Optimization of Protein Extraction from Chinese Bitter Apricot Kernel Using Response Surface Methodology
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℃, 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.
Bitter apricot (Prunus armeniaca L) kernel Protein Extraction Optimization Response surface methodology (RSM)
Zhen-Bao ZHU Hui-Jiang ZHOU Jian-HuaYI
College of Life Science & Engineering Shaanxi University of Science & Technology,Shaanxi Province Re College of Life Science & Engineering Shaanxi University of Science & Technology Xian, China
国际会议
哈尔滨
英文
841-845
2012-06-16（万方平台首次上网日期，不代表论文的发表时间）