Location: Stored Product Insect and Engineering Research
2023 Annual Report
Objectives
Objective 1: Expand genomic resources for stored product insects and use functional genomics to find new gene targets or pathways for biorational control, identify genes that insects use to detect and respond to sensory cues, and improve nutritional content of stored product insects as food sources for humans and livestock.
Subobjective 1A: Improve genomic resources for stored product insects.
Subobjective 1B: Use functional genomics to identify genes that insects use to respond to pheromones and kairomones.
Subobjective 1C: Genetic research to improve insects as animal feed.
Subobjective 1D: Investigate molecular responses that allow insects to recover after exposure to insecticides and oral RNAi.
Objective 2: Improve monitoring strategies for stored product insects through the identification of new attractants, improve understanding of insect response to traps and attractants, and develop and evaluate remote sensing and imaging technologies for detection of stored product insects and other quality issues.
Subobjective 2A: Identify new semiochemicals that can be used as attractants or repellents for stored product insects and evaluate factors that impact active spaces around traps and packages.
Subobjective 2B: Develop remote sensing and imaging for rapid detection of stored product insect infestations and other grain quality issues that occur during storage.
Objective 3: Improve and develop new pest management tools and strategies for stored product insects in bulk grain storage and food facilities that focus on preventing infestations and reducing risks associated with insecticides.
Subobjective 3A: Develop tools that exclude insects from infesting products, bulk storage facilities, and food processing plants.
Subobjective 3B: Develop and use long-term monitoring data to improve pest management practices.
Subobjective 3C: Optimize use of aerosols for treatment and management of stored product insects.
Subobjective 3D: Evaluate efficacy of reduced-risk insecticides for pest management, grain protection, and residual surface treatments.
Subobjective 3E: Investigate the impacts of behavior-based integrated pest management (IPM) tactics on insect behavior.
Approach
Whole and processed durable grain-based commodities are susceptible to infestation by a community of stored product insects throughout the distribution chain, which can cause considerable economic losses for the food industry. Additional issues such as phosphine resistance, the phase-out of methyl bromide fumigation, and a growing demand by consumers and producers to reduce pesticide inputs necessitate the development and expansion of alternate approaches to pest management. We propose to develop systems-level pest management tactics that reduce chemical residues that come into direct contact with food, develop new prevention and exclusion techniques to keep insects from infesting facilities and packaged goods, optimize behavior-based management strategies, and develop automated techniques to detect insect infestations. Genomic resources will also be an integral component as these tools can be used to reduce the emergence of insecticide resistant populations, identify genes involved in response to chemical cues associated with food and conspecifics, and improve mass rearing of insects for human and animal consumption. Ultimately, innovative tools and strategies based on research in the areas of genomics, behavior, biology, and ecology will be developed for management of postharvest pests to minimize grain commodity losses and maintain quality at all stages of the marketing chain.
Progress Report
Substantial progress was made towards Objective 1 in FY 2023. An extensive collection of multiple populations of lesser grain borers from around the Great Plains, Mexico, and Canada was organized. Protocols for DNA extraction and genotyping were refined in FY 2023 and samples are currently being processed for DNA extraction and library construction for population genetics and whole genome re-sequencing analysis. The breadth of data will allow us to investigate the genetic diversity of chemosensory genes within this species, which is important given the number of pseudogenes that were found in the lesser grain borer genome assembly. It is unclear whether the number of pseudogenes is reflective of a high genetic diversity of chemosensory genes or whether this is due to the recent evolution of these species into a new ecological niche (from field to storage environments). In addition, genome assemblies of six different species of red flour beetle were released into National Center for Biotechnology Information and are being annotated by the eukaryotic annotation pipeline with manual annotation of chemosensory genes being conducted in tandem.
Furthermore, as part of the ARS Grand Challenges project developing insects for poultry and fish feed, researchers in Manhattan, Kansas, along with collaborators at ARS in Stoneville, Mississppi, North Carolina State University, All Things Bugs, and National Institutes of Health recently released the genome of the house cricket and demonstrated that genetic engineering can be successfully applied to this species, which has contributed towards improving the health and production of farmed insects. Likewise, large-scale mealworm farms are benefitting from an updated mealworm genome and associated transcriptome data on different life-stages, as well as blueprints for genetic engineering in this species. These data are being used in projects with collaborators in Greece to understand genetic profiles in European and U.S. farmed mealworms, and with ARS Stoneville, Mississippi, to evaluate the genetic elements underpinning mealworm development and body size.
We have additionally developed pipelines in collaboration with the Food and Drug Administration to rapidly identify potential pathogens in insects used for supplemental animal feed that could pose food security risks. As part of these efforts, protocols were developed to identify a pathogenic bacterium that likely led to the collapse of a mealworm colony. In contrast, healthy mealworms had a more diverse microbiome with beneficial Lactobacilli comprising about 20% of the microbiome, providing insight into how the microbiome can influence colony health. These data will ensure that farmed insects are safe and efficacious for supplemental animal feed and demonstrate how sequencing can be used to monitor farmed insects for problematic pathogens.
As part of our efforts to understand the role of food in recovery after exposure to insecticide, we conducted a large-scale time-course experiment with two different types of insecticidal netting using red flour beetle adults. In addition, the nutritional content of the diet was varied by mixing wheat flour with various amounts of cellulose, to determine whether the simple presence of a food-like substrate was responsible for the recovery or whether nutritional content mattered. We found that significantly more beetles recovered after short-term exposures to both netting types in the presence of 100% flour compared to diets containing cellulose only or 5 and 25% flour. This finding suggests that the food does not simply dilute the insecticide and that the nutritional content of the flour might impact physiology in a way that allows insects to overcome insecticide exposure. RNA-Sequencing and biochemical assays are underway to understand the role of food in this process.
For Objective 2, behavior and oviposition data of Indianmeal moths were investigated when exposed to mating disruption dispensers. Additionally, mating success and frequency of mating behaviors (courtship) associated with distance from the mating disruption dispensers were measured. Spatial distribution maps and statistical models that account for differences in oviposition and mating behaviors based on distance away from the dispensers are currently being compiled, which can be used to refine mating disruption protocols.
Progress was also made in automating detection of stored product insects using either image data or electronic nose. In FY 2023, electronic nose data were collected from wheat and rice containing various amounts of infested grains to determine its sensitivity. Unsupervised machine learning approaches failed to reliably resolve infested and uninfested samples, especially at low densities; however, convolutional neural networks and other more sophisticated machine learning approaches are being tested to determine if they provide greater discriminatory power. In addition, through a collaboration with co-located ARS engineers, deep learning was used to develop image classification tools for identifying stored product insect species. Identification was reliable with 96% accuracy for all species. Gradient-weighted Class Activation Mapping Analysis (Grad-CRAM) identified body shape as the most significant characteristic in discerning among stored product insect species. Elytral patterns were important for beetle classification, but features like antennal morphology, snout, and legs were less critical.
For Objective 3, a research fellow sponsored by USDA SCINet (Scientific Computing Initiative) in collaboration with five different university and museum collaborators, has been collecting occurrence data for the larger grain borer, a species of concern. We have also developed a species distribution prediction based on changes in climate to determine suitable areas for the larger grain borer. In addition, we have obtained forest cover data for the contiguous United States so we can predict how changes in forest cover may affect larger grain borer distribution and establishment. Ultimately, these datasets can be interfaced with population data collected for Objective 1 to determine seasonal and location specific trends associated with populations of future populations of larger grain borer and current populations of lesser grain borer and other prominent stored-product insect species. In addition, we have collected two years of Indianmeal moth population data in a seed storage warehouse to understand how spatial and seasonal trends influence indoor populations of stored product insects.
Progress was also made in improving pest management strategies, especially regarding lower risk materials, such as packaging and long-lasting insecticidal netting (LLIN). Specifically, experiments investigating the degradation of insecticide incorporated packaging due to temperature and ultraviolet light effects across several materials were conducted in FY 2023. Additionally, research involving the efficacy of these materials was expanded to include two new stored product insects, sawtoothed grain beetles and confused flour beetles. The longevity and efficacy of the insecticide in these materials in the presence of direct sunlight was also investigated. The active ingredient methoprene, was found to be 100% effective at inhibiting adult emergence of red flour beetle after 52 days of exposure to Kansas weather in two packaging types. In addition, the use of LLIN in conjunction with fumigation was tested to determine whether the presence of the netting improved fumigation efficacy. We found miniature silos deployed in 3 metric ton grain bins with Carifend netting (0.34% alpha-cypermethrin) had 82–97% less insect infestation (including red flour beetle and lesser grain borer) and 98–99% less progeny production as compared to the silos with untreated netting or no netting, regardless of fumigation. Damaged grain was reduced by 97–99% in miniature silos protected with LLIN compared those protected by untreated netting or no netting. Carifend netting reduced the number of fumigations required by 58–100% over the course of the season. This technology is highly promising in extending the efficacy of fumigation, while preserving this tool of last resort for bulk storage.
Research on grain protectants, contact insecticides, and aerosols were also continued in FY 2023 and were specifically evaluated for short term and residual effect on different surfaces. Hard and non-porous material had increased immediate and residual effect on rice weevils and lesser grain borers for contact insecticides and red flour beetles for aerosol applications. Semi field experiments were conducted using a cylinderized methoprene aerosol product, and a new chemical reference method was developed to quantify methoprene depositions and correlate with aerodynamic particle sizer data. There are ongoing research experiments to further evaluate the HPLC deposition with insect bioassays.
Finally, we investigated the impacts of behavior-based integrated pest management tactics on insect behavior by assessing whether mating disruption could work as a rapid response for facilities affected by the quarantine pest, khapra beetle, or as a tactic to implement in facilities shipping to the U.S. or its partners. We found that mating disruption was successful at preventing mating in collaborative simulated warehouse experiments performed in Greece over multiple six-week periods. Compared to control warehouses receiving no pheromone, females almost never found a mate in warehouses where pheromone was deployed. This indicates there is promise in mating disruption for khapra beetle.
Accomplishments
1. Artificial intelligence automates insect identification in food samples. Food samples are routinely screened for the presence of insects and rapid identification methods are needed for species identification. Most identifications are done manually by examining forewing patterns under a microscope, which is laborious and requires specialized expertise. ARS researchers in Manhattan, Kansas, and collaborators demonstrated that automated identification of 27 different species of beetles is feasible through forewing pattern recognition using artificial intelligence. Although high quality images were associated with improved prediction accuracy, multiple high-quality images were often needed to identify some species, especially those with high variation in forewing patterns. However, coupling forewing images with whole body images will likely improve species identification, providing a significant step towards a mechanism for autonomous species identification. Overall, automating insect identification will benefit pest control specialists and food facility managers
2. Sorghum milling products support stored product pest populations. Sorghum production and milling has rapidly increased in the central plains region of the United States because of its adaptability to arid climates and a high consumer demand for products containing gluten-free flour. However, the susceptibility of sorghum and its milling products to damage and infestation by stored product insects is not well characterized. ARS researchers in Manhattan, Kansas, determined that all sorghum milling by-products (bran, shorts, coarse grits, fine grits, red dogs and flour) were susceptible to infestations by several species of stored product insects, including sawtooth grain beetle and red flour beetle, both common pests found worldwide, and the khapra beetle, a quarantine insect that has been previously eradicated from the United States. Although insect development was slower on flour, all fractions readily supported development from egg to adult. Sorghum bran also supported high numbers of immature khapra beetles and red flour beetle adults. This finding suggests that sorghum storage and milling facilities can support populations of stored product insects and that concerted efforts should be undertaken to monitor for insect activity as sorghum production for human food products increases in the United States.
3. The cricket genome unleashes new tools for protein shortages in livestock feed. The world is facing critical shortages because of limitations on producing protein for human food and livestock feed. Insects, including the house cricket, represent promising alternatives for nutritious supplemental protein. However, genomic and genetic resources are needed to refine the nutritional profiles of crickets and improve their disease resistance in mass rearing facilities. As part of the Ag100Pest initiative, USDA-ARS researchers in Manhattan, Kansas, and Stoneville, Mississippi, along with collaborators sequenced and assembled a high-quality house cricket genome and developed gene editing techniques. These data and techniques will directly benefit producers and farmers to improve crickets for animal food and feed.
4. Female behavior: an overlooked factor in the efficacy of mating disruption in Indianmeal moths. Mating disruption is a common pest management tactic deployed for controlling stored product insects in warehouses and retail stores. This approach uses high concentrations of female-produced pheromones to confuse males and prevent them from finding and mating with females, which can quickly reduce populations. The impact of mating disruption on male behavior is well documented, but it is unknown how females respond. USDA-ARS researchers in Manhattan, Kansas, demonstrated that female Indianmeal moths reduced their movement in the presence of pheromone lures. In addition, calling behaviors were differentially impacted in a population-dependent manner, with one population increasing their calling behavior with the pheromone present while the other population reduced its calling behavior. Although reduced movement by females should increase the effectiveness in mating disruption, increased calling by some females could actually reduce its success in some populations and lead to the emergence of resistance to mating disruption in some populations of Indianmeal moths and other insect species. These findings suggest the need for additional research on how female behavior impacts the efficacy of mating disruption.
Review Publications
Dossey, A.T., Oppert, B.S., Chu, F., Lorenzen, M.D., Scheffler, B., Simpson, S., Koren, S., Johnston, J., Kataoka, K., Ide, K. 2023. Genome and genetic engineering of the house cricket (Acheta domesticus): Applications for sustainable agriculture. PLOS ONE. 13(4). Article 589. https://doi.org/10.3390/biom13040589.
Fatehi, S., Aikens, M., Phillips, T.W., Brown, S., Zhu, K., Scully, E.D., Park, Y. 2023. Characterization of Iflavirus in the red flour beetle, Tribolium castaneum (Coleoptera; Tenebrionidae). Insects. 14(3). Article 220. https://doi.org/10.3390/insects14030220.
Bisgin, H., Bera, T., Wu, L., Ding, H., Bisgin, N., Liu, Z., Pava-Ripoll, M., Barnes, A., Campbell, J.F., Vyas, H., Furlanello, C., Tong, W., Xu, J. 2022. Accurate species identification of food-contaminating beetles with quality-improved elytral images and deep learning. Frontiers in Artificial Intelligence. https://doi.org/10.3389/frai.2022.952424.
Gerken, A.R., Dryer, D.L., Abts, S.R., Campbell, J.F. 2022. Behavioral response of unmated female Plodia interpunctella Hübner (Lepidoptera: Pyralidae) to synthetic sex pheromone lure. Environmental Entomology. 51(6):1200-1209. https://doi.org/10.1093/ee/nvac087.
Ponce, M.A., Sierra, P., Jacqueline, M., Kim, T.N., Scully, E.D., Morrison III, W.R. 2023. Attraction, mobility, and preference by Lasioderma serricorne (F.) (Coleoptera: Ptinidae) to microbially-mediated volatile emissions by two species of fungi in stored grain. Scientific Reports. 13(1). Article 6176. https://doi.org/10.1038/s41598-023-32973-y.
Brabec, D.L., Kaloudis, E., Athanassiou, C., Campbell, J.F., Agrafioti, P., Scheff, D.S., Bantas, S., Sotiroudas, V. 2022. Fumigation monitoring and modeling of hopper-bottom railcars loaded with corn grits. Journal of Biosystems Engineering. 47:358-369. https://doi.org/10.1007/s42853-022-00148-8.
Palmer, N.A., Sarath, G., Bowman, M.J., Saathoff, A.J., Edme, S.J., Mitchell, R., Tobias, C.M., Madhavan, S., Scully, E.D., Sattler, S.E. 2023. Divergent metabolic changes in rhizomes of lowland and upland switchgrass (panicum virgatum) from early season through dormancy onset. Plants. 12(8). Article 1732. https://doi.org/10.3390/plants12081732.
Sakka, M.K., Gourgouta, M., Morrison III, W.R., Domingue, M.J., Grosdidier, R.F., Wilkins, R.V., Athanassiou, C.G. 2023. Different trap designs and attractants affect the capture of multiple life stages of Trogoderma granarium Everts and Trogoderma variabile Ballion in the laboratory. Journal of Stored Products Research. 102. Article 102108. https://doi.org/10.1016/j.jspr.2023.102108. LOG NO. 398948.
Ponce, M.A., Lizarraga, S., Bruce, A., Kim, T.N., Morrison III, W.R. 2022. Grain inoculated with different growth stages of the fungus, Aspergillus flavus, affect the close-range foraging behavior by a primary stored product pest, Sitophilus oryzae (Coleoptera: Curculionidae). Chemoecology. 51(5):927-939. https://doi.org/10.1093/ee/nvac061.
Campbell, J.F., Athanassiou, C., Hagstrum, D., Zhu, K. 2021. Tribolium castaneum: A model insect for fundamental and applied research. Annual Review of Entomology. 67:347-365. https://doi.org/10.1146/annurev-ento-080921-075157.
Zhiganov, N.I., Tereshchenkova, V.F., Oppert, B.S., Filippova, I.Y., Belyaeva, N.V., Dunaevsky, Y.E., Belozersky, M.A., Elpidina, E.N. 2021. The dataset of trypsin type serine peptidases and their inactive homologs in Tenebrio molitor transcriptomes. Data in Brief. 38. Article 107301. https://doi.org/10.1016/j.dib.2021.107301.
Dunaevsky, Y., Tereshchenkova, V., Belozersky, M., Filippova, I., Oppert, B.S., Elpidina, E. 2021. Effective degradation of gluten and its fragments by gluten-specific peptidases: application for the treatment of patients with gluten sensitivity. Pharmaceutics. 13(10). Article 1603. https://doi.org/10.3390/pharmaceutics13101603.
Lampiri, E., Scully, E.D., Arthur, F.H., Athanassiou, C.G. 2023. Development and immature mortality of the saw-toothed grain beetle, Oryzaephilus surinamensis, on different sorghum fractions. Journal of Economic Entomology. 116(2):615-620. https://doi.org/10.1093/jee/toad024.
Gerken, A.R., Morrison III, W.R. 2023. Viewing Farm2Fork agriculture through the lens of community ecology: The who, why, and what of IPM in the postharvest agricultural supply chain. Frontiers in Agronomy. 7. https://doi.org/10.3389/fsufs.2023.1137683.
