Production of bioethanol by using pretreated coconut husk as carbon source | Blazingprojects Postgraduate Thesis
Home / Chemical engineering / Production of bioethanol by using pretreated coconut husk as carbon source

Production of bioethanol by using pretreated coconut husk as carbon source

 

Table Of Contents


  • 1    INTRODUCTION        
  • 1.1   Energy Sources        
  • 1.2   Problem Statement        
  • 1.3   Scope of Study        
  • 1.4   Research Objectives     2    LITERATURE REVIEW        
  • 2.1   Energy Crisis        
  • 2.2   Bioethanol as Alternative of Fossil Fuel            2.
  • 2.1   Feedstock for Bioethanol Production        
  • 2.3   Overview of Coconut Palm            2.
  • 3.1   Coconut Husk        
  • 2.4   Compositions of Lignocellulosic Materials            2.
  • 4.1   Cellulose            2.
  • 4.2   Hemicellulose            2.
  • 4.3   Lignin        
  • 2.5   Lignocelluloses Bioconversion Technology            2.
  • 5.1   Pretreatment Process            2.
  • 5.2   Saccharification Process            2.
  • 5.3   Fermentation Process        
  • 2.6   Batch Production of Bioethanol        
  • 2.7   Factors Affecting Bioethanol Fermentation by Yeast            2.
  • 7.1   Temperature            2.
  • 7.2   pH            2.
  • 7.3   Carbon Source            2.
  • 7.4   Nitrogen Source        
  • 2.8   Concluding Remarks     3    GENERAL MATERIALS AND METHODS        
  • 3.1   Chemical Reagents        
  • 3.2   Microorganism and Maintenance        
  • 3.3   Inoculums Preparation        
  • 3.4   Analytical Procedures            3.
  • 4.1   Determination of Reducing Sugar Concentration            3.
  • 4.2   Determination of Ethanol Concentration            3.
  • 4.3   Determination of Ethanol Productivity            3.
  • 4.4   Viable Cell Counts        
  • 3.5   Experimental Designs of Project Works    
  • 1.   COMPARISON OF PRETREATMENT STRATEGIES ON 49 CONVERSION OF COCONUT HUSK FIBER TOFERMENTABLE SUGARS    
  • 4.1   Introduction    
  • 4.2   Materials and Methods        4.
  • 2.1   Collection and Processing of Coconut Husk        4.
  • 2.2   Pretreatments on Coconut Husk        4.
  • 2.3   Enzymatic Hydrolysis Process        4.
  • 2.4   Characterisation of Pretreated Coconut Husk        4.
  • 2.5   Scanning Electron Microscopy (SEM) Analysis        4.
  • 2.6   Data analysis    
  • 4.3   Results and Discussions        4.
  • 3.1   Effect of Different Pretreatment Techniques            Coconut Husk for Production of Reducing Sugar        4.
  • 3.2   Characterization of Pretreated Coconut Husk        4.
  • 3.3   Comparison of Pretreatment Techniques        4.
  • 3.4   Scanning Electron Microscope (SEM) Analysis    
  • 4.4   Concluding Remarks    
  • 1.   STATISTICAL OPTIMISATION OF BIOETHANOL 72 PRODUCTION USING MAA-PRETREATED COCONUT   HUSK                
  • 5.1   Introduction            
  • 5.2   Materials and Methods                5.
  • 2.1   Optimization of Simultaneous Saccharification                    and Fermentation Process                5.
  • 2.2   Gas Chromatography-Mass Spectrometry (GC-                    MS) Analysis                5.
  • 2.3   Data Analysis            
  • 5.3   Results and Discussions                5.
  • 3.1   Screening of Significant Factors by Plackett-                    Burman Design                5.
  • 3.2   Path of Steepest Ascent                5.
  • 3.3   Optimization of Ethanol Productivity by using                    Response Surface Methodology (RSM)                5.3.4Validation of Bioethanol Fermentation using            Optimized Condition            5.3.5Gas Chromatography-Mass Spectrometry            (GC-MS) Analysis of Bioethanol        
  • 5.4   Concluding Remarks     6    CONCLUSIONS   AND   RECOMMENDATIONS   FOR        FUTURE RESEARCH        
  • 6.1   Conclusions        
  • 6.2   Recommendations for Future Research     REFERENCES     APPENDIX                                    LIST OF TABLESTable        Page
  • 2.1   Comparison of first and second generation bioethanol    
  • 2.2   Bioethanol production from various lignocellulosic        feedstock    
  • 2.3   Comparison of lignocellulose in several sources on dry        basis    
  • 2.4   The common pretreatments and their possible effects    
  • 3.1   Formulation of NDF solution    
  • 3.2   Formulation of ADF solution    
  • 4.1   Cellulose, hemicellulose and lignin contents of the        pretreated coconut husks    
  • 5.1   Experimental range and levels of independent variables in        the Plackett-Burman experiment    
  • 5.2   Plackett-Burman design matrix representing the coded        values for 7 independent variables    
  • 5.3   Path of steepest ascent experiment design    
  • 5.4   Levels of the factors tested in central composite design    
  • 5.5   The central composite design of RSM for optimization of        bioethanol production    
  • 5.6   Plackett-Burman design matrix representing 7 independent        variables and the response     
  • 5.7   Statistical analysis of the model (ANOVA)    
  • 5.8   Step size for substrate and pectinase loading    
  • 5.9   Experiment design and results for the path of steepest        ascent    
  • 5.10   The Central Composite Design and results of RSM for        optimization of bioethanol production    
  • 5.11   Model summary and analysis of variance (ANOVA) for        the quadratic model    LIST OF FIGURES Figure        Page
  • 2.1   Cocos nucifera L.    
  • 2.2   Cross-section of the fruit of Cocos nucifera L.    
  • 2.3   Coconut husk    
  • 2.4   A schematic diagram of plant cell wall showing cellulose        fibrils laminated with hemicellulose and lignin polymers    
  • 2.5   The structure of cellulose    
  • 2.6   The structure of hemicelluloses    
  • 2.7   ρ-coumaryl (1), coniferyl (2) and sinapyl (3) alcohols:        dominant building blocks of the three dimensional lignin    
  • 2.8   Schematic presentation of effects of pretreatment on        lignocellulosic biomass    
  • 2.9   General nature of batch culture    
  • 3.1   Glucose standard curve    
  • 3.2   Standard curve for ethanol determination    
  • 3.3   Protocol in performing serial dilution    
  • 3.4   Overall process in bioethanol production by using coconut        husk as lignocellulosic raw material    
  • 4.1   Level of reducing sugar released from coconut husk with        two different particle sizes after enzymatic hydrolysis        process    
  • 4.2   Level of reducing sugar produced through hydrolysis of        thermally-treated coconut husk    
  • 4.3   Level of reducing sugars using acid pretreated coconut husk    
  • 4.4   Level of reducing sugars produced through hydrolysis of        alkaline-treated (5% w/v of NaOH for 24 hours) coconut        husk    
  • 4.5   Level of reducing sugars produced through hydrolysis of        microwave-assisted-alkaline-treated coconut husk    
  • 4.6   Maximum level of reducing sugars produced from the        pretreated coconut husk    
  • 4.7   SEM images of coconut husk after several pretreatment        process    
  • 5.1   Schematic diagram of simple distillation process    
  • 5.2   Pareto chart    
  • 5.3   Main effect plots    
  • 5.4   Response surface curve for bioethanol productivity showing        the interaction between substrate and pectinase loading    
  • 5.5   Profile of enzymatic hydrolysis and bioethanol fermentation        by Saccharomyces cerevisiae at optimum conditions    
  • 5.6   Gas Chromatography-Mass Spectrometry analysis  

Thesis Abstract

In the current study, coconut husk, a lignocellulosic biomass, was employed as the feedstock for production of bioethanol. The powderised coconut husks were subjected to thermal pretreatment, chemical pretreatment and microwave-assisted-alkaline (MAA) pretreatment prior to enzymatic and hydrolysis process. The composition profile of coconut husks was significantly altered upon the MAA pretreatment as compared to the untreated sample, with the cellulose content increasing from 18-21% to 38-39% while lignin content decreased from 46-53% to 31-33%. Enzymatic hydrolysis of MAA-pretreated coconut husk also achieved the highest yield of fermentable sugars (measured as glucose) with 0.279 g sugar/g coconut husk. Scanning electron microscopy (SEM) imaging also proved the obvious and significant disruption of coconut husks’ structure. The results demonstrated that the combination of microwave radiation with alkaline solution was effective in altering the physical structures of coconut husks. Hence, MAA-

 pretreated coconut husk was chosen as the substrate for subsequent hydrolysis and fermentation process.For the optimization of simultaneous saccharification and bioethanol fermentation process, the critical variables that affected bioethanol production were identified by using Plackett-Burman design and tested using the analysis of variance (ANOVA). The factors with p-value less than 0.05 in this test were coconut husk loading (p = 0.0087) and pectinase loading (p = 0.0198). These two significant factors were further optimized using a Central Composite Design (CCD). The maximum response predicted from the model would yield 0.0525 g ethanol per g coconut husk daily under the optimal conditions of 3.06 g MAA-pretreated coconut husks, 0.58 mL cellulase, 0.38 mL pectinase and 1 g yeast extract in 100 mL of medium (pH 6) incubated at 30oC. The experimental result gave bioethanol productivity of approximately 0.0593 g ethanol per g coconut husks daily, which was 13% higher than the estimated value (0.0525 g ethanol per g coconut husk). The results of validation experiments proved the usefulness and effectiveness of CCD as an optimization tool in enhancement of bioethanol production from indigenous renewable resources.

 

Thesis Overview

<p> </p><p><strong>INTRODUCTION</strong></p><p><strong>1.1 &nbsp; &nbsp; &nbsp; &nbsp; Energy Sources</strong><br><br>In recent years, the negative impacts of fossil fuels such as global warming, greenhouse gases emissions and the fast depletion of fossil resources have resulted in an increased interest in the research of alternate power or sustainable energy such as biofuel (Palma et al., 2012). Bioethanol has been considered a better choice than conventional fuels, as it reduces the dependence on reserves of crude oil. Bioethanol also promises cleaner combustion, lower emissions of air pollutants, high octane rating and more resistant to engine knock, which may overall lead to a healthier environment because it is carbon neutral and essentially free from sulfur and aromatics (Bailey, 1996; Prasad et al., 2007; Gupta et al., 2009).</p><p>Today, bioethanol is one of the most dominant biofuel and its global production has increased sharply since year 2000. Generally, current production of bioethanol comes from sugar and starch-based materials such as sugarcane and grains (Dermirbas, 2009). However, considering the growing demand for human food,<br><br>&nbsp;lignocellulosic biomass has arisen as a more suitable feedstock for bioethanol production and a viable long-term option for bioethanol production as compared to the other two groups of raw material (Hamelinck et al., 2005). Lignocellulosic material is the most abundant plant biomass resources that can be used in bioethanol production industry. Examples of lignocelluloses are woody biomass, logging residues, energy crops (i.e. switchgrass and poplar), agricultural residues (i.e. wheat straw, rice straw and corn stover), agricultural by-products (i.e. rice hull, sugarcare bagasse) and municipal solid waste (Tan et al., 2008; Duku et al., 2011).<br><br>The lignocellulosic feedstock used in the current study for bioethanol production was the coconut husk. Coconuts are abundantly growing in coastal areas of all tropical countries. In Malaysia, about 115,000 ha of land were being used for coconut plantation in Year 2010 (Sulaiman et al., 2013). It was estimated that approximately 5.3 tons of coconut husk will become available per hectare of coconut. Some of the coconut husk was used as fibre source for rope and mats but most of the coconut husks are routinely disposed of after the coconut water is sold (Tan et al., 2008). This makes coconut husk a cheap and potential substrate that could be used for bioethanol production due to the presence of relatively high levels of cellulose and hemicelluloses in it (van Dam et al., 2004).<br><strong>&nbsp;1.2 &nbsp; &nbsp; &nbsp; &nbsp; Problem Statement</strong></p> <br><p></p>

Blazingprojects Mobile App

📚 Over 50,000 Research Thesis
📱 100% Offline: No internet needed
📝 Over 98 Departments
🔍 Thesis-to-Journal Publication
🎓 Undergraduate/Postgraduate Thesis
📥 Instant Whatsapp/Email Delivery

Blazingprojects App

Related Research

Quantity Surveying. 3 min read

A Framework for Integrating Sustainability Metrics into Cost Estimation Models...

This research aims to develop a practical framework that combines sustainability metrics with existing cost estimation models used in construction projects. The...

BP
Blazingprojects
Read more →
Pure and Industrial . 2 min read

A Framework for Enhancing Catalyst Efficiency through Surface Modification Technique...

This research focuses on finding ways to improve how well catalysts perform by changing their surface properties. Catalysts are substances that speed up chemica...

BP
Blazingprojects
Read more →
Purchasing and suppl. 3 min read

A Framework for Integrating Sustainable Practices in Strategic Sourcing Decisions...

This research is about developing a practical model or framework to help companies incorporate sustainable practices into their strategic sourcing decisions. St...

BP
Blazingprojects
Read more →
Public administratio. 4 min read

A Framework for Enhancing Public Sector Innovation through Institutional Capacity Bu...

This research focuses on understanding how public organizations can become more innovative by improving their internal capabilities, which is known as instituti...

BP
Blazingprojects
Read more →
Psychology. 3 min read

A Framework for Integrating Emotional Regulation and Cognitive Flexibility in Adoles...

This research aims to develop a clear framework that shows how emotional regulation and cognitive flexibility can work together to help adolescents manage their...

BP
Blazingprojects
Read more →
Political Science. 3 min read

A Framework for Analyzing Impact of Social Media on Political Polarization...

This research aims to understand how social media influences political polarization, which is the growing division between different political groups. As more p...

BP
Blazingprojects
Read more →
Physiotherapy. 3 min read

Developing a Holistic Model for Chronic Low Back Pain Management in Physiotherapy...

This research aims to create a comprehensive and practical model to help physiotherapists better manage patients with chronic low back pain. Chronic low back pa...

BP
Blazingprojects
Read more →
Physiology. 2 min read

A Framework for Integrating Autonomic Nervous System Responses in Cardiovascular Reg...

This research aims to develop a comprehensive framework that explains how the autonomic nervous system (ANS) controls and coordinates cardiovascular functions. ...

BP
Blazingprojects
Read more →
Philosophy. 3 min read

A Model for Ethical Decision-Making in Autonomous Artificial Agents...

This research explores how to help autonomous artificial agents, like robots or self-driving cars, make ethical decisions when facing dilemmas. As these machine...

BP
Blazingprojects
Read more →
WhatsApp Click here to chat with us