Literature DB >> 28489499

The Evidential Basis of Decision Making in Plant Disease Management.

Gareth Hughes1.   

Abstract

The evidential basis for disease management decision making is provided by data relating to risk factors. The decision process involves an assessment of the evidence leading to taking (or refraining from) action on the basis of a prediction. The primary objective of the decision process is to identify-at the time the decision is made-the control action that provides the best predicted end-of-season outcome, calculated in terms of revenue or another appropriate metric. Data relating to disease risk factors may take a variety of forms (e.g., continuous, discrete, categorical) on measurement scales in a variety of units. Log10-likelihood ratios provide a principled basis for the accumulation of evidence based on such data and allow predictions to be made via Bayesian updating of prior probabilities.

Keywords:  Bayes’ rule; likelihood ratios; risk; risk factors; weight of evidence

Mesh:

Year:  2017        PMID: 28489499     DOI: 10.1146/annurev-phyto-080516-035342

Source DB:  PubMed          Journal:  Annu Rev Phytopathol        ISSN: 0066-4286            Impact factor:   13.078


  3 in total

1.  Predicting plant disease epidemics from functionally represented weather series.

Authors:  D A Shah; P A Paul; E D De Wolf; L V Madden
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-06-24       Impact factor: 6.237

2.  Information Graphs Incorporating Predictive Values of Disease Forecasts.

Authors:  Gareth Hughes; Jennifer Reed; Neil McRoberts
Journal:  Entropy (Basel)       Date:  2020-03-20       Impact factor: 2.524

3.  Mutual Information as a Performance Measure for Binary Predictors Characterized by Both ROC Curve and PROC Curve Analysis.

Authors:  Gareth Hughes; Jennifer Kopetzky; Neil McRoberts
Journal:  Entropy (Basel)       Date:  2020-08-26       Impact factor: 2.524

  3 in total

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