Search Results (108)

Insect pests are a major threat to agricultural production, causing significant crop yield reductions annually. Integrated pest management (IPM) is well-studied, but its precise application in farmlands is still challenging due to variable weather, diverse insect behaviors, crop variability, and soil heterogeneity. Recent advancements in Artificial Intelligence (AI) have shown the potential to revolutionize pest management by implementing 4R pest stewardship: right pest identification, right method selection, right control timing, and right action taken. This review explores the roles of AI technologies within the 4R framework, highlighting AI models for accurate pest identification, computer vision systems for real-time monitoring, predictive analytics for optimizing control timing, and tools for selecting and applying pest control measures. Innovations in remote sensing, UAV surveillance, and IoT-enabled smart traps further strengthen pest monitoring and intervention strategies. By integrating AI into 4R pest management, this study underscores the potential of precision agriculture to develop sustainable, adaptive, and highly efficient pest control systems. Despite these advancements, challenges persist in data availability, model generalization, and economic feasibility for widespread adoption. The lack of interpretability in AI models also makes some agronomists hesitant to adopt these technologies. Future research should focus on scalable AI solutions, interdisciplinary collaborations, and real-world validation to enhance AI-driven pest management in field crops. Full article

The extensive use of veterinary antibiotics in livestock production is a growing concern, particularly in terms of environmental sustainability and health security. This review presents the case of veterinary antibiotic use and regulations in Canada before exploring a potential novel avenue for agricultural antibiotics waste up-cycling. The impact of the widespread use of antibiotics in animal husbandry is reviewed, and the dissemination routes of antibiotic residues and antibiotic-resistant bacteria from farms to the environment are explored to identify potential weaknesses in the management of veterinary antibiotics. The presence of antibiotic residues in livestock products and manure poses significant challenges, as these residues contribute to the development of antibiotic-resistant bacteria, which poses a threat to both the environment and health. The review examines the fate of animal waste contaminated with antibiotics in the environment, exploring the impact of management practices on antibiotic degradation and their persistence in soil and water systems. Additionally, the potential risks to human and animal health are addressed, emphasizing the links between antibiotic residues in the environment and the rising threat of antimicrobial resistance. The last part of this review focuses on exploring how up-cycling veterinary antibiotic residues in insects for feed and fertilizers could contribute to mitigating these risks. Overall, this review calls for more integrated solutions that balance the need for antibiotics in animal agriculture with the prevention of environmental contamination and the antibiotic resistance threat, while meeting the rising demand for animal proteins, highlighting the need for more region-specific surveillance programs. Full article

Chagas disease, caused by Trypanosoma cruzi, is a significant health concern in Latin America, with triatomine insects serving as its primary vectors. Among them, Triatoma barberi is an important yet understudied species in Querétaro, Mexico. This study employs ecological niche modeling (ENM) to predict the potential distribution of T. barberi in the region, using occurrence records and environmental variables. The MaxEnt algorithm was used to generate the model, which was validated through AUC and TSS metrics. Results indicate that temperature seasonality and altitude are key drivers of T. barberi distribution, with high-suitability areas found in semi-urban and peri-urban zones. Additionally, six new occurrence records were documented, suggesting a growing urban presence of this species. These findings highlight the need for enhanced vector surveillance and targeted control measures to reduce the risk of Chagas disease transmission. Full article

Biting midges, Culicoides spp. (Diptera: Ceratopogonidae), are significant vectors capable of transmitting arboviruses, such as bluetongue virus, to livestock. New Zealand is free of Culicoides, and a national surveillance programme is in place for the early detection of an incursion. Traditionally, insect trap samples from the surveillance programme are analyzed using morphology-based diagnostics under microscopes, which is time-consuming and relies on specialized taxonomic expertise. Here, we assessed the effectiveness of DNA metabarcoding using insect bulk samples and environmental DNA (eDNA) from liquid samples collected in surveillance traps. Two Cytochrome oxidase I (COI) barcoding primer sets were employed to study biodiversity and detect exotic species. The results indicated that DNA metabarcoding with homogenized insect bulk samples had a higher overall detection accuracy rate (over 81% for both primer pairs) compared to ethanol fluid-derived eDNA samples from traps (68.42% and 55.26% for the primer sets LCO1490/HCO2198 and mlCOIintF/jgHCO2198, respectively) based on congruence with morphological identification. Detection failures were likely due to eDNA extraction issues or low target species abundance. Both approaches showed similar insect community composition and diversity in the surveillance trap samples, suggesting the potential of DNA metabarcoding for biosecurity surveillance and biodiversity assessments. Overall, DNA metabarcoding using bulk insect samples could enhance the efficiency of Culicoides surveillance, reducing workload and screening time. Full article

Human activities and land use changes have a major impact on the distribution and diversity of mosquito vectors and their associated viruses. This study describes the diversity and differential abundance of viruses associated with mosquito species from four habitats of the Yucatan Peninsula, Mexico. Using next-generation sequencing (NGS), we analyzed 61 genomic libraries belonging to 20 mosquito species to characterize the viral community. A total of 16 viral species were identified, representing 14 different viral families. Most identified viruses were associated with insects, plants, and fungi. Additionally, vertebrate associated viral families, including Herpesviridae, Peribunyaviridae, Nairoviridae, and Arenaviridae, were detected in mosquitoes from urban habitats. Notably, insect-associated viruses like Hubei mosquito virus 4 and Hubei virga-like virus 2 were identified, along with the first report of Mercadeo virus in Mexico. Variations in viral community composition were primarily driven by mosquito species, with species of the same genus maintaining similar viromes despite occupying different habitats. These findings reinforce that intrinsic traits of mosquito species play a key role in shaping viral community composition. To our knowledge, this is the first study that describes the viral community in mosquitoes in Yucatan Peninsula, Mexico. This study provides essential baseline data for the surveillance of mosquitoes and associated viruses from a biodiverse tropical region that faces strong land use modifications. Full article

Monitoring insect activity at hive entrances is essential for advancing precision beekeeping practices by enabling non-invasive, real-time assessment of the colony’s health and early detection of potential threats. This study evaluates deep learning models for detecting worker bees, pollen-bearing bees, drones, and wasps, comparing different YOLO-based architectures optimized for real-time inference on an RTX 4080 Super and Jetson AGX Orin. A new publicly available dataset with diverse environmental conditions was used for training and validation. Performance comparisons showed that modified YOLOv8 models achieved a better precision–speed trade-off relative to other YOLO-based architectures, enabling efficient deployment on embedded platforms. Results indicate that model modifications enhance detection accuracy while reducing inference time, particularly for small object classes such as pollen. The study explores the impact of different annotation strategies on classification performance and tracking consistency. The findings demonstrate the feasibility of deploying AI-powered hive monitoring systems on embedded platforms, with potential applications in precision beekeeping and pollination surveillance. Full article

Arthropod-borne viruses (arboviruses) represent a growing concern for global public and veterinary health, with cases reported across all continents. This review presents a broad overview of the geographic distribution of arboviruses transmitted by insect vectors, emphasizing the importance of early viral detection as a cornerstone of surveillance and outbreak preparedness. Special attention is given to the phenomenon of zoonotic spillover, where viruses maintained in natural transmission cycles often involving wildlife reservoirs and arthropod vectors cross into human populations, triggering emergent or re-emergent outbreaks. This article discusses key arboviral families of medical and veterinary significance, including Togaviridae, Flaviviridae, Nairoviridae, Phenuiviridae, Peribunyaviridae, and Orthomyxoviridae, highlighting their molecular and structural characteristics. These features are essential for guiding the development and implementation of specific and sensitive detection strategies. In addition, this work provides a comparative analysis of diverse laboratory methodologies for viral detection in vectors. From serological assays and viral isolation to advanced molecular tools and next-generation sequencing, we explore their principles, practical applications, and context-dependent advantages and limitations. By compiling this information, we aim to support researchers and public health professionals in selecting the most appropriate tools for vector surveillance, ultimately contributing to improved response strategies in the face of arboviral threats. Full article

The Clonostachys genus is a saprophytic soil microfungus (Ascomycota). It exhibits significant ecological adaptability and plays a crucial role in maintaining the balance of soil microorganisms. Species within this genus are natural antagonists of insects and nematodes, and they also combat phytopathogenic fungi through mycoparasitism. This process involves producing lytic enzymes and competing for space and nutrients. Clonostachys species are effective biocontrol agents in agriculture and have been utilized to manage pests affecting many high-value commercial crops, acting as a natural biopesticide. They inhabit plant tissues, boosting plant defenses and activating genes for water and nutrient uptake, enhancing plant performance. Additionally, they produce enzymes and bioactive metabolites with antimicrobial, antifungal, nematocidal, anticancer, and antioxidant properties. Clonostachys species can degrade plastic waste and remove hydrocarbons from crude oil-contaminated sites when functioning as endophytes, positioning Clonostachys as a promising candidate for reducing environmental pollution. There are still challenges and limitations, such as the continuous surveillance of the safety of Clonostachys species on plants, the establishment of commercial applications, formulation viability, and variability due to field conditions. These issues will have to be addressed. This review provides an overview of Clonostachys ecology, morphology, classification, and biotechnological applications, emphasizing its significance in various fields. Full article

Insect-borne viruses may account for a significant proportion of non-malaria and non-bacterial febrile illnesses in Liberia. Although the presence of many arthropod vectors has been documented, the collective burden of arbovirus infections and baseline pre-existing immunity remains enigmatic. Our goal was to determine the seroprevalence of arbovirus exposure across the country using a resource-sparing, multiplex immunoassay to determine IgG responses to immunodominant antigens. 532 human serum samples, from healthy adults, collected from 10 counties across Liberia, were measured for IgG reactivity against antigens of eight common flavi-, alpha-, and orthobunya/nairoviruses suspected to be present in West Africa. Approximately 32.5% of our samples were reactive to alphavirus (CHIKV) E2, ~7% were reactive separately to West Nile (WNV) and Zika virus (ZIKV) NS1, while 4.3 and 3.2% were reactive to Rift Valley Fever virus (RVFV) N and Dengue virus-2 (DENV-2) NS1, respectively. Altogether, 21.6% of our samples were reactive to ≥1 flavivirus NS1s. Of the CHIKV E2 reactive samples, 8.5% were also reactive to at least one flavivirus NS1, and six samples were concurrently reactive to antigens of all three arbovirus groups, suggesting a high burden of multiple arbovirus infections for some participants. These insights suggest the presence of these four arbovirus families in Liberia with low and moderate rates of flavi- and alphavirus infections, respectively, in healthy adults. Further confirmational investigation, such as mosquito surveillance or other serological tests, is warranted and should be conducted before initiating additional flavivirus vaccination campaigns. The findings of these studies can help guide healthcare resource mobilization, vector control, and animal husbandry practices. Full article

Mosquitoes, as vectors of numerous serious infectious diseases, require rigorous behavior monitoring for effective disease prevention and control. Simultaneously, precise surveillance of flying insect behavior is also crucial in agricultural pest management. This study proposes a three-dimensional trajectory reconstruction method for mosquito behavior analysis based on video data. By employing multiple synchronized cameras to capture mosquito flight images, using background subtraction to extract moving targets, applying Kalman filtering to predict target states, and integrating the Hungarian algorithm for multi-target data association, the system can automatically reconstruct three-dimensional mosquito flight trajectories. Experimental results demonstrate that this approach achieves high-precision flight path reconstruction, with a detection accuracy exceeding 95%, an F1-score of 0.93, and fast processing speeds that enables real-time tracking. The mean error of three-dimensional trajectory reconstruction is only 10 ± 4 mm, offering significant improvements in detection accuracy, tracking robustness, and real-time performance over traditional two-dimensional methods. These findings provide technological support for optimizing vector control strategies and enhancing precision pest control and can be further extended to ecological monitoring and agricultural pest management, thus bearing substantial significance for both public health and agriculture. Full article

Invasive insect pests pose a significant threat to forest ecosystems. Effective pest management relies on detecting these pests, which can be challenging when populations are sparse, newly introduced, or not easily observable. The spotted lanternfly (Lycorma delicatula White), a recent invader to North America, has caused extensive damage across the eastern United States since its introduction in 2014. Conventional monitoring methods, such as traps or visual inspections, are limited in their spatial coverage and may not reliably attract or capture target species. In this study, we explored the potential of bat guano as an additional tool for invasive insect detection. We collected guano samples from five bat species across three forested sites in New Jersey, USA, between 2018 and 2022 and used species-specific quantitative PCR (qPCR) to detect spotted lanternfly DNA. Spotted lanternfly DNA was detected in guano from two bat species: big brown bats (Eptesicus fuscus) and eastern red bats (Lasiurus borealis). Detection probability was strongly influenced by spotted lanternfly phenology, with higher detection rates occurring during the adult life stage. The detection of spotted lanternfly DNA in bat guano demonstrates the feasibility of using guano analysis as a complementary tool for insect pest surveillance. Integrating guano-based monitoring with traditional methods could enhance insect pest detection efforts across diverse forested and agricultural landscapes. Full article

Chagas disease, caused by Trypanosoma cruzi, remains a significant public health challenge, particularly in Latin America, where it is one of the most neglected diseases and is primarily transmitted by triatomine insects. The disease exhibits complexity due to its diverse transmission routes, including vectorial and non-vectorial mechanisms such as blood transfusions and congenital transmission. Effective monitoring and control strategies are critical to mitigating its impact. This review focuses on current monitoring and control efforts, emphasizing the importance of enhanced surveillance systems, improved risk assessments, and integrated vector control programs. Surveillance plays a pivotal role in early detection and timely intervention, particularly in endemic regions, while vector control remains central to reducing transmission. Moreover, the development of novel diagnostic tools, treatments, and vaccines is a crucial step in advancing control efforts. This review also highlights the involvement of local governments, international organizations, and civil society in executing these strategies, stressing the need for sustained political commitment to ensure the success of public health programs. By addressing key challenges in monitoring, control, and prevention, this review aims to provide insights and recommendations to further global efforts in reducing the burden of Chagas disease. Full article

High-flying insects that exploit tropospheric winds can disperse over far greater distances in a single generation than species restricted to below-canopy flight. However, the ecological consequences of such long-range dispersal remain poorly understood. For example, high-altitude dispersal may facilitate more rapid range shifts in these species and reduce their sensitivity to habitat fragmentation, in contrast to low-flying insects that rely more on terrestrial patch networks. Previous studies have primarily used surface-level variables with limited spatial coverage to explore dispersal timing and movement. In this study, we introduce a novel application of niche modelling to insect aeroecology by examining the relationship between a comprehensive set of atmospheric conditions and high-flying insect activity in the troposphere, as detected by weather surveillance radars (WSRs). We reveal correlations between large-scale dispersal events and atmospheric conditions, identifying key variables that influence dispersal behaviour. By incorporating high-altitude atmospheric conditions into niche models, we achieve significantly higher predictive accuracy compared with models based solely on surface-level conditions. Key predictive factors include the proportion of arable land, altitude, temperature, and relative humidity. Full article

Spodoptera frugiperda (J.E. Smith) (Noctuidae: Lepidoptera) is a notable insect pest that invades major cereal crops, causing significant damage and loss. Resistances of 2nd instar larvae of two Egyptian field populations of S. frugiperda, collected from the Fayoum and Giza governments, were measured against eight insecticides, including traditional insecticides (profenofos and cypermethrin), bio-insecticides (emamectin benzoate, spinosad, and Bacillus thuringiensis), and insect growth regulators (IGRs) (lufenuron, diflubenzuron, and methoxyfenozide). In addition, the synergistic effects of three synergists (Piperonyl butoxide (PBO), diethyl maleate (DEM), and triphenyl phosphate (TPP) were assessed, and the activities of detoxification enzymes (acetylcholine esterase (AChE), cytochrome P-450 (CYP-450), carboxylesterase (CarE), and glutathione-s-transferase (GST) were also determined. Resistance surveillance revealed that the Fayoum field population showed moderate resistance to cypermethrin (RR = 5.75-fold), followed by spinosad (RR = 2.62-fold), and lufenuron (2.01-fold). On the other hand, the Giza population exhibited significant resistance to cypermethrin only (RR = 3.65-fold). Our results revealed that emamectin benzoate was the most effective insecticide, with an LC₅₀ value of 0.003 mg/L for the Fayoum population and 0.001 mg/L for the Giza population, compared to the susceptible strain (0.005 mg/L). Among the biological insecticides, Bacillus thuringiensis was the least toxic insecticide of all the tested strains. Synergism assays indicated that DEM and TPP had the most synergistic effect on spinosad (SR = 8.00-fold for both), followed by PBO (SR = 5.71-fold) for the Fayoum population, compared with spinosad alone. The assay of detoxification enzymes showed that GST activity significantly (p < 0.05) increased in the two field strains compared to the susceptible strain. However, no significant changes were observed among the tested strains in CYP-450, CarE, or AChE. The findings of this study provide substantial insights into tracking and managing the development of insecticide resistance in S. frugiperda in Egypt. Full article

Vesicular stomatitis (VS) is a viral disease that affects horses, cattle, and swine that is transmitted by direct contact and hematophagous insects. In 2023, a multi-state outbreak of vesicular stomatitis New Jersey virus (VSNJV) occurred in California, Nevada, and Texas, infecting horses, cattle, and rhinoceros. To identify possible insect vectors, we conducted insect surveillance at various locations in San Diego County, CA, including at a wildlife park. CO₂ baited traps set from mid-May to mid-August 2023 collected 2357 Culicoides biting midges and 1215 Simulium black flies, which are insect genera implicated in VSNJV transmission. Insects were pooled by species, location, and date, then tested for viral RNA. Nine RNA-positive pools of Culicoides spp. and sixteen RNA-positive pools of Simulium spp were detected. Infectious virus was detected by cytopathic effect in 96% of the RNA-positive pools. This is the first report of VSNJV in wild-caught C. bergi, C. freeborni, C. occidentalis, S. argus, S. hippovorum, and S. tescorum. The vector competency of these species for VSNJV has yet to be determined but warrants examination. Active vector surveillance and testing during disease outbreaks increases our understanding of the ecology and epidemiology of VS and informs vector control efforts. Full article