Kamal Md Mostafa, Ali Md Rahmat, Shishir Mohammad Rezaul Islam, Saifullah Md, Haque Md Raihanul, Mondal Shakti Chandra
1Department of Food Processing and Preservation, Hajee Mohammad Danesh Science and Technology University, Dinajpur, 5200 Bangladesh.
2Department of Food Science and Nutrition, Zhejiang University, Hangzhou, 310058 China.
Food Sci Biotechnol. 2019 Jun 7;28(6):1693-1702. doi: 10.1007/s10068-019-00636-2. eCollection 2019 Dec.
This study was aimed to optimize the process variables for improved production of biomass protein using from banana fruit peel by the use of response surface methodology. A five-level-four factors central composite rotatable design was applied to elucidate the influence of process variables viz. temperature (20-40 °C), pH (4-8), substrate concentration (5-25%), and fermentation period (1-5 days) on biomass and protein content. The second-order polynomial models were established, which effectively explicated the variation in experimental data and significantly epitomized the appreciable correlation between independent variables and responses. After numerical optimization, the predicted optimum conditions (temperature of 31.02 °C, pH of 6.19, substrate concentration of 19.92%, and the fermentation period of 4 days) were obtained with biomass of 24.69 g/L and protein of 61.23%, which were verified through confirmatory experiments.
本研究旨在运用响应面法优化工艺变量，以提高利用香蕉果皮生产生物质蛋白的产量。采用五水平四因素中心复合旋转设计，以阐明温度（20 - 40°C）、pH值（4 - 8）、底物浓度（5 - 25%）和发酵周期（1 - 5天）等工艺变量对生物质和蛋白质含量的影响。建立了二阶多项式模型，该模型有效地解释了实验数据的变化，并显著体现了自变量与响应之间的显著相关性。经过数值优化，得到了预测的最佳条件（温度31.02°C、pH值6.19、底物浓度19.92%、发酵周期4天），生物质产量为24.69 g/L，蛋白质含量为61.23%，并通过验证实验进行了验证。
