Data were collected from two laboratory rearing experiments conducted in 2018 of Trichoplusia ni caterpillars that had been parasitized by Copidosoma floridanum parasitoids. In the first experiment, parasitized caterpillars were fed artificial diets spiked with increasing concentrations of the phytochemical xanthotoxin in order to assess the effect of xanthotoxin on parasitoid success. In the second experiment, parasitized caterpillars were switched between diets with differing xanthotoxin concentration, such that all caterpillars experienced the same mean xanthotoxin concentration over their lives, but different treatments experienced different variability in xanthotoxin concentration. Data were recorded on caterpillar survival and parasitoid fitness components (e.g. number of offspring, proportion of offspring emerging from host, sex ratio of adult offspring).

,This document contains all data and R statistical software code needed to reproduce the analyses presented in the manuscript:,Woolfolk, S., G. Matthews, and Q. D. Read. 2024. Comparison of infestation rates of fall armyworm (Lepidoptera: Noctuidae) neonates for maize resistance screening. Journal of Insect Science. (Citation to be updated),The data included here come from an experiment to assess a technique for measuring resistance of maize to fall armyworm. An economically important global maize pest, fall armyworm (FAW, Spodoptera frugiperda), causes damage mainly to the above-ground parts of maize plants, primarily the whorl tissues. One of our research unit missions is to identify and develop maize germplasm with resistance to FAW. One method to measure resistance in maize to FAW is visual rating of leaf-feeding damage after infestation with neonates into the whorl. The data presented here are from a replicated experiment crossing eleven maize lines (four susceptible and seven resistant) with five FAW infestation rates; the experiment was repeated in two consecutive years. The measured response was leaf feeding damage on a categorical scale.,The statistical model presented here is a cumulative logistic mixed model. It treats the response variable (leaf damage rating) as an ordered categorical response. We include a random effect to account for the split-plot design, and include three-way interactions between fixed effects of genotype, treatment, and year. We present means for each genotype and treatment based on the underlying modeled probabilities of each category (weighted averages of the modeled probabilities).,,

,Real-time, image-based monitoring for stored product insect pests could increase timely treatments and protection for postharvest products throughout the supply chain. Artificial intelligence (AI) and machine learning can provide the models necessary for accurate identification and population-counting within a trap-based system. This study presents the development of a smart vision-based monitoring system for moth population estimation using sticky traps with automated camera imaging. The proposed system integrates advanced image processing techniques with a Convolutional Neural Network (CNN) to accurately detect and classify moths and non-moth insects captured on sticky traps. Sticky traps, widely employed in integrated pest management (IPM) systems, often require manual inspection, which is labor-intensive and prone to human error. To address this, the developed system automates the detection process, reducing reliance on manual counting while improving classification precision. The dataset, consisting of 1,739 high-resolution images, was divided into training and testing subsets with a 70–30% split. Each image was preprocessed and annotated with ground-truth labels for accurate performance evaluation. The model demonstrated a high overall classification accuracy of 95.8%, with precision, recall, and F1-scores consistently exceeding 90%. These results highlight the effectiveness of the CNN in managing complex scenarios such as insect overlap, varied environmental conditions, and trap orientations, offering a scalable and efficient solution for real-time insect population monitoring in storage environments. The findings suggest that the proposed system provides a reliable and automated alternative for pest management, significantly reducing labor and enhancing decision-making in storage facilities and postharvest agriculture. In addition, field validation demonstrated the system’s feasibility in real-world storage environments, offering an effective and scalable alternative to traditional inspection practices while minimizing labor and enhancing precision pest control decisions.,This dataset features a subset of the images captured every hour in a sticky trap baited with a Plodia interpunctella pheromone lure. The images were processed for classificaiton of Indian meal moths and for population counting over time. A read me on image file naming convention, meta data, and conversion code for MatLab are included in the data files.,This research used resources provided by the SCINet project and/or the AI Center of Excellence of the USDA Agricultural Research Service, ARS project numbers 0201-88888-003-000D and 0201-88888-002-000D.,

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농림축산식품부에서 제공하는 시설원예 농작물(딸기) 병해충에 대한 데이터로 병, 해충의 이미지 데이터를 제공합니다.

- Text description of regulatory methods for estimating nectar and pollen concentrations from soil applications and seed treatments; - Table S1: Parameter set for imidacloprid used for simulations to assess the relative risk of neonicotinoid pesticides to hummingbirds. - Table S2: Full sensitivity results for ruby-throated hummingbird exposure to imidacloprid simulation - Table S3: Data used for estimating the Mineau scaling factor for imidacloprid. This dataset is associated with the following publication: Etterson, M., E. Paulukonis, and S. Purucker. Using Pop-GUIDE to Assess the Applicability of MCnest for Relative Risk of Pesticides to Hummingbirds. Ecologies. MDPI, Basel, SWITZERLAND, 4(1): 171-194, (2023).

,Aim of Dataset,In this work, we performed a two-year latitudinal biosurveillance program for Prostephanus truncatus (Horn) (Coleoptera: Bostrichidae), related bostrichids, and Sitophilus spp. (Coleoptera: Curculionidae) in and around grain production and some natural areas to evaluate how landscape elements, latitude, and season affected their spatiotemporal dynamics.,Sampling locations & traps,The biosurveillance program was conducted by use of a trapping network in central North America in 2021 and 2022 and also in Greece in 2022. Trapping locations were selected along a latitudinal series across major grain-producing states in central North America from 19.6 to 46.8° N, including Estado de México in México, Texas, Oklahoma, Kansas, Nebraska, South Dakota, and North Dakota (Figure 1; Supplementary Table 1). The number of sites was expanded in 2022 compared to 2021 to provide a more comprehensive picture. At each location, we set up three-trap transects in each of two to three habitats: (1) near row crops (e.g., wheat, maize or soybean), (2) near a food storage facility (e.g. bins, elevator, or processor), and (3) in a natural habitat with no grain source nearby. Pitfall traps (Storgard Dome™ traps, Trécé, Inc., Adair, OK, USA) and 4-funnel Lindgren traps (Bioquip, Rancho Dominguez, CA, USA) spaced 5–10 m apart with a vented collection cup (9.5 × 15.2 cm D:H) at the base were used. The Lindgren traps included a 9 cm (D) piece of 0.4% w/w deltamethrin-incorporated netting or a 1-inch piece of No-Pest Strip (Hot Shot, Reynold’s Consumer Products, Lake Forest, IL) as the kill mechanism, as these have successfully been used in traps in the past (Wilkins et al. 2021). There were either three or four Lindgren or four pitfall traps in a given transect. The Lindgren traps were baited with a commercial formulation of male-produced P. truncatus aggregation pheromone (IL-953, Insects Limited, Westfield, IN, USA), Sitophilus spp. aggregation pheromone separately (IL-703, Insects Limited), multi-species pheromone lures for the cigarette beetle, Lasioderma serricorne (F.) (Coleoptera: Anobiidae), the Indian meal moth, Plodia interpunctella (Hübner) (Lepidoptera: Pyralidae), and Trogoderma spp. (Coleoptera: Dermestidae) (IL-708, Insects Limited), and a R. dominica pheromone septa (Item#3158, Trece, Inc., Adair, OK, USA). A batch of lures was purchased in May 2021, and another batch was purchased in April 2022. The pitfall trap only contained the Sitophilus spp. and/or P. truncatus lure. We also added a small amount of maize or wheat to keep insects in the pitfall trap based on synergized response with food cues + pheromones for Sitophilus spp. (Trematerra and Girgenti 1989). The traps were deployed for 7-d periods either on a weekly or monthly basis depending on location from 14 June to as late as 7 Dec 2021 and 4 May to 6 Dec 2022. In Greece, the same protocol as above was utilized in a compressed timeframe consisting of 4 weeks during the key maize harvest in September 2022 at 4 sites between Volos and Thessaloniki (Central and Northern Greece).,Insect identification and specimen deposition,Insects were identified to species or genus where possible for all specimens using the USDA and Canadian taxonomic keys for stored product insects (Bousquet 1990; USDA 1991). Each trap capture was noted separately along with identifying information, and the abundance of P. truncatus, P. punctatus, other Bostrichidae, and Sitophilus spp. (including S. zeamais and S. oryzae) were recorded. Insects were identified using a dissecting microscope (SMZ18, Nikon Inc., Tokyo, Japan) at 30 x magnification. All specimens for project were deposited at the Kansas State University Museum of Entomological and Prairie Arthropod Research in the Department of Entomology.,,

농림축산식품부에서 제공하는 시설원예 농작물(가지) 병해충에 대한 데이터로 병, 해충의 이미지 데이터를 제공합니다.