عنوان

Predicting the establishment and spread of plant disease from regulatory sampling

Number

LA2x24t1b6

.Language of Text, Soundtrack etc

انگلیسی

Title Proper

Predicting the establishment and spread of plant disease from regulatory sampling

General Material Designation

[Article]

First Statement of Responsibility

Luo, W.; Gottwald, T. R.; Pietravalle, S.; Irey, M. S.

Text of Note

Invasive plant diseases can have devastating consequences on the local plant populations, in both agricultural and natural landscapes. Knowledge of the spatial patterns of pathogen spread can be used to guide more time- and cost-effective disease management strategies. Based on disease dispersal principles and consideration of host pattern, an improved plant disease epidemiological model was developed and tested for plant disease mapping. The model is able to characterize the disease dispersal gradient and predict infection risk, with indication of uncertainty, through heterogeneous environments without reference to the source of infection. As a result, sampling methods can be informed by the predicted prevalence map of the disease. In order to better describe the shapes of the dispersal gradients, three different dispersal functions (Exponential, Modified power law, and Cauchy distribution) were considered in the model. Two data sets of disease observations of Huanglongbing (HLB) of citrus in different landscapes (Southern Garden and Devils Garden plantation) in Florida were used to evaluate the performance of the improved method for disease mapping. The results showed that the improved model provided estimates of greater precision for unsampled hosts. With all different dispersal models compared, the exponential dispersal gradient gave the most satisfactory performance. All the determined information can help decision makers understand the spatial aspects of disease processes, and formulate decisions about disease control accordingly.

Date of Publication

2014

Title

Journal of Citrus Pathology

Volume Number

1

Entry Element

Luo, W.; Gottwald, T. R.; Pietravalle, S.; Irey, M. S.

Electronic name

[Article]

275578

a

Y