Fermentation

Factors affecting Fermentation Temperature Most microorganisms that are mesophiles require temperatures of 25-40 C for optimum growth. As temperatures increase or decrease the growth rate is adversely affected. Thermophiles require high temperatures over 50 C; they cannot survive at low temperatures. Psychrophiles require very low temperatures - 15 to 20 C for survival and growth

Factors affecting Fermentation Water Microorganisms require optimum amounts of water to maintain their metabolism and produce required products. pH Optimum pH for bacteria is 6.5-7.5, yeasts 4-5, molds 4-7. The pH of the medium should be maintained at optimum level for the micro- organism being employed to ensure better product yield.

CONTROL / PROCESS VARIABLES 1. Temperature 2. Pressure 3. Vessel contents 4. Foam 5. Impeller speed 6. Gas Flow rates 7. Liquid flow 8. pH 9. Dissolved and Gas phase Oxygen 10. Dissolved and Gas phase Carbon Dioxide 11. General gas analysis

Optimization of the Fermenter System Fermenter should be designed to exclude entrance of contaminating organisms as well as containing the desired organisms Culture volume should remain constant Dissolved oxygen level must be maintained above critical levels of aeration and culture agitation for  aerobic organisms Parameters such as temperature of pH must be controlled, and the culture volume must be well mixed.

Control of Chemical and Physical Conditions Intensive properties temperature, concentration, pressure, specific heat‡  Extrinsive properties mass, volume, entropy and energy‡  Mass and energy levels should balance at the start an d finish of fermentations.‡  Combining this with determination of thermodynamic properties and rate equations we can build computer and mathematical models to control processes.

Process sensors and their possible control functions Category Sensor Possible control function Physical Temperature Heat/cool Foam Foam control Weight Change flow rate Flow rate Change flow rate Chemical pH Acid or alkali addition Redox Additives to change redox potential Oxygen Change feed rate Exit-gas analysis Change feed rate Medium analysis Change in medium composition

Control systems An agitator system An oxygen delivery system A foam control system A temperature control system A pH control system

Model of the Fermentation Process

Three Sub-systems of the model Reactor – where the fermentation occurs Heat Exchanger – used to control the temperature of the process Feed System – controls both the flow and pH dynamics

Fermentation Operation The cane juice that is mixed with acid substance to maintain the pH in a desired value feeds the reactor until it reaches the desired level defined by the operator. The reactor is a batch unit and during each production period, a continuous recirculation of the must is performed.

Fermentation Operation The must passes through a heat exchanger, which uses a coolant circulation to keep the must inside the reactor at an ideal temperature.

pH dynamic Model

pH dynamic Model very common process in sugar and alcohol plants strong nonlinearity of this process makes it one of the hardest type of SISO (single input single output) systems to be controlled large variations in pH can significantly impact the quality of the product and process efficiency. Besides temperature and dissolved oxygen concentration, pH is one of the major influential factors in fermentation processes.

What causes the pH to change? Overfeeding substrate can cause the cells to  produce  organic acids, such as acetate – pH drops Lack of carbohydrate substrate causes the  cells to consume protein in the media – producing NH3-NH4OH –pH rises

pH Control In real life, bioreactors actually use on-off control for pH. The two position control system is designed; so that the element controlling reagent addition is always set in one of two positions, either fully open or fully closed. The important consideration in pH control is hold time, which is required to provide time for neutralization reaction to go to completion.

pH Control Regarding the model for pH neutralization process, it is known that the pH denotes the concentration of the ions [H+] through the following logarithmic function: The dissociation equation for water is expressed as:

pH Control The equation describing the pH neutralization process dynamics is Where Fa and Fb are the flow of acid and base, ca and cb represents the concentration of acid and base.

A dynamic model for neutralization process is described by a first order with dead time; the approximate transfer function is; The responses of pH electrode were analyzed to give the first order transfer function which is -adaptive control of pH (Putrus, 2006)

Transfer of Heat in Bioreactors Microbial growth is usually accompanied by the release of metabolic heat into the fermentation medium. Metabolic activities can generate as much as 100-200 BTU gal-1h-1 of thermal energy, while mechanical energy inputs of 0.5 and 2.5 HP per 100 gal can generate an additional 10-60 BTU gal-1h-1.

Transfer of Heat in Bioreactors To maintain a constant temperature in the fermenter, heat is either supplied or removed from the fermentation broth during the course of fermentation. Heat transfer takes place in well stirred fermenters by forced convection.

Temperature control Provision of heat – fermenter in thermostatically controlled bath or by use of internal heating coils or by a silicone heating jacket through which water is circulated Heat jacket consists of silicone rubber mats wrapped around the vessel Cooling surface/cooling water

Cooling water addition Total heat to be removed by cooling water is due to metabolic heat generation plus heat added from the stirring Heat is removed by running cooling water through the cooling coils in the reactor coils in the reactor

Cooling water addition U is the overall heat transfer coefficient of the coils Ac is the total area of the coils in contact with the broth ΔT is the “log-mean temperature difference” between the broth and the cooling water

Temperature Heating system In many applications such as electrical heating systems, the heating element is controlled by a contactor that has only two states (on or off) Electric heater controls the temperature of the liquid in a tank and the aim is to control the temperature at the desired value.

Temperature Heating system Most of the temperature control systems can be approximated to a single order transfer function with a transportation delay and time constant which depends on the parameters such a specific heat coefficient, temperature coefficient etc.,

Temperature Heating system Transfer function of the temperature system where a liquid at temperature enters a tank which is heated with an electric heater and q is the heat flow of the heating element with flow rate constant k, specific heat coefficient P, thermal resistance of tank insulation R and thermal capacitance of water C, is given by,

Temperature Heating system According to Ziegler and Nichols, an open- loop process can be approximated by the transfer function The coefficients K, Td and Ti are found from a simple open-loop unit step response of the process. Defines the mathematical model for heating system which controls the temperature of the bioreactors process

Reactor Modeling The mathematical modeling of the alcoholic fermentation was performed based on mass balance equations with the correspondents kinetic rates of the cell, substrate and product as well as global balance of energy for the overall process.

Reactor Modeling Thus, the volume variation during the fermentative process is described as: in which F3(m3/h) is the volumetric flow rate of must at the entrance of the reactor.

Reactor Modeling The cell growth rate is defined as follows

Sample Control Strategy Global Control System: in this top layer, the optimizer computes the optimum pH, temperature (T) and level (H) in the reactor to maximize the ethanol production. It works as master controller and defines the set-point for the slave loops. Local Control System: this layer is composed by three slave loops which work in cascade with the optimizer. The objective of these local controllers is to keep the fermentation process in the operating point (pH; T; H) defined by the upper layer.

Sample Control Strategy