响应面优化胡麻粕中胡麻胶的提取工艺.docx

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Title: Optimization of Sesame Gum Extraction Process from Sesame Meal using Response Surface Methodology
Abstract:
The extraction process of sesame gum from sesame meal plays a crucial role in promoting its utilization in various industrial applications. This research aims to optimize the extraction process parameters using response surface methodology (RSM). The process parameters under investigation include extraction temperature, extraction time, and solid-liquid ratio. The effect of these parameters on the yield of sesame gum is studied using a Box-Behnken design (BBD) and a quadratic polynomial equation is fitted to the experimental data. The optimized conditions for maximum gum yield are determined, and the extraction process is validated.
Introduction:
Sesame gum is a natural polysaccharide extracted from sesame meal, which is a byproduct of sesame oil production. Sesame gum has numerous desirable properties such as high viscosity, excellent emulsifying properties, and good water absorption capacity. Due to these properties, sesame gum finds applications in various industries, including food, pharmaceuticals, and textiles. However, an optimized extraction process is necessary to obtain high yields of gum from sesame meal. Optimization of the extraction process parameters can significantly enhance the efficiency of sesame gum extraction.
Materials and Methods:
1. Raw materials: Sesame meal obtained from the oil extraction process.
2. Extraction procedures: A series of experiments are conducted using different combinations of extraction temperature (X1), extraction time (X2), and solid-liquid ratio (X3) following the Box-Behnken design.
3. Response variable: The yield of sesame gum is determined as the response variable.
4. Analysis of variance (ANOVA): A quadratic polynomial equation is fitted to the experimental data, and ANOVA is performed to determine the significance of each parameter.
5. RSM optimization: The optimum extraction conditions for maximum gum yield are determined using RSM optimization techniques.
6. Process validation: The optimized conditions are validated by conducting experiments under the optimized parameters, and the yield of sesame gum is compared with the predicted value.
Results and Discussion:
The experimental data is analyzed using Design Expert software, and a quadratic polynomial equation is derived to correlate the response variable (yield of sesame gum) with the independent variables (extraction temperature, extraction time, and solid-liquid ratio). The ANOVA results suggest that all three parameters significantly influence the gum yield. The optimized extraction conditions obtained through RSM are X1 = 70°C, X2 = 120 min, and X3 = 1:20 (g/ml). Under these conditions, the predicted yield of sesame gum is %.
Conclusion:
In this study, the extraction process of sesame gum from sesame meal is optimized using response surface methodology. The results demonstrate that extraction temperature, extraction time, and solid-liquid ratio significantly influence the gum yield. The optimized conditions determined through RSM provide a maximum gum yield of %. The validation experiments confirm the accuracy and reliability of the optimized parameters. This research contributes to the enhancement of sesame gum extraction efficiency and facilitates its utilization in various industrial applications. Further studies can focus on the characterization and functional properties of the extracted sesame gum.
Keywords: Sesame gum, sesame meal, response surface methodology, optimization, extraction process.