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18BTC202J – BIOPROCESSS ENGINEERING LABORATORY

Offered to

B. Tech – Biotechnology / Specialization of Genetic Engineering /

Regenerative Medicine

MANUAL & RECORD NOTE BOOK

Name :

Register No. :

Year & Semester : III Year & V - Semester

Branch and Specialization: Biotechnology ……………………………………..

DEPARTMENT OF BIOTECHNOLOGY

SCHOOL OF BIOENGINEERING

SRM INSTITUTE OF SCIENCE AND TECHNOLOGY

KATTANKULATHUR - 603 203

2020 - 2021

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DEPARTMENT OF BIOTECHNOLOGY

SCHOOL OF BIOENGINEERING

SRM INSTITUTE OF SCIENCE AND TECHNOLOGY

BONAFIDE CERTIFICATE

This is a bonafide record of work done by ………………………………… register number

RA……………………………….of III year / V semester B. Tech. Biotechnology, specialization of

………………………………… for 18BTC202J - BIOPROCESSING LABORATORY at SRM Institute

of Science and Technology, Kattankulathur – 603 203, during the academic year 2020 – 2021.

Handling Faculty Head of the Department

Date:

Submitted for University Examination held on …../00/2021 in Bioprocess Engineering

Laboratory (Third Floor) / Genetic Engineering lab (Fourth Floor) at Department of Biotechnology,

School of Bioengineering, SRM Institute of Science and Technology, Kattankulathur – 603 203.

Date: Examiner - 1 Examiner - 2

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INDEX

Ex.No Name of Experiments Page No. Remarks

1 Batch Bioreactore Operation

2 Fed batch Operation

3 Batch Sterilization Kinetics

4 Determination of kLa by Sulphite Oxidation Method

5 Determination of kLa by Power Correlation

6 Production of Wine

7 Batch Growth Kinetics of Bacteria

8 Dynamic Simulation of a Batch Reactor

9 Dynamic Simulation of a continuous Reactor

10 Determination of kLa by Dynamic Degassing Method

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Date:

Exp.No. 1

BATCH BIOREACTOR OPERATION

Aim:

To study the design, construction and control systems of a bioreactor.

Principle:

A bioreactor is a device in which a substrate of low value is utilized by living cells or enzymes to

generate a product of higher value. Bioreactors are extensively used for food processing, fermentation,

waste treatment, etc. On the basis of the agent used, bioreactors are grouped into the following two broad

classes: (i) those based on living cells and, (ii) those employing enzymes. But in terms of process

requirements, they are of the following types: (i) aerobic, (ii) anaerobic, (iii) solid state, and (iv)

immobilized cell bioreactors.

A bioreactor should provide for the following: (i) agitation (for mixing of cells and medium), (ii)

aeration (aerobic fermenters; for O2 supply), (iii) regulation of factors like temperature, pH, pressure,

aeration, nutrient feeding, liquid level, etc., (iv) sterilization and maintenance of sterility, and (v)

withdrawal of cells/medium (for continuous fermenters). Modern fermenters are usually integrated with

computers for efficient process monitoring, data acquisition, etc.

Basic Functions of a Fermenter:

1. It should provide a controlled environment for optimum biomass/product yields.

2. It should permit aseptic fermentation for a number of days reliably and dependably, and meet the

requirements of containment regulations. Containment involves prevention of escape of viable cells from

a fermenter or downstream processing equipment into the environment.

3. It should provide adequate mixing and aeration for optimum growth and production, without damaging

the microorganisms/cells. The above two points (items 2 and 3) are perhaps the most important of all.

4. The power consumption should be minimum.

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5. It should provide easy and dependable temperature control.

6. Facility for sampling should be provided.

7. It should have a system for monitoring and regulating pH of the fermentation broth.

8. Evaporation losses should be as low as possible.

9. It should require a minimum of labour in maintenance, cleaning, operating and harvesting operations.

10. It should be suitable for a range of fermentation processes. But this range may often be restricted by

the containment regulations.

11. It should have smooth internal surfaces, and joints should be welded wherever possible.

12. The pilot scale and production stage fermenters should have similar geometry to facilitate scale-up.

13. It should be contrasted using the cheapest materials that afford satisfactory results.

Key parts of the bioreactor:

Agitator – This facilitates the mixing of the contents of the reactor which eventually keeps the “cells”

in the perfect homogenous condition for better transport of nutrients and oxygen for adequate metabolism

of cell to the desired product(s).

The agitator can be top driven or bottom which could be basically magnetic / mechanically driven.

The bottom driven magnetic /mechanical agitators are preferred as opposed to top driven agitators as it

saves adequate space on the top of the vessel for insertion of essential probes (Temperature, pH, dissolved

oxygen foam, CO2 etc) or inlet ports for acid, alkali, foam, fresh media inlet /exit gases etc. However

mechanical driven bottom impellers need high quality mechanical seals to prevent leakage of the broth.

* Types of agitators:

• Disc turbine

• Open turbines of variable patch.

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• Propellers

Baffle – The purpose of the baffle in the reactor is to break the vortex formation in the vessel, which is

usually highly undesirable as it changes the centre of gravity of the system and consumes additional

power.

• Baffles are metal stripes roughly 1/10th of the vessel diameter and are attached radially to the

wall.

• Normally 4 baffles are used, but in vessel over 3 dm3 diameter 6-8 baffles may be used.

Sparger – In aerobic cultivation process the purpose of the sparger is to supply oxygen to the growing

cells. Bubbling of air through the sparger not only provide the adequate oxygen to the growing cells but

also helps in the mixing of the reactor contents thereby reducing the power consumed to achieve a

particular level of (mixing) homogeneity in the culture.

Three basic types of sparger are used:

• Porous sparger.

• Orifice sparger.

• Nozzle sparger

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Bioreactor (Bottom Driven)

Jacket – The jacket provides the annular area for circulation of constant temperature water which keeps

the temperature of the bioreactor at a constant value. The desired temperature of the circulating water is

maintained in a separate Chilled Water Circulator which has the provision for the maintenance of

low/high temperature in a reservoir. The contact area of jacket provides adequate heat transfer area

wherein desired temperature water is constantly circulated to maintain a particular temperature in the

bioreactor.

Body construction:

For a small scale (1 to 30 dm3) glass and/ or stainless steel is used because it can withstand repeated

steam sterilization cycles.

Two basic types are used:

• A glass vessel with a round or flat bottom and top flanged carrying plates.

• A glass cylinder with stainless steel top and bottom plates. This bioreactor may be sterilized in

situ. (AISI graded steel are now commonly used in bioreactor construction).

Peripheral parts:

*Reagent pumps

• Pumps are normally part of the instrumentation system for pH and antifoam control.

• Peristaltic pumps are used and flow rate is usually fixed with a timed shot and delay feed system

of control.

*Medium feed pumps and reservoir bottles

Medium feed pumps are often variable speed to give the maximum possible range of feed rates.

The reservoir bottles are usually larger, but are prepared in the same as normal reagent bottles.

*Rotameter

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A variable area flow meter indicates the rate of gas flow into a bioreactor. A pressure regulator valve

before the rotameter ensures safe operation.

*Stirrer glands and bearings:

These are used for the sealing of the stirrer shaft assembly and can be operated aseptically for a long

duration. Four basic types of seal assembly have been used,

• The stuffing box (packed gland seal)

• The simple bush seal

• The mechanical seal

• Magnetic drive.

Basic control systems for the operation of the bioreactor are described below:

• Temperature Measurement and control – The measurement of the temperature of the

bioreactor is done by a thermocouple or Pt -100 sensor which essentially sends the signal to the

Temperature controller. The set point is entered in the controller which then compares the set

point with the measured value and depending on the error, either the heating or cooling finger of

the bioreactor is activated to slowly decrease the error and essentially bring the measured

temperature value close to the set point.

• pH measurement and control – The measurement of pH in the bioreactor is done by the

autoclavable pH probe. The measured signal is compared with the set point in the controller unit

which then activates the acid or alkali to bring the measured value close to the set point. However

before the pH probe is used, it needs to be calibrated with two buffers usually in the pH range

which is to be used in the bioreactor cultivation experiment. The probe is first inserted in (let us

say) pH 4 buffer and the measured value is corrected by the zero knob of the controller. Thereafter

the probe is put in pH 7 buffer and if needed the measured value is corrected by the asymmetry

knob of the controller. The pH probe is now ready for use in the range 0-7 pH range.

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• Dissolved oxygen controller – The dissolved oxygen in the bioreactor broth is measured by a

dissolved oxygen probe which basically generates some potential corresponding to the dissolved

oxygen diffused in the probe. Before the measurement can be done by the probe it is to be

calibrated for its zero and hundred percent values. The zero of the probe is set by (zero knob) the

measured value of the dissolved oxygen when the broth is saturated with nitrogen purging.

Similarly the hundred percent of the instrument is calibrated by the measured value of dissolved

oxygen when broth is saturated with purging air in it. After calibration the instrument is ready for

the measurement of the dissolved oxygen in the broth. In the event of low oxygen in the

fermentation broth, more oxygen can be purged in the bioreactor &/or stirrer speed can be

increased to enhance the beating of the bubbles which essentially enhances the oxygen transfer

area and net availability of oxygen in the fermentation broth.

• Foam control – The fermentation broth contains a number of organic compounds and the broth

is vigorously agitated to keep the cells in suspension and ensure efficient nutrient transfer from

the dissolved nutrients and oxygen. This invariably gives rise to lot of foam. It is essential that

control of the foam is done as soon as possible.

• Speed control- Speed control relies on the feedback from tachometer located with drive motor

determining the power delivered by the speed controller to maintain the speed set point valve set

by the user. A digital display shows the actual speed in rpm, as determined by the tachometer

signals.

Table 1: Measurements of various parameters in a bioreactor

Measurements

Methods Remarks

Agitator speed Frequency counter tacho generator More precise less reliable.

Agitator power Torque sensor.

Electrical power.

Difficult.

Recommended.

Temperature Resistance

Thermometer

Probably best

Fragile

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Significance of the experiment:

Thermistor

Thermocouple

Satisfactory

Not recommended

Flow rate Rota meter

Orifice meter

Thermal mass flow meter

Satisfactory

Less accurate

Set-point control

Dissolved oxygen Galvanic probe

Polarographic probe

Widely used

Widely used

pH pH electrode Widely used

Foam Conductivity probe Widely used

Redox Redox electrode Empirical valve

Turbidity Turbidity sensor Complex

Liquid feed rate Peristaltic pump

Syringe pump

Magnet flow meter

Widely used

Limited capacity

Large

Pressure Pressure transducer Satisfactory

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Date:

Exp. No. 2.

FED BATCH OPERATION

AIM: To study the fed batch operation and strategies adopted to optimise the fed batch culture.

PRINCIPLE

The simplest category of fermentation is batch cultivation where in the substrate is taken in the

beginning of cultivation and nothing is added or withdrawn during the fermentation. However, the yield

and productivity is lower in these cultivations mainly because, either the substrate &/or product inhibition

occurs and the product accumulation in never optimal.

Fed-batch cultivation can provide the solution to substrate inhibition problem by slow feeding of

nutrients to the bioreactor; however, it can still not address the severe inhibition problem due to

accumulating high product concentrations. The optimal design of fed-batch cultivation has to take in to

account several factors in to consideration for example time to start the fresh nutrient feed (in the end or

when the culture is exponentially growing) what should be the substrate concentration in the feed and its

rate of addition and when to finish the nutrient feeding so that the highest concentration of product is

produced and no unconverted substrate when the reactor is full. It is rather impossible to do trial and error

experimentation with so many “open ended” variables (as described above) which may play key role in

the overall performance of the fed-batch cultivation.

Different types of Fed-batch cultivation

Various feed strategies can be adopted in order to establish fed batch culture.

1. The same medium used to establish the batch culture is added, resulting in an increase in

volume.

2. A solution of the limiting substrate at the same concentration as that in the initial medium is

added, resulting in an increase in volume.

3. A concentrated solution of the limiting substrate is added resulting in moderate increase in

volume.

4. A very concentrated solution of limiting substrate is added less frequently resulting in an

insignificant increase in volume.

Apart from above feeding strategies, following scenario of nutrient feeding can also contribute in

the elimination of substrate inhibition to yield high productivity of the product.

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Add substrate when low

This is the simplest type of fed-batch cultivation where in the fresh feeding of the nutrient is done

when substrate has become limiting towards the end of the batch cultivation. At this point of time if no

feeding of fresh nutrient is done for some time, the culture dies out. A step input of substrate (predesigned

concentration and its rate) is identified by the mathematical model and is administered to the dying culture

in the bioreactor which instantaneously raises the concentration of substrate and thereby gives an

“installment” of life to the starving culture for few hours which results in product formation also for some

more time than the batch cultivation. This cycle can be repeated number of times till the reactor is full of

medium. In fact different combinations of substrate concentration, its rate and time of feeding can be

chosen and used in the mathematical model to arrive at the best possible cultivation protocol for highly

productive fermentation. The best offline simulated protocol can then be taken in to the lab and

implemented to optimize the production.

Constant feeding of substrate

Significant Improvement in product concentration and improvement in yield /productivity is

possible if the nutrient feeding is done during the exponential phase of the cell growth when the maximum

cell population is young and growing. This may be suitably selected by the study of batch kinetics. The

mathematical model can then be used to simulate number of possibilities of start /stop time of nutrient

feed, substrate concentration, its rate and so on. The simplest feeding profile could be constant feeding

of suitably selected nutrient concentration and its pre-identified rate such that it does not yield increased

concentration of substrate than the initial substrate concentration at any time during the feeding in the

bioreactor. The advantage of this strategy is that it is very simple it does not required computer coupled

peristaltic pump to implement the feeding strategy. But the disadvantage is that it leads to build up of

substrate which need to fermented by yet another batch cultivation so that in the end no unconverted

substrate is left in the bioreactor.

Linearly or exponentially increasing nutrient feeding strategy

In this fed-batch cultivation the nutrient feed is linearly or exponentially increased at

predetermined time of cultivation. If the feeding rate coincides with the growth rate in the bioreactor by

model simulations it may be possible to achieve non-limiting non-inhibitory concentration of substrate

during the feeding period. However, after the termination of feeding it may be necessary to do a secondary

batch cultivation to consume the residual substrate in the bioreactor.

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Decreasing rate nutrient feeding strategy

The disadvantage of above feeding strategy can be overcoming by suitable selection of nutrient

feeding strategy where in the feeding starts in exponential phase of fermentation and nutrient feeding

rate is so designed that feeding is high when the culture is young and there after the rate is gradually

decreased as the culture gets older & is diluted by incoming feed nutrients. It is possible to arrive at a

simulation where the feeding rate of nutrient gradually decreases & stops when the reactor is full. In

this there will not be any requirement of secondary batch fermentation.

Pseudo steady state of substrate or biomass

It is possible to design the nutrient feeding at a particular substrate concentration so that its

concentration is neither high enough to inhibit the fermentation nor it is too low to limit the growth in the

bioreactor. To arrive at the feeding profile, which might result the constant substrate concentration in the

broth, the first derivative (say ds/dt) is made zero and the model equations (because for S to be constant

its first derivative has to be made zero) are rearranged to calculate the corresponding feeding rate of the

substrate The feeding of the nutrient thus calculated can then be implemented to achieve pseudo steady

state of any variable e.g., S, X etc.

In this type of fed-batch cultivation design the start/stop time of feeding is first identified and the

nutrient feeding concentration rate / profile is so designed that it gives highest product concentration

when the reactor is full at the end of the feeding.

When fed batch culture is being established by these strategies, there will be variation in the

volume or the volume will almost be maintained constant. Based on the volume of the culture, fed batch

operation can also be categorized into variable volume fed batch culture and fixed volume fed batch

culture

Variable Volume Fed Batch Culture

Here, the growth is limited by the concentration of one essential substrate. In such case, the

biomass at any time will be described by the following equation

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Where Xt is the biomass concentration after time t hours, X0 is the initial concentration of biomass at the

time of addition of inoculum and Y is the yield coefficient.

When S= 0 , maximum biomass is being produced and and x0 is considered negligible, thus

Xmax = . S

The total amount of biomass in the vessel is Xt = VX, where V is the culture volume at time t. The rate

of increase in culture volume is

Integration of this equation yields

Where V0 is the initial culture volume. The biomass concentration in the vessel at any time t is

When the substrate is totally consumed, S 0 and X = Xm = Y.S0. Furthermore, since nearly all the

substrate in a unit volume is consumed, then dX/dt = 0. This is an example of a quasi-steady state. A fed-

batch system operates at quasi-steady state when nutrient consumption rate is nearly equal to nutrient

feed rate. Since dX/dt = 0 at quasi-steady state, then

If maintenance energy is neglected

Then

The balance on the rate-limiting substrate without maintenance energy is

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where St is the total amount of the rate-limiting substrate in the culture and S0 is the concentration of

substrate in the feed stream.

At quasi-steady state, Xt = VXm and essentially all the substrate is consumed, so no significant level of

substrate can accumulate. Therefore,

Then the equation at quasi-steady state with S 0 yields

Integration of this equation from t = 0 to t with the initial amount of biomass in the reactor being X0t

yields

That is, the total amount of cell in the culture increases linearly with time (which is experimentally

observed) in a fed-batch culture. Dilution rate and therefore µnet decrease with time in a fed-batch

culture. Since µnet = D at quasi-steady state, the growth rate is controlled by the dilution rate.

Product profiles in a fed-batch culture can be obtained by using the definitions of YP/S or qP.

When the product yield coefficient YP/S is constant, at quasi-steady state with S << S0

or

When the specific rate of product formation qP is constant,

Where Pt is the total amount of product in culture. Substituting Xt = (V0 + Ft)Xm in the above equation

yields

On integration yields

This equation can also be written as

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Cyclic Fed Batch Culture

In some fed-batch operations, part of the culture volume is removed at certain intervals, since the

reactor volume is limited. This operation is called the repeated fed-batch culture. The culture volume

and dilution rate (= µnet) undergo cyclical variations in this operation.

If the cycle time tw is constant and the system is always at quasi-steady state, then the product

concentration at the end of each cycle is given by

Where Dw = F/Vw, Vw is the culture volume at the end of each cycle, V0 is the residual culture

volume after removal, g is the fraction of culture volume remaining at each cycle (= V0/Vw), and tw is

the cycle time.

The cycle time is defined as

Substituting thin tw in the above equation yields

Fixed Volume Fed Batch Culture

In some fed-batch operations, the limiting substrate is added as concentrated feed such that the

culture volume remains almost constant, then

dX/dt = µX = F.Y

Where, F is the substrate feed rate and Y is the yield coefficient and the above equation can be written as

Xt = X0 + FYt

The product formation rate can be written as

dP/dt = qp.X where qp is product yield coefficient.

On substituting the X value, the above equation yields

dP/dt = qp (X0 + FYt)

If qp is growth rate related then product concentration will rise linearly as biomass increases. If qp

is constant then the rate of increase in product concentration will rise as growth rate declines.

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Application of Fed Batch Culture

The use of fed-batch culture by the fermentation industry takes advantage of the fact that the

concentration of the limiting substrate may be maintained at a very low level, thus avoiding both the

repressive and toxic effects of high substrate concentration. Furthermore, the fed-batch system also gives

control over the organisms’ growth rate, which is related to a wide range of industrially important

physiological properties including product formation, intracellular storage levels, RNA and protein

levels, plasmid stability, overflow metabolite production (such as acetate and lactate), the substrate

consumption rate, the specific oxygen uptake rate, and the specific product production rate.

Both variable and fixed volume systems result in low limiting substrate concentrations and growth

rate control, and while the quasi steady state of the variable volume system has the advantage of

maintaining the concentrations of the biomass and the nonlimiting nutrients constant, most commercial

processes involve the addition of concentrated feeds resulting in the biomass concentration increasing

with time. The obvious advantage of cyclic fed-batch culture is that the productive phase of a process

may be extended under controlled conditions. However, a further advantage lies in the controlled periodic

shifts in growth rate that may provide an opportunity to optimize product synthesis, particularly relevant

to secondary metabolite production.

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DATE:

Exp.No. 3

BATCH HEAT STERILIZATION KINETICS

AIM:

To study the batch heat sterilization kinetics of the given sample and to determine the holding

time.

PRINCIPLE:

A fermentation product is produced by the culture of a certain organism, or organisms, in a

nutrient medium. If a foreign microorganism invades the fermentation, the following consequences

may occur.

• The medium would have to support the growth of both the production organism and the

contaminant, thus resulting in a loss of productivity.

• If the fermentation is a continuous one then the contaminant may 'outgrow' the production

organism and displace it from the fermentation.

• The foreign organism may contaminate the final product, e.g., single-cell protein where the cells,

separated from the broth, constitute the product.

• The contaminant may produce products which make subsequent extraction of the final product

is difficult.

• The contaminant may degrade the desired product.

• Contamination of a bacterial fermentation with phage could result in lysis of the culture.

Avoidance of contamination may be achieved by

• Using pure inoculums to start the fermentation.

• Sterilizing the medium and the fermenter vessel, and all the materials employed in the process.

• Maintaining aseptic conditions during the fermentation.

Liquid medium is most commonly sterilized in batch in the vessel where it will be used. The l iquid

is heated to sterilization temperature by introducing steam into the coils or the jacket of the vessel;

alternatively, steam is bubbled into the medium or the vessel is heated electrically. If direct steam

injection is used allowance must be made for dilution of the medium by condensate which typically

adds 10-20% to the liquid volume; quality of the steam just also is high to avoid contamination of the

medium by metal ions or organics.

Depending upon the rate of heat transfer from the steam or electrical element, raising the

temperature of the medium in large fermenters can take a significant period of time. Once the holding

or sterilization temperature is reached the temperature is held constant for a period of time thd. Cooling

water in the coils or jacket of the fermenter is then used to reduce the medium temperature to the

required value.

For operation of batch sterilization also destroys nutrients in the medium. To minimize this

loss, holding times at the sterilization temperature must be kept as short as possible. Cell death occurs

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at all time during batch sterilization, including heating up and cooling down periods. The holding time

thd can be minimized by taking into account cell death during these periods

Kinetics of cell death

The destruction of micro organisms by steam is described as a first order chemical reaction

and represented by the equation and represented by the equation, −𝒅𝑵

𝒅𝒕 = K N

Where,

N= Number of viable organism

t = time of sterilization treatment

K = reaction rate constant of the reaction or specific death rate

∫−𝒅𝑵

𝒅𝒕 = ∫ 𝒌𝑵 =

𝑵𝒕

𝑵𝒐 = 𝒆−𝒌𝒕

Where,

No = Number of viable organisms present at the start of sterilization treatment,

Nt = Number of viable organisms present after the treatment period, t.

On taking natural logarithm of equation,

ln 𝑵𝒐

𝑵𝒕 = −𝒌 𝒕

MODEL CALCULATION:

Specific Death Rate

In the first order reaction the reaction rate increases with increase in temperature due to

increase in the reaction rate constant, which in the case of destruction of micro organism is the

specific death rate (K).

Relation between temperature and reaction rate constant is given by Arrhenius equation.

k = 𝑨 𝒆(−𝑬 𝑹𝑻)⁄

Where

E = Activation energy

R = Gas constant

T= Absolute temperature

A = Arrhenius constant

The term 𝑙𝑛 (𝑁𝑜 𝑁𝑡)⁄ is called as Del factor or Nabla factor and is represented by the term 𝛁.

Del factor

It is a measure of fractional reduction in viable organism count produced by certain heat and

time regime.

ln 𝑵𝒐

𝑵𝒕 = 𝑨 𝒕 𝒆(−𝑬 𝑹𝑻)⁄

𝛁 = 𝑨 𝒕 𝒆(−𝑬 𝑹𝑻)⁄

In a batch sterilization process there are 3 regimes, Heating, Holding and Cooling.

Overall 𝛁 factor may be represented by as

𝛁 Overall = 𝛁 Heating + 𝛁 Holding + 𝛁 Cooling

By knowing 𝛁 heating and 𝛁 cooling from the temperature time profile, 𝛁 holding is calculated as

𝛁 Holding = 𝛁 Overall - 𝛁 Heating - 𝛁 Cooling

Holding time (t) can be calculated by knowing the specific death rate of the organism under consideration.

tholding = 𝛁 Holding/k

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PROCEDURE :

• Fill the fermenter with 7L of distilled water.

• The temperature rises from 300C onwards.

• Note the Increase in temperature per minute till it reaches 1210C.

• Close the exhaust valve at 950C.

• At 1210C, open, the outlet valve and to draw out the condensed water so as to prevent from

any contamination.

• After 15 minutes, the cooling process is started (ie.) temperature cooling down from 1210C to

300C. Note down the decrease in temperature per minute.

• Plot the graph between Temperature vs. Time and determine the hold time

RESULT:

INFERENCE:

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HEATING CYCLE

Time

(Min)

Temperature

K=A e-Ea/RT ▽heating = K▽t °C °K

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COOLING CYCLE

Time

(Min)

Temperature K=A e-Ea/RT ▽heating = K▽t

°C °K

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Date:

Exp.No. 4

DETERMINATION OF KLa BY SULPHITE OXIDATION METHOD

AIM:

To determine the oxygen mass transfer coefficient, KLa using sodium sulfite oxidation method.

THEORY:

The volumetric liquid mass transfer coefficient (KLa) is a useful parameter to characterize the

bioreactor's capacity for aeration. This helps the reactor design, optimization of technologies and scaling

up or scaling down processes. The sodium sulfite combines with oxygen to give sodium sulfate, with

CuSO4 as a catalyst in the reactor. The concentration of sodium sulfite at various time points is inversely

proportional to the oxygen transfer rate.

Cu2+

Na2SO3 + ½ O2 Na2SO4

The above reaction is

A. Independent of sodium sulfite concentration within the range of 0.04N to 1.0N

B. The rate of the reaction is much faster than the O2 transfer rate.

Thus, the rate of oxidation is controlled by the rate of mass transfer alone.

The reaction consumes oxygen at a rate that is sufficiently fast so that transport of O2 from gas to a liquid

through the liquid film is the rate-limiting step. The rate of the reaction is zeroth order in Na2SO3. If the

reaction is not fast enough, the reaction occurs in the liquid film around the gas bubbles. This would

decrease apparent film thickness and give incorrectly high values of KLa. Concentrations of unreacted

sulfite are determined by reacting to the sulfite with excess iodine and then back titration of the iodine

with thiosulphate. It is important to note that the dissolved oxygen is zero through the reaction.

By titrating sodium sulfite present in the reactor (by taking a sample at fixed intervals of time) against

sodium thiosulphate, the quantity of sodium sulfite that would have reacted according to the equation can

be measured as the difference between successive rate instants of time. Then based on stoichiometry, the

corresponding number of moles of O2 that would have been consumed can be determined.

The Oxygen transfer rate

OTR = KLa (C*-CL)

Where C* = 8.43X10-3g/l at 25oC

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CL = Dissolved Oxygen content.

In this case, CL = 0, since the DO is maintained such that it is not saturated.

OTR = KLa (C*) -------- (1)

KLa = OTR/ C*

Thus KLa can be determined.

PROCEDURE:

• Take 100 ml of 0.5M Sodium sulphite & 0.002M copper sulphate solutions in a 250ml

conical flask.

• Keep the conical flask with sodium sulfite solution in a magnetic stirrer for mixing and take the

‘0th h’ sample for titration.

• Add 15 mL of Iodine solution and few drops of starch indicator to the 1 ml of sample

withdrawn from the flask.

• Titrate the sample against 0.5N Sodium thiosulphate. (It becomes straw yellow color and then

turn into dark blue color)

• Repeat the analysis for 5,10,15,20…….minutes samples ( till constant titer value reached to

continue the sampling)

• Plot the graph between titer volume vs. time

• Calculate the OTR by using the slope of the graph

• Calculate the Kla by using the given formula

REACTION:

O2 + 2 Na2SO3 2 Na2SO4

2 Na2SO3 + 2I + 2 H2O 2 Na2SO4 + 4HI

4 Na2SO3 + 2I2 2Na2S4O6 + 4NaI

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MODEL GRAPH:

CALCULATION:

Slope x Molarity of Na2S2O3 x Molecular weight of O2

OTR =

Sample volume x Molecular weight of Na2S2O3

Kla = OTR/ C*

kLa = Slope x Molarity of Sodium thio sulphate x Mol.Weight of O2 x 1000 x 60 h-1

Volume of sample (ml) x Mol. Weight of Sodium thio sulphate x C*

TABULATION:

Sample time (min) Titer volume (ml)

27

RESULT:

INFERENCE:

28

DATE:

Exp.No. 5

DETERMINATION OF VOLUMETRIC MASS TRANSFER COEFFICIENT BY POWER

CORRELATION METHOD

AIM:

To determine the volumetric mass transfer coefficient (KLa) value by the power correlation method.

PRINCIPLE:

The rate of O2 transfer air bubble to broth is KLa (C* - CL)

𝑑𝐶𝐿

𝑑𝑡= 𝐾𝐿𝑎 (𝐶∗ − 𝐶𝐿)

Where, KL = mass transfer coefficient (m/s)

a = interstitial cross sectional area (m2/m3liquid)

C* = saturated dissolved O2 concentration (moles/m3)

CL = DO concentration in liquid (moles/m3)

KLa = Volumetric mass transfer coefficient (1/s)

qO2 = O2 transfer rate (moles of O2/m3.S)

KLa is a measure of aeration capacity of the fermenter. KLa is influenced by the degree of agitation.

The relation between KLa and power is given by,

𝐾𝐿𝑎 = (𝑃𝑔

𝑉) ( 𝑉𝑠) 𝑘

Where, Pg = effective power used by gassing system (watts)

V = liquid volume (m3)

Vs = superficial air velocity (m/s)

K, x, y = empirical constants.

K= 0.026, x =0.4, y =0.5

KLa is directly proportional to the gassed power consumption per unit volume and the size of the vessel.

The KLa and Np relation are used for scale up and calculation of power for the agitator.

PROCEDURE:

• Fill the fermenter with 7L of water

• Provide the constant agitation at 500 rpm

29

• Connect the Voltmeter and Ammeter

• Vary the airflow from 0 to 10 vvm and note down the increment in volt (V) and Current (I)

• Calculate the power P= VI, with Pg at 0vvm as P; calculate the value of Pg/ P for other vvm

• Calculate the superficial gas velocity Vs. = VVM/cross-sectional area

• Plot the graph between Pg/P vs. Vs

.

RESULT:

INFERENCE;

30

TABLE 1: DETERMINATION OF KLa

The volume of the liquid V= 7 liter

VVM

Air

flow

in

LPM

Air

flow

in

LPS

Air

flow

in

m3/sec

V I P = VI Pg/P Pg/V Vs

CALCULATION:

Vs = VVS/Cross sectional area

R = 0.8 cm = 0.8 x 10-2 m

H = 15 cm = 15 x 10-2m

Cross sectional area = 2𝜋𝑟ℎ

31

DATE:

Exp.No: 6

PRODUCTION OF WINE

AIM:

To produce wine from grapefruit juice by the yeast fermentation process and estimation of ethanol

content present in the wine sample.

PRINCIPLE:

The most popular and best-known baker’s yeast – Saccharomyces cerevisiae is used for alcohol

production through anaerobic fermentation. The yeast is used for brewing beer, making bread, making

wine, ethanol and distilled beverages. The yeasts appear to be more tolerant of ethanol than other strains

of yeasts so that they can produce the wine that contains 20 % v/v of alcohol whereas brewer’s yeasts

yield only 9% v/v of ethanol. Yeasts are grown on grapes for making wine anaerobically, and the yield

of alcohol of the fermentation depends on the amount of substrate (sugars) that is being utilized during

the fermentation process. The utilization of the substrate can be expressed by the following reaction.

C6H12O6 2C2H5OH + 2CO2

PROCEDURE:

• Add fresh and healthy black grapes in a glass beaker and squeeze them to collect the juice

• Filter the collected juice

• Transfer the filtered juice to a sterile Erlenmeyer flask and close tightly.

• Add 1.5 g of brewer’s yeast and 200 gms of sugar per kg of grapes

• Incubate the flask at 15 – 20°C for 8-15 days.

• Determine the percentage of alcohol content by colorimetric titration using potassium dichromate

method.

REAGENT PREPARATION:

Potassium dichromate solution (K2 Cr2O7):

Weigh 34g of Potassium dichromate and dissolve in 500 ml of distilled water in a one-liter

standard measuring flask.

Concentric sulphuric acid (Conc. H2SO4):

32

Measure 325 ml of concentric sulphuric acid and slowly add to the potassium dichromate solution

by keeping it in an ice bucket.

PREPARATION OF STANDARD CURVE FOR ETHANOL ESTIMATION:

• Prepare 2 % (v/v) Ethyl alcohol as a stock solution

• Take 0.1, 0.2, 0.3, 0.4 and 0.5 ml of this 2% alcohol and add it to the test tubes and

makeup to 7.0 ml using distilled water

• Take 0.5 ml of wine sample and make it up to 7 ml

• Add 3.0 ml of potassium dichromate solution to all the test tubes

• Incubate the test tubes at 60˚C for 30 minutes.

• Measure optical density at 600 nm

• Plot the standard graph between the concentration of alcohol and optical density

• Calculate the concentration of ethanol in the wine sample from the standard graph.

RESULT:

INFERENCE:

33

Date:

Exp.No. 7

BATCH GROWTH KINETICS OF BACTERIA

AIM

To analyze the growth kinetics of bacterial culture and estimate specific growth rate, monod

constant, doubling time and yield coefficient.

PRINCIPLE:

Batch culture systems represent growth in a closed system. This can either use a flask or fermentor

containing a suitable growth supporting medium operated under optimum conditions of temperature, pH

and redox potential, which is inoculated with the cells grown until some essential component of the

medium is exhausted, or the environment changes because of the accumulation of a toxic product, pH

change, etc. In general microbial growth is determined by cell dry weight measurement. The growth

curve can be divided into three phases:

Lag phase: During this period the cell adapts to the new environment by

synthesizing necessary enzymes for the utilization of available substrates.

Exponential phase: The cell constituents in this phase increase at a constant rate

so that the cell population doubles and continues to double at regular intervals.

Stationary phase: In this phase, cell death occurs because of the depletion of

essential the rate of growth, hence there is no net growth or increase in cell

number. This is followed by a death phase.

The growth rate typically changes in a hyperbolic fashion, if the concentration of the essential

medium component is varied while the concentration of the other medium components is kept constant

and it follows the Monod growth kinetics.

𝛍 =𝛍𝐦𝐚𝐱 . 𝐒

𝑲𝒔 + 𝑺

Where S- concentration of the essential medium component, μ - specific growth rate hr-1, μMax-

Maximum specific growth rate achievable when S>>KS, KS - Monod constant and is equal to the

concentration of the essential medium component at which the specific growth rate is half of its maximum

value. The specific growth rate is linearly dependent on the concentration of the essential medium

34

component at lower concentration, and it is independent at higher the concentration of the essential

medium component.

The growth of the microbial cells is autocatalytic.

The General mass balance is

Input + Formation = Output + Accumulation + Disappearance

The Cell mass Balance is

Cell mass Input + Cell Growth = Cell mass Output + Cell mass Accumulation + Cell death

Here we neglect cell death, and no cells are removed in a batch reactor.

𝒅𝒙

𝒅𝒕= 𝛍𝐱 … … (𝟏)

Where, X = biomass conc, t = time

On integrating eqn. (1)

𝑿𝒕 = 𝑿𝟎. 𝒆µ𝒕 ….. (2)

This is the equation for microbial growth in the exponential phase,

Where, Xo = initial biomass concentration, Xt = biomass concentration after time t

On taking “ln,”

𝐥𝐧 𝑿𝒕 = 𝐥𝐧 𝑿𝟎 + µ 𝒕 … … . . (3)

A plot of ln x versus t gives a straight line with slope μ.

Doubling time of the strain,

𝐭𝐝 =𝐥𝐧 𝟐

µ

Following the log phase is the decelerating phase and stationary phase, where the growth is almost

constant with respect to time. Depletion of nutrients leads to declining growth phase where growth

occurs, but the death rate is greater.

The yield coefficient:

𝐘𝐱/𝐬 =∆𝐱

∆𝒔=

𝑿𝒕−𝑿𝟎

𝑺𝟎−𝑺𝒕 ------ (5)

Xo - initial concentration of biomass Xt = concentration of biomass at time‘t’, S0 = initial substrate

concentration, St = Residual substrate concentration at time‘t’.

35

Medium composition (g/L): Glucose- 3- 15; Yeast extract- 5; NH4Cl- 1 NaCl- 0.5; K2HPO4- 5; MgSO4-

0.5; pH: 7.0.

PROCEDURE:

• Prepare medium with varying concentrations of glucose

• Inoculate the 100 ml of sterilized medium with 5% (v/v) 24 h culture of E.coli grown in LB broth.

• Incubate the conical flasks at 37 ºC in a shaker at 150 rpm.

• Withdraw 3ml of sample from flasks at regular time intervals

• Measure the O.D at 600 nm for biomass and centrifuge the samples at 10,000 rpm for 15 minutes

at 4°C.

• Transfer the supernatant from the eppendorf tubes and incubate at 70°C for 24 h to measure the

dry weight

• Estimate the residual glucose from the supernatant by DNS assay

• Calculate the specific growth rate, Monod’s constants, doubling time and yield coefficients as per

given formulas and graphs.

DNS assay

• Take 2 ml of culture supernatant collected from various time intervals in test tubes

• 2ml of water serves as a blank

• Add 2ml of DNS reagent to all the test tubes

• Incubate at 90°C for 15 minutes in a water bath.

• Add 1 ml 40 % Sodium Potassium tartrate solution.

• Read the OD at 575 nm.

• Calculate the residual glucose concentration from standard graph

CALCULATION:

(Wt. of eppendorf tube with biomass) – Empty wt. of eppendorf tube) (g)

Dry weight of biomass (Xt, g/L) = ------------------------------------------------------------------------- Volume of sample (L)

MODEL GRAPHS:

36

37

TABULATION:

Time (h) OD for biomass at 600 nm Dryweight (g/L) Specific growth rate (µ) h-1

5

g/L

10

g/L

15

g/L

20

g/L

5

g/L

10

g/L

15

g/L

20

g/L

5

g/L

10

g/L

15

g/L

20

g/L

38

Time

(min)

OD for DNS assay at 575

nm

Residual substrate (S), g/L Yield coefficient (Yx/s) =

Dryweight (g) / Residual

substrate (g).

5

g/L

10

g/L

15

g/L

20

g/L

5

g/L

10

g/L

15

g/L

20

g/L

5

g/L

10

g/L

15

g/L

20

g/L

39

RESULT:

Specific growth rate μ =

Doubling time td =

Yield coefficient Yx\s =

INFERENCE:

40

Date:

Exp.No : 8

Dynamic simulation of batch culture using Berkeley- Madonna

AIM:

To simulate microbial batch growth kinetics using Berkeley- Madonna

Theory on Berkeley Madonna

Berkeley Madonna is the fastest, most convenient general purpose differential equation solver

available today. It is relatively inexpensive,it is currently used by academic and commercial institutions

for constructing mathematical models for research and teaching. It will have the user interface written in

Java, while retaining the simulation engine in C for speed. This will allow us to extend Berkeley Madonna

in many ways, including a Linux version.

The Runge–Kutta model:

One member of the family of Runge–Kutta methods is often referred to as "RK4", "classical

Runge–Kutta method" or simply as "the Runge–Kutta method".

Let an initial value problem be specified as follows.

Here, y is an unknown function (scalar or vector) of time t which we would like to approximate; we are

told that , the rate at which y changes, is a function of t and of y itself. At the initial time the

corresponding y-value is . The function f and the data , are given. RK4 model was used in

Berkely Madonna software to analyze the various growth parameters in batch, fed batch and continuous

cultures.

Sailent features of Berkley Madonna software:

• Used to solve ordinary differential equation

• Easy to use

• Very fast execution

41

• Sensitivity analysis- plots the partial derivative of any variable with respect to any parameter

• Fast Fourier transform - plot results in frequency domain.

42

The system is represented in the Figure, and the important variables are

• Biological dry bio mass X

• Substrate concentration S

• Product concentration P

The reactor volume , V is well mixed and the growth is assumed to follow Monod kinetics based on

substrate limiting.

Substrate consumption is related to cell growth by a constant yield factor of Y x/s

Product formation is the results of both growth associated and Non growth Associated.

Lag and decline phases are not included in the model.

Model

Where k1 and k2 are growth and non growth associated coefficients

If the number of equation is equal to the number of unknowns , the model is complete and the

solution can be obtained.

It is seen from the information flow diagram , all the variables required for the solution of any

one equation blocks are obtained as the product of the other blocks.

The information flow diagram thus emphasizes the complex inter-relation ship involved in even

in this simple problem.

The solution begins with Xo, So and Po at time t = 0

The specific growth rate is calculated, enabling rs,rx,and rp to be calculated.

The initial gradients such as dx/dt, ds/dt and dP/dt.

At this time integration routine takes over to estimate revised values of X, S and P over the first

integration step length.

)7()(

)6(

)5(

)4(

)3(

)2(

)1(

21 Xkkr

Yr

SK

mS

Xr

Vrdt

dPV

Vrdt

dSV

Vrdt

dXV

P

SX

S

S

X

P

S

X

+=

−=

+=

=

=

=

=

43

The procedure is repeated for succeeding step lengths until the entire X, S and P concentration

time profiles have been calculated for the required final time.

Thumb Rule :

Init --- Specifies initial conditions

Xo, So and Po are the initial values at time t = 0

X’ or dX/dt are time derivatives

Most models are conveniently structured in terms are mass balance and Kinetics

Plot can be time vs Concentration, or rate vs Concentration

Integration can be by DT, DTMIN and DTMAX

Procedure:

Type the below mentioned program, except the content which is in bracket in the program

space of BM(Berkeley Madonna)

Press RUN after successfully typed the program.

Observe profile of the various varaibles with respect to time.

PROGRAM:

METHOD RK4 (Runge Kutta 4th order method)

STARTTIME = 0

STOPTIME=70

DT = 0.02 (differential time)

(Models of Mass Balances)

d/dt(X)=RX (Biomass Balance)

d/dt(S)=RS (Substrate balance)

d/dt(P)=RP (Product balance)

(Kinetics)

RX=U*X

U=UM*S/(KS+S)

RS=-RX/Y

RP=(K1+K2*U)*X

(Initial Conditions)

init X= Xo

init S=So

init P=Po

(Constants)

K1=0.005

K2=0.002

Y=0.8

KS=0.1

UM=0.03

Xo = 0.01

So =100

Po = 0

44

OBSERVATION:

Exercise:

1) Ks and UM of your Growth kinetics Experiment and observe the effect of graph.

2) Vary K1 and k2 as 0.08 and 0.19 and find the effect of graph

3) Plot graph between rate vs concentrations

RESULT

45

Date:

Exp.No : 9

Dynamic simulation of CSTR using Berkeley- Madonna

AIM:

To simulate microbial growth kinetics of CSTR using Berkeley- Madonna

Theory on Berkeley Madonna

Berkeley Madonna is the fastest, most convenient general purpose differential equation solver

available today. It is relatively inexpensive, It is currently used by academic and commercial institutions

for constructing mathematical models for research and teaching. It will have the user interface written in

Java, while retaining the simulation engine in C for speed. This will allow us to extend Berkeley Madonna

in many ways, including a Linux version.

The Runge–Kutta model:

One member of the family of Runge–Kutta methods is often referred to as "RK4", "classical

Runge–Kutta method" or simply as "the Runge–Kutta method".

Let an initial value problem be specified as follows.

Here, y is an unknown function (scalar or vector) of time t which we would like to approximate; we are

told that , the rate at which y changes, is a function of t and of y itself. At the initial time the

corresponding y-value is . The function f and the data , are given. RK4 model was used in

Berkely Madonna software to analyze the various growth parameters in batch, fed batch and continuous

cultures.

Sailent features of Berkley Madonna software:

• Used to solve ordinary differential equation

• Easy to use

• Very fast execution

• Sensitivity analysis- plots the partial derivative of any variable with respect to any parameter

• Fast Fourier transform - plot results in frequency domain.

46

The system is represented in the Figure, and the important variables are

• Biological dry bio mass X

• Substrate concentration S

• Product concentration P

The reactor volume, V is well mixed and the growth is assumed to follow Monod kinetics based on

substrate limiting.

Substrate consumption is related to cell growth by a constant yield factor of Y x/s

Product formation is the results of both growth associated and Non growth Associated.

Lag and decline phases are not included in the model.

47

Model

RX=U*X

U=UM*S/(KS+S)

RS=-RX/Y

RP=(K1+K2*U)*X

Where k1 and k2 are growth and non growth associated coefficients

If the number of equations is equal to the number of unknowns, the model is complete and the solution

can be obtained.

It is seen from the information flow diagram, all the variables required for the solution of any one equation

blocks are obtained as the product of the other blocks.

The information flow diagram thus emphasizes the complex inter-relationship involved in even in this

simple problem.

The solution begins with Xo, So and Po at time t = 0

The specific growth rate is calculated, enabling rs, rx, and rp to be calculated.

The initial gradients such as dx/dt, ds/dt and dP/dt.

At this time integration routine takes over to estimate revised values of X, S and P over the first

integration step length.

The procedure is repeated for succeeding step lengths until the entire X, S and P concentration time

profiles have been calculated for the required final time.

Thumb Rule:

Init --- Specifies initial conditions

Xo, So and Po are the initial values at time t = 0

X’ or dX/dt are time derivatives

Most models are conveniently structured in terms are mass balance and Kinetics

Plot can be time vs Concentration, or rate vs Concentration

Integration can be by DT, DTMIN and DTMAX

P

SF

X

rDPdt

dPFOR

rSSDdt

dSFOR

rDXdt

dXFOR

PRODUCTS

)( SUBSTRATES

CELLS

+−=

+−−=

+−=

48

Procedure:

Type the below mentioned program, except the content which is in bracket in the program space of BM

(Berkeley Madonna)

Press RUN after successfully typed the program.

Observe profile of the various varaibles with respect to time.

PROGRAM:

• METHOD RK4

• STARTTIME = 0

• STOPTIME = 50

• DT = 0.02

• d/dt (X) = -D*X+RX

• d/dt (S) = D*(SF-S)+RS

• d/dt (P) = -D*P+RP

• RX=U*X

• U=UM*S/(KS+S)

• RS=-RX/Y

• RP=(K1+K2*U)*X

• init X =0.01

• init S = 10

• init P = 0

• K1 =0.03

• K2 =0.08

• Y=0.8

• KS=0.1

• UM=0.3

• SF=10

• D=0

OBSERVATION:

RESULT:

49

DATE:

Exp No. 10

DETERMINATION OF VOLUMETRIC OXYGEN MASS TRANSFER COEFFICIENT BY

DYNAMIC DEGASSING METHOD

AIM

To determine the volumetric oxygen mass transfer coefficient (KLa) value by dynamic gassing out method.

PRINCIPLE:

Taguchi and Humphrey (1966) utilized the respiratory activity of a growing culture in the fermentor

to lower the oxygen level before aeration. Therefore, the estimation has the advantage of being carried

out during a fermentation, which should give a more realistic assessment of the fermentor's efficiency.

The procedure involves stopping the air supply to the fermentation, which results in a linear decline in

the dissolved oxygen concentration to the culture's respiration, as shown in Fig.1. The Slope line AB is

a measure of the respiration rate of the culture. At point B, the aeration is resumed, and the dissolved

oxygen concentration increases until it reaches concentration X. Over the period BC, the observed

increase in dissolved oxygen concentration is the difference between the transfer of oxygen into the

solution and the uptake of oxygen by the respiring culture as expressed by the equation

dCL/dt = KLa(C* - CL) - xQO2 ------------------ (1)

Where,

CL is the concentration of dissolved oxygen in the fermentation broth (mmoles dm-3)

dCL/dt is the change of oxygen concentration over some time, i.e., oxygen transfer

rate (mmoles O2 dm-3 h-1)

kLa is the mass transfer coefficient (cm h-1)

'a' is the gas/ liquid interface area per liquid volume (cm2 cm-3)

C is the saturated dissolved oxygen concentration (mmoles dm-3)

'x' is the concentration of biomass, and QO2 is the specific respiration rate (mmoles of

Oxygen g-1 biomass h-1

50

Fig.1. Dynamic gassing out for the determination of kLa values.

Aeration was terminated at point A and resumed at point B.

The term xQ is given by the slope of the line AB. Equation 1 may be rearranged as:

CL = -1/KLa {(dCL/dt) + xQO2 } + C* ------------------ (2)

Thus, from equation 2, a plot of CL versus dCL/dt + xQO2 will yield a straight line, the slope of which will

equal -1/KLa, as shown in Fig 2 below. This technique is convenient because the rates of transfer and

uptake that are being monitored so that the percentage saturation readings generated by the electrode may

be used directly.

Fig.2. The dynamic method for the determination of kLa values. The information is generated from

Fig.1. by taking the tangent of the curve, BC, at various values of CL

51

The dynamic gassing-out method has the advantage over the previous methods of determining the

KLa during an actual fermentation and may determine KLa values at different stages in the process. The

technique is also rapid and only requires a dissolved-oxygen probe of the membrane type. A significant

limitation in the technique's operation is the range over which the increase in dissolved oxygen

concentration may be measured. It is essential not to allow the oxygen concentration to drop below C crit

during the deoxygenation step as the specific oxygen uptake rate will then be limited. The term xQO2

would not be constant on the resumption of aeration. The occurrence of oxygen-limited conditions during

deoxygenation may be detected by the deviation of the decline in oxygen concentration from a linear

relationship with time, as shown in Figure.

When the oxygen demand of culture is very high, it may be challenging to maintain the dissolved

oxygen concentration significantly above Ccrit during the fermentation. The range of measurements that

could be used in the KLa determination would be minimal. Thus, it may be difficult to apply during a

fermentation that has an oxygen demand close to the fermentor's supply capacity.

Fig.3. The occurrence of oxygen limitation during the dynamic gassing out of

fermentation

52

PROCEDURE:

1. Prepare 10 liters of LB broth and transfer into the fermentor, sterilize and cool to room temperature

2. Add 100 ml of 24 h grown E.coli culture into the fermentor

3. Stop the aeration and continue measuring the DO value until the dissolved oxygen concentration

reaches Ccrit for every 60 seconds.

4. Start the aeration and take a reading until the dissolved oxygen concentration reaches C for every 60

sec.

5. Plot the graph between dissolved oxygen concentration (CL) vs. time (t)

6. Find out the slope of the curve at degassing (xQO2).

7. Plot the graph for dissolved oxygen concentration (CL) vs. (dCL/dt) + XQO2.

8. Find out the slope of the curve to obtain the KLa value.

CALCULATION:

From the graphs,

XQo2 =

Slope = -1/ KLa =

RESULT:

INFERENCE:

53

TABLE 1: KLa Determination by degassing method

S.No

Time

(sec)

(Degassing)

D.O

concentration

CL

(mg/L)

Sl. No. Time

(sec)

(Regassing)

D.O

concentration

CL

(mg/L) 1 1

2 2

3 3

4 4

5 5

6 6

7 7

8 8

9 9

10 10

11 11

12 12

13 13

14 14

15 15

16 20

17 21

18 22

19 23

20 24

21 25

22

23

24

25

26

27

28

29

30

31

32

33

34

35

54

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

Table: 2

dCL/dt dCL/dt + xQO2 CL