Figure 2 - available from: Environmental Sciences Europe
This content is subject to copyright. Terms and conditions apply.
Source publication
Background:
Accurate pesticide use data are essential when studying the environmental and public health impacts of pesticide use. Since the mid-1990s, significant changes have occurred in when and how glyphosate herbicides are applied, and there has been a dramatic increase in the total volume applied.
Methods:
Data on glyphosate applications we...
Similar publications
Glyphosate is one of the most widely used herbicides in the world. Its safety for both human health and aquatic biomes is a subject of wide debate. There are limits to glyphosate’s presence in bodies of water, and it is usually detected through complex analytical procedures. In this work, the presence of glyphosate is detected directly through opti...
Citations
... Glyphosate-based herbicides (GBHs) are the most extensively utilized herbicides worldwide, containing glyphosate (GLY), or N-(phosphonomethyl) glycine, as their active component [1,2]. Despite GBHs being used in 140 countries globally and commanding a corresponding global market share of 71.6 % from 1974 to 2014, evidence regarding their kinetics in humans, especially concerning metabolism, is still lacking [1][2][3]. ...
... Glyphosate-based herbicides (GBHs) are the most extensively utilized herbicides worldwide, containing glyphosate (GLY), or N-(phosphonomethyl) glycine, as their active component [1,2]. Despite GBHs being used in 140 countries globally and commanding a corresponding global market share of 71.6 % from 1974 to 2014, evidence regarding their kinetics in humans, especially concerning metabolism, is still lacking [1][2][3]. Moreover, the toxicity of GBHs has been a subject of continuous debate. ...
... The proton NMR spectrum was recorded using a Bruker AVANCE 500 MHz instrument (Bruker, Bremen, Germany) equipped with a Carr-Purcell-Meiboom-Gill (CPMG, RD-90°, (t-180°), n-acquire) pulse sequence for 1 H-NMR measurements. The spectra were obtained at 27 °C with water suppression pre-saturation. ...
Background and purpose: Glyphosate-based herbicides, extensively utilized worldwide, raise concerns regarding potential human risks due to the detection of glyphosate (GLY) in human body fluids. This study aims to address critical knowledge gaps regarding whether GLY undergoes metabolism in humans, particularly considering the limited information available on human metabolism. Experimental approach: The study investigated GLY and its metabolites in eight amenity horticultural workers using proton nuclear magnetic resonance (1H-NMR) data analysis. Multiple spot urine samples were collected before and after herbicide applications. Key results: Findings reveal the presence of GLY and its metabolites (AMPA, formaldehyde, sarcosine, glyoxylic acid, and methylamine). Results demonstrate a moderate correlation between median GLY concentration and its metabolites within the studied population. Conclusion: Persuasive evidence suggests the potential metabolism of GLY in humans. 1H-NMR data analysis might be a promising technique for determining the metabolism of GLY in humans, offering valuable insights into urinary excretion patterns.
... Herbicides are a ubiquitous part of our environment that may consequently pose harm to human health. Glyphosate (N-(phosphonomethyl) glycine) is the most heavily-applied herbicide in the US [7]. Approximately 300 million pounds are used annually in agricultural communities throughout the US [8]. ...
Background
Glyphosate use in the United States (US) has increased each year since the introduction of glyphosate-tolerant crops in 1996, yet little is known about its effects on the brain. We recently found that C57BL/6J mice dosed with glyphosate for 14 days showed glyphosate and its major metabolite aminomethylphosphonic acid present in brain tissue, with corresponding increases in pro-inflammatory cytokine tumor necrosis factor-⍺ (TNF-⍺) in the brain and peripheral blood plasma. Since TNF-⍺ is elevated in neurodegenerative disorders such as Alzheimer’s Disease (AD), in this study, we asked whether glyphosate exposure serves as an accelerant of AD pathogenesis. Additionally, whether glyphosate and aminomethylphosphonic acid remain in the brain after a recovery period has yet to be examined.
Methods
We hypothesized that glyphosate exposure would induce neuroinflammation in control mice, while exacerbating neuroinflammation in AD mice, causing elevated Amyloid-β and tau pathology and worsening spatial cognition after recovery. We dosed 4.5-month-old 3xTg-AD and non-transgenic (NonTg) control mice with either 0, 50 or 500 mg/kg of glyphosate daily for 13 weeks followed by a 6-month recovery period.
Results
We found that aminomethylphosphonic acid was detectable in the brains of 3xTg-AD and NonTg glyphosate-dosed mice despite the 6-month recovery. Glyphosate-dosed 3xTg-AD mice showed reduced survival, increased thigmotaxia in the Morris water maze, significant increases in the beta secretase enzyme (BACE-1) of amyloidogenic processing, amyloid-β (Aβ) 42 insoluble fractions, Aβ 42 plaque load and plaque size, and phosphorylated tau (pTau) at epitopes Threonine 181, Serine 396, and AT8 (Serine 202, Threonine 205). Notably, we found increased pro- and anti-inflammatory cytokines and chemokines persisting in both 3xTg-AD and NonTg brain tissue and in 3xTg-AD peripheral blood plasma.
Conclusion
Taken together, our results are the first to demonstrate that despite an extended recovery period, exposure to glyphosate elicits long-lasting pathological consequences. As glyphosate use continues to rise, more research is needed to elucidate the impact of this herbicide and its metabolites on the human brain, and their potential to contribute to dysfunctions observed in neurodegenerative diseases.
... Glyphosate [N-(phosphonomethyl)glycine] is the most widely used herbicide worldwide (Benbrook, 2016;Maggi et al., 2019). Compared to most other herbicides, glyphosate is a high-dose rate compound, usually requiring 0.5-2.0 ...
The evolution and spread of antibiotic resistance are problems with important consequences for bacterial disease treatment. Antibiotic use in animal production and the subsequent export of antibiotic resistance elements in animal manure to soil is a concern. Recent reports suggest that exposure of pathogenic bacteria to glyphosate increases antibiotic resistance. We review these reports and identify soil processes likely to affect the persistence of glyphosate, antibiotic resistance elements, and their interactions. The herbicide molecular target of glyphosate is not shared by antibiotics, indicating that target‐site cross‐resistance cannot account for increased antibiotic resistance. The mechanisms of bacterial resistance to glyphosate and antibiotics differ, and bacterial tolerance or resistance to glyphosate does not coincide with increased resistance to antibiotics. Glyphosate in the presence of antibiotics can increase the activity of efflux pumps, which confer tolerance to glyphosate, allowing for an increased frequency of mutation for antibiotic resistance. Such effects are not unique to glyphosate, as other herbicides and chemical pollutants can have the same effect, although glyphosate is used in much larger quantities on agricultural soils than most other chemicals. Most evidence indicates that glyphosate is not mutagenic in bacteria. Some studies suggest that glyphosate enhances genetic exchange of antibiotic‐resistance elements through effects on membrane permeability. Glyphosate and antibiotics are often present together in manure‐treated soil for at least part of the crop‐growing season, and initial studies indicate that glyphosate may increase abundance of antibiotic resistance genes in soil, but longer term investigations under realistic field conditions are needed. Although there are demonstratable interactions among glyphosate, bacteria, and antibiotic resistance, there is limited evidence that normal use of glyphosate poses a substantial risk for increased occurrence of antibiotic‐resistant, bacterial pathogens. Longer term field studies using environmentally relevant concentrations of glyphosate and antibiotics are needed.
... This interest grew particularly after federal lawmakers authorized conservation compliance policies in the 1990s, mandating less tillage for producers operating on highly erodible land [23]. Additionally, the increased availability and popularity of post-emergent (i.e., applied after emergence of the cash crop) herbicides and herbicide resistant crops became commercially available and more popular in U.S. crop production [24,25] further motivated this research area. The body of prior research is relatively outdated and relied on standard economic and statistical techniques to evaluate the use of conservation tillage and herbicides in isolation, without explicitly accounting for other geographic, agronomic, and economic factors that would play a role in a producer's decision to adopt conservation tillage. ...
Herbicide use is widespread in agricultural production to control weeds prior to and after planting and to “burndown” weeds in the spring for conservation tillage. Whether conservation tillage adoption leads to higher herbicide usage has been a question of policy relevance for decades in the United States. Older U.S. studies using standard statistical and economic techniques have not consistently demonstrated higher herbicide usage levels among producers practicing conservation tillage, but these studies did not fully account for other practices, economic, or agronomic factors. To provide a more timely and comprehensive understanding of the importance of herbicides to conservation tillage, this study achieves two objectives with the most recent, nationally representative data from the US Department of Agriculture. First, it describes trends and compares conservation tillage and herbicide usage among field corn and soybean producers, similar to previous studies using standard economic techniques. Second, a Classification and Regression Tree (CART) model is employed—a novel methodology relative to previous studies that offers distinct advantages over traditional regression modeling—to evaluate the importance of herbicide use for conservation tillage adoption while accounting for other factors. Pairwise mean comparisons for field corn and soybeans indicated that herbicide usage pre-emergence was significantly higher with conservation tillage, but there was no consistent, significant differences in herbicide usage post-emergence. The CART analysis (with prediction accuracy ranging from 68–72%) also showed that pre-emergent use of glyphosate was the strongest predictor (with predicted probabilities from 0.83–0.86) of conservation tillage for field corn in 2016 and soybeans in 2018. Other factors such as the use of crop rotations, highly erodible land, region, and farm size were also strong predictors of conservation tillage. These findings highlight the importance and complexity of herbicide use in the adoption of conservation tillage for U.S. field corn and soybeans.
... The potential food loss is projected to exceed 150 million tons [1]. Currently, traditional manual or semi-mechanical pesticide spraying methods suffer from incomplete coverage and low efficiency, failing to meet the current pest and disease control requirements [2,3]. Thus, accelerating the development of an efficient modern pest control technology system is urgent. ...
Traditional manual or semi-mechanized pesticide spraying methods often suffer from issues such as redundant coverage and cumbersome operational steps, which fail to meet current pest and disease control requirements. Therefore, there is an urgent need to develop an efficient pest control technology system. This paper builds upon the Deep Q-Network algorithm by integrating the Bi-directional Long Short-Term Memory structure to propose the BL-DQN algorithm. Based on this, a path planning framework for pest and disease control using agricultural drones is designed. This framework comprises four modules: remote sensing image acquisition via the Google Earth platform, task area segmentation using a deep learning U-Net model, rasterized environmental map creation, and coverage path planning. The goal is to enhance the efficiency and safety of pesticide application by drones in complex agricultural environments. Through simulation experiments, the BL-DQN algorithm achieved a 41.68% improvement in coverage compared with the traditional DQN algorithm. The repeat coverage rate for BL-DQN was 5.56%, which is lower than the 9.78% achieved by the DQN algorithm and the 31.29% of the Depth-First Search (DFS) algorithm. Additionally, the number of steps required by BL-DQN was only 80.1% of that of the DFS algorithm. In terms of target point guidance, the BL-DQN algorithm also outperformed both DQN and DFS, demonstrating superior performance.
... El mecanismo de acción del GLY es la interrupción de la síntesis de los aminoácidos fenilalanina, tirosina y triptófano. Este proceso se presenta al inhibir la enzima 5-enolpiruvilshikimato-3-fosfato sintasa (EPSPS) (Benbrook 2016). La inhibición de la enzima EPSPS produce un flujo alto de carbono hacia el shikimato-3-fosfato, que se convierte en altos niveles de shikimato, acumulándose en los tejidos vegetales y causando daños a las plantas ) (figura 2). ...
esticide pollution, such as that caused by glyphosate, affects marine and terrestrial ecosystems globally. This agrochemical pollution is exacerbated by climate change, which leads to fluctuations in temperatures and increases in greenhouse gases. These factors stress organisms and their microbiomes. Additionally, the stress caused by climate change forces organisms to adapt to changes in precipitation patterns, resulting in droughts and floods. Consequently, the use of pesticides has also changed, often leading to the application of larger quantities than were previously required, due to the growing resistance of some pests. It has been documented that climate change has driven many organisms to migrate geographically. The interaction between pesticide uses and temperature fluctuations promotes plant diseases, reducing the availability and quality of food, while also causing damage to the reproduction of certain organisms, such as insects, amphibians, and fish, among others. In the case of glyphosate, its intensive and widespread use—primarily due to genetically modified seeds—has led to contamination of virtually all ecosystems with this compound, including humans. Keywords: Pesticides, Glyphosate, Climate change.
... Glyphosate is the most widely used herbicide globally due to its effectiveness in eliminating a wide variety of weeds, making it an essential tool for modern farmers (Benbrook, 2016). However, its long-term and large-scale use raises questions about its impact on soil, particularly on soil texture and its ability to support sustainable agricultural practices (Giesy et al., 2000). ...
This study examines the effect of different glyphosate doses on the soil texture in four rural communes of the N'Zérékoré prefecture in Guinea. A complete randomized block design was used to assess the impact of glyphosate doses on several soil parameters, including granulometry, aggregate stability, bulk density, and porosity. The analysis of variance (ANOVA) revealed that glyphosate doses significantly influence Granulometry A (p = 0.02881) and show a trend toward affecting soil aggregate stability (SI) and overall stability (Sg), although these effects are not significant at the 0.05 threshold. Conversely, glyphosate doses had no significant effect on Granulometry Lf, Granulometry Lg, bulk density, and soil porosity, as these parameters were more influenced by soil type and year. These results suggest that higher doses of glyphosate can alter soil structure, but the effect varies depending on specific environmental conditions, particularly soil type and annual variations. Careful management of glyphosate doses is therefore recommended to preserve soil quality and support sustainable agricultural practices.
... Glyphosate is the most widely used herbicide globally due to its effectiveness in eliminating a wide variety of weeds, making it an essential tool for modern farmers (Benbrook, 2016). However, its long-term and large-scale use raises questions about its impact on soil, particularly on soil texture and its ability to support sustainable agricultural practices (Giesy et al., 2000). ...
... While these developments are promising, it is essential to recognize that they remain in early stages and do not yet offer a proven alternative that matches the cost-effectiveness and broad efficacy of synthetic herbicides like glyphosate across all criteria. Due to its broad-spectrum weed control, reliable yield impact, and relatively low environmental persistence under regulated use, glyphosate remains one of the most widely employed herbicides worldwide [12]. Though nano-based and bio-stimulant alternatives show great potential, "new" does not automatically mean "better" when considering critical agricultural factors, such as scalability, yield consistency, environmental persistence, and economic feasibility. ...
The integrity of environmental toxicology is undermined by selective risk assessments that focus intently on certain chemicals while overlooking others. Glyphosate, one of the most widely used herbicides, serves as a case study of how regulatory decisions can be shaped by incomplete or biased evidence. This paper argues for a holistic approach to toxicology, calling for balanced assessments that consider both health risks and societal benefits. It critically examines current regulatory practices concerning glyphosate, investigating its association with non-Hodgkin’s lymphoma and its positive effects on agricultural productivity and food security. While definitive evidence linking glyphosate to cancer remains inconclusive, its role in enhancing crop yields, by as much as 20 % in some regions, has had measurable benefits for food security and public health. The paper advocates for regulatory frameworks that transparently weigh these societal benefits against potential health risks, particularly in settings of occupational exposure, where the need for balanced assessment is especially pressing. Through a narrative review of major studies, this paper underscores the need for transparency, accountability, and evidence-based approaches in environmental regulation. Such practices are essential for crafting policies that not only mitigate risk but also promote global food security and well-being. By integrating both risks and benefits into the regulatory process, the study proposes an inclusive and data-driven approach to chemical policy that aligns with the broader goals of sustainability and public health.
... Evolution of HR weeds not only compromise effectiveness of herbicides to which weeds have developed resistance but also places a significant financial strain on the farmers [9][10][11][12]. To tackle these HR weed populations, farmers generally rely on alternative effective and expensive preemergence and postemergence herbicide premixes or tank-mixtures with multiple herbicide modes of action (MOA) [13]. This strategy increases the production costs and the use of unintended herbicides, leading to higher risk of herbicide residues in the environment that can disrupt ecosystems and reduce biodiversity [14]. ...
Weeds pose a serious production challenge in various agronomic crops by reducing their grain yields. Increasing cases of herbicide-resistant (HR) weed populations further exacerbate the problem. Future weed control tactics require the integration of non-chemical and reduced chemical-based strategies that can target site- and specie-specific weed management (SSSWM). Advanced machine learning technology has the potential to localize and detect weed seedlings to implement SSSWM. However, due to large biological variability among various weed species and environmental conditions where they grow, accurate and precise weed detection remains challenging. The main objectives of this research were to (1) develop an annotated image database of cocklebur (Xanthium strumarium L.), dandelion (Taraxacum officinale), common waterhemp (Amaranthus tuberculatus), Palmer amaranth (Amaranthus palmeri) and common lambsquarters (Chenopodium album L.), and (2) investigate the comparative performance (speed and accuracy) of YOLOv8, YOLOv9, YOLOv10, YOLOv11 and Faster R-CNN algorithms in detecting those weed species. A weed dataset with bounding box annotations for each weed species was created, consisting of images collected under variable field conditions which were preprocessed and augmented to create a dataset of 2348 color images. The YOLOv8, YOLOv9, YOLOv10, YOLOv11 and Faster R-CNN were trained using the annotated weed image database to detect each weed species. Results indicated that YOLOv11 was the fastest model with inference time of 13.5 milliseconds (ms) followed by YOLOv8 and YOLOv10 with inference time 23 and 19.3 milliseconds (ms), respectively. The YOLOv9 had the highest accuracy in detecting different weed species with an overall mean average precision (mAP@0.5) of 0.935. In contrast, the Detectron2 with Fast R-CNN configuration provided mAP@0.5 of 0.821 with an inference time of 63.8 ms. These results suggest that the YOLO series algorithms have the potential for real-time deployment for weed species detection more accurately and faster than Faster R-CNN in agricultural fields.
