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蜡蚧轮枝菌对烟粉虱的时间-剂量-死亡率模型研究
引用本文:王联德,黄建,林谷园,梁智生.蜡蚧轮枝菌对烟粉虱的时间-剂量-死亡率模型研究[J].福建农林大学学报(自然科学版),2003,32(2):167-171.
作者姓名:王联德  黄建  林谷园  梁智生
作者单位:福建农林大学植物保护学院,福建,福州,350002
基金项目:国家自然科学基金资助项目(39970511、30270904).
摘    要:以叶片浸液接种法测定了烟粉虱对蜡蚧轮枝菌菌株(Vp28和Vl6063)的感染反应.运用时间、剂量、死亡率模型对死亡率随时间和剂量的变化作了拟合.接种后4-8d,Vl6063的LC50分别为3.98×108,3.55×107、6.31×106、1.17×106、6.03×105孢子·mL-1;Vp28的LC50分别为6.61×106,1.95×106、1.10×106、7.76×105和6.03×105孢子·L-1.2个菌株的LT50值为105-106孢子·mL-1(约为5.5-10.0d).在小于105孢子·mL-1的剂量下,Vp28的LT50值大于Vl6063;在大于106孢子·mL-1剂量下,Vl6063的LT50值则大于Vp28、Vp28的.

关 键 词:蜡蚧轮枝菌  烟粉虱  生物测定  时间-剂量-死亡率模型
文章编号:1006-7817(2003)02-0167-05
修稿时间:2002年9月30日

The time-dose-mortality model of two Verticillium lecanii isolates on sweetpotato whitefly,Bemisia tabaci
Abstract:Bioassays of 2 isolates (Vp28, Vl6063) of Verticillium lecanii (Zimm.) were conducted on Bemisia tabaci. For inoculation, batches of 3rd instar whitefly nymphs on sweet potato seedlings were immersed in conidial suspensions at the content of 103-107 conidia·mL-1. The nymphs were maintained at 25 ℃, under 90% RH, photo phase of 16∶8 (L∶D) and observed daily for mortality. The resulting time dose mortality data fitted well to a conditional mortality probability model based on the Hosmer Lemeshow test, resulting in a cumulative mortality probability model. The parameters from the latter model were used to estimate the lethal concentration (LC50) and time (LT50) for two isolates against Bemisia tabaci. The LC50 values for Vl6063 were 3.98×108,3.55×107,6.31×106,1.17×106,6.03×105 conidia·mL-1 on 4-8 d after inoculation, and the values for Vp28 were 6.61×106,1.95×106,1.10×106,7.76×105,6.03×105 conidia·mL-1 on 4-8 d after inoculation, respectively. The estimates of LT50 values were similar at the dosage of 105-106 conidia·mL-1 for two isolates. The results indicated that isolate Vl6063 from Canada was also a promising microbial agent as isolate Vp28 for whiteflies in Fuzhou, China.
Keywords:Verticillium lecanii  Bemisia tabaci  bioassay  time-dose-mortality model
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