Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Heat Engines01:10

Heat Engines

3.6K
A heat engine is a device used to extract heat from a source and then convert it into mechanical work used for various applications. For example, a steam engine on an old-style train can produce the work needed for driving the train.
Whenever we consider heat engines (and associated devices such as refrigerators and heat pumps), we do not use the standard sign convention for heat and work. For convenience, we assume that the symbols Qh, Qc, and W represent only the amounts of heat transferred...
3.6K
Steps in the Modeling Process01:14

Steps in the Modeling Process

661
Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...
661
Design Example: Creating a Hydraulic Model of a Dam Spillway01:21

Design Example: Creating a Hydraulic Model of a Dam Spillway

708
Scaled hydraulic models of dam spillways provide a practical way to replicate and study the intricate flow dynamics of these structures. Often built to a 1:15 ratio, these models allow for observing critical water behavior, such as velocity distribution, flow patterns, and energy dissipation.
708
Heating and Cooling Curves02:44

Heating and Cooling Curves

27.4K
When a substance—isolated from its environment—is subjected to heat changes, corresponding changes in temperature and phase of the substance is observed; this is graphically represented by heating and cooling curves.
For instance, the addition of heat raises the temperature of a solid; the amount of heat absorbed depends on the heat capacity of the solid (q = mcsolidΔT). According to thermochemistry, the relation between the amount of heat absorbed or released by a substance, q, and its...
27.4K
Generation of Straight or Branched Actin Filaments01:14

Generation of Straight or Branched Actin Filaments

3.7K
The straight or branched structure formation of actin filaments is controlled by nucleating proteins such as the formins and Arp2/3 complex. Formin-mediated assembly results in straight filaments, whereas Arp2/3 protein complex-mediated assembly results in branched actin filaments.
Arp2/3 Complex
Arp2/3 complex is a seven-subunit complex consisting of two proteins similar to actin- Arp2 and Arp3, and five other subunits that help keep Arp2 and Arp3 inactive. When required, the complex is...
3.7K
One-Compartment Open Model: Urinary Excretion Data and Determination of k01:11

One-Compartment Open Model: Urinary Excretion Data and Determination of k

621
The one-compartment open model leverages urinary excretion data to estimate renal clearance, which gauges the kidney's capacity to expel a drug. This method offers several benefits, including directly measuring drug elimination and assessing the kidney's contribution to overall drug clearance. However, this approach has limitations. It assumes sole renal excretion of the drug, which is not true for all drugs. Accurate urinary excretion and plasma drug concentration measurement can also...
621

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Evaluating a Ground-Beef Patty Cooking Process Using the General Method of Process Calculation.

Journal of food protection·2019
Same author

Heat Penetration Rates of Natural Convection Heating Liquids in Metal Containers.

Journal of food protection·2019
Same author

Heat Penetration Rates of Natural Convection Heating Liquids in Metal Containers.

Journal of food protection·2019
Same author

Establishing the Heat-Preservation Process For Aseptically-Packaged Low-Acid Food Containing Large Particulates, Sterilized in a Continuous Heat-Hold-Cool System <sup>1</sup>.

Journal of food protection·2019
Same author

Endpoint of a Preservation Process <sup>1</sup>.

Journal of food protection·2019
Same author

Factors Important in Determining the Heat Process Value, F<sub>T</sub>, for Low-Acid Canned Foods <sup>1</sup>.

Journal of food protection·2019

Related Experiment Video

Updated: Jan 26, 2026

Designing a Bioreactor to Improve Data Acquisition and Model Throughput of Engineered Cardiac Tissues
12:28

Designing a Bioreactor to Improve Data Acquisition and Model Throughput of Engineered Cardiac Tissues

Published on: June 2, 2023

3.1K

Using the Straight-Line Semilogarithmic Microbial Destruction Model as an Engineering Design Model for Determining

I J Pflug1

  • 1Department of Food Science and Nutrition, University of Minnesota, 1334 Eckles Avenue, St. Paul, Minnesota 55108.

Journal of Food Protection
|April 11, 2019
PubMed
Summary
This summary is machine-generated.

This review supports using the semilogarithmic microbial destruction model for determining heat process FT-values. This engineering approach aids in food preservation by predicting microbial inactivation and understanding failure rates.

More Related Videos

Somatic Genome-Engineered Mouse Models Using In Vivo Microinjection and Electroporation
08:06

Somatic Genome-Engineered Mouse Models Using In Vivo Microinjection and Electroporation

Published on: May 5, 2023

2.5K
A Rapid Method for Modeling a Variable Cycle Engine
04:58

A Rapid Method for Modeling a Variable Cycle Engine

Published on: August 13, 2019

8.0K

Related Experiment Videos

Last Updated: Jan 26, 2026

Designing a Bioreactor to Improve Data Acquisition and Model Throughput of Engineered Cardiac Tissues
12:28

Designing a Bioreactor to Improve Data Acquisition and Model Throughput of Engineered Cardiac Tissues

Published on: June 2, 2023

3.1K
Somatic Genome-Engineered Mouse Models Using In Vivo Microinjection and Electroporation
08:06

Somatic Genome-Engineered Mouse Models Using In Vivo Microinjection and Electroporation

Published on: May 5, 2023

2.5K
A Rapid Method for Modeling a Variable Cycle Engine
04:58

A Rapid Method for Modeling a Variable Cycle Engine

Published on: August 13, 2019

8.0K

Area of Science:

  • Food Science
  • Microbiology
  • Chemical Engineering

Background:

  • Food preservation relies on both scientific understanding and engineering application.
  • Heat processing is a critical engineering operation in food production.
  • Existing models may prioritize scientific data fitting over engineering design requirements.

Purpose of the Study:

  • To advocate for the semilogarithmic microbial destruction model as a practical tool for establishing heat process FT-values.
  • To highlight the engineering aspects of heat processing and the need for an engineering design model.
  • To demonstrate the model's utility in predicting outcomes based on microbial load variations.

Main Methods:

  • Review of existing literature on microbial destruction models.
  • Analysis of the characteristics of engineering design models versus scientific data models.
  • Application of the semilogarithmic model to a case study involving microbial load changes.

Main Results:

  • The semilogarithmic model is presented as a suitable engineering design model for FT-value determination.
  • The model effectively contrasts engineering design needs with scientific data fitting requirements.
  • An example illustrates how initial microbial load impacts observed failures.

Conclusions:

  • The semilogarithmic microbial destruction model is a valuable engineering tool for optimizing heat processes.
  • This model supports informed decision-making in food preservation by predicting microbial inactivation.
  • Utilizing this engineering approach enhances the reliability of heat process FT-value calculations.