利用纤维素酶和酿酒酵母进行预处理甘蔗渣同步糖化发酵的动力学与建模

S. Elumalai, V. Thangavelu
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引用次数: 22

摘要

研究了纤维素酶和酿酒酵母同时糖化发酵(SSF)对预处理甘蔗渣进行生物转化的工艺参数优化。采用2 3个中心点和轴点的五水平中心复合设计(CCD)实验,建立了培养温度、pH和发酵时间等工艺变量优化的统计模型。采用响应面法(Response Surface Methodology, RSM)对乙醇生产数据进行方差分析(ANOVA)和二阶多项式方程分析,并利用等高线图研究发酵过程中三个相关变量之间的相互作用。发酵实验采用容量为2L的在线监测模块化发酵罐进行。在最佳温度(35℃)、pH(5.5)和发酵时间(114 h)条件下,获得了生产乙醇的最佳工艺参数。在最佳工艺条件下,50 g/l预处理甘蔗渣可获得最大乙醇浓度(4.80 g/l)。对Monod模型、修正Logistic模型、修正Logistic合并Leudeking - Piret模型和修正Logistic合并Modified Leudeking - Piret模型等动力学模型进行了评价,并对动力学常数进行了预测。关键词:优化,响应面法(RSM),同步糖化发酵(SSF),乙醇,酿酒酵母DOI = 10.3329/cerb.v14i1.4156化学工程研究进展14 (2010)29-35
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simultaneous Saccharification and Fermentation (SSF) of pretreated sugarcane bagasse using cellulase and Saccharomyces cerevisiae - Kinetics and modeling
Optimization of process variables in the bioconversion of pretreated sugarcane bagasse using cellulase and Saccharomyces cerevisiae by Simultaneous Saccharification and Fermentation (SSF) was investigated in the present study. A 2 3 five level Central Composite Design (CCD) experiments with central and axial points were used to develop a statistical model for the optimization of process variables such as incubation temperature , pH and fermentation time. Data obtained from Response Surface Methodology (RSM) on ethanol production were subjected to the analysis of variance (ANOVA) and analyzed using a second order polynomial equation and the contour plots were used to study the interactions among three relevant variables of the fermentation process. The fermentation experiments were carried out using an online monitored modular fermenter 2L capacity. The processing parameters setup for reaching a maximum response for ethanol production was obtained when applying the optimum values for temperature (35°C), pH (5.5) and fermentation time (114 h). Maximum ethanol concentration (4.80 g/l) was obtained from 50 g/l pretreated sugarcane bagasse at the optimized process conditions in aerobic batch fermentation. Various kinetic models such as Monod, Modified Logistic model, Modified Logistic incorporated Leudeking – Piret model and Modified Logistic incorporated Modified Leudeking – Piret model have been evaluated and the constants were predicted. Keywords: Optimization, response surface methodology (RSM), simultaneous saccharification and fermentation (SSF), ethanol, Saccharomyces cerevisiae DOI = 10.3329/cerb.v14i1.4156 Chemical Engineering Research Bulletin 14 (2010) 29-35
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