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Web URL(s): | http://apsjournals.apsnet.org/doi/pdf/10.1094/PHYTO-107-2-S2.5#page=4 Last checked: 03/02/2017 Requires: PDF Reader Notes: Item is within a single large file |
Publication Type:
| Report |
Content Type: | Abstract or Summary only |
Author(s): | Hempfling, J.;
Murphy, J.;
Clarke, B. |
Author Affiliation: | Rutgers University, New Brunswick, NJ |
Title: | Predictability of dollar spot disease development on bentgrass using weather-based models |
Section: | 2016 Northeastern Division meeting abstracts Other records with the "2016 Northeastern Division meeting abstracts" Section
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Meeting Info.: | Ithaca, New York: October 19-21, 2016 |
Source: | Phytopathology. Vol. 107, No. 2S, February 2017, p. S2.8. |
Publishing Information: | Lancaster, Pennsylvania: The Society Intelligencer Printing Company for The American Phytopathological Society |
# of Pages: | 1 |
Keywords: | TIC Keywords: Agrostis tenuis; Disease prevention; Dollar spot; Meteorological factors; Weather monitoring
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Abstract/Contents: | "Dollar spot epidemics (caused by Sclerotinia homoeocarpa F.T. Bennett) differ among bentgrass (Agrostis spp.) species and cultivars. The objectives of this research were to evaluate disease incidence on bentgrasses that vary in tolerance to dollar spot under fairway conditions and to assess the reliability of two existing weather-based models for predicting dollar spot epidemics on these grasses. Six bentgrass cultivars ['Independence', 'Penncross', 'Shark', '007', and 'Declaration' creeping bentgrass (A. stolonifera), and 'Capri' colonial bentgrass (A. capillaris)] were seeded in a randomized complete block design with five blocks in North Brunswick, NJ during September 2014. Disease severity was assessed every 2- to 5-d and compared to a growing degree day (GDD) model for predicting the onset of disease symptoms and a logistic regression model for predicting season-long disease activity. The GDD model accurately predicted the onset of disease symptoms in highly susceptible cultivars during 2015 but not 2016. The logistic regression model forecasted a high risk of dollar spot one week before symptoms first appeared in highly susceptible cultivars during both years. Disease forecasting by the logistic regression model was fairly accurate for highly susceptible cultivars throughout 2015, but over-predicted disease activity during 2016. Accurate disease forecasting on tolerant cultivars was more problematic with either model in both years of this study." |
Language: | English |
References: | 0 |
Note: | This item is an abstract only! |
| ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete): Hempfling, J., J. Murphy, and B. Clarke. 2017. Predictability of dollar spot disease development on bentgrass using weather-based models. Phytopathology. 107(2S):p. S2.8. |
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| Web URL(s): http://apsjournals.apsnet.org/doi/pdf/10.1094/PHYTO-107-2-S2.5#page=4 Last checked: 03/02/2017 Requires: PDF Reader Notes: Item is within a single large file |
| MSU catalog number: b2219736a |
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