Kinetic Model for Enzymatic Hydrolysis of Cellulose from Pre-Treated Rice Husks

Abstract

Rice husks contain cellulose as a raw material for manufacturing second-generation bioethanol. Cellulose from pre-treated rice husks was converted into reducing sugars through enzymatic hydrolysis using enzymes derived from Aspergillus niger. This study aims to determine the kinetics of enzymatic hydrolysis at enzyme concentrations of 10, 15, and 20% (v/w) and hydrolysis times of 5, 10, 15, 20, and 25 h. The results showed that cellulose was hydrolyzed to form reducing sugars. The CMCase activity and FPase activity reached 548.940 and 314.892 U mL−1, respectively, much higher than most previous reports on this genus. From the calculation of the reaction rate using the Michaelis–Menten kinetic model, the value of the Michaelis constant ranges from 0.001 to 0.0007, and the maximum rate is 1.3 × 10−7 to 2.7 × 10−7 Mol L−1 s−1. The highest reducing sugar concentration was obtained (1.80 g L−1) at an enzyme concentration of 20% (v/w) and a hydrolysis time of 25 h.

Enzymatic hydrolysis of cellulose banana stem (alkaline microwave-assisted pre-treatment)

“…The activity of crude cellulase enzymes produced from any agricultural waste is influenced by various factors, including the cellulose content in the material, type of substrate, media, substrate concentration, pH, and temperature [15]. The small cellulase enzyme activity test results may be caused by the low concentrations of chemicals and small-volume samples with minimal sample preparation compared to a previous study [23].…”

Renewable Carbohydrates: Advancements in Sustainable Glucose Production and Optimization

“…The Michaelis-Menten model, a well-established enzyme kinetics model, can be applied to describe the enzymatic hydrolysis of cellulose and hemicellulose by Aspergillus niger. By determining the kinetic parameters, such as the maximum reaction rate and the Michaelis constant, researchers can gain valuable insights into the enzymatic efficiency and the overall process dynamics (Efrinalia et al, 2022). Comprehensive characterization of the feedstock is essential to comprehend the complex interactions between the microorganism and the substrate during glucose production.…”

“…The kinetics of enzymatic hydrolysis can be described by various models, such as the Michaelis-Menten model or the Langmuir-Hinshelwood model. These models help in understanding the enzyme-substrate interactions, determining reaction rates, and estimating kinetic parameters such as the maximum reaction rate (Vmax) and Michaelis-Menten constant (Km) (Efrinalia et al, 2022). Kinetic studies provide valuable insights into the efficiency of the hydrolysis process and assist in process optimization.…”

“…These models are essential for understanding the underlying mechanisms, optimizing process conditions, and predicting glucose yields. The commonly used kinetic models for enzymatic hydrolysis, their assumptions, and their applications will be discussed (Efrinalia et al, 2022;Shokrkar & Ebrahimi, 2021).…”

“…These models incorporate additional parameters or variables to improve the accuracy of the predictions and provide a more comprehensive representation of the acid hydrolysis process. Kinetic models for acid hydrolysis provide insights into the reaction rates, reaction mechanisms, and optimal process conditions for glucose production (Efrinalia et al, 2022). By fitting these models to experimental data using parameter estimation techniques (Salmi et al, 2020;Yu et al, 2021), the kinetic parameters can be determined, enabling the prediction of glucose yields and the optimization of acid hydrolysis processes.…”