Advanced Quantitative Microbiology for Foods and Biosystems: Models for Predicting Growth and Inactivation

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ISBN: 9780849336454 | 0849336457
Cover: Hardcover
Copyright: 4/12/2006

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Presenting a novel view of the quantitative modeling of microbial growth and inactivation patterns in food, water, and biosystems, this book describes new models and calculation methods that enable estimation of microbial growth and survival under a variety of conditions. The author provides coverage of both traditional and alternative models of thermal and non-thermal inactivation. The volume includes chapters on microbial dose response, interpretation of irregular count records and estimation of the frequencies of future outbursts. Featuring numerous illustrations, equations, tables and figures, Advanced Quantitative Microbiology for Foods and Biosystems: Models for Predicting Growth and Inactivation makes a valuable reference tool for food and water microbiologists, food technologists and engineers, government officials, public health specialists, academicians and researchers.

Isothermal Microbial Heat Inactivation

(48)

Primary Models --- the Traditional Approach

(10)

The First-Order Kinetics and the D Value

(3)

The ``Thermal Death Time''

(1)

Biphasic and Multiexponential Decay Models and Their Limitations

(4)

The Logistic Models

(1)

Concluding Remarks to This Section

(1)

The Survival Curve as a Cumulative Form of the Heat Distribution Resistances

(29)

The Weibull Distribution

(5)

Interpretation of the Concavity Direction

(1)

The Fermi (Logistic) Distribution Function

(4)

The Activation Shoulder

(3)

Estimation of the Number of Recoverable Spores

(3)

Sigmoid and Other Kinds of Semilogarithmic Survival Curves

(1)

Sigmoid Curves

(4)

Residual Survival (Strong ``Tailing'')

(1)

Can an Absolute Thermal Death Time Exist?

(2)

Secondary Models

(9)

The ``z'' Value and the Arrhenius Equation

(3)

The Log Logistic Model

(2)

A Discrete b(T) vs. T

(1)

Other Empirical Models

(2)

Nonisothermal Heat Inactivation

(46)

The Traditional Approach

(4)

The F0 Value and Its Limitations

(3)

The Proposed Alternative

(4)

Nonisothermal Weibuillian Survival

(11)

The Rate Model

(2)

Heating and Cooling

(1)

Simulation of Heating Curves by Empirical Models

(3)

Simulated Survival Curves for Processes with Different Target Temperature and Holding Durations

(2)

Temperate Oscillations

(1)

Discontinuous Temperature Profiles

(1)

The Special Case of Log Linear Isothermal Survival

(2)

Non-Weibullian Survival Models

(10)

Logistic (Fermian) Survival

(1)

Extreme Tailing

(3)

Sigmoid Survival Curves

(2)

Isothermal Survival Model's Equation with No Analytic Inverse

(2)

Independence of the Calculated Nonisothermal Survival Curve of the Chosen Survival Model

(1)

Experimental Verification of the Model

(12)

The Isothermal and Nonisothermal Inactivation Patterns of L. monocytogenes

(1)

The Isothermal and Nonisothermal Inactivation of Salmonella

(3)

Isothermal and Nonisothermal Survival Curves of B. sporothermodurans Spores in Soups

(1)

The Isothermal and Nonisothermal Inactivation of E. coli

(6)

Heat-Induced Chemical and Physical Changes

(5)

Generating Nonisothermal Heat Inactivation Curves with Difference Equations in Real Time (Incremental Method)

(16)

The Difference Equation of the Weibullian--Log Logistic Nonisothermal Survival Model

(6)

Non-Weibullian Survival Curves

102

(4)

Comparison between the Continuous and Incremental Models

106

(5)

Estimation of Microbial Survival Parameters from Nonisothermal Inactivation Data

111

(24)

The Linear Case

113

(7)

Linear Survival at Constant Rate Heating

113

(3)

Linear Survival at Varying Heating Rate

116

(4)

The Nonlinear Case

120

(10)

Weibullian--Power Law Inactivation at Arbitary Heating Rate History

120

(1)

Testing the Concept with Simulated Data

120

(4)

Testing the Method with Salmonella Survival Data

124

(1)

Salmonella in a Growth Medium

124

(5)

Salmonella in Minced Chicken Meat

129

(1)

Concluding Remarks

130

(5)

Isothermal Inactivation with Stable and Dissipating Chemical Agents

135

(30)

Chemical Inactivation under ``Constant'' Agent Concentration

137

(2)

Microbial Inactivation with a Dissipating Chemical Agent

139

(18)

Traditional Models

140

(2)

Alternative General Model

142

(3)

Dissipation and Inactivation

145

(1)

Monotonic Agent Dissipation

145

(3)

Agent Dissipation with Regular and Random Oscillations

148

(6)

Agent Replenishment

154

(3)

Estimation of Survival Parameters from Data Obtained during Treatments with a Dissipating Agent

157

(6)

Demonstrations of the Procedure with Published Data

161

(2)

Discrete Version of Survival Model

163

(2)

High CO2 and Ultrahigh Hydrostatic Pressure Preservation

165

(24)

Microbial Inactivation under High CO2 pressure

167

(10)

Effect of Pressure Level and Treatment Duration

170

(4)

Is the Pressurization Rate a Factor?

174

(3)

Ultrahigh Pressure

177

(9)

Ultrahigh-Pressure Treatment in a Perfectly Insulated Vessel

182

(3)

Treatment in an Uninsulated Vessel

185

(1)

How to Use the Model?

186

(3)

Dose--Response Curves

189

(16)

The Fermi (Logistic) Distribution

190

(6)

The Weibull Distribution

196

(4)

Mixed Populations

200

(5)

Isothermal and Nonisothermal Bacterial Growth in a Closed Habitat

205

(42)

The Traditional Models

205

(9)

The Logistic Equation and the Logistic Function

206

(5)

The Gompertz, Baranyi and Roberts, and Other Growth Models

211

(2)

The Lag Time

213

(1)

The Logistic--Fermi Combination Model

214

(6)

Simulation of Nonisothermal Growth Pattern Using the Logistic--Fermi Model

220

(11)

Monotonic Temperature Histories

226

(1)

Regular and Random Temperature Oscillations

226

(5)

Prediction of Nonisothermal Growth Patterns from Isothermal Growth Data

231

(16)

The Growth of Pseudomonas in Refrigerated Fish

235

(6)

The Growth of E. coli

241

(6)

Interpretation of Fluctuating Microbial Count Records in Foods and Water

247

(30)

Microbial Quality Control in a Food Plant

249

(1)

The Origins and Nature of Microbial Count Fluctuations

250

(1)

Asymmetry between Life and Death

251

(1)

Estimating the Frequency of Future Outbursts---the Principle

252

(2)

Testing the Counts' Independence

254

(4)

Uneven Rounding and Record Derounding

258

(3)

Choosing a Distribution Function

261

(8)

Nonparametric Distributions

261

(1)

Parametric Distributions

262

(1)

Calculation of a Distribution's Parameters

262

(3)

The Q--Q Plot

265

(2)

Truncated Distributions

267

(2)

Exinction and Absence

269

(1)

Special Patterns

270

(7)

Populations with a Detection Threshold Level

270

(3)

Records of Positive/Negative Entries

273

(1)

Records with a True or Suspected Trend or Periodicity

274

(3)

Estimating Frequencies of Future Microbial High Counts or Outbursts in Foods and Water --- Case Studies

277

(44)

Microbial Counts in a Cheese-Based Snack

278

(11)

Analysis of Raw Records

278

(7)

Analysis of Normalized Data

285

(4)

Rating Raw Milk Sources

289

(4)

Frozen Foods

293

(5)

E. coli in Wash Water of a Poultry Plant

298

(9)

Fecal Bacteria in Lake Kinneret

307

(14)

Characterization of Count Distributions

311

(1)

Nonlogarithmic Transformations of the Counts

311

(1)

Finding a Truncated Distribution

312

(1)

Distribution of Fecal Bacteria in the Lake's Water

312

(3)

Estimating the Frequency of Future Outbursts

315

(2)

Issues of Concern

317

(4)

A Probabilistic Model of Historic Epidemics

321

(12)

The Model

322

(2)

Mortality from Smallpox and Measles in 18th Century England

324

(7)

Smallpox

324

(4)

Measles

328

(3)

Potential Uses of the Model

331

(2)

Aperiodic Microbial Outbursts with Variable Duration

333

(26)

Microbial Fluctuations in a Water Reservoir

334

(14)

Determination of Model Parameters

338

(2)

Fluctuation Parameters of the Massachusetts Water Reservoir

340

(2)

Validation of the Threshold Estimation Method

342

(6)

A Model of Pathogen Outbursts in Foods

348

(7)

Other Potential Applications of the Model

355

(4)

Outstanding Issues and Concluding Remarks

359

(20)

Inactivation Models

359

(10)

Determination of Survival Parameters from Inactivation Curves Determined under Nonisothermal Conditions

359

(3)

Modeling and Predicting Survival Patterns when Several Influential Factors Vary Simultaneously

362

(3)

Non-Weibullian Inactivation Patterns

365

(1)

Systems in which the Inoculum Size May Affect Inactivation

366

(1)

Robustness and Sensitivity

367

(1)

Relationship between Survival Parameters and Inactivation Mechanism

368

(1)

Alternative Inactivation Technologies

368

(1)

Growth Models

369

(3)

Terminology

369

(1)

Growth under Changing Conditions

369

(1)

Growth under Arbitrary Conditions

370

(1)

Simultaneous Growth and Inactivation or Inactivation and Growth

371

(1)

Fluctuating Records in Water and Foods

372

(2)

Censored Data

372

(1)

Sampling at Different Locations

373

(1)

Risk Assessment

373

(1)

A Few Last Remarks

374

(5)

References

379

(10)

Freeware

389

(2)

Index

391

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Advanced Quantitative Microbiology for Foods and Biosystems: Models for Predicting Growth and Inactivation

Summary

Table of Contents

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Advanced Quantitative Microbiology for Foods and Biosystems: Models for Predicting Growth and Inactivation

Summary

Table of Contents

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