An Algorithm for Predicting Outbreaks of Sclerotinia Blight of Peanut and Improving the Timing of Fungicide Sprays
Algorithms were evaluated for computing disease risk and improving the timing of fungicide applications for control of Sclerotinia blight of peanut. Disease risk was calculated by multiplying indices of moisture, soil temperature, vine growth, and canopy density each day, and summing values for the...
| Veröffentlicht in: | Plant disease. - 1997. - 86(2002), 2 vom: 01. Feb., Seite 118-126 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2002
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| Zugriff auf das übergeordnete Werk: | Plant disease |
| Schlagworte: | Journal Article |
| Zusammenfassung: | Algorithms were evaluated for computing disease risk and improving the timing of fungicide applications for control of Sclerotinia blight of peanut. Disease risk was calculated by multiplying indices of moisture, soil temperature, vine growth, and canopy density each day, and summing values for the previous 5 days to obtain a 5-day risk index (FDI). After fungicide application, the FDI was reset to zero for 3 weeks. Fluazinam at 0.58 kg a.i./ha applied at FDI 24 or 32 in 1994 and 1995 suppressed disease and increased yield as much as or more than programs of weekly scouting and applying fungicide at the initial onset of disease with additional sprays at 3- to 4-week intervals. The FDI algorithm was also more efficient than calendar sprays at 60, 90, and 120 days after planting (DAP). Environmental and host parameters were expanded in 1996 and 1997 by adding new temperature and new vine growth indices. These parameters along with DAP-dependent thresholds consistently improved the timing of fungicide sprays and disease management when using the FDI algorithm in comparison to weekly scouting or calendar sprays at 60, 90, and 120 DAP |
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| Beschreibung: | Date Revised 20.11.2019 published: Print Citation Status PubMed-not-MEDLINE |
| ISSN: | 0191-2917 |
| DOI: | 10.1094/PDIS.2002.86.2.118 |