In recent years, the East African region has seen an increase in arboviral diseases transmitted by blood-feeding arthropods. Effective surveillance to monitor and reduce incidence of these infections requires the use of appropriate vector sampling tools. Here, trapped skin volatiles on fur from sheep, a known preferred host of mosquito vectors of Rift Valley fever virus (RVFV), were used with a standard CDC light trap to improve catches of mosquito vectors. We tested the standard CDC light trap alone (L), and baited with (a) CO(2) (LC), (b) animal volatiles (LF), and (c) CO(2) plus animal volatiles (LCF) in two highly endemic areas for RVF in Kenya (Marigat and Ijara districts) from March-June and September-December 2010. The incidence rate ratios (IRR) that mosquito species chose traps baited with treatments (LCF, LC and LF) instead of the control (L) were estimated. Marigat was dominated by secondary vectors and host-seeking mosquitoes were 3-4 times more likely to enter LC and LCF traps [IRR = 3.1 and IRR = 3.8 respectively] than the L only trap. The LCF trap captured a greater number of mosquitoes than the LC trap (IRR = 1.23) although the difference was not significant. Analogous results were observed at Ijara, where species were dominated by key primary and primary RVFV vectors, with 1.6-, 6.5-, and 8.5-fold increases in trap captures recorded in LF, LC and LCF baited traps respectively, relative to the control. These catches all differed significantly from those trapped in L only. Further, there was a significant increase in trap captures in LCF compared to LC (IRR = 1.63). Mosquito species composition and trap counts differed between the RVF sites. However, within each site, catches differed in abundance only and no species preferences were noted in the different baited-traps. Identifying the attractive components present in these natural odors should lead to development of an effective odor-bait trapping system for population density-monitoring and result in improved RVF surveillance especially during the inter-epidemic period.
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http://dx.doi.org/10.1371/journal.pntd.0001879 | DOI Listing |
J Econ Entomol
January 2025
Department of Agronomy, María de Maeztu Excellence Unit DAUCO, ETSIAM, University of Cordoba, Campus de Rabanales, Building C4 Celestino Mutis, 14071 Cordoba, Spain.
This work aimed to optimize olive fruit fly (OFF) Bactrocera oleae (Rossi) (Diptera: Tephritidae) monitoring and integrated management, thereby ensuring optimal and less-costly decision-making and timely intervention. Field trials in Andalusia (Spain) were undertaken over 2 years to optimize trap model, color, size, and density for the accurate determination of pest spatial distribution and damage as a function of olive cultivar. McPhail traps and yellow sticky panels outperformed the other 4 models with respect to the number of OFF captured.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Computing Sciences, University of East Anglia (UEA), Norwich, NR4 7TJ, UK.
Monitoring animal populations is crucial for assessing the health of ecosystems. Traditional methods, which require extensive fieldwork, are increasingly being supplemented by time-lapse camera-trap imagery combined with an automatic analysis of the image data. The latter usually involves some object detector aimed at detecting relevant targets (commonly animals) in each image, followed by some postprocessing to gather activity and population data.
View Article and Find Full Text PDFMicromachines (Basel)
December 2024
Science for Life Laboratory, Department of Protein Science, Division of Nanobiotechnology, KTH Royal Institute of Technology, 171 65 Solna, Sweden.
Micro- and nanoplastics have become increasingly relevant as contaminants to be monitored due to their potential health effects and environmental impact. Nanoplastics, in particular, have been shown to be difficult to detect in drinking water, requiring new capture technologies. In this work, we applied the acoustofluidic seed particle method to capture nanoplastics in an optimized, tilted grid of silica clusters even at the high flow rate of 5 mL/min.
View Article and Find Full Text PDFInsects
December 2024
The State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
The beet armyworm (Hübner), a global pest, feeds on and affects a wide range of crops. Its long-distance migration with the East Asian monsoon frequently causes large-scale outbreaks in East and Southeast Asia. This pest mainly breeds in tropical regions in the winter season every year; however, few studies have investigated associations with its population movements in this region.
View Article and Find Full Text PDFInsects
November 2024
Commodity Protection and Quality Unit, San Joaquin Valley Agricultural Sciences Center, United States Department of Agriculture, Agriculture Research Service, Parlier, CA 93648, USA.
The navel orangeworm, , is the principal pest of pistachio and almond in California. The timing of the insecticide application is challenging because there is no model that predicts when pistachio is vulnerable to infestation. Sixteen years of pistachio flight data from Madera and Fresno counties (541,892 adults) were analyzed to determine if there was a consistent starting point each year for flights that overlap pistachio vulnerability.
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