https://sure.su.ac.th/xmlui/handle/123456789/15171 คณะวิศวกรรมศาสตร์และเทคโนโลยีอุตสาหกรรม Mon, 20 Jul 2026 01:22:36 GMT 2026-07-20T01:22:36Z https://sure.su.ac.th/xmlui/handle/123456789/23297 Mechanistic kinetic models of enzymatic cellulose hydrolysis-A review Nardrapee Karuna Bioconversion of lignocellulose forms the basis for renewable, advanced biofuels, and bioproducts. Mechanisms of hydrolysis of cellulose by cellulases have been actively studied for nearly 70 years with significant gains in understanding of the cellulolytic enzymes. Yet, a full mechanistic understanding of the hydrolysis reaction has been elusive. We present a review to highlight new insights gained since the most recent comprehensive review of cellulose hydrolysis kinetic models by Bansal et al. (2009) Biotechnol Adv 27:833-848. Recent models have taken a two-pronged approach to tackle the challenge of modeling the complex heterogeneous reaction-an enzyme-centric modeling approach centered on the molecularity of the cellulase-cellulose interactions to examine rate limiting elementary steps and a substrate-centric modeling approach aimed at capturing the limiting property of the insoluble cellulose substrate. Collectively, modeling results suggest that at the molecular-scale, how rapidly cellulases can bind productively (complexation) and release from cellulose (decomplexation) is limiting, while the overall hydrolysis rate is largely insensitive to the catalytic rate constant. The surface area of the insoluble substrate and the degrees of polymerization of the cellulose molecules in the reaction both limit initial hydrolysis rates only. Neither enzyme-centric models nor substrate-centric models can consistently capture hydrolysis time course at extended reaction times. Thus, questions of the true reaction limiting factors at extended reaction times and the role of complexation and decomplexation in rate limitation remain unresolved. Sat, 01 Jul 2017 00:00:00 GMT https://sure.su.ac.th/xmlui/handle/123456789/23297 2017-07-01T00:00:00Z https://sure.su.ac.th/xmlui/handle/123456789/23296 Oil extracted from spent coffee grounds for bio-hydrotreated diesel production Worapon Kiatkittipong Oil extracted from spent coffee grounds is utilized as a renewable source for bio-hydrotreated fuel production. In the present work, oil yield up to 13% can be obtained by Soxhlet extraction with hexane as a solvent. As the extracted oil contained high content of free fatty acids (6.14%), therefore one step alkali-catalyzed for ester based biodiesel production is impractical. Hydrotreating of extracted oil was performed over two catalysts i.e. NiMo/γ-Al2O3 and Pd/C with different operating parameters i.e. reaction time, operating temperature, and H2/oil. It was found that the reaction time of 2 h and the reaction temperature of 400 °C are favorable operating conditions. The liquid products mostly consisted of n-pentadecane and n-heptadecane, which contain one carbon atom shorter than the corresponding fatty acid (Cn−1) i.e. palmitic and stearic acid, respectively. Unfavorable cracking of diesel product is pronounced at high temperature and prolonged reaction time. In addition, although increased H2/oil promoted overall reaction and hydrodeoxygenation activity (Cn−1/Cn decreased) for both catalysts, hydrocracking is enhanced over Pd/C, leading to significant increase in gasoline yield. Moreover, Pd/C gave higher olefin content in liquid product (22.3 wt%) than NiMo/γ-Al2O3 (4.8 wt%). However, NiMo/γ-Al2O3 shows higher isomerization activity. The amount of isoparaffins catalyzed by NiMo/γ-Al2O3 and Pd/C were 10.8 and 1.7 wt%, respectively. Physiochemical analysis of the diesel fraction exhibit satisfactory properties. The density and kinematic viscosity were consistent with the specification of commercial bio-hydrogenated diesel, NExBTL, while the cetane index was much higher than conventional diesel. Sat, 15 Oct 2016 00:00:00 GMT https://sure.su.ac.th/xmlui/handle/123456789/23296 2016-10-15T00:00:00Z https://sure.su.ac.th/xmlui/handle/123456789/23295 Robust NIRS models for non-destructive prediction of postharvest fruit ripeness and quality in mango Busarakorn Mahayothee; Pramote Khuwijitjaru The effect of harvest year on near-infrared spectroscopy (NIRS) prediction models to determine postharvest quality of mango was evaluated. Diffuse reflectance spectra in region of 700–1100 nm were used to develop calibration models for firmness, total soluble solids (TSS), titratable acidity (TA) and ripening index (RPI) using partial least squares (PLS) regression analysis. The results showed that model robustness was influenced by harvest year. High prediction error was found when models from single harvest year were used to predict the data of other years, whereas using combined data from two or three years for calibration greatly enhanced the prediction accuracy. The prediction models established from three-year data performed the most suitably for prediction of TSS (R2 = 0.9; SEP = 1.2%), firmness (R2 = 0.82; SEP = 4.22 N), TA (R2 = 0.74; SEP = 0.38 %) and RPI (R2 = 0.8; SEP = 0.8). Classification of mango ripeness was successfully achieved using second derivative pretreated spectra with an accuracy of more than 80%. The results indicated that NIRS can be used as a reliable non-destructive technique for mango quality assessment and a robust model could be developed when effect of harvest year was taken into account. Fri, 01 Jan 2016 00:00:00 GMT https://sure.su.ac.th/xmlui/handle/123456789/23295 2016-01-01T00:00:00Z