Figure - available from: Experimental and Applied Acarology
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Counting grid with twelve wedges, center and 10 rings. The new ring numbers 1–6 (concentric circles in white) were used for the lateral mite distribution analysis
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Direct visual inspection and enumeration for estimating field population density of economically important arthropods, such as spider mites, provide more information than alternative methods, such as binomial sampling, but is laborious and time consuming. A brushing machine can reduce sampling time and perhaps improve accuracy. Although brushing te...
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Phytoseiidae; Neoseiulus longispinosus: Prey stage preference; Leaf disc method.
An annotated list and key to the 26 species of phytophagous false spider mites (Trombidiformes: Tenuipalpidae) known from Israel is provided. About two thirds are exotics, having invaded Israel within the last 35 years. Eight species, namely Brevipalpus californicus, B. lewisi, B. obovatus, B. phoenicis, B. yothersi, Raoiella indica, Tenuipalpus gr...
Citations
... Due to the small size of the DPM (0.2-0.5 mm), its high density, mobility, and ability to hide beneath the silken webs, it is extremely difficult to make a direct visual count in the field [30]. Therefore, indirect counting followed. ...
... Additionally, a fine camel hairbrush was gently moved on the fruit skin to ensure all mites on the infested fruits had been removed. Brushed mites were deposited on a rotating glass plate (12.5 cm diameter) after coating it with an adhesive substance consisting of 55% corn syrup, 44% glycerol, and 1% liquid detergent [30]. The glass plate was placed over a counting grid (pie grid) with 12 wedges. ...
The date palm mite (DPM), Oligonychus afrasiaticus (McGregor), is a key pest of unripe date fruits. The detection of this mite depends largely on the visual observations of the webs it produces on the green fruits. One of the most important problems of DPM control is the lack of an accurate decision-making approach for monitoring and predicting infestation on date fruits. Therefore, this study aimed to develop, evaluate, and validate prediction models for DPM infestation on fruits based on meteorological variables (temperature, relative humidity, wind speed, and solar radiation) and the physicochemical properties of date fruits (weight, firmness, moisture content, total soluble solids, total sugar, and tannin content) using two machine learning (ML) algorithms, i.e., linear regression (LR) and decision forest regression (DFR). The meteorological variables data in the study area were acquired using an IoT-based weather station. The physicochemical properties of two popular date palm cultivars, i.e., Khalas and Barhee, were analyzed at different fruit development stages. The development and performance of the LR and DFR prediction models were implemented using Microsoft Azure ML. The evaluation of the developed models indicated that the DFR was more accurate than the LR model in predicting the DPM based on the input variables, i.e., meteorological variables (R 2 = 0.842), physicochemical properties variables (R 2 = 0.895), and the combination of both meteorological and the physicochemical properties variables (R 2 = 0.921). Accordingly, the developed DFR model was deployed as a fully functional prediction web service into the Azure cloud platform and the Excel add-ins. The validation of the deployed DFR model showed that it was able to predict the DPM count on date palm fruits based on the combination of meteorological and physicochemical properties variables (R 2 = 0.918). The deployed DFR model by the web service of Azure Ml studio enhanced the prediction of the DPM count on the date fruits as a fast and easy-to-use approach. These findings demonstrated that the DFR model using Azure Ml Studio integrated into the Azure platform can be a powerful tool in integrated DPM management.
... urticae) and predatory mites. Ten leaflets were collected from each of the plots, and their contents brushed onto soapy plates using a mite brushing machine that were then counted under a microscope (Macmillan and Costello 2015). Plots were assigned as high or low T. urticae infested and an even number of SmartWater-treated and control treatments was assigned to each to ensure evenness of pre-existing spider mite densities between treatments. ...
New marking methods for studying small biocontrol agents (especially predatory mites) are needed because many current techniques are expensive, ineffective or not applicable to small organisms. The objective of this study was to determine whether SmartWater, a liquid and permanent fluorescent dye, can be used to mark Phytoseiulus persimilis for experimentation without any deleterious effects on its dispersal, behavior, reproduction, and biocontrol efficacy. Our results show that there were no significant differences in movement, inter-plant dispersal, feeding behavior, survivability, and reproduction between marked P. persimilis and control individuals sprayed with water. We also found that the SmartWater mark lasted for the duration of the mites' life, indicating strong durability over time. Marking efficacy may be reduced, due to a trade-off between batch marking efficacy and the possibility of drowning study organisms. However, we feel future research could improve liquid marking techniques that would reduce this risk. Overall, this study concludes that SmartWater could be a useful marking tool for predatory mites in both laboratory and field studies.
... Two clear sticky cards (12 × 10 cm) (Catchmaster®, Bayonne, NJ), each attached to a wire stand, were deployed within each plot at roughly 5 cm above the plant canopy. Ten strawberry leaflets were collected, brushed onto soapy plates, and observed under a dissecting microscope to determine the presence of predatory mites (Phytoseiidae) (Macmillan and Costello, 2015). All beneficial arthropods captured by pitfall traps, sticky cards, and leaflet collections were counted and morphologically identified to order, family, or if possible, to species. ...
Although growing strawberries under low tunnels is increasing in popularity across the northeastern United States, little is known of how they impact the presence of natural enemies and pollinators that provide key ecosystem services on strawberry. We employed passive (fruit collections, sticky cards and pitfall traps) and direct (direct observations, leaf brushing and fruit bagging) monitoring over 2-3 growing seasons to compare the abundance and impact of beneficial insects and mites on strawberry grown under low tunnels versus the open field. Three different low tunnel plastics ranging in UV-selectivity were included to determine any effect of UV exclusion on natural enemy and pollinator presence. Plant yield and fruit marketability was higher under low tunnels compared to the open field for two of three years observed. The abundance of predators, and to a lesser extent parasitoids, was similar or higher under low tunnels compared to the open field. However, catch on sticky cards revealed lower densities of parasitoids under tunnels. There was some evidence that UV-selecting plastics resulted in poorly pollinated fruit compared to UV-transmitting and open-field treatments. However, there was no difference in pollinator presence among treatments, so the mechanisms causing the plastic effect are unclear. Overall, we conclude that growing strawberries under low tunnels, regardless of UV selectively, can support higher and more marketable yield in some years while likely having neutral to positive impacts on beneficial predators, parasitoids and pollinators.
... The sampling methods adopted in the different habitats were: beating the branch on a blackboard and collecting specimens with micro-aspirator ; collecting leaves from the field and then placing them directly under a stereomicroscope at 30-100× of magnification for the counting of mites on the leaf surface with particular attention to the trichomes and leaf domatia (Ragusa, 1974); collecting leaves from the selected plant species and then collecting mites by using a brusher machine (Henderson and McBurnie, 1943;Macmillan and Costello, 2015) and by using a Berlese-Tullgren Funnel for litter samples; ...
... The plate was coated with vaseline oil in order to adhere mites to the glass plate. After brushing, the plate was placed on a counting grid (Macmillan and Costello 2015) and mites were counted under a stereomicroscope. The number of mites per leaf was calculated. ...
