摘要
为了提高棉秆的还原糖产率,为新疆棉秆的糖化利用研究奠定一定的基础,本文选用酶解温度、纤维素酶用量、pH和水解时间为输入参数,还原糖产率为目标输出参数,在响应曲面设计实验的基础上,采用人工神经网络对H2SO4处理棉秆在纤维素酶中的水解过程进行模拟与优化,建立其神经网络模型(4-5-1),得到棉秆在纤维素酶中水解的最优条件为酶解温度45.32℃、纤维素酶用量434.23 FPU、pH 4.98和水解时间68.37 h,最优条件下还原糖产率最高,为72.93%;经过分析得知纤维素酶用量是影响棉秆酶解产糖的主要因素,当纤维素酶用量为150FPU,并向纤维素酶中添加125 IU木聚糖酶时,棉秆经混合酶酶解后的还原糖产率增大至92.42%,比纤维素酶酶解的还原糖产率提高了1.27倍。
In order to enhance the reducing sugar yield,lay a foundation for the utilization of cotton stalk for sugar production.hydrolysis of H 2SO 4 treated cotton stalks in cellulase was investigated,in this paper selecting hydrolysis temperature,cellulase dosage,pH and hydrolysis time as four input parameters,the reducing sugar yield as the target output,artificial neural network was used to simulate the hydrolysis process,based on the data obtained from the response surface experiment.The optimized model for the hydrolysis of dilute H 2SO 4 treated cotton stalk in cellulase was established(4-5-1);when hydrolysis temperature,cellulase dosage,pH and hydrolysis time were 45.32℃,434.23 FPU,4.98 and 68.37 h,respectively,the highest yield of reducing sugar yield 72.93%was obtained;cellulase dosage was found to be the main factor which influenced enzymatic saccharification of cotton stalk.The addition of xylanase into cellulase could enhance reducing sugar yield to 92.42%,when the amount of xylanase and cellulase were 125 IU and 150 FPU,respectively,which was 1.27 times as much as the reducing sugar yield released from hydrolysis in cellulase.
作者
龚晓武
李琴
呼肖娜
李勇
周娜
GONG Xiaowu;LI Qin;HU Xiaona;LI Yong;ZHOU Na(School of Chemistry and Chemical Engineering/Key Laboratory of Green Processing of Chemical Engineering of Xinjiang Bingtuan,Shihezi University,Shihezi,Xinjiang 832003,China)
出处
《石河子大学学报（自然科学版）》
CAS
北大核心
2020年第3期265-270,共6页
Journal of Shihezi University(Natural Science)
基金
国家自然科学基金项目(21464011)。
关键词
神经网络
棉秆
还原糖
纤维素酶
木聚糖酶
artificial neural network
cotton stalk
reducing sugar
cellulase
xylanase
