Analysis and modeling of time-dose-mortality of Melanoplus sanguinipes, Locusta migratoria migratorioides, and Schistocerca gregaria (Orthoptera: Acrididae) from Beauveria, Metarhizium, and Paecilomyces isolates from Madagascar
Analysis and modeling of time-dose-mortality of Melanoplus sanguinipes, Locusta migratoria migratorioides, and Schistocerca gregaria (Orthoptera: Acrididae) from Beauveria, Metarhizium, and Paecilomyces isolates from Madagascar
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DOI：
10.1006/jipa.1996.0039
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发表时间：
1996-05-01
影响因子：
3.4
通讯作者：
Swearingen, W
中科院分区：
文献类型：
--
作者：
Nowierski, RM;Zeng, Z;Swearingen, W
一个互补的对数-对数（CLL）模型被用来模拟时间-剂量-死亡率的关系，从生物测定测试的26个真菌分离物，主要来自马达加斯加，非洲，对三个蝗种，在这里都被称为“蚱蜢”。病原真菌包括球孢白僵菌15个，黄病毒绿僵菌9个，拟青霉2个。测试的蝗虫物种包括Melanoplus sanguinipes、Locusta migratoria migratorioides和Schistocerca gregaria。使用比例偏差、平均偏差、Pearson X（2）统计量、Hosmer-Lemeshow（H-L）C统计量和三维时间-剂量-死亡率图评估二项外变异、作为潜在离群值的数据点、比例偏差统计量和Pearson X（2）统计量与卡方（2）分布的一致性以及CLL模型的拟合。H-LC统计量也被发现是有用的，在显示CLL模型的拟合优度的真菌分离株建模的额外二项式变异之前。在使用威廉姆斯方法对超二项变异进行建模后，最大似然估计的斜率、修正的log（LD（50））估计值（使用CLL模型校正背景死亡率），log（LD（50））值随时间的动态排序，以及时间，剂量，和死亡率来评估真菌分离物的有效性。通常，CLL模型提供了在生物测定测试中具有大量重复试验的真菌分离株的相当差的拟合（即，大样本量）。CLL模型提供了一个极好的拟合的时间-剂量-死亡率的关系，这些分离株后，额外的二项式变异建模，并纳入CLL模型。结果表明，MFV和SP 5是对绿僵菌最强的毒力菌株。其次是绿僵菌分离株：SP 8、SP 7、SP 9、SP 6和SP1，以及白僵菌分离株S33 B。绿僵菌SP3、SP 5、SP 6、SP 9和白僵菌SP11、SP12、SP13、SP16对L.在所测试的时间段内，比所检查的其它病原体分离物更长时间内，绿僵菌SP 9和SP 5对S. gregaria。绿僵菌菌株对蝗虫的毒力高于白僵菌菌株，白僵菌菌株对蝗虫的毒力高于拟青霉菌株。CLL模型被认为是非常有用的描述蝗虫死亡率作为时间和剂量的函数。这种方法与模型和真菌分离物评估统计相结合，将有助于确定哪些病原体分离物在未来控制蝗虫和其他害虫的潜力最大。(C)出版社：Academic Press，Inc.
A complementary log-log (CLL) model was used to model time-dose-mortality relationships from bioassay tests of 26 fungal isolates mostly from Madagascar, Africa, against three acridid species, all referred to here as ''grasshoppers.'' The fungal pathogens included 15 isolates of Beauveria bassiana, 9 isolates of Metarhizium flavoviridae, and 2 isolates of Paecilomyces spp. Grasshopper species tested included Melanoplus sanguinipes, Locusta migratoria migratorioides, and Schistocerca gregaria. The scaled deviance, mean deviance, Pearson X(2) statistic, Hosmer-Lemeshow (H-L) C statistic, and three-dimensional time-dose-mortality graphs were used to assess extra-binomial variation, data points that were potential outliers, conformance of the scaled deviance statistic and Pearson's X(2) statistic to a chi(2) distribution, and the fit of the CLL model. The H-L C statistic also was found to be useful in showing the goodness of fit of the CLL model for the fungal isolates prior to modeling the extra-binomial variation. After the extra-binomial variation was modeled using Williams' method, the slope from maximum likelihood estimation, modified log(LD(50)) estimates (which were corrected for background mortality using the CLL model), a dynamic ranking of the log(LD(50)) values over time, and a three-dimensional plot of time, dose, and mortality of the three grasshopper species were used to evaluate the effectiveness of the fungal isolates. In general, the CLL model provided a rather poor fit of the fungal isolates which had a large number of replicate trials in the bioassay tests (i.e., a large sample size) due to extra-binomial variation. The CLL model provided an excellent fit of the time-dose-mortality relationships of such isolates after the extra-binomial variation was modeled and included in the CLL model. Metarhizium isolates MFV and SP5 were found to be the most virulent isolates tested against M. sanguinipes, followed by Metarhizium isolates: SP8, SP7, SP9, SP6, and SP1, and Beauveria isolate S33B. Metarhizium isolates SP3, SP5, SP6, and SP9, and Beauveria isolates SP11, SP12, SP13, and SP16 showed higher levels of virulence against L. migratoria migratorioides over more of the time periods tested than the other pathogen isolates examined. Metarhizium isolates SP9 and SP5 were the most effective isolates tested against S. gregaria. In general, the Metarhizium isolates were more virulent against the grasshoppers than the Beauveria isolates, which were more virulent than the Paecilomyces isolates. The CLL model was found to be very useful in describing grasshopper mortality as a function of time and dose. This approach combined with model and fungal isolate assessment statistics will be helpful for determining which pathogen isolates have the greatest potential for controlling grasshoppers and other pests in the future. (C) 1996 Academic Press, Inc.