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Optimization of Protein Extraction from Chinese Bitter Apricot Kernel Using Response Surface Methodology

机译:使用响应表面方法的蛋白质杏仁优化蛋白质提取

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To utilize a new plant protein resource, the optimum conditions for the extraction of protein from Chinese bitter apricot kernel were determined using response surface methodology. A Box-Behnken design was used to investigate the effects of four independent variables, namely pH value, liquid-to-solid ratio (LSR), extraction temperature and NaCI concentration, on the protein yield. Data analysis was performed with Design-Expert version 6.0.6 software. A secondorder polynomial model was used for predicting the response. Regression analysis showed that the reduced quadratic model developed for protein yield exhibited non-significance for lack of fit (p>0.05) and a high value for the coefficient of determination (R2=0.9222). The optimal conditions for the protein yield obtained were pH value of 11, LSR 30:1 mL/g, temperature 50°C, without addition of NaCI. The protein was extracted under optimum conditions to check validity of the model. Additionally, the amino acid profile of apricot kernel protein isolate was analyzed. Glutamic acid is the most abundant, along with arginine and aspartic acid.
机译:为了利用新的植物蛋白质资源,使用响应表面方法确定来自中国苦杏仁核的蛋白质提取的最佳条件。 Box-Behnken设计用于研究四个独立变量,即pH值,液体比(LSR),提取温度和NaCl浓度对蛋白质产率的影响。使用Design-Experial V6.0.6软件进行数据分析。二阶多项式模型用于预测响应。回归分析表明,用于蛋白质产量的减少的二次模型表现出缺乏拟合(p> 0.05)的非显着性,并且测量系数的高值(R2 = 0.9222)。所得蛋白质产量的最佳条件为pH值为11,LSR 30:1mL / g,温度50℃,不添加NaCl。在最佳条件下提取蛋白质以检查模型的有效性。另外,分析了杏仁蛋白分离物的氨基酸谱。谷氨酸是最丰富的,以及精氨酸和天冬氨酸。

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