The agroecological transition offer opportunities to reduce agriculture's environmental impacts by reducing reliance on synthetic fertilisers and pesticides. Crop diversification, in both time and space, is a key strategy including extended crop rotations, intercropping, and cover crops. Yet, relationships between reduced input use and associated environmental impacts remain insufficiently quantified. We assessed the environmental performance of six innovative low-input cropping systems that used cover crops, cultivar mixture and intercropping in term of nitrogen fertiliser and pesticide use, as well as nitrate and pesticide losses. From 2010 to 2016, cropping systems were monitored for input use and drainage water was collected with tension plate lysimeters at 1 m depth. Nitrate and up to 44 pesticide compounds were analysed annually. Nitrogen fertiliser application varied across systems, with more diversified systems applying less thanks to legumes. Pesticide use remained similar among systems but reduced by over 50% compared to conventional rates. Cover crops played a key role in reducing pollution. Nitrate leaching reduced by 42–56% in systems with cover crops. More originally, pesticide leaching decreased by 53–82% for these systems with S-metolachlor representing more than 50% of the quantity of pesticide losses. These results demonstrate that diversifying cropping systems, particularly through cover cropping, can reduce agriculture's environmental footprint greatly. When combined with reducing input use, such strategies provide a promising pathway towards more sustainable and resilient farming systems, with clear benefits for water quality and agroecosystem functioning. • Six low-input diversified arable cropping systems were tested for six years. • Nitrate and pesticide leaching were collected over the six years of monitoring. • Cover crops cut nitrate leaching by 42–56% under field conditions. • First evidence that cover crops reduce pesticide leaching by 53–82%. • S-metolachlor loss is the main driver of the pesticide leaching pattern observed.

Pesticide use in agriculture is a pressing but complex sustainability problem. It involves various stakeholders and trade-offs between health, environmental, agroeconomic, and sociopolitical objectives. To address the problem, effective policy mixes must be designed. For this, they must be evaluated for their probability of achieving the diverse objectives, considering stakeholder preferences for trade-offs and risks. Previous studies have evaluated the coherence of objectives and the consistency and congruence of instruments to assess the effectiveness of policy mixes. However, they overlook the influence of nondesign activities in policy formulation that are shaped by interests. To grasp the full potential of policy mixes, evaluations must consider stakeholder preferences and measure consequences across multiple objectives. This study aims to conduct such an evaluation. We adapted a participatory multicriteria decision analysis using multiattribute value and utility theory to evaluate seven mixes of policy instruments for reducing agricultural pesticide risks in Switzerland. Our evaluation included the consequences of the policy mixes for 16 objectives, predicted from expert interviews and literature, and the preferences of stakeholders in economy, administration, and civil society. Stakeholder preferences, including rarely considered attitudes toward the risks of gains and losses for specific objectives, were decisive for the performance of the policy mixes. Despite conflicting preferences and high uncertainty, we found that one policy mix of risk-based tax incentives on pesticide use and an adapted pesticide approval process performed best for all. This finding was surprising given the limited support from some stakeholders for the tax incentives when asked directly. We conclude that a value-based evaluation of policy mixes could enrich policy choice architecture. Focusing on stakeholders' preferences for achieving policy objectives can inform decision-making by identifying effective policy mixes with a potential for consensus in contentious debates about how to reduce agricultural pesticide risks. • Participatory multicriteria decision analysis process to address complex problems. • Evaluation of various policy mixes to reduce agricultural pesticide risks. • Evaluation considering trade-offs, uncertainty, and stakeholder preferences. • Rarely considered attitudes to risk affect policy mix performance under uncertainty. • Focusing on objectives can help find policy mixes with consensus potential.

QSAR meets ecology: Predictive framework for assessing pesticide toxicity against mayfly using consensus modelling.

Occurrence of insecticides, fungicides, and herbicides in household drinking and irrigation water in an intensive floriculture region of Ecuador.

Phasing out glyphosate in orchards: What matters to farmers when adapting in-row weed management practices?

Comprehensive lipidomics reveal Rotenone exposure induces redox-driven lipid droplet accumulation, systemic lipidome perturbation and differential metabolic prioritization linked to Parkinson's disease.

The extensive use of agricultural pesticides has led to widespread environmental contamination, raising concerns about their adverse biological effects. The fungicide imazalil is known to cause endocrine-disrupting and hepatotoxic effects in vertebrates, but potential underlying epigenetic mechanisms remain poorly understood. In this multiomics study, we investigated hepatic epigenetic and transcriptomic responses in juvenile Xenopus tropicalis (6.5weeks post-metamorphosis) following two weeks exposure to an environmentally relevant concentration of imazalil (12.3μg/L). Thousands of differentially methylated cytosines (DMCs) were identified in both sexes, whereas significant gene expression changes were primarily detected in males. The genomic locations of DMCs were largely sex-specific, with only 162 sites shared between males and females. Gene Set Enrichment Analysis indicated disruption of energy metabolism in both sexes, while sex-specific responses included downregulation of cell cycle and chromatin organization pathways in males and upregulation of immune-related pathways in females. Integration of methylation and expression data identified 8083 strong correlations involving 2303 CpGs, including individual CpG sites whose methylation levels were linked to the expression of multiple functionally related genes enriched for cell cycle regulation and chromatin organization pathways. Together, these results suggest coordinated, potentially trans-regulatory epigenetic control of hepatic transcriptional networks that may mediate imazalil-induced hepatotoxic effects. The observed sex-specific responses further suggest that disruption of sex-hormone signaling may contribute to differential sensitivity to exposure. Overall, this study highlights the toxicogenomic effects of imazalil and underscores the importance of considering epigenetic mechanisms in future chemical risk assessment frameworks, with implications for both amphibian health and human environmental exposure.

Soil biological quality and microbial functional diversity under diversified conservation agriculture systems in the Indo-Gangetic Plain

Abstract However, the agricultural industries have to deal with many issues caused by plant disease, poor productivity, lack of expert knowledge, loss of soil nutrients and many others. There are numerous issues in identifying plant disease as early as possible, due to the fact that the process of cultivation is on a large scale, where manual monitoring is impossible, and requires much time and expertise, which is unattainable in rural areas. Early identification of leaf disease can save a lot of money otherwise incurred, and can even increase crop yields. Hence, agriculture in India desires to increase yield without causing any damage to the environment. Therefore, the purpose of this project is to create an automatic leaf identification system based on image processing algorithms, to help farmers identify disease in plants to enhance their productivity and yield, thereby saving a lot of money and time. For this project, various technologies like image processing, machine learning, and deep learning are used for the identification and analysis of images. Python programming language has been used along with various libraries such as OpenCV and NumPy for image processing operations. Machine learning techniques such as Convolutional Neural Networks (CNN) are used for classification. TensorFlow/Keras is used for model training and evaluation. It is well understood that agriculture continues to play a key role in the maintenance of economic stability and food security in many developing nations, where a major part of their population relies on agriculture as a source of income. With the rapid increase in population, climatic fluctuations, and various biotic stressors, the need for sustainable agriculture practices has become more pressing than ever before. Among all the other issues, diseases affecting crops rank high on the list of important considerations. Crop disease detection is crucial not only for food security but also for reducing unnecessary pesticide use.

Agricultural intensification and rising insecticide use are known threats to biodiversity in agroecosystems. Using a series of agricultural and landscape metrics, we tested the hypothesis that barn swallows (Hirundo rustica), as an avian wildlife indicator species, are at greater risk of insecticide exposure in more agriculturally intensive landscapes. We used spatial datasets for insecticide use density, landscape simplification, and relative cover of row crops and aquatic habitats (wetlands and other water bodies) at multiple spatial scales (500m-20km) as proxies of agro-intensity. In 2022 and 2023, we captured and blood sampled 173 barn swallows from 54 farms across a large agricultural gradient in southern Saskatchewan, Canada, and collected invertebrate sweep samples from three habitat types (cropland, grass or pastureland, and wetland margins) on 37 farms for chemical analysis to determine detection prevalence and sum concentrations of seven systemic insecticides (imidacloprid, clothianidin, thiamethoxam, acetamiprid, thiacloprid, flonicamid, and dinotefuran). The neonicotinoids thiamethoxam, clothianidin, and imidacloprid were detected in 54%, 47%, and 27% of the 173 barn swallow plasma samples and 98% of the 120 invertebrate samples. Insecticide concentration and detection in swallow plasma declined over the season but showed no clear or strong relationship with the measured metrics of agricultural intensity. However, the detection or concentration of insecticides in invertebrate samples positively correlated with most agricultural metrics. These results are consistent with the foraging behavior of barn swallows, whose movement across several kilometers likely integrates variation in prey contamination across farmland. The lack of association of agricultural intensity with barn swallow plasma neonicotinoid levels and positive relationship with invertebrates indicates that either rapid metabolism of these compounds in birds prevents accurate exposure characterization using blood, or land-use intensity maps are insufficiently precise at the relevant spatial scales for a wide-ranging species, and/or lower detection frequency of insecticides precludes characterization of fine-scale insecticide risk. We advocate for finer scale spatial data on agricultural intensity by crop type and pesticide use and recommend broader invertebrate sampling to more accurately reflect pesticide exposure risk for wildlife.

β-Hexachlorocyclohexane (β-HCH), a highly stable and persistent residue from pesticide use, poses significant risks to the environment and human health, so its sensitive and specific detection is of critical importance for accurate risk assessment. Conventional optical methods are often compromised by autofluorescence and matrix interferences. Here, we report a highly sensitive and selective persistent luminescence-based competitive enzyme biosensor for the detection of β-HCH. A key innovation is the design of a carboxylated HaloTag ligand grafted onto amino-functionalized persistent luminescence nanoparticles, Mn2+-doped Zn2GeO4, a conjugate (ZGOM@L) to serve as both the optical reporter and a competing substrate for the dehalogenase LinB. In this competitive assay, the presence of β-HCH preferentially consumes the LinB activity, sparing ZGOM@L for covalent conjugation with the immobilized HaloTag protein. This results in an increasing persistent luminescence proportional to the β-HCH concentration, inherently eliminating matrix-derived optical interference. The proposed method gives a detection limit of 0.02 ng mL-1 along with quantitative recoveries (88.0% to 105.3%) in vegetable samples. This work provides a robust, autofluorescence-free sensing platform and a generalizable strategy for monitoring trace haloalkanes in complex samples.

Introduction: Poisoning is a leading cause of preventable mortality worldwide, with trends shaped by changingsocietal, environmental, and toxicological factors. This study examines poisoning-related fatalities in Patiala,Punjab, using autopsy data to identify patterns, demographic correlations, and toxicological profiles, aiming toinform preventive and intervention strategies.Aims and Hypothesis: The study hypothesizes that poisoning trends are shifting due to the increased availabilityof hazardous substances and changing socio-economic pressures. It aims to analyze these trends and exploreinnovative approaches to mitigate poisoning-related mortality.Materials and Methods: A descriptive prospective study was conducted over 1.5 years on 360 autopsy cases withalleged poisoning. Data was analyzed on parameters including demographic profiles, type of poison, route andtiming of exposure, and the socio-environmental context of incidents. Statistical analysis, including Fisher’s ExactTest, identified significant associations, with p ≤ 0.05 considered significant.Results: Among 360 cases, 301 (83.6%) were males, and 59 (16.4%) were females, with the highest incidence inthe 21–30 years age group (30.56%). Aluminum phosphide was the most commonly detected poison (21.39%),followed by alcohol (11.11%). Suicide was the predominant manner of death (37.22%), strongly associated withaluminum phosphide, while alcohol was a key factor in accidental and overdose cases.Innovative findings revealed that 29.44% of cases had pending toxicology reports, underscoring systemic delaysthat hinder timely legal and preventive interventions. Furthermore, most incidents (77.78%) involved oralingestion, with 59.17% occurring in domestic settings, highlighting the need for stricter regulation and storageof household toxins. Seasonal analysis identified a significant spike in poisoning cases during the rainy season(43.61%), suggesting the role of agricultural practices and pesticide use during this period.Conclusion: This study emphasizes the critical need for gender- and age-specific interventions, enhanced mentalhealth services, and stricter regulations on toxic substances, particularly aluminum phosphide. Innovativemeasures, such as real-time toxicological diagnostics, community-based poison control programs, and educationalcampaigns targeting rural and urban populations, are essential to reduce the burden of poisoning-related mortality

Objective: This study aimed to study occupational health hazards and risk assessment among three farmer groups and propose guidelines for setting up occupational health management in farmer groups Method: The cross-sectional study of 315 rice, vegetable, and melon farmers in Phranakorn Si, Ayutthaya province, Thailand. The tool for data collection was a two-part questionnaire: (1) general characteristics, and (2) risk assessment from pesticide use, working behavior, and symptoms from exposure to agricultural chemicals. The questionnaire was scored on 5 levels, and the relationship was assessed using the Chi-square test. Results: Farmers in each group are exposed to different health hazards according to the production process. The risk assessment level was low in each group: the melon group (91%), the vegetable group (89.1%), and the rice group (53.3%). The association between risk assessment levels and associated factors was statistically significant in the rice group (p = 0.019; OR = 2.70, 95% CI = 1.22–5.97). (OR = 7.89, 95% CI = 1.98 – 31.35) in the vegetable group, and p = 0.023 (OR= 5.44, 95% CI = 1.32 – 22.43) in the melon group, respectively. Conclusion: This study suggested that guidelines for occupational health management should account for differences in occupational and health hazards across groups. Nevertheless, the operation of occupational health management will be successful with close cooperation from all three parties: government agencies, community leaders, and local farmers.

Pesticides are widely used to improve crop production; however, their impact on human health remains a concern. This study aimed to assess the level of knowledge about pesticide use, identify symptoms after exposure, and evaluate biosecurity measures among farmers in Miraflores. A descriptive, cross-sectional study was conducted in 2025 with 50 participants selected from a population of 4,118 inhabitants. Data was collected through a structured survey. Results showed that 85% of participants had some level of education, but only 35% used complete protective equipment. The most common symptoms reported were headache (60%) and dizziness (30%). A significant proportion of farmers used incomplete or no protection. In conclusion, despite having basic education, farmers lack adequate training in pesticide use, which increases the risk of health problems. Strengthening education and promoting proper biosecurity measures are essential to reduce exposure risks.

Apple leaf diseases (ALD) pose a significant challenge to global apple production, and accurately identifying ALD is crucial for reducing pesticide use and improving fruit quality, particularly in the context of smart agriculture. However, traditional approaches rely on single-model feature extraction, failing to account for relationships between different tasks, which limits their applicability in the apple industry. To address this, we design an optimized convolutional neural network–vision transformer (CNN–ViT) hybrid framework named ResViT-AM, focusing on domain-specific enhancement rather than architectural novelty. Instead of proposing a completely new structure, this work refines existing CNN–Transformer paradigms through task-oriented feature fusion and adaptive attention weighting, tailored for apple leaf disease classification under complex orchard conditions. Using a weighted attention fusion mechanism, our model dynamically integrates features extracted by Residual Network 101 (ResNet-101) and vision transformer (ViT), combining proven architectures in a task-adaptive way rather than pursuing architectural innovation, blending the local convolutional details of Residual Network (ResNet) with the global contextual features of ViT. This approach enhances the model’s representation capability and allows parallel processing of multiple tasks, thereby saving training time and computational resources. Additionally, we evaluate on the public AppleLeaf dataset, which reflects real-world outdoor conditions. On its held-out test split, our model achieves 99.14% top-1 accuracy on the AppleLeaf test split, indicating promising performance under complex orchard conditions. Compared with representative convolutional baselines, ResViT-AM shows greater stability and adaptability on challenging cases, offering a competitive and practical solution for automated apple leaf disease diagnosis.

Surface water contamination by pesticides is intertwined to surface runoff and soil erosion from agricultural farms. This study determined the presence and levels of pesticide residue in water from Themi River which is a source of irrigation water at Fire vegetable farm located in Arusha, Tanzania. Using grabbing water sampling technique, three (3) composite samples of water were collected from three strategic locations along the Themi River. Applying liquid phase extraction method, the residual of three pesticides namely trichlorfon, dimethoate, and vamidothion were detected and quantified using Gas Chromatography Mass Spectrophotometer (GC-MS) Agilent 7890A with 2-20 ppm detection limit. Results shows that the concentration of trichlorfon in the water was averaged at 0.71±0.1 µg/l, dimethoate was at 1.64±0.31 µg/l while vamidothion was at 0.78±0.38 µg/l all exceeding the 0.1 µg/l International Union of Pure and Applied Chemistry (IUPAC) recommended limits for individual pesticides residual in irrigation water. Unsustainable application of pesticide in vegetable farms not only contaminates the river but also threatens environment, life below water and human health through trophic chain.

In our study, the sequential extractions and environmental risk assessment of Cu, Zn, Pb, Ni, Cr, Ba, Mn were performed in soil depth profiles and in sediments transported by surface runoff in two vineyards with contrasted soil pH in NE Hungary. Our data indicate that while both sites showed Cu contamination from fungicide applications, the slightly acidic soil in Tállya had considerably higher Cu levels (131 ± 38mg/kg) than the alkaline soil in Tokaj (51 ± 15mg/kg) due to longer-term pesticide use history in the former. Potentially toxic elements (PTEs) exhibited overall low mobility in both vineyard soils, with Cr and Ni being strongly retained in the residual fractions (≥ 64-95%). However, Cu revealed high extractability in Tállya (> 57%) down to a depth of 40cm, further corroborating its predominantly anthropogenic origin and more labile character within the slightly acidic conditions. Contamination and risk assessments using the geoaccumulation index (Igeo) and the Risk Assessment Code (RAC) showed similar patterns between the two vineyards: while Ni, Cr, Mn, Ba, and Pb were of geogenic origin, Cu and Zn exhibited moderate to heavy contamination status (Igeo up to 3.17 (sediment)-3.34 (topsoil) for Cu in Tállya), with sediments showing Cu enrichment compared to topsoil in Tokaj. Copper emerged as the dominant concern, reaching medium risk levels (RAC ≥ 10%) at both sites due to substantial proportions detected in the acid-soluble fraction. This study highlights two critical management priorities for winegrowers: monitoring mobile PTE fractions and preventing contaminated sediment transport to adjacent surface waters.

Phosphatic rock weathering and agricultural activities may pollute soils with potentially toxic elements (PTEs) in phosphate-rich regions. However, the behavior of PTEs during rock weathering and their subsequent fate under agricultural influence remain poorly understood. Therefore, the natural weathering profile and farmland soil in a typical phosphatic zone were selected as the subjects for investigating the behavior characteristics of PTE during weathering, as well as PTE bioavailability and sources in surface soil under the influence of agricultural activities. The investigation into natural weathered profiles demonstrated that the weathering of phosphatic rock could generate a significant geological background of cadmium (Cd), lead (Pb) and mercury (Hg) due to their geochemical fractions in minerals. The agricultural activities were associated with elevated levels and increased bioavailability of PTE, particularly lead (Pb), copper (Cu) and zinc (Zn). In farmland topsoil, mean Cd and Pb concentrations reached 0.86 and 151 mg/kg, respectively, with 87% and 70% of samples classified as seriously polluted. The correlation analysis indicated that iron oxide was the predominant controlling factor for the bioavailability of PTE in farmland soil. The results of sources based on Pb isotope and positive matrix factorization (PMF) model suggested that the presence of Cd and Pb in farmland soil was mainly caused by the pesticide use and fertilization, respectively, with PMF attributing approximately 81% and 74% of their totals to these anthropogenic sources. Our study reveals that severe PTE pollution in the phosphatic zone stems from the synergistic effects of natural rock weathering and agricultural activities. This research served as a valuable reference for the prevention and control of PTE in the phosphatic zone.

This study examined pesticide residues in food crops (beans and groundnut) across five local government areas in Nasarawa South Senatorial District, Nigeria. It focused on pesticide use, safety practices and residue levels. Data from 430 respondents were analyzed using descriptive statistics and Chi-Square tests. QuEChERS extraction and GC-MS methods were employed for detection, identification, and quantification of residues. Pesticide residue recovery ranged from 70% to 130%, demonstrating the method's applicability to complex matrices. The findings revealed that most respondents were farmers (64.65%) using herbicides (73.95%) for crop protection (77.67%). Safety practices were suboptimal, with only 16.51% always reading labels and 39.53% not using any personal protective equipment (PPE). Health issues, notably skin irritation (39.77%) and respiratory problems (18.60%), were reported. Despite high awareness of alternatives to chemical pesticides (59.30%) and willingness to switch (77.44%), cost (33.95%) and lack of knowledge (42.09%) were major barriers. The Chi-square test established that there exist significant associations between the safety practices and locations. Post-hoc analysis revealed significant regional disparities in pesticide safety practices, with Lafia showing higher compliance in areas like label reading and use of protective clothing, while Doma, Awe, and Obi lag. The results of residue concentration analysis revealed that the analyzed food samples contained organochlorine, organophosphate, carbamate, and pyrethroid pesticides. In Doma, banned pesticides such as Ethion, Mirex, and DDT were detected at concentrations of 2.40E-04±2.36E-05 mg/kg, 1.13E-04±2.72E-06 mg/kg, and 2.33E-05±2.72E-06 mg/kg, respectively. The mean concentrations of all pesticide residues in the food samples were below the maximum residue limits.

Pesticide use is widespread in agricultural systems in Iraq, raising concerns about their potential impact on the gut mycobiome. This study investigated how residues of a fungicide containing metalaxyl-M and azoxystrobin affect the gut fungal microbiome using a mouse model. Thirty 12-week-old male Swiss albino mice (Mus musculus) weighing 30–40 g were divided into two groups: a control group (n=15) fed a regular diet and a treatment group (n=15) fed the same diet supplemented with 10 ppm of fungicide. Due to high inter-individual variation observed in preliminary analysis and cost constraints, fecal samples from mice within each group were pooled (5 pools per group, 3 mice per pool) prior to DNA extraction, effectively resulting in n=5 biological replicates per group for sequencing. Metagenetic libraries of the internal transcribed spacer (ITS) gene were generated and analyzed using QIIME2, DESeq2, DECIPHER, and Phangorn. A total of 191 amplicon sequence variants of fungal taxa were identified across all samples. The bioinformatic analysis revealed that the gut fungal community was significantly altered by fungicide treatment. Some species were enriched, including uncultured Nakazawaea and Neosartorya hiratsukae, and others were reduced, including Trichomonascus ciferrii, Alternaria conjuncta, and Ophiostoma canum. This study reveals that fungicides used in Iraq have profound effects on gut microbiome communities in mice, and it is recommended to pursue these aspects towards the further development of a research agenda focused on the health implications of dietary fungicide exposure and also on the methods of minimization.