A method of computing the effectiveness of an insecticide
TL;DR: In order to make experimental studies comparable and statistically meaningful, the article recommends the following formula: per cent control = 100(X - Y)/X, which eliminates errors due to deaths in the control sample which were not due to the insecticide.
Abstract: There are several statistical methods used in biology (entomology) for computing the effectiveness of an insecticide, based on relating the number of dead insects in the treated plat to the number of live ones in the untreated plat. In order to make experimental studies comparable and statistically meaningful, the article recommends the following formula: per cent control = 100(X - Y)/X, where X = % living in the untreated check sample and Y = % living in the treated sample. Calculation using this method eliminates errors due to deaths in the control sample which were not due to the insecticide. An example based on treatments of San Jose scale includes computation of probable errors for X and Y, and the significance of the difference between the two counts. Common biometric convention holds that when the difference between the results of two experiments is greater than three times its probable error, the results are significant and due to the treatment applied.
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TL;DR: Resistance monitoring for Bemisia tabaci field populations to the juvenile hormone mimic, pyriproxyfen, was conducted from 1996 to 2003 in commercial cotton fields in two areas of Israel and resulted in continued pyri proxyfen resistance, predominantly of Q biotype.
Abstract: Resistance monitoring for Bemisia tabaci field populations to the juvenile hormone mimic, pyriproxyfen, was conducted from 1996 to 2003 in commercial cotton fields in two areas of Israel: the Ayalon Valley (central Israel) and the Carmel Coast (northwestern Israel). Although the use of pyriproxyfen ceased in these areas in 1996-1997 (because of the resistance), resistance levels to pyriproxyfen declined to some extent in the fields but remained quite stable, and the susceptibility has not been totally restored. Two strains of B. tabaci collected from the Ayalon Valley in the late 1999 and 2002 cotton seasons (AV99L, AV02L) were assayed for their susceptibility to pyriproxyfen at F1, and subsequently a line of each strain was kept under controlled conditions without exposure to insecticides. After maintenance of more than 20 generations under laboratory conditions, the resistance to pyriproxyfen in the untreated strains substantially declined. This decline was concurrent with a replacement of Q biotype by B-type under non-insecticidal regimes; apparently B biotype was more competitive than the pyriproxyfen-resistant Q-type. Selection under controlled conditions with neonicotinoids on these B. tabaci strains resulted in continued pyriproxyfen resistance, predominantly of Q biotype. Based on our data, applications of either pyriproxyfen or neonicotinoids may select for biotype Q, which would survive to a greater degree where these insecticides are applied.
409 citations
TL;DR: In this article, it was shown that thiamethoxam is likely a neonicotinoid precursor for clothianidin, an open-chain nAChR inhibitor.
406 citations
TL;DR: It is concluded that entomopathogenic nematode species have well-defined thermal niches which may be unaffected by their locality, and that heterorhabditids are endemic to warmer climates.
393 citations
TL;DR: The results showed that the pesticides greatly differed in their toxicity, both in terms of lethal and sub lethal effects, as well as in their persistence, and abamectin was the most noxious and persistent, and was classified as harmful up to 14 d after the treatment.
384 citations
Cites methods from "A method of computing the effective..."
...…coefficient Ex for pesticide x (Urbaneja et al., 2008) using the formula: Ex ¼ 100 1 1 Emx 100 1 Efx 100 where Emx is the corrected mortality (Abbott, 1925) and Efx is the corrected Predator reproductive capacity estimated using the formula: Efx ¼ 100 Fx100 Fc where Fx is the mean Predator…...
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TL;DR: Standardisation of some of the methods to study the bioactivity of essential oils and their constituents is desirable to permit more comprehensive evaluation of plant oils, and greater comparability of the results obtained by different investigators.
Abstract: Many essential oils are extracted, analysed and their main components are identified, characterised and then published without any biological testing whatsoever. Their useful biological activities can remain unknown for years. Yet, the search for these activities often increases our knowledge of the potential use of oils in therapeutics. Therefore, there is a real need for a simple, reliable and reproducible methods to study the bioactivity of essential oils and their constituents which can detect a broad spectrum of action or specific pharmacological activities in aromatic plants. These methods can then be employed by natural product chemists, pharmacologists and biologists to conduct their scientific research and to valorize natural products. Standardisation of some of these methods is therefore desirable to permit more comprehensive evaluation of plant oils, and greater comparability of the results obtained by different investigators.
378 citations