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THE EFFECT OF THE WEATHER ON THE LIGHT-TRAP’S DATA OF THE COTTON BOLLWORM IN HUNGARY

THE EFFECT OF THE WEATHER ON THE LIGHT-TRAP’S DATA OF THE COTTON BOLLWORM IN HUNGARY. Péter Balogh , József Takács, Miklós Nádasy, Lénárd Márton University of Veszprém, Georgikon Faculty of Agriculture, Department of Agricultural Entomology, Keszthely, Hungary

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THE EFFECT OF THE WEATHER ON THE LIGHT-TRAP’S DATA OF THE COTTON BOLLWORM IN HUNGARY

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  1. THE EFFECT OF THE WEATHER ON THE LIGHT-TRAP’S DATA OF THE COTTON BOLLWORM IN HUNGARY Péter Balogh, József Takács, Miklós Nádasy, Lénárd Márton University of Veszprém, Georgikon Faculty of Agriculture, Department of Agricultural Entomology, Keszthely, Hungary IV. Alps-Adria Scientific Workshop Portoroż, Slovenia

  2. Our aims: • To examine the correlation between the effective heat of the year and the number of captured individuals • To examine the correlation between the rainfall and the number of the captured moths • To examine the correlation between the number of the heat days and the number of the captured moths

  3. Methods I. • In our present study we processed the meteorological and light-trap data of the Plant Protection and Soil Conservation Services of Borsod, Csongrád, Fejér, Komárom-Esztergom and Tolna Counties • At first we had to count the effective heat of the counties for every year • We subtracted 13oC from the daily mean temperature of the counties, than we summed the positive differences separately. This amount is the effective heat of the year • In the second examination we summed the fallen precipitation between the first and last days, those daily mean temperature is higher than 13oC

  4. Methods II. • In the third examination we summed the number of the heat days in every year. Heat days are the days, those daily maximum temperature is over 30oC • We represented these data separately with the catching numbers of the light-traps on a point diagram • We fitted a trend line to the data • This line can be defined with an equation • we counted the correlation coefficient “r” and we made a comparison on P=0,05 probability level with a critical correlation coefficient “r*”

  5. Our results

  6. The correlation diagram between the effective heat of the year and the catching number The critical correlation coefficient on probability level P=0,05: r*=0,3809.

  7. Correlation diagram between the precipitation and the catching numbers The critical correlation coefficient on probability level P=0,05: r*=0,3809

  8. Correlation diagram between the heat days and the catching numbers The critical correlation coefficient on probability level P=0,001: r*=0,5974

  9. Conclusions • It can be summarised that the cotton bollworm responses to the hot and droughty weather very positively • The presence of cotton bollworm shows us very clearly, that our climate is changing, and becomes more and more hot and droughty

  10. Acknowledgement • I would like to express my thanks to Géza Gabi, Adrienne Garai, Péter Kemény, Péter Prohászka, Zsolt Tatár and Géza Vörös for their help

  11. Thank you for your attention!

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