Disease risk map of anthracnose-twister of onion based on previous disease locations as a future predictors
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Understanding the disease epidemiology of anthracnose-twister disease provide us with information about the spread of disease in different areas with different climates which necessitates site specific disease predictions, management and spread of infection to other areas. Anthracnose-twister disease is caused by Colletotrichum gloeosporioides and Gibberella moniliformis and is considered to be the most destructive disease of onion in the Philippines. The disease had spread in Nueva Ecija and neighboring onion growing provinces in Luzon. To prevent the same situation in the future, disease risk maps could be of great value among decision makers and farmers to minimize damage and losses due to the disease. A geographic information system is an essential tool in analyzing disease data associated with geographic locations which can generate spatial distribution, spread and occurrence of plant diseases in the form of maps. These can provide meaningful information that can be easily interpreted. In this study, the data of previous disease location was utilized to generate prediction and disease risk maps through interpolation using Kriging model. Based on the results, the prediction map suggests anthracnose-twister disease of onion will become an epidemic and the disease outbreak will most likely to occur in the southern part of Bongabon (Philippines). It shows that the southeastern part of Bongabon has a very high risk due to the high incidence rate (50.01% to 75.00%) on this area during the previous cropping seasons. To mitigate the situation in these areas it is recommended to avoid using white onion varieties which is very susceptible to anthracnose-twister, and spray potential fungicides 1 week after transplanting.
KeywordsGeographic information system Kriging Anthracnose-twister disease risk map Epidemiology
This research is an output of the Project Titled Detection, Spatial Tracking, Damage and Yield Assessment and Mapping of Disease and Armyworm Infestations of Onion Using Remote Sensing Technology. We are grateful to the Department of Agriculture-Bureau of Agricultural Research (DA-BAR) for the financial support.
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