scholarly journals Optimization of combined pre-treatments on sugarcane leaves for bioethanol production

2019 ◽  
Vol 1 (1) ◽  
pp. 30-39
Author(s):  
Numchok Manmai ◽  
Katherine Bautista ◽  
Yuwalee Unpaprom ◽  
Rameshprabu Ramaraj
Keyword(s):  
Low Temperature ◽  
Central Composite Design ◽  
Lignocellulosic Biomass ◽  
Process Optimization ◽  
Reducing Sugar ◽  
Biofuel Production ◽  
Bioethanol Production ◽  
Renewable Source ◽  
Naoh Pretreatment ◽  
Central Composite

This paper reports the comparison of an optimized pretreatment model for Reducing Sugar (RS) production from Sugarcane leaf (SL) using NaOH to depolymerize of lignocellulosic biomass. The addition variables for a pretreatment model consisted of NaOH concentrations, heating temperatures and pretreatment times in the variety of 1-2% (v/v), 30-40 °C and 1-3 days individually. After pretreatment RS was estimated to transform into energy, both of RS and the energy were optimized by Respond surface methodology (RSM) on Central composite design (CCD). The models showed high determinational coefficients (R2) above 0.9876. Process optimization provided highest RS yield and energy of 5.632 g/L and 90.112 kJ/L. for NaOH pretreatment at condition 2% (v/v) NaOH, low temperature (40 °C) for 3 days. This report presented demonstrate that sugarcane leaf waste which is usually burnt after harvesting can be a part of renewable source for the biofuel production.

Pretreatment of Cocoa Waste for Bioethanol Production Using Ionic Liquid

2012 ◽  
Vol 59 (1) ◽  
Author(s):  
Ahmad Idi ◽  
Madihah Md. Salleh ◽  
Zaharah Ibrahim ◽  
Shaza Eva Mohamad
Keyword(s):  
Gas Chromatography ◽  
Ionic Liquid ◽  
Treatment Process ◽  
Fossil Fuel ◽  
Fermented Food ◽  
Reducing Sugar ◽  
Bioethanol Production ◽  
Ionic Liquid Pretreatment ◽  
Naoh Pretreatment ◽  
Biomass Loss

One of the major advantages of biofuel over fossil fuel is that it is environmentally friendly but unfortunately most of the chemicals used in the pretreatment of lignocelluloses biomass to produce biofuel can cause adverse effects to the environment. In this study, ionic liquid was used for the pretreatment of cocoa waste. Its effectiveness in the treatment process was compared to the alkalis and acids used in the conventional pretreatment media. The effectiveness of pretreatment using ionic liquid, H2SO4 and NaOH was based on the reduction of biomass, production of reducing sugar and also bioethanol. Ionic liquid pretreatment was found to show minimal biomass loss of only 31% after pretreatment compared to H2SO4 and NaOH which showed loss of 61% and 79% respectively. The untreated biomass has 10% amount of cellulose but upon pretreatment with ionic liquid, H2SO4 and NaOH, significant amount of cellulose was detected compared to NaOH which produced only 7% of cellulose. Two types of yeasts were also isolated from Malaysian local fermented food, the tapai ubi which were tested for the abilities to ferment the reducing sugar produced. Using the DNS method for determining reducing sugar, ionic liquid pretreatment was shown to produce 6.3×10–2g/L of reducing sugar while the untreated, H2SO4 and NaOH pretreatment produced 2.87×10–2g/L, 7.4×10–2g/L and 3.37×10–2g/L respectively at the end of 24 hours of incubation. Bioethanol produced during the fermentation was analysed using gas chromatography. Ionic liquid produced a total of 7.885g/L, H2SO4 produced 7.911g/L NaOH produced 6.824g/L and untreated cocoa waste produced 5.116g/L of ethanol at the end of 24 hours incubation.

Degradation of antidepressant drug fluoxetine in aqueous media by ozone/H2O2system: process optimization using central composite design

2015 ◽  
Vol 36 (12) ◽  
pp. 1477-1488 ◽  
Author(s):  
Abbas Aghaeinejad-Meybodi ◽  
Amanollah Ebadi ◽  
Sirous Shafiei ◽  
Alireza Khataee ◽  
Mohammad Rostampour
Keyword(s):  
Central Composite Design ◽  
Process Optimization ◽  
Aqueous Media ◽  
Antidepressant Drug ◽  
Central Composite

scholarly journals The Potential of Microbial Symbionts Macrotermes gilvus Hagen Termite Gut as Degrading Agents of Cellulose in Bioethanol Production

2018 ◽  
Vol 10 (2) ◽  
pp. 396-401
Author(s):  
Dewi Susilowati ◽  
Niken Subekti ◽  
Siti Harnina Bintari
Keyword(s):  
Enzyme Activity ◽  
Cell Density ◽  
Reducing Sugar ◽  
Bioethanol Production ◽  
Microbial Symbionts ◽  
Student’S T ◽  
Central Composite ◽  
High Cellulose ◽  
Test Result ◽  
Student’S T Test

Water hyacinth is a potential feedstock for bioethanol production because of their high cellulose. The microbial symbionts of the Macrotermes gilvus termite’s gut have a high endoglucanase enzyme activity. This research was aimed to analyze the pH, temperature and agitation effects towards cell density, endoglucanase enzyme activity and reducing sugar, and to determine the effective optimum condition that can produce maximum reducing sugar. This research used central composite design (CCD) with the total number of run was . The independent variables were including pH (5.9, 6.4, 7.0, 7.6, 8.0), temperature (30 0C, 33 0C, 37 0C, 41 0C, 44 0C) and agitation (90 rpm,114 rpm, 150 rpm,185 rpm, 210 rpm), with six replications at central points. Parameters measured were cell density, endoglukanase enzyme activity and reducing sugar, thus analyzed by the statistical software package MINITAB 18.0. The Student’s t-test result showed the primary sequence influencing cell density as pH ˃ agitation ˃ temperature and towards endoglucanase enzyme activity and reducing sugar as pH ˃ temperature ˃ agitation, P ˂ 0.05. The maximum reducing sugar (60.13 ± 3.16 mmolL-1) was obtained at pH 6.95, temperature 37 0C and agitation 150 rpm. The results of this research can be used to explore the more potential microbial symbionts of the Macrotermes gilvus Hagen termite’s gut.

scholarly journals Mathematical Modelling and Optimisation of Low-Temperature Drying on Quality Aspects of Rough Rice

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Shakeel Ahmed Soomro ◽  
Kunjie Chen ◽  
Sohail Ahmed Soomro
Keyword(s):  
Low Temperature ◽  
Central Composite Design ◽  
Cooking Time ◽  
Quadratic Model ◽  
Rough Rice ◽  
Quality Aspects ◽  
Tropical Conditions ◽  
Low Temperature Drying ◽  
Central Composite

Rice when harvested normally has a high moisture content of 20–25% which requires immediate drying, reducing its mass loss and preventing it to spoil. This situation is more crucial with the areas under humid tropical conditions, where moisture and temperature mainly play an important role in deteriorating the quality of rough rice. Keeping the importance of quality attributes of rough rice, the study was carried out to assess the effects of low-temperature drying and suggest an optimum condition. Response surface methodology (RSM) with a central composite design was employed to study the effects of variables, i.e., temperature (X1), time (X2), and air velocity (X3) on responses, i.e., head rice yield (HRY), hardness, lightness, and cooking time. The experimental data were fitted to the quadratic model, studying the relationship between independent and dependent variables. The results revealed that the HRY, hardness, lightness, and cooking time increased with increasing variables, whereas for HRY, it particularly increased and then decreased. It was observed that temperature had more influence on the quality of rough rice followed by time and velocity. Results for analysis of variance revealed that the quality aspects of rough rice were significantly (p<0.05) affected by temperature and time, whereas for velocity, it only significantly affected hardness. The optimal drying conditions predicted by RSM for variables were 25°C, 600 min, and 1 m·s−1, and the optimal predicted HRY, hardness, lightness, and cooking time were 73.93%, 38.28 N, 71.40, and 27.58 min respectively. Acceptable values of R2, Adj R2, and nonsignificance of lack of fit demonstrated that the model applied was adequate and can be used for optimization. The study concluded that the RSM with a central composite design was successfully used to study the dependence of quality aspects of rough rice at low temperature and can be utilized by the rice processing industries.

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