摘要
为了提高伯克霍尔德氏菌Burkholderia sp.ZYB002发酵液降解马尾松树脂的效价,对培养基进行优化。通过单因素试验确定1%葡萄糖为发酵最适碳源、0.3%尿素和2%玉米粉为最适复合氮源。采用响应面法得到3种主控因子最佳配比:葡萄糖0.576%、橄榄油1.81%、接种量2.57%,优化后降解马尾松树脂的效价提高到42.5%;运用BPGA耦合法得到最佳配比:葡萄糖0.676 3%、橄榄油1.803 4%、接种量3.381 3%,优化后马尾松树脂的降解效价提高到47.4%。结果还表明:BP-GA耦合法较响应面更具优化效应,优化后比初始降解效价提高了38.6%。通过BP-GA耦合法优化后,Burkholderia sp.ZYB002菌株的摇瓶发酵最佳培养基组成为:葡萄糖0.676 3%、玉米粉1.2%、橄榄油1.803 4%、尿素(氮含量)0.05%、K2HPO40.2%、NaHCO30.1%、吐温801.0%、初始pH 8.5。培养条件:发酵温度为30℃,接种量3.381 3%,摇床转速220 r·min^-1,装液量35 mL(250 mL三角瓶),培养时间36 h。
In order to improve the titer of Pinus massoniana resin degraded by the fermentation broth of Burkholderia sp.ZYB002,the medium was optimized.The single factor experiment was carried out to determine that 1%glucose was the most suitable carbon source for the fermentation,0.3%urea and 2%corn flour were the most suitable compound nitrogen sources.The response surface method was used to obtain the optimal ratio of the three main control factors:glucose 0.576%,olive oil 1.81%and inoculation quantity 2.57%.After the optimization,the degradation titer of Pinus massoniana resin was increased to 42.5%.While the optimal ratio was obtained by the BP-GA coupled method:glucose 0.676 3%,olive oil 1.803 4%,inoculation quantity 3.381 3%.After the optimization,the degradation titer of Pinus massoniana resin was increased to 47.4%.The results also showed that compared with the response surface method,the BP-GA coupled method had the better optimization effect,and the titer after the optimization was improved by 38.6%compared with the initial degradation titer.After the optimization by the BP-GA coupled method,the optimal medium composition for the shake-flask fermentation of Burkholderia sp.ZYB002 was:glucose 0.676 3%,corn flour 1.2%,olive oil 1.803 4%,urea(nitrogen content)0.05%,K2HPO40.2%,NaHCO30.1%,Tween 801.0%,and initial pH 8.5.The culture condition was as follows:the fermentation temperature was 30℃,the inoculation quantity was 3.381 3%,the shaking speed was 220 r·min^-1,the loaded liquid was 35 mL(250 mL triangular flask),and the culture time was 36 h.
作者
王恒
WANG Heng(Ningde Product Quality Inspection Institute, Ningde, Fujian 352100, China;Fujian Normal University, Fuzhou, Fujian 350108, China)
出处
《福建农业科技》
2020年第3期6-12,共7页
Fujian Agricultural Science and Technology
关键词
马尾松树脂
响应面
神经网络
遗传算法
培养基优化
Pinus massoniana resin
Response surface
Neural network
Genetic algorithm
Culture medium optimization
