Nonnative pest establishment: Spatial patterns and public detection.

Early detection of new pests can reduce their long-term impacts by enabling more rapid management response. Knowledge of pest establishment risk and background rates of detection (e.g., by the public) can help inform more cost-effective targeting of formal early detection survey programs. Here we quantify county-level locational attributes associated with pest establishment and detection by the public using data for 113 new pest incursions detected in the United States from 2010 through 2018. Aligning with expectations, we find a higher likelihood of new pest establishment in counties with higher human population numbers, nearer to ports (<250 km), and with amenable climate characteristics. Controlling for potential sample selection issues, we find that pests are less likely to be first detected by the public (e.g., homeowners, community members) versus by other sources (e.g., agency surveys, researchers, or agricultural operators) in counties with higher total crop sales values and lower human population number. The negative association between public detection and high agricultural values may reflect greater survey efforts by other sources (e.g., by agency surveillance programs, researchers, and agricultural operators) in high-value agricultural areas. The positive association between public detection and human population size may reflect larger numbers of public detectors (i.e., people) available to encounter the pests. Our models provide spatially explicit estimates of the likelihood of new pest establishment across U.S. counties and of the likelihood that an established pest would first be detected by the public. These estimates can serve as quantitative inputs to decision-support activities for new pest surveillance planning.

Ethnobotanical insights on the management of plant pests and diseases by smallholder farmers in Mpumalanga Province of South Africa.

BACKGROUND: Pests and diseases are a major contributor to yield losses in sub-Saharan Africa, prompting smallholder farmers to seek cost-effective, accessible and ecologically friendly alternatives for crop protection. This study explored the management of pests and diseases affecting crops across eight selected villages in Ehlanzeni District, Mpumalanga Province, South Africa. METHODS: A total of 120 smallholder farmers were purposefully selected utilising the snowball technique. Information on the management of plant pests and diseases was collected through interviews and focus group discussions using semi-structured interview schedules. Ethnobotanical indices, including relative frequency of citation (RFC), use-value (UV) and informant consensus factor (Fic), were used to quantify and rank the plants used for crop protection in the study area. RESULTS: Twenty-three plant species (16 naturalised exotics and seven indigenous plants) belonging to 16 families were used for managing pests (vertebrates and invertebrates) and diseases (fungal and bacterial related) affecting crops in the study area. The dominant (100%) crops cultivated by the participants were Allium cepa L., Mangifera indica L., Solanum lycopersicum L. and Zea mays L. The RFC value ranged from 0.08 to 0.83 and the three most popular plants for crop protection were Capsium annuum L. (0.83), A. cepa (0.63) and Dichrostachys cinerea (L.) Wight & Arn. (0.43). In terms of the UV, the five most promising plants used as biocontrol were Tulbaghia violacea (0.13), A. cepa (0.12), C. annuum L. (0.09), Solanum campylacanthum Hochst. Ex A.Rich.(0.09) and Pinus pinaster (0.08). Based on the Fic, four categories were established and dominated by fungal diseases (0.64). Furthermore, T. violacea and A. cepa were the most often mentioned plants used against fungal conditions. Other categories cited were bacterial diseases (0.3), invertebrate pests (0.11) and vertebrate pests (0.14), an indication that smallholder farmers had limited agreement or common knowledge about the plants used for their management. The preparation methods included maceration (38%), decoction (38%) and burning (24%). Foliar application (67%) and soil drenching (33%) were used for administering plant extracts during the management of crop pests and diseases. CONCLUSION: The study highlights the importance of botanicals and associated indigenous knowledge among smallholder farmers in Mpumalanga Province, South Africa. It is pertinent to explore the valorisation of these botanicals by generating empirical data on their biological efficacies and phytochemical profiles.

Adapting pest management strategies to changing climates for the redlegged earth mite, Halotydeus destructor.

As climate change continues to modify temperature and rainfall patterns, risks from pests and diseases may vary as shifting temperature and moisture conditions affect the life history, activity, and distribution of invertebrates and diseases. The potential consequences of changing climate on pest management strategies must be understood for control measures to adapt to new environmental conditions. The redlegged earth mite (RLEM; Halotydeus destructor [Tucker]) is a major economic pest that attacks pastures and grain crops across southern Australia and is typically controlled by pesticides. TIMERITE® is a management strategy that relies on estimating the optimal timing (the TIMERITE® date) for effective chemical control of RLEM populations in spring. In this study, we assessed the efficacy of control at the TIMERITE® date from 1990 to 2020 across southern Australia using a simulation approach that incorporates historical climatic data and field experimental data on life history, seasonal abundance, and population level pesticide responses. We demonstrate that moisture and temperature conditions affect the life history of RLEM and that changes in the past three decades have gradually diminished the efficacy of the TIMERITE® strategy. Furthermore, we show that by incorporating improved climatic data into predictions and shifting the timing of control to earlier in the year, control outcomes can be improved and are more stable across changing climates. This research emphasises the importance of accounting for dynamic environmental responses when developing and implementing pest management strategies to ensure their long-term effectiveness. Suggested modifications to estimating the TIMERITE® date will help farmers maintain RLEM control outcomes amidst increasingly variable climatic conditions.

Bird Boxes and Sparrow Traps: The Technological Regulation of Avian Life in the United States.

Only a few decades after its introduction to the United States in the mid-nineteenth century, the house sparrow was considered a pest that drove away native birds. Its downfall is representative of a story familiar to scholars of animals and technology who have studied the methods used to control or exclude unwanted species from both rural and urban areas. The case of the house sparrow, however, differs in a crucial respect: the birds made their homes in bird boxes, built technologies designed to attract avian species and bring them closer to humans. This article documents how bird boxes were used as tools to regulate avian life in the late nineteenth and early twentieth centuries in the United States and argues that they should be seen as a technology that mediates and regulates our relationship with nature by promoting or controlling certain aspects of living organisms.

Immobilization of Bacillus thuringiensis Cry1Ac in metal-organic frameworks through biomimetic mineralization for sustainable pest management.

Traditional chemical pesticide dosage forms and crude application methods have resulted in low pesticide utilization, increased environmental pollution, and the development of resistance. Compared to traditional pesticides, nanopesticides enhance the efficiency of pesticide utilization and reduce the quantity required, thereby decreasing environmental pollution. Herein, Cry1Ac insecticidal crystal protein from Bacillus thuringiensis Subsp. Kurstaki HD-73 was encapsulated in a metal-organic framework (zeolite imidazolate framework-8, ZIF-8) through biomimetic mineralization to obtain Cry1Ac@ZIF-8 nanopesticides. The Cry1Ac@ZIF-8 nanopesticides exhibited a dodecahedral porous structure, and the introduction of Cry1Ac did not affect the intrinsic crystal structure of ZIF-8. The indoor toxicity analysis revealed that the toxicity of Cry1Ac towards Ostrinia furnacalis (Guenée), Helicoverpa armigera Hubner, and Spodoptera litura Fabricius was not affected by ZIF-8 encapsulation. Surprisingly, Cry1Ac@ZIF-8 still exhibited excellent pest management efficacy even after exposure to heat, UV irradiation, and long-term storage. More importantly, the encapsulation of ZIF-8 significantly enhanced the internal absorption performance of Cry1Ac in maize leaves and extended its persistence period. Thus, ZIF-8 could potentially serve as a promising carrier for the preparation of nanopesticides with enhanced applicability, stability, and persistence period, providing a powerful strategy to improve the application of Cry1Ac in future agricultural pest management.

[Effect of ground cage use on Oncomelania hupensis spread].

OBJECTIVE: To examine the effect of ground cage use on Oncomelania hupensis spread, so as to provide insights into precision snail control. METHODS: Twenty ground cages that were frequently used to capture rice field eels were purchased, including 11 packaging tape-made cages, 7 plastic cages and 2 nylon rope-made cages. The eel-capturing activity was mimicked, and 20 ground cages were assigned in settings with relatively high (1.00 snail/0.1 m2 and higher) and low snail densities (< 1.00 snail/0.1 m2) in Xindai Township, Pinghu City, Zhejiang Province during the period from 15 : 00 to 8 : 00 of the following day on April 13, 26 and 28. The numbers of snails carried by different types of ground cages were compared in settings with different types of snail densities using the rank-sum test. RESULTS: A total of 11 cage-times were assigned in settings with a high snail density, and a total of 77 snails were captured, with a mean number of 7 snails in each cage-time and 2.15 snails in 0.1 m2 ground cage. The mean numbers of snails carried by packaging tape-made and plastic cages were 2.47 snails/0.1 m2 cage and 0.37 snails/0.1 m2 cage, respectively. A total of 24 cage-times were assigned in settings with a low snail density, and a total of 8 snails were captured, with a mean number of 0.33 snails in each cage-time and 0.09 snails in 0.1 m2 ground cage. The mean numbers of snails carried by packaging tape-made cages were 0.12 snails/0.1 m2 cage; however, no snails were carried by plastic or nylon rope-made cages. The number of snails carried by ground cages was higher in settings with a high snail density than in settings with a low snail density (Z = -4.019, P < 0.01), and the number of snails carried by packaging tape-made cages was higher in settings with a high snail density than in settings with a low snail density (Z = -4.086, P < 0.01). No significant differences were found in the numbers of snails carried by different types of ground cages. CONCLUSIONS: The use of ground cage in snail habitats is a contributor to snail spread.

Fabrication and application of carrier-free and carrier-based nanopesticides in pest management.

Pesticides are widely used for pest control to promote sustained and stable growth of agricultural production. However, indiscriminate pesticide usage poses a great threat to environmental and human health. In recent years, nanotechnology has shown the ability to increase the performance of conventional pesticides and has great potential for improving adhesion to crop foliage, solubility, stability, targeted delivery, and so forth. This review discusses two types of nanopesticides, namely, carrier-free nanopesticides and carrier-based nanopesticides, that can precisely release necessary and sufficient amounts of active ingredients. At first, the basic characterization and preparation methods of these two distinct types of nanopesticides are briefly summarized. Subsequently, current applications and future perspectives on scientific examples and strategies for promoting the usage efficacy and reducing the environmental risks of these nanopesticides were also described. Overall, nanopesticides can promote higher crop yields and lay the foundation for sustainable agriculture and global food security.

Farmland pest recognition based on Cascade RCNN Combined with Swin-Transformer.

Agricultural pests and diseases pose major losses to agricultural productivity, leading to significant economic losses and food safety risks. However, accurately identifying and controlling these pests is still very challenging due to the scarcity of labeling data for agricultural pests and the wide variety of pest species with different morphologies. To this end, we propose a two-stage target detection method that combines Cascade RCNN and Swin Transformer models. To address the scarcity of labeled data, we employ random cut-and-paste and traditional online enhancement techniques to expand the pest dataset and use Swin Transformer for basic feature extraction. Subsequently, we designed the SCF-FPN module to enhance the basic features to extract richer pest features. Specifically, the SCF component provides a self-attentive mechanism with a flexible sliding window to enable adaptive feature extraction based on different pest features. Meanwhile, the feature pyramid network (FPN) enriches multiple levels of features and enhances the discriminative ability of the whole network. Finally, to further improve our detection results, we incorporated non-maximum suppression (Soft NMS) and Cascade R-CNN's cascade structure into the optimization process to ensure more accurate and reliable prediction results. In a detection task involving 28 pest species, our algorithm achieves 92.5%, 91.8%, and 93.7% precision in terms of accuracy, recall, and mean average precision (mAP), respectively, which is an improvement of 12.1%, 5.4%, and 7.6% compared to the original baseline model. The results demonstrate that our method can accurately identify and localize farmland pests, which can help improve farmland's ecological environment.

Landscape features support natural pest control and farm income when pesticide application is reduced.

Future trajectories of agricultural productivity need to incorporate environmental targets, including the reduction of pesticides use. Landscape features supporting natural pest control (LF-NPC) offer a nature-based solution that can serve as a partial substitute for synthetic pesticides, thereby supporting future productivity levels. Here, we introduce a novel approach to quantify the contribution of LF-NPC to agricultural yields and its associated economic value to crop production in a broad-scale context. Using the European Union as case study, we combine granular farm-level data, a spatially explicit map of LF-NPC potential, and a regional agro-economic supply and market model. The results reveal that farms located in areas characterized by higher LF-NPC potential experience lower productivity losses in a context of reduced synthetic pesticides use. Our analysis suggests that LF-NPC reduces yield gaps on average by four percentage points, and increases income by a similar magnitude. These results highlight the significance of LF-NPC for agricultural production and income, and provide a valuable reference point for farmers and policymakers aiming to successfully invest in landscape features to achieve pesticides reduction targets.

Enhancing arthropod occurrence in wheat cropping systems: the role of non-chemical pest management and nitrogen optimization.

This study analyzes arthropod biomass and abundance to track the changes in arthropod occurrence in relation to pesticide use in three winter wheat cropping systems managed at different intensities (organic, conventional, and hybrid). Arthropod occurrence was surveyed using three collection tools: sweeping nets, eclector traps, and yellow traps. Sampling was conducted over three years from 2020 to 2022 with 588 samples collected. The wet weight of the captured organisms was determined and arthropod abundance calculated. The application of a NOcsPS (no chemical-synthetic pesticides) strategy, a new hybrid cultivation method realized with optimized use of nitrogen fertilizers but without chemical-synthetic pesticides, showed a higher arthropod occurrence and performed more convincingly regarding produced arthropod biomass and abundance than the other cropping variants. The results also demonstrate a dependence of the obtained insect indices on the collection method. Although arthropod biomass and abundance correlated for all collection methods, the combination of various methods as well as multiple procedures of sample analysis gives a more realistic and comprehensive view of the impact of the wheat cultivation systems on the arthropod fauna than one-factor analyses.

Emerging trends to replace pesticides with nanomaterials: Recent experiences and future perspectives for ecofriendly environment.

Despite the widespread usage to safeguard crops and manage pests, pesticides have detrimental effects on the environment and human health. The necessity to find sustainable agricultural techniques and meet the growing demand for food production has spurred the quest for pesticide substitutes other than traditional ones. The unique qualities of nanotechnology, including its high surface area-to-volume ratio, controlled release, and better stability, have made it a promising choice for pest management. Over the past ten years, there has been a noticeable growth in the usage of nanomaterials for pest management; however, concerns about their possible effects on the environment and human health have also surfaced. The purpose of this review paper is to give a broad overview of the worldwide trends and environmental effects of using nanomaterials in place of pesticides. The various types of nanomaterials, their characteristics, and their possible application in crop protection are covered. The limits of the current regulatory frameworks for nanomaterials in agriculture are further highlighted in this review. Additionally, it describes how standard testing procedures must be followed to assess the effects of nanomaterials on the environment and human health before their commercialization. In order to establish sustainable and secure nanotechnology-based pest control techniques, the review concludes by highlighting the significance of taking into account the possible hazards and benefits of nanomaterials for pest management and the necessity of an integrated approach. It also emphasizes the importance of more investigation into the behavior and environmental fate of nanomaterials to guarantee their safe and efficient application in agriculture.

Effective pest management approaches can mitigate honey bee (Apis mellifera) colony winter loss across a range of weather conditions in small-scale, stationary apiaries.

Managed honey bee (Apis mellifera L.) colonies in North America and Europe have experienced high losses in recent years, which have been linked to weather conditions, lack of quality forage, and high parasite loads, particularly the obligate brood parasite, Varroa destructor. These factors may interact at various scales to have compounding effects on honey bee health, but few studies have been able to simultaneously investigate the effects of weather conditions, landscape factors, and management of parasites. We analyzed a dataset of 3,210 survey responses from beekeepers in Pennsylvania from 2017 to 2022 and combined these with remotely sensed weather variables and novel datasets about seasonal forage availability into a Random Forest model to investigate drivers of winter loss. We found that beekeepers who used treatment against Varroa had higher colony survival than those who did not treat. Moreover, beekeepers who used multiple types of Varroa treatment had higher colony survival rates than those who used 1 type of treatment. Our models found weather conditions are strongly associated with survival, but multiple-treatment type colonies had higher survival across a broader range of climate conditions. These findings suggest that the integrated pest management approach of combining treatment types can potentially buffer managed honey bee colonies from adverse weather conditions.

Developing agricultural pest management strategies with reduced-risks to surface water: An economic case study of California's Central Coast region.

Pesticides are critical for protecting agricultural crops, but the off-site transport of these materials via spray drift and runoff poses risks to surface waters and aquatic life. California's Central Coast region is a major agricultural hub in the United States characterized by year-round production and intensive use of pesticides and other chemical inputs. As a result, the quality of many waterbodies in the region has been degraded. A recent regulatory program enacted by the Central Coast Regional Water Quality Control Board set new pesticide limits for waterways and imposed enhanced enforcement mechanisms to help ensure that water quality targets are met by specific dates. This regulatory program, however, does not mandate specific changes to pest management programs. In this study, we evaluate the economic, environmental, and pest management impacts of adopting two alternative pest management programs with reduced risks to surface water: 1) replacing currently used insecticide active ingredients (AIs) that pose the greatest risk to surface water with lower-risk alternatives and 2) converting conventional arthropod pest management programs to organic ones. We utilize pesticide use and toxicity data from California's Department of Pesticide Regulation to develop our baseline and two alternative scenarios. We focus on three crop groups (cole crops, lettuce and strawberry) due to their economic importance to the Central Coast and use of high-risk AIs. For Scenario 1, we estimate that implementing the alternative program in the years 2017-2019 would have reduced annual net returns on average by $90.26 - $190.54/ha, depending on the crop. Increased material costs accounted for the greatest share of this effect (71.9%-95.6%). In contrast, Scenario 2 would have reduced annual net returns on average by $5,628.12 - $18,708.28/ha during the study period, with yield loss accounting for the greatest share (92.8-97.9%). Both alternative programs would have reduced the associated toxic units by at least 98.1% compared to the baseline scenario. Our analysis provides important guidance for policymakers and agricultural producers looking to achieve environmental protection goals while minimizing economic impacts.

From economic threshold to economic injury level: Modeling the residual effect and delayed response of pesticide application.

Integrated Pest Management (IPM) poses a challenge in determining the optimal timing of pesticide sprays to ensure that pest populations remain below the Economic Injury Level (EIL), due to the long-term residual effects of many pesticides and the delayed responses of pest populations to pesticide sprays. To address this issue, a specific pesticide kill-rate function is incorporated into a deterministic exponential growth model and a subsequent stochastic model. The findings suggest the existence of an optimal pesticide spraying cycle that can periodically control pests below the EIL. The results regarding stochasticity indicate that random fluctuations promote pest extinction and ensure that the pest population, under the optimal cycle, does not exceed the EIL on average, even with a finite number of IPM strategies. All those confirm that the modeling approach can accurately reveal the intrinsic relationship between the two key indicators Economic Threshold and EIL in the IPM strategy, and further realize the precise characterization of the residual effect and delayed response of pesticide application.

Efficient agricultural pest classification using vision transformer with hybrid pooled multihead attention.

Accurate pest classification plays a pivotal role in modern agriculture for effective pest management, ensuring crop health and productivity. While Convolutional Neural Networks (CNNs) have been widely used for classification, their limited ability to capture both local and global information hinders precise pest identification. In contrast, vision transformers have shown promise in capturing global dependencies and enhancing classification performance. However, the traditional attention mechanism employed in vision transformers, which uses the same query (Q), key (K), and value (V), overlooks spatial relationships between patches, limiting the model's capacity to capture fine-grained details and long-range dependencies in the image. To address these limitations, this study presents a novel approach, termed Hybrid Pooled Multihead Attention (HPMA), for superior pest classification that outperforms both CNN models and vision transformers. The HPMA model integrates hybrid pooling techniques and modifies the attention mechanism to effectively capture local and global features within images. By emphasizing discriminative features and suppressing irrelevant information, the HPMA model achieves heightened robustness and generalization capabilities. The model is trained and tested on a newly built dataset consisting of 10 pest classes, achieving a remarkable accuracy of 98 %. Furthermore, the proposed HPMA model is validated on two benchmark datasets and achieves accuracies of 98 % and 95 %, demonstrating its effectiveness across diverse pest datasets. The results and ablation study of the proposed model contribute to exceptional performance in accurate pest classification. This tackles agricultural pest challenges and enables prompt pest control to reduce crop losses.

Copper-based grape pest management has impacted wine aroma.

Despite the high energetic cost of the reduction of sulfate to H2S, required for the synthesis of sulfur-containing amino acids, some wine Saccharomyces cerevisiae strains have been reported to produce excessive amounts of H2S during alcoholic fermentation, which is detrimental to wine quality. Surprisingly, in the presence of sulfite, used as a preservative, wine strains produce more H2S than wild (oak) or wine velum (flor) isolates during fermentation. Since copper resistance caused by the amplification of the sulfur rich protein Cup1p is a specific adaptation trait of wine strains, we analyzed the link between copper resistance mechanism, sulfur metabolism and H2S production. We show that a higher content of copper in the must increases the production of H2S, and that SO2 increases the resistance to copper. Using a set of 51 strains we observed a positive and then negative relation between the number of copies of CUP1 and H2S production during fermentation. This complex pattern could be mimicked using a multicopy plasmid carrying CUP1, confirming the relation between copper resistance and H2S production. The massive use of copper for vine sanitary management has led to the selection of resistant strains at the cost of a metabolic tradeoff: the overproduction of H2S, resulting in a decrease in wine quality.

Do typologies of pesticide risk knowledge influence the adoption of IPM strategies? Evidence from rice farmers' behavior in northern Iran.

BACKGROUND: The active participation of farmers in adopting eco-friendly practices is vital to mitigate the environmental and health risks linked to pesticide usage. Farmers' awareness of these risks significantly influences their adoption of integrated pest management (IPM) methods over traditional pesticide applications. This study sought to explore the range of understanding on pesticide effects, categorize IPM strategies employed in pest management, and examine the correlation between knowledge levels and IPM strategy choices. Data was gathered through structured questionnaires from 391 rice farmers in Sari County, Mazandaran province, Northern Iran. RESULTS: Exploratory factor analysis revealed three distinct dimensions of pesticide risk knowledge: personal risk of pesticide, environmental risk of pesticide, and community risk of pesticide. Furthermore, the study identified three primary categories of IPM strategies: high familiarity, intermediate familiarity, and low familiarity. The results of the regression analysis indicated that the personal risk of pesticides (ß = 0.556; P < 0.01) and the environmental risk of pesticides (ß = 0.262; P < 0.01) are significantly correlated with the adoption of high familiarity IPM strategies. Furthermore, the study revealed that there was no significant statistical evidence to support the notion that different types of pesticide risk knowledge had any influence on the adoption of intermediate and low familiarity strategies. CONCLUSION: The findings of this study imply the critical importance for agricultural extension programs to focus on enhancing farmers' knowledge of pesticide risks and various IPM strategies. © 2024 Society of Chemical Industry.

Acute toxicity effects of pesticides on beneficial organisms - Dispelling myths for a more sustainable use of chemicals in agricultural environments.

Agricultural practitioners, researchers and policymakers are increasingly advocating for integrated pest management (IPM) to reduce pesticide use while preserving crop productivity and profitability. Using selective pesticides, putatively designed to act on pests while minimising impacts on off-target organisms, is one such option - yet evidence of whether these chemicals control pests without adversely affecting natural enemies and other beneficial species (henceforth beneficials) remains scarce. At present, the selection of pesticides compatible with IPM often considers a single (or a limited number of) widely distributed beneficial species, without considering undesired effects on co-occurring beneficials. In this study, we conducted standardised laboratory bioassays to assess the acute toxicity effects of 20 chemicals on 15 beneficial species at multiple exposure timepoints, with the specific aims to: (1) identify common and diverging patterns in acute toxicity responses of tested beneficials; (2) determine if the effect of pesticides on beetles, wasps and mites is consistent across species within these groups; and (3) assess the impact of mortality assessment timepoints on International Organisation for Biological Control (IOBC) toxicity classifications. Our work demonstrates that in most cases, chemical toxicities cannot be generalised across a range of beneficial insects and mites providing biological control, a finding that was found even when comparing impacts among closely related species of beetles, wasps and mites. Additionally, we show that toxicity impacts increase with exposure length, pointing to limitations of IOBC protocols. This work challenges the notion that chemical toxicities can be adequately tested on a limited number of 'representative' species; instead, it highlights the need for careful consideration and testing on a range of regionally and seasonally relevant beneficial species.

Segmentation and detection of crop pests using novel U-Net with hybrid deep learning mechanism.

OBJECTIVE: In India, agriculture is the backbone of economic sectors because of the increasing demand for agricultural products. However, agricultural production has been affected due to the presence of pests in crops. Several methods were developed to solve the crop pest detection issue, but they failed to achieve better results. Therefore, the proposed study used a new hybrid deep learning mechanism for segmenting and detecting pests in crops. METHOD: Image collection, pre-processing, segmentation, and detection are the steps involved in the proposed study. There are three steps involved in pre-processing: image rescaling, equalized joint histogram based contrast enhancement (Eq-JH-CE), and bendlet transform based De-noising (BT-D). Next, the pre-processed images are segmented using the DenseNet-77 UNet model. In this section, the complexity of the conventional UNet model is mitigated by hybridizing it with the DenseNet-77 model. Once the segmentation is done with an improved model, the crop pests are detected and classified by proposing a novel Convolutional Slice-Attention based Gated Recurrent Unit (CS-AGRU) model. The proposed model is the combination of a convolutional Neural Network (CNN) and a Gated Recurrent Unit (GRU). In order to achieve better accuracy outcomes, the proposed study hybridized these models due to their great efficiency. Also, the slice attention mechanism is applied over the proposed model for fetching relevant feature information and thereby enhancing the computational efficiency. So, pests in the crop are finally detected using the proposed method. RESULT: The Python programming language is utilized for implementation. The proposed approach shows a better accuracy range of 99.52%, IoU of 99.1%, precision of 98.88%, recall of 99.53%, F1-score of 99.35%, and FNR of 0.011 compared to existing techniques. DISCUSSION: Identifying and classifying pests helps farmers anticipate potential threats to their crops. By knowing which pests are prevalent in their region or are likely to infest certain crops, farmers can implement preventive measures to protect their crops, such as planting pest-resistant varieties, using crop rotation, or deploying traps and barriers. © 2024 Society of Chemical Industry.

Biosafety aspects of RNAi-based pests control.

While the overuse of classical chemical pesticides has had a detrimental impact on the environment and human health, the discovery of RNA interference (RNAi) offered the opportunity to develop new and sustainable approaches for pest management. RNAi is a naturally occurring regulation and defense mechanism that can be exploited to effectively protect crops by silencing key genes affecting the growth, development, behavior or fecundity of pests. However, as with all technologies, there is a range of potential risks and challenges associated with the application of RNAi, such as dsRNA stability, the potential for off-target effects, the safety of non-target organisms, and other application challenges. A better understanding of the molecular mechanisms involved in RNAi and in-depth discussion and analysis of these associated safety risks, is required to limit or mitigate potential adverse effects. © 2024 Society of Chemical Industry.