Dr.H. Yazdanpanah Assistant Professor, Dept.of Geography, University of Isfahan ,Iran

1. Weather-based Apple fire blight risk map generation using GIS (Case study: east Azerbaijan province, Iran) Dr.H. Yazdanpanah Assistant Professor, Dept.of Geography, University of Isfahan ,Iran Dr. P.Ziaeian Assistant Professor, Dept.of Remote sensing, Shahid beheshti university,Iran

2. Objective • To study and map the areas of east Azerbaijan province for the Fire blight

3. Fire Blight (Erwinia amylovora )Symptoms

4. Maryblyt Model: • The most successful computerised prediction system developed in the United States is the MARYBLYT™ model. MARYBLYT™ has been trialed for over 10 years in the United States and is now being used by American growers and consultants to predict fire blight. • The MARYBLYT™ programme uses the infection criteria to identify infection events and predict the development of symptoms. • The criteria to identify infection events are: • 1. Flowers open with stigmas and petals intact. • 2. The accumulation of at least 110 degree hours* when temperatures are greater than 18.3ºC after first bloom. • 3. Wetting caused either by dew or 0.25 mm of rain (or at least 2.5 mm of rain the previous day). • 4. An average daily temperature of at least 15.6ºC.Computer printouts give the daily temperatures, wetness and likelihood of infection which can be interpreted to decide whether a streptomycin spray is required

5. Growth v/s Temperature of fire blight

6. Disease Development v/s Rainfall

7. GIS Applications in disease risk mapping • Geographic Information Systems/Science (GIS) seem to be a natural fit for epidemiology, the study of the origin and transmission of disease.  Epidemiology attempts to integrate a vast array of risk factors such as temperature, moisture, vegetation type/percent cover, the presence and density of disease vectors (i.e. mosquitoes, ticks, etc.), the presence and density of susceptible hosts, pathogen transmission rates- even the molecular, cellular, reproductive and behavioral biology of the host- in an orderly way.  This information is used to identify which factors are necessary for disease, the areas that support disease vectors, and the risk of disease transmission and outbreak. 

8. Information layers preparation in GIS • In this study based on the MARYBLYT model , the temperature and relative humidity maps of area were prepared and then by using GIS the areas of the province which have got climatic conditions suitable for spreading and infecting the orchards were modeled .

9. Digital elevation model(DEM): • Digital elevation model(DEM) was prepared using topographic map. For this purpose Arc/Info software and a Digitizer were used to digitize all necessary features presented on the map based on UTM map projection system. By exporting the layer prepared in Arc/Info to IDRISI software the format of the map was converted from vector to raster

10. Temperature Map: • The phonological data of apple and pear shown that the flowering period of these two host in east Azerbaijan is during April and may. so,we first calculated the probability of occurrence of daily temperature between 18.3 and 30.0ºC for all meteorological stations available in the area.To do this we used daily temperature data and HYFA software to calculate probabilities of occurrence of daily temperature between 18.3 and 30.0ºC during flowering date of Apple. Then the probability map of occurrence of daily temperature between 18.3 and 30.0ºC during the flowering period was prepared using IDRISI software

11. Probability map of a daily temperature between 18.2 and 30 degree centigrade during the flowering of Apple

12. Probability map of occurring a wet day with suitable temperature for fire blight • Wetting period is one of the most important factors affecting the epidemy of disease. So, the daily relative humidity and rainfall amount of all meteorological stations available in the province was first analysed.. For each station, the probability of occurrence of daily relative humidity greater than 60% or rainfall amount greater than 0.25 mm was calculated

13. Geographical distribution of probability of a day during flowering period with RH>60% or rainfall>0.25 mm

14. fire blight risk map of the east Azerbainan province

15. Risk Rating Low (1): The event would unlikely be to occur. • Medium (2) The event would occur with an even probability. • High (3): The event would be very likely to occur

16. Thanks