PREDICTION OF SYNANTHEDON MYOPAEFORMISBORKH. MOTHS ACTIVITY BASED ON PHEROMONE TRAPPING AND DEGREE-DAY ACCUMULATIONS OF TEMPERATURE IN APPLE ORCHARDS IN EGYPT | ||||
Egyptian Journal of Agricultural Research | ||||
Article 10, Volume 85, Issue 4, December 2007, Page 1239-1251 PDF (3.12 MB) | ||||
Document Type: Original Article | ||||
DOI: 10.21608/ejar.2007.227897 | ||||
View on SCiNiTO | ||||
Authors | ||||
ANTWAN W. TADROS1; REFAT GH. ABOU EL-ELA2; MAHMOUD M. ABD EL-AZIMI1 | ||||
1Plant Protection Research Institute, Agricultural Research Center, Dokki, Giza, Egypt | ||||
2Faculty of Science, Cairo University, Giza, Egypt | ||||
Abstract | ||||
In Egypt, the clearwing moth S. myopaeformis (Lepidoptera: Aegeriidae) is a serious pest on apple trees. The relationship between weather factors (of temperature and relative humidity) and the population fluctuation was quantitatively calculated during six successive years (from 1997 to 2002 separately, and 1997-2002 together) in apple orchards at Qalubia governorate. Trials were conducted to determine the correlations between the main weather factors and moths activity as well as using the day-degree method for predicting the peak emergence period of adult moths, i.e. to asses prediction formula through which population fluctuation could be expected. R-square values of each single weather factor indicated that daily maximum (Xl) and minimum temperature (X2) significantly affected S. myopaefomils population fluctuation, showing 0.461-0.958 for (X1) and 0.607-0.904 for (X2) and were included in . selection of suitable statistical models used. Statistical combined models ((X1X2), (X1X12), (X2)22), (X1X22), (X12X2), (X12)(22) and (X1X2X12X22)} were used In assessing the prediction formula. The effective weather factor was the daily maximum temperature (Xl) rather than minimum temperature (X2). Prediction calculations were based on the linear regression formula described by Bishop (1969) <r = a + 01X1 + b2X2 bjXj}. Results indicated that the degrees of correlation between the predicted and observed data varied between very close correlation in 2000, close correlation in 2001 and 2002, moderate correlation in 1997/2002 together and very poor correlation in 1999. Other factors such as the nutrition of trees, horticultural practices that may accelerate or delay the tree activity played an important role in predicting the population activity. According to graphs and statistical analysis ()(2 test) which magnified the differences between the observed and predicted population it could not relay on temperature and relative humidity only to predict the copulation activity of S. mvoceeionnis in the followina seasons. | ||||
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