Method for microbiological quasi-chemical kinetics growth-death modeling in food

• US 10,437,909 B2
• Filed: 09/01/2009
• Issued: 10/08/2019
• Est. Priority Date: 09/01/2009
• Status: Active Grant

• Current Assignee: Brandeis University
• Original Assignee: Brandeis University
• Inventors: Doona, Christopher J, Ross, Edward W, Feeherry, Florence E, Kustin, Kenneth
• Primary Examiner(s): Skibinsky, Anna
• Application Number:
  US12/551,596
• Publication Number:
  US 20110054855A1
• Time in Patent Office: 3,689 Days
• Field of Search: None
• CPC Class Codes: G06F 17/13 Differential equations using digital differential analysers G06F7/64

Abstract

A food safety management tool that utilizes a mathematical model based on differential equations that is generalized for describing the continuous growth-death kinetics of microbial populations in foodstuffs. The method is used to provide a way to control target microorganisms when designing product formulations of minimally processed foodstuffs or when processing foods with high pressures, temperatures, or other lethal agents to achieve effective pasteurization, disinfection, or sterilization of foodstuffs, and includes the use of model parameters to predict food formulations to inhibit the growth of microorganisms and the processing times needed to reduce microbial hazards to levels that ensure consumer safety.

Claims

1. A method for determining the safety and shelf-life of a storable food product for consumption using a microbiological Quasi-chemical kinetics growth-death tailing model based on differential equations, comprising:

collecting, over time, from a microbial population within a storable food product, a plurality of samples;

inputting, into a computer comprising a microprocessor executing instructions stored on the computer, a plurality of time-dependent microbial data from the plurality of samples, the plurality of time-dependent microbial data comprising a plurality of pairs of microbial counts with respect to time;

modeling a storable food product composition, said modeling comprising;

inputting, into the computer, experimentally measured data pair vectors comprising time (td) vector and corresponding population count (xd) vector;

inputting, into the computer, initial values of rate constant estimates comprising a k-vector of at least six numerical values (k₁, k₂, k₃, k₄, k₅, k₆ . . . k_n);

storing each of the td vector, xd vector and k-vector values in memory of the computer for use in a Quasi-chemical kinetics growth-death-tailing model wherein the model is defined by five rate equations derived from a hypothetical mechanism of reaction steps of biochemical processes;

2. The method of claim 1, wherein the steps of repeatedly integrating and varying comprise:

comparing the calculated population data to the experimentally obtained measured data pair vectors;

changing specific numerical values of the k-vector to minimize a difference between compared experimentally measured data pair vectors and the calculated population data for all data pairs of the k-vector;

wherein said integrating, comparing and changing are iterated until a predetermined fitting criterion is obtained, said predetermined fitting criterion representing attainment of an optimal curve fit of the calculated population data compared with the experimentally determined population data on the screen of the computer.

3. The method of claim 1, wherein the informational composite comprises a graphical plot of the pre-stored experimentally obtained measured data, a graphical plot of calculated data values at identical times as data points of the pre-stored experimentally obtained measured data, a listing of k-vector values used to generate a fitted curve, and an estimate of an overall error in the fitting.

4. The method of claim 3, wherein the graphical plot of measured data comprises a log-log or log-time graphical plot of the measured experimental data pair vectors.

5. The method of claim 3, wherein the graphical plot of calculated values comprises a log-log plot of the calculated values.

6. The method of claim 1, further comprising:

entering an additional command to obtain a smoother curve of the calculated population based on a computation of additional population time pair vectors.

7. The method of claim 1, further comprising using the model to guide the manufacturing of the storable food product where the storable food product has been determined safe for consumption.

8. The method of claim 1, wherein the food processing technology includes a system to perform at least one of thermal processing, high-pressure processing, pulsed-electric-field processing, irradiation processing, chemical-agent processing, or ultraviolet processing.

9. A method for determining whether a storable food product is safe for consumption using a model that predicts microbial growth or processing conditions to ensure microbial destruction and assure consumer safety, comprising:

inputting, into a computer comprising a microprocessor executing instructions stored on the computer, a plurality of time-dependent microbial data from a plurality of samples collected over time from a microbial population within a stored product, the plurality of time-dependent microbial data comprising a plurality of pairs of microbial counts with respect to time;

Inputting, into the computer, experimentally measured data pair vectors comprising time (td) vector and corresponding population count (xd) vector;

Inputting, into the computer, initial values of rate constant estimates comprising a k-vector of at least six numerical values (k₁, k₂, k₃, k₄, k₅, k₆ . . . k_n);

storing each of the td vector, xd vector and k-vector values in memory of the computer for use in a Quasi-chemical kinetics growth-death-tailing model wherein the model is defined by five rate equations derived from a hypothetical mechanism of reaction steps of biochemical processes;

10. The method of claim 9, further comprising the step of:

wherein the steps of repeatedly integrating and varying comprise;

comparing the calculated population data to the experimentally obtained measured data pair vectors;

changing specific numerical values of the k-vector to minimize a difference between compared experimentally measured data pair vectors and the calculated population data for all data pairs of the k-vector;

wherein said integrating, comparing and changing are iterated until a predetermined fitting criterion is obtained, said predetermined fitting criterion representing attainment of an optimal curve fit of the calculated population data compared with the experimentally determined population data on the screen of the computer.

11. The method of claim 9, wherein the informational composite comprises a graphical plot of the pre-stored experimentally obtained measured data, a graphical plot of calculated data values at identical times as data points of the pre-stored experimentally obtained measured data, a listing of k-vector values used to generate a fitted curve, and an estimate of an overall error in the fitting.

12. The method of claim 11, wherein the properties of the fitted curve are evaluated to determine lag times, growth or death rates, or processing times.

13. The method of claim 11, wherein the values of lag times, growth or death rates, and processing times are mathematically interrelated with environmental parameters to allow predictions of microbial growth or survival in response to environmental parameters such as conditions which were not measured experimentally.

14. The method of claim 9, further comprising:

entering an additional command to obtain a smoother curve of the calculated population on the screen of the computer based on a computation of additional population time pairs vectors.

15. The method of claim 11, wherein the environmental parameters comprise one of pH, water activity, storage temperature, high pressure processing conditions and high temperature processing conditions.

16. The method of claim 9, further comprising using the model to guide the manufacturing of the storable food product where the storable food product has been determined safe for consumption.

17. The method of claim 9, wherein the food processing technology includes a system to perform at least one of thermal processing, high-pressure processing, pulsed-electric-field processing, irradiation processing, chemical-agent processing, or ultraviolet processing.