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CHEN Xiaolei, HU Wang, LI Haiyang, et al. Optimization of Salting Technology for Bream by Response Surface Method[J]. JOURNAL OF YUNNAN AGRICULTURAL UNIVERSITY（Natural Science）, 2015, 30(6): 859-867. DOI: 10.16211/j.issn.1004-390X(n).2015.06.006
Citation: CHEN Xiaolei, HU Wang, LI Haiyang, et al. Optimization of Salting Technology for Bream by Response Surface Method[J]. JOURNAL OF YUNNAN AGRICULTURAL UNIVERSITY（Natural Science）, 2015, 30(6): 859-867. DOI: 10.16211/j.issn.1004-390X(n).2015.06.006
shu

Optimization of Salting Technology for Bream by Response Surface Method

  • 1.

    Fisheries Institute, Anhui Academy of Agricultural Science, Hefei 230031, China

  • 2.

    Anhui Haozailai Food Company, Maanshan 238100, China

  • 3.

    Taihu Guoxian Aquatic Products Co., Ltd., Anqing 246400, China

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  • Received Date: June 11, 2014
  • Revised Date: September 29, 2014
  • Published Date: November 15, 2015
    Graphical Abstract
    • Abstract
  • In this study, bream was used as the main raw material, and the effect of different salting conditions, including concentration of brine, temperature and time, on the quality of the products were studied with the moisture content, the content of sodium chloride in bream muscle and amino nitrogen in bittern as the main indicators by response surface method. A multiple regression model was set up between sensory evaluation value and different salting conditions. The results showed that there was positive correlation among salting conditions such as concentration of brine,temperature and time and the content of sodium chloride in bream muscle as well as amino nitrogen in bittern. The model set up by response surface method showed the regression equation fitted well with experimental data, and the concentration of brine and temperature extremely significantly affected sensory evaluation value(P0.01), but the effect of time was not significant. The optimum salting conditions are as followed:the concentration of brine is 5.7%, temperature 12℃, salting time 47h, and the result is basically corresponding to model prediction.
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    • References (27)
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