Volume 16, Issue 95 (2019)                   FSCT 2019, 16(95): 111-125 | Back to browse issues page


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Mahjoorian A, Saeedi Asl M, Jafarian S, Tahanezhad M, Golzadeh B. Optimization of extraction conditions of gelatin from Caspian White fish (Rutilus frisii Kutum) scale. FSCT 2019; 16 (95) :111-125
URL: http://fsct.modares.ac.ir/article-7-36513-en.html
1- Department of Agricultural Engineering and Technology, Payame Noor University (PNU), Tehran, Iran
2- Department of Food Science & Technology, Sabzevar Branch, Islamic Azad University, Sabzevar, Iran , mrezasaeidi@yahoo.com
3- Department of Food Science & Technology, Savadkooh Branch, Islamic Azad University, Savadkooh, Iran
4- Department of Chemisty, Payame Noor University (PNU), Tehran, Iran
Abstract:   (3001 Views)
Gelatin has many applications in the food, pharmaceutical and cosmetic industries due to its technological and functional properties. By-products from fish cleaning are rich sources of collagen. The physical, chemical and rheological properties of gelatin or collagen depend on their sources as well as the extraction conditions. Response surface methodology (RSM) with three parameters was conducted to determine the optimum extraction conditions of gelatin from Caspian whitefish scale. A Box-Behnken design was used to study the combined effects of sodium hydroxide concentration (0.075-0.225 M), soaking time in sodium hydroxide solution (60-180 minute), and extraction temperature (30-50 oC) were determined. Viscosity (cp), gel strength (g), L*, a*, and b* were chosen as responses. The results showed the optimum conditions were sodium hydroxide concentration 0.109 M, soaking time in sodium hydroxide solution of 115.735 minutes, and Extraction temperature of 37.585oC. The predicted responses including viscosity, gel strength, L*, a*, and b* were 2.17 cP, 145 g, 6.039, 6.801, and 38.859 respectively. The response surface method was able to estimate the optimal conditions of extraction gelatin with high desirability (0.99).
 
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Article Type: Original Research | Subject: Statistics, modeling and response levels in the food industry
Received: 2019/09/16 | Accepted: 2019/12/15 | Published: 2019/12/31

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