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ISHS Acta Horticulturae 411: VII International Workshop on Fire Blight

USE OF THE AREA UNDER THE DISEASE PROGRESS CURVE FOR QUANTIFICATION OF RESISTANCE OF APPLE AND PEAR VARIETIES AND ROOTSTOCKS TO ERWINIA AMYLOVORA

Authors:   M.T. Momol, J.L. Norelli, H.S. Aldwinckle, W. Zeller
Abstract:
An important aim in many apple and pear improvement programs around the world, is to increase resistance to Erwinia amylovora by classical breeding and/or genetic engineering. Disease assessment is an important aspect of resistance quantification. The assessment method should be accurate, precise and, reproducible. Disease severity is the area or volume of plant tissue that is diseased, usually relative to the total area or volume. Disease incidence refers to number of plant units (whole plant, limbs, shoots, blossom clusters) that are visibly diseased relative to the total number. In fire blight research severity is often measured as percentage of shoot length infected. Blossom resistance is often measured by incidence of blossom infection. When and how often disease assessment should be made, is dependent on the purpose and available sources.

In general, the final amount of disease (Yf) is measured when lesions have ceased extending. As an alternative, temporal analysis of the development of disease could be performed when greater quantification is needed for resistance evaluation. The disease progress curve (DPC) represents an integration of all host, pathogen and environmental effects occurring during disease development and provides an opportunity for greater in depth analysis when comparing small differences among cultivars. Although DPC has been used for fire blight research, it has generally not been used to its full potential. From each DPC, the time of disease onset, the initial amount of disease (Yo), the rate of disease increase (r), the area under the DPC (AUDPC), the shape of curve, the maximum (Ymax) and final (Yf) amounts of disease, the latent period (p), and the overall duration of disease development can be determined or can be estimated statistically.

AUDPC incorporates many of these parameters in one summary value. Several data sets were used to discuss the use of AUDPC for the quantification of resistance in fire blight screening programs.

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