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研究生:游峻偉
研究生(外文):Jun-wei You
論文名稱:本土根瘤菌Cupriavidustaiwanensis對酚降解雙基質指數饋料策略之可行性研究
論文名稱(外文):Feasibility Study of Exponential Feeding Strategy for Phenol degradation of Indigenous Rhizobium Cupriavidus taiwanensis
指導教授:張嘉修張嘉修引用關係
指導教授(外文):Jo-shu Chang
學位類別:碩士
校院名稱:國立成功大學
系所名稱:化學工程學系碩博士班
學門:工程學門
學類:化學工程學類
論文種類:學術論文
畢業學年度:96
語文別:英文
論文頁數:116
中文關鍵詞:指數進料雙基質批次饋料系統
外文關鍵詞:phenol degradationexponential feedingFed-batchdual-substrate
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由於先前開發利用本土根瘤菌Cupriavidus taiwanensis進行酚之生物降解具有工業應用性之成效,本後續研究試圖推出雙基質(酚與甘油)指數饋料技術,以提昇C. taiwanensis對酚之生物降解效率。雖然C. taiwanensis對於酚具有高容忍性,但若濃度過高仍會發生基質抑制酚降解之現象。由該菌株對酚降解情形可由Haldane model描述來看,其酚單基質條件下之生長動力參數為mmax1=0.50 h-1, KS1=0.06 g L-1, Ki=0.28 g L-1,而其產率係數(Yx/s1)為 0.908 g cell/g phenol。由於基質抑制的存在,高濃度下酚降解遲滯期愈趨顯著,所以控制酚在生物降解系統中之濃度,以避免其發生明顯之抑制現象,進而提昇其降解速率並縮短遲滯期。因此本研究以指數饋料批次操作系統進行酚之生物降解,以酚進料量之操控策略下,來額外提供菌體最適量之碳源需求,以提昇降解速率,並避免系統中酚濃度之過量殘留累積。
此外,依之前研究成果 (Chen et al., 2007) 更顯示出在外加第二種能量基質(如甘油)於系統下,確實可達到促進酚生物分解之效果。因此,本研究先就單一甘油基質對於該菌株的生長動力學進行探討,藉由Monod model描述其菌體生長與基質降解情形,得到其生長動力參數為 mmax2=0.058 h-1和KS2=0.53 g L-1,並得產率係數為Yx/s2=0.15 g cell/g glycerol。後續研究則探討當兩種基質共存時,產生對酚降解與菌體生長動力學之影響。由於過量添加甘油會壓抑酚降解作用,但是若甘油添加量低於臨界值時,則無顯著促進酚降解之效果,因此需尋找一個適當的甘油添加範圍,並由批次系統的雙基質降解中瞭解甘油與酚的交互作用,引入甘油濃度對酚降解動力方程式的修正項( ),進而可將雙基質生長模式可表為 ,其中修正參數K’約為15.4 g L-1,而且甘油促進酚降解的最適濃度約為0.8 到 1.2 g L-1。在雙基質指數進料策略下,各種基質的進料速率主要由比生長速率控制,由於因應操作上的不穩定動態行為,因此各基質的比生長速率分別設定為m1=a1mmax1, m2=a2mmax2,進而利用推導出雙基質指數進料方程式為 及 。接著,依據先前對單一基質酚降解指數進料之先前研究結果(Chen et al., 2008),設定酚最適降解進料之比生長速率於在0.5mmax1以下,而甘油的最佳進料速率亦經由指數進料實驗得到最適進料曲線的比生長速率為0.4mmax2以下,因此可得到最適基質設定濃度及最佳進料條件。
在得到最適動力學參數與操作條件後,本研究利用由動力學模式模擬得到的在不同的酚與甘油比生長速率設定下,降解總酚量為3 g時所需之時間,經過數值分析軟體JMP得到二元二次多項式來描述酚降解所需之時間(tp)如下

藉此企圖有效預測在雙基質指數進料下,不同的m1與m2 (亦即 m1=a1mmax1, m2=a2mmax2) 之tp值。該二元二次多項式預測之tp值與動力學模式模擬值,誤差皆在5%以內。為了確認該二元二次多項式未來在實場應用的可行性,在預測總酚降解時間等高曲線圖上的最低谷底區域做五組再確認實驗,亦即(a1, a2) = (0.5, 0.4), (0.5, 0.35), (0.5, 0.3), (0.48, 0.37), (0.52, 0.32),發現實際總酚降解時間與二元二次多項式的預測時間(tp)誤差均在5%以下,並發現在(a1, a2) = (0.5, 0.3)之組合(m’=0.281 h-1)時可得到最迅速的酚降解時間(tp)約為14小時。
關鍵字: 批次饋料系統、酚降解、指數進料、雙基質
Previous study showed that an indigenous rhizobium Cupriavidus taiwanensis isolated from southwest Taiwan was effective in phenol biodegradation. This follow-up study tended to apply the exponential feeding strategy of dual substrates (i.e., phenol and glycerol) to improve the performance of phenol degradation. Although C. taiwanensis could express high tolerance to phenol, phenol inhibition is still present at high-level phenol. As described by Haldane model, the kinetic parameters were ca. mmax1=0.5 h-1, KS1=0.06 g L-1, Ki=0.28 g L-1. The yield coefficient was Yx/s=0.908 g cell/g phenol. To guarantee highest phenol degradation rate and shortest time of lag phase, the phenol concentration should be controlled at a nontoxic level to avoid any provoked inhibitory effect. Therefore, dropwise fed-batch operation was employed to control the minimal residual phenol concentration and to provide a sufficient phenol substrate for microbial growth.
Our previous study (Chen et al. 2007) also showed that an augmentation of a second carbon source (i.e., glycerol) could enhance phenol degradation efficiency. Therefore, a dual substrate feeding strategy was proposed. First, growth kinetics using glycerol as a sole carbon source was studied. The microbial growth and glycerol degradation could be described by Monod model with the kinetic parameters of mmax2=0.058 h-1 and KS2=0.53 g L-1 , while Yx/s value was ca. 0.15 g cell/g glycerol. Next, the exponential feeding strategy of dual substrates in fed-batch system for phenol degradation was investigated. In addition, it was found that the appropriate concentration of augmented glycerol was ranged ca. 0.8 to 1.2 g L-1. The combined interaction between phenol and glycerol was determined in batch cultures through the introduction of modified term ( ); thus, the specific growth rate in dual substrate system could be derived as . The parameter K’ was estimated as 15.4 g L-1. Next, as exponential feeding rates could be pre-determined by the specific growth rate, the specific growth rates of phenol and glycerol were assigned as m1=a1mmax1, m2=a2mmax2 for determining optimal feeding rates of dual substrates. The exponential dual-substrate feeding rate for phenol and glycerol is thus obtained to be and , respectively. According to the criteria shown in previous findings (Chen et al., 2008), for system optimality, the m1 and m2 used in determining the feeding rates should be lower than 0.5mmax1 and 0.4mmax2, respectively. With the pre-determined kinetic parameters and different operation conditions, the time required for complete degradation of 3 g of phenol (tp) could be predicted by selecting different values of a1 and a2. A second-order polynomial equation (response model) obtained from JMP software could be used to predict tp as follows:

The time required for complete phenol degradation (tp) could be evaluated via contour map on (a1, a2) plane. Comparing the results of response and kinetic model, the deviation was less than 5%. To test the validity of the proposed response contour, experiments were also conducted based upon the contour diagram ((a1, a2) = (0.5, 0.4), (0.5, 0.35), (0.5, 0.3), (0.48, 0.37), (0.52, 0.32)). The deviations of experimental results and the response model were also less than 5% strongly indicating the promising feasibility of response model. Meanwhile, the optimal variable set (a1, a2) = (0.5, 0.3) (i.e., the overall specific growth rate was ca. 0.281 h-1) appeared to result in the shortest phenol degradation time of ca. 14 h.
Keywords: Fed-batch, phenol degradation, exponential feeding, dual-substrate
Abstract (Chinese version) I
Abstract (English version) IV
Acknowledgement VII
Table of content IX
List of Tables XII
List of Figures XIII
Nomenclature XVI
Chapter 1 Introduction 1
1-1 Background 1
1-2 Motivation and purpose 2
Chapter 2 Literature review 5
2-1 Introduction to Cupriavidus taiwanensis 5
2-2 Mechanism of phenol biodegradation 7
2-3 Mechanism of glycerol biodegradation 9
2-4 The biological effects of phenol 11
2-5 Kinetic model for phenol biodegradation 12
2-5-1 Evaluation of kinetic parameters 12
2-5-2 Modified model for multi-substrate cultures 15
2-6 Feeding strategy for single/dual substrates 18
2-6-1 Overview of fed-batch cultures 18
2-6-2 Feeding strategies for fed-batch cultures 22
Chapter 3 Materials and methods 27
3-1 Chemicals and Materials 27
3-2 Equipments 28
3-2-1 Fermentor 30
3-3 Medium composition 32
3-4 Determination of bacterial characteristics 33
3-4-1 Bacterial growth 33
3-4-2 Biomass determination 34
3-5 Analytical methods 35
3-5-1 Phenol analysis 35
3-5-2 Glycerol analysis 36
3-5-3 Polyhydroxyalkanoates analysis 37
3-5-4 2-Hydroxymuconate semialdehyde analysis 38
3-6 Evaluation of phenol and glycerol degradation 38
3-6-1 Determination of kinetic parameters of phenol degradation 38
3-6-2 Determination of kinetic parameters of glycerol degradation 39
3-6-3 Development of kinetic model for dual-substrate systems 39
3-7 Exponential feeding strategy for dual-substrate degradation 40
3-7-1 Determination of dual-substrate feeding strategy 42
3-7-2 Model prediction of cell growth and dual-substrate consumption 43
3-7-3 Performance index for exponential feeding strategy 45
Chapter 4 Results and discussion 47
4-1 Kinetics of phenol degradation 47
4-1-1 Phenol inhibition on Cupriavidus taiwanensis 47
4-1-2 Model identification of the kinetics of phenol degradation 48
4-1-3 Model identification of the kinetics of glycerol utilization 54
4-2 Kinetic simulation of phenol degradation using dual-substrates 59
4-2-1 Effects of augmented glycerol on phenol degradation 59
4-2-2 Model reconstruction for dual-substrate system 69
4-3 Exponential feeding strategy for dual substrates 75
4-3-1 Concept of dual-substrate exponential feeding 75
4-3-2 Strategy for glycerol feeding rate 77
4-3-3 Implementation of dual-substrate exponential feeding strategy 80
4-4 Model validation for exponential feeding strategy of dual-substrate 81
4-4-1 Response surface analysis upon dual-substrate results 81
4-4-2 Comparison of polyhydroxybutyrate content in different operations 99
Chapter 5 Conclusions and future perspectives 104
References 108
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