Author
Simko, Ivan | |
PIEPHO, HANS-PETER - University Of Hohenheim |
Submitted to: Phytopathology
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 11/16/2011 Publication Date: 3/13/2012 Citation: Simko, I., Piepho, H. 2012. The area under the disease progress stairs: calculation, advantage, and application. Phytopathology. 102:381-389. Interpretive Summary: Disease typically starts at a low level, gradually increasing in incidence and/or severity over time. Progress of disease on plants is usually observed several times during pathogen epidemics. Extent of disease is assessed at each observation using scales that are based on disease incidence, severity, or a combination of both. To combine these repeated observations into a single value the Area Under the Disease Progress Curve (AUDPC) approach is used. A common approach to determine AUDPC is through a simple midpoint (trapezoidal) rule that breaks up a disease progress curve into a series of trapezoids, calculating the area of each, and then adding up the areas. However, our analysis shows that this approach severely underestimates the effect of the first and last observation. To get a better estimate of disease progress, we have developed a new formula termed the Area Under the Disease Progress Stairs (AUDPS). The AUDPS approach improves the estimation of disease progress by giving a weight closer to optimal to the first and last observations. We propose using AUDPS and its standardized (sAUDPS) and relative (rAUDPS) forms when combining multiple observations from disease progress experiments into a single value. Technical Abstract: The Area Under the Disease Progress Curve (AUDPC) is frequently used to combine multiple observations of disease progress into a single value. However, our analysis shows that this approach severely underestimates the effect of the first and last observation. To get a better estimate of disease progress, we have developed a new formula termed the Area Under the Disease Progress Stairs (AUDPS). The AUDPS approach improves the estimation of disease progress by giving a weight closer to optimal to the first and last observations. Analysis of real data indicates that AUDPS outperforms AUDPC in most of the tested trials and may be less precise than AUDPC only when assessments in the first or last observations have a comparatively large variance. We propose using AUDPS and its standardized (sAUDPS) and relative (rAUDPS) forms when combining multiple observations from disease progress experiments into a single value. |