共查询到20条相似文献,搜索用时 15 毫秒
1.
Kinetics of ethanol inhibition in alcohol fermentation 总被引:3,自引:0,他引:3
Luong JH 《Biotechnology and bioengineering》1985,27(3):280-285
The inhibitory effect of ethanol on yeast growth and fermentation has been studied for the strain Saccharomyces cerevisiae ATCC No. 4126 under anaerobic batch conditions. The results obtained reveal that there is no striking difference between the response of growth and ethanol fermentation. Two kinetic models are also proposed to describe the kinetic pattern of ethanol inhibition on the specific rates of growth and ethanol fermentation: \documentclass{article}\pagestyle{empty}\begin{document}$$\begin{array}{*{20}c} {\frac{{\mu _i }}{{\mu _0 }} = 1{\rm } - {\rm }\left( {\frac{P}{{P_m }}} \right);\alpha } \hfill & {\left( {{\rm for}\ {\rm growth}} \right)} \hfill \\ {\frac{{\nu _i }}{{\nu _0 }} = 1{\rm } - {\rm }\left( {\frac{P}{{P'_m }}} \right);\beta } \hfill & {\left( {{\rm for}\ {\rm ethanol}\ {\rm production}} \right)} \hfill \\ \end{array}$$\end{document} The maximum allowable ethanol concentration above which cells do not grow was predicted to be 112 g/L. The ethanol-producing capability of the cells was completely inhibited at 115 g/L ethanol. The proposed models appear to accurately represent the experimental data obtained in this study and the literature data. 相似文献
2.
Jürgen Benndorf 《International Review of Hydrobiology》1973,58(1):1-18
The phosphate removal in small, completely mixed storage reservoirs (preimpoundment basins) mainly is a function of the production of biomass by the phytoplankton. The knowledge of the critical detention time of the water is the most important premise to the prediction. The critical detention time t̄ is computed from the equation: \documentclass{article}\pagestyle{empty}\begin{document}$ \overline t _c = \frac{1}{{\mu ^* - 0,1}} $\end{document} and the growth rate μ* at a given combination of the light intensity J, temperature T and phosphate concentration P is computed from: \documentclass{article}\pagestyle{empty}\begin{document}$ \mu ^* = \frac{{\mu T \cdot \mu J \cdot \mu P}}{{\mu \max ^2 }}\mu \max \cdot \frac{P}{{K_p + P}}\frac{J}{{K_j + J}}\frac{T}{{T_{opt} }}, $\end{document} (μmax = maximum possible growth rate of the dominant species; Kp, Kj and Topt are constants computed from batch cultures). The quotient \documentclass{article}\pagestyle{empty}\begin{document}$ \frac{{\bar t_{act.} }}{{\bar t_c }}(\bar t_{act.} = {\rm actual detention time in the water body)} $\end{document} enables prediction of the phosphate removal. A comparison of the predicted results from semicontinuous cultures and from the preimpoundment basin of the Weida reservoir revealed a satisfactory degree of conformity. 相似文献
3.
Generalization of monod kinetics for analysis of growth data with substrate inhibition 总被引:6,自引:0,他引:6
Luong JH 《Biotechnology and bioengineering》1987,29(2):242-248
The inhibitory effect of butanol on yeast growth has been studied for the strain Candida utilis ATCC 8205 growing aerobically on butanol under batch conditions. A mathematical expression was then proposed to fit the kinetic pattern of butanol inhibition on the specific growth rate: \documentclass{article}\pagestyle{empty}\begin{document}$$ \mu = \frac{{\mu _m S}}{{K_s + S}}\left[{1 - \frac{S}{{S_m }}} \right];n $$\end{document}The maximum allowable butanol concentration above which cells do not grow was predicted to be 9.16g/L. The proposed model appears to accurately represent the experimental data obtained in this study and the literature data developed for a variety of batch culture systems at widely ranging substrate concentrations. 相似文献
4.
5.
Bolle WL van Breugel J van Eybergen GC Kossen NW van Gils W 《Biotechnology and bioengineering》1986,28(4):542-548
As a part of the development of an integral mathematical model describing the up-flow anaerobic sludge blanket (UASB) reactor, the kinetics of the conversion of organic wastes has to be known. We compared the Monod model with the model proposed by Andrews et al. Together with the assumption that the substrate for the anaerobic bacteria is formed by nonionized, volatile fatty acids, the Andrews model is able to describe substrate inhibition and reactor failure due to pH changes.From four batch experiments, with different concentrations of microorganisms, it could be concluded with a reliability of over 95% that the monod model was inadequate and Andrews' model was adequate to describe the measurements. Standard statistical techniques like the X2- and the F-test were used for this purpose.From a parameter sensitivity analysis for the Andrews model it followed that the maximum specific growth rate mu(A) (max) of the bacteria and the inhibition constant K(1) are the parameters which influence the system most. Thus, these parameter were determined experimentally and most accurately. The results are: \documentclass{article}\pagestyle{empty}\begin{document}$$\mu;{A}_{\max} = 16*10;{-4}{\rm h};{-1}\pm 2\%\quad {\rm and}\quad K_l = 0.0158\,{\rm g}\,{\rm HAc/L}\pm 2.5\%$$\end{document} The other parameters were taken from literature. From calculation of the Thiele modulus for the particles it follows that transport limitation of the substrate in the flocus is not significant. The efficiency eta is 0.85 in the worst case. 相似文献
6.
Experimental kinetic data (initial rate and high conversion) on the hydrolysis of cellobiose by 1,4-β-glucosidace (Gliocladium sp.) have been analysed and a competitive inhibition by glucose has been proposed. The determination of kinetic parameters from integral data is based upon algorithms for non-linear optimization and numerical integration. The values of kinetic constants \documentclass{article}\pagestyle{empty}\begin{document}$(v_{\max } = 1.02\frac{{\mu {\rm M}_{{\rm glucose}} }}{{{\rm mg}_{{\rm protein}} \cdot \min }},K_M = 2.6{\rm mM/l, and }K_P = 1.2{\rm mM/l)}$\end{document} agree well with the initialrate results. An important distinction is the confidence limit of parameters. Linear regression analysis shows a virtual accuracy and can lead to wrong conclusions. 相似文献
7.
Methanobacterium thermoautotrophicum was grown in continuous culture in a fermenter gassed with H2 and CO2 as sole carbon and energy sources, and in a medium which contained either NH4Cl or gaseous N2 as nitrogen source. Growth was possible with N2. Steady states were obtained at various gas flow rates with NH4Cl and with
and the maintenance coefficient varied with the gas input and with the nitrogen source. Growth of Methanococcus thermolithotrophicus in continuous culture in a fermenter gassed with H2, CO2 as nitrogen, carbon and energy sources was also examined.Abbreviations
molecular growth yield (g dry weight of cells per mol of CH4 evolved)
-
growth rate (h-1)
-
D
dilution rate (h-1)
- rate (h-1);
relation of Neijssel and Tempest and of Stouthamer and Bettenhaussen
-
energy 相似文献
8.
An electrochemical method of measuring the oxidation rate of ferrous to ferric iron with oxygen in the presence of Thiobacillus ferrooxidans 总被引:4,自引:0,他引:4
The oxidation of Fe(2+) with oxygen in sulfate solutions was studied in the presence of T. ferrooxidans. To measure the chemical activity of bacteria, and the oxidation rate of iron, the redox potentials of solutions were continuously monitored during the experiments. The redox potentials were simultaneously monitored on the platinum and pyrite indicator electrodes. The redox potential versus time curves were further used to calculate the basic kinetic parameters, such as the reaction orders, the activation energy, and the frequency factor. It was found that under atmospheric conditions, and at Fe(2+) < 0.001M, T < 25 degrees C, and at pH above 2.2, the oxidation of iron is governed by the following rate expression: \documentclass{article}\pagestyle{empty}\begin{document}$$ - \frac{{d[{\rm Fe};{2 + }]}}{{dt}} = 1.62 \times 10;{11} C_{{\rm bact}} [{\rm H}; + ][{\rm Fe};{2 + }]p{\rm O}_2 e;{ - (58.77/RT)} $$\end{document} Below pH = 2.2, the oxidation rate is independent of H(+) Concentration. 相似文献
9.
The presence of anions in solution was found to inhibit the uptake of La(3+), Cd(2+), Pb(2+), UO(2+) (2), and Ag(+) by Rhizopus arrhizus biomass. The effects ranged from total inhibition of Cd(2+) and Pb(2+) uptake at equimolar concentrations of EDTA to no change in uptake of La(3+) or UO(2+) (2) at 12-fold molar excesses of Cl(-) or CO(2-) (3). No anion was found to enhance metal uptake levels, and the degree of inhibition generally followed the series: \documentclass{article}\pagestyle{empty}\begin{document}$${\rm EDTA } \ge \ge {\rm SO}_{;{;{;{\rm 4} } } };{{\rm 2} - } \ge {\rm Cl}; - \ge {\rm PO}_{;{;{;{\rm 4} } } };{{\rm 3} - } \ge {\rm glutamate} \ge {\rm CO}_{;{;{\rm 3} } };{{\rm 2} - } $$\end{document} The chemical equilibrium model REDEQL2 was adapted to treat metal uptake by R. arrhizus biomass and used to predict the effects of anions in solution. Comparisons with the experimental results are made and discussed in light of the assumptions underlying the model. 相似文献
10.
Peter B. Bright 《Bulletin of mathematical biology》1967,29(1):95-121
Starting from the basic flux equation, it is possible to obtain an integral form relating the current componentsI i at an arbitrary pointr 2 to the distribution of mobilities and concentrationsc i, potential forces\(\bar \mu \), and chemical productivityp i without any restrictive assumptions such as constant mobilities, constant field, steady state, or electrical neutrality. The equation is
$$\begin{gathered} I_i (r_2 ) = G_i (r_2 )\left[ {\Delta \bar \mu _i - \int_{r_1 }^{r_2 } {z_i } FA\left( {p_i - dc_i /dt} \right)\left( {\frac{1}{{G_i (r)}}} \right)dr} \right]; \hfill \\ G_i (r) = 1/\int_{r_1 }^r {\frac{{dr}}{{z_i^2 F^2 c_i u_i }}.} \hfill \\ \end{gathered} $$ 相似文献
11.
Differential values of the specific ethanol production rate \documentclass{article}\pagestyle{empty}\begin{document}$$ v_{(t)} = \frac{1}{{x_{(t)} }} \cdot \frac{{dP}}{{dt}} $$ \end{document} can be calculated exactly from experimental batch fermentation process data by use of a nonlinear regression programme. The method used is based on the fact, that the function P = f(t) can be approximated by an exponential equation. The specific ethanol production rate is calculated then from the first differential derivation of this equation using the appropriated values of actual biomass concentration. For two strains of Saccharomyces cerevisiae a linear and nonlinear kinetic pattern, respectively, was found for product formation. This result can be explained by a simple mathematical relation according to ν=ν0 ? a . Pb,in which the exponent becomes 1 in the case of linear kinetic pattern. 相似文献
12.
W. J. Cunningham 《Bulletin of mathematical biology》1955,17(2):101-110
The simultaneous equations
$$\begin{gathered} \frac{{dx}}{{dt}} = \frac{{a_x }}{{k_x }}[k_x - x - f_x (y)] x \hfill \\ \frac{{dy}}{{dt}} = \frac{{a_y }}{{k_y }}[k_y - y - f_y (x)] y \hfill \\ \end{gathered}$$ 相似文献
13.
Deepak Pant 《The International Journal of Life Cycle Assessment》2013,18(8):1465-1469
Purpose
E-waste is the most rapidly growing problem throughout the world, which has serious future concerns over its management and recycling. This article proposes a simple approach for future e-waste projection which can be obtained by using life-span data of various electronic items along with incorporation of population statistics.Methods
For this purpose, 7-year sales data of electronic items were collected, which is then used to generate various mathematical equations. These mathematical relations are then modified by incorporating life-span and population data.Results and discussion
By comparing sales data with their life-span (average) and population statistics, future e-waste can be quantified both in terms of specified area under investigation and proposed estimation area. The following equation is thus proposed: E - waste In terms of quantity = m Waste projection year ? Life - span ? Initial data collection year + C × Population of estimation area Population of study area $$ \begin{array}{c}\mathrm{E}-\mathrm{waste}\;\\ {}\left(\mathrm{In}\ \mathrm{terms}\ \mathrm{of}\ \mathrm{quantity}\right)=\left[m\left\{\mathrm{Waste}\;\mathrm{projection}\;\mathrm{year}-\mathrm{Life}-\mathrm{span}\right\}-\mathrm{Initial}\ \mathrm{data}\ \mathrm{collection}\ \mathrm{year}+C\right]\times \frac{\mathrm{Population}\ \mathrm{of}\ \mathrm{estimation}\ \mathrm{area}}{\mathrm{Population}\ \mathrm{of}\ \mathrm{study}\ \mathrm{area}\ }\end{array} $$ Where m and C can be obtained from plotting year-wise sales data over Excel sheet.Conclusions
Local as well as global projection of future e-waste can be possible with the help of final equation. 相似文献14.
N(alpha)-Palmitoyl-L-lysyl-L-lysine-ethyl ester dihydrochloride (PLL) has antimicrobial properties and may be useful as a food preservative. This study was conducted to see if PLL can inhibit growth and synthesis of aflatoxin by Aspergillus parasiticus. Growth of mold and accumulation of aflatoxins were monitored for up to 15 days. To compare these data with those of a known inhibitor of aflatoxin synthesis, dichlorvos was added to media, and mold growth and aflatoxin accumulation were monitored. The kinetic model of Brown and Vass that correlates growth and formation of secondary metabolites was applied to results of this study, and values for maturation time (t(m)) and aflatoxin accumulation rate constant (alpha) were calculated. Values of t(m) decreased when cultures contained PLL, whereas presence of dichlorvos resulted in a considerable increase. The lag phase of mold growth increased in the presence of PLL. The values of alpha increased with an increasing amount (up to 300 ppm) of PLL in media. Higher concentrations of PLL decreased the value of alpha. All levels of dichlorvos tested decreased the value of alpha. The aflatoxin accumulation rate constant (alpha) as a function of concentration of additive (C) followed the general equation: \documentclass{article}\pagestyle{empty}\begin{document}$$\alpha = \frac{{\alpha _m C\exp (- {C \mathord{\left/ {\vphantom {C {K_i }}} \right. \kern-\nulldelimiterspace} {K_i }})}}{{C + K_a }}$$\end{document} where alpha(m), K(a), and K(i) are constants. 相似文献
15.
Isoelectric soya-protein precipitate densities were measured for mean particle sizes ranging from 3.4-65 mum by gradient centrifugation, centrifugation in water-immiscible solvents, tracerdilution, gravity sedimentation of isolated particles. Coulter counter volume determination, and a comparison of Coulter counter and centrifugal sedimentation size distributions. The immiscible system and tracer dilution methods were both found to be unreliable due to experimental uncertainties. The Coulter counter volume measurement indicated the existence of a density-size relationship with the aggregate density decreasing as the size increased. Comparison with sedimentation measurements showed that the Coulter counter measures 80% of the total aggregate volume for 6-mum particles. The relation between aggregate density (rho(a), kg m (-3)) and size (d, mum) was measured for isoelectric soya protein and casein precipitated by ammonium sulfate, using a comparison of the Coulter counter size distribution and centrifugal sedimentation. The functions were described for soya by \documentclass{article}\pagestyle{empty}\begin{document}$$ \rho _a - 1004 = 246d;{ - 0.408} $$\end{document} and for casein by \documentclass{article}\pagestyle{empty}\begin{document}$$ \rho _a - 1136 = 31d;{ - 0.441} $$\end{document} The gradient centrifugation method measured the buoyant density of hydrated protein precipitate which was independent of size, and is consistent with an aggregate structure consisting of primary particles. However, the aggregate structure was not described for all sizes by the theoretical cubic packing of hard-sphere primary particles, nor by the successive random addition of primary particles. The density-size functions indicated up to a fivefold difference in Stokes settling velocities compared to those calculated assuming a constant density difference. 相似文献
16.
Theoretical expressions are derived for the change in the polarized components of the fluorescence, resulting from the orientation of a rigid molecule bearing a chromophore with arbitrary angles for the absorption and transition moments \documentclass{article}\pagestyle{empty}\begin{document}$ \vec \mu _a $\end{document} and \documentclass{article}\pagestyle{empty}\begin{document}$ \vec \mu _e $\end{document} with respect to the molecular axis. The break in the symmetry relation HV = VH is related to the tilt angle between \documentclass{article}\pagestyle{empty}\begin{document}$ \vec \mu _a $\end{document} and \documentclass{article}\pagestyle{empty}\begin{document}$ \vec \mu _e $\end{document}. The theory is applied to a sonicated DNA–2-hydroxy-4,4′-diamidinostilbene complex, in the blue and red emission bands of this peculiar dye. Simultaneous measurements of linear dichroism and fluorescence lead to the determination of an angle of 47° between a fluorescent bound dye and the DNA axis, with no difference for the blue- and red-emitting species, but confirm the presence of nonfluorescent bound dye in a more perpendicular arrangement. 相似文献
17.
Claude Marmasse 《Bulletin of mathematical biology》1962,24(4):361-367
The fundamental equation of the theory of multiple fixations without interaction (MFWI) is
$$\frac{1}{r} = \frac{1}{m} + \frac{1}{{mKA}}$$ 相似文献
18.
Amylase synthesis by the yeasts Saccharomycopsis fibuligera and Schwanniomyces castellii and alluvius is repressed by glucose. Steady state continuous culture data for amylase activity, E, biomass concentration, X, and reducing sugar concentration, S, were fitted to the three-parameter catabolite repression model \documentclass{article}\pagestyle{empty}\begin{document}$ \frac{E}{X} = \frac{{[1 + a(S/X)]}}{{[1 + b(S/X)]}}, $\end{document} and biomass productivity, DX, and amylase productivity, DE, were determined for S. castellii and S. alluvius. 相似文献
19.
L. H. Pardo P. H. Templer C. L. Goodale S. Duke P. M. Groffman M. B. Adams P. Boeckx J. Boggs J. Campbell B. Colman J. Compton B. Emmett P. Gundersen J. Kjønaas G. Lovett M. Mack A. Magill M. Mbila M. J. Mitchell G. McGee S. McNulty K. Nadelhoffer S. Ollinger D. Ross H. Rueth L. Rustad P. Schaberg S. Schiff P. Schleppi J. Spoelstra W. Wessel 《Biogeochemistry》2006,80(2):143-171
N saturation induced by atmospheric N deposition can have serious consequences for forest health in many regions. In order to evaluate whether foliar may be a robust, regional-scale measure of the onset of N saturation in forest ecosystems, we assembled a large dataset on atmospheric N deposition, foliar and root and N concentration, soil C:N, mineralization and nitrification. The dataset included sites in northeastern North America, Colorado, Alaska, southern Chile and Europe. Local drivers of N cycling (net nitrification and mineralization, and forest floor and soil C:N) were more closely coupled with foliar than the regional driver of N deposition. Foliar increased non-linearly with nitrification:mineralization ratio and decreased with forest floor C:N. Foliar was more strongly related to nitrification rates than was foliar N concentration, but concentration was more strongly correlated with N deposition. Root was more tightly coupled to forest floor properties than was foliar . We observed a pattern of decreasing foliar values across the following species: American beech>yellow birch>sugar maple. Other factors that affected foliar included species composition and climate. Relationships between foliar and soil variables were stronger when analyzed on a species by species basis than when many species were lumped. European sites showed distinct patterns of lower foliar , due to the importance of ammonium deposition in this region. Our results suggest that examining values of foliage may improve understanding of how forests respond to the cascading effects of N deposition. 相似文献
20.
Patterns of tooth size variability in the dentition of primates 总被引:2,自引:0,他引:2
Published data on tooth size in 48 species of non-human primates have been analyzed to determine patterns of variability in the primate dentition. Average coefficients of variation calculated for all species, with males and females combined, are greatest for teeth in the canine region. Incisors tend to be somewhat less variable, and cheek teeth are the least variable. Removing the effect of sexual dimorphism, by pooling coefficients of variation calculated for males and females separately, reduces canine variability but does not alter the basic pattern. Ontogenetic development and position in functional fields have been advanced to explain patterns of variability in the dentition, but neither of these appears to correlate well with patterns documented here. We tentatively suggest another explanation. Variability is inversely proportional to occlusal complexity of the teeth. This suggests that occlusal complexity places an important constraint on relative variability within the dentition. Even when the intensity of natural selection is equal at all tooth positions, teeth with complex occlusal patterns must still be less variable than those with simple occlusion in order to function equally well. Hence variability itself cannot be used to estimate the relative intensity of selection. Low variability of the central cheek teeth ( \documentclass{article}\pagestyle{empty}\begin{document}$ \mathop {\rm M}\frac{1}{1} $\end{document} and \documentclass{article}\pagestyle{empty}\begin{document}$ \mathop {\rm M}\frac{2}{2} $\end{document}) makes them uniquely important for estimating body size in small samples, and for distinguishing closely related species in the fossil record. 相似文献