Modification and verification of the dynamic cell cycling model for baker's yeast

The cell cycling model (CCM) for S. cerevisiae proposed earlier is modified and tested with our own experimental data. Although the original CCM was well verified in steady states and exponential growth with data available in literature, some discrepancies between model predictions and experiments were found for the dynamics of fed-batch culture. The redistribution pattern of the age distribution of daughter cells is suggested as cause of the model error. With an exponential type of redistribution, instead of the original linear one, the model behaviour in transients is improved. The modified model was verified with data of fraction of budding cells and cell number for five fed-batch cultivations. The model agreed well with the experimental data. The simulation results suggest that the cell cycling process indeed is essentially in a pseudo-steady state during fed-batch cultivation, as was assumed in the model. Due to the strong correlation between the quality of baker's yeast and the state of the population in the cell cycling process, the model was applied to optimize the feeding rate of a fedbatch process with consideration of final product quality. The optimal feeding was used succesfully in a laboratory experiment, which demonstrates the validity of the model.List of Symbols B h length of budding phase - C _b1, C _d1, C _p1 parameters in cycling phase equations - C _b2, C _d2, C _p2 h parameters in cycling phase equations - d(i) number of cells in ith cycling interval inU _d - E kg m^–3 ethanol concentration - F m³ h^–1 substrate feeding rate - F _max and F _min m³ h^–1 upper and lower limit of F - FBC, FDC, FPC % fraction of budding cells, unbudded daughter cells and unbudded parent cells - K _B1, K _B2, K _B3, K _EG, K _Ad parameters in the metabolic model - m _ATP mol(gh)^–1 maintenance coefficient for ATP - n _b, n _d, n _p number of age intervals in the budding phase, daughter phase and parent phase - PO _min, PO _max minimal and maximal effectiveness of oxidative phosphorylation - r _Acmax mol(gh)^–1 saturation value of the specific acetyl-CoA-reaction rate - S kg m^–3 concentration of total reduceable sugars - S _R kg m^–3 substrate concentration in the feed - T cell number doubling time - T _fh fermentation period - U _dh length of unbudded daughter cell cycling phase - U _ph length of unbudded parent cell cycling phase - V _cell m³ average volume of yeast cells - V _L m³ liquid volume of the reactor - X kg m^–3 cell mass concentration - X _N cm^–3 cell number concentration - Y _ATP g mol_ATP ^–1 yield coefficient of ATP - parameter in the exponential redistribution function - h^–1 specific growth rate - h length of the discrete age interval of cell cycle phases - suffix old and new denote the value before and after increasing of      

Intraparticle mass-transfer resistance and apparent time stability of immobilized yeast alcohol dehydrogenase

The stability and, consequently, the lifetime of immobilized enzymes (IME) are important factors in practical applications of IME, especially so far as design and operation of the enzyme reactors are concerned. In this paper a model is presented which describes the effect of intraparticle diffusion on time stability behaviour of IME, and which has been verified experimentally by the two-substrate enzymic reaction. As a model reaction the ethanol oxidation catalysed by immobilized yeast alcohol dehydrogenase was chosen. The reaction was performed in the batch-recycle reactor at 303 K and pH-value 8.9, under the conditions of high ethanol concentration and low coenzyme (NAD⁺) concentration, so that NAD⁺ was the limiting substrate. The values of the apparent and intrinsic deactivation constant as well as the apparent relative lifetime of the enzyme were calculated.The results show that the diffusional resistance influences the time stability of the IME catalyst and that IME appears to be more stabilized under the larger diffusion resistance.List of Symbols C _A, C_B, C_E mol · m^–3 concentration of coenzyme NAD⁺, ethanol and enzyme, respectively - C _p mol · m³ concentration of reaction product NADH - d _p mm particle diameter - D _eff m² · s^–1 effective volume diffusivity of NAD⁺ within porous matrix - k _d s^–1 intrinsic deactivation constant - K _A, K_A, K_B mol · m^–3 kinetic constant defined by Eq. (1) - K _A ^x mol · m^–3 kinetic constant defined by Eq. (5) - r _A mol · m^–3 · s^–1 intrinsic reaction rate - R m particle radius - R _v mol · m^–3 · s^–1 observed reaction rate per unit volume of immobilized enzyme - t _E s enzyme deactivation time - t _r s reaction time - V mol · m^–3 · s^–1 maximum reaction rate in Eq. (1) - V ^x mol · m^–3 · s^–1 parameter defined by Eq. (4) - V _f m³ total volume of fluid in reactor - w _s kg mass of immobilized enzyme bed - factor defined by Eqs. (19) and (20) - kg · m^–3 density of immobilized enzyme bed - unstableness factor - effectiveness factor - Thiele modulus - relative half-lifetime of immobilized enzyme Index o values obtained with fresh immobilized enzyme     

Modelling continuous culture of Rhodospirillum rubrum in photobioreactor under light limited conditions

Rhodospirillum rubrum was grown continuously and photoheterotrophically under light limitation using a cylindrical photobioreactor in which the steady state biomass concentration was varied between 0.4 to 4 kg m^–3 at a constant radiant incident flux of 100 W m^–2. Kinetic and stoichiometric models for the growth are proposed. The biomass productivities, acetate consumption rate and the CO₂ production rate can be quantitatively predicted to a high level of accuracy by the proposed model calculations. Nomenclature: C _X, biomass concentration (kg m^–3) D, dilution rate (h^–1) Ea, mean mass absorption coefficient (m² kg^–1) I , total available radiant light energy (W m^–2) K, half saturation constant for light (W m^–2) R _W, boundary radius defining the working illuminated volume (m) r _X, local biomass volumetric rate (kg m^–3 h^–1) <r _X>, mean volumetric growth rate (kg m^–3 h^–1) V _W, illuminated working volume in the PBR (m^–3). Greek letters: , working illuminated fraction (–) _M, maximum quantum yield (–) bar, mean energetic yield (kg J^–1).     

New solution method for equations of reaction and mass transfer in biocatalyst particles

Summary For numerical solution of the reaction-mass transfer equations for immobilised biocatalysts it may be better to start integration at the particle surface and proceed inwards: calculations are targetted on the region to which practically interesting changes are often confined (because concentrations are effectively zero in the interior); and during iterative solution wrong initial estimates may be rejected after detecting anomalies early in the integration.Symbols C_b substrate concentration in bulk (mol m^–3) - c dimensionless substrate concentration (C/C_b) (-) - D_e effective diffusion coefficient (m²s^–1) - Da Damkohler number (V.r_o ²/D_e.K_s) (-) - K_s substrate concentration kinetic coefficient (mol m^–3) - k_e external mass transfer coefficient (ms^–1) - r_o bead radius (m) - Sh Sherwood number (k_e.r_o/D_e) (-) - V maximum rate per unit volume in beads (mol m^–3s^–1) - x dimensionless distance from bead centre (r/r_o) (-) - dimensionless kinetic coefficient (K_s/C_b) (-) - _o effectiveness factor (-)     

Effect of light intensity and ammonium-N on carotenogenesis ofTrentepohlia odorata andDunaliella bardawil

AxenicTrentepohlia odorata was cultured at three different NH₄Cl levels (3.5 × 10^–2, 3.5 × 10^–3, 3.5 × 10^–4 M) and three different light intensities (48, 76, 122 µmol m^–2 s^–1). Chloride had no effect on growth over this range of concentration. High light intensity and high NH₄Cl concentration enhanced the specific growth rate. The carotenoid content increased under a combination of high light intensity and low N concentration. WhenD. bardawil was exposed to the same combination of growth conditions, there was an increase in its carotenoid content. The light saturation and the light inhibition constants (K _s andK _i, respectively) for growth, and the saturation constant (K _m) for NH₄Cl were determined. TheK _s andK _i values were higher inT. odorata (66.7 and> 122 mol m^–2 s^–1, respectively) than inD. bardawil (5.1 and 14.7 µmol m^–2 s^–1, respectively). TheK _m value determined at 122 µmol m^–2 s^–1, however, was lower inT. odorata (0.048 µM) than inD. bardawil (0.062 µM).Author for correspondence     

Modeling of the pyruvate production with<Emphasis Type="Italic"> Escherichia coli</Emphasis> in a fed-batch bioreactor

A family of 10 competing, unstructured models has been developed to model cell growth, substrate consumption, and product formation of the pyruvate producing strain Escherichia coli YYC202 ldhA::Kan strain used in fed-batch processes. The strain is completely blocked in its ability to convert pyruvate into acetyl-CoA or acetate (using glucose as the carbon source) resulting in an acetate auxotrophy during growth in glucose minimal medium. Parameter estimation was carried out using data from fed-batch fermentation performed at constant glucose feed rates of q_VG=10 mL h^–1. Acetate was fed according to the previously developed feeding strategy. While the model identification was realized by least-square fit, the model discrimination was based on the model selection criterion (MSC). The validation of model parameters was performed applying data from two different fed-batch experiments with glucose feed rate q_VG=20 and 30 mL h^–1, respectively. Consequently, the most suitable model was identified that reflected the pyruvate and biomass curves adequately by considering a pyruvate inhibited growth (Jerusalimsky approach) and pyruvate inhibited product formation (described by modified Luedeking–Piret/Levenspiel term).List of symbols c_A acetate concentration (g L^–1) - c_A,0 acetate concentration in the feed (g L^–1) - c_G glucose concentration (g L^–1) - c_G,0 glucose concentration in the feed (g L^–1) - c_P pyruvate concentration (g L^–1) - c_P,max critical pyruvate concentration above which reaction cannot proceed (g L^–1) - c_X biomass concentration (g L^–1) - K_I inhibition constant for pyruvate production (g L^–1) - K_I^A inhibition constant for biomass growth on acetate (g L^–1) - K_P saturation constant for pyruvate production (g L^–1) - K_P inhibition constant of Jerusalimsky (g L^–1) - K_S^A Monod growth constant for acetate (g L^–1) - K_S^G Monod growth constant for glucose (g L^–1) - m_A maintenance coefficient for growth on acetate (g g^–1 h^–1) - m_G maintenance coefficient for growth on glucose (g g^–1 h^–1) - n constant of extended Monod kinetics (Levenspiel) (–) - q_V volumetric flow rate (L h^–1) - q_VA volumetric flow rate of acetate (L h^–1) - q_VG volumetric flow rate of glucose (L h^–1) - r_A specific rate of acetate consumption (g g^–1 h^–1) - r_G specific rate of glucose consumption (g g^–1 h^–1) - r_P specific rate of pyruvate production (g g^–1 h^–1) - r_P,max maximum specific rate of pyruvate production (g g^–1 h^–1) - t time (h) - V reaction (broth) volume (L) - Y_P/G yield coefficient pyruvate from glucose (g g^–1) - Y_X/A yield coefficient biomass from acetate (g g^–1) - Y_X/A,max maximum yield coefficient biomass from acetate (g g^–1) - Y_X/G yield coefficient biomass from glucose (g g^–1) - Y_X/G,max maximum yield coefficient biomass from glucose (g g^–1) - growth associated product formation coefficient (g g^–1) - non-growth associated product formation coefficient (g g^–1 h^–1) - specific growth rate (h^–1) - _max maximum specific growth rate (h^–1)     

Nonlinear adaptive optimization of biomass productivity in continuous bioreactors

A novel on-line adaptive optimization algorithm is developed and applied to continuous biological reactors. The algorithm makes use of a simple nonlinear estimation model that relates either the cell-mass productivity or the cell-mass concentration to the dilution rate. On-line estimation is used to recursively identify the parameters in the nonlinear process model and to periodically calculate and steer the bioreactor to the dilution rate that yields optimum cell-mass productivity. Thus, the algorithm does not require an accurate process model, locates the optimum dilution rate online, and maintains the bioreactors at this optimum condition at all times. The features of the proposed new algorithm are compared with those of other adaptive optimization techniques presented in the literature [1–5]. A detailed simulation study using three different microbial system models [3, 6–7] was conducted to illustrate the performance of the optimization algorithm.List of Symbols A(q ^–1) polynomial in q ^–1 - b bias term - c _F nutrient cost term - B(q ^–1) polynomial in q ^–1 - C(q ^–1) polynomial in q ^–1 - CMPR kg/(m³ · h) cell mass productivity - D 1/h dilution rate - D _opt 1/h optimum dilution rate - E(q ^–1) polynomial in q ^–1 - h exponential filter constant - J objective function - k time index - K _m Monod's constant - n optimization interval - P covariance matrix - q ^–1 backward shift operator - r defined by equation (28) - S kg/m³ substrate concentration - S _F kg/m³ feed substrate concentration - T _s h sampling period - u vector containing previous input values - V dm³ fermenter volume - X kg/dm³ cell mass concentration - Y output variable - Y vector containing previous output values - Y _x/s g/g yield coefficient - optimization tuning constant - vector linear or nonlinear combination of u and Y - denominator covariance matrix update equation - forgetting factor - parameter vector - 1/h specific growth rate - _m 1/h maximum specific grow rate     

Development of reactor model for glucose isomerization catalyzed by whole-cell immobilized glucose isomerase

Based on the kinetic constants determined and the mathematical model of the reactor system developed, the performance of axial flow packed bed continuous enzyme reactor system was studied experimentally and also simulated with the aid of a computer for ultimate objective of optimization of the glucose isomerase reactor system.A reactor model was established analogous to heterogeneous catalytic reactor model taking into account the effect of fluid mass transfer and reversible kinetics. The investigated catalyst system consists of immobilized Streptomyces bambergiensis cells containing the enzyme glucose isomerase, which catalyzes the isomerization of glucose to fructose.List of Symbols A ₀, A ₁, A ₂ parameters in axial dispersion reactor model - c _go, c_g, c_gemol m^–3 glucose concentration at time t=0, at any time and at equilibrium conditions - c _gsmol m^–3 glucose concentration at particle surface - C dimensionless glucose concentration - d _pm particle diameter - d _rm diameter of reactor tube - Da Damkohler number - D _eff m² s^–1 effective glucose diffusion coefficient in Ca-alginate gel beads - k _fm s^–1 film transfer coefficient - K _e equilibrium constant - K _mg, K_mfmol m^–3 Michaelis-Menten constant for glucose and fructose, respectively - K _mmol m^–3 modified Michaelis-Menten constant - K dimensionless parameter - K ^* dimensionless parameter - L m length of reactor tube - Pe Peclet number - Pe _p particle Peclet number - Q m³ s^–1 volumetric flow rate - (-r _g) mol m^–3 s^–1 reaction rate - Re _p Reynolds particle number - Sc Schmidt number - Sh Sherwood number - t s time - v ₀ m s^–1 linear superficial fluid velocity - V _mg, V_mfmol g^–1 s^–1 maximal reaction rate for glucose and fructose, respectively - V _mmol m^–3 s^–1 modified maximal reaction rate for glucose - V _mg ^x mol m^–2 s^–1 maximal reaction rate for glucose - X _g, X_ge glucose conversion and glucose conversion at equilibrium conditions - X normalized conversion - Y dimensionless glucose concentration - void fraction of fixed bed - effectiveness factor of biocatalyst - Pa s kinematic viscosity of substrate - ₁ s first absolute weighted moment - ₂ s² second central weighted moment - _gkg m^–3 substrate density - _pkg m^–3 particle density - ² dimensionless variance of RTD curve - s residence time     

Inhibitory effect of dihydroxyacetone onGluconobacter oxydans: Kinetic aspects and expression by mathematical equations

Summary Microbial conversion of glycerol into dihydroxyacetone (DHA) byGluconobacter oxydans was subjected to inhibition by excess substrate. Comparison of cultures containing increasing initial DHA contents (0 to 100 g l^–1) demonstrated that DHA also inhibited this fermentation process. The first effect was on bacterial growth (cellular development stopped when DHA concentration reached 67 gl^–1), and then on oxidation of glycerol (DHA synthesis only occurred when the DHA concentration in the culture medium was lower than 85 g l^–1). Productivity, specific rates and, to a lesser extent, conversion yields decreased as initial concentrations of DHA increased. The changes in the specific parameters according to increasing initial DHA contents were described by general equations. These formulae satisfactorily express the concave aspect of the curves and the reduction in biological activity when the cells were in contact with DHA concentrations of up to 96 g l^–1.Abbreviations X, S, P biomass, substrate, product concentrations - r _x,r _s,r _p rates of growth, consumption and production - ,q _s,q _p specific rates of growth, glycerol consumption and DHA production - Y _x/s, Y_p/s conversion yields of substrate into biomass and product - K _s constant of affinity of cells to the substrate - K _ip product inhibition constant - P _m threshold concentration of DHA in substrate     

Photosynthetic light-use by three bromeliads originating from shaded sites (<Emphasis Type="Italic">Ananas ananassoides,Ananas comosus</Emphasis> cv. Panare) and exposed sites (<Emphasis Type="Italic">Pitcairnia pruinosa</Emphasis>) in the medium Orinoco basin,Venezuela

Three Bromeliaceae species of the medium Orinoco basin, Venezuela, were compared in their light-use characteristics. The bromeliads studied were two species of pineapple, i.e. the wild species Ananas ananassoides originating from the floor of covered moist forest, and the primitive cultivar Panare of Ananas comosus mostly cultivated in semi-shaded palm swamps, and Pitcairnia pruinosa, a species abundant in highly sun exposed sites on rock outcrops. Ananas species are Crassulacean acid metabolism (CAM) plants, P. pruinosa is C₃ plant. Plants were grown at low daily irradiance (LL = 1.3 mol m^–2 d^–1 corresponding to an incident irradiance of 30 mol m^–2 s^–1) and at high irradiance (HL = 14.7 mol m^–2 d^–1 or 340 mol m^–2 s^–1), and CO₂ and H₂O-vapour gas exchange and photochemical (q_P) and non-photochemical quenching (q_NP) of chlorophyll a fluorescence of photosystem 2 (PS2) were measured after transfer to LL, medium irradiance (ML = 4.1 mol m^–2 d^–1 or 95 mol m^–2 s^–1) and HL. All plants showed flexible light-use, and q_P was kept high under all conditions. LL-grown plants of Ananas showed particularly high rates of CAM-photosynthesis when transferred to HL and were not photoinhibited.     

Cost minimization in the predesign of an enzymatic CSTR: an overall approach

The balance equations pertaining to the modelling of a CSTR performing an enzyme-catalyzed reaction in the presence of enzyme deactivation are developed. Combination of heuristic correlations for the size-dependent cost of equipment and the purification-dependent cost of recovery of product with the mass balances was used as a basis for the development of expressions relating a (suitably defined) dimensionless economic parameter with the optimal outlet substrate concentration under the assumption that overall production costs per unit mass of product were to be minimized. The situation of Michaelis-Menten kinetics for the substrate depletion and first order kinetics for the deactivation of enzyme (considering that the free enzyme and the enzyme in the enzyme/substrate complex deactivate at different rates) was explored, and plots for several values of the parameters germane to the analysis are included.List of Symbols C _E mol m^–3 concentration of active enzyme - C _E,0 mol m^–3 initial concentration of active enzyme - C _p mol m^–3 concentration of product of interest - C _s mol m^–3 concentration of substrate - C _s,0 mol m^–3 initial concentration of substrate - I $ capital cost of equipment - k _d s^–1 deactivation constant of free enzyme - k _d s^–1 deactivation constant of enzyme in enzyme/substrate complex - K _m mol m^–3 Michaelis-Menten constant - K _m dimensionless counterpart of K _m - k _r s^–1 rate constant associated with conversion of enzyme/substrate complex into product - M _w kg mol^–1 molecular weight of product of interest - P $ kg^–1 cost of recovery of product of interest in pure form - Q m³s^–1 volumetric flow rate - V m³ volume of reactor - X $ kg^–1 global manufacture cost of product of interest in pure form - X dimensionless counterpart of X Greek Symbols ₁ $ m^–1.8 constant - ₂ $ m^–3 constant - t s useful life of CSTR - ₀ ratio of initial concentrations of enzyme and substrate - ratio of deactivation constant of free enzyme to rate constant of depletion of substrate - ratio of deactivation constants - univariate function expressing the dependence of the rate of enzyme deactivation on C _S - univariate function expressing the dependence of the rate of substrate depletion on C _S - dimensionless economic parameter     

Relationship Between Photosystem 2 Electron Transport and Photosynthetic CO2 Assimilation Responses to Irradiance in Young Apple Tree Leaves

The responses to irradiance of photosynthetic CO₂ assimilation and photosystem 2 (PS2) electron transport were simultaneously studied by gas exchange and chlorophyll (Chl) fluorescence measurement in two-year-old apple tree leaves (Malus pumila Mill. cv. Tengmu No.1/Malus hupehensis Rehd). Net photosynthetic rate (P _N) was saturated at photosynthetic photon flux density (PPFD) 600-1 100 (mol m^-2 s^-1, while the PS2 non-cyclic electron transport (P-rate) showed a maximum at PPFD 800 mol m^-2 s^-1. With PPFD increasing, either leaf potential photosynthetic CO₂ assimilation activity (F_d/F_s) and PS2 maximal photochemical activity (F_v/F_m) decreased or the ratio of the inactive PS2 reaction centres (RC) [(F_i – F_o)/(F_m – F_o)] and the slow relaxing non-photochemical Chl fluorescence quenching (q_s) increased from PPFD 1 200 mol m^-2 s^-1, but cyclic electron transport around photosystem 1 (RFp), irradiance induced PS2 RC closure [(F_s – F_o)/F_m – F_o)], and the fast and medium relaxing non-photochemical Chl fluorescence quenching (q_f and q_m) increased remarkably from PPFD 900 (mol m^-2 s^-1. Hence leaf photosynthesis of young apple leaves saturated at PPFD 800 mol m^-2 s^-1 and photoinhibition occurred above PPFD 900 mol m^-2 s^-1. During the photoinhibition at different irradiances, young apple tree leaves could dissipate excess photons mainly by energy quenching and state transition mechanisms at PPFD 900-1 100 mol m^-2 s^-1, but photosynthetic apparatus damage was unavoidable from PPFD 1 200 mol m^-2 s^-1. We propose that Chl fluorescence parameter P-rate is superior to the gas exchange parameter P _N and the Chl fluorescence parameter F_v/F_m as a definition of saturation irradiance and photoinhibition of plant leaves.     

Optimal control strategy for the enhanced production of cellulase enzyme using the new mutant Trichoderma reesei E-12

Cellulase enzyme production was enhanced using the mutant strain Trichoderma reesei, E-12, which was shown to be partially resistant to catabolite repression. An optimal profile for pH, which was found to be the critical environmental parameter, was determined using a rigorous mathematical optimization procedure. Semi-empirical models were used to minimize complications in the computation. A 30% increase in enzyme activity and productivity was obtained using the optimal pH strategy as compared to the pH cycling strategy.List of Symbols a ₁ , a ₂ , a ₃ d^–1, d^–2, d^–3 coefficients of the polynomial in the generalized logistic growth model - a ₄, a ₅, a ₆ d^–1, d^–2, d^–3 coefficients of the polynomial in the generalized logistic product model - b ₁ d^–1 enzyme synthesis rate constant - b ₂ d ^–1 enzyme decay rate constant - b ₃ power coefficient in the polynomial model for enzyme synthesis - H Hamiltonian function - J Objective function of the maximization procedure - K ₁ kg/m³ limiting cell mass concentration in biomass logistic model - K _s kg/m³ saturation constant - K ^s kg/m³ saturation death rate constant - q power coefficient in polynomial model - s kg/m³ substrate concentration - t d fermentation time - T d total fermentation time (=7 d) - x ₁₀ kg/m³ initial biomass concentration - x ₁ kg/m³ biomass concentration at time t - x ₂ F.P.A enzyme activity at time t - x ₃ d state variable replacing time term on the right hand side of biomass equation - x _f kg/m³ final biomass concentration - z ₁, z ₂, z ₃ adjoint variable corresponding to state variable x ₁, x ₂, x ₃ - d^–1 specific death rate - d^–1 specific growth rate     

Process kinetic analysis of pleuromulin fermentation

The industrial production of pleuromulin, an example for the production of secondary metabolites, has been carried out of the corporation Biochemie Kundl/Austria. The results of the experiments, especially the process kinetics are analyzed following the principles of the integrating strategy, which has been developed by the authors.Experiments on technical and laboratory scale were carefully designed and evaluated in order to allow an adequate insight in to this complex bioprocess. Typical plots are presented to illustrate the general macroscopic behaviour which serve as a reliable basis for process quantification.Mathematic modelling of this bioprocess will be presented in a following paper.List of Symbols n l/min rotational speed - P kg/m³ pleuromulin concentration - q _P h^–1 specific production rate - q _S1 h^–1 specific rate of glucose consumption - q _S2 h^–1 specific rate of oil consumption - r _P kg/m³ · h product formation rate - r _S1 kg/m³ · h glucose consumption rate - r _X kg/m³ · h growth rate - S ₁ kg/m³ glucose concentration - S ₂ kg/m³ oil concentration - T °C temperature - t h, d time - _g m³/h gas flow rate - X kg/m³ mycelium dry weight - Y _i/j yield coefficient - _app mPa s apparent viscosity - h^–1 specific growth rate The authors extend their gratitude to Biochemie Kundl Gmbh, where the experimental work has been carefully carried out     

Determination of the inherent kinetics of immobilized glucose oxidase using a diffusion cell

The enzyme glucose oxidase (GO) was covalently immobilized onto a poly(vinyl alcohol) hydrogel, cross-linked with glutardialdehyde and a polyazonium salt. To compare the kinetic parameters of immobilized GO with the known kinetic parameters of soluble GO, the diffusion cell method was used.Between two compartments, containing solutions with different glucose concentrations, a GO-containing hydrogel membrane was placed. Simultaneous diffusion through and enzymatic reaction in the membrane occurred. In this way diffusional effects of the membrane could be eliminated from the effective kinetic parameters to yield the inherent kinetic parameters.It appeared that the enzymatic reaction is independent of the oxygen concentration at oxygen concentrations 0.22 mol m^–3 (Michaelis constant for oxygen < 0.22 mol m^–3). Further, the Michaelis constant for glucose does not change dramatically after immobilizing the enzyme. The maximal reaction rate is depending on the enzyme concentration. As the enzyme concentration in the membrane is not exactly known (mainly due to leakage of enzyme out of the membrane during membrane preparation), only an estimation of the turnover number can be made.The diffusion cell method is easy to carry out. Still, some recommendations can be made on the performance.List of Symbols _g , _0x partition coefficient of glucose and oxygen, respectively - thickness of the wetted membrane (m) - A _m surface area of membrane (m^–2) - C constant (mol² m^–3) - c _g , c _0x concentration of glucose and oxygen, respectively (mol m^–3) - c _g,0 c _g, glucose concentration at the filter-paper/membrane interface next to compartment A and B, respectively (mol m^–3) - c _{g, A} c _{g, B} glucose concentration in compartment A and B, respectively (mol m^–3) - c _GO glucose oxidase concentration (mol m^–3) - D _eff effective diffusion coefficient (m² s^–1) - D _m , D _sl diffusion coefficient in, respectively, the membrane and the solution layer (m² s^–1) - d _dl , d _df , d _sl thickness of, respectively, the diffusion layer, the filter-paper and the solution layer (m) - h _B initial slope of concentration versus time curve of compartment B (mol m^–3 s^–1) - J flux (mol m^–2 s^–1) - J ₀ flux in the membrane at membrane/filter-paper interface next to compartment A and B, respectively (mol m^–2 s^–1) - J _A , J _B flux leaving compartment A and entering compartment B, respectively (mol m^–2 s^–1) - J _m flux through the membrane (mol m^–2 s^–1) - k total mass transfer coefficient (m s^–1) - k ₁ , k ₂ rate constant of a particular reaction step (m³ mol^–1 s^–1) - k_–1, k_–2 rate constant of a particular reaction step (s^–1) - k _cat (intrinsic) catalytic constant of turnover number (s^–1) - k _cat ^* inherent catalytic constant, determined by inserting D _m (s^–1) - k _cat ^** inherent catalytic constant, determined by inserting D _eff (s^–1) - k _m (g) (intrinsic) Michaelis constant for glucose (mol m^–3) - k _m (o) (intrinsic) Michaelis constant for oxygen (mol m^–3) - k _m ^* (g) inherent Michaelis constant for glucose (mol m^–3) - k _m ^* (o) inherent Michaelis constant for oxygen (mol m^–3) - m _GO number of moles of GO present (mol) - P _m permeability of glucose in the mebrane (m s^–1) - P _eff effective permeability (m s^–1) - V volume (m³) - v ₀ initial reaction velocity (mol m^–3 s^–1) - V _max ^** inherent maximal reaction velocity, determined by inserting D_eff (mol m^–3 s^–1) - x distance (m)     

Process engineering aspects of the bioleaching of copper ores

The bioleaching of minerals is a complex process that is affected by a number of biological, mineralogical, electrochemical and engineering factors. This work presents and discusses the most significant process engineering aspects involved in the bacterial leaching of copper ores, i.e. bacterial population, type of mineral and particle size, nutrients and inhibitors, oxygen and carbon dioxide, temperature and pH, leaching kinetics and operation mode.It is concluded that more work is needed in this area in order to gain a deeper insight in the many factors that govern this process. This would allow to significantly improve its overall productivity.List of Symbols C _L kg/m³ dissolved oxygen concentration - C ^* kg/m³ equilibrium oxygen concentration - d, e, f, g % percentage of C, H, O and N in the cell - D m impeller diameter - K consistency index - K _S, K₁, K_c constants - k _La h^–1 volumetric oxygen transfer coefficient - M _b mol/kg biomass apparent molecular weight - N s^–1 rotation frequency - n behavior index - P kg/m³ ungassed agitation power, product concentration - P _g kW/m³ gassed agitation power - p % pulp density - Q m³/h air flow rate - S kg/m³ limiting substrate concentration - W kg/(m³ · h) mass transfer rate per unit volume - X cells/cm³ biomass concentration - Y _o g cells/g Fe oxygen cell yield - Y _x g cells/g Fe substrate cell yield - h^–1 specific growth rate - _m h^–1 maximum specific growth rate     

Analysing the responses of photosynthetic CO2 assimilation to long-term elevation of atmospheric CO2 concentration

Understanding how photosynthetic capacity acclimatises when plants are grown in an atmosphere of rising CO₂ concentrations will be vital to the development of mechanistic models of the response of plant productivity to global environmental change. A limitation to the study of acclimatisation is the small amount of material that may be destructively harvested from long-term studies of the effects of elevation of CO₂ concentration. Technological developments in the measurement of gas exchange, fluorescence and absorption spectroscopy, coupled with theoretical developments in the interpretation of measured values now allow detailed analyses of limitations to photosynthesisin vivo. The use of leaf chambers with Ulbricht integrating spheres allows separation of change in the maximum efficiency of energy transduction in the assimilation of CO₂ from changes in tissue absorptance. Analysis of the response of CO₂ assimilation to intercellular CO₂ concentration allows quantitative determination of the limitation imposed by stomata, carboxylation efficiency, and the rate of regeneration of ribulose 1:5 bisphosphate. Chlorophyll fluorescence provides a rapid method for detecting photoinhibition in heterogeneously illuminated leaves within canopies in the field. Modulated fluorescence and absorption spectroscopy allow parallel measurements of the efficiency of light utilisation in electron transport through photosystems I and IIin situ.Abbreviations A net rate of CO₂ uptke per unit leaf area (µmol m^–2 s^–1) - A_sat light-saturated A - A₈₂₀ change in absorptance of PSI on removal of illumination (OD) - c CO₂ concentration in air (µmol mol^–1) - c_a c in the bulk air; c_i, c in the intercellular spaces - ce carboxylation efficiency (mol m^–2 s^–1) - E transpiration per unit leaf area (mol m^–2 s^–1) - F fluorescence emission of PSII (relative units) - F_m maximal level of F - F_o minimal level of F upon illumination when PSII is maximally oxidised - F_s the steady-state F following the m peak - F_v the difference between F_m and F_o - F'_m maximal F' generated after the m peak by addition of a saturating light pulse - F'_o the minimal level of F' after the m peak determined by re-oxidising PSII by far-red light - g₁ leaf conductance to CO₂ diffusion in the gas phase (mol m^–2 s^–1) - g'₁ leaf conductance to water vapour diffusion in the gas phase (mol m^–2 s^–1) - k_c and k_o the Michaelis constants for CO₂ and O₂, respectively, (µmol mol^–1); - J_max the maximum rate of regeneration of rubP (µmol m^–2 s^–1) - l stomatal limitation to CO₂ uptake (dimensionless, 0–1) - LCP light compensation point of photosynthesis (µmol m^–2 s^–1) - o_i the intercellular O₂ concentration (mmol mol^–1) - Pi cytosol inorganic phosphate concentration - PSI photosystem I - PSII photosystem II - Q photon flux (µmol m^–2 s^–1) - Q_abs Q absorbed by the leaf - rubisCO ribulose 1:5 bisphosphate carboxylase/oxygenase; rubP, ribulose 1:5 bisphosphate; s, projected surface area of a leaf (m²) - V_c,max is the maximum rate of carboxylation (µmol m^–2 s^–1) - W_c the rubisCO limited rate of carboxylation (µmol m^–2 s¹) - W_j the electron transport limited rate of regeneration of rubP (µmol m^–2 s^–1) - W_p the inorganic phosphate limited rate of regeneration of rubP (µmol m^–2 s^–1) - absorptance of light (dimensionless, 0–1) - _a of standard black absorber ₁, of leaf - _s of integrating sphere walls - , CO₂ compensation point of photosynthesis (µmol mol^–1) - the specificity factor for rubisCO carboxylation (dimensionless) - , convexity of the response of A to Q (dimensionless 0–1) - the quantum yield of photosynthesis on an absorbed light basis (A/Q_abs; dimensionless) - the quantum yield of photosynthesis on an incident light basis (A/Q; dimensionless) - _app the maximum - _m the maximum - _m,app the photochemical efficiency of PSII (dimensionless, 0–1) - _PSII,m the maximum      

Fed-batch production of baker's yeast using millet (Pennisetum typhoides) flour hydrolysate as the carbon source

A fermentation medium based on millet (Pennisetum typhoides) flour hydrolysate and a four-phase feeding strategy for fed-batch production of baker's yeast,Saccharomyces cerevisiae, are presented. Millet flour was prepared by dry-milling and sieving of whole grain. A 25% (w/v) flour mash was liquefied with a thermostable 1,4--d-glucanohydrolase (EC 3.2.1.1) in the presence of 100 ppm Ca²⁺, at 80°C, pH 6.1–6.3, for 1 h. The liquefied mash was saccharified with 1,4--d-glucan glucohydrolase (EC 3.2.1.3) at 55°C, pH 5.5, for 2 h. An average of 75% of the flour was hydrolysed and about 82% of the hydrolysate was glucose. The feeding profile, which was based on a model with desired specific growth rate range of 0.18–0.23 h^–1, biomass yield coefficient of 0.5 g g^–1 and feed substrate concentration of 200 g L^–1, was implemented manually using the millet flour hydrolysate in test experiments and glucose feed in control experiments. The fermentation off-gas was analyzed on-line by mass spectrometry for the calculation of carbon dioxide production rate, oxygen up-take rate and the respiratory quotient. Off-line determination of biomass, ethanol and glucose were done, respectively, by dry weight, gas chromatography and spectrophotometry. Cell mass concentrations of 49.9–51.9 g L^–1 were achieved in all experiments within 27 h of which the last 15 h were in the fedbatch mode. The average biomass yields for the millet flour and glucose media were 0.48 and 0.49 g g^–1, respectively. No significant differences were observed between the dough-leavening activities of the products of the test and the control media and a commercial preparation of instant active dry yeast. Millet flour hydrolysate was established to be a satisfactory low cost replacement for glucose in the production of baking quality yeast.Nomenclature C _ox Dissolved oxygen concentration (mg L^–1) - CPR Carbon dioxide production rate (mmol h^–1) - C _s0 Glucose concentration in the feed (g L^–1) - C _s Substrate concentration in the fermenter (g L^–1) - C _s.crit Critical substrate concentration (g L^–1) - E Ethanol concentration (g L^–1) - F _s Substrate flow rate (g h^–1) - i Sample number (–) - K _e Constant in Equation 6 (g L^–1) - K _o Constant in Equation 7 (mg L^–1) - K _s Constant in Equation 5 (g L^–1) - m Specific maintenance term (h^–1) - OUR Oxygen up-take rate (mmol h^–1) - q _ox Specific oxygen up-take rate (h^–1) - q _ox.max Maximum specific oxygen up-take rate (h^–1) - q _p Specific product formation rate (h^–1) - q _s Specific substrate up-take rate (g g^–1 h^–1) - q _s.max Maximum specific substrate up-take rate (g g^–1 h^–1) - RQ Respiratory quotient (–) - S Total substrate in the fermenter at timet (g) - S ₀ Substrate mass fraction in the feed (g g^–1) - t Fermentation time (h) - V Instantaneous volume of the broth in the fermenter (L) - V ₀ Starting volume in the fermenter (L) - V _si Volume of samplei (L) - x Biomass concentration in the fermenter (g L^–1) - X ₀ Total amount of initial biomass (g) - X _t Total amount of biomass at timet (g) - Y _p/s Product yield coefficient on substrate (–) - Y _x/e Biomass yield coefficient on ethanol (–) - Y _x/s Biomass yield coefficient on substrate (–) Greek letters Moles of carbon per mole of yeast (–) - Moles of hydrogen atom per mole of yeast (–) - Moles of oxygen atom per mole of yeast (–) - Moles of nitrogen atom per mole of yeast (–) - Specific growth rate (h^–1) - _crit Critical specific growth rate (h^–1) - _E Specific ethanol up-take rate (h^–1) - _max.E Maximum specific ethanol up-take rate (h^–1)     

Woody-tissue respiration for Simarouba amara and Minquartia guianensis,two tropical wet forest trees with different growth habits

We measured CO₂ efflux from stems of two tropical wet forest trees, both found in the canopy, but with very different growth habits. The species were Simarouba amara, a fast-growing species associated with gaps in old-growth forest and abundant in secondary forest, and Minquartia guianensis, a slow-growing species tolerant of low-light conditions in old-growth forest. Per unit of bole surface, CO₂ efflux averaged 1.24 mol m^–2 s^–1 for Simarouba and 0.83 mol m^–2s^–1 for Minquartia. CO₂ efflux was highly correlated with annual wood production (r ²=0.65), but only weakly correlated with stem diameter (r ²=0.22). We also partitioned the CO₂ efflux into the functional components of construction and maintenance respiration. Construction respiration was estimated from annual stem dry matter production and maintenance respiration by subtracting construction respiration from the instantaneous CO₂ flux. Estimated maintenance respiration was linearly related to sapwood volume (39.6 mol m^–3s^–1 at 24.6° C, r ²=0.58), with no difference in the rate for the two species. Maintenance respiration per unit of sapwood volume for these tropical wet forest trees was roughly twice that of temperate conifers. A model combining construction and maintenance respiration estimated CO₂ very well for these species (r ²=0.85). For our sample, maintenance respiration was 54% of the total CO₂ efflux for Simarouba and 82% for Minquartia. For our sample, sapwood volume averaged 23% of stem volume when weighted by tree size, or 40% with no size weighting. Using these fractions, and a published estimate of aboveground dry-matter production, we estimate the annual cost of woody tissue respiration for primary forest at La Selva to be 220 or 350 g C m^–2 year^–1, depending on the assumed sapwood volume. These costs are estimated to be less than 13% of the gross production for the forest.     

Photosynthesis and Water Use Efficiency in Twenty Tropical Tree Species of Differing Succession Status in a Brazilian Reforestation

Leaf gas exchange characteristics were measured in twenty woody species that differ in succession status ranging from pioneer species (PS) to late succession species (LS) in a Brazilian rain-reforestation ecosystem. Photon-saturated photosynthetic rate, calculated per either a leaf area (P _NA) or a dry mass (P _NM) basis, differed among species. P _NA and P _NM were highest in PS and lowest in LS. Variation among species was 3-fold (from 7 to 23 mol m^–2 s^–1) for P _NA, and 5-fold (from 50 to 275 mol kg^–2 s^–1) for P _NM. The highest P _NA (23 mol m^–2 s^–1) and P _NM (275 mol kg^–2 s^–1) values were recorded in PS Croton urucurana, while the lowest P _NA (7 mol m^–2 s^–1) and P _NM (50 mol kg^–2 s^–1) values were recorded in LS Aspidosperma cylindrocarpon. A considerable overlap was recorded between PS and LS in values of stomatal conductance (g _s), transpiration rate (E), and leaf mass to area ratio (ALM). However, C. urucurana also showed highest g _s and E. P _NM was highly correlated with ALM in both PS and LS (r=–0.75 and –0.90, respectively). The high values of instantaneous transpiration efficiency (ITE) and intrinsic water use efficiency (WUE_i) were also observed in the PS when compared with the LS.