Disease risk curves

Phytopathology

Volumn 103, Issue 11, 2013, Pages 1108-1114

  Hughes, G ^a   Burnett, F J ^a   Havis, N D ^a  

^a SCOTTISH AGRICULTURAL COLLEGE   (United Kingdom)

Author keywords

Conditional dependence; Disease management; Sequential diagnosis

Indexed keywords

ARTICLE; CROP; DISEASE COURSE; PLANT DISEASE; RISK; RISK ASSESSMENT; STATISTICAL MODEL; STATISTICS;

CROPS, AGRICULTURAL; DISEASE PROGRESSION; MODELS, STATISTICAL; PLANT DISEASES; RISK; RISK ASSESSMENT;

EID: 84887029490     PISSN: 0031949X     EISSN: None     Source Type: Journal    
DOI: 10.1094/PHYTO-12-12-0327-R     Document Type: Article

References (33)

1. Burnett, F., Butler-Ellis, C., Hughes, G., Knight, S., and Ray, R. 2012. Forecasting Eyespot Development and Yield Losses in Winter Wheat. Project Report Number 491. HGCA, Kenilworth, UK.
2. Campbell, C. L., and Madden, L. V. 1990. Introduction to Plant Disease Epidemiology. John Wiley & Sons, Inc., New York.
3. Copas, J. B. 1993. The shrinkage of point scoring methods. J. R. Stat. Soc. C 42:315-331.
4. Fabre, F., Plantegenest, M., and Yuen, J. 2007. Financial benefit of using crop protection decision rules over systematic spraying strategies. Phytopathology 97:1484-1490.
5. Glass, R. D. 1996. Diagnosis, a Brief Introduction. Oxford University Press, Melbourne, Australia.
6. Good, I. J. 1979. Studies in the history of probability and statistics. XXXVII. A. M. Turing's statistical work in World War II. Biometrika 66:393-396.
7. Good, I. J. 1985. Weight of evidence: A brief survey. In: Bayesian Statistics
8. J. M. Bernardo, M. H. De Groot, D. V. Lindley, and A. F. M. Smith, eds. Elsevier Science Publishers B. V. (North-Holland), Amsterdam, The Netherlands.
9. Good, I. J. 2003. The accumulation of imprecise weights of evidence. SIPTA Newsl. 1:2-8.
10. Havis, N. D., Oxley, S. J. P., and Burnett, F. J. 2012. Advances in control of Ramularia collo-cygni. Pages 119-124 in: Proc. Crop Prot. North. Britain, Dundee, UK.
11. Havis, N. D., Oxley, S. J. P., Burnett, F. J., and Hughes, G. 2012. Epidemiology of Ramularia collo-cygni. Pages 125-130 in: Proc. Crop Prot. North. Britain, Dundee, UK.
12. Hood, C., Rothstein, H., and Baldwin, R. 2004. The Government of Risk-Understanding Risk Regulation Regimes. Oxford University Press, Oxford.
13. James, W. C. 1974. Assessment of plant diseases and losses. Annu. Rev. Phytopathol. 12:27-48.
14. Jeger, M. 2004. Analysis of disease progress curves as a basis for evaluating disease management practices. Annu. Rev. Phytopathol. 42:61-82.
15. Johnson, D. A., Alldredge, J. R., and Hamm, P. B. 1998. Expansion of potato late blight forecasting models for the Columbia Basin of Washington and Oregon. Plant Dis. 82:642-645.
16. Johnson, D. A., Alldredge, J. R., and Vakoch, D. L. 1996. Potato late blight forecasting models for the semiarid environment of south-central Washington. Phytopathology 86:480-484.
17. Kass, R. E., and Raftery, A. E. 1995. Bayes factors. J. Am. Stat. Assoc. 90:773-795.
18. Lloyd, C. J. 2002. Estimation of a convex ROC curve. Stat. Probabil. Lett. 59:99-111.
19. Makowski, D., Taverne, M., Bolomier, J., and Ducarne, M. 2005. Comparison of risk indicators for Sclerotinia control in oilseed rape. Crop Prot. 24:527-531.
20. Nita, M., Ellis, M. A., and Madden, L. V. 2008. Variation in disease incidence of Phomopsis cane and leaf spot of grape in commercial vineyards in Ohio. Plant Dis. 92:1053-1061.
21. Pethybridge, S. J., Gent, D. H., and Hay, F. S. 2011. Epidemics of ray blight on pyrethrum are linked to seed contamination and overwintering inoculum of Phoma ligulicola var.inoxydabilis. Phytopathology 101:1112-1121.
22. Rembold, C. M., and Watson, D. 1988. Posttest probability calculation by weights, a simple form of Bayes' theorem. Ann. Intern. Med. 108:115-120.
23. Spiegelhalter, D. J. 1986. Probabilistic prediction in patient management and clinical trials. Stat. Med. 5:421-433.
24. Spiegelhalter, D. J., Abrams, K. R., and Myles, J. P. 2004. Bayesian Approaches to Clinical Trials and Health-Care Evaluation. John Wiley & Sons, Ltd., Chichester, UK.
25. Spiegelhalter, D. J., and Knill-Jones R. P. 1984. Statistical and knowledge-based approaches to clinical decision support systems, with an application in gastroenterology (with discussion). J. R. Stat. Soc. A 147:35-77.
26. Teng, P. S., and Gaunt, R. E. 1980. Modelling systems of disease and yield loss in cereals. Agric. Syst. 6:131-154.
27. Tribus, M. 1969. Rational Descriptions, Designs and Decisions. Pergamon Press, New York.
28. Twengström, E., Sigvald, R., Svensson, C., and Yuen, J. 1998. Forecasting Sclerotinia stem rot in spring sown oilseed rape. Crop Prot. 17:405-411.
29. Van Den Ende, J., Bisoffi, Z., Van Puymbroek, H., Van Gompel, A., Derese, A., Lynen, L., Moreira, J., and Janssen, P. A. J. 2007. Bridging the gap between clinical practice and diagnostic clinical epidemiology: Pilot experiences with a didactic model based on a logarithmic scale. J. Eval. Clin. Pract. 13:374-380.
30. Van Den Ende, J., Moreira, J., Basinga, P., and Bisoffi, Z. 2005. The trouble with likelihood ratios. Lancet 366:548.
31. Van Der Plank, J. E. 1963. Plant Diseases: Epidemics and Control. Academic Press, New York.
32. Yuen, J. E., and Hughes, G. 2002. Bayesian analysis of plant disease prediction. Plant Pathol. 51:407-412.
33. Yuen, J., Twengström, E., and Sigvald, R. 1996. Calibration and verification of risk algorithms using logistic regression. Eur. J. Plant Pathol. 102:847-854.