Orius laevigatus (Hemiptera, Anthocoridae) is a generalist predator extensively used for the biocontrol of diverse agricultural pests. Previous studies on O. laevigatus have focused on the improvement of insect genetic traits, but little is known about its association with microbes, especially viruses that may influence its production and efficacy. More than 280 RNA viruses have been described in other Hemiptera insects, in line with the continuous discovery of insect-specific viruses (ISVs) boosted by next-generation sequencing. In this study, we characterized the repertoire of RNA viruses associated with O. laevigatus. Its virome comprises 27 RNA viruses, classified within fourteen viral families, of which twenty-three viruses are specific to O. laevigatus and four are likely associated with fungal microbiota. The analysis of viral abundance in five O. laevigatus populations confirmed the presence of simultaneous viral infections and highlighted the ubiquitous presence and high abundance of one solinvivirus and three totiviruses. Moreover, we identified 24 non-retroviral endogenous viral elements (nrEVEs) in the genome of O. laevigatus, suggesting a long-term relationship between the host and its virome. Although no symptoms were described in the insect populations under study, the high diversity of viral species and the high abundance of certain RNA viruses identified indicate that RNA viruses may be significant for the applicability and efficacy of O. laevigatus in biocontrol programs.

Soybean (Glycine max) is the world\'s most cultivated legume; currently, most of its varieties are Bt. Spodoptera spp. (Lepidoptera: Noctuidae) are important pests of soybean. An artificial neural network (ANN) is an artificial intelligence tool that can be used in the study of spatiotemporal dynamics of pest populations. Thus, this work aims to determine ANN to identify population regulation factors of Spodoptera spp. and predict its density in Bt soybean. For two years, the density of Spodoptera spp. caterpillars, predators, and parasitoids, climate data, and plant age was evaluated in commercial soybean fields. The selected ANN was the one with the weather data from 25 days before the pest\'s density evaluation. ANN forecasting and pest densities in soybean fields presented a correlation of 0.863. It was found that higher densities of the pest occurred in dry seasons, with less wind, higher atmospheric pressure and with increasing plant age. Pest density increased with the increase in temperature until this curve reached its maximum value. ANN forecasting and pest densities in soybean fields in different years, seasons, and stages of plant development were similar. Therefore, this ANN is promising to be implemented into integrated pest management programs in soybean fields.

Heavy metals are defined as an abiotic factor that affects the efficiency of biological pest control. This study constructed a cadmium (Cd)-polluted artificial diets-Hyphantria cunea-Arma chinensis food chain to analyze the effects of Cd exposure on the ability of A. chinensis to control H. cunea. The results revealed that Cd was transferred through the artificial diet to H. cunea larvae and A. chinensis nymphs via a biological amplification effect. After feeding on Cd-accumulated H. cunea larvae, the body weight of A. chinensis nymphs reduced, mortality increased, developmental duration prolonged, and the expression of growth regulatory genes (EX, cycE, and MER) decreased. Cd activated the antioxidant defense system of the nymphs, accompanied by a significant enhancement in the contents of H2O2 and MDA, marked damage to the midgut sub-microstructure, and a remarkable induction in the expression of genes crucial for the mitochondrial pathway/ER stress-apoptosis pathway. Cd significantly diminished the contents of total amino acids, glucose, free fatty acids, and expression of the genes (HK2, PFK, IDH1, and IDH2) essential for the TCA cycle and glycolysis in the nymphs. The preference of the A. chinensis nymphs to Cd-treated H. cunea larvae was evidently reduced. Cd diminished the search-ability, food intake, instantaneous attack rate, and maximum theoretical daily food intake but prolonged the feeding time of the nymphs. Taken together, Cd exposure reduces the ability of A. chinensis nymphs to control H. cunea and provides a new challenge for the efficiency of insect pest control using natural enemies. These findings have important reference value for optimizing pest control strategies in heavy metal polluted areas.

Urbanization is rapidly influencing the abundance and diversity of arthropods. Within urban systems, managed turfgrass is a prominent land cover which can support only a limited number of arthropod groups. To allow for more arthropod biodiversity and to support beneficial insects within turfgrass, increasing numbers of land managers are choosing to partially convert turf habitat to wildflower habitat using commercially available seed mixes. However, the population dynamics of arthropod groups in these systems are poorly known, with consequentially little information on best long-term practices for managing wildflower habitats in turfgrass systems. To address this gap, we sampled insects using pan traps in turfgrass systems pre- and post-implementation of wildflower habitats and examined the change in abundance of several insect families and functional guilds. Insect groups had variable responses to wildflower habitat implementation, with some groups such as sweat bees and skipper butterflies showing a decline two years post-implementation. Other groups, such as predatory flies, were relatively more abundant one and two years post-implementation. These variable responses point to the need for more research on the long-term effects of wildflower habitats on beneficial insects in turfgrass habitats.

Biological control of weeds involves deliberate introduction of host-specific natural enemies into invaded range to reduce the negative impacts of invasive species. Assessing the specificity is a crucial step, as introduction of generalist natural enemies into a new territory may pose risks to the recipient communities. A mechanistic understanding of host use can provide valuable insights for the selection of specialist natural enemies, bolster confidence in non-target risk assessment and potentially accelerate the host specificity testing process in biological control. We conducted a comprehensive analysis of studies on the genomics of host specialization with a view to examine if genomic signatures can help predict host specificity in insects. Focusing on phytophagous Lepidoptera, Coleoptera and Diptera, we compared chemosensory receptors and enzymes between \"specialist\" (insects with narrow host range) and \"generalist\" (insects with wide host range) insects. The availability of genomic data for biological control agents (natural enemies of weeds) is limited thus our analyses utilized data from pest insects and model organisms for which genomic data are available. Our findings revealed that specialists generally exhibit a lower number of chemosensory receptors and enzymes compared with their generalist counterparts. This pattern was more prominent in Coleoptera and Diptera relative to Lepidoptera. This information can be used to reject agents with large gene repertoires to potentially accelerate the risk assessment process. Similarly, confirming smaller gene repertoires in specialists could further strengthen the risk evaluation. Despite the distinctive signatures between specialists and generalists, challenges such as finite genomic data for biological control agents, ad hoc comparisons, and fewer comparative studies among congeners limit our ability to use genomic signatures to predict host specificity. A few studies have empirically compared phylogenetically closely related species, enhancing the resolution and the predictive power of genomics signatures thus suggesting the need for more targeted studies comparing congeneric specialists and generalists.

Lablab (Lablab purpureus L.) is an important food and livestock feed legume that can also enhance soil fertility. However, its production is limited by insect pests, notably the black bean aphid (Aphis fabae). The present field study was conducted to determine the difference in the contribution of lablab genotypes and natural field margin vegetation (FMV) to the abundance and diversity of natural enemies and the damage, incidence, and abundance of bean aphids. Eighteen lablab genotypes were planted in the presence or absence of FMV in a randomized complete block design experiment replicated four times. Data on aphid abundance, incidence, and severity of damage were collected at four growth stages of the crop. Lablab genotypes significantly influenced aphid incidence, suggesting some level of tolerance to aphid colonization. Findings showed that lablab genotypes were a significant influence on natural enemy species richness with no statistical difference for abundance and natural enemy species diversity. However, the genotypes did not vary significantly in their influence on the number of aphid natural enemies. FMV was associated with low bean aphid damage. Overall, the presence or absence of FMV did not influence the number of natural enemies caught on the crop. This concurs with recent work that shows a similar number of natural enemies with field margin plants but may reflect the reduced number of pest insects. Cropping seasons influenced aphid abundance and damage severity, with the populations developing at the early stages of lablab development and decreasing as the crop advanced. This pattern was similar both in the presence or absence of FMV. The findings of this study highlight the important contribution of crop genotype together with the presence of field margin species in the regulation of aphids and their natural enemies in lablab.

Melanaphis sacchari (Zehntner;Hemiptera: Aphididae), sugarcane aphid (SCA), is an invasive phloem-feeder found worldwide with a wide host range of economically important plants including sorghum and sugarcane. Given its high reproductive capacity and ability to rapidly spread over long distances, SCA presents challenges for effective control, leading to substantial economic losses. Recent studies have identified two multiloci SCA genotypes specialized in feeding on sugarcane (MLL-D) and sorghum (MLL-F) in the USA, which raises concerns as the USA is the second largest sorghum-producing country. This has encouraged research towards identifying these two biotypes where some research has stated them as two species; MLL-D clade to be M. sacchari and MLL-F clade to be M. sorghi Theobald (Hemiptera: Aphididae), sorghum aphid (SA). This review aims at compiling research progress that has been made on understanding the SCA/SA species complex. Furthermore, this review also highlights a wide range of management strategies against SCA/SA that includes both biological and chemical methods. In addition, the review emphasizes studies examining host plant resistance to understand and evaluate the role of R-genes and phytohormones such as jasmonic acid, salicylic acid and ethylene against SCA. Beside this, plant volatiles and other secondary metabolites such as flavonoids, terpenes and phytanes are also explored as potential control agents. Being an invasive pest, a single management tactic is inadequate to control SCA population and hence, integrated pest management practices incorporating physical, cultural and biological control methods should be implemented with exclusive chemical control as a last resort, which this review examines in detail. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Herbivory is a major fitness pressure for plants and a key driver of crop losses in agroecosystems. Dense monocultures are expected to favor specialist herbivorous insects, particularly those who primarily consume crop species; yet, levels and types of herbivory are not uniform within regional cropping systems. It is essential to determine which local and regional ecological factors drive variation in herbivory in order to support functional agroecosystems that rely less on chemical inputs. Crops in the genus Cucurbita host a suite of both generalist and specialist herbivores that inflict significant damage, yet little is known about the relative contribution of these herbivores to variation in herbivory and how local- and landscape-scale Cucurbita resource concentrations, management practices, and natural enemies mediate this relationship. In this study, we tested whether three foundational ecological hypotheses influenced Cucurbita herbivory across 20 pumpkin fields in the semi-arid Southern High Plains Region of Texas. We used generalized linear mixed models and confirmatory path analysis to assess whether the Density-dependent Herbivory Hypothesis, Resource Concentration Hypothesis, or the Natural Enemies Hypothesis, could explain variation in Cucurbita herbivory and insect dynamics in the context of conventional agronomic practices. We found that herbivory increased over time, indicating that herbivores were causing sustained damage throughout the growing season. We also found that fields with higher local Cucurbita resources had lower herbivory, suggesting a resource dilution effect. Natural enemy communities were more abundant and taxonomically rich in sites with greater generalist herbivore abundance, though predator abundance declined over time, indicating that late-season crop fields are most at risk given high herbivory and low natural enemy-based control. Our findings also suggest that while local resource availability may drive the abundance and richness of arthropod communities, additional agronomic and phenological information is needed to anticipate herbivory risk in an agriculturally dominated landscape.

Insect pest control can be achieved by the application of RNA interference (RNAi), a key molecular tool in functional genomics. Whereas most RNAi research has focused on insect pests, few studies have been performed on natural enemies. Validating the efficacy of RNAi in natural enemies is crucial for assessing its safety and enabling molecular research on these organisms. Here, we assessed the efficacy of RNAi in the ladybird beetle Eriopis connexa Germar (Coleoptera: Coccinellidae), focusing on genes related to reproduction, such as vitellogenin (Vg) and its receptor (VgR). In the transcriptome of E. connexa, we found one VgR (EcVgR) and two Vg genes (EcVg1 and EcVg2). These genes have been validated by in silico analyses of functional domains and evolutionary relationships. Five-day-old females were injected with 500 ng/µL of a specific double-stranded RNA (dsRNA) (dsEcVg1, dsEcVg2, or dsEcVgR) for RNAi tests, while nonspecific dsRNA (dsGFP or dsAgCE8.1) was used as a control. Interestingly, dsEcVg2 was able to knockdown both Vg genes, while dsEcVg1 could silence only EcVg1. Additionally, the viability of the eggs was significantly reduced when both Vg genes were knocked down at the same time (after treatment with dsEcVg2 or \"dsEcVg1+dsEcVg2\"). Ultimately, malformed, nonviable eggs were produced when EcVgR was silenced. Interestingly, no dsRNA treatment had an impact on the quantity of eggs laid. Therefore, the feasibility of RNAi in E. connexa has been confirmed, suggesting that this coccinellid is an excellent Neotropical model for molecular research on natural enemies and for studying RNAi nontarget effects.

Effective management of fertilizers is essential in influencing the prevalence of insects in rice (Oryza sativa L.) fields. Over two years (2019-20 and 2020-21), an experiment conducted at Bangladesh Rice Research Institute (BRRI), Habiganj, during the boro season aimed to identify the most effective multidimensional treatment (EMT) by testing various combinations of chemical fertilizers and its effect on rice insects. The goal was to optimize rice grain yield while minimizing harmful insect infestation and supporting natural enemies. Eight different chemical fertilizer applications were used as follows: T1 contained a full mix of nitrogen (N), phosphorus (P), potassium (K), and sulfur (S); T2 had PKS but lacked N; T3 had NKS but lacked P; T4 had NPS but lacked K; T5 had NPK but lacked S; T6 had KS but lacked N and P; T7 had PS but lacked N and K; and T8 lacked all four elements - N, P, K, and S. The relationship between the dynamics of harmful insects and natural enemies was highly positively correlated (r = 0.72 to 0.97). In two consecutive growing years, the 2020-21 season exhibited notably higher counts of harmful insects, with Rice Leafroller (RLR) dominating in the booting stage and White Backed Planthopper (WBPH) in mid-tillering, while Green Mirid Bug (GMB) prevailed among natural enemies across both stages, surpassing insect pest counts, notably GMB, Lady bird beetle (LBB), Carabid beetle (CDB), and Staphylinid (STD). However, the yield was notably higher in the 2019-20 growing season despite these pest pressures. Throughout the mid-tillering and booting stages, T1 consistently exhibited the highest average populations of harmful insects and natural enemies, while T7 demonstrated the lowest count of harmful insects, followed by T2 at both growth stages. Additionally, the highest grain yield (GY) was consistently recorded in T1, followed by T5, T6, and T3, with yields of 7.98 t/ha, 7.63 t/ha, 7.38 t/ha, and 7.33 t/ha, respectively. In both stages, beneficial insects prevailed over harmful ones in all fertilizer applications, with significant declines noted in T2 and T7. Factor analysis showed successful selection for EMT in the MGIDI index for all variables except INT and GY during the 2019-20 season, with selection differentials (SD) ranging from -0.10 to 8.29. However, in 2020-21, selection was achieved for all variables with SD ranging from 0.37 to 6.08. According to the MGIDI index, the top-ranked EMTs were identified as T4 and T3 for the 2019-20 period, and T3 and T5 for the 2020-21 period. The EMT shared in both years, T3, proved effective because of its positive impact on enhancing natural enemies throughout both periods (with SD ranging from 4.76 to 8.29 for 2019-20 and 3.03 to 6.08 for 2020-21), and its notable contribution to rice grain yield (SD = 0.37) in 2020-21. This study uniquely integrates EMT to optimize rice grain yield while simultaneously managing harmful insect infestations and supporting natural enemies, addressing a critical need in sustainable rice cultivation. The suggestion is to give preference to fertilizer application T3, which omits P but contains N and K, to improve rice grain yield and boost natural enemies, thereby reducing harmful insect infestation. Moreover, future investigations should concentrate on refining fertilizer blends to strike a harmony between maximizing yield and fostering ecological robustness in rice cultivation.