,该研究聚焦于常用模型在食品领域的应用。除了预测食品的新鲜度指数和剩余保质期外,该研究还涉及食品分类(成熟度和损伤)及含量预测等方面。最后,预计将进一步推广食品领域的保质期模型,运用多变量分析方法,并开发新模型。基于实时食品质量监测,可以筛选出更可靠的运输、加工和包装方法。

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