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评估在不同温度下于两种不同气氛中储存的鳕鱼(大西洋鳕)鱼片货架期的预测模型。

Evaluation of a predictive model for the shelf life of cod (Gadus morhua) fillets stored in two different atmospheres at varying temperatures.

作者信息

Einarsson H

机构信息

Icelandic Fisheries Laboratories, Reykjavik.

出版信息

Int J Food Microbiol. 1994 Dec;24(1-2):93-102. doi: 10.1016/0168-1605(94)90109-0.

Abstract

The shelf life of fish and food in general is difficult to predict especially if stored at varying temperatures. Shelf life models were constructed (Einarsson, 1992) for cod fillets stored at constant temperatures. The aim of this study was to evaluate if these models could be used to predict spoilage and bacterial growth in cod fillets stored in air and modified atmosphere at constant and varying temperatures. Fresh fillets were packed and stored at constant or varying temperatures between -2 degrees C and 5 degrees C. Samples were taken at regular intervals for bacteriological and sensory evaluation. The results showed that fish stored at +0.6 degrees C in air had a shelf life (assessed by sensory analysis) of 11 days which is close to what could be expected and predicted. The increase in bacterial number observed was generally less than predicted. For fish fillets, stored in air at +5 degrees C for 3 days, then at +0.6 degrees C for 3 days and finally at -2 degrees C, the shelf life was found to be 7 days which was in good agreement with the predicted shelf life. The shelf life of fillets stored at same the temperatures in modified atmosphere was found to be 9 days but by prediction 11 to 12 days. The models for predicting changes in sensory score were more accurate than those predicting changes in bacterial numbers.

摘要

一般来说,鱼类和食品的保质期很难预测,尤其是在不同温度下储存时。已构建了针对在恒定温度下储存的鳕鱼片的保质期模型(埃纳尔松,1992年)。本研究的目的是评估这些模型是否可用于预测在恒定和变化温度下,在空气和改良气氛中储存的鳕鱼片的腐败和细菌生长情况。将新鲜鱼片包装后,在-2℃至5℃之间的恒定或变化温度下储存。定期取样进行细菌学和感官评估。结果表明,在空气中+0.6℃储存的鱼的保质期(通过感官分析评估)为11天,这与预期和预测的结果相近。观察到的细菌数量增加通常低于预测值。对于在空气中+5℃储存3天,然后在+0.6℃储存3天,最后在-2℃储存的鱼片,发现其保质期为7天,这与预测的保质期高度一致。在改良气氛中相同温度下储存的鱼片保质期为9天,但预测为11至12天。预测感官评分变化的模型比预测细菌数量变化的模型更准确。

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