Fourth International Bemisia Workshop International Whitefly Genomics Workshop
Cotton Whitefly, Bemisia tabaci (Genn.) Degree-Hour Model for Predicting Phenological Development
1 Entolomology Department, Agricultural Research Center, Iranian Research Organization for Science and Technology, Tehran, Iran. Correspondence: tafaghodi@irost.org
2 Entomology Department, Faculty of Agriculture, Tehran University, Karaj, Iran
As part of a pest management analysis and planning program we developed a degree-day based computer simulation model to forecast development periods of immature stages of Bemisia tabaci in cotton fields of Tehran state. B. tabaci has been reported from all continents except Antarctica. Over 900 host plants have been recorded for B. tabaci and it reportedly transmits 111 virus species. This insect has been difficult to control because of its resistance to many pesticides, its ability to attack many different plants, its high rate of population growth, and its readiness to disperse from field to field. Because of these characteristics the adequate management of this pest may require an ability to forecast population growth. In this situation, simulation models can be useful because they allow the prediction of B. tabaci abundance over a period of time. Our model was designed to imitate the dynamics of the real B. tabaci system so as to help in choosing the best time and strategy for management from amongst the whole range of possibilities. Parameter values were obtained from the literature or calculated from cotton field data. All simulations were performed on an IBM compatible computer, using the Stella Ver 7.0 program. Based on these data we developed a phenological model for B. tabaci that uses temperature to predict development times of immatures. The inputs to the model are maximum and minimum temperature and latitude of the local area; the outputs are growth and dynamics of population of all stages during night and day. The model has three parts. In the first part, length of day is calculated based on the day number (1 is for first of January) and local latitude. We considered three different periods during a night and day to calculate temperature oscillations. Lower and upper developmental thresholds for eggs to pupa were estimated using linear regression (Lower=10C° and Upper=.32 C°). Length of day and maximum and minimum daily temperature were used to calculate the hourly changes in temperature during the day. Finally the effective degree-hour was calculated using hourly temperature data. In the second part, the output of the first part (effective degree-hour) was used to calculate the transit time of all stages. The degree-hours to complete all stages from egg to pupa are: 1189, 1271, 922, 893, 1084, 2235 C°, respectively. In the third part, we will have the population oscillation of all stages. To verify the model predictions we checked the output by constant transit time. This model simulated phenological patterns that agreed with field records. Thus, the model may be useful for predicting the density and phenology of B. tabaci.