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PRESENTATION

Goutam Chandra RoyAnd

Abdul Ohab Rana

M.S in Food Engineering &Technology

Goutam Chandra RoyAnd

Abdul Ohab Rana

M.S in Food Engineering &Technology

PRESENTED BY:

Thermal Processing is an accepted terminology to describe the heating, holding and cooling process required to eliminate the potential for a foodborne illness.Food product spoil by different microorganisms.Microorganisms can destroy or reduce by different thermal processing method.Thermal Processing Method are –

-Pasteurization -Sterilization

-Cooling -Freezing

-Refrigeration

Thermal Processing

MICROBIAL SURVIVOR CURVES

During preservation processes for foods, an external agent is used to reduce the population of microorganisms present in the food. The population of vegetative cells such as E. coli, Salmonella, or Listeria monocytogenes will decrease in a logarithmic manner.

A general model for description of the microbial curve would be:

where k = the rate constant and n = the order of the modelThis general model describes the reduction in the microbial population (N) as a function of time.

A special case of above equation is:

The decimal reduction time D is defined as the time necessary for a 90% reduction in the microbial population. Alternatively, the D value is the time required for a one log-cycle reduction in the population of microorganisms.

Decimal Reduction Time (D)

Based on the definition of decimal reduction time,the following equation would describe the survivor curve:

Where, N0 = the initial microbial population andN = the final microbial populationt= timeD= decimal reduction time

By comparison of above two equations, it is evident that:

The kinetics of a chemical reaction are more often described by equation, and the rates of change in chemical components are expressed by first-order rate constants (k). In many situations, the changes in quality attributes of food products during a preservation process are described in terms of first-order rate constants (k).

Relationship between Decimal reduction time (D) and rate constant(k):

Since the microbial population usually follows an exponential path, the change should follow first order kinetics. Therefore,

Again we have,

Where, N0 =the initial microbial population N = the desired final microbial population

SPOILAGE PROBABILITY

Then, if r is the number of containers exposed to the preservation process, and N0 is the initial population of spoilage microorganisms in each container, the total microbial load at the beginning of the process is rN0, and then we get:

Based on the definition of decimal reduction time, the following equation can be used:

For a thermal death time of F, we can obtain

If the goal of the preservation process is to achieve a probability of one survivor from the microbial population for all containers processed, then

The ratio on the left side of above equation represents the total number of containers processed (r) and resulting in one container with spoilage.

The expression can be used to estimate the thermal death time required to accomplish a stated spoilage probability, based on -the initial population, -the decimal reduction time, D and -the microbial population.

The spoilage probability expression does assume that the survivor curve for the spoilage microorganism follows a first-order model.

The Z-value (Thermal Resistance Constant)

The Z-value is the increase or decrease in temperature required to reduce or increase the decimal reduction time by one decimal. It is a measure of the change in death rate with a change in temperature.

The z-value is obtained by plotting the logarithms of at least 2 D-values against temperature or by the formula:

Where, T = temperature and D = D-value

Graphical Representation of Z-value (Thermal Resistance Constant)

THERMAL DEATH TIME (F)

Thermal death time (F): The total time required to accomplish a stated reduction in a population of vegetative cells or spores.

This time can be expressed as a multiple of D values, as long as the survivor curve follows a first-order model.

For example, a 99.99% reduction in microbial population would be equivalent to four log-cycle reductions or F=4D.

A typical thermal death time in thermal processing of shelf-stable foods is F=12D, with the D value for Clostridium botulinum.

Thus, FTz is the thermal death time for a temperature T and a thermal

resistance constant z.

A commonly used thermal death time is F25018 in the Fahrenheit

temperature scale, or F12110 in the Celsius temperature scale.

This reference thermal death time, simply written as F0, represents the time for a given reduction in population of a microbial spore with a z value of 10°C (or 18°F) at 121°C (or 250°F).

The survivor curves for microbial populations are influenced by external agents such as temperature, pressure, and pulsed electric fields increase, the rate of the microbial population reduction increases. In chemical kinetics, we use the Arrhenius equation to describe the influence of temperature on the rate constant. Thus,

Where, k= rate constant (k) Ea = Activation Energy .

Relationship between activation energy, Ea and thermal resistance constant (z):

These constants are determined from experimental data by plotting ln k versus 1/TA, and the slope of the linear curve is equal to Ea/Rg.

On the other hand, defined as the increase in temperature necessary to cause a 90% reduction in the decimal reduction time D. The D values for different temperatures are plotted on semilog coordinates, and the temperature increase for a one log-cycle change in D values is the z value given in the figure:

Based on the definition, z can be expressed by the following equation:

By comparing Arrhenius equation and the above equation by considering that k=2.303/D,

SETTING CRITERIA FOR HEAT INACTIVATION:• The criteria for minimum thermal treatment of a food product

should be set within the frame of a microbiological risk assessment.

• One element of risk assessment is exposure assessment.

• Exposure assessment generally includes contamination of raw materials, contamination during processing, growth and/or inactivation of the microorganism, storage and distribution conditions, and infectivity of the microorganism.

• FSO is defined as the maximum frequency and/or concentration of a hazard in a food at the time of consumption that provides or contributes to the appropriate level of protection (ALOP).

• The FSO equation was developed by the ICMSF (International Commission on Microbiological Specifications for Foods, 2002) as,

• Esty and Meyer (1922) observed that the heat resistance of a population of Clostridium botulinum was dependent on the initial number of microorganisms, and from their results, it could be inferred that the decrease was exponential with time.

• Bigelow et al.(1920) formulated the death kinetics of bacterial spores in mathematical terms.

• Inactivation of microorganisms is still described in terms of decimal reduction time, i.e., the time to reduce the number of microbial cells by a factor of 10 or D value.

• The increase in temperature corresponding to a decrease of the D value by a factor of 10 is called the z value.

Classical Thermal Death Model

Thus, thermal inactivation can be described by the two linear equations:

In which N0 = the initial number, Nt = the number at time t,D = the decimal reduction time,–(1/D) = the slope of the curve.

The equation can be written in line with enzyme kinetics in the form:

The relation between D and temperature (T) can be described as

Where,D=the decimal reduction timeDref =reference D valueTref= Corresponding to the reference temperature z is the temperature increase that corresponds to a10-fold reduction of the D value. z is the reciprocal of the slope in the above equation; z is expressed in ◦C or F; D can be Expressed in seconds or minutes; T = temperature,

Nonlinear Models

There are a number of nonlinear models:

Weibull Like ModelsBiphasic InactivationNormal Distribution ModelS-shaped CurvesSapru Model

A simple way to describe nonlinear curves is the Weibull equation. This equation can properly describe inactivation curves that are either upward or downward concave.Weibull and Weibull like equations have been applied for the description of inactivation of bacterial spores as well as inactivation of vegetative cells. They couldwell be described by a Weibull equation as was proposed by Mafart et al.(2002).

Weibull Like Models

Where,Nt=the number of microorganisms at time t, N0 =the initial number of microorganisms, t=heating time, δ =the scale parameter, and p = the shape parameter.

One of the causes of tailing that were suggested by Cerf(1977) was the existence of two phenotypically different sub populations. The majority is relatively heat sensitive, whereas a minority is relatively heat resistant.

Nt = number of microorganisms at time t,N0 = initial number of microorganisms, 1−f = majority fraction of heat sensitive cells, k1 = inactivation rate constant of sensitive(majority),f = minority fraction of resistant cells, k2 = inactivation rate constant of resistant (minority)fraction.

Biphasic Inactivation

The oldest secondary model is the z concept as described above in the paragraph on classical inactivation models. Contrary to the log linear equation between D and T, the relation between k and1/T is expressed by the Arrhenius equation:

Secondary Models

Where Ea is the activation energy (kjmol−1);R is the gas constant(8.314446 × Jmol−1K−1); T is the absolute temperature(K);k∞ is the rate constant at infinite temperature.

The relation between and the Arrhenius equation can be written as

In heat processing, the difference between Tr and T is relatively small and hence z may be considered as

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