A Site-Specific, Weather-Based Disease Regression Model for Sclerotinia Blight of Peanut
In North Carolina, losses due to Sclerotinia blight of peanut, caused by the fungus Sclerotinia minor, are an estimated 1 to 4 million dollars annually. In general, peanut (Arachis hypogaea) is very susceptible to Sclerotinia blight, but some partially resistant virginia-type cultivars are available...
| Veröffentlicht in: | Plant disease. - 1997. - 91(2007), 11 vom: 01. Nov., Seite 1436-1444 |
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| Weitere Verfasser: | , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2007
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| Zugriff auf das übergeordnete Werk: | Plant disease |
| Schlagworte: | Journal Article groundnut |
| Zusammenfassung: | In North Carolina, losses due to Sclerotinia blight of peanut, caused by the fungus Sclerotinia minor, are an estimated 1 to 4 million dollars annually. In general, peanut (Arachis hypogaea) is very susceptible to Sclerotinia blight, but some partially resistant virginia-type cultivars are available. Up to three fungicide applications per season are necessary to maintain a healthy crop in years highly favorable for disease development. Improved prediction of epidemic initiation and identification of periods when fungicides are not required would increase fungicide efficiency and reduce production costs on resistant and susceptible cultivars. A Sclerotinia blight disease model was developed using regression strategies in an effort to describe the relationships between modeled environmental variables and disease increase. Changes in incremental disease incidence (% of newly infected plants of the total plant population per plot) for the 2002-2005 growing seasons were statistically transformed and described using 5-day moving averages of modeled site-specific weather variables (localized, mathematical estimations of weather data derived at a remote location) obtained from SkyBit (ZedX, Inc.). Variables in the regression to describe the Sclerotinia blight disease index included: mean relative humidity (linear and quadratic), mean soil temperature (quadratic), maximum air temperature (linear and quadratic), maximum relative humidity (linear and quadratic), minimum air temperature (linear and quadratic), minimum relative humidity (linear and quadratic), and minimum soil temperature (linear and quadratic). The model explained approximately 50% of the variability in Sclerotinia blight index over 4 years of field research in eight environments. The relationships between weather variables and Sclerotinia blight index were independent of host partial resistance. Linear regression models were used to describe progress of Sclerotinia blight on cultivars and breeding lines with varying levels of partial resistance. Resistance affected the rate of disease progress, but not disease onset. The results of this study will be used to develop site- and cultivar-specific spray advisories for Sclerotinia blight |
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| Beschreibung: | Date Revised 20.11.2019 published: Print Citation Status PubMed-not-MEDLINE |
| ISSN: | 0191-2917 |
| DOI: | 10.1094/PDIS-91-11-1436 |