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首页> 外文期刊>Progress in Artificial Intelligence >Design of Predictive Tools to Estimate Freshness Index in Farmed Sea Bream (Sparus aurata) Stored in Ice
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Design of Predictive Tools to Estimate Freshness Index in Farmed Sea Bream (Sparus aurata) Stored in Ice

机译:估算冰中养殖鲷鱼的新鲜度指数的预测工具设计

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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型材,通过储存时间研究海鲷新鲜度进化。从这些数据设计了新鲜度指数,存储时间和微生物计数的预测模型。评估物理化学参数以评估鱼的质量;控制微生物生长以确保食品安全性,并进行感官分析以表征质量恶化。推动预测模型和改进了,目的是被用作海鲜行业质量管理的工具。进行验证以确定模型的准确性。物理化学和微生物参数之间存在良好的关系。感官分析和微生物计数允许建立10天的保质期,其质量差(根据欧洲社区的销售目的的分级系统),新鲜指数低于50%。感官剖面显示鳃和肉纹是在与腐败相关的冰中储存期间最脆弱的属性。新鲜度指数(%)和冰储存时间(h)的预测模型表现出在实际验证后的精度接近90%。

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