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Design of Predictive Tools to Estimate Freshness Index in Farmed Sea Bream (Sparus aurata) Stored in Ice

机译:冰中养殖的鲷鱼(Sparus aurata)新鲜度指数预测工具的设计

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摘要

This research studied sea bream freshness evolution through storage time in ice by determining different quality parameters and sensory profiles. Predictive models for freshness index, storage time, and microbial counts were designed from these data. Physico–chemical parameters were assessed to evaluate the quality of fish; microbial growth was controlled to ensure food safety, and sensory analyses were carried out to characterize quality deterioration. Predictive models were developed and improved with the aim of being used as tools for quality management in the seafood industry. Validation was conducted in order to establish the accuracy of models. There was a good relationship between the physico–chemical and microbiological parameters. Sensory analysis and microbial counts allowed for the establishment of a shelf-life of 10 days, which corresponded to a poor quality (according to the European Community’s system of grading fish for marketing purposes), with a freshness index lower than 50%. Sensory profiles showed that gill and flesh texture were the most vulnerable attributes during storage in ice related to spoilage. The predictive models for the freshness index (%) and ice storage time (h) exhibited an accuracy close to 90% following practical validation.
机译:这项研究通过确定不同的质量参数和感官特征,研究了鲷鱼在冰中的储存时间的新鲜度演变。根据这些数据设计了新鲜指数,储存时间和微生物数量的预测模型。评估了理化参数以评估鱼的质量;控制微生物的生长以确保食品安全,并进行了感官分析以表征质量下降。开发并改进了预测模型,旨在将其用作海产品行业质量管理的工具。进行验证以建立模型的准确性。理化和微生物学参数之间存在良好的关系。感官分析和微生物计数可以确定10天的保质期,这对应于质量差(根据欧洲共同体用于销售目的的鱼分级系统),新鲜指数低于50%。感官特征表明,g和果肉质地是冰中与腐败相关的最易受伤害的属性。经过实际验证,新鲜度指数(%)和冰存储时间(h)的预测模型显示出接近90%的精度。

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