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Isothermal Microbial Heat Inactivation |
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1 | (48) |
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Primary Models --- the Traditional Approach |
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1 | (10) |
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The First-Order Kinetics and the D Value |
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1 | (3) |
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The ``Thermal Death Time'' |
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4 | (1) |
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Biphasic and Multiexponential Decay Models and Their Limitations |
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5 | (4) |
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9 | (1) |
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Concluding Remarks to This Section |
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10 | (1) |
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The Survival Curve as a Cumulative Form of the Heat Distribution Resistances |
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11 | (29) |
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17 | (5) |
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Interpretation of the Concavity Direction |
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22 | (1) |
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The Fermi (Logistic) Distribution Function |
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23 | (4) |
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27 | (3) |
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Estimation of the Number of Recoverable Spores |
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30 | (3) |
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Sigmoid and Other Kinds of Semilogarithmic Survival Curves |
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33 | (1) |
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33 | (4) |
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Residual Survival (Strong ``Tailing'') |
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37 | (1) |
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Can an Absolute Thermal Death Time Exist? |
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38 | (2) |
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40 | (9) |
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The ``z'' Value and the Arrhenius Equation |
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41 | (3) |
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44 | (2) |
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46 | (1) |
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47 | (2) |
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Nonisothermal Heat Inactivation |
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49 | (46) |
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49 | (4) |
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The F0 Value and Its Limitations |
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50 | (3) |
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53 | (4) |
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Nonisothermal Weibuillian Survival |
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57 | (11) |
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57 | (2) |
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59 | (1) |
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Simulation of Heating Curves by Empirical Models |
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59 | (3) |
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Simulated Survival Curves for Processes with Different Target Temperature and Holding Durations |
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62 | (2) |
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64 | (1) |
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Discontinuous Temperature Profiles |
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65 | (1) |
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The Special Case of Log Linear Isothermal Survival |
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66 | (2) |
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Non-Weibullian Survival Models |
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68 | (10) |
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Logistic (Fermian) Survival |
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69 | (1) |
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70 | (3) |
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73 | (2) |
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Isothermal Survival Model's Equation with No Analytic Inverse |
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75 | (2) |
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Independence of the Calculated Nonisothermal Survival Curve of the Chosen Survival Model |
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77 | (1) |
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Experimental Verification of the Model |
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78 | (12) |
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The Isothermal and Nonisothermal Inactivation Patterns of L. monocytogenes |
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80 | (1) |
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The Isothermal and Nonisothermal Inactivation of Salmonella |
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81 | (3) |
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Isothermal and Nonisothermal Survival Curves of B. sporothermodurans Spores in Soups |
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84 | (1) |
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The Isothermal and Nonisothermal Inactivation of E. coli |
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84 | (6) |
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Heat-Induced Chemical and Physical Changes |
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90 | (5) |
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Generating Nonisothermal Heat Inactivation Curves with Difference Equations in Real Time (Incremental Method) |
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95 | (16) |
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The Difference Equation of the Weibullian--Log Logistic Nonisothermal Survival Model |
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96 | (6) |
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Non-Weibullian Survival Curves |
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102 | (4) |
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Comparison between the Continuous and Incremental Models |
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106 | (5) |
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Estimation of Microbial Survival Parameters from Nonisothermal Inactivation Data |
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111 | (24) |
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113 | (7) |
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Linear Survival at Constant Rate Heating |
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113 | (3) |
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Linear Survival at Varying Heating Rate |
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116 | (4) |
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120 | (10) |
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Weibullian--Power Law Inactivation at Arbitary Heating Rate History |
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120 | (1) |
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Testing the Concept with Simulated Data |
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120 | (4) |
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Testing the Method with Salmonella Survival Data |
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124 | (1) |
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Salmonella in a Growth Medium |
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124 | (5) |
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Salmonella in Minced Chicken Meat |
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129 | (1) |
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130 | (5) |
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Isothermal Inactivation with Stable and Dissipating Chemical Agents |
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135 | (30) |
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Chemical Inactivation under ``Constant'' Agent Concentration |
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137 | (2) |
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Microbial Inactivation with a Dissipating Chemical Agent |
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139 | (18) |
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140 | (2) |
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Alternative General Model |
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142 | (3) |
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Dissipation and Inactivation |
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145 | (1) |
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Monotonic Agent Dissipation |
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145 | (3) |
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Agent Dissipation with Regular and Random Oscillations |
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148 | (6) |
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154 | (3) |
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Estimation of Survival Parameters from Data Obtained during Treatments with a Dissipating Agent |
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157 | (6) |
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Demonstrations of the Procedure with Published Data |
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161 | (2) |
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Discrete Version of Survival Model |
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163 | (2) |
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High CO2 and Ultrahigh Hydrostatic Pressure Preservation |
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165 | (24) |
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Microbial Inactivation under High CO2 pressure |
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167 | (10) |
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Effect of Pressure Level and Treatment Duration |
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170 | (4) |
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Is the Pressurization Rate a Factor? |
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174 | (3) |
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177 | (9) |
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Ultrahigh-Pressure Treatment in a Perfectly Insulated Vessel |
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182 | (3) |
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Treatment in an Uninsulated Vessel |
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185 | (1) |
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186 | (3) |
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189 | (16) |
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The Fermi (Logistic) Distribution |
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190 | (6) |
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196 | (4) |
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200 | (5) |
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Isothermal and Nonisothermal Bacterial Growth in a Closed Habitat |
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205 | (42) |
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205 | (9) |
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The Logistic Equation and the Logistic Function |
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206 | (5) |
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The Gompertz, Baranyi and Roberts, and Other Growth Models |
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211 | (2) |
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213 | (1) |
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The Logistic--Fermi Combination Model |
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214 | (6) |
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Simulation of Nonisothermal Growth Pattern Using the Logistic--Fermi Model |
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220 | (11) |
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Monotonic Temperature Histories |
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226 | (1) |
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Regular and Random Temperature Oscillations |
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226 | (5) |
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Prediction of Nonisothermal Growth Patterns from Isothermal Growth Data |
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231 | (16) |
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The Growth of Pseudomonas in Refrigerated Fish |
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235 | (6) |
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241 | (6) |
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Interpretation of Fluctuating Microbial Count Records in Foods and Water |
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247 | (30) |
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Microbial Quality Control in a Food Plant |
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249 | (1) |
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The Origins and Nature of Microbial Count Fluctuations |
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250 | (1) |
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Asymmetry between Life and Death |
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251 | (1) |
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Estimating the Frequency of Future Outbursts---the Principle |
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252 | (2) |
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Testing the Counts' Independence |
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254 | (4) |
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Uneven Rounding and Record Derounding |
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258 | (3) |
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Choosing a Distribution Function |
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261 | (8) |
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Nonparametric Distributions |
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261 | (1) |
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262 | (1) |
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Calculation of a Distribution's Parameters |
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262 | (3) |
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265 | (2) |
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267 | (2) |
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269 | (1) |
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270 | (7) |
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Populations with a Detection Threshold Level |
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270 | (3) |
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Records of Positive/Negative Entries |
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273 | (1) |
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Records with a True or Suspected Trend or Periodicity |
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274 | (3) |
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Estimating Frequencies of Future Microbial High Counts or Outbursts in Foods and Water --- Case Studies |
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277 | (44) |
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Microbial Counts in a Cheese-Based Snack |
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278 | (11) |
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278 | (7) |
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Analysis of Normalized Data |
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285 | (4) |
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289 | (4) |
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293 | (5) |
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E. coli in Wash Water of a Poultry Plant |
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298 | (9) |
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Fecal Bacteria in Lake Kinneret |
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307 | (14) |
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Characterization of Count Distributions |
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311 | (1) |
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Nonlogarithmic Transformations of the Counts |
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311 | (1) |
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Finding a Truncated Distribution |
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312 | (1) |
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Distribution of Fecal Bacteria in the Lake's Water |
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312 | (3) |
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Estimating the Frequency of Future Outbursts |
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315 | (2) |
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317 | (4) |
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A Probabilistic Model of Historic Epidemics |
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321 | (12) |
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322 | (2) |
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Mortality from Smallpox and Measles in 18th Century England |
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324 | (7) |
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324 | (4) |
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328 | (3) |
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Potential Uses of the Model |
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331 | (2) |
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Aperiodic Microbial Outbursts with Variable Duration |
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333 | (26) |
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Microbial Fluctuations in a Water Reservoir |
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334 | (14) |
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Determination of Model Parameters |
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338 | (2) |
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Fluctuation Parameters of the Massachusetts Water Reservoir |
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340 | (2) |
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Validation of the Threshold Estimation Method |
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342 | (6) |
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A Model of Pathogen Outbursts in Foods |
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348 | (7) |
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Other Potential Applications of the Model |
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355 | (4) |
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Outstanding Issues and Concluding Remarks |
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359 | (20) |
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359 | (10) |
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Determination of Survival Parameters from Inactivation Curves Determined under Nonisothermal Conditions |
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359 | (3) |
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Modeling and Predicting Survival Patterns when Several Influential Factors Vary Simultaneously |
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362 | (3) |
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Non-Weibullian Inactivation Patterns |
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365 | (1) |
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Systems in which the Inoculum Size May Affect Inactivation |
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366 | (1) |
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Robustness and Sensitivity |
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367 | (1) |
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Relationship between Survival Parameters and Inactivation Mechanism |
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368 | (1) |
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Alternative Inactivation Technologies |
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368 | (1) |
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369 | (3) |
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369 | (1) |
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Growth under Changing Conditions |
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369 | (1) |
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Growth under Arbitrary Conditions |
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370 | (1) |
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Simultaneous Growth and Inactivation or Inactivation and Growth |
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371 | (1) |
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Fluctuating Records in Water and Foods |
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372 | (2) |
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372 | (1) |
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Sampling at Different Locations |
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373 | (1) |
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373 | (1) |
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374 | (5) |
References |
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379 | (10) |
Freeware |
|
389 | (2) |
Index |
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391 | |