Mapping disease risk using a joint probability distribution
A major determinant of plant disease occurrence is the temperature and relative humidity experienced during the growing season. Historical temperature and relative humidity data may be used to determine the probable risk of specific crop diseases occurring in a particular region or country. These risk probabilities can then be used to select appropriate hybrids, chemical protection, or other agricultural production practices to reduce the impact of disease on economic yield. A method of estimating the risk probabilities for plant diseases is presented with an example of corn (Zea mays L.) diseases in Illinois. The disease risks were determined by the construction of a joint probability distribution from information about the marginal distributions of temperature and relative humidity during different growing season periods. The number of consecutive days with favorable conditions play an important role in disease development and their probabilities were also computed. Spatial distributions of disease risks are shown in maps.
Year of publication: |
1996
|
---|---|
Authors: | Hollinger, Steven E. ; Kuchar, Leszek |
Published in: |
Mathematics and Computers in Simulation (MATCOM). - Elsevier, ISSN 0378-4754. - Vol. 42.1996, 2, p. 293-298
|
Publisher: |
Elsevier |
Saved in:
Online Resource
Saved in favorites
Similar items by person
-
Using WGENK to generate synthetic daily weather data for modelling of agricultural processes
Kuchar, Leszek, (2004)
-
Climate indices for application in empirical crop production studies
Mjelde, James W., (1989)
-
ESTIMATING CORN YIELD RESPONSE MODELS TO PREDICT IMPACTS OF CLIMATE CHANGE
Dixon, Bruce L., (1994)
- More ...