FOOD SCIENCE ›› 2020, Vol. 41 ›› Issue (10): 255-264.doi: 10.7506/spkx1002-6630-20190506-038

• Processing Technology • Previous Articles     Next Articles

Optimization of the Preparation of Fat Substitutes Using Plackett-Burman Design Combined with Box-Behnken Response Surface Methodology

AN Panyu, WANG Jingxin, XIAO Lan, LI Xiexin, LI Wei, LIANG Xinmei   

  1. (1. College of Food Science, Sichuan Tourism College, Chengdu 610100, China;2. Chengdu Textile College, Chengdu 611731, China)
  • Online:2020-05-25 Published:2020-05-15

Abstract: In order to improve the quality of composite gels as a fat substitute, the formulation was optimized using combination of Plackett-Burman design, steepest ascent method and Box-Behnken response surface methodology. Firstly, eight factors affecting the quality of composite gels were evaluated by Plackett-Burman design, and four of these were found to have significant effects on the response variable: the amounts of carrageenan, whey protein, water and sodium carbonate. Subsequently, the optimal response region was approached by the steepest ascent method. Finally, the response surface methodology was used to determine the optimal proportion of ingredients was carrageenan:whey protein:water:sodium carbonate:konjac fine powder:gelatin:soybean protein isolate:vegetable oil = 1.19:1:254.52:2:6:1.5:1:18.4. The validation experiments showed that the hardness of the composite gel prepared with the optimized formulation was 6.96 N, sensory elasticity 49.41%, chewiness 4.14 mJ, whiteness value 49.44, shrinkage rate 48.33%, and mass loss percentage 45.77%. These experimental values were close to the predicted values with relative error of 0.85%–1.7%. Thus, combination of Plackett-Burman design, the steepest ascent method and response surface methodology was feasible to optimize the formulation of composite gels, and the prepared composite gel could well simulate the animal fat in Chinese sausage.

Key words: fat substitutes, Plackett-Burman design, formulation optimization, response surface methodology

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