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
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
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
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*”
Our results
The correlation diagram between the effective heat of
the year and the catching number
Catching number (piece)
Correlation between the effective heat of the year and the catching number
2000
Data
1800
1600
Expon. (Data)
1400
y = 0,0344e0,0061x
1200
R2 = 0,2773
1000
r=0,5266
800
600
400
200
0
900
1000
1100
1200
1300
1400
Effective heat of the year (dayoC)
1500
The critical correlation coefficient on probability level P=0,05: r*=0,3809.
1600
Correlation diagram between the precipitation and the
catching numbers
Catching number (piece)
Correlation between the precipitation and the catching number
2000
1800
Data
1600
1400
Expon. (Data)
y = 509,9e-0,0063x
R2 = 0,3
r=0,5477
1200
1000
800
600
400
200
0
50
100
150
200
250
300
350
Precipitation (mm)
400
450
500
550
The critical correlation coefficient on probability level P=0,05: r*=0,3809
600
Correlation diagram between the heat days and the
catching numbers
Catching number (piece)
Correlation between the heatdays and the catching number
2000
Data
1800
1600
Expon. (Data)
1400
y = 3,6363e0,0606x
1200
R2 = 0,4717
1000
r=0,6868
800
600
400
200
0
0
20
40
Heatdays (day)
60
80
The critical correlation coefficient on probability level P=0,001: r*=0,5974
100
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
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
Thank you for your attention!