Combined beef thawing using response surface methodology

Jiahui Jin, Xiaodan Wang, Yunxiu Han, Yaoxuan Cai, Yingming Cai, Hongmei Wang, Lingtao Zhu, Liping Xu, Lei Zhao and Zhiyuan Li
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Jiahui Jin: College of Food Science and Engineering, Jilin University, Changchun, P.R. China
Xiaodan Wang: College of Food Science and Engineering, Jilin University, Changchun, P.R. China
Yunxiu Han: College of Food Science and Engineering, Jilin University, Changchun, P.R. China
Yaoxuan Cai: College of Food Science and Engineering, Jilin University, Changchun, P.R. China
Yingming Cai: College of Food Science and Engineering, Jilin University, Changchun, P.R. China
Hongmei Wang: College of Food Science and Engineering, Jilin University, Changchun, P.R. China
Lingtao Zhu: College of Food Science and Engineering, Jilin University, Changchun, P.R. China
Liping Xu: College of Food Science and Engineering, Jilin University, Changchun, P.R. China
Lei Zhao: College of Food Science and Engineering, Jilin University, Changchun, P.R. China
Zhiyuan Li: College of Food Science and Engineering, Jilin University, Changchun, P.R. China

Czech Journal of Food Sciences, 2016, vol. 34, issue 6, 547-553

Abstract: Based on four thawing methods (still air, still water, ultrasonic wave, and microwave) and single-factor tests, we established a four-factor three-level response surface methodology for a regression model (four factors: pH, drip loss rate, cooking loss rate, protein content). The optimal combined thawing method for beef rib-eye is: microwave thawing (35 s work/10 s stop, totally 170 s) until beef surfaces soften, then air thawing at 15°C until the beef centre temperature reaches -8°C, and finally ultrasonic thawing at 220 W until the beef centre temperature rises to 0°C. With this method, the drip loss rate is 1.9003%, cooking loss rate is 33.3997%, and protein content is 229.603 μg, which are not significantly different from the model-predicted theoretical results (P ≥ 0.05).

Keywords: microwave; Box-Behnken; thaw; ultrasound (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnlcjf:v:34:y:2016:i:6:id:138-2016-cjfs

DOI: 10.17221/138/2016-CJFS

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