Misuse Of Pesticides Research Articles

APD-YOLOv7: Enhancing Sustainable Farming through Precise Identification of Agricultural Pests and Diseases Using a Novel Diagonal Difference Ratio IOU Loss

The diversity and complexity of the agricultural environment pose significant challenges for the collection of pest and disease data. Additionally, pest and disease datasets often suffer from uneven distribution in quantity and inconsistent annotation standards. Enhancing the accuracy of pest and disease recognition remains a challenge for existing models. We constructed a representative agricultural pest and disease dataset, FIP6Set, through a combination of field photography and web scraping. This dataset encapsulates key issues encountered in existing agricultural pest and disease datasets. Referencing existing bounding box regression (BBR) loss functions, we reconsidered their geometric features and proposed a novel bounding box similarity comparison metric, DDRIoU, suited to the characteristics of agricultural pest and disease datasets. By integrating the focal loss concept with the DDRIoU loss, we derived a new loss function, namely Focal-DDRIoU loss. Furthermore, we modified the network structure of YOLOV7 by embedding the MobileViTv3 module. Consequently, we introduced a model specifically designed for agricultural pest and disease detection in precision agriculture. We conducted performance evaluations on the FIP6Set dataset using mAP75 as the evaluation metric. Experimental results demonstrate that the Focal-DDRIoU loss achieves improvements of 1.12%, 1.24%, 1.04%, and 1.50% compared to the GIoU, DIoU, CIoU, and EIoU losses, respectively. When employing the GIoU, DIoU, CIoU, EIoU, and Focal-DDRIoU loss functions, the adjusted network structure showed enhancements of 0.68%, 0.68%, 0.78%, 0.60%, and 0.56%, respectively, compared to the original YOLOv7. Furthermore, the proposed model outperformed the mainstream YOLOv7 and YOLOv5 models by 1.86% and 1.60%, respectively. The superior performance of the proposed model in detecting agricultural pests and diseases directly contributes to reducing pesticide misuse, preventing large-scale pest and disease outbreaks, and ultimately enhancing crop yields. These outcomes strongly support the promotion of sustainable agricultural development.

Biocompatible Nano-Cocrystal Engineering for Targeted Herbicide Delivery: Enhancing Efficacy through Stimuli-Responsive Release and Reduced Environmental Losses.

In addressing the critical challenges posed by the misuse and inefficiency of traditional pesticides, we introduce a Nano-Cocrystal material composed of the herbicide clopyralid and coformer phenazine. Developed through synergistic supramolecular self-assembly and mechanochemical nanotechnology, this Nano-Cocrystal significantly enhances pesticide performance. It exhibits a marked improvement in stability, with reductions in hygroscopicity and volatility by approximately 38%. Moreover, it intelligently modulates release according to environmental factors, such as temperature, pH, and soil inorganic salts, demonstrating decreased solubility by up to four times and improved wettability and adhesion on leaf surfaces. Importantly, the herbicidal activity surpasses that of pure clopyralid, increasing suppression rates of Medicago sativa L. and Oxalis corniculata L. by up to 27% at the highest dosage. This Nano-Cocrystal also shows enhanced crop safety and reduced genotoxicity compared to conventional formulations. Offering a blend of simplicity, cost-effectiveness, and robust stability, our findings contribute a sustainable solution to agricultural practices, favoring the safety of nontarget organisms.

MicroRNA bmo-miR-31-5p inhibits apoptosis and promotes BmNPV proliferation by targeting the CYP9e2 gene of Bombyx mori.

Bombyx mori nuclear polyhedrosis virus (BmNPV), as a typical baculovirus, is the primary pathogen that infects the silkworm B. mori, a lepidopteran species. Owing to the high biological safety of BmNPV in infecting insects, it is commonly utilized as a biological insecticide for pest control. Apoptosis is important in the interaction between the host and pathogenic microorganisms. MicroRNAs (miRNAs) influence immune responses and promote stability of the immune system via apoptosis. Therefore, the study of apoptosis-related miRNA in silkworms during virus infection can not only provide support for standardizing the prevention and control of diseases and insect pests, but also reduce the economic losses to sericulture caused by the misuse of biological pesticides. Through transcriptome sequencing, we identified a miRNA, miR-31-5p, and demonstrated that it can inhibit apoptosis in silkworm cells and promote the proliferation of BmNPV in BmE-SWU1 cells. We identified a target gene of miR-31-5p, B. mori cytochrome P450 9e2 (BmCYP9e2), and demonstrated that it can promote apoptosis in silkworm cells and inhibit the proliferation of BmNPV. Moreover, we constructed transgenic silkworm strains with miR-31-5p knockout and confirmed that they can inhibit the proliferation of BmNPV. These data indicate that miR-31-5p may exert functions of inhibiting apoptosis and promoting virus proliferation by regulating BmCYP9e2. The findings demonstrate how miRNAs influence host cell apoptosis and how they are involved in the host immune system response to viruses, providing important insights into the applications of biological insecticides for pest control. © 2024 Society of Chemical Industry.

Addressing residue and resistance in food animals: a policy imperative in Southeast Asia

SummaryResidue and resistance in food animals pose significant challenges to Southeast Asia's public health, animal welfare, agricultural productivity, and sustainability. This article emphasises the need for policy interventions to address these issues effectively. Residue, the presence of harmful substances in animal products, is a concern due to the misuse of veterinary drugs and pesticides. Robust surveillance programs, risk assessment, and enforcement of maximum residue limits are crucial to ensure food safety. Antimicrobial resistance (AMR) is another critical challenge in the region, driven by intensive animal production systems and disproportionate antimicrobial use. Responsible antimicrobial use, surveillance systems, and alternative production practices like vaccination, enhanced animal husbandry, and improved biosecurity a re essential to combat the menace. Addressing residue and resistance requires a comprehensive mindset and policy approach, including strengthening regulatory frameworks and inter‐agency collaboration, including a One Health approach. Governments, farms, veterinarians, and other stakeholders must work together to develop and enforce effective policies. Education and awareness campaigns can promote responsible practices throughout the food‐animal production chain. By prioritising the reduction of residue and resistance, Southeast Asian countries can safeguard public health, ensure sustainable agriculture, and contribute to global efforts in tackling AMR. Policymakers supported by academia, industry, and other stakeholders play a crucial role in effectively shaping and implementing policies to address these challenges.

Flexible Surface-Enhanced Raman Scattering (SERS) sensor for residue-free pesticide detection based on agriculture 4.0 concepts

Given the health and environmental risks associated with pesticide misuse, achieving zero pesticide residues is pivotal in Agriculture 4.0. Traditional detection methods such as HPLC and GC-MS are both complex and time-consuming. In contrast, surface-enhanced Raman scattering (SERS) offers rapid detection and high sensitivity, aligning with the efficiency and accuracy requirements of Agriculture 4.0. In this study, we developed a high-performance flexible substrate using a simple chemical synthesis method. We used material adsorption, anisotropic charge attraction and electron migration to facilitate the growth of the substrate material, which promoted more 'hot spots' and electron transfer, and continued optimisation of the preparation process, which resulted in a significant increase in spectral intensity. The substrate demonstrated outstanding detection capability, with a detection limit of 10−15 M for thiabendazole (TBZ). In practical fruit testing, TBZ residue concentrations on the surface of American cherries could be detected as low as 10−8 mg/mL, well below China's prescribed limit of 5 mg/kg. Relative to previous work in the field of pesticide detection, our study has lower detection limits and concentrations, as well as lower cost and simpler preparation, which provide more options for the detection of very low concentrations of hazardous substances. At the same time, it was confirmed that SERS is consistent with the zero pesticide residue goal of Agriculture 4.0, demonstrating practical efficacy and accuracy within this framework.

ENTOMOPATHOGENIC FUNGI AS MYCO-BIOCONTROL AGENT OF STORED GRAIN INSECT PESTS

Chemical insecticides have been a fairly successful means of controlling pests that cause harm to stored agricultural commodities. However, there are risks, involved in applying these pesticides continuously; these risks are fast becoming problem of global proportion. The overuse and misuse of chemical pesticides by agricultural value chain actors has made the development of new and lower-risk, benign methods for managing insect pests necessary. One lower risk method of managing insect pest that is gaining traction in terms of utilization is myco-biocontrol, one of which is entomopathogenic fungi (EPF) with a biological origin. Entomopathogenic fungi are pathogenic to insects, and based on their widespread presence in natural environments are purported as less harmful to the environment. Toxicologically, EPF are considered benign to man, making them desirable in the context of the new integrated pest management (IPM) framework. Fundamentally, this review covers the current state of knowledge regarding EPF fungi and their use for biological pest management as well as recent developments in the bio-control of stored-grain insects using formulated and unformulated strains. It also covers the mode of application, mechanism of action, and environmental factors necessary for the germination and growth of conidia.

Biological activity of essential oils from Ferulago angulata and Ferula assa-foetida against food-related microorganisms (antimicrobial) and Ephestia kuehniella as a storage pest (insecticidal); an in vitro and in silico study

Misuse of synthetic pesticides and antimicrobials in agriculture and the food industry has resulted in food contamination, promoting resistant pests and pathogen strains and hazards for humanity and the environment. Therefore, ever-increasing concern about synthetic chemicals has stimulated interest in eco-friendly compounds. Ferulago angulata (Schltdl.) Boiss. and Ferula assa-foetida L., as medicinal species with restricted natural distribution and unknown biological potential, aimed at investigation of their essential oil (EO) biological properties, were subjected. Z-β-Ocimene and Z-1-Propenyl-sec-butyl disulfide molecules were identified as the major composition of the essential oil of the fruits of F. angulata and F. assa-foetida, respectively. In vitro antimicrobial activity and membrane destruction investigation by scanning electron microscopy imaging illustrated that F. angulata EO had potent antibacterial activity. Besides, the EOs of both plants exhibited significant anti-yeast activity against Candida albicans. In relation to insecticidal activity, both EOs indicated appropriate potential against Ephestia kuehniella; however, the F. assa-foetida EO had more toxicity on the studied pest. Among several insecticidal-related targets, acetylcholinesterase was identified as the main target of EO based on the molecular docking approach. Hence, in line with in vitro results, in silico evaluation determined that F. assa-foetida has a higher potential for inhibiting acetylcholinesterase and, consequently, better insecticide properties. Overall, in addition to the antioxidant properties of both EO, F. angulata EO could serve as an effective prevention against microbial spoilage and foodborne pathogens, and F. assa-foetida EO holds promise as a multi-purpose and natural biocide for yeast contamination and pest management particularly against E. kuehniella.

Estimating cost efficiency and sources of inefficiency in paddy farming: A study in Vietnam’s Mekong Delta

The misuse of chemical fertilizers, pesticides and herbicides in rice cultivation is leading to low-quality outputs, high production costs, health issues and environmental problems (e.g., degraded soil quality, water pollution and increasing greenhouse gases). The efficient use of production inputs would be a feasible way to mitigate these issues. This paper employed a true random-effects model to measure cost efficiency and investigate the factors affecting cost inefficiency among Vietnamese rice producers. This study used the surveyed data of 350 rice households collected in the Mekong Delta, Vietnam. The findings of this research show that the mean cost efficiency score is 0.92 with a wide variation (0.26 – 0.99). This study indicates that there is still potential for inefficient rice producers to save production costs by improving their cost inefficiency. The study also reveals a positive relationship between cost inefficiency and farm size, natural disasters and rice diseases. This suggests that as farms grow, natural disasters and rice diseases become more prevalent and rice producers become increasingly incapable of managing input costs. This study suggests that supportive policies should focus on improving rice farmers’ skills to manage production inputs and deal with rice diseases and natural disasters to minimize rice production costs.

Uridine diphosphate glucosyltransferases are involved in spinosad resistance in western flower thrips Frankliniella occidentalis (Pergande)

Uridine diphosphate glucosyltransferases (UGTs) play crucial roles in the insect detoxification system and are associated with pesticide resistance. Our previous transcriptomic analysis of spinosad-susceptible (Ivf03) and resistant (NIL-R) Frankliniella occidentalis revealed numerous upregulated UGT genes in the NIL-R strain, suggesting their potential contribution to spinosad resistance. To investigate this hypothesis, here we conducted UGT activity assays and spinosad induction experiments, employing RNA interference (RNAi) techniques for gene function validation. We found significantly elevated UGT activity in the NIL-R strain compared to Ivf03, with 5-nitrouracil showing a substantial synergistic effect on the resistant strain. Eighteen UGT genes were identified in F. occidentalis, with gene expansion and duplication observed within families UGT466, 467, and 468. Ten out of the eighteen UGTs exhibited higher expression levels in NIL-R, specifically FoUGT466B1, FoUGT468A3, and FoUGT468A4 consistently being upregulated across nymphs, males, and females. RNAi-based functional validation targeting these three UGT genes led to increased susceptibility to spinosad in a life stage-, sex-, and dose-dependent manner. These results indicate that UGTs are indeed involved in spinosad resistance in F. occidentalis, and the effects are dependent on life stage, sex, and dose. Therefore, sustainable control for F. occidentalis resistance should always consider these differential responses.

Organochlorine pesticide residues in water and sediments in river Kibos-Nyamasaria in Kisumu County: An inlet river of Lake Victoria, Kenya

The misuse of organochlorine pesticides (OCPs) and the lack of adequate regulations have led to contamination of rivers and lakes. In this study, we determined the concentrations of OCPs that have either been banned or restricted for use in the Kibos-Nyamasaria River during two seasons: wet (April-May) and dry (February-March). OCPs were analyzed using GC–MS. Nineteen pesticide residues were detected in the river (water) and sediments. In water, aldrin had the highest concentration of 8.33 ± 0.58 μg/L, dieldrin (8.67 ± 0.5 μg/L), endosulfan sulphate (0.23 ± 0.00 μg/L), α-endosulfan (0.19 ± 0.00 μg/L), methoxychlor (4.57 ± 0.03 μg/L) and α-HCH (3.47 ± 0.00 μg/L) during the wet season, while dieldrin (6.03 ± 5.1 μg/L), methoxychlor (3.43 ± 0.06 μg/L), and α-HCH (8.27 ± 0.06 μg/L) were above 0.1 μg/L detection limit during the dry season. In sediments, aldrin, methoxychlor, and δ-HCH were not detected in either season; however, dieldrin and β-endosulfan were detected only during the dry season. Additionally, OCPs were above 0.2 μg/kg (maximum residue level (MRLs). The concentration of OCPs increased downstream as the river approached Lake Victoria. Because some pesticides were present at levels beyond the recommended limits, strategies must be developed to reduce them and identify potential sources of banned pesticides.

Occupational Health Hazards of Pesticides Use among Commercial Vegetable Farmers of Kirtipur Municipality, Kathmandu

Background: Occupational health and safety are the integral components of the general concepts of health. In Nepalese context, misuse of pesticides have been observed and practiced in several ways. Nepalese farmers use too much pesticide than needed with too little protection when using pesticides due to which many accidental poisonings occur annually. This study aims to assess the occupational health hazards related to pesticide use among commercial vegetable farmers of Kirtipur municipality, Kathmandu. Methodology: A community-based cross-sectional study was conducted among 107 randomly selected commercial vegetable farmers in Kirtipur Municipality of Kathmandu by using semi-structured questionnaire. Data were collected using face to face interview method. The questionnaire included socio-demographic characters, pesticide use practices, storage and disposal techniques and health effects among the farmers. Data were entered in Epidata and then analyzed in SPSS version 21. Frequency, percentage, mean, and standard deviation were calculated to measure the practice of pesticide use and occupational health hazards related to pesticide use among farmers. Result: The study is comprised of 52% male and 48% female. About 89% of farmers were wearing Personal Protective Equipment (PPE) during spraying of pesticides. Maximum numbers of farmers change clothes and take a bath right after the application of pesticide i.e. 87% and 88% respectively. Almost half of the vegetable farmers (45.1%) use burn method for disposal of empty pesticide containers. However, 45.6% of the respondents experience health problems within 48 hours of pesticide application. Conclusion: The study concluded that almost half of the pesticide users have shown various symptoms of health hazards. Unsafe equipment and condition, inadequate training, limited availability and use of PPE all contribute to the health hazards of pesticide users.

YOLO_MRC: A fast and lightweight model for real-time detection and individual counting of Tephritidae pests

Tephritidae pests severely affect the quality and safety of various melons, fruits and vegetable crops. However, many agricultural managers lack an adequate understanding of the level of pest occurrence, resulting in the misuse of pesticides, which ultimately leads to environmental pollution and economic loss. Therefore, real-time detection and counting of Tephritidae pests are important for timely pest spotting and control. This work helps quickly determine the distribution and abundance of pests in the current environment, thus providing data on pest conditions for agricultural management to optimize pesticide use. Nevertheless, the fast speed, high accuracy, and lightweight performance of real-time detection and counting are difficult to balance. To address this problem, based on the YOLOv8n model, this paper takes Bactrocera cucurbitae pests as the detection target and proposes a fast and lightweight real-time detection and individual counting model for Tephritidae pests, named YOLO_MRC. This paper introduces three key improvements: (1) Constructing a new module called Multicat into the neck network increases the focus on the detection target by incorporating an attention mechanism; (2) Reducing the original three detection heads to two and then adjusting their sizes to decrease the number of parameters in the network model; (3) Devising a novel module, C2flite, to enhance the deep feature extraction capability of the backbone network. According to the above points, this paper conducts ablation experiments to compare the performances of different models. Experiments showed that the Multicat module significantly offsets the large increase in GFLOPs and processing time caused by reducing the detection head and can further reduce the number of parameters and improve the accuracy when combined with the C2flite module. On our Bactrocera cucurbitae pest dataset, the mAP@0.5 of the YOLO_MRC model reached 99.3%. Simultaneously, as the number of parameters decreases by 63.68%, GFLOPs is reduced by 19.75%, and the processing time is shortened by 5%. To ensure the validity of the model, YOLO_MRC is compared with four excellent detection models by using manual counting results as the benchmark. YOLO_MRC achieves an average pest counting accuracy of 94%, demonstrating superior performance in terms of model size and processing time. To further explore the performance of YOLO_MRC in multiclass insect detection tasks, we choose the public dataset Pest_24_640 for comparison with four state-of-the-art models. YOLO_MRC achieves a 3.6 ms processing time and 70.4% accuracy with only a 2.4 MB model size, which demonstrates the potential of YOLO_MRC in multiclass pest detection.

Effectiveness of pesticide labels (pictograms and color codes): a cross-sectional study of farmers’ understanding and practices in Lebanon

This study aims to assess the effectiveness of the pesticide labels (pictograms and color codes) and the technical sign-related practices among the farming community in Lebanon. Methods: A cross-sectional study was conducted between November 2021 and October 2022 among 104 farmers from three Lebanese provinces. An Arabic survey (score-based questionnaire) was conducted to evaluate the farmers’ levels of understanding the pesticide labels (pictograms and color codes) and relevant practices to pesticide labels. Spearman correlation and One-Way ANOVA were applied to determine the statistical correlation between farmers’ understanding and practice levels and their significant differences in gender, age, provinces, educational level, and attendance of training programs. Results: It was found that the majority of the participants showed moderate levels of understanding (71.2%) and practices (75%). Spearman’s correlation analysis concluded a weak correlation between the understanding and performance levels (p < 0.05). Comparative analyses showed higher levels of label pictograms’ understanding and label-related practices with a significant difference (p < 0.05) among younger and well-educational farmers. However, training programs significantly enhanced the farmers’ practices only. Incidence of irritations-to-poisoning symptoms was self-reported as consequences of misinterpretations and misuse of pesticides. Conclusion: The study findings highlighted the limited effectiveness of pictograms and color codes in Lebanon and thereby highlighted the necessity of training programs addressing the knowledge of technical signs among farmers.

Diagnosis of soybean bacterial blight progress stage based on deep learning in the context of data-deficient

Soybean bacterial spot disease is a predominant disease that impairs the quality and yield of soybean produce. In order to minimize production losses to the greatest extent possible, rapid detection and identification of disease progression stages are crucial. However, the conventional techniques used for identifying bacterial spot disease exhibit limitations in terms of providing real-time and objective analysis for dynamically identifying significant differences in the disease manifestation. In the present study, a novel sliding segmentation method was proposed for solving the problem of insufficient data volume, which can diagnose soybean disease stages in a timely and accurate manner, take measures to reduce the impact of diseases on soybeans, and solve the problem of difficulty in obtaining disease datasets. Further, a convolutional neural network (CNN) based image recognition method for soybean leaves at different disease stages was proposed. Different depth learning classical network models were used for transfer learning, and the characteristics of soybean leaf spots in different stages and the differences between diseased leaves and normal leaves were considered. The focus of the experiment was on optimizing a network model by adjusting three factors: the optimization algorithm, epoch number, and batch size number. The aim was to enhance the recognition accuracy of the model. The experimental results show that the optimal network model was based on Swin Transformer, with an optimization algorithm of SGD, epoch, and batch size of 200 and 8, respectively. In the experiment, the optimal model achieved an accuracy of 99.64 % in identifying soybean leaf disease stages. The model can accurately identify soybean leaf diseases at different stages, meet practical production needs, prevent pesticide misuse, reduce yield losses caused by soybean leaf diseases, provide a reference for identifying the development process of leaf diseases, and also provide theoretical support for the establishment of soybean disease warning systems.

Levels of organochlorine pesticide residues in fresh tomatoes from selected farming communities in Navrongo, Ghana

The levels of organochlorine pesticide (OCP) residues in tomatoes sourced from three agricultural communities in Navrongo (Bonia, Korania, and Nangalkenia) were analyzed using gas chromatography. A comprehensive analysis revealed the presence of nineteen (19) distinct organochlorine pesticides, with a minimum of five different residues detected in each tomato sample. The OCPs were detected within a range of 0.04 to 15.90 μg/kg. Remarkably, beta-hexachlorocylohexane (β-HCH) exhibited the highest concentration (15.90 μg/kg), while both cis-chlordane and trans-heptachlor epoxide displayed the lowest concentration (0.04 μg/kg) in Korania. In the Nangalkenia community, gamma-hexachlorocylohexane (δ-HCH) demonstrated the highest concentration (10.21 μg/kg), while trans-chlordane and o,p'‑Dichlorodiphenyltrichloroethane (o, p-DDT) exhibited the lowest concentration (0.04 μg/kg). Furthermore, within the Bonia community, p, p-Dichlorodiphenyltrichloroethane (p, p-DDT) displayed the highest concentration (8.25 μg/kg), whereas o, p-DDT and trans-heptachlor epoxide exhibited the lowest concentration (0.13 μg/kg). Notably, the analysis indicated that two (2) of the organochlorine pesticides, specifically β-HCH and δ-HCH, surpassed the Maximum Residue Limits (MRLs) established by the United Kingdom/European Commission (UK/EC). The results of the questionnaire survey unveiled a substantial proportion of illiterate farmers (54%), which potentially plays a significant role in the farmers' misuse or indiscriminate use of pesticides. Additionally, both the questionnaire responses and field visits provided insight into the specific types of pesticides employed by the farmers. These include karate, lambda, carbofuran, mancozeb, ridomil, sunpyrifos, kocide, cypermethrin, and dimethoate.

Efficient removal of carbofuran by sono-photo active CdS@MIL based Ti Framework

The misuse of pesticides is resulted in their deposition in the soil, plants and animals which consequently affecting the environment's pollution and constitute a potential risk to human beings. Cadmium sulfide (CdS) has an efficient band gap which resulted in the trapping of electron and consequently preventing the recombination of photogenerated radical species (electron/hole). The current approach is considered with the in-situ nucleation of CdS directly over MIL-125-NH2 to obtain CdS@MIL-125-NH2, that was sequentially applied for removal of carbofuran pesticide by sono-photocatalytic degradation. The electron microscope declared that spherical agglomerated CdS was densely covered MIL-125-NH2 framework. Catalytic degradation of carbofuran in presence of the prepared materials was systematically investigated by sonolysis, photolysis and sono-photolysis. The degradation of carbofuran was followed the first order model. The catalyzation of CdS@MIL-125-NH2 by daylight was much efficient rather than ultrasonic. By applying CdS@MIL-125-NH2, the degradation amount of carbofuran reached 331.5 mg/g, 630.0 mg/g and 738.0 mg/g for sonolytic, photolytic and sono-photolytic, respectively within 90 min. Insertion of CdS, enhanced the sono-photolytic activity of MIL-125-NH2 by 3.1 times. CdS@MIL-125-NH2 showed good recyclability and its efficiency in carbofuran degradation was diminished by 6.5% only after five repetitive using cycles.

Biological responses to imazapic and methyl parathion pesticides in bioinspired lipid membranes and Tilapia fish

Pesticide misuse has well-documented detrimental effects on ecosystems, with Nile tilapia (Oreochromis niloticus) being particularly vulnerable. The current study focuses on the impact of widely used sugarcane crop pesticides, Imazapic (IMZ) and Methyl Parathion (MP), on tilapia gill tissues and their lipid membranes. This investigation was motivated by the specific role of the lipid membrane in transport regulation. Bioinspired cell membrane models, including Langmuir monolayers and liposomes (LUVs and GUVs), were utilized to explore the interaction of IMZ and MP. The results revealed electrostatic interactions between IMZ and MP and the polar head groups of lipids, inducing morphological alterations in the lipid bilayer. Tilapia gill tissue exposed to the pesticides exhibited hypertrophic increases in primary and secondary lamellae, total lamellar fusion, vasodilation, and lifting of the secondary lamellar epithelium. These alterations can lead to compromised oxygen absorption by fish and subsequent mortality. This study not only highlights the harmful effects of the pesticides IMZ and MP, but also emphasizes the crucial role of water quality in ecosystem well-being, even at minimal pesticide concentrations. Understanding these impacts can better inform management practices to safeguard aquatic organisms and preserve ecosystem health in pesticide-affected environments.

Cultural practices and use of pesticides on tomato (Solanum lycopersicum L.) market gardeners in Loumbila and Ouahigouya (Burkina Faso)

The misuse of pesticides and their overdose on vegetables has an impact on people's health. The purpose of this study was to evaluate the cultivation and phytosanitary practices of tomato growers at the Loumbila and Ouahigouya vegetable growing sites. A survey on cultural and phytosanitary practices was carried out among 25 tomato producers at these two market gardening sites. Results show that 16% of producers use dams and 80% traditional wells as a source of water supply. The inputs used are mainly organic (cow's mouth, household waste) and chemical (NPK, urea) fertilizer. The frequency of use of chemical fertilizer is once a week at the Loumbila site and only once a month in the Ouahigouya site. All the producers surveyed used pesticides and 67% do not respect the deadlines for indicated on the packaging labels. A total of 16 pesticides (insecticides, fungicides) are used during tomato production. Cypermethrin and Lambda-cyhalothrin from the pyrethroid family and acetamiprid from the Neonicotinoid family were the most used by producers. Most of these pesticides are not intended for vegetable crops but rather for cotton crops. The pesticides used may remain in the tomato in significant amounts and pose a threat to consumers.

PesViT: a deep learning approach for detecting misuse of pesticides on farm

PesViT: a deep learning approach for detecting misuse of pesticides on farm

Overview of Pesticide Usage, Misuse and Its Impact on Environmental Degradation in South-western States and Some Part of Northern States in Nigeria

This study assessed and oversees the pesticides usage, misuse and its effects on environmental degradation in Southwest and some Northern part of Nigeria. It also gathered information on why farmers misused the pesticides. Data for this study were collected from secondary sources like books, electronic sources, experimental and field reports. It was discovered from the literature searched that males were majorly pesticide users than the females. Higher education levels of farmers reduced the misuse of pesticides. Majority of farmers were reusing pesticide containers for keeping valuable thing in homes and that pesticides which are highly toxic are being used by farmers. It was also noted that, farmers are misusing agrochemicals due to inappropriate use of PPE (Personal Protective Equipment), mixing of two chemicals which are meant to perform different role, lack of checking expiry dates on the pesticides containers and inability of many farmers to read and understand the instructions on pesticide containers. Many farmers experience discomforts such as vomiting, itching eyes, burning sensation, dizziness, nausea etc. Impact of pesticides on the environment were revealed to have detrimental effect on hatching of egg of some aquatic organisms, hinders reproductive and endocrine systems and contamination of food, water, death of livestock, fish death and loss of biodiversity as a result of environmental hazards caused by pesticide usage. It is therefore concluded that farmers should be encouraged to use their complete PPE during pesticides application to avoid having discomfort, and the use of pesticides should not be anchored by old age farmers. Moreso, banned pesticides should be monitored not to be sold in the market, adult education should be organized for the pesticide users and encourage proper disposal of pesticide cans into appropriate incinerator after used.