Skip to main content
ARS Home » Southeast Area » Byron, Georgia » Fruit and Tree Nut Research » Research » Publications at this Location » Publication #301409
Title: What interval characteristics make a good disease assessment category scale

Author
item CHIAN, KUOSZU - National Chung-Hsing University
item LIU, SHIH-CHIA - National Chung-Hsing University
item Bock, Clive
item Gottwald, Timothy

Submitted to: Phytopathology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/16/2014
Publication Date: 6/1/2014
Publication URL: http://dx.doi.org/10.1094?PHYTO-10-13-0279-R
Citation: Chian, K., Liu, S., Bock, C.H., Gottwald, T.R. 2014. What interval characteristics make a good disease assessment category scale. Phytopathology. 104(6): 575-585 http://dx.doi.org/10.1094?PHYTO-10-13-0279-R.

Interpretive Summary: Plant pathologists most often estimate the severity of plant disease based on visual assessments. Category scales are widely used for assessing plant disease severity in field experiments, epidemiological studies, and for screening germplasm. A widely used category scale is the Horsfall-Barratt (H-B) scale which divides the 0 to 100% severity scale into 12 unequal (nonlinear) sized intervals. Few studies have compared different category scales. The objective of this study was to compare the 0 to 100% scale, H-B category scale, and four different linear category scales (5% and 10% increments, with and without additional grades at low severity. Results of simulations based on known distributions of disease estimation using the type II error rate (the risk of failing to reject H0 when H0 is false) showed that the 5 and 10% category scales with the additional grades included performed as well as the 0 to 100% scale. A better knowledge of the advantages and disadvantages of category scale types will provide a basis for plant pathologists and plant breeders seeking to maximize accuracy and reliability of assessments to make an informed decision when choosing a disease assessment method.

Technical Abstract: Plant pathologists most often obtain quantitative information on disease severity using visual assessments. Category scales have been used for assessing plant disease severity in field experiments, epidemiological studies, and for screening germplasm. The most widely used category scale is the Horsfall-Barratt (H-B) scale, but reports show that estimates of disease severity using the H-B scale are less precise compared to nearest percent estimates (NPEs) using the 0-100% ratio scale. Few studies have compared different category scales. The objective of this study was to compare NPEs, the H-B midpoint converted data, and four different linear category scales (5% and 10% increments, with and without additional grades at low severity (0.1, 0.5, 1.0, 2.0, 5.0, 10.0, 15.0, 20.0...100%, and 0.1, 0.5, 1.0, 2.0, 5.0, 10.0, 20.0, 30.0...100%, respectively)). Results of simulations based on known distributions of disease estimation using the type II error rate (the risk of failing to reject H0 when H0 is false) showed that at disease severity =5%, a 10%-category scale had a greater probability of failing to reject H0 when H0 is false compared to all other methods, while the H-B scale performed least well at 20-50% severity. The 5% category scale performed as well as NPEs except when disease severity was =1%. Both the 5 and 10% category scales with the additional grades included performed as well as NPEs. These results were confirmed with a mixed model analysis and bootstrap analysis of the original rater assessment data. A better knowledge of the advantages and disadvantages of category scale types will provide a basis for plant pathologists and plant breeders seeking to maximize accuracy and reliability of assessments to make an informed decision when choosing a disease assessment method.