Agricultural Pests Research Articles

Method of intelligent agricultural pest image recognition based on machine vision algorithm

In recent years, people have paid increasing attention to smart agriculture. Its core technology is to combine information technology such as computer vision with agricultural production. In agricultural production, the occurrence of pests and diseases can seriously affect agricultural production. Therefore, in agricultural production, the diagnosis and identification of agricultural pests and diseases is the key to improve crop yield. Traditional machine vision methods often rely on feature extraction and classifier design, lack of strong learning and generalization ability, and can not effectively control crop diseases and pests in a timely manner. In order to solve this problem, this paper designs an agricultural pest recognition system based on machine vision algorithm of fuzzy recognition theory, and applies it to agricultural pest recognition. Compared with the traditional machine vision method, this method has obvious advantages, and can effectively improve the monitoring and early warning ability of crop diseases and pests. The experimental results show that the highest recognition rate of the machine vision optimization algorithm based on fuzzy recognition theory is 98.06%, and the lowest recognition error rate is 5.83%. It can be seen that the machine vision recognition algorithm based on fuzzy recognition theory has good recognition effect and can be used in agricultural pest recognition system to help farmers carry out agricultural production and reduce economic losses caused by diseases and pests.

Characterisation of the bacteriomes harboured by major wireworm pest species in the Canadian Prairies.

Nearly all insects harbour bacterial communities that can have a profound effect on their life history, including regulating and shaping host metabolism, development, immunity and fitness. The bacteriomes of several coleopterans have been described; however, very little has been reported for wireworms. These long-lived larvae of click beetles (Coleoptera: Elateridae) are major agricultural pests of a variety of crops grown in the Canadian Prairies. Consequently, the goal of this study was to characterise the bacteriomes of five of the most significant pest species within the region: Limonius californicus, Hypnoidus abbreviatus, H. bicolor, Aeolus mellillus and Dalopius spp. To do this, we collected larvae from southern Manitoba fields (pre-seeding) and carried out 16S rRNA sequencing on individual specimens. Our results indicate wireworms have diverse and taxon-rich bacterial communities, with over 400 genera identified predominately from the phyla Proteobacteria, Actinobacteriota, Bacteroidota and Firmicutes. However, each species had nine or fewer genera comprising >80% of their bacteriome. Network analyses revealed some community structuring consistent among species, which may culminate in shaping/regulating host biology. Moreover, the microbial signatures were influenced by both ontogeny (early vs. late stage larvae) and reproductive strategy (sexual vs. parthenogenetic), with a myriad of other factors likely contributing to bacterial diversity that are impossible to resolve from our study. Overall, this metagenomics study represents the first to characterise the bacteriomes of wireworms in the Canadian Prairies and the findings could assist in the development of sustainable management strategies for these important agricultural pests.

Conserved fungal effector NLS1 suppresses Lepidoptera insect immunity by targeting the host defense protein Hdd11.

Entomopathogenic fungi have been widely used as the main mycoinsecticide for controlling agricultural and forest pests. The effector molecules of these mycopathogens have evolved to adapt to their hosts. The role of fungal effectors in evading the host immune system in insects remains mainly unclear. We characterized the widely distributed fungal effector necrosis-inducing-like secreted protein 1 (NLS1) in the entomopathogenic fungus Metarhizium robertsii. Our findings revealed the presence of M. robertsii NLS1 (MrNLS1) in host hemocytes during the early stage of hemocoel infection. MrNLS1 knock down (ΔMrNLS1) reduced fungal pathogenicity during infection and altered the expression of host immune genes. The molecular docking results and the yeast 2-hybrid assay confirmed that MrNLS1 interacts with the host defense protein Hdd11. The phylogenetic analysis indicated that Hdd11 is conserved across a broad range of Lepidoptera species. Knock down of hdd11 in Helicoverpa armigera, Bombyx mori, and Galleria mellonella markedly suppressed their immune responses against M. robertsii. However, no significant difference was observed in the mean lethal time between hdd11-knockdown Lepidoptera species infected with ΔMrNLS1 and those infected with wild-type M. robertsii. Therefore, in Lepidoptera insects, Hdd11 is essential for fungal defense. In conclusion, M. robertsii infects Lepidoptera insects by targeting host Hdd11 through its protein MrNLS1, thereby suppressing the host immune response. Our findings clarify the molecular mechanisms underlying fungal infection pathogenesis.

Identification and expression profiling of neuropeptides and neuropeptide receptor genes in a natural enemy, Coccinella septempunctata.

Neuropeptides and their receptors constitute diverse and abundant signal molecules in insects, primarily synthesized and released primarily from neurosecretory cells within the central nervous system Neuropeptides act as neurohormones and euromodulators, regulating insect behavior, lifecycle, and physiology by binding to receptors on cell surface. As a typical natural predator of agricultural pests, the lady beetle, Coccinella septempunctata, has been commercially mass-cultured and widely employed in pest management. Insect diapause is a physiological and ecological adaptative strategy acquired in adverse environments. In biological control programs, knowledge about diapause regulation in natural enemy insects provides important insight for improving long-term storage, transportation, and field adoption of these biological control agents. However, little is known about the function of neuropeptides and their receptors in controlling reproductive diapause of C. septempunctata. It is unclear which neuropeptides affect diapause of C. septempunctata. In this study, RNA-seq technology and bioinformatics were utilized to investigate genes encoding neuropeptides and their receptors in female adults of C. septempunctata. Quantitative real-time PCR (qRT-PCR) analysis was employed to examine gene expression across different development/diapause stages. A total of 17 neuropeptide precursor genes and 9 neuropeptide receptor genes were identified, implicated in regulating various behaviors such as feeding, reproduction, and diapause. Prediction of partial mature neuropeptides from precursor sequences was also performed using available information about these peptides from other species, conserved domains and motifs. During diapause induction, the mRNA abundance of AKH was notably higher on the 10th day compared to non-diapause females, but decreased by the 20th day. In contrast, GPHA showed lower expression levels on the 5th day of diapause induction compared to non-diapause females, but increased significantly by the 15th and 20th days. NPF was higher expressed in head and midgut while DH showed higher expression in the fat body and midgut. Additionally, NPF expression remained consistently lower throughout all stages of diapause induction compared to non-diapause conditions in females. This study represents the first sequencing, identification, and expression analysis of neuropeptides and neuropeptide receptor genes in C. septempunctata. Our results could provide a foundational framework for further investigations into the presence, functions, and potential targets of neuropeptides and their receptors, particularly in devising novel strategies for diapause regulation in C. septempunctata.

Mitochondrial DNA sequence-based identification of two subterranean termite species, from Riyadh Province, Kingdom of Saudi Arabia.

Termites are economically important wood-destroying and agricultural pests. The termite fauna almost consists of 2900 described species in 286 genera worldwide. In the present study, hundreds of termite samples from 42 different locations in the Riyadh province were collected. These samples were previously used for morphometric identification and reported two subterranean termite species, Coptotermes heimi and Psammotermes hypostoma, in the family Rhinotermitidae. In the present study, these samples were analysed using DNA barcoding with the mitochondrial cytochrome c oxidase subunit 1 gene to confirm the conventional taxonomical identification on a molecular basis. The obtained COI gene sequences of all 42 termite specimens were submitted to GenBank (accession numbers: ON529959-ON529969, OP825131-OP825132, and OP890882-OP890910). Eleven of the 42 samples were thus identified as C. heimi and the remaining 31 samples as P. hypostoma, which were phylogenetically analysed. All the 11 C. heimi sequences were grouped in a single clade, indicating close relatedness. While 31 sequences of P. hypostoma constituted two clades in the phylogenetic tree. Pairwise nucleotide sequence identity and divergence analysis showed that C. heimi sequences showed high nucleotide identities of 87.6-99.5% and less divergence ranging from 0.5% to 13.6%. Similarly, sequences of P. hypostoma also showed high nucleotide identity of 78.6-100% and low divergence among them ranging from 0-10.7%. A further application, significance, and shortcomings of COI-based DNA barcoding have been discussed. DNA barcoding using the COI gene is a reliable tool to distinguish C. heimi and P. hypostoma genotypes.

Annotated checklist of chalcidid (Hymenoptera: Chalcididae) fauna of the Chhattisgarh region

Chalcidid wasps are a diverse group of insects belonging to the order Hymenoptera and family Chalcididae. They are natural biocontrol agents for many agricultural and forestry pests. The present study was undertaken from 2021 to 2023. The objective of this study was to document the Chalcididae diversity from the Chhattisgarh region. Based on this study, the first checklist of chalcidid wasps from Chhattisgarh state is prepared. In total, 71 species of chalcidid wasps were collected from 11 genera falling under four subfamilies. The chalcidid wasps identified belonged to the subfamilies, Chalcidinae, Dirhininae, Epitraninae and Haltichellinae of which, subfamily Haltichellinae was found to be most predominant. The results of this preliminary study shed light on the hidden biodiversity of chalcidid wasps.

First Report of <i>Tetrastichus howardi</i> (Olliff) and <i>Chelonus formosanus</i> Sonan as parasitoids of fall armyworm, <i>Spodoptera frugiperda</i> (J.E. Smith), in Pakistan

Fall armyworm, Spodoptera frugiperda (J.E. Smith), an invasive agricultural pest, causes substantial economic losses in Pakistan. This study reports the first record of Tetrastichus howardi (Olliff) and Chelonus formosanus Sonan as natural enemies parasitising S. frugiperda within the country. Parasitoids were collected from infested maize fields and identified through morphological analysis. This discovery enhances our understanding of the natural enemy complex associated with S. frugiperda in Pakistan and provides a foundation for investigating their potential as biological control agents. These findings underscore the potential of these parasitoids as components of integrated pest management systems to diminish reliance on chemical insecticides and foster sustainable agricultural practices.

Pest Detection Based on Lightweight Locality-Aware Faster R-CNN

Accurate and timely monitoring of pests is an effective way to minimize the negative effects of pests in agriculture. Since deep learning-based methods have achieved good performance in object detection, they have been successfully applied for pest detection and monitoring. However, the current pest detection methods fail to balance the relationship between computational cost and model accuracy. Therefore, this paper proposes a lightweight, locality-aware faster R-CNN (LLA-RCNN) method for effective pest detection and real-time monitoring. The proposed model uses MobileNetV3 to replace the original backbone, reduce the computational complexity, and compress the size of the model to speed up pest detection. The coordinate attention (CA) blocks are utilized to enhance the locality information for highlighting the objects under complex backgrounds. Furthermore, the generalized intersection over union (GIoU) loss function and region of interest align (RoI Align) technology are used to improve pest detection accuracy. The experimental results on different types of datasets validate that the proposed model not only significantly reduces the number of parameters and floating-point operations (FLOPs), but also achieves better performance than some popular pest detection methods. This demonstrates strong generalization capabilities and provides a feasible method for pest detection on resource-constrained devices.

Sublethal effects of emamectin benzoate on biological characteristics and the expression of vitellogenin (SgVg) and its receptor in Sclerodermusguani

Emamectin benzoate (EMB) is a commonly used insecticide for controlling agricultural and forest pests. To facilitate its rational use in integrated pest management (IPM), the sublethal effects of EMB on the development and reproduction of Scleroderma guani were evaluated. Sublethal doses of EMB (LD10 and LD30) significantly reduced the longevity and fecundity of F0 females. In the F1 generation, sublethal doses significantly reduced larval development duration and male longevity but significantly extended female longevity. Additionally, the LD30 treatment significantly decreased the number of laid eggs in F1 females by 20.72% compared with the control group. The net reproductive rate (R0) was significantly declined by the LD30 treatment compared with the control group (CK). Furthermore, the mean generation time (T) was significantly extended in both LD10 and LD30 treatment groups. Compared to the control group, the expression of SgVg and SgVgR genes in the LD10 and LD30 groups was significantly lower, which may be a crucial factor for the reduced fecundity of the females. These results indicate that sublethal doses of EMB significantly reduced adult longevity and fecundity of S. guani. The findings are practical for developing IPM strategies for forestry pests using S. guani and EMB.

Loss-of-function in testis-specific serine/threonine protein kinase triggers male infertility in an invasive moth

Genetic biocontrol technologies present promising and eco-friendly strategies for the management of pest and insect-transmitted diseases. Although considerable advancements achieve in gene drive applications targeting mosquitoes, endeavors to combat agricultural pests have been somewhat restricted. Here, we identify that the testis-specific serine/threonine kinases (TSSKs) family is uniquely expressed in the testes of Cydia pomonella, a prominent global invasive species. We further generated male moths with disrupted the expression of TSSKs and those with TSSKs disrupted using RNA interference and CRISPR/Cas9 genetic editing techniques, resulting in significant disruptions in spermiogenesis, decreased sperm motility, and hindered development of eggs. Further explorations into the underlying post-transcriptional regulatory mechanisms reveales the involvement of lnc117962 as a competing endogenous RNA (ceRNA) for miR-3960, thereby regulating TSSKs. Notably, orchard trials demonstrates that the release of male strains can effectively suppress population growth. Our findings indicate that targeting TSSKs could serve as a feasible avenue for managing C. pomonella populations, offering significant insights and potential strategies for controlling invasive pests through genetic sterile insect technique (gSIT) technology.

Chromosome-scale genome of the polyphagous pest Anastrepha ludens (Diptera: Tephritidae) provides insights on sex chromosome evolution in Anastrepha.

The Mexican fruit fly, Anastrepha ludens, is a polyphagous true fruit fly (Diptera: Tephritidae) considered one of the most serious insect pests in Central and North America to various economically relevant fruits. Despite its agricultural relevance, a high-quality genome assembly has not been reported. Here, we described the generation of a chromosome-level genome for the A. ludens using a combination of PacBio high fidelity long-reads and chromatin conformation capture sequencing data. The final assembly consisted of 140 scaffolds (821 Mb, N50 = 131 Mb), containing 99.27% complete conserved orthologs (BUSCO) for Diptera. We identified the sex chromosomes using three strategies: 1) visual inspection of Hi-C contact map and coverage analysis using the HiFi reads, 2) synteny with Drosophila melanogaster, and 3) the difference in the average read depth of autosomal versus sex chromosomal scaffolds. The X chromosome was found in one major scaffold (100 Mb) and eight smaller contigs (1.8 Mb), and the Y chromosome was recovered in one large scaffold (6.1 Mb) and 35 smaller contigs (4.3 Mb). Sex chromosomes and autosomes showed considerable differences of transposable elements and gene content. Moreover, evolutionary rates of orthologs of A. ludens and Anastrepha obliqua revealed a faster evolution of X-linked, compared to autosome-linked, genes, consistent with the faster-X effect, leading us to new insights on the evolution of sex chromosomes in this diverse group of flies. This genome assembly provides a valuable resource for future evolutionary, genetic, and genomic translational research supporting the management of this important agricultural pest.

Microbial Biopesticides: An Ecofriendly Plant Protection Measures

Microbial pesticides possess active microbes capable of controlling plant pests in agriculture, horticulture, and forests. Microbes benefit plants through metagenomics, metabolomics, and strain enhancement efforts, keeping the loss below the economic threshold. The study looked at over 50 years of literature from various sources. Other investigations combined the factors used in this review study. They are biologically effective in controlling plant disease and insect pests. Since the modern agroecosystem depends more on chemical-based pesticides for pest control, microbial biopesticides are gaining popularity in terms of their natural, eco-friendly, and cost-effectiveness. Furthermore, the higher demand for organic food products further propels the future market for microbial pesticides. This review updates the mechanisms of controlling insect pests and plant diseases through biological control using biopesticides.

Few-shot agricultural pest recognition based on multimodal masked autoencoder

Visual recognition methods based on deep convolutional neural networks have performed well in pest diagnosis and have gradually become a research hotspot. However, agricultural pest recognition faces challenges such as few-shot learning, category imbalance, similarity in appearance, and small pest targets. Existing deep learning-based pest recognition methods typically rely solely on unimodal image data, which results in a model whose recognition performance is heavily dependent on the size and quality of the annotated training dataset. However, the construction of large-scale, high-quality pest datasets requires significant economic and technical costs, limiting the practical generalization of existing methods for pest recognition. To address these challenges, this paper proposes a few-shot pest recognition model called MMAE (multimodal masked autoencoder). Firstly, the masked autoencoder of MMAE integrates self-supervised learning, which can be applied to few-shot datasets and improves recognition accuracy. Secondly, MMAE embeds textual modal information on top of image modal information, thus improving the performance of pest recognition by utilizing the correlation and complementarity between the two modalities. The experimental results show that MMAE is the most effective for pest identification compared with the existing excellent models, and the identification accuracy is as high as 98.12%, which is 1.61 percentage points higher than the current state-of-the-art MAE method. The work in this paper shows that the introduction of textual information can assist the visual coder in capturing agricultural pest characterization information at a higher level of granularity, providing a methodological reference for solving the problem of agricultural pest recognition under few-shot conditions.

Deltamethrin exposure caused renal inflammation and renal fibrosis via upregulating endoplasmic reticulum stress-mediated TXNDC5 level in mice

Deltamethrin (DLM) is a type II pyrethroid insecticide that is extensively applied to agriculture, veterinary medicine and livestock pest control. Excessive accumulation of DLM in the body can lead to nephrotoxicity, but the precise toxic mechanism remains obscure. Therefore, we established in vivo models of DLM-exposed mice for 30 days and in vitro models of DLM-exposed renal tubular epithelial cells of mice. The results revealed adverse effects on renal function in mice exposed to excessive DLM, manifested as endoplasmic reticulum (ER) swelling, local inflammatory infiltration in renal tissue and increased collagen fibers, suggesting renal inflammation and fibrosis, etc. Subsequently, in vivo experiments, we found that DLM exposure increased expression levels of endoplasmic reticulum stress (ERS)-related factors, significantly upregulated the expression of TXNDC5, and enhanced the colocalization of GRP78 with TXNDC5. Notably, DLM exposure also strengthened the co-localization of TXNDC5 with NF-κB p65 and TGF-β1, upregulated the expression levels of TLR4/MYD88/NF-κB and TGF-β/SMAD2/3 pathways, alongside inflammation and fibrosis-related factors, these changes exhibited a dose-dependent effect. Meanwhile, in vitro experiments, the results of ERS, inflammation, and fibrosis-related factor expression levels were consistent with those observed in vivo. In conclusion, our results demonstrated that TXNDC5 might played a certain role in DLM-induced nephrotoxicity. Specifically, DLM exposure could trigger ERS, increase TXNDC5 expression, and promote TLR4/MYD88/NF-κB and TGF-β/Smad2/3 pathways, leading to renal inflammation and fibrosis in mice. These discoveries not only deepen our understanding of DLM toxicity but also provide valuable avenues for exploring mitigation strategies and therapeutic interventions.

Functional analyses of dopamine receptors involved in virus transmission and reproduction in the small brown planthopper Laodelphax striatellus

Dopamine (DA) is the most abundant biogenic amine present in the insect central nervous system, and regulates multiple functions in physiology and behaviors through dopamine receptors (DARs). The small brown planthopper Laodelphax striatellus is an important agricultural pest and causes serious damage by transmitting diverse plant viruses, such as rice stripe virus (RSV). However, DARs have not yet been molecularly characterized in planthoppers, and their roles in virus infection and transmission remain largely unknown in insect vectors. In this study, we cloned four LsDARs (LsDOP1, LsDOP2, LsDOP3 and LsDopEcR) from L.striatellus. LsDARs share considerable sequence identity with their orthologous DARs, and cluster nicely with their corresponding receptor groups. The transcript levels of LsDARs varied in different developmental stages and adult tissues, with the highest expressions in the egg stage and in the brain. The expression levels of LsDARs were significantly higher in RSV-viruliferous L.striatellus. Knockdown of LsDOP2 and LsDOP3 significantly downregulated the expressions of viral genes of capsid protein (CP) and RNA3 segment (RNA3), while LsDOP1 knockdown upregulated their expressions. Silencing LsDopEcR upregulated and then downregulated CP and RNA3 expressions. Moreover, LsDOP2 and LsDOP3 knockdown significantly decreased the vertical transmission rates of RSV. Meanwhile, DA injection promoted RSV transmission and accumulation. We further demonstrated that silencing of LsDARs significantly altered the expressions of vitellogenin (LsVg) and Vg receptor (LsVgR). Furthermore, the reproduction performance of L.striatellus was reduced by LsDOP2 and LsDOP3 knockdown, but increased by LsDopEcR knockdown, and not affected by LsDOP1 silencing. These results provide critical information concerning the roles of DARs in virus transmission and reproduction in L.striatellus, and open the way for the development of innovative strategies for planthopper control.

Peruvian origin and global invasions of five continents by the highly damaging agricultural pest Liriomyza huidobrensis (Diptera: Agromyzidae).

Identification of the geographic origin of invasive species can be critical to effective management and amelioration of negative impacts in the introduced range. Liriomyza huidobrensis is a polyphagous leafmining fly that is a devastating pest of many vegetable and floriculture crops around the world. Considered native to South and possibly Central America, L. huidobrensis became invasive in the 1980s and has since spread to at least 30 countries on five continents. We used phylogeographic analysis of over 2 kb of mitochondrial cytochrome oxidase I and II sequence data from 403 field-collected specimens from both native and introduced populations to investigate the geographic origins of invasive L. huidobrensis worldwide. Within South America, there was substantial genetic variation, as well as the strong phylogeographic structure typical of a native range. In contrast, leafminers from the introduced range and Central America all contained little genetic variation and shared the same small set of haplotypes. These haplotypes trace to Peru as the ultimate geographic origin of invasive populations. Central America is rejected as part of the original geographic range of L. huidobrensis. Within Peru, the primary export region of Lima shared an extremely similar pattern of reduced haplotype variation to the invasive populations. An additional 18 specimens collected at US ports of entry did not share the same haplotype profile as contemporary invasive populations, raising perplexing questions on global pathways and establishment success in this species.

Generation and characterization of a novel ovariole cell line derived from Spodoptera frugiperda in China with sensitivity to both SfMNPV and AcMNPV

Spodoptera frugiperda multiple nucleopolyhedrovirus (SfMNPV), belonging to the species Alphabaculovirus spofrugiperdae, has been recently registered as an insecticide in China. This virus has a specific effect on the global major agricultural pest Spodoptera frugiperda. To gain insights into viral infection, replication processes, and the complex formation of viral particles, in vitro studies using cell lines are essential tools. Although the IPLB-Sf9 and IPLB-Sf21 cell lines derived from S. frugiperda are widely used for studies on the infection and replication mechanisms of Autographa californica multiple nucleopolyhedrovirus (AcMNPV), their capacity to produce viral polyhedra after SfMNPV infection is not optimal. To address this limitation, a novel cell line named IOZCAS-Sf-1 has been developed from a S. frugiperda population sourced Yunnan, China. The mitochondrial COX1 gene analysis confirmed the species origin of the IOZCAS-Sf-1 cell line. Furthermore, a comparative study was carried out to contrast the COX1 gene sequence of this novel cell line with that of IPLB-Sf9, highlighting the distinctions between the two. Importantly, the IOZCAS-Sf-1 cells exhibited a remarkable ability to generate polyhedra when infected with AcMNPV and SfMNPV, respectively. Consequently, this cellular lineage is considered a promising and valuable resource. It serves not only to investigate the molecular mechanisms of viral replication and its impact on host cells, but also to explore the transfection efficiency of SfMNPV DNA. This exploration further expands into its potential application in recombinant DNA experiments, laying a theoretical groundwork for the advancement of more effective biopesticides and sustainable agricultural practices.

An Aphid Pest Superclone Benefits From a Facultative Bacterial Endosymbiont in a Host-Dependent Manner, Leading to Reproductive and Proteomic Changes.

The English grain aphid, Sitobion avenae, is a significant agricultural pest affecting wheat, barley, and oats. In Chile, the most prevalent and persistent clone (superclone) of S. avenae harbors the facultative endosymbiont bacterium Regiella insecticola. To determine the role of this bacterium in the reproductive success of this superclone, the presence of R. insecticola was manipulated to assess its impact on (1) the reproductive performance of this clone on two host plant species (wheat and barley), (2) the production of winged morphs, (3) changes in the insects' proteomic profiles, and (4) the root/shoot ratio of plant. It was found that the reproductive performance of this S. avenae superclone varied across host plants, depending on the presence of the facultative bacterial endosymbiont. Aphids infected with R. insecticola showed higher reproductive success on wheat, while the opposite effect was observed on barley. Aphid biomass was greater when infected with R. insecticola, particularly on barley. Additionally, aphids harboring R. insecticola exhibited a higher proportion of winged individuals on both host plants. Protein regulation in aphids on wheat was lower compared to those on barley. A higher root/shoot biomass ratio was observed in wheat plants compared to barley when infested by R. insecticola-infected aphid. Thus, R. insecticola significantly influences the reproductive performance and proteomic profile of a S. avenae superclone, with these effects shaped by the host plant. This suggests that the interaction between the host plant and the facultative endosymbiont contributes to the ecological success of this superclone.

Design of a portable bioassay system based on highly efficent nanozyme and Au-DNA nanocluster: Toward current/colorimetric dual-signal detection of sugarcane smut

Sugarcane smut is a major agricultural pest affecting sugarcane yield and quality, posing a significant threat to the sustainable and healthy development of the global sugar industry. The best strategy for controlling Sugarcane smut is early and precise diagnosis. An intelligent mobile bio-platform is constructed based on Au-Co/Zn ZIF nanozymes and Au-DNA nanoclusters for current/colorimetric dual signal detection of the sugarcane smut pathogen. Efficient and specific cycling of the specific gene fragment (bE4′) for Sugarcane smut is achieved by strand displacement reaction. The output strand then forms Au-DNA nanoclusters with AuNPs-DNA, and the bioconjugate is captured by H2 probe, which results in the formation of more double-stranded structures, causing methylene blue (MB) to adsorb on electrode. The anodic nanozyme efficiently catalyzes the oxidation of glucose, generating a large number of electrons, and MB in the system is therefore reduced to MBH, causing a color change. This results in distinct current/colorimetric dual output signals, significantly enhancing the accuracy. A capacitor is further coupled with the system to improve the sensitivity. The detection signals are read in real-time by a smartphone. The developed method for sugarcane smut genes shows good linearity within a concentration range of 0.0001–10000 pM, with a detection limit as low as 23.59 aM (S/N = 3). This work integrates advanced technologies from various fields to create a portable sensing device with extremely high sensitivity and precision for detecting sugarcane smut. It provides a reliable new option for early and precise diagnosis of the disease and offers valuable theoretical and technical insights for early prevention, intelligent detection, and real-time monitoring of other plant diseases.

Identifying insect predators using camera traps reveal unexpected predator communities in oilseed rape fields

Cameras are common tools for ecologists studying species abundance, richness, and interactions. They are mainly used to study large animals but are increasingly used to study invertebrates. Camera traps could be a powerful tool to identify and quantify the natural enemies, such as predators, of specific agricultural pests. This knowledge can then be applied to adapt farming practices to favour the predators identified and improve conservation biocontrol.Here, cameras were used to identify predators of two insect pests of oilseed rape (Brassica napus): the pollen beetle (Brassicogethes aeneus) and the brassica pod midge (Dasineura brassicae). These insects are spring pests of oilseed rape and are both susceptible to predation by ground-dwelling arthropods during their development cycle. The objectives of this study were to 1) identify the predators of the pest species, and 2) investigate the hypothesis that the diel activity periods of the predators match the timing of pest larval presence on the ground. Field observations were conducted in two locations over two consecutive years in the UK.In contrast to previous reports, our data collected using cameras showed that larval stages of predatory beetles are responsible for most of the predation events and that adult stages were not frequently observed feeding on the prey. Our data also showed that the traditional method, using pitfall traps, failed to detect the presence of large numbers of beetle larvae. Interestingly, the pests dropped to the ground and were therefore most susceptible to predation at the time when predators were most active.These results give new insight on the predators of the two most important spring pests of oilseed rape in Europe. This knowledge can be used by practitioners to develop framing practices targeted on enhancing the abundance of the larval stages of these beneficial arthropods to better control the pests in a more sustainable way.