| |
| Web URL(s): | http://apsjournals.apsnet.org/doi/pdf/10.1094/PHYTO.2008.98.6.S9#page=140
Last checked: 10/20/2015
Requires: PDF Reader
Notes: Item is within a single large file |
|---|
| Publication Type:
| Report |
|---|
| Content Type: | Abstract or Summary only |
|---|
| Author(s): | Smith, D. L.;
Walker, N. R. |
|---|
| Author Affiliation: | Oklahoma State University |
|---|
| Title: | Regressionbased modeling of dollar spot epidemics in creeping bentgrass |
|---|
| Source: | Phytopathology. Vol. 98, No. 6, June Supplement 2008, p. S148. |
|---|
| Publishing Information: | St. Paul, MN: American Phytopathological Society |
|---|
| # of Pages: | 1 |
|---|
| Keywords: | TIC Keywords: Dollar spot; Agrostis stolonifera; Computer modeling; Models; Weather data; Disease forecasting
|
|---|
| Abstract/Contents: | "Dollar spot of turfgrass is caused by the fungus Sclerotinia homoeocarpa. Previously, several weather dependent fundamental prediction models have been developed to predict dollar spot epidemics. These models have been used as disease management tools with limited success. An alternative approach using multiple regression modeling was explored. Number of disease foci and difference in the number of foci from a previous evaluation were determined daily from bentgrass receiving no fungicide. Various sitespecific weather variables were recorded using the Oklahoma MESONET. Weather data were transformed to 2-, 3-, or 4-day moving averages. Disease and weather data were subjected to principal components analysis. Weather data were used as independent variables and disease data as dependent variables in regression analysis to explore potential models. As in previous findings, models using 2-day averages of weather variables were marginally better than models using 3- or 4-day averages. Air temperature and relative humidity were highly influential variables. Soil temperature and solar radiation were also identified as important weather variables, but have not been used in previous dollar spot models. Previous models may have had limited success because they over looked these or other variables. More epidemiological research and regressionbased modeling will be used to improve predictive models and identify other influential weather variables." |
|---|
| Language: | English |
|---|
| References: | 0 |
|---|
| Note: | This item is an abstract only! |
|---|
| ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Smith, D. L., and N. R. Walker. 2008. Regressionbased modeling of dollar spot epidemics in creeping bentgrass. Phytopathology. 98(6):p. S148. |
| Fastlink to access this record outside TGIF: https://tic.msu.edu/tgif/flink?recno=136687 |
| If there are problems with this record, send us feedback about record 136687. |
| Choices for finding the above item: |
|---|
| Web URL(s):
http://apsjournals.apsnet.org/doi/pdf/10.1094/PHYTO.2008.98.6.S9#page=140
Last checked: 10/20/2015
Requires: PDF Reader
Notes: Item is within a single large file |
| 
MSU catalog number: b2219736a |
| Find from within TIC:
Digitally in TIC by record number. |
| Request through your local library's inter-library loan service (bring or send a copy of this TGIF record) |
