Journal of economic entomology最新文献

Strawberry, Fragaria x ananassa Duchesne (Rosales: Rosaceae), is an important specialty crop in Florida, generating about $500 million in annual revenue. An invasive insect, chilli thrips, Scirtothrips dorsalis Hood (Thysanoptera: Thripidae), has emerged as a major strawberry pest, causing considerable yield and revenue loss in recent years. Pesticide application is the leading control option but is not always recommended due to resistance development. Host plant resistance (HPR) can be a novel option to manage S. dorsalis sustainably. Four commercial cultivars, 'Florida Brilliance', 'Florida Medallion FL16.30-128', 'Sweet Sensation 'Florida127', and 'Florida Pearl FL16.78-109', were evaluated for their performance in the 2021-2022 field season under the natural population of S. dorsalis. In 2022-2023 and 2023-2024, 3 more cultivars, 'Strawberry Festival', 'Florida Radiance', and 'Florida Beauty', were added to this list. Twenty bare-root strawberry transplants were planted in each field plot, and each cultivar was replicated 8 times in a randomized complete block design. Damage on trifoliate, number of adults and larval S. dorsalis on trifoliate, number of flowers, and marketable fruit yield were assessed for each cultivar. Results revealed that 'Florida Pearl 109' had the highest insect count and damage index of all 3 year. 'Strawberry Festival' also showed the same trend after its introduction in the second year. 'Florida Brilliance' and 'Sweet Sensation' had the lowest damage index, lowest adult insect count, and higher marketable yield compared to 'Florida Pearl 109' and 'Strawberry Festival'. Therefore, utilizing resistant cultivars can be an effective tool for managing S. dorsalis in the field.

The tea aphid Toxoptera aurantii Boyer (Hemiptera: Aphididae) is a destructive pest that infests tea plants. The resistance mechanisms of the tea plant against T. aurantii infestation are largely unexplored. This study investigates the defensive response of tea plants to T. aurantii feeding using an aphid-resistant Camellia sinensis cultivar 'Qiancha1' (QC1) and an aphid-susceptible C. sinensis cultivar 'Huangjinya' (HJY). Transcriptomics and metabolomics analyses were conducted on 4 samples: QCCK (T. aurantii non-infested QC1), HJYCK (T. aurantii non-infested HJY), QC24 (T. aurantii-infested QC1 for 24 h), and HJY24 (T. aurantii-infested HJY for 24 h). The results showed that the differentially expressed genes (DEGs) and differentially accumulated metabolites (DAMs) in the 2 comparison groups (QCCK vs. QC24 and HJYCK vs. HJY24) were primarily enriched in metabolic pathways, including hormone signal transduction, phenylpropanoid biosynthesis and flavonoid biosynthesis. Following aphid infestation, the resistant cultivar QC1 exhibited more DEGs and DAMs than the susceptible cultivar HJY, indicating a stronger response to T. aurantii feeding stress. Additionally, the expression of phenylpropanoid- and flavonoid-related genes (CYP, 4CL, FLS, F3H, and LAR) was significantly upregulated in the resistant cultivar QC1 compared with that in the susceptible cultivar HJY. Metabolites involved in phenylpropanoid/flavonoid pathways, such as p-coumaroyl-CoA, caffeoylquinic acid, and feruloyl-CoA, were exclusively induced in QC1. These findings suggest that phenylpropanoid/flavonoid pathways play pivotal roles in tea plant resistance to T. aurantii infestation, providing valuable insights for the breeding and utilization of resistant germplasms.

Tricolus simplicis Wood 1974 (Coleoptera: Curculionidae: Scolytinae) is reported to bore and reproduce on the branches of Robusta coffee (Coffea canephora) in Chiapas, Mexico. This is the first report of T. simplicis associated with Robusta coffee worldwide. The risk this insect poses for coffee production is discussed.

The fall armyworm Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae), a notorious invasive pest, has been widely monitored for insecticide resistance. Since its invasion of China in late 2018, early to mid-stage monitoring of resistance is particularly crucial to inform effective control strategies. Resistance ratios (RRs) derived from bioassays offer valuable insights into the overall resistance levels of field populations, while the detection of resistance allele frequencies helps uncover the potential causes of resistance variation. In this study, we established a baseline of susceptibility in third-instar larvae to 7 insecticides using a laboratory strain Xinzheng2019 and assessed the resistance levels of 9 populations collected from central and southern China between 2022 and 2023. Compared to the susceptible Xinzheng2019 strain, 2 field populations showed low-level resistance (RR = 5-10) to indoxacarb, and one exhibited low-level resistance to chlorantraniliprole. Minor resistance (RR = 3-5) was observed in 2 populations to lambda-cyhalothrin, 5 to indoxacarb, and 5 to chlorantraniliprole. All populations remained susceptible (RR < 3) to spinetoram, emamectin benzoate, chlorfenapyr, and lufenuron. Molecular analysis of 11 mutation sites across 3 key resistance-related genes (Ace-1, GluCl, and voltage-gated sodium channel [VGSC]) revealed that 52.1% of all tested samples carried either homozygous or heterozygous resistance alleles at the F290V locus of the Ace-1 gene, while no resistance mutations were detected at other sites. Our findings offer valuable insights into the insecticide resistance status of S. frugiperda field populations in China and provide guidance for effective chemical insecticide use.

Plant-specific insect scouting and prediction are still challenging in most crop systems. In this article, a machine-learning algorithm is proposed to predict populations during whiteflies (Bemisia tabaci, Hemiptera; Gennadius Aleyrodidae) scouting and aid in determining the population distribution of adult whiteflies in cotton plant canopies. The study investigated the main location of adult whiteflies relative to plant nodes (stem points where leaves or branches emerge), population variation within and between canopies, whitefly density variability across fields, the impact of dense nodes on overall canopy populations, and the feasibility of using machine learning for prediction. Daily scouting was conducted on 64 non-pesticide cotton plants, focusing on all leaves of a node with the highest whitefly counts. A linear mixed-effect model assessed distribution over time, and machine-learning model selection identified a suitable forecasting model for the entire canopy whitefly population. Findings showed that the top 3 to 5 nodes are key habitats, with a single node potentially accounting for 44.4% of the full canopy whitefly population. The Bagging Ensemble Artificial Neural Network Regression model accurately predicted canopy populations (R² = 85.57), with consistency between actual and predicted counts (P-value > 0.05). Strategic sampling of the top nodes could estimate overall plant populations when taking a few samples or transects across a field. The suggested machine-learning model could be integrated into computing devices and automated sensors to predict real-time whitefly population density within the entire plant canopy during scouting operations.

The Jack Beardsley mealybug, Pseudococcus jackbeardsleyi Gimpel & Miller (Hemiptera: Pseudococcidae), is a dangerous invasive pest that feeds on plants more than 115 genera from 54 families, and has spread over 59 countries or regions, often causing direct and indirect damage to host plants, and resulting in significant economic losses. In this study, we assessed the potential global distribution of P. jackbeardsleyi using a Maximum Entropy (MaxEnt) model under current and future climate scenarios. Here, we obtained prediction models with high credibility and accuracy, which showed that isothermality (Bio 3) and annual precipitation (Bio 12) were the environmental variables with the largest contribution on the potential distribution of this pest. The potential distribution areas predicted by this study were mainly located in South America, Central Africa, the southern regions of Asia and the eastern coast of Australia. Under future climate scenarios, the total geographical distribution of this pest will contract to varying degrees by the end of this century, but the highly suitable areas will increase. This study provides a reference for the development of control strategies, but also offers a scientific basis for the effective biological control of this pest.

Honey bees (Apis mellifera) are important pollinators for natural and cultivated species. Due to their high sensitivity to stressors, they are also valuable indicators of environmental changes and agricultural management practices. In this study, we compared the performance and incidence of pesticides over sentinel hives within forest remnants with those within linear forest fragments (LFF) surrounded by soybean fields under conventional management. Sentinel hives in LFF showed some signs of deterioration, such as colony collapse, low numbers of brood frames, and pesticide occurrences, but honey production and the number of adult bees were similar to hives in the forest. Soybean pollen was scarce in honey and absent in bee bread, suggesting that bees may be relying more on wild plant species. We detected 5 pesticides (azoxystrobin, carbendazim, chlorpyrifos, imidacloprid, and coumaphos) in hives both at forests and LFF in pollen, bee bodies, and wax; pesticides in honey were detected in old sentinel hives (2 yr of exposition to agricultural conventional management). Only 2 of the 5 pesticides were applied in one of the farms under study, highlighting the importance of considering landscape-scale agricultural management. Our results indicate that conventional agriculture of soybean/maize primarily affected the performance of beehives, and pesticides were detected in honey only after long exposure to hives. Beekeeping in soybean fields in the Chaco could be feasible if cautions were followed, such as the conservation of forest fragments and key plant species, appropriate pesticide schedules, coordinated applications among farms, and linear forest remnants improvements.

Balsam woolly adelgid, Adelges piceae (Ratz.) (BWA), invasive in North America, was first detected on subalpine fir [Abies lasiocarpa (Hook.) Nutt.] in several northern Utah counties in 2017. BWA phenology is known to vary by elevation and climate; a degree-day (DD) model focused on population expansion into the Intermountain West is needed. Bark samples were collected weekly from infested subalpine fir in early summer through late fall at 5 northern Utah sites from August 2020 to December 2022. At a single site, additional samples were collected biweekly to monthly during winter and spring. The presence of live individuals of all life stages in winter through early summer samples confirmed that life stages other than crawlers can successfully overwinter in northern Utah. Two generations were observed at all sites. Degree-day models were developed by fitting proportional adult counts and local air temperatures to Weibull distributions. Model fit was optimized with a 0 °C lower threshold, 30 °C upper threshold, and 1 Jan biofix. Completion of the first generation required 1,104 DD and 2 generations required 2,412 DD. Using the models and historical (1980 to 2020) temperatures, study sites were predicted to have thermal suitability for 2 generations at least 2 to 3 decades prior to detection in northern Utah, depending on site. Although upper estimates of future (2025 to 2099) predictions forecast a doubling of generations by 2060, knowledge of potential dormancies that may be disrupted in a changing climate is needed. The degree-day model will be a useful tool for predicting thermal suitability for future BWA expansion.

The black cutworm Agrotis ipsilon (Hufnagel) (Lepidoptera: Noctuidae) can damage the cotton seedlings and induce destructive yield loss. Seed coating with systemic insecticides is a cost-effective alternative to control A. ipsilon during the early stage of cotton, but the control efficacy and exposure risk to honeybees remain unclear. This study evaluated the control effects of the anthranilic diamide insecticide chlorantraniliprole on A. ipsilon in cotton crops and the corresponding exposure risks to honeybees. Field studies revealed the control efficacy of chlorantraniliprole at 2 or 4 g/kg seed was greater than 75%, which was comparable to its spray control during the seedling development stage. A residual toxicity trial revealed that chlorantraniliprole treatment had a dose-response control effect on A. ipsilon during the 19 days after sowing. The residue levels of chlorantraniliprole in the stem bases and soil were found consistent with the residual toxicity against A. ipsilon. In the cotton flowering period, the highest detection frequency and residue of chlorantraniliprole were found in pollen from the plots treated with 4 g/kg seed. By using 2 independent risk assessment approaches, the exposure risk of chlorantraniliprole seed treatments were evaluated to be acceptable to honeybees. Overall, chlorantraniliprole coated with 2 g/kg seed was an effective alternative for controlling A. ipsilon at the cotton seedling stages.

Intraguild predation (IGP) is a crucial ecological interaction that influences the dynamics of natural enemies and affects the effectiveness of biological control. Harmonia axyridis (Pallas) (Coleoptera: Coccinellidae), an invasive predator, significantly impacts native predators through IGP in certain countries. Pyemotes zhonghuajia (Yu, Zhang & He) (Prostigmata: Pyemotidae), a small ectoparasitoid, parasitizes various pests from the orders Lepidoptera, Coleoptera, and Hemiptera. Although both natural enemies are essential in controlling pests like Neotoxoptera formosana (Takahashi) (Hemiptera: Aphididae), their interactions and effects on pest management remain poorly understood. The study investigates the functional response of H. axyridis to N. formosana, the lethal ability of P. zhonghuajia against N. formosana, and how intraguild interactions affect the mortality rates of both N. formosana and H. axyridis when exposed to P. zhonghuajia. Our findings revealed that H. axyridis exhibited a Holling type II functional response to N. formosana, with female adults being the most effective predators. Pyemotes zhonghuajia demonstrated significant lethality against N. formosana, particularly at higher mite densities. However, the presence of P. zhonghuajia also increased the mortality rate of H. axyridis, highlighting a parasitism-driven intraguild interaction in which the mite dominates the predator. These results challenge conventional views of predator-parasitoid dynamics and highlight the complexity of interactions among natural enemies in pest control systems.