Preparation of Collagen Casings with High Mechanical Properties using Response Surface Methodology
- 1 Shandong University of Technology, China
- 2 Zibo Huanghelong Bioengineering Co. Ltd, China
Copyright: © 2021 Zhike Xie, Ming He, Yuhan Zhai, Feifei Xin, Shuyan Yu, Shaoxuan Yu, Huanying Zhao, Haifang Xiao and Yuanda Song. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Usages of plastic casing have a number of drawbacks like generation of waste associated with the materials used to package foods and the source of natural casings is limited. So, the interest in the development of biodegradable collagen casing is increasing. For this reason, the present study aimed at developing a new type of collagen casing sprayed with Tea Polyphenols (TP), sodium alginate and sodium pyrophosphate. Box-Behnken Design (BBD) of Response Surface Methodology (RSM) was used to optimize concentrations of TP, sodium alginate and sodium pyrophosphate for the development of collagen casing. The optimization was done on the basis of responses viz. tensile force, tensile strength and elongation at break. The results showed that TP has a significant influence on tensile force and longitudinal tensile strength of collagen casing. Moreover, sodium alginate and sodium pyrophosphate had a significant effect on transverse elongation at break of collagen casing. The optimum level of different parameters resulting in collagen casing with maximum mechanical properties were obtained under conditions of 1.99% TP, 2.90% sodium alginate and 2.99% sodium pyrophosphate concentrations. Further verification test of the optimized conditions revealed a sufficient specific accuracy. The new type of collagen casing exhibited good mechanical properties, so these casings can be utilized for packaging in sausage industry.
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- Collagen Casings
- Mechanical Properties
- Response Surface Methodology