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Fig. 3 in Susceptibility of Spodoptera frugiperda (Lepidoptera: Noctuidae) field populations to the Cry1F Bacillus thuringiensis insecticidal protein
Fig. 3. Mean percentage of mortality and mean percentage of growth inhibition responses of Spodoptera frugiperda for 2012 and 2013 field-collected populations exposed to Cry1F Bacillus thuringiensis toxin.
Fig. 1 in Susceptibility of Spodoptera frugiperda (Lepidoptera: Noctuidae) field populations to the Cry1F Bacillus thuringiensis insecticidal protein
Fig. 1. EC50s estimated by nonlinear regression of growth inhibition fitted to a probit model and the 95% confidence intervals of Spodoptera frugiperda neonates field collected in 2012 and exposed to the Cry1F Bacillus thuringiensis toxin.
Fig. 2 in Susceptibility of Spodoptera frugiperda (Lepidoptera: Noctuidae) field populations to the Cry1F Bacillus thuringiensis insecticidal protein
Fig. 2. EC50s estimated by nonlinear regression of growth inhibition fitted to a probit model and the 95% confidence intervals of Spodoptera frugiperda neonates field collected in 2013 and exposed to the Cry1F Bacillus thuringiensis toxin.
Fig. 1 in A maximum concentration bioassay to assess insecticide efficacy against hemipteran pests of tomato
Fig. 1. Mortality of third instar nymphs from 5 populations of Nezara viridula ('green'), 3 populations of Euschistus quadrator ('brown'), and 1 population of Leptoglossus phyllopus ('leaf') stink bug subjected to a maximum concentration test of 3 pyrethroid and 3 neonicotinoid insecticides and an untreated control (UTC). Percentage mortalities (+ SEM) are based on the mean of 5 nymphs per replicate with 3 replicates. Insecticides designated with the same letter in the horizontal axis are not statistically different (by Bonferroni t-test, P <0.05).
Simulation Results Data for 'Modelling new insecticide-treated bed nets for malaria-vector control: How to strategically manage resistance?'
<p>GENERAL INFORMATION</p> <p>1. Title of Dataset: Simulation Results Data for 'Modelling new insecticide-treated bed-nets for malaria-vector control: How to strategically manage resistance?'</p> <p>2. Author Information<br> A. Investigator Contact Information<br> Name: Philip G. Madgwick<br> Institution: Syngenta <br> Address: Jealott’s Hill International Research Centre, Bracknell, RG42 6EY, UK<br> Email: philip.madgwick@syngenta.com</p> <p> B. Investigator Contact Information<br> Name: Ricardo Kanitz<br> Institution: Syngenta <br> Address: Syngenta Crop Protection, Rosentalstrasse 67, CH-4058 Basel, Switzerland<br> Email: ricardo.kanitz@syngenta.com</p> <p><br> 3. Date of data collection (single date, range, approximate date): 2021-01-13 to 2021-02-01 </p> <p>4. Geographic location of data collection: UK </p> <p>5. Information about funding sources that supported the collection of the data: </p> <p>This work was conducted during a postdoctoral research position for PGM funded by the Innovative Vector Control Consortium (IVCC).</p> <p><br> SHARING/ACCESS INFORMATION</p> <p>1. Licenses/restrictions placed on the data: NA</p> <p>2. Links to publications that cite or use the data: [UPDATE]</p> <p>3. Links to other publicly accessible locations of the data: NA</p> <p>4. Links/relationships to ancillary data sets: NA</p> <p>5. Was data derived from another source? No</p> <p>6. Recommended citation for this dataset: [UPDATE]</p> <p><br> DATA & FILE OVERVIEW</p> <p>1. File List: <br> PSData_random6.csv - 10^6 random samples of each of the 17 parameters in the model, where rows are samples and columns are parameters (with column names corresponding to the parameters identified in the rows of Table 1 of the manuscript; see also DATA-SPECIFIC INFORMATION)<br> Data_random6_maxpsMixture_Fixed_mm.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A and B are used in a mixture (at rate k=1; see manuscript) as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has mitochondrial inheritance <br> Data_random6_maxpsMixture_Fixed_mn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A and B are used in a mixture (at rate k=1; see manuscript) as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has nuclear inheritance <br> Data_random6_maxpsMixture_Fixed_nn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A and B are used in a mixture (at rate k=1; see manuscript) as a fixed strategy for the entire run; the resistance allele at locus 1 has nuclear inheritance and the resistance allele at locus 2 has nuclear inheritance <br> Data_random6_Mixture_Fixed_mm.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A and B are used in a mixture (at rate k; see manuscript) as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has mitochondrial inheritance <br> Data_random6_Mixture_Fixed_mn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A and B are used in a mixture (at rate k; see manuscript) as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has nuclear inheritance <br> Data_random6_Mixture_Fixed_nn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A and B are used in a mixture (at rate k; see manuscript) as a fixed strategy for the entire run; the resistance allele at locus 1 has nuclear inheritance and the resistance allele at locus 2 has nuclear inheritance <br> Data_random6_Mosaic_Fixed_mm.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A and B are used at 50% frequency each as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has mitochondrial inheritance <br> Data_random6_Mosaic_Fixed_mn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A and B are used at 50% frequency each as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has nuclear inheritance <br> Data_random6_Mosaic_Fixed_nn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A and B are used at 50% frequency each as a fixed strategy for the entire run; the resistance allele at locus 1 has nuclear inheritance and the resistance allele at locus 2 has nuclear inheritance <br> Data_random6_Rotation_Fixed_mm.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A is used first in a rotation that switch between insecticides every 36 generations as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has mitochondrial inheritance <br> Data_random6_Rotation_Fixed_mn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A is used first in a rotation that switch between insecticides every 36 generations as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has nuclear inheritance <br> Data_random6_Rotation_Fixed_nn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A is used first in a rotation that switch between insecticides every 36 generations as a fixed strategy for the entire run; the resistance allele at locus 1 has nuclear inheritance and the resistance allele at locus 2 has nuclear inheritance <br> Data_random6_Rotation_Fixed_revmm.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide B is used first in a rotation that switch between insecticides every 36 generations as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has mitochondrial inheritance <br> Data_random6_Rotation_Fixed_revmn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide B is used first in a rotation that switch between insecticides every 36 generations as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has nuclear inheritance <br> Data_random6_Rotation_Fixed_revnn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide B is used first in a rotation that switch between insecticides every 36 generations as a fixed strategy for the entire run; the resistance allele at locus 1 has nuclear inheritance and the resistance allele at locus 2 has nuclear inheritance <br> Data_random6_SoloA_Fixed_mm.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A is used solo as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has mitochondrial inheritance <br> Data_random6_SoloA_Fixed_mn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A is used solo as a fixed strategy for the entire run; the resistance allele at locus 1 has nuclear inheritance and the resistance allele at locus 2 has mitochondrial inheritance <br> Data_random6_SoloA_Fixed_nn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide A is used solo as a fixed strategy for the entire run; the resistance allele at locus 1 has nuclear inheritance and the resistance allele at locus 2 has nuclear inheritance <br> Data_random6_SoloB_Fixed_mm.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide B is used solo as a fixed strategy for the entire run; the resistance allele at locus 1 has mitochondrial inheritance and the resistance allele at locus 2 has mitochondrial inheritance <br> Data_random6_SoloB_Fixed_mn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide B is used solo as a fixed strategy for the entire run; the resistance allele at locus 1 has nuclear inheritance and the resistance allele at locus 2 has mitochondrial inheritance <br> Data_random6_SoloB_Fixed_nn.csv - simulation dataset of 10^6 runs for each set of randomly sampled parameters; insecticide B is used solo as a fixed strategy for the entire run; the resistance allele at locus 1 has nuclear inheritance and the resistance allele at locus 2 has nuclear inheritance </p> <p>2. Relationship between files, if important: </p> <p>Files are named in accordance with the variables that describe each simulation setup, as described above. Each simulation dataset has 10^6 runs that correspond to the 10^6 random samples of each of the 17 parameters in the model in 'PSData_random6.csv'.</p> <p>3. Additional related data collected that was not included in the current data package: NA</p> <p>4. Are there multiple versions of the dataset? No</p> <p><br> METHODOLOGICAL INFORMATION</p> <p>1. Description of methods used for collection/generation of data: Data were collected using Simulator.R, which is in the vignettes of the 'detsims' R package that accompanies the manuscript. </p> <p>2. Methods for processing the data: Data were processed using Figures.R, which is in the vignettes of the 'detsims' R package that accompanies the manuscript. </p> <p>3. Instrument- or software-specific information needed to interpret the data: Analysis was conducted in R version 4.0.3 (2020-10-10), using R packages identified in Figures.R, which is in the vignettes of the 'detsims' R package that accompanies the manuscript. </p> <p>4. Standards and calibration information, if appropriate: NA</p> <p>5. Environmental/experimental conditions: NA</p> <p>6. Describe any quality-assurance procedures performed on the data: NA</p> <p>7. People involved with sample collection, processing, analysis and/or submission: NA </p> <p><br> DATA-SPECIFIC INFORMATION FOR: PSData_random6.csv</p> <p>1. Number of variables: </p> <p>17 variables with column names that have the following parameter meanings (see Table 1 in the manuscript): <br> Population Size = N = starting population size (and carrying capacity in logistic model); random sample range on log-scale: 10^2 - 10^9<br> Intrinsic Birth Rate = b = % population growth rate (in logistic model); random sample following a standard log-normal distribution with mean=0 and sd=1<br> Intrinsic Death Rate = d = % breeding mosquitoes that die into next generation; random sample range: 0 - 1<br> Female Exposure = x_[female-symbol] = % female mosquitoes that receive a dose; random sample range: 0 - 1<br> Male Exposure x_[male-symbol] = % male mosquitoes that receive a dose; random sample range: 0 - 1<br> Initial Frequency A = f_0,A = starting frequency of allele A; random sample range on log-scale: 10^-9 - 10^-2, limited to be within the range 1/N - N/100 where N is Population Size<br> Effectiveness 1 = m_1 = % dosed mosquitoes that die from insecticide 1; random sample range: 0 - 1<br> Resistance Restoration A = r_A = % return to baseline fitness with resistance allele A; random sample range: 0 - 1<br> Dominance of Resistance Restoration A = h^r_A = % resistance restoration in heterozygote with allele A; random sample range: 0 - 1<br> Resistance Cost A = c_A = % non-dosed mosquitoes that die from carrying allele A; random sample range on log-scale: 10^-3 - 10^-0.5<br> Dominance of Resistance Cost A = h^c_A = % resistance cost in heterozygote with allele A; random sample range: 0 - 1<br> Initial Frequency B = f_0,B = starting frequency of allele B; random sample range on log-scale: 10^-9 - 10^-2, limited to be within the range 1/N - N/100 where N is Population Size<br> Effectiveness 2 = m_2 = % dosed mosquitoes that die from insecticide 2; random sample range: 0 - 1<br> Resistance Restoration B = r_B = % return to baseline fitness with resistance allele B; random sample range: 0 - 1<br> Dominance of Resistance Restoration B = h^r_B = % resistance restoration in heterozygote with allele B; random sample range: 0 - 1<br> Resistance Cost B = c_B = % non-dosed mosquitoes that die from carrying allele B; random sample range on log-scale: 10^-3 - 10^-0.5<br> Dominance of Resistance Cost B = h^c_B = % resistance cost in heterozygote with allele B; random sample range: 0 - 1</p> <p>2. Number of cases/rows: </p> <p>10^6, corresponding to the number of random samples </p> <p>3. Variable List: NA </p> <p>4. Missing data codes: NA</p> <p>5. Specialized formats or other abbreviations used: NA</p> <p><br> DATA-SPECIFIC INFORMATION FOR: all other dataset files (e.g. Data_random6_maxpsMixture_Fixed_mm.csv) </p> <p>1. Number of variables: </p> <p>10 variables with column names that have the following meanings:<br> A_t_50% = the recorded number of generations that it takes for resistance allele A to reach >50% frequency; 0 means that resistance allele A never reaches >50% frequency <br> A_f_250 = the frequency of resistance allele A at the 250th generation <br> A_f_bar = the mean frequency of resistance allele A over the first 250 generations <br> B_t_50% = the recorded number of generations that it takes for resistance allele B to reach >50% frequency; 0 means that resistance allele B never reaches >50% frequency <br> B_f_250 = the frequency of resistance allele B at the 250th generation <br> B_f_bar = the mean frequency of resistance allele B over the first 250 generations <br> nf_80% = the recorded number of generations that it takes for the female population size to recover to >80% of its original size in the 0th generation; 0 means that the female population size never reaches >80% recovery; 1 means that the female population size never drops below 80% of its original size in the 1st generation<br> nf_250 = the female population size at the 250th generation<br> nf_bar = the mean female population size over the first 250 generations <br> nf_ext = the recorded number of generations that it takes for the female population size to drop below 1 (i.e. population extinction); 0 means that female population size never reaches <1</p> <p>2. Number of cases/rows: </p> <p>10^6, corresponding to the number of random samples </p> <p>3. Variable List: NA</p> <p>4. Missing data codes: all missing data is recorded as 0 </p> <p>5. Specialized formats or other abbreviations used: NA</p>
Toxicogenomic profiles of neuronal targeting insecticides in zebrafish embryos as non-target aquatic vertebrate model
<p>We have conducted semi-static exposure studies with six neuronal targeting insecticides on fertilized zebrafish (Danio rerio) eggs, similar to the OECD 236 guideline for the 96h zebrafish embryo toxicity test. The aim of these transcriptomic profiling experiments was to screen for ecotoxicogenomic fingerprints in zebrafish (Danio rerio) embryos as aquatic vertebrate non-target model exposed to sub lethal concentrations of pesticides. Data published in <a href="https://doi.org/10.1016/j.chemosphere.2021.132746">Reinwald et al. 2021</a> (PMID:<strong>34748799</strong>).</p> <p>For experimental details please refer to the publicly accessible experiment description and treatment protocols deposited in the <a href="https://www.ebi.ac.uk/arrayexpress/">ArrayExpress database </a>at EMBL-EBI (www.ebi.ac.uk/arrayexpress) under the following accession numbers: <a href="https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-9852/">E-MTAB-9852</a> (Abamectin), <a href="https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-9855/">E-MTAB-9855 </a>(Carbaryl),<a href="https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-9853/"> E-MTAB-9853</a> (Chlorpyrifos), <a href="https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-9854/">E-MTAB-9854</a> (Fipronil), <a href="https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-9859/">E-MTAB-9859</a> (Imidacloprid), <a href="https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-9860/">E-MTAB-9860</a> (Methoxychlor).</p> <p>The uploaded data archives (<a href="https://www.7-zip.org/">7-zip</a> compressed) consists of three major data types:<br> 1. MultiQC reports from raw RNA-Seq read processing and QC (50bp SR) ( <a href="https://zenodo.org/api/files/5c06b1b3-0d96-4ab8-8925-a7419f0a379d/Neuotox_multiQCreports.7z">Neuotox_multiQCreports.7z </a>)<br> 2. Result tables of differential gene expression analysis (DGEA) with DESEq2 ( <a href="https://zenodo.org/api/files/5c06b1b3-0d96-4ab8-8925-a7419f0a379d/Neurotox_DESeq2_ResultTables.7z">Neurotox_DESeq2_ResultTables.7z </a>)<br> 3. Result tables of gene set enrichment analysis (GSEA) with clusterProfiler ( <a href="https://zenodo.org/api/files/5c06b1b3-0d96-4ab8-8925-a7419f0a379d/Neurotox_clusterProfiler_ResultTables.7z">Neurotox_clusterProfiler_ResultTables.7z </a>)<br> 4. Result tables of overrepresentation analysis (ORA) via <em>clusterProfiler::compareCluster() </em>( <a href="https://zenodo.org/api/files/c3fb14b4-6a90-4b12-a2be-ed5661d19683/Neurotox_clusterProfiler_ORA_on_core_DEGs.7z?versionId=2156d2be-b815-4157-b0f9-3eeed117b812">Neurotox_clusterProfiler_ORA_on_core_DEGs.7z </a>)</p> <p>Each data archive contains a README file describing the methods applied to generate the respective result tables / reports. For each tested substance and exposure condition a DGEA and GSEA result table is uploaded. The corresponding bash and R codes for each analysis step are available on github under:<br> <a href="https://github.com/hreinwal/zfeNeurotox">https://github.com/hreinwal/zfeNeurotox</a></p> <p>Gene count normalization and DGEA was conducted with DESeq2 (<a href="https://genomebiology.biomedcentral.com/articles/10.1186/s13059-014-0550-8">Love et al., 2014</a>, DOI 10.1186/s13059-014-0550-8). Three biological replicates per condition, exposure treatments were compared with respect to the control group in a pairwise fashion, applying Wald’s t-test. P values were corrected for multiple testing with independent hypothesis weighting (IHW) (<a href="https://www.nature.com/articles/nmeth.3885">Ignatiadis et al., 2016</a>, DOI 10.1038/nmeth.3885) after Benjamini-Hochberg (BH). To improve the signal to statistical noise ratio, the obtained log<sub>2</sub>-fold change (lfc) values were shrunk with the apeglm method described by Zhu and colleagues (<a href="https://academic.oup.com/bioinformatics/article/35/12/2084/5159452?login=true">2019</a>, DOI 10.1093/bioinformatics/bty895) before DGEA result tables were subjected to GSEA via clusterProfiler (<a href="https://www.liebertpub.com/doi/10.1089/omi.2011.0118">Yu et al., 2012</a>, DOI 10.1089/omi.2011.0118)<br> and reactomePA (<a href="https://pubs.rsc.org/en/content/articlehtml/2015/mb/c5mb00663e">Yu and He, 2016</a>, DOI 10.1039/C5MB00663E). The linked ArrayExpress accession numbers above, provide access to the raw and DESeq2 normalized gene count matrices upon which these analysis were performed. Genes were annotated through the biomaRt package (<a href="https://www.nature.com/articles/nprot.2009.97.pdf?origin=ppub">Durinck et al., 2009</a>, DOI 10.1038/nprot.2009.97) in R (<a href="https://www.r-project.org/">R Core Team 2021</a>).</p>
Insecticide resistance triggers a reduction of virulence to host-plant defenses in the brown planthopper
<p>This dataset contains R scripts to analyze the virulence of resistance rice cultivars and to draw figures. Data contains the LD<sub>50</sub> values of imidacloprid, virulence test and figure data. This study was supported by grants-in-aid from Japan's National Agriculture and Food Research Organization (NARO) project 315 and the NARO Innovation Project 2017 for the NARO.</p>
Dataset and RScript - Effect of insecticide on termite alarm behavior
<p>Dataset and RScript of the MS "How to perceive the insecticide? The Neotropical termite <em>Nasutitermes corniger</em> (Termitidae: Nasutitermitinae) triggers alert behavior after exposure to imidacloprid".</p>
Figure 1 in Formicidae fauna in pig carcasses contaminated by insecticide: implications for forensic entomology
Figure 1 Median (square), quartile range (box) and total range (vertical line) of the species richness in each stage of decomposition in non-contaminated carcasses (A) and in contaminated carcasses (B). Different lowercase letters (a, b, c) indicate significant differences between stages in each treatment (p <0.05). The stages are 1= Fresh; 2= bloated; 3= deterioration; 4= post-deterioration; 5= skeletonization.
Figure 2 in Formicidae fauna in pig carcasses contaminated by insecticide: implications for forensic entomology
Figure 2 Detrended Correspondence Analysis (DCA) using species occurrence to assess the change in the composition of ant species that occurs in both types of carcasses. The numbers correspond to the species appear in Table 1. On the right are those that occur more effectively in noncontaminated carcasses, and on the left are those that occurred in contaminated carcasses.
Figure 3 in Formicidae fauna in pig carcasses contaminated by insecticide: implications for forensic entomology
Figure 3 Nonmetric multidimensional scaling analysis (nMDS), using species occurrence to assess the change in the composition of ant species that act on different types of carcasses, along the different stages of decomposition. The numbers correspond to the species appear in Table 1. On the right are those that occur in contaminated carcasses, and on the left are those that occurred more effectively in non-contaminated carcasses. Noncont. = Non-contaminated and Cont. = Contaminated, I= Fresh; II= bloated; III= deterioration; IV= post-deterioration; V= skeletonization.
Figure 5 in Trapping Pestiferous Fruit Flies (Diptera: Tephritidae): Additional Studies on the Performance of Solid Bactrocera Male Lures and Separate Insecticidal Strips Relative to Standard Liquid Lures
Figure 5. Captures of Bactrocera cucurbitae males in traps baited with toxicants of variable age. Data for DDVP strips weathered in Arizona and Florida are given in top and bottom plots, respectively. While toxicant age varied among treatments, the lure was fresh (no weathering) in all treatments. All traps were baited with fresh liquid CL, except the Fresh DDVP treatment which employed a fresh CL plug. Height of bar represents mean number of males captured per trap (n = 15 traps per treatment) in a 24-h period; error bars are + 1 SE. No significant variation existed among treatments for either Arizona (F = 2.5, P = 0.07) or Florida (F = 0.5, P = 0.66). Bars sharing a letter did not differ significantly (P> 0.05).
Figure 1 in Trapping Pestiferous Fruit Flies (Diptera: Tephritidae): Additional Studies on the Performance of Solid Bactrocera Male Lures and Separate Insecticidal Strips Relative to Standard Liquid Lures
Figure 1. (A) CL plug contained in two face-to-face perforated baskets along with Plato strip (red object). (B) ME wafer with plastic basket holding DDVP strip affixed. Photos show the lures and DDVP strips only, and when deployed in the field, these were housed in Jackson traps.
Figure 3 in Trapping Pestiferous Fruit Flies (Diptera: Tephritidae): Additional Studies on the Performance of Solid Bactrocera Male Lures and Separate Insecticidal Strips Relative to Standard Liquid Lures
Figure 3. Captures of Bactrocera dorsalis males in traps baited with toxicants of variable age. Data for DDVP strips weathered in Arizona and Florida are given in top and bottom plots, respectively. While toxicant age varied among treatments, the lure was fresh (no weathering) in all treatments. All traps were baited with fresh liquid ME, except the Fresh DDVP treatment which employed a fresh ME wafer. Height of bar represents mean number of males captured per trap (n = 15 traps per treatment) in a 24-h period; error bars are + 1 SE. Significant variation existed among treatments for Arizona (F = 3.7, P = 0.02) but not for Florida (H = 1.8, P = 0.61); bars sharing a letter did not differ significantly (P> 0.05).
Figure 2 in Trapping Pestiferous Fruit Flies (Diptera: Tephritidae): Additional Studies on the Performance of Solid Bactrocera Male Lures and Separate Insecticidal Strips Relative to Standard Liquid Lures
Figure 2. Captures of Bactrocera dorsalis males in traps baited with ME lures of variable age. Data for wafers weathered in Arizona and Florida are given in top and bottom plots, respectively. While lure age varied among treatments, the toxicant was fresh (no weathering) in all treatments. Liquid was applied to a cotton wick; in all other cases ME was presented in a polymeric wafer. Height of bar represents mean number of males captured per trap (n = 15 traps per treatment) in a 24-h period; error bars are + 1 SE. Significant variation existed among treatments for both Arizona (F = 10.5, P <0.001) and Florida (F = 11.0, P <0.001); bars sharing a letter did not differ significantly (P> 0.05).
Figure 4 in Trapping Pestiferous Fruit Flies (Diptera: Tephritidae): Additional Studies on the Performance of Solid Bactrocera Male Lures and Separate Insecticidal Strips Relative to Standard Liquid Lures
Figure 4. Captures of Bactrocera cucurbitae males in traps baited with CL lures of variable age. Data for CL plugs weathered in Arizona and Florida are given in top and bottom plots, respectively. While lure age varied among treatments, the toxicant was fresh (no weathering) in all treatments. Liquid was applied to a cotton wick; in all other cases CL was presented in a polymeric plug. Height of bar represents mean number of males captured per trap (n = 15 traps per treatment) in a 24-h period; error bars are + 1 SE. No significant variation existed among treatments for either Arizona (F = 0.5, P = 0.65) or Florida (F = 1.9, P = 0.15). Bars sharing a letter did not differ significantly (P> 0.05).
FIGURE 3 in Physiological selectivity of insecticides to eggs and larvae of predator Chrysoperla externa (HAGEN) (Neuroptera: Chrysopidae)
FIGURE 3 - Survival (%) (± SE) of immature stages of Chrysoperla externa from second instar larvae treated with the pesticides. Treatments: 1: chlorpyrifos; 2: cartap hydrochloride; 3: pyriproxyfen, 4: profenofos/lufenuron; 5: fenpropathrin; 6: triazophos/deltamethrin; 7: zetacypermethrin and 8: control.
FIGURE 4 in Physiological selectivity of insecticides to eggs and larvae of predator Chrysoperla externa (HAGEN) (Neuroptera: Chrysopidae)
FIGURE 4 - Duration (days) of immature stages of Chrysoperla externa from second instar larvae treated with the insecticides. Treatments: 1: chlorpyrifos; 2: cartap hydrochloride; 3: pyriproxyfen, 4: profenofos/lufenuron; 5: fenpropathrin; 6: triazophos/deltamethrin; 7: zetacypermethrin and 8: control.
FIGURE 1 in Physiological selectivity of insecticides to eggs and larvae of predator Chrysoperla externa (HAGEN) (Neuroptera: Chrysopidae)
FIGURE 1 - Survival of three larval instars and viability pupal (%) (± SE) stage of Chrysoperla externa, from first instar larvae treated with the insecticides. Treatments: 1: chlorpyrifos; 2: cartap hydrochloride; 3: pyriproxyfen, 4: profenofos/lufenuron; 5: fenpropathrin; 6: deltamethrin/triazophos; 7: zetacypermethrin and 8: control.
Thesis: Transcriptome analysis of insecticide resistant Drosophila suzukii
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