生产与科研应用

不同贮藏条件下东北农家酱品质变化及其货架期预测

  • 李天一 ,
  • 孙波 ,
  • 解双瑜 ,
  • 柳凯 ,
  • 李智
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  • (东北农业大学 食品学院,黑龙江 哈尔滨,150030)
硕士研究生(孙波副教授为通讯作者,E-mail:bosun 1962@163.com)

收稿日期: 2019-10-31

  网络出版日期: 2020-06-17

Study on the quality change and shelf life prediction of northeast farmhouse sauce under different storage conditions

  • LI Tianyi ,
  • SUN Bo ,
  • XIE Shuangyu ,
  • LIU Kai ,
  • LI Zhi
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  • (College of Food Science,Northeast Agricultural University, Harbin 150030,China)

Received date: 2019-10-31

  Online published: 2020-06-17

摘要

该文通过对4、 25、 37 ℃贮藏条件下东北农家酱中感官评分、氨基酸态氮、总酸、总酯、菌落总数的分析来研究其品质变化。结果表明,在不同贮藏条件下,随着时间的延长,感官评分逐渐减少,氨基酸态氮、总酸、总酯、菌落总数含量逐渐增加。并将感官评分和其他指标进行Pearson相关性分析筛选出菌落总数这一关键指标,建立菌落总数与贮藏时间和贮藏温度相关联的数学模型对东北农家酱的货架期进行预测,并与货架期的实测值进行对比验证。通过计算得出4、 25、 37 ℃贮藏条件下东北农家酱的货架期预测值分别为243、 130、 101 d,与实测值相对误差均在10%以内,表明构建的数学模型可以对该产品的货架期达到准确预测。

本文引用格式

李天一 , 孙波 , 解双瑜 , 柳凯 , 李智 . 不同贮藏条件下东北农家酱品质变化及其货架期预测[J]. 食品与发酵工业, 2020 , 46(10) : 209 -214 . DOI: 10.13995/j.cnki.11-1802/ts.022674

Abstract

In this paper, the sensory score, amino acid nitrogen, total acid, total ester and aerobic plate count of northeast farmhouse sauce stored at 4, 25 and 37 ℃ were analyzed to study its quality change. The results showed that, under different storage conditions, the sensory score gradually decreased with time, the content of amino acid nitrogen, total acid, total ester and aerobic plate count gradually increased. The sensory score and other indicators were analyzed by Pearson correlation, and the aerobic plate count as key indicator. We established a mathematical model that correlated the total number of colonies with storage time and storage temperature to predict the shelf life of northeast farmhouse sauce. The predicted data were compared and verified by the measured value of shelf life. By calculation, the predicted shelf life of northeast farmhouse sauce under the storage conditions of 4, 25, and 37 ℃ were 243, 130, 101 d, respectively. The relative error was less than 10%, indicating that the mathematical model constructed could accurately predict the shelf life of the product.

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