谷氨酸棒杆菌
响应面法
发酵
产量(工程)
氮气
尿素
化学
谷氨酸
二次模型
碳纤维
生物化学
食品科学
色谱法
氨基酸
材料科学
有机化学
冶金
复合材料
复合数
基因
作者
Naiyf S. Alharbi,Shine Kadaikunnan,Jamal M. Khaled,Taghreed N. Almanaa,I. Ganesh Moorthy,Rajoo Baskar,Khalid F. Alanzi,Shyam Kumar Rajaram
标识
DOI:10.1016/j.jksus.2019.11.034
摘要
The body to build proteins can use l-Glutamic acid (l-GA). Earlier it was obtained from plant sources, later on microbes have been explored for the production. Corynebacterium glutamicum is a prominent organism used to harvest the glutamic acid. Submerged fermentation was adopted for l-GA production. Various nitrogen/carbon substrates used to find out the best nitrogen and carbon source. Statistical methods especially RSM (response surface method) stayed employed for the effect of various factors such as inoculum size, urea, glucose and salt on the l-GA production. As per the preliminary studies, urea and glucose were chosen as carbon and nitrogen sources. Further, the optimum values have been maximally documented in the glucose (50 g/L), then urea (10 g/L), 19.24% of salt solution and 5% of inoculum size. Maximum Yield of l-GA is produced through RSM-16.49 g/L. The experimental l-Glutamic acid production was 16.36 g/L at an optimum condition that compared well to the maximum predicted values by RSM (16.499 g/L). Non-linear regression quadratic model was developed for the l-GA synthesis; the methodology was validated statistically and the determination coefficient (R2) was found to be 0.991. Thus the study identified the potential carbon and nitrogen source for a higher yield for l-GA using C. glutamicum under submerged fermentation and also this method minimizes the time for optimizing the medium components statistically.
科研通智能强力驱动
Strongly Powered by AbleSci AI