Search Results (8,552)

Pesticides play a crucial role in modern agriculture by protecting crops from pests, diseases, and weeds, thereby contributing to increased agricultural productivity and food security. However, their extensive use may lead to the presence of residues in food products, particularly vegetables, which can pose potential risks to human health. Therefore, continuous monitoring of pesticide residues in vegetables is essential to ensure food safety, assess dietary exposure, and protect consumers from possible acute and chronic health effects associated with pesticide intake. In this study, the concentrations of pesticide residues were determined in 1236 samples of 44 vegetable species collected over a four-year period. Vegetables originated from 39 countries, including Serbia (n = 213). Pesticide residues were determined by liquid chromatography–tandem mass spectrometry (LC-MS/MS) and gas chromatography–tandem mass spectrometry (GC-MS/MS) after extraction using a modified QuEChERS protocol. A total of 148 pesticide residues were detected. Of the vegetable samples, 40.13% had pesticide residues at or above 0.01 mg/kg, and 1.78% exceeded the maximum residue limits (MRLs) set by the Serbian regulation. MRL values were most often exceeded in ginger, cucumber, and spinach. The most frequently found pesticide was imidacloprid (detected in 74 samples, 5.99%). Multiple pesticides were detected in 22.01% of the vegetable samples, and one tomato sample contained up to 10 pesticide residues. Based on the available data and further development of a representative dataset, together with appropriate statistical analyses, dietary exposure assessments for pesticides can be conducted. Full article

Growing pesticide use is linked to increased health risks for farmers across Africa, due to factors such as improper handling, insufficient knowledge, and lack of resources. To better understand these risk factors in Rwanda, where the majority of the population and most women are farmers, we held focus group discussions (FGDs) with 31 Sector Agricultural Officers (SAOs) and Sector Animal Resources Officers (SAROs) in five districts of Eastern Province. Among their views on this topic, we identified four core themes among the FGDs of (1) interconnected challenges, (2) shared exposure and health risks, (3) gender differences in risk behavior, and (4) transmission of knowledge, in addition to six pesticides—abamectin, cypermethrin, lambda-cyhalothrin, profenofos, mancozeb, and metalaxyl—most commonly used across all districts. Our findings suggest that Rwandan farmers may overestimate variety in the pesticides that they use and thus potentially contribute to problems such as pest resistance, underlining a critical need for integrated, locally informed approaches to pesticide management. This study also demonstrates the valuable role of extension officers in highlighting challenges related to pesticide use in farming communities and advancing research that engages with them. Full article

Accurate pest recognition is an important foundation for intelligent plant protection, precision pesticide application, and sustainable agricultural management. However, in real field environments, pest targets are often small in scale, severely occluded, and embedded in complex backgrounds, which limits the performance of existing supervised learning methods under low-annotation and cross-scenario conditions. To address these issues, a multimodal self-supervised pretraining framework is proposed for pest recognition, in which field pest images and environmental sensor data are integrated to construct pest representations with environmental awareness. In this framework, image features, including pest morphology, leaf texture, and damaged regions, are first extracted through a visual encoding branch, while temporal variation features of ecological factors, including temperature, humidity, illumination, soil moisture, rainfall, and wind speed, are modeled through an environmental encoding branch. On this basis, a cross-modal contrastive consistency module is designed to align visual and environmental representations, a temporal consistency self-supervised module is introduced to characterize the continuous evolutionary relationship between pest occurrence and environmental changes, and a multimodal collaborative representation fusion module is constructed to adaptively integrate information from different modalities. The experimental results show that the proposed method achieves favorable performance in the pest recognition task, with Accuracy, Precision, Recall, and F1-score reaching $94.37\%$, $93.96\%$, $93.42\%$, and $93.69\%$, respectively, outperforming ConvNeXtV2-T, ViT-B/16, Swin-T, SimCLR, MAE, and the conventional Image + Sensor fusion method. The ablation experiments further show that, after removing the cross-modal contrastive consistency module, the temporal consistency self-supervised module, and the multimodal collaborative fusion module, the F1-score decreases to $91.00\%$, $91.36\%$, and $90.49\%$, respectively, thereby demonstrating the contribution of each module. This study provides a viable multimodal self-supervised learning approach for AI-driven intelligent pest recognition, early warning, and precision control in agriculture. Full article

To address the issues of poor sustained-release behavior and limited long-term efficacy associated with conventional salt-storage materials, this study developed the epoxy-resin-encapsulated slow-release salt-storage filler to enhance both the engineering performance and the deicing/snow-melting capacity of salt-storage pavements. In this study, attapulgite was optimized and selected as the salt storage carrier through the adoption of pesticide coating technology and experimental testing, wherein a deicing salt blend with a CaCl₂ to NaCl mass ratio of 2:1 was loaded via a wet adsorption method. Subsequently, using dimethicone as the surface modifier, the optimal encapsulation process was determined to involve the dilution ratio of epoxy resin to cyclohexanone of 4:1 and the curing agent dosage of 30% by weight. The results indicated that the recommended content of the filler should not exceed 5%. The filler reduced the high-temperature stability and water stability of the mixture, while the low-temperature crack resistance first increased and then decreased, peaking at the 2% filler content with an improvement of 12.2%. The water stability was the most significantly affected by the filler content. Ice–snow melting performance tests demonstrated that the salt-storage mixture with 5% filler achieved the deicing rate of 56.35% at −5 °C, meeting the industry standard requirements. The self-prepared slow-release salt-storage filler exhibited superior long-term ice–snow melting performance to V-260, with the slow-release duration extended by 60%. The salt release process was divided into three distinct stages: rapid dissolution, stable release and slow dissolution. The 60 °C was determined as the optimal temperature for the accelerated immersion testing, which the accelerated test could effectively simulate the natural immersion process. Based on the prediction model established accordingly, the functional service life of snow-melting for this slow-release salt-storage asphalt pavement in northern area was estimated be approximately 4.07 years. The slow-release salt-storage filler fabricated in this work possesses both remarkable sustained-release behavior and deicing efficacy. The findings provide the technical foundation for the development of novel salt-storage pavement materials, performance characterization, and mechanistic analysis of snow-ice melting. Full article

The rice leaffolder, Cnaphalocrocis medinalis, has developed widespread resistance to conventional insecticides, severely threatening rice production. Pesticide combination is a critical strategy for enhancing efficacy and delaying resistance evolution. In this study, binary mixtures with distinct modes of action were screened against C. medinalis neonates. Bioassays indicated that mixtures of spinosad and indoxacarb exhibited significant synergism, while several other combinations showed antagonism. To elucidate the synergistic mechanism of the optimal 1:1 mixture, comparative transcriptomic analyses were performed. Results revealed a time-dependent dual-phase response. At 6 h, the mixture induced broader upregulation of detoxification genes and activated stress signaling pathways due to competitive enzyme saturation, impairing metabolic clearance and amplifying neurotoxicity. At 24 h, massive transcriptional reprogramming uniquely activated lysosome, autophagy, lipid metabolism, and neurodegenerative disease pathways. This study demonstrates that the synergism arises from early competitive inhibition of detoxification and late overactivation of the autophagy–lysosomal system associated with cellular damage. These findings provide transcriptomic evidence for the dynamic synergistic mechanism and offer a scientific basis for rational resistance management of C. medinalis. Full article

Organic fruit production is associated with a specific form of farm management: no artificial pesticides or mineral fertilizers are allowed. Only natural methods of fertilization and plant protection, including preventive practices, are used. The Organic Production Regulation describes all organic farming practices. Fruits from organic production are often perceived by consumers as safe and potentially beneficial to health. Pears contain many bioactive compounds from the polyphenol and carotenoid groups. In the present study, three pear cultivars, namely ‘Alexander Lucas’, ‘Conference’, and ‘Xenia’, grown under organic and conventional systems, were examined during the 2019–2020 cultivation season. The contents of polyphenols, carotenoids, chlorophylls, and vitamin C in pear fruits were measured using total and HPLC methods. Compared with conventional pears, organic pears were characterized by significantly higher vitamin C (8.99 mg/100 g fresh weight), total polyphenol (108.20 mg/100 g F.W.), total flavonoid (63.92 mg/100 g F.W.), total carotenoid (14.58 mg/100 g F.W.), and total chlorophyll (4.29 mg/100 g F.W.) contents. Among the three examined cultivars, ‘Xenia’ exhibited the highest concentrations of several analysed phytochemicals. The growing season significantly affected the phytochemical composition and quality attributes of pear fruits. Full article

South Korea is a highly import-dependent food economy and therefore offers a useful case for examining how an integrated national food control system can be built under trade openness, limited domestic agricultural capacity and changing consumer risk perceptions. This article presents a structured narrative review, rather than a causal impact evaluation, of South Korea’s transition from multi-agency food safety regulation toward an integrated, risk-based food control system. The review is organized through the FAO/WHO national food control system framework and maps Korean legal, institutional and operational evidence onto six analytical dimensions: legal foundations, institutional coordination, risk-based official controls, import supervision, traceability and recall, and risk communication. Examples of embedded risk-analysis principles include the Positive List System for pesticide residues with a default limit of 0.01 mg/kg for substances without a Korean MRL, inspection orders and risk-ranked import controls, barcode-linked recall blocking through the Hazardous Food Sales Prevention System, and public disclosure of unsafe directly purchased overseas products. Quantitative evidence is used descriptively: Korea’s agricultural and food imports reached USD 45.3 billion in 2024, hepatitis A notifications fell from 17,598 in 2019 to 3989 in 2020 after the salted-clam outbreak, and MFDS reported that 12 of 544 overseas direct-purchase products tested in the first half of 2020 contained restricted substances. These indicators suggest improvements in coordination and crisis response capacity, but they do not prove that institutional integration alone reduced foodborne disease incidence. The review finds that South Korea’s model is strongest in institutional consolidation, import-oriented technical standards and digital recall communication, while key challenges remain in small-business compliance burden, scientific independence, data transparency, cross-border e-commerce and novel foods such as cell-cultured food ingredients. Full article

Pesticides are widely used chemical compounds in agriculture, but their presence in water systems represents a significant environmental and health problem. Due to their stability and toxicity, many pesticides are difficult to remove using conventional water treatment methods, which has led to the development of advanced oxidation processes. Photocatalytic processes are based on the activation of semiconductor materials under light irradiation, leading to the formation of reactive species that degrade pesticides into less harmful products. On the other hand, electrocatalytic processes use electrical energy to generate oxidation and reduction reactions on electrode surfaces, enabling efficient degradation of organic pollutants. Both approaches offer high efficiency and the potential for complete mineralization of pesticides. Nanomaterials play a key role in improving these processes, as they provide a large specific surface area, enhanced conductivity, and increased reactivity. In photocatalysis, nanostructured metal oxides such as TiO₂ and ZnO are commonly used, while in electrocatalysis, advanced nanocomposites and modified electrodes are applied to improve electron transfer efficiency and system stability. This review paper provides an overview of recent research in the field of photocatalytic and electrocatalytic systems for pesticide removal from water, with a particular focus on the role of nanomaterials. Special attention is given to current trends, including the development of new nanostructures, hybrid systems, and energy-efficient technologies. The aim of this paper is to present, in a simple and clear way, the potential of these methods and to contribute to a better understanding of their application in environmental protection. Full article

Background: Interpretation of pesticide residues in fruits requires tight integration of surveillance evidence, analytical capability, regulatory context, and mitigation data. Methods: This critical integrative review synthesises analytical chemistry, cumulative risk assessment (CRA), regulatory divergence, and mitigation evidence, strengthened by quantitative monitoring summaries and auditable regulatory examples. Routine enforcement continues to rely on validated QuEChERS extraction coupled with targeted LC-MS/MS and GC-MS/MS. High-resolution mass spectrometry (HRMS) adds unique value for metabolites, transformation products (TPs), and incident response, but its routine enforcement role remains constrained by confirmation logic and harmonised validation. Results: Monitoring shows that exposure is typically multi-residue rather than single-compound; the key interpretive challenge therefore shifts toward CRA prioritisation, sensitive-subpopulation assumptions, and transparent distinction between compliance signals and toxicological inference. We provide (i) headline compliance metrics from EU and US programmes, (ii) surveillance-derived high-frequency residue patterns and co-occurrence motifs to guide CRA prioritisation, (iii) an illustrative, traceable comparison of EU/US/Codex MRL divergence for emblematic citrus residues with EU evidence extracts and US/Codex traceability records, and (iv) mitigation evidence statements standardised by study type and transformation-product reporting. Conclusions: Pesticide residues in fruits should be interpreted through a risk-based framework that distinguishes compliance findings from toxicological concern, prioritises relevant multi-residue drivers, and evaluates mitigation according to both residue reduction and transformation-product uncertainty. Full article

Ethylene oxide (EtO) has been banned in the European Union since 1991 as a fumigant for food commodities. Nevertheless, recurrent contamination incidents, especially since 2020, involving imports from India, have raised significant food safety concerns. Despite regulatory measures, EtO and its metabolite, 2-chloroethanol (2-CE), continue to be detected in a variety of food products, including dried foods, dietary supplements, and food additives. This study presents a QuEChERS-based method involving the conversion of EtO into 2-CE, which is subsequently quantified by isotope dilution gas chromatography–tandem mass spectrometry (GC-MS/MS). In contrast to previously published methods, this protocol utilises an Agilent HP-5ms Ultra Inert column (30 m × 250 μm × 0.25 mm), routinely employed in our laboratory for multi-residue pesticide analysis. The proposed approach is therefore readily adaptable to laboratories already performing multi-residue analyses, as it does not require modifications to existing instrumental configurations. The method was validated in accordance with SANTE/11312/2021 guidelines. A total of 84 samples, primarily imported from India, as well as from Brazil, Argentina, and the United Kingdom, were analysed. 2-CE was detected in four samples, and in two cases, the sum of EtO and 2-CE, expressed as EtO, exceeded the European Union (EU) maximum residue limit (MRL). Full article

Fusarium verticillioides is a maize pathogenic fungus that produces the mycotoxin fumonisin B₁ (FB₁) and causes significant losses in grain quality and yield. In addition, the insect Sitophilus zeamais damages the grains and contributes to the dispersal of the fungus. Although synthetic pesticides provide effective pest control, their excessive use has raised concerns regarding environmental contamination and human health. Therefore, safer alternatives with biopesticide potential are being explored. The aim of this study was to identify an oxygenated volatile compound capable of protecting maize grains against fungal infection and fungal dispersal by the insect vector. The antifungal activity of 1,4-cineole, 1,8-cineole, α-terpineol, terpinen-4-ol, and 1-decen-3-ol against F. verticillioides was evaluated through the fumigant method. Among the tested compounds, 1-decen-3-ol and terpinen-4-ol showed the highest antifungal activity with minimum inhibitory concentration values of 0.5 and 0.9 mM, respectively, significantly affecting fungal growth rate and lag phase. The compound 1-decen-3-ol was selected for further evaluation in stored grains. The application of 1-decen-3-ol effectively prevented maize weight loss and reduced the accumulation of ergosterol and FB₁. These findings suggest that 1-decen-3-ol could represent a potential candidate for the development of biocontrol strategies in grain storage systems. Full article

Edible insects have emerged as a promising alternative to conventional livestock as the global demand for sustainable protein sources rises. Ensuring the safety of insect-based foods is crucial for consumer acceptance and regulatory approval. This review provides a comprehensive overview of the primary chemical and microbiological contaminants associated with edible insects, including heavy metals, pesticides, veterinary drugs, persistent organic pollutants (POPs), mycotoxins, microbiological hazards, and allergenic risks. Current evidence indicates that, when insects are farmed and processed under controlled conditions and in compliance with existing European Union regulations, contaminant levels are generally low and within the range of those found in traditional animal-derived foods. Most studies report that current risks are primarily linked to substrate quality and storage practices. Allergenic risks, particularly cross-reactivity with crustacean and mite allergens, remain a crucial consideration for individuals with sensitivities. Despite these reassuring findings, knowledge gaps persist regarding insect-specific contaminant limits, the metabolic fate of toxins, and the long-term safety of consuming novel insect-derived products. Continued research, targeted monitoring, and regulatory adaptation will be essential to ensure the safe and sustainable integration of insect-based foods into the human diet. Full article

The deployment of insect-resistant rice cultivars is a sustainable strategy for pest control, while the adaptation of pest insects to resistance limits the efficiency of resistant rice varieties. The cytochrome P450 gene CYP4C61 was previously identified as a key locus underlying brown planthopper (BPH, Nilaparvata lugens) adaptation to the resistant rice variety IR36, but its metabolic function remained unknown. Here, we integrated RNAi-mediated gene silencing, untargeted metabolomics, and transcriptomics to elucidate the metabolic role of CYP4C61 in the BPH population virulent to resistant rice IR36. CYP4C61 silencing significantly impaired BPH fitness, including reduced body weight, increased mortality, disrupted feeding behavior, and a progressive body darkening of BPH reared on IR36 rice, reflecting dopamine accumulation entering the melanization branch. Metabolomic analysis identified 240 differentially abundant metabolites in silenced BPH on IR36, revealing a pattern of precursor reduction and product accumulation in the dopamine pathway. Transcriptomic analysis also revealed that CYP4C61 knockdown altered gene expression in the dopamine pathway in a host-dependent manner. Enzyme-linked immunosorbent assay validated dopamine accumulation after CYP4C61 knockdown exclusively in the IR36 background. Our integrated multi-omics evidence indicates that CYP4C61 contributes to dopamine homeostasis in the virulent BPH, providing a mechanistic link between a P450 gene and dopamine-mediated insect adaptation to resistant host plants. Full article

The dynamic spreading behavior of droplets impacting surfaces with different wettability is a critical hydrodynamic issue in industrial applications such as inkjet printing, spray cooling, and pesticide spraying. The maximum spreading diameter coefficient (${\beta }_{max}$) is the key parameter characterizing this process. Existing theoretical models often overlook the gravitational potential energy of droplets, resulting in significant discrepancies between the calculated viscous dissipation times and experimental results, which compromises the prediction accuracy. In this study, we incorporated gravitational potential energy into the energy balance system based on the principle of system energy conservation. We introduced the Bond number (Bo) to characterize the coupling effect of gravity and surface tension. By fitting experimental data, we corrected the viscous dissipation time, obtaining $t_c$ = 3.17$d_0/v_0$, which improves the reliability of dissipated energy calculation. Using Young’s equation and the Cassie model, we derived a fourth-order ${\beta }_{max}$ prediction model that includes the Weber number (We), Reynolds number (Re), contact angle (${\theta }_c$), and Bo number. The results show that regulating the impact height and droplet diameter will affect the trend of the maximum spreading coefficient model curve: the crossover Weber numbers are 41.519 and 41.530 for different liquid viscosities under the specific experimental and modeling conditions of this study. Below these thresholds, the maximum spreading diameter coefficients are more sensitive to impact height (inertial and kinetic-energy) than to droplet diameter (volume, mass, surface energy, gravitational potential energy, Bond number). Above the critical value, the influence of droplet diameter on the maximum spreading diameter coefficient becomes more pronounced. These intersections reflect the balance between size-dependent effects and impact-inertia-related effects under specific conditions, rather than universal physical thresholds. Compared with selected classical models, the proposed model shows better consistency with experimental data and provides improved prediction for the maximum spreading coefficient of water droplets on surfaces with different wettability. This study supplements the perspective of energy analysis for the modeling of droplet impact dynamics, and can provide a basis for the theoretical optimization of spray systems and interfacial fluid control. Full article

This study developed an integrated stochastic framework to forecast cotton pest outbreaks across six tropical Indian agroecosystems. Methodologically, the approach fused entropy and Gini inequality indices, Random Forest machine learning, SHAP-based feature interpretation, fuzzy logic risk assessment, and climate scenario simulations (+2 °C, +20% rainfall) to quantify outbreak variability, driver importance, and system resilience. Findings revealed extreme pest stochasticity (mean = 15.7, variance > 4200), with low entropy (0.06) and a high Gini coefficient (0.82) confirming highly concentrated spatial and temporal outbreaks. While Random Forest demonstrated limited predictive skill (RMSE = 68.9, R² = 0.07), SHAP analysis transparently identified evaporation, wind speed, and humidity as dominant drivers. Fuzzy logic yielded an average risk score of 1.0, reflecting frequent exceedance of biological thresholds. Scenario simulations demonstrated pronounced climate sensitivity: a +2 °C temperature increase raised mean incidence to 18.7, and +20% rainfall increased it to 18.6, resulting in a resilience index of 1.51 that indicates disproportionate vulnerability. In conclusion, combining stochastic variability metrics, explainable machine learning, and threshold-based risk modeling significantly advances tropical pest forecasting under uncertainty. Importantly, this framework contributes to sustainability by enabling climate-resilient cotton production, reducing reliance on chemical pesticides, and supporting adaptive advisory systems that strengthen long-term agroecosystem resilience. These results emphasize the critical need for adaptive, location-specific management strategies to mitigate climate-driven pest intensification and enhance resilience in cotton production systems. Full article