Search Results (157)

Sitophilus zeamais Motschulsky (Coleoptera: Curculionidae) is one of the most destructive pests of stored grains worldwide. Sublethal concentrations of insecticides are known to influence insect behavior, potentially disrupting critical processes such as mating. This study investigated the effects of λ-cyhalothrin at the lethal concentration (LC) values LC₁₀ and LC₃₀ and lateralization on the mating behavior patterns of S. zeamais males. Results showed that the exposure to sublethal concentrations of λ-cyhalothrin significantly altered the copulation success rate and key time-related parameters, including mate recognition and copulation duration, while the lateralization caused significant differences in mating time-related parameters within each tested group (control, LC_10, and LC₃₀). Additionally, the λ-cyhalothrin-treated groups showed prolonged mate recognition times and required more mounting attempts to achieve mating. These findings highlight the potential of sublethal insecticide applications to control S. zeamais populations by impairing reproduction. Full article

In this study, the seeking behaviour and food acceptance of larvae of Plodia interpunctella Hübner (Lepidoptera: Pyralidae) were analysed under laboratory conditions. Larval orientation and feeding preferences were assessed using a selection arena for neonate larvae and a four-way olfactometer for third-instar larvae. Stimulants included amaranth bars with additives (honey and chocolate) and natural amaranth (toasted grain only). The results showed that amaranth volatiles influence the orientation and feeding behaviour of this polyphagous insect. A marked preference for sugar-rich foods was observed, with amaranth with honey and amaranth with chocolate being the food sources most frequently chosen by the neonate larvae. These individuals exhibited a gregarious feeding behaviour and did not engage in cannibalism. The third-instar larvae also showed a preference for sweet food but were more attracted to the amaranth–additive combination. In the four-way olfactometer bioassays, chocolate was the most frequently chosen stimulus, while cellophane did not differ significantly from air. An analysis of volatile compounds by gas chromatography mass spectrometry (GC-MS) revealed that amaranth with chocolate releases more volatile compounds (16) compared with honey (12) and natural amaranth (6), suggesting that these volatiles could possibly influence the larvae’s choice of food source. Full article

This study investigated the physiological regulatory mechanisms by which exogenous trehalose intake enhances the adaptation of the global stored-grain pest T. castaneum to high-concentration carbon dioxide (CO₂) stress. By supplementing exogenous trehalose under high-CO₂ controlled atmosphere stress, we measured the activities of key detoxification enzymes (e.g., carboxylesterase and cytochrome P450) and the levels of carbohydrate substances (e.g., glycogen, glucose, and trehalose). The results demonstrated that trehalose feeding significantly alleviated CO₂ induced mortality in T. castaneum and prolonged their survival time. In terms of detoxification metabolism, a trehalose-rich diet significantly reduced the activities of cytochrome P450 and carboxylesterase, while the glucose content in the beetles decreased markedly. These findings indicate that trehalose accumulation mitigates physiological damage caused by high-CO₂ stress in T. castaneum. Furthermore, exogenous trehalose intake did not disrupt carbohydrate metabolic homeostasis in the beetles, as trehalase activity and the levels of various carbohydrates remained relatively stable. This study elucidates the role of trehalose metabolism in T. castaneum’s adaptation to high-CO₂ environments, providing a theoretical foundation for optimizing controlled atmosphere grain storage technology and developing novel pest control strategies. Full article

Detecting stored-grain pests on the surface of the grain pile plays an important role in integrated pest management (IPM), which is crucial for grain security. Recently, numerous deep learning-based pest detection methods have been proposed. However, a critical limitation of existing methods is their inability to detect out-of-distribution (OOD) categories that are unseen during training. When encountering such objects, these methods often misclassify them as in-distribution (ID) categories. To address this challenge, we propose a one-stage framework named PestOOD for out-of-distribution stored-grain pest detection via flow-based feature reconstruction. Specifically, we propose a novel Flow-Based OOD Feature Generation (FOFG) module that generates OOD features for detector training via feature reconstruction. This helps the detector learn to recognize OOD objects more effectively. Additionally, to prevent network overfitting that may lead to an excessive focus on ID feature extraction, we propose a Noisy DropBlock (NDB) module and integrate it into the backbone network. Finally, to ensure effective network convergence, a Stage-Wise Training Strategy (STS) is proposed. We conducted extensive experiments on our previously established multi-class stored-grain pest dataset. The results show that our proposed PestOOD demonstrates superior performance over state-of-the-art methods, providing an effective AI-enabled solution to ensure grain security. Full article

Cowpea, Vigna sp., is an important, low-cost protein source in subtropical and semi-arid regions, where seasonal rainfall makes storage necessary. However, the weevils Callosobruchus maculatus and C. chinensis cause significant grain losses during storage. While synthetic fumigants are commonly used to control these pests, their risks to mammals have prompted the search for safer alternatives. In this context, we tested palo santo, Bursera graveolens, essential oil with limonene, α-phellandrene, o-cymene and β-phellandrene, menthofuran, and germacrene-D as a sustainable approach. This plant is readily accessible, produces high fruit yields, and is used in households for various purposes. We evaluated the fumigant toxicity, repellency, and ovicidal effects of B. graveolens essential oil on both Callosobruchus species. Our results showed that B. graveolens oil was toxic to C. maculatus (LC₅₀ = 80.90 [76.91–85.10] µL) and C. chinensis (LC₅₀ = 63.9 [60.95–66.99] µL), with C. chinensis being more susceptible (SR = 1.27). Molecular docking analyses revealed that all the oil’s compounds bind to both the GABA and octopamine receptors, exhibiting high energy affinities; however, germacrene shows the strongest affinity in these receptors. C. chinensis was strongly repelled at all concentrations, while C. maculatus was repelled only at lethal concentrations. No ovicidal effect was observed in either species. In conclusion, our findings suggest that B. graveolens essential oil is a promising and sustainable protectant for stored cowpeas in small-scale storage units. Full article

Effective stored-grain insect pest detection is crucial in grain storage management to prevent economic losses and ensure food security throughout production and supply chains. Existing detection methods suffer from issues such as high labor costs, environmental interference, high equipment costs, and inconsistent performance. To address these limitations, we proposed PDA-YOLO, an improved stored-grain insect pest detection algorithm based on YOLO11n which integrates three key modules: PoolFormer_C3k2 (PF_C3k2) for efficient local feature extraction, Attention-based Intra-Scale Feature Interaction (AIFI) for enhanced global context awareness, and Dynamic Multi-scale Aware Edge (DMAE) for precise boundary detection of small targets. Trained and tested on 6200 images covering five common stored-grain insect pests (Lesser Grain Borer, Red Flour Beetle, Indian Meal Moth, Maize Weevil, and Angoumois Grain Moth), PDA-YOLO achieved an mAP@0.5 of 96.6%, mAP@0.5:0.95 of 60.4%, and F1 score of 93.5%, with a computational cost of only 6.9 G and mean detection time of 9.9 ms per image. These results demonstrate the advantages over mainstream detection algorithms, balancing accuracy, computational efficiency, and real-time performance. PDA-YOLO provides a reference for pest detection in intelligent grain storage management. Full article

Sitophilus zeamais, a major pest of stored grains, causes significant post-harvest losses and challenges effective control. While synthetic insecticides pose risks of resistance and toxicity, essential oils (EOs) offer a safer alternative. However, the insecticidal potential of their individual volatile constituents (VCs) remains largely unexplored. This study evaluated the insecticidal activity of 51 EO-derived volatile compounds (VCs) against S. zeamais, identifying the most toxic ones, optimizing 15 synergistic mixtures, and assessing their effects on key insect enzymes. A structure–activity relationship (SAR) analysis determined functional groups associated with insecticidal activity, while a cluster analysis pre-selected 29 ternary mixtures, later refined using response surface methodology (RSM). Additionally, enzymatic assays explored their impact on detoxification and nervous system enzymes, providing insights into potential mechanisms of action. Among the 51 VCs tested, 37 exhibited significant toxicity, with 11 acting as fumigants and 13 displaying contact toxicity. Monocyclic monoterpenoids with ketone or alcohol functional groups and exocyclic unsaturation demonstrated the highest insecticidal activity via both exposure routes. Notably, pulegone enantiomers were particularly effective (LC₅₀ < 0.1 mg/L, LD₅₀ < 7.5 µg/adult). Among the optimized mixtures, 10 displayed strong insecticidal effects, 8 were active through both routes, and 5 exhibited synergistic fumigant interactions. The most effective formulations were M2 (R-pulegone + S-pulegone + S-carvone, LC₅₀ 0.48 mg/L) and M20 (isopulegone + δ-3-carene, LC₅₀ 2.06 mg/L), showing the strongest fumigant and synergistic effects, respectively. Enzymatic assays revealed that while some compounds mildly inhibited GST and CAT, others, such as δ-3-carene (IC₅₀ 0.19 mg/L), significantly inhibited AChE. Five mixtures exhibited synergistic neurotoxicity, with M20 (IC₅₀ 0.61 mg/L) and M12 (IC₅₀ 0.81 mg/L) emerging as the most potent AChE inhibitors. These findings highlight the potential of plant-derived volatile compounds as bioinsecticides, leveraging synergistic interactions to enhance efficacy, disrupt enzymatic pathways, and mitigate resistance. Full article

Stored wheat pests threaten food quality and economic returns, yet existing detection methods struggle with small-object detection, complex scenarios, and efficiency–accuracy trade-offs, largely due to the lack of high-quality datasets. To address these challenges, this study constructed MPest3 dataset for stored wheat pests and proposed an enhanced detection model, FCA-YOLO, based on YOLOv8. This multi-scale fusion architecture, combining pyramid feature extraction with adaptive spatial weighting, improves the detection of small pests through hierarchical feature integration. Experimental results demonstrate that FCA-YOLO enhances multi-scale feature extraction and spatial fusion, achieving a 2.06% increase in mAP, a 4.51% improvement in accuracy, and reducing the pre- and postprocessing time for each image. Compared to Faster-rcnn, FCA-YOLO achieves a better balance between accuracy and computational efficiency, providing a robust and efficient solution for intelligent pest monitoring in grain storage applications. Full article

Stored grain pests cause significant economic losses during cereal grain storage. Insecticides have long been central to pest control; however, growing concerns over resistance, environmental harm, and human health demand alternative strategies. Diatomaceous earth (DE) treatments are a safe, eco-friendly alternative to insecticides, although their efficacy depends on the temperature, humidity, dose, and insect species. This study assessed the insecticidal effects of two natively-sourced raw (Ankara and Aydin) and one commercial (Silico-Sec) DE treatments against the key pest species Rhyzopertha dominica (F.) and Sitophilus granarius (L.) on stored wheat. Five doses (0, 250, 500, 750, and 1000 ppm) of each DE treatment were tested under two temperatures (25 °C and 30 °C) and two humidity levels (40% and 60%). Mortality was assessed at 7, 14, and 21 days after treatment (DAT). All DE treatments caused higher mortality in S. granarius than R. dominica. The highest mortality occurred in S. granarius at 30 °C and 40% RH with the highest dose. Aydin DE was most effective, but did not reach 100% mortality in S. granarius by 21 DAT. In contrast, it caused 100% mortality in R. dominica under the same conditions. There was no F₁ progeny produced by surviving individuals of both species. Given the similarity of the environmental conditions to the optimal conditions for DE efficacy present in Turkish storage facilities, natively sourced Aydin DE is a promising control option. Full article

Stored product pests are controlled primarily through applying pyrethroid and organophosphate insecticides or through fumigation with phosphine (PH₃). However, several populations of weevils are resistant to these insecticides. Essential oils appear to be safe alternatives for both humans and the environment. The objective was to investigate the toxicity of Piper aduncum essential oil (PAEO) to Sitophilus zeamais and evaluate its effects on corn grain quality during the four-month storage period. This study was conducted in two stages. In the first stage, the toxicity of PAEO at concentrations lethal to 50 and 95% of insects (LC₅₀ and LC₉₅) was estimated. The second step evaluated the degree of infestation, water content, apparent specific mass, loss of mass, electrical conductivity, and percentage of germination of grains at 0, 30, 60, 90, and 120 days after exposure to PAEO, deltamethrin (pyrethroid), and the control treatment. PAEO presents toxicity to S. zeamais. The LC₅₀ and LC₉₅ values are 298.50 µL kg⁻¹ and 585.20 µL kg⁻¹, respectively. The increases in infestation degree, water content, electric conductivity, and mass loss, as well as reductions in apparent specific mass and germination, show the loss of corn quality during the 120-day storage period, being more significant when no product is applied. PAEO delays the loss of quality of the grains, presenting a greater capacity to preserve the grains for a longer period. Full article

The phasing out of most chemicals has created a demand for alternative methods to preserve grain quality and market value. Hermetic storage offers a chemical-free solution for pest control by creating an airtight environment that naturally leads to insect death. Adding oxygen scavengers can further enhance hermetic storage by accelerating oxygen depletion. However, no study has examined scaling hand warmers in hermetic storage bags used by large grain handlers and farmers. We evaluated the effects of 1, 2, or 3 hand warmers in 25-kg PICS bags and 2, 4, or 6 hand warmers in 50-kg PICS bags on oxygen consumption and grain quality. We hypothesized that doubling the number of hand warmers used in 25-kg to 50-kg PICS bags would maintain the same rate of oxygen reduction. Oxygen levels decreased as the number of hand warmers increased. Additionally, oxygen concentrations in 25-kg PICS bags with 1, 2, or 3 hand warmers closely mirrored those of 2, 4, or 6 hand warmers in 50-kg PICS bags, respectively. Using 2 or 3 hand warmers in 25-kg PICS bags and 4 or 6 hand warmers in 50-kg PICS bags reduced oxygen concentrations below the 5% threshold for pest suppression within 12 h and maintained it for at least 8 days. While a slight rise in relative humidity was observed with more hand warmers, this did not negatively affect seed moisture content or germination rates. Doubling hand warmers along with the bag size from 25 to 50 kg produced similar oxygen depletion rates. These findings are helpful for large grain handlers and farmers who use 50-kg hermetic bags to store seeds or specialty crops to maintain quality. Hermetic bags combined with hand warmers promote sustainability by reducing chemical usage and minimizing food and nutrient losses. Full article

The foreign grain beetle, Ahasverus advena (Waltl) (Coleoptera: Silvanidae), has been reported from 110 countries on more than 162 commodities, more than 35 types of facilities, and 14 other habitats such as compost heaps and haystacks or manure. Compost heaps, haystacks, and manure heated by fermentation may allow overwintering in cold climates, making them important sources of infestation. From these sources the A. advena can fly and infest grain storage and processing facilities. A. advena has been found in empty grain storage bins, is often found in wheat immediately after harvest, and is most abundant early in wheat storage. Larvae and adults of A. advena are well adapted to feeding on several species of fungi and have higher chitinase levels and greater tolerance for fungal aflatoxins than other species. A. advena lay more eggs on the fungal species on which their offspring can develop most successfully. They are attracted to fungal odors and high moisture commodities and have the capability to disseminate grain fungi that cause hot spots within the grain mass. The presence of fungus beetles is indicative of poor storage conditions. A. advena is capable of feeding on some commodities and is a predator that may have a potential role in biological control. They are strong fliers but are distributed extensively with the movement of commodities in the marketing system. In countries with a zero tolerance for insects, their presence is sufficient for rejection of a load and associated economic losses. In other countries, contamination by A. advena is a problem, and in India, it is listed as a quarantine pest. Extension agents have had many requests for the identification of this species, and two other species of the same genus have been found in stored products. Some information is available for the effectiveness of nine pest management methods for A. advena. Full article

Corn is one of the world’s most economically important cereal crops and can be attacked by Sitophilus zeamais. The control of S. zeamais is mostly based on synthetic insecticides; however, populations of this insect have developed resistance to various chemical compounds. New rational insecticides that prevent the development of resistant populations need to be continuously evaluated. This research aimed to assess the effects mediated by azadirachtin on S. zeamais populations in terms of mortality, survival, food preference, and repellency. Azadirachtin is toxic to S. zeamais at the larval (LC₅₀ = 3.36 ppm), pupal (LC₅₀ = 23.0 ppm), and adult (LC₅₀ = 37.7 ppm) stages. At all stages of insect development, the survival rate was 99.9% in insects not treated with azadirachtin, decreasing to 29.9%, 44.9%, and 68.5% in larvae, pupae, and adults treated with the LC₅₀ of the bioinsecticide, respectively. The preference for untreated corn grains was higher with the LC₂₅ and LC₅₀ of azadirachtin, while the LC₉₅ (209 ppm) repelled adults. Azadirachtin causes lethality in S. zeamais, compromising its survival and reducing the feeding preference on grains protected with repellent activity at high concentrations. Therefore, the use of this bioinsecticide may offer an alternative to control S. zeamais in the field and post-harvest. Full article

Background/Objectives: Phosphine resistance in insects involves a complex interplay of genetic and physiological factors, which are often poorly understood. Resistance to high concentrations of phosphine worldwide poses a formidable challenge for stored-product pest management and affects global food security. Understanding the genetic basis of phosphine resistance in the red flour beetle, Tribolium castaneum, is urgent because of the species’ status as a notorious insect pest of stored grains and their resistance to major classes of insecticides. In this study, we take advantage of T. castaneum as a model species for biological and genetic studies. Methods: To tease apart genetic mutations and the differential expression of genes responding to phosphine intoxication, we set up 16 different exposure tests to compare the effects of phosphine dose, exposure time, and sampling time on gene expression in phosphine-susceptible and -resistant T. castaneum adults. Results: We examined the enrichment of gene ontology terms in genes that were differentially expressed and found that the data further distinguished differences in gene expression by insect strain, phosphine dose, exposure time, and recovery from phosphine exposure. The gene-encoding cytochrome P450 9e2 was expressed more in phosphine-resistant compared to phosphine-susceptible insects under all treatment conditions and was significantly higher in expression in resistant insects that were sampled after short or long phosphine exposures. Therefore, this gene may serve as a new phosphine resistance marker in T. castaneum and can further be utilized as a diagnostic tool for resistance detection. Conclusions: These data are important to understand the complex molecular changes in insects that have reduced sensitivity to phosphine to develop new monitoring and resistance prevention strategies. Full article

Accurate, rapid, and intelligent stored-grain insect detection and counting are important for integrated pest management (IPM). Existing stored-grain insect pest detection models are often not suitable for detecting tiny insects on the surface of grain bulks and often require high computing resources and computational memory. Therefore, this study presents a YOLO-SGInsects model based on YOLOv8s for tiny stored-grain insect detection on the surface of grain bulk by adding a tiny object detection layer (TODL), adjusting the neck network with an asymptotic feature pyramid network (AFPN), and incorporating a hybrid attention transformer (HAT) module into the backbone network. The YOLO-SGInsects model was trained and tested using a GrainInsects dataset with images captured from granaries and laboratory. Experiments on the test set of the GrainInsects dataset showed that the YOLO-SGInsects achieved a stored-grain insect pest detection mean average precision (mAP) of 94.2%, with a counting root mean squared error (RMSE) of 0.7913, representing 2.0% and 0.3067 improvement over the YOLOv8s, respectively. Compared to other mainstream approaches, the YOLO-SGInsects model achieves better detection and counting performance and is capable of effectively handling tiny stored-grain insect pest detection in grain bulk surfaces. This study provides a technical basis for detecting and counting common stored-grain insect pests on the surface of grain bulk. Full article