THE PREAH VIHEAR TEMPLE: ROOTS OF THAILAND-CAMBODIA BORDER DISPUTE

ABSTRAC

Stabilization of Empty Fruit Bunch derived Bio-oil using Solvents

The intention of this research was to select the ideal condition for accelerated aging of bio-oil and the consequences of additive in stabilizing the bio-oil. The bio-oil was produced from the catalytic pyrolysis of empty fruit bunch. The optimum reaction conditions applied to obtain the utmost bio-oil yield were 5 wt% of H-Y catalyst at reaction temperature of 500 °C and nitrogen flow rate of 100 ml/min. A 10 wt% of solvents including acetone, ethanol, and ethyl acetate were used to study the bio-oil’s stability. All the test samples were subjected to accelerated aging at temperature of 80 °C for 7 days. The properties of samples used as the indicator of aging were viscosity and water content. The effectiveness of solvents increased in the following order: acetone, ethyl acetate, and 95 vol% ethanol. Based on the result of Gas Chromatography-Mass Spectrometry (GC-MS), it could impede the chain of polymerization by converting the active units in the oligomer chain to inactive units. The solvent reacted to form low molecular weight products which resulted in lower viscosity and lessen the water content in bio-oil. Addition of 95 vol% ethanol also inhibited phase separation

Stabilization of Empty Fruit Bunch derived Bio-oil using Solvents

The intention of this research was to select the ideal condition for accelerated aging of bio-oil and the consequences of additive in stabilizing the bio-oil. The bio-oil was produced from the catalytic pyrolysis of empty fruit bunch. The optimum reaction conditions applied to obtain the utmost bio-oil yield were 5 wt% of H-Y catalyst at reaction temperature of 500 °C and nitrogen flow rate of 100 ml/min. A 10 wt% of solvents including acetone, ethanol, and ethyl acetate were used to study the bio-oil’s stability. All the test samples were subjected to accelerated aging at temperature of 80 °C for 7 days. The properties of samples used as the indicator of aging were viscosity and water content. The effectiveness of solvents increased in the following order: acetone, ethyl acetate, and 95 vol% ethanol. Based on the result of Gas Chromatography-Mass Spectrometry (GC-MS), it could impede the chain of polymerization by converting the active units in the oligomer chain to inactive units. The solvent reacted to form low molecular weight products which resulted in lower viscosity and lessen the water content in bio-oil. Addition of 95 vol% ethanol also inhibited phase separation

Simulation and validation of pig growth model

noneThe purpose of this study was to integrate the current state of knowledge in a pig growth model to predict voluntary feed intake (VFI) and pig performance, and the aim was to explain the model and the method used to calculate the VFI of a growing pig and make it available as a decision support tool to end-users by online access. Chapter 1 describes simulation model and background of the use of growth models in pig science. In Chapter 2, NCHU (National Chung Hsing University) pig growth simulation model was developed and the main goal of this simulator is to predict voluntary feed intake based on the effects of temperature and stocking density. The model indicates the limiting factors relative to diet (protein, energy or ash), housing environmental conditions and stocking density. The concepts of compensatory protein growth, correction of lipid growth, the desired feed intake to meet energy, protein and ash requirements, and influences of stocking density, genotype and sex are also introduced in this model. This study draws a flow chart and steps to predict feed intake of a growing pig to make it clear how the model works. The model simulates the outcomes of feed intake, energy and protein requirements for maintenance, the energy cost for cold thermogenesis, and protein and lipid retention on a daily basis until slaughter weight. In Chapter 3, five parameters were used to describe the effects of pig genotype and sex based on the ratio of lipid mass to protein mass at maturity and the scaling of lipid mass to protein mass during potential growth (b). The simulation aimed to predict VFI, performance and body composition based on the inherent potential protein growth rate according to pig genotype and sex. All aspects of pig performance and body composition were affected to different degrees by both genotype and sex. In a simulation including both the growing stage and the finishing stage, type Lb1 (entire male with improved genotype) grew faster, had a lower feed conversion ratio, took less time reach to 120 kg and had a higher total protein mass and lower total lipid mass than the other types investigated. The relationship between different protein and energy intake levels on the performance and body composition of a growing pig are presented in Chapter 4. Fifty diets were used to describe the effects of protein and energy intake levels. The average daily feed intake increases with both protein and energy intake levels. The average daily gain increases with increasing energy intake and dietary ideal protein content. The feed conversion ratio, which is comprised of the feed used and the scaled feed intake, decreases with increasing protein and energy intake levels. Increasing the diet protein content improves daily protein retention and total protein mass. Increasing the diet energy content also improves daily lipid retention and total lipid mass. The ratio of LR to PR decreases with increasing protein contents and decreasing energy contents. The validation of this simulation is described in Chapter 5. The objective of the present study was to analyse the actual voluntary feed intake and performance of growing pigs to validate the NCHU simulation model. Nine diets were fed to 27 hybrid pigs to support the validation of this model. The diet that showed the highest level of agreement between the experimental and the simulated results for the average daily feed intake had CP 15 % and DE 12.77 MJ/kg. The results for the average daily feed intake suggest that the difference between the simulations and the experiment decreased in size from the beginning to the end of the validation. The model yielded better predictions of the average daily gain for the diet content level of CP 16% and DE 13.60 MJ/kg than for the other diets. The validations of the NCHU model for predicting the FCR and feed used indicated that the highest accuracy was obtained for the diet with CP 15% and DE 12.77 MJ/kg. The results of the comparison between the experimental and simulated results demonstrate that the NCHU simulation model could adequately simulate the average daily feed intake and performance of growing pigs.TABLE OF CONTENTS Page ACKNOWLEDGMENTS i ABSTRACT ii TABLE OF CONTENTS iv LIST OF TABLES vi LIST OF FIGURES viii CHAPTER 1: Literature review-------------------------------------------------------------------------------- 1 1. Simulation model--------------------------------------------------------------------- 2 2. Empirical model----------------------------------------------------------------------- 3 3. Mechanistic model-------------------------------------------------------------------- 3 4. The grey-box model------------------------------------------------------------------ 4 5. Background of pig growth model--------------------------------------------------- 6 6. Building and validation of the simulation model--------------------------------- 7 CHAPTER 2: A simulation model for predicting the voluntary feed intake of a growing pig--------- 9 1. Abstract--------------------------------------------------------------------------------- 10 2. Introduction---------------------------------------------------------------------------- 11 3. Modelling approach------------------------------------------------------------------- 11 4. Using the model to predict voluntary feed intake--------------------------------- 31 5. Results and Discussion--------------------------------------------------------------- 34 CHAPTER 3: Effects of genotype and sex on predicted feed intake of a growing pig----------------- 45 1. Abstract--------------------------------------------------------------------------------- 46 2. Introduction---------------------------------------------------------------------------- 47 3. Materials and methods---------------------------------------------------------------- 48 Page 4. Results---------------------------------------------------------------------------------- 51 5. Discussion----------------------------------------------------------------------------- 60 CHAPTER 4: The effects of protein and energy intake levels on predicted performance and body composition of a growing pig---------------------------------------------------------- 67 1. Abstract--------------------------------------------------------------------------------- 68 2. Introduction---------------------------------------------------------------------------- 69 3. Materials and methods---------------------------------------------------------------- 70 4. Results and Discussion--------------------------------------------------------------- 70 CHAPTER 5: A validation of pig growth model for predicting the voluntary feed intake and performance of a growing pig---------------------------------------------------------- 87 1. Abstract--------------------------------------------------------------------------------- 88 2. Introduction---------------------------------------------------------------------------- 89 3. Materials and methods---------------------------------------------------------------- 90 4. Results---------------------------------------------------------------------------------- 92 5. Discussion------------------------------------------------------------------------------ 97 REFERENCES---------------------------------------------------------------------------------- 99 APPENDICES Appendix 1. List of symbols used in the the chapter 2------------------------------ 121 Appendix 2. Steps of using the model to predict voluntary feed intake---------- 124 Appendix 3. List of symbols used in the the chapter 3------------------------------ 127