title: A Weibull statistics-based lignocellulose saccharification model and a built-in parameter accurately predict lignocellulose hydrolysis performance.
abstract: Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed.
authors.affiliation: State Key Laboratory of Microbial Technology, School of Life Sciences, Shandong University, Jinan, China.
authors.forename: Mingyu
authors.initials: M
authors.lastname: Wang
authors.affiliation: State Key Laboratory of Microbial Technology, School of Life Sciences, Shandong University, Jinan, China.
authors.forename: Lijuan
authors.initials: L
authors.lastname: Han
authors.affiliation: State Key Laboratory of Microbial Technology, School of Life Sciences, Shandong University, Jinan, China.
authors.forename: Shasha
authors.initials: S
authors.lastname: Liu
authors.affiliation: Institute of Applied Chemistry, Department of Chemical Engineering, Tsinghua University, Beijing, China.
authors.forename: Xuebing
authors.initials: X
authors.lastname: Zhao
authors.affiliation: Department of Surgery, VA Boston Healthcare System, Boston University, Boston, MA, USA.|Cancer Research Center, Shandong University School of Medicine, Jinan, China.
authors.forename: Jinghua
authors.initials: J
authors.lastname: Yang
authors.affiliation: Malaysian Palm Oil Board, Kuala Lumpur, Malaysia.
authors.forename: Soh Kheang
authors.initials: SK
authors.lastname: Loh
authors.affiliation: Environment Research Institute, Shandong University, Jinan, China.
authors.forename: Xiaomin
authors.initials: X
authors.lastname: Sun
authors.affiliation: Department of Resource and Environment, Binzhou University, Binzhou, China.
authors.forename: Chenxi
authors.initials: C
authors.lastname: Zhang
authors.affiliation: State Key Laboratory of Microbial Technology, School of Life Sciences, Shandong University, Jinan, China. fangxu@sdu.edu.cn.
authors.forename: Xu
authors.initials: X
authors.lastname: Fang
mesh_terms: D018533:Biomass; D002480:Cellulase / Q000378:metabolism*; D005947:Glucose / Q000378:metabolism; D006868:Hydrolysis; D008031:Lignin / Q000737:chemistry* / Q000378:metabolism*; D008954:Models, Biological; D015233:Models, Statistical; D059205:Renewable Energy
chemical_list: C036909:lignocellulose; D008031:Lignin; D002480:Cellulase; D005947:Glucose
keywords: Cellulase; Delignined corncob residue; Empty fruit bunch; Lignocelluloses saccharification model; Weibull statistics