Disease assessment concepts and the advancements made in improving the accuracy and precision of plant disease data

Forrest W. Nutter, Paul Esker, Rosalee A. Coelho Netto

Research output: Chapter in Book/Report/Conference proceedingChapter

10 Scopus citations

Abstract

New concepts in phytopathometry continue to emerge, such as the evolution of the concept of pathogen intensity versus the well-established concept of disease intensity. The concept of pathogen severity, defined as the quantitative measurement of the amount of pathogen per sampling unit has also emerged in response to the now commonplace development of quantitative molecular detection tools. Although the concept of disease severity, i.e., the amount of disease per sampling unit, is a well-established concept, the accuracy and precision of visual estimates of disease severity is often questioned. This article will review disease assessment concepts, as well as the methods and assessment aides currently available to improve the accuracy and precision of visually-based disease severity data. The accuracy and precision of visual disease severity assessments can be improved by quantitatively measuring and comparing the accuracy and precision of rates and/or assessment methods using linear regression, by using computer-based disease assessment training programmes, and by developing and using diagrammatic keys (standard area diagrams).

Original languageEnglish (US)
Title of host publicationPlant disease epidemiology
Subtitle of host publicationfacing challenges of the 21st Century: Under the aegis of an International Plant Disease Epidemiology Workshop held at Landernau, France, 10-15th April, 2005
PublisherSpringer Netherlands
Pages95-103
Number of pages9
ISBN (Print)1402050194, 9781402050190
DOIs
StatePublished - Dec 1 2006

All Science Journal Classification (ASJC) codes

  • General Medicine

Fingerprint

Dive into the research topics of 'Disease assessment concepts and the advancements made in improving the accuracy and precision of plant disease data'. Together they form a unique fingerprint.

Cite this