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Recent advances in shelf life prediction models for monitoring food quality.
Cui, Fangchao; Zheng, Shiwei; Wang, Dangfeng; Tan, Xiqian; Li, Qiuying; Li, Jianrong; Li, Tingting.
Afiliación
  • Cui F; 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.
  • Zheng S; 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.
  • Wang D; 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.
  • Tan X; College of Food Science and Technology, Jiangnan University, Wuxi, China.
  • Li Q; 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.
  • Li J; 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.
  • Li T; 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.
Compr Rev Food Sci Food Saf ; 22(2): 1257-1284, 2023 03.
Article en En | MEDLINE | ID: mdl-36710649
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Calidad de los Alimentos / Almacenamiento de Alimentos Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Compr Rev Food Sci Food Saf Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Calidad de los Alimentos / Almacenamiento de Alimentos Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Compr Rev Food Sci Food Saf Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos