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Title اثرات دما بر رشد و نمو مراحل نابالغ کنه Rhyncophytoptus ficifoliae (Acari: Diptilomiopidae)
Type of Research Presentation
Keywords Fig leaf mite, Developmental time, Temperature, SSI model, Fig
Abstract Rhyncaphytoptus ficifoliae Keifer (Trombidiformes; Diptilomiopidae) is the main pest of fig trees in south and southwestern regions of Iran. The effects of temperature on developmental time of R. ficifoliae were measured at constant temperatures of 17, 20, 25, 30, 33 and 36 °C, with the relative humidity of 65 ± 5% and a photoperiod of 16: 8 (L: D) h on fig leaves under laboratory conditions. According to results, R. ficifoliae successfully developed to adult stage at six tested temperatures fed on fig leaves. The total developmental time (from egg to adult emergence) at above mentioned temperatures was 21.62 ± 0.2, 15.02 ± 0.19, 10.05 ± 0.11, 7.77 ± 0.08, 6.02 ± 0.10 and 6.47 ± 0.16 days for females and 19.13 ± 0.17, 13.26 ± 0.18, 9.270.13, 6.91 ± 0.18, 5.65 ± 0.09 and 5.83 ± 0.19 days for males. The total developmental rate of females increased as temperature increased from 17 to 33 °C, and then decreased at 36 ºC. Two linear and one nonlinear models were fitted to developmental rate of immature stages to predict the developmental rate as a function of temperature, as well as to estimate the thermal constant (k) and critical temperatures. Using the ordinary and Ikemoto and Takai (2000) linear models the estimated lower temperature thresholds (Tmin) for total developmental time of females were 10.78 and 10.37 °C and the constant temperatures (k) were 140.25 and 144.78 degree-days (DD), respectively. Also the estimated low temperature at which an enzyme is half active (TL), intrinsic optimum temperature (TФ) and high temperature at which an enzyme is half active (Th) for total immature stages of females by SSI model were 11.11, 23.72 and 37.98 °C, respectively. The highest (100%) and lowest values (51.67%) of survival rate for immature stages were found at 25 and 36 °C, respectively. The presented information here could be used to predict the population dynamics of this pest for an effective management.
Researchers Shahryar Jafari (First Researcher)، Fereshteh Bahirai (Second Researcher)، Parisa Lotfollahi (Third Researcher)، Jahanshir Shakarami (Fourth Researcher)