A Study about Wheat Sunn Pest Diffusion According Temperature Characteristics in Kordestan Province (Case Study: Bijar Countryship)

Introduction
The sunn pest is main pest of wheat in west Asia and Near East (Afghanistan, Iran, Iraq, lobnan, Syria and Turkey) and in Central Asia Republics (Ghzagestan, Ghergizestan, Tajikistan, Turkmenistan, Uzbekistan) Bulgaria and Romania. It is estimated damage amount of wheat production between 20 and 70 percent. Unless unbattle with sunn pest, damage amount will receive to 100 percent. The pollutant amount of agriculture lands is about 8 million Hectare in the world. The damage amount resulted from pest, and herbs are about 30-35 percent which It is about 10-12 percent is belong to pest.
The sunn pest is an important pest of wheat and barley in Iran that damage wheat and barly production each year. The importance of wheat as a main food of Iranian people is not hidden to any one. Kurdistan is the main producer of wheat in the country. Wheat production in this province is similar to any other parts of the country is not safe from sunn pest, and a great amount of wheat produced is spoiled each year. This research, the temperature Characteristics is analyzed, including average, min, max temperature and daily degree-days in different development stages of sunn pest and it’s relations with sunn pest widespread has been studied.

Methodology
The case study is Bijar country ship where located in north east of Kurdistan Province. It’s area is about 7730 km2 and located in 47 deg and 36 min East longitude and 35 deg and 52 min North latitude. For doing this research, It has been used sunn pest information and climatological elements from 1370-71 to 1381-82. The sunn pest and sunn pest battle level information during this period were collected from the institute center of agriculture Kurdistan and the daily temperature data were taken Bijar Synoptic station. The frost days number were classified in 3 groups, weak frost (0 to -3), medium frost (-3.1 to -5) and hard frost (-5.1 and less). The monthly, seasonally and annually variations of sunn pest battle level were computed. The degree-day amount for 6 centigrade degree in five different times were computed. The correlation coefficient and coefficient of determination R2 were used to analyze the results statistically.

Results and Discussion
The variation coefficient of sunn pest battle level is high during past 12 years. The sunn pest battle level total were among 52 till 82389 hectares during this period. The sunn pest battle level increase when temperature increases and frost days number decreases. The very low temperatures along with hard frost are caused to kill winter diapauses periods and activity periods sunn pest at field surface. The finding research shows that the degree-days amount for 6 centigrade degree (temperature base for vital sunn pest ) is between 413.8 till 1132.7 degree-days in turn 1375-76 and 1378-79 years. The maximum degree-day amount is relevant 1378-79 year about 1132.7 and the minimum degree-day is about 413.8 degree-day for 1375-76 year. The degree-day amount has been increased from 1377-78 forward.

Conclusion
The sunn pest density is dependent to temperature situation. When temperature and degree-days are high in the spring and also the total number of yearly frost and hard frost during former autumn and winter is low, sunn pest spreads hard and vice versa, When temperature and degree-days in the spring is low and total number of yearly frost and hard frost during former autumn and winter is high, sunn pest spreads low. There is a non meaningful negative correlation between weak frost, medium frost, hard frost frequency, and total frost number in autumn and winter seasons with sunn pest combat level. The R2 amount was computed equal 0/424 for these elements.Then, the regression analysis was achieved between degree-days yearly amount and degree-days amount during activity sunn pest in field surface with sunn pest combat level. The R2 amount was computed equal 0/703 which It shows the importance of degree-day for forecasting sunn pest uprising. Finally, the regression model was given according such two parameters.