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| Web URL(s): | https://scisoc.confex.com/scisoc/2020am/meetingapp.cgi/Paper/126765
Last checked: 09/14/2023 |
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| Publication Type:
| Report |
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| Content Type: | Abstract or Summary only |
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| Author(s): | Zhang, Pingyuan;
Murphy, James A.;
Clarke, Bruce B. |
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| Author Affiliation: | Department of Plant Biology, Rutgers University, New Brunswick, NJ |
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| Title: | Interpretations of a logistic regression model for fungicide control of dollar spot on creeping bengrass |
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| Section: | Turfgrass pest management poster: Diseases, insects, weeds (includes student competition)
Other records with the "Turfgrass pest management poster: Diseases, insects, weeds (includes student competition)" Section
C05 turfgrass science
Other records with the "C05 turfgrass science" Section
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| Meeting Info.: | San Antonio, Texas: November 9-13, 2020 |
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| Source: | ASA, CSSA, SSSA International Annual Meeting. November 2020, p. 126765. |
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| Publishing Information: | [Madison, Wisconsin]: [American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America] |
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| # of Pages: | 1 |
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| Abstract/Contents: | "A logistic regression model was developed to produce a risk index (RI) based on 5-d moving averages of air temperature and relative humidity to guide fungicide control of dollar spot caused by Clarireedia jacksonii. Additional interpretation of the RI threshold may be needed, particularly for cultivars that are more tolerant of the disease. A field trial was initiated in May 2019 to assess multiple interpretations of the RI output from a logistic regression model for the control of dollar spot on two creeping bentgrass (A. stolonifera) cultivars in North Brunswick, NJ. Each cultivar (Declaration, more tolerant and Independence, more susceptible) was subjected to 22 fungicide programs based on a calendar-based preventive schedule, disease-threshold curative schedule, or 20 interpretations of the RI output from the logistic regression model. The 20 interpretations of the model output included four RI threshold levels (20, 30, 40, 50%), four RI slope conditions after disease onset, and a 3*4 factorial combination of RI threshold levels (20, 30, 40%) and four RI slope conditions. The four conditions of RI slope considered the change in RI over the previous and/or forecasted 5-day period. Fungicide was applied if the slope was positive over the previous 5-d; positive over the forecasted 5-d; positive over both the previous and forecasted 5-d; or positive over the previous or forecasted 5-d). The alternative interpretations of the RI output resulted in two to nine applications during 2019 compared to the nine calendar-based applications and two to five curative-based applications on Declaration and Independence, respectively. Compared to using RI threshold alone, combinations of RI threshold and slopes reduced the number of applications needed to control dollar spot by 1 to 3, especially when a positive forecasted slope was required. An economic analysis of disease response is in progress." |
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| Language: | English |
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| References: | 1 |
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| Note: | This item is an abstract only!
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| ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Zhang, P., J. A. Murphy, and B. B. Clarke. 2020. Interpretations of a logistic regression model for fungicide control of dollar spot on creeping bengrass. Agron. Abr. p. 126765. |
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https://scisoc.confex.com/scisoc/2020am/meetingapp.cgi/Paper/126765
Last checked: 09/14/2023 |
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