Fermentation substrate consumption

Where yield coefficients are constant for a particular cell cultivation system, knowledge of how one variable changes can be used to determine changes in the other. Such stoichiometric relationships can be useful in monitoring fermentations. For example, some product concentrations, such as CO2 leaving an aerobic bioreactor, are often the most convenient to measure in practice and give information on substrate consumption rates, biomass formation rates and product formation rates. 

To answer these questions, at first mass balance is required to determine conversion and how much air to supply into the fermentation broth. The substrate consumption or production rates must be set as a start. To demonstrate suitable answers to the above statements, we may approach the questions by reviewing a few biological processes and illustrating all the assumptions and process conditions. 

Microbial production of secondary metabolites is also an important source of novel therapeutic agents. However, the physiological and biochemical factors that determine the onset of production of a specific secondary metabolite in a particular species are incompletely understood. Generally, a range of analytical techniques, often elaborate, time-consuming and involving extensive sample pre-treatment, have to be developed in order to monitor the details of the metabolic changes and substrate consumption that accompany secondary metabolite production. In order to provide rapid multi-parametric information about the microbial fermentation process, H HPLC-NMR has been applied to characterise microbial metabolites directly in the broth supernatants from a... 

The OMBRE approach is applied to a biomass fermentation model [1], which, assuming Monod-type kinetics for biomass growth and substrate consumption, is described by the following DAEs set ... 

Further study of the mass and heat transfer, the kinetics of substrate consumption, cell growth and product formation, estabhshment of a workable mathematical model for process scale up and optimization for sohd-state fermentation. 

There are two different ways of operating a continuous stirred-tank fermentor, namely chemostat and turbidostat. In the chemostat, the flow rate of the feed medium and the liquid volume in the fermentor are kept constant. The rate of cell growth will then adjusts itself to the substrate concentration, which depends on the feed rate and substrate consumption by the growing cells. In the turbidostat the liquid volume in the fermentor and the liquid turbidity, which varies with the cell concentration, are kept constant by adjusting the liquid flow rate. Whereas, turbidostat operation requires a device to monitor the cell concentration (e.g., an optical sensor) and a control system for the flow rate, chemostat is much simpler to operate and hence is far more commonly used for continuous fermentation. The characteristics of the continuous stirred-tank fermentor (CSTF), when operated as a chemostat, is discussed in Chapter 12. 

Capacity of the plant Fermentation volume Productivity Biomass concentration Ethanol concentration Acetic acid concentration Substrate consumption Ethanol in pervaporate Inlet dilution rate Product dilution rate Medium bleed rate Cell bleed rate Recirculation rate Pervaporation area Microfiltration area Investment fermentor Investment distillation Investment pervaporation Investment microfiltration Total capital cost Depreciation membranes Molasses and nutrients Steam Electricity Process water Cooling water Total production costs... 

Specific growth rates (/Xx), specific substrate rates (/xs), and ethanol production rates (/Xp) were calculated, and results are shown in Fig. 2 for 5o= 103.1 g L. Similar profiles were obtained for the other initial substrate concentration studied (data not shown). As can be observed, specific growth rates, substrate consumption, and product formation followed a typical pattern for ethanol fermentation [16]. The specific rate of substrate consumption (ps) and ethanol production (/Xp) present sunilar profiles, thus correlating it very well. The specific growth rate (/Xx) presents, approximately, the same course of the others two curves. Then, ethanol formation is associated with growth, consumption of substrate, and catabolism reaction, typical of a primary metabolite (Fig. 2). 

Fig. 2 Specific rates of growth (/ix). substrate consumption (/is), and ethanol production (/ip) for the fermentation of CAJ medium by S. cerevisiae at 30 C,...

Maximum ethanol concentration was obtained (=44 g L ) when 87.7 and 103.1 g of initial sugar concentration was used in the fermentation medium. Specific rates of growdi, substrate consumption, and product formation followed a typical pattern for ethanol fermentation. Maximum ethanol yield (0.488 g g ) and productivity (9.71 g L h ) were obtained when 87.7 g L of initial sugar concentration was used. Finally, initial sugar concentration had no important effect on selectivity. The results obtained indicate that CAJ is a suitable substrate for ethanol production. Moreover, the use of the CAJ as a medium will not only reduce the cost of the resulting ethanol production, but it will also make use of an agricultural waste that is otherwise discarded in the field. 

Samples were collected at regular intervals for 2 weeks of fermentation to quantify cell mass, substrate consumption, and bacterial cellulose production. The cells were collected after centrifugation at 9,200 xg force for 30 min at 4 °C. The cell mass was estimated by... 

Although several types of models have been explored in the description of biological systems, the unstructured black box continuum models based on a linear equation for substrate consumption are still most frequently used for the description of fermentation processes. In these models the growth rate of the cells generally is assumed to be a function of the external concentration of the growth-limiting substrate Cs according to Monod kinetics ... 

In the present case there are seven flows, and Equ. 2.11 specifies four equations between the flows represented in the matrix of Equ. 1.8. Hence, only three flows are independent variables (cf. Sect. 1.2). Which kind of flows to be chosen for measurement depends on the possibilities for experimental determination. The knowledge, for example, of the respiratory quotient and the ratio of oxygen consumption to substrate consumption allows direct estimation of the biomass production rate and the product formation rate. This conclusion from the application of balancing is of the greatest importance in situations where process variables, for example, X, are very difficult to measure, which is the case in penicillin fermentation (Mou and Cooney, 1983). 

Optimized redox potential in the fermentation broth has been revealed to give improved reducing power to shift the metabolic flux toward the reverse TCA cycle. This creates a higher ratio of succinate to by-products. Furthermore, it has also been exposed to enhance cell growth and the substrate consumption rate (Park and Zeikus, 1999 Li et al., 2010a,b). 

This will be illustrated in the following example. Sustained oscillations of glycolytic intermediates have been shown in the yeast S. cerevisiae, both in cell free extracts [64, 65] and in whole cell cultures [63, 66]. Oscillatory growth is also a well-documented phenomenon in this yeast (see reference [16]) for further references). In the latter case, there may be an oscillatory shift in proportion of the respiratory and fermentative catabolism, during continuous aerobic growth on glucose. The oscillatory behaviour has been documented as an oscillation of substrate consumption rates and product formation rates rather than as an oscillation of metabolic intermediates [16]. An oscillatory behaviour may be of short (duration less than 1 min. [62, 63, 66]), medium (duration less than 1 hour [64]), or long term duration (duration of several days [16] ). 

Temperature, pH, and feed rate are often measured and controlled. Dissolved oxygen (DO) can be controlled using aeration, agitation, pressure, and/or feed rate. Oxygen consumption and carbon dioxide formation can be measured in the outgoing air to provide insight into the metaboHc status of the microorganism. No rehable on-line measurement exists for biomass, substrate, or products. Most optimization is based on empirical methods simulation of quantitative models may provide more efficient optimization of fermentation. 

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