The effect of temperature on the development of the Plutella xylostella （Linnaeus） （Lepidoptera： PluteUidae）, was evaluated at eight constant temperatures （10, 15, 20, 25, 28, 30, 32.5 and 35~C）, with relative ...The effect of temperature on the development of the Plutella xylostella （Linnaeus） （Lepidoptera： PluteUidae）, was evaluated at eight constant temperatures （10, 15, 20, 25, 28, 30, 32.5 and 35~C）, with relative humidity of 65% and a photoperiod of 14：10 （L： D） hours on two host plants, cauliflower, Brassica oleracea var. botrytis and cabbage, Brassica oleracea var. capitata. The low temperature threshold was estimated to be 7.06℃ and 7.84℃ and the thermal constant was 263.74 and 261.58 degree-days for P. xylostella on cauliflower and cabbage, respectively, using the linear model. Data were fitted to various nonlinear temperature-dependent models, and the low and high temperature thresholds, as well as the optimum temperature for development, has been estimated. Criteria of choice from the literature were used to evaluate models and to select the most suitable equation for P. xylostella development on each host plant. Conclusively, linear and Briere-2 models are recommended for the description of temperature-dependent development of P. xylostella on two host plants.展开更多
The potato tuberworm, Phthorimaea operculella （Zeller） （Lepidoptera： Gelechiidae）, is the most destructive pest of potato, Solanum tuberosum L. （Solanaceae）, in tropical and subtropical regions in both field an...The potato tuberworm, Phthorimaea operculella （Zeller） （Lepidoptera： Gelechiidae）, is the most destructive pest of potato, Solanum tuberosum L. （Solanaceae）, in tropical and subtropical regions in both field and storeroom situations. The modeling of temperature-dependent development can be useful in forecasting occurrence and population dynamics of the pests. Published developmental parameters for this pest vary greatly for many reasons. We determined temperature-dependent development ofP operculella at seven constant temperatures （16, 20, 24, 28, 32, 34 and 36℃）. Developmental period of whole immature stage （egg to the end of the pupal stage） varied from 75.5 days at 16℃ to 17 days at 32℃ The population failed to survive at 36℃. The observed data was modeled to determine mathematical functions for simulating P operculella development in each stage of development and overall. Two linear models, ordinary linear regression and the Ikemoto linear model were used to describe the relationship between temperature and de- velopment rate of the different stages ofP. operculella and estimating the thermal constant and lower temperature threshold. The lower temperature threshold （t） and thermal constant （k） of whole immature stage were estimated to be 11.6~C and 338.5 DD by Ikemoto linear model, and the estimated parameters were not substantially different with those estimated by ordinary linear models. Different models provided a better fit to the various develop- mental stages. Of the eleven nonlinear models fitted, the Beriere-1, Logan-6 and Lactin-1 model was found to be the best for modeling development rate of egg, larva and pupa of P. operculella, respectively. Phenological models based on these findings can be part of a decision-support tool to improve the efficiency of pest management programs.展开更多
文摘The effect of temperature on the development of the Plutella xylostella （Linnaeus） （Lepidoptera： PluteUidae）, was evaluated at eight constant temperatures （10, 15, 20, 25, 28, 30, 32.5 and 35~C）, with relative humidity of 65% and a photoperiod of 14：10 （L： D） hours on two host plants, cauliflower, Brassica oleracea var. botrytis and cabbage, Brassica oleracea var. capitata. The low temperature threshold was estimated to be 7.06℃ and 7.84℃ and the thermal constant was 263.74 and 261.58 degree-days for P. xylostella on cauliflower and cabbage, respectively, using the linear model. Data were fitted to various nonlinear temperature-dependent models, and the low and high temperature thresholds, as well as the optimum temperature for development, has been estimated. Criteria of choice from the literature were used to evaluate models and to select the most suitable equation for P. xylostella development on each host plant. Conclusively, linear and Briere-2 models are recommended for the description of temperature-dependent development of P. xylostella on two host plants.
文摘The potato tuberworm, Phthorimaea operculella （Zeller） （Lepidoptera： Gelechiidae）, is the most destructive pest of potato, Solanum tuberosum L. （Solanaceae）, in tropical and subtropical regions in both field and storeroom situations. The modeling of temperature-dependent development can be useful in forecasting occurrence and population dynamics of the pests. Published developmental parameters for this pest vary greatly for many reasons. We determined temperature-dependent development ofP operculella at seven constant temperatures （16, 20, 24, 28, 32, 34 and 36℃）. Developmental period of whole immature stage （egg to the end of the pupal stage） varied from 75.5 days at 16℃ to 17 days at 32℃ The population failed to survive at 36℃. The observed data was modeled to determine mathematical functions for simulating P operculella development in each stage of development and overall. Two linear models, ordinary linear regression and the Ikemoto linear model were used to describe the relationship between temperature and de- velopment rate of the different stages ofP. operculella and estimating the thermal constant and lower temperature threshold. The lower temperature threshold （t） and thermal constant （k） of whole immature stage were estimated to be 11.6~C and 338.5 DD by Ikemoto linear model, and the estimated parameters were not substantially different with those estimated by ordinary linear models. Different models provided a better fit to the various develop- mental stages. Of the eleven nonlinear models fitted, the Beriere-1, Logan-6 and Lactin-1 model was found to be the best for modeling development rate of egg, larva and pupa of P. operculella, respectively. Phenological models based on these findings can be part of a decision-support tool to improve the efficiency of pest management programs.
