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Corn wireworm, Melanotus communis Gyllenhal (Coleoptera: Elateridae), is an economically important larval pest of root and tuber crops in the United States. Previous work to estimate field-level abundance of M. communis has focused on grain-based larval baits placed in soil. However, this sampling method is labor intensive and may not estimate population size accurately. Recent discovery of the M. communis sex pheromone, 13-tetradecenyl acetate, provides a new method to monitor this pest during the adult stage. Early studies with this pheromone showed that different trapping methods might enhance catch and improve trap servicing. We hypothesized that placing lures on elevated traps would increase M. communis capture relative to the in-ground pitfall trapping that is currently used. We had 2 objectives for this study: (a) to compare pheromone captures among in-ground pitfall traps, on-ground pitfalls, elevated pitfalls (1 m), or elevated sticky cards (1 m) and (b) test lure longevity by aging the lures outdoors at 8-, 6-, 4-, 2-, and 0-wk intervals prior to trap deployment in the field. Experiments were conducted in North Carolina, Virginia, South Carolina, and Florida during the 2021 and 2022 field seasons. Results highlight large variation in M. communis abundance across the 4 states. We showed that 1 m elevated pheromone traps caught the most beetles. The age of the lure prior to deployment had a significant effect on trap catch. The lures that were aged for fewer weeks attracted significantly more beetles, with 0- and 2-wk-old lures capturing the greatest numbers. Graphical Abstract

Onion thrips, Thrips tabaci Lindeman, is a global pest of onion crops, causing substantial economic damage by diminishing bulb yields and transmitting plant pathogens. Insecticides are used to manage T. tabaci infestations with control decisions traditionally based on action thresholds that require visually counting thrips on a fixed, predetermined number of onion plants per field. However, this approach for treatment decisions is inefficient when thrips populations are well above or below the action threshold. The aim of this research was to develop a sequential sampling plan that would provide a rapid and reliable classification of thrips populations in commercial onion fields above or below prespecified management thresholds. The study was conducted in a total of 24 commercial onion fields in New York in 2021 and 2022. Taylor's power law and Wald's Sequential Probability RatioTest were used in concert to develop each sampling plan. Simulated and historical field data of thrips populations were used to further validate the efficacy of each sampling plan. Results demonstrated the sequential sampling plan required an average of 78% fewer samples to make a control decision compared with the traditional fixed-sampling approach. Treatment decisions were reached in 72% of cases after inspecting only 10 plants, while only 6% of the cases required examining more than 25 plants. Comparisons with fixed-sample sizes ranging from 23 to 68 plants revealed a 96% agreement in decision-making and a 78% reduction in sampling effort when using the sequential sampling plans.

Typical delimitation trapping survey designs for area-wide (nonlocalized) insect populations are regularly spaced grids, and alternative shapes have not been evaluated. We hypothesized that transect-based designs could give similar detection rates with significantly shorter servicing distances. We used the TrapGrid model to investigate novel “trap-sect” designs incorporating crossed, spoked, and parallel lines of traps, comparing them to a regular grid, in single survey and multiple-site scenarios. We calculated minimum servicing distances and simulated mean probabilities of detecting a pest population, judging overall performance of trap network designs using both metrics. For single sites, trap-sect designs reduced service distances by 65–89%, and most had similar detection probabilities as the regular grid. Kernel-smoothed intensity plots indicated that the best performing trap-sect designs distributed traps more fully across the area. With multiple sites (3 side by side), results depended on insect dispersal ability. All designs performed similarly in terms of detection for highly mobile insects, suggesting that designs minimizing service distances would be best for such pests. For less mobile pests the best trap-sect designs had 4–6 parallel lines, or 8 spokes, which reduced servicing distances by 33–50%. Comparisons of hypothetical trap-sect arrays to real program trap locations for 2 pests demonstrated that the novel designs reduced both trap numbers and service distances, with little differences in mean nearest trap distance to random pest locations. Trap-sect designs in delimitation surveys could reduce costs and increase program flexibility without harming the ability to detect populations.

Argentine ant, Linepithema humile (Mayr) (Hymenoptera: Formicidae), is a pest in southern California citrus orchards because it protects honeydew-producing hemipteran pests from natural enemies. A major impediment to controlling L. humile is estimating ant densities in orchards. Ants use irrigation lines to travel across orchard floors to reach trees infested with hemipterans. However, for making ant control decisions, it is the number of ants in trees, not on pipes that is critical. Work completed here demonstrates that the number of ants counted on pipes is highly correlated with the number of ants counted on trunks. Densities of ants counted on trunks are correlated with trunk diameter, citrus variety, and time of year and time of day counts. Six regression models, linear regression, zero-inflated Poisson regression, and zero-inflated negative binomial regression models, and each of their mixed model extensions, indicated a strong positive relationship between ant counts on irrigation pipes and ant counts on tree trunks. Mean squared prediction error and 5-fold cross-validation analyses indicated that the best performing of these 6 models was the zero-inflated Poisson mixed regression model. A binary classification model developed using support vector machine learning for ant infestation severity levels, categorized as low (<100 ants counted in 1 min) or high (≥100 ants counted in minutes), predicted ant densities on trunks with 85% accuracy. These models can be used to estimate the number of ants on the trunks of citrus trees by using counts of ants made on irrigation pipes.

The Mexican bean beetle, Epilachna varivestis Mulsant (Coleoptera: Coccinellidae), is a key pest of beans, and early detection of bean damage is crucial for the timely management of E. varivestis.This study was conducted to assess the feasibility of using drones and optical sensors to quantify the damage to field beans caused by E. varivestis. A total of 14 bean plots with various levels of defoliation were surveyed aerially with drones equipped with red-blue-green (RGB), multispectral, and thermal sensors at 2 to 20 m above the canopy of bean plots. Ground-validation sampling included harvesting entire bean plots and photographing individual leaves. Image analyses were used to quantify the amount of defoliation by E. varivestis feeding on both aerial images and ground-validation photos. Linear regression analysis was used to determine the relationship of bean defoliation by E. varivestis measured on aerial images with that found by the ground validation.The results of this study showed a significant positive relationship between bean damages assessed by ground validation and those by using RGB images and a significant negative relationship between the actual amount of bean defoliation and Normalized Difference Vegetation Index values.Thermal signatures associated with bean defoliation were not detected. Spatial analyses using geostatistics revealed the spatial dependency of bean defoliation by E. varivestis. These results suggest the potential use of RGB and multispectral sensors at flight altitudes of 2 to 6 m above the canopy for early detection and site-specific management of E. varivestis, thereby enhancing management efficiency.

Fully trapped survey designs are widely used to delimit adventive pests populations that can be detected using traps and lures. Delimitation includes verifying the presence of the pest and determining its spatial extent. The size and shape of the survey design and the density of traps can vary; however, resulting variation in detecting efficiency is often unknown. We used a trapping network simulation model with diffusion-based insect movement to investigate delimiting survey trapping design performance for fully trapped and some modified designs. Simulations included randomized outbreak locations in a core area and a duration of 30 d. We assessed impacts of insect dispersal ability, grid size and shape, and trap attractiveness and density on survey performance, measured as mean probability of capturing individual pests [p(capture)]. Most published grids are square, but circles performed equally well and are more efficient. Over different grid sizes, p(capture) increased for insects with greater dispersal ability but was generally unresponsive to size because most captures occurred in central areas. For low dispersing insects, the likelihood of egress was approximately zero with a 3.2-km square grid, whereas an 11.3-km grid was needed to contain highly vagile insects. Trap attractiveness affected p(capture) more strongly than density: lower densities of poorly attractive traps may underperform expectations. Variable density designs demonstrated potential for cost savings but highlighted that resource-intensive outer bands are critical to boundary determination. Results suggesting that many grids are oversized need empirical verification, whereas other principles, such as using circular shapes, are readily adoptable now.

The fall armyworm, Spodoptera frugiperda (J.E. Smith) (Lepidoptera, Noctuidae), is a polyphagous and highly destructive agricultural pest that invaded mainland China in 2019. To facilitate research on this pest, it is important to formulate and formalize a suitable artificial diet based on local ingredients. In this study, the life histories of fall armyworm reared on corn leaves and four artificial diets were recorded. The four artificial diets used were: soybean and sucrose-based (SS), soybean and wheat germ-based (SW), chickpea and wheat germ-based (CPW), and corn and soybean-based (CNS). The intrinsic rates of increase were 0.1957, 0.1981, 0.1816, 0.1748, and 0.1464 per day in the fall armyworm populations fed corn leaves, CNS, SW, CPW, and SS, respectively. The highest fecundity (F = 1225.4 eggs per female) and net reproduction rate (R0 = 544.7 offspring per individual) were observed for the fall armyworm reared on the CNS diet. Moreover, the developmental rate, survival rate, and fecundity were used to calculate the projection of the population growth. Projection results showed that the fall armyworm populations can increase considerably faster when fed the CNS diet compared with the other diets. In addition, the mass-rearing system showed that the most efficient and economical strategy would be to rear the fall armyworm on the CNS diet. The results indicated that the CNS diet was the most suitable diet for the fall armyworm mass rearing.

The hemp russet mite, Aculops cannabicola (Farkas) is a key pest of hemp (Cannabis sativa L.). Given its microscopic size, estimating the size of its populations can be a major limitation to control this pest. Here, we describe a method to count A. cannabicola using photographs taken with a handheld digital microscope. We compared the consistency and strength of the relationship between photographic- and microscope-based counts of mites from infested plants. Among the three sections of the leaflet, the maximum consistency levels were observed in the proximal (50%) and middle photographs (50%). However, it reached from 64% to 100% when the three sections were considered. Photographic and a microscope-based counts were positively correlated (>0.7). A single photograph can be a good predictor of the total mites per leaflet, however, using two pictures (proximal and middle sections) will increase the consistency of the abundance of A. cannabicola per leaflet. A minimum of 22 leaflets per sampling event can support a strong correlation between the microscope and photographic counts. Our method requires low budget and training and takes short time (0.4 to 1.3 min per leaflet) to count mites per sample. Additionally, photographs can be stored on a smartphone, computer, or tablet, allowing users to share, store and process the photos. This method simplifies counts of A. cannabicola on hemp for research purposes and provides a practical tool for growers to assess mite populations for management decisions. In addition, it may be useful for monitoring eriophyid mites on cultivated plants.

The sugarcane aphid (Melanaphis sacchari Zehntner) is a significant economic pest of grain sorghum (Sorghum bicolor (L.) Moench) in the Southern United States. Current nominal and research-based economic thresholds are based on estimates of mean aphids per leaf. Because enumerating aphids per leaf is potentially time consuming, binomial sequential sampling plans for M. sacchari were developed that allow users to quickly classify the economic status of field populations and determine when an economic threshold has been exceeded. During 2016 and 2017, counts of M. sacchari were recorded from 281 sampling events in 140 sorghum fields located in six states (Oklahoma, Kansas, Texas, Arkansas, Louisiana, Mississippi) . Regression analysis was used to describe the relationships between the mean M. sacchari density per two-leaf sample and proportion of plants infested with one or more aphids. Tally thresholds of T50 and T100 aphids per two-leaf sample were selected based on goodness of fit and practicality. Stop lines for both tally thresholds were developed for selected economic thresholds using Wald's sequential probability ratio test. Model validations using an additional 48 fields demonstrated that reliable classification decisions could be made with an average of 11 samples regardless of location. This sampling system, when adopted, can allow users to easily and rapidly determine when M. sacchari infestations need to be treated.

Sampling plans are an essential part of integrated pest management programs. Sequential sampling plans enable rapid and low-cost assessment of pest densities. Thrips are emerging pests in soybean crops, and the main method used in pest control is chemical. In soybean crops, insecticides are applied mainly using tractors or airplanes. Thus, this work aimed to determine sequential sampling plans for thrips in soybean crops with insecticide applications using a tractor or airplane. Data were collected in 56 soybean fields, and each field was 20 ha. Sampling plans were determined and validated. The lower (m0) and upper (m1) limits of the sequential sampling plans were: m0 = 1.72 and m1 = 3.43 (by tractor applications) and, m0 = 2.27 and m1 = 4.53 thrips. sample–1 (by airplane applications). The slope (S) and the lower (h0) and upper (h1) intercepts of the sequential sampling plans were: S = 2.42, h0 = –5.79, and h1 = 5.79 (by tractor applications) and, S = 3.19, h0 = –6.83, and h1 = 6.83 (by airplane applications). Sequential sampling plans allowed for correct decisions to be made in all situations using a maximum of 10 samples. The sequential plan reduced the sampling effort by over 87% compared to conventional sampling plans. Therefore, these control decision-making systems have proven feasible and advantageous for implementing integrated pest management programs for controlling thrips species in soybean crops. Graphical Abstract