| Contributors | |
| Preface | |
| Principles and Methods | |
| Plant disease diagnosis | |
| Introduction | |
| Choice of diagnostic | |
| Diagnosis by conventional techniques | |
| Use of immunological reactions | |
| Methods based on the nucleic acids of pathogens | |
| Future trends in diagnosis | |
| References | |
| Disease assessment and yield loss | |
| Introduction | |
| Why assess disease and yield loss in plants? | |
| Methods used in sampling plants for disease | |
| Timing and frequency of disease assessment | |
| Methods of disease assessment | |
| Assessment of yield loss | |
| Conclusions and future developments | |
| References | |
| Surveys of variation in virulence and fungicide resistance and their application to disease control | |
| Introduction | |
| Characterizing individual pathogens | |
| Populations and samples | |
| Molecular detection of virulence and fungicide resistance | |
| Characterizing pathogen populations | |
| Applications of pathogen survey data | |
| Dissemination of survey results | |
| Pathogen surveys and disease management | |
| Acknowledgement | |
| References | |
| Infection strategies of plant parasitic fungi | |
| Introduction | |
| The pre-penetration phase | |
| Entering the plant tissue | |
| Strategies for colonizing the host tissue | |
| Concluding remarks | |
| References | |
| Epidemiological consequences of plant disease resistance | |
| Introduction | |
| Horizontal resistance | |
| Vertical resistance | |
| Cultivar mixtures | |
| Induces resistance | |
| Non-host immunity | |
| Tolerance | |
| References | |
| Dispersal of foliar plant pathogens: mechanisms, gradients and spatial patterns | |
| Introduction | |
| Underlying mechanisms: spore dispersal | |
| Spore deposition and disease gradients | |
| Disease spread: modeling developments of foci | |
| Conclusions | |
| Acknowledgements | |
| References | |
| Pathogen population dynamics | |
| Introduction | |
| The measurement of populations | |
| Time-scales | |
| Changes in population | |
| Density-dependent and density-independent factors | |
| Short-term change in a static host population | |
| Affected host tissue and pathogen multiply at comparable rates | |
| Changes over time-scales longer than either crop or pathogen | |
| Spatial population structure | |
| Appendix 7A | |
| References | |
| Modelling and interpreting disease progress in time | |
| Introduction | |
| General considerations | |
| Analysing individual epidemics | |
| Reducing data dimension | |
| Comparing epidemics | |
| Concluding remarks | |
| References | |
| Disease forecasting | |
| Introduction | |
| What is forecasting? | |
| Polycyclic and monocyclic diseases | |
| Equipment | |
| Forecasting schemes | |
| Potatoes | |
| Cereals | |
| Oilseed rape | |
| Conclusions | |
| References | |
| Diversification strategies | |
| Introduction | |
| Definitions | |
| Benefits from spatial diversification: small-scale | |
| Benefits of diversification in time (crop rotation) | |
| Diversity and interactions | |
| Responses of pest and pathogen populations to diversification strategies | |
| Diversification strategies in practice | |
| Conclusions | |
| References | |
| Epidemiology in sustainable systems | |
| Introduction | |
| Inoculum | |
| Disease development | |
| Control strategies | |
| Conclusions | |
| Acknowledgement | |
| References | |
| Information technology in plant disease epidemiology | |
| Introduction | |
| Definition of information technology in plant disease epidemiology | |
| The world according to Google'' | |
| Real world data capture | |
| Information accumulation or dissemination? | |
| Bringing together disciplines | |
| Models, expert systems and decision support systems | |
| Some examples of DSS | |
| Disease forecasting and decision making in an information theory framework | |
| Where next? | |
| Conclusions | |
| Acknowledgements | |
| References | |
| Case Examples | |
| Seedborne diseases | |
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