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食品研究与开发:2021,42(18):92-99
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超声结合酶法辅助提取甘蔗渣中水溶性多糖的工艺优化
(河南牧业经济学院,河南 郑州 450046)
Optimization of Extraction Technology of Water-soluble Polysaccharide from Bagasse by Ultrasonic and Enzyme-assisted Extraction
(Henan University of Animal Husbandry and Economy,Zhengzhou 450046,Henan,China)
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投稿时间:2020-10-30    
中文摘要: 该文以甘蔗渣为原材料,采用单因素试验和正交试验对甘蔗渣中水溶性多糖的提取条件进行优化,然后对其进行紫外吸收扫描和红外光谱分析。先用果胶酶、纤维素酶、中性蛋白酶逐个进行试验,比较提取率,结果表明,纤维素酶提取率最高。以纤维素酶作为辅助酶结合超声进行优化试验,结合极差分析和方差分析得到最佳优化工艺条件:料液比1∶30(g/mL),酶解pH5.0,纤维素酶添加量为底物的4.5%,超声酶解时间60 min,超声酶解温度55℃,超声功率350 W,平均提取率为12.78%,比优化之前提取率高16.78%。紫外吸收图谱显示在波长260 nm~280 nm无特征吸收峰,即多糖中不含核酸和蛋白质,通过红外光谱检测官能团的伸缩振动峰图谱表明提取物质符合多糖的基本特征,进一步说明该提取工艺的可靠性。
Abstract:In this study,the extraction conditions of water-soluble polysaccharide from bagasse as a raw material were optimized by single factor and orthogonal experiments.Then,the extraction conditions were analyzed by ultraviolet(UV)absorption scanning and infrared spectroscopy.First,pectinase,cellulase,and neutral protease were used to compare the individual extraction rate.Cellulase had the highest extraction rate.The optimized process conditions for the enzyme-assisted cellulase combined with the ultrasonic optimization experiment using poor and variance analyses were as follows:material-liquid concentration 1∶30(g/mL);enzyme solution pH5.0;cellulase concentration 4.5%of the substrate mass;ultrasonic digestion time 60 min;ultrasonic enzyme solution temperature 55 ℃;and ultrasonic power 350 W.The average extraction yield was 12.78%,which was 16.78%higher than that before optimization.The UV absorption spectrum did not show the characteristic absorption peak at wavelengths between 260 nm and 280 nm,suggesting that the crude polysaccharide did not contain nucleic acids or proteins.The stretching vibration spectrum of the functional group detected by infrared spectrum revealed that the extracted substance conformed to the basic characteristics of the polysaccharide,further demonstrating the extraction process′s reliability.
文章编号:202118014     中图分类号:    文献标志码:
基金项目:河南省高等学校重点科研项目(20A150019)
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