首页 | 本学科首页   官方微博 | 高级检索  
   检索      


Parameter determination and validation for a mechanistic model of the enzymatic saccharification of cellulose‐Iβ
Authors:Ambarish Nag  Michael A Sprague  Andrew J Griggs  James J Lischeske  Jonathan J Stickel  Ashutosh Mittal  Wei Wang  David K Johnson
Institution:1. Computational Science Center, National Renewable Energy Laboratory, Golden, CO;2. National Bioenergy Center, National Renewable Energy Laboratory, Golden, CO;3. Biosciences Center, National Renewable Energy Laboratory, Golden, CO
Abstract:Cost‐effective production of fuels and chemicals from lignocellulosic biomass often involves enzymatic saccharification, which has been the subject of intense research and development. Recently, a mechanistic model for the enzymatic saccharification of cellulose has been developed that accounts for distribution of cellulose chain lengths, the accessibility of insoluble cellulose to enzymes, and the distinct modes of action of the component cellulases Griggs et al. (2012) Biotechnol. Bioeng., 109(3):665–675; Griggs et al. (2012) Biotechnol. Bioeng., 109(3):676–685]. However, determining appropriate values for the adsorption, inhibition, and rate parameters required further experimental investigation. In this work, we performed several sets of experiments to aid in parameter estimation and to quantitatively validate the model. Cellulosic materials differing in degrees of polymerization and crystallinity (α‐cellulose‐Iβ and highly crystalline cellulose‐Iβ) were digested by component enzymes (EGI/CBHI/ urn:x-wiley:87567938:media:btpr2122:btpr2122-math-0001) and by mixtures of these enzymes. Based on information from the literature and the results from these experiments, a single set of model parameters was determined, and the model simulation results using this set of parameters were compared with the experimental data of total glucan conversion, chain‐length distribution, and crystallinity. Model simulations show significant agreement with the experimentally derived glucan conversion and chain‐length distribution curves and provide interesting insights into multiple complex and interacting physico‐chemical phenomena involved in enzymatic hydrolysis, including enzyme synergism, substrate accessibility, cellulose chain length distribution and crystallinity, and inhibition of cellulases by soluble sugars. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1237–1248, 2015
Keywords:biomass  α  ‐cellulose  highly crystalline cellulose  enzymatic hydrolysis model  kinetic parameter estimation
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号