García Míriam R, Ferez-Rubio Jose Antonio, Vilas Carlos
Research Group on Biosystems and Bioprocess Engineering (Bio2eng), IIM-CSIC, 36208 Vigo, Spain.
Research Group on Microbiology and Quality of Fruit and Vegetables, CEBAS-CSIC, 30100 Murcia, Spain.
Foods. 2022 Aug 2;11(15):2312. doi: 10.3390/foods11152312.
Fish freshness can be considered as the combination of different nutritional and organoleptic attributes that rapidly deteriorate after fish capture, i.e., during processing (cutting, gutting, packaging), storage, transport, distribution, and retail. The rate at which this degradation occurs is affected by several stress variables such as temperature, water activity, or pH, among others. The food industry is aware that fish freshness is a key feature influencing consumers' willingness to pay for the product. Therefore, tools that allow rapid and reliable assessment and prediction of the attributes related to freshness are gaining relevance. The main objective of this work is to provide a comprehensive review of the mathematical models used to describe and predict the changes in the key quality indicators in fresh fish and shellfish during storage. The work also briefly describes such indicators, discusses the most relevant stress factors affecting the quality of fresh fish, and presents a bibliometric analysis of the results obtained from a systematic literature search on the subject.
鱼类的新鲜度可被视为不同营养和感官属性的综合体现,这些属性在鱼被捕捞后,即在加工(切割、去内脏、包装)、储存、运输、分销和零售过程中会迅速恶化。这种降解发生的速率受几个应激变量的影响,如温度、水分活度或pH值等。食品行业意识到鱼类新鲜度是影响消费者为产品支付意愿的关键特征。因此,能够快速且可靠地评估和预测与新鲜度相关属性的工具正变得越来越重要。这项工作的主要目标是全面综述用于描述和预测新鲜鱼和贝类在储存期间关键质量指标变化的数学模型。该工作还简要描述了这些指标,讨论了影响鲜鱼质量的最相关应激因素,并对从关于该主题的系统文献检索中获得的结果进行了文献计量分析。