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[1]王维乐,牟志美,张淑君,等.响应面法优化Paraconiothyrium variabile GHJ-4产漆酶发酵条件[J].应用与环境生物学报,2011,17(03):321-325.[doi:10.3724/SP.J.1145.2011.00321]
 WANG Weile,MU Zhimei,ZHANG Shujun,et al.Optimization of Fermentation Conditions of Paraconiothyrium variabile GHJ-4 for Laccase Production by Response Surface Methodology[J].Chinese Journal of Applied & Environmental Biology,2011,17(03):321-325.[doi:10.3724/SP.J.1145.2011.00321]
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响应面法优化Paraconiothyrium variabile GHJ-4产漆酶发酵条件()
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《应用与环境生物学报》[ISSN:1006-687X/CN:51-1482/Q]

卷:
17卷
期数:
2011年03期
页码:
321-325
栏目:
研究论文
出版日期:
2011-06-24

文章信息/Info

Title:
Optimization of Fermentation Conditions of Paraconiothyrium variabile GHJ-4 for Laccase Production by Response Surface Methodology
作者:
王维乐牟志美张淑君于奇任春久赵凯姚娟高绘菊
(山东农业大学林学院 泰安 271018)
Author(s):
WANG Weile MU Zhimei ZHANG Shujun YU Qi REN Chunjiu ZHAO Kai YAO Juan GAO Huiju
(College of Forestry, Shandong Agricultural University, Tai’an 271018, Shandong, China)
关键词:
Paraconiothyrium variabile GHJ-4漆酶Plackett-Burman响应面发酵条件优化
Keywords:
Paraconiothyrium variabile GHJ-4 laccase Plackett-Burman response surface methodology optimization of fermentation condition
分类号:
TQ925
DOI:
10.3724/SP.J.1145.2011.00321
文献标志码:
A
摘要:
为提高子囊菌Paraconiothyrium variabile GHJ-4产漆酶的能力,采用响应面法对其发酵条件进行优化. 首先用Plackett-Burman法筛选出4个影响较大的重要因素,分别为:接种量(X1)、培养时间(X2)、装样量(X3)和转速(X4). 继而采用最陡爬坡路径逼近最大响应区域,并结合中心组合试验以及响应面分析,建立了以漆酶酶活为响应值的二次回归方程模型,即Y = 698.72 – 13.64X1 + 3.46X2 + 25.45X3 – 11.64X4 + 44.94X1X3 + 0.31X2X3 + 23.14X2X4 – 19.55X3X4 – 44.65X12 – 45.07X22 – 36.52X32 – 21.60X42. 从中获得最优的发酵条件:接种量6.43%(φ),温度28 ℃,初始pH 4,培养时间182 h,装液量72.5 mL,转速157 r/min,种龄96 h. 采用该发酵条件,供试菌株的漆酶酶活达到710.44 U/mL,较优化前漆酶的产量提高了1.73倍,其试验值与预测值基本相符,说明预测模型可靠性高,可应用于漆酶发酵条件的优化. 图1 表6 参20
Abstract:
In order to enhance the production of laccase by Paraconiothyrium variabile GHJ-4, response surface methodology was applied to optimize the fermentation conditions. Plackett-Burman design was used to investigate the main factors affecting laccase yield of Paraconiothyrium variabile GHJ-4. The results showed that four factors played important roles in the fermentation conditions, including inoculation volume (X1), culture time (X2), broth content (X3) and rotating speed (X4). After steepest ascent experiment approaching the optimal level of the four factors, central composite design and response surface analysis were applied to establish the second-order regression equation model, Y = 698.72 –13.64X1 + 3.46X2 + 25.45X3 – 11.64X4 + 44.94X1X3 + 0.31X2X3 + 23.14X2X4 – 19.55X3X4 – 44.65X12 – 45.07X22 – 36.52X32 – 21.60X42, for the yield of laccase. Based on this model, the optimal fermentation conditions were obtained as following: 6.43% (φ) of inoculation, 28 ℃ of culture temperature, initial pH value 4, 182 h of culture time, 72.5 mL of broth content, 157 r/min of rotating speed, and 96 h of seed age. Under the optimum conditions, the activity of laccase increased nearly 1.73 times to 710.44 U/mL and the experimental values argreed with the predicted values. These results suggested that the predicted model was reliable and available for the optimization of laccase fermentation conditions. Fig 1, Tab 6, Ref 20

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备注/Memo

备注/Memo:
山东省自然科学基金项目(No. Q2008D08)资助
更新日期/Last Update: 2011-06-23