Spatio-temporal analysis of a plant disease in a non-uniform crop: A Monte Carlo approach
Document Type
Article
Publication Date
1-1-2011
Abstract
Identification of the type of disease pattern and spread in a field is critical in epidemiological investigations of plant diseases. For example, an aggregation pattern of infected plants suggests that, at the time of observation, the pathogen is spreading from a proximal source. Conversely, a random pattern suggests a lack of spread from a proximal source. Most of the existing methods of spatial pattern analysis work with only one variety of plant at each location and with uniform genetic disease susceptibility across the field. Pecan orchards, used in this study, and other orchard crops are usually composed of different varieties with different levels of susceptibility to disease. A new measure is suggested to characterize the spatio-temporal transmission patterns of disease; a Monte Carlo test procedure is proposed to test whether the transmission of disease is random or aggregated. In addition, we propose a mixed-transmission model, which allows us to quantify the degree of aggregation effect. © 2011 Taylor & Francis.
Publication Source (Journal or Book title)
Journal of Applied Statistics
First Page
175
Last Page
182
Recommended Citation
Li, B., Sanderlin, R., Melanson, R., & Yu, Q. (2011). Spatio-temporal analysis of a plant disease in a non-uniform crop: A Monte Carlo approach. Journal of Applied Statistics, 38 (1), 175-182. https://doi.org/10.1080/02664760903301150