Pesticide Losses Research Articles

Machine learning‐based screening of pesticide adjuvants for reduction of pesticide losses on wheat leaf surfaces

AbstractUsing pesticide spray adjuvants to improve the physicochemical properties of pesticide liquids can effectively increase droplet deposition on target surfaces. However, there are no clear guidelines for the selection among complex and diverse adjuvants. We aimed to build a model for screening pesticide adjuvants through machine learning. In this paper, five machine learning classification models (decision tree, support vector machine, random forest, logistic regression, and naive Bayes) were developed to predict droplet deposition performance on the superhydrophobic plant leaf surfaces based on the physicochemical properties of pesticide liquids. Among these models, decision tree, support vector machine, and random forest exhibited superior performance. Significance analysis showed that adhesion, equilibrium surface tension, and contact angle are critical factors influencing droplet deposition on wheat leaves. Notably, the decision tree model, due to its simplicity and intuitiveness, is particularly suitable for field applications. Our findings provide a platform for the rapid and accurate screening of pesticide spray adjuvants by simply measuring the physicochemical properties of pesticide droplets.

Optimization of Ferimzone and Tricyclazole Analysis in Rice Straw Using QuEChERS Method and Its Application in UAV-Sprayed Residue Study.

Rice straw is used as livestock feed and compost. Ferimzone and tricyclazole, common fungicides for rice blast control, can be found in high concentrations in rice straw after unmanned aerial vehicle (UAV) spraying, potentially affecting livestock and human health through pesticide residues. In this study, an optimized method for the analysis of the two fungicides in rice straw was developed using the improved QuEChERS method. After the optimization of water and solvent volume, extraction conditions including ethyl acetate (EtOAc), acetonitrile (MeCN), a mixed solvent, and MeCN containing 1% acetic acid were compared. Different salts, including unbuffered sodium chloride, citrate, and acetate buffer salts, were compared for partitioning. Among the preparation methods, the MeCN/EtOAc mixture with unbuffered salts showed the highest recovery rates (88.1-97.9%, RSD ≤ 5.1%). To address the severe matrix effect (%ME) of rice straw, which is characterized by low moisture content and cellulose-based complex matrices, samples were purified using 25 mg each of primary-secondary amine (PSA) and octadecylsilane (C18), without pesticide loss. The developed method was validated with a limit of quantification (LOQ) of 0.005 mg/kg for target pesticides, and recovery rates at levels of 0.01, 0.1, and 2 mg/kg met the permissible range (82.3-98.9%, RSD ≤ 8.3%). The %ME ranged from -17.6% to -0.3%, indicating a negligible effect. This optimized method was subsequently applied to residue studies following multi-rotor spraying. Fungicides from all fields and treatment groups during harvest season did not exceed the maximum residue limits (MRLs) for livestock feed. This confirms that UAV spraying can be safely managed without causing excessive residues.

Surface hydrophobicity mechanism of poultry red mite, Dermanyssus gallinae (Acari: Dermanyssidae), gives novel meaning to chemical control

Surface hydrophobicity of organisms provides biological self-protection. The hydrophobicity of pest surface, acting as a main obstacle for the pest control, can lead to low utilization and high loss of pesticides. Dermanyssus gallinae is a notorious pest in egg-laying hens, whose control primarily depends on acaricide spraying, while its surface hydrophobicity and potential influence on pesticide effectiveness are not clear. In the present study, the contact angle measurements revealed that the surface of D. gallinae was hydrophobic. Analysis using scanning electron microscopy (SEM) and transmission electron microscopy (TEM) showed that the surface microstructures of D. gallinae consist of cuticular folds, with a lipid-rich outermost layer of the cuticle. Based on gas chromatography-mass spectrometry (GC-MS) and gas chromatography (GC), it was found that the major compositions of cuticular lipids were fatty acids and n-alkanes. Modifying the chemical compositions and microstructures of the D. gallinae surface resulted in a reduction in surface hydrophobicity and an increase in the permeation of Rhodamine B through the cuticle. This observation suggested that the chemical compositions and microstructures were pivotal in determining surface hydrophobicity, hindering compound penetration into the cuticle. Finally, it was found improving the wettability of pesticide solution by adding surfactants could overcome the surface hydrophobicity and enhance the efficacy of pesticide against the mites. This study sheds light on the surface hydrophobicity mechanism of D. gallinae and provides a novel strategy to improve the efficacy of acaricides against the mites.

Downsizing gum Arabic-based abamectin particles using flash nanoprecipitation method for enhanced pesticide deposition

Pesticides are vital for ensuring crop protection and stable yields, but their low efficiency and eco-unfriendly carriers raise environmental concerns. In this study, abamectin nanopesticides were designed and fabricated using natural polysaccharides [gum arabic (GA)] and a co-stabiliser via flash nanoprecipitation (FNP) method to reduce the size of nanopesticides and enhance their foliar affinity and deposition. Various co-stabilisers were innovatively introduced into the FNP process; the synergy between GA and the co-stabiliser significantly reduced the particle size (111.5 nm), narrowed the size distribution (polydispersity index = 0.078), and enhanced the stability and release performance of the nanopesticides. Importantly, the downsized nanopesticides effectively improved retention on leaf surfaces, reducing pesticide loss. In addition, because of the excellent control capability of the FNP method, the particle size of the nanopesticides could be flexibly adjusted by modifying the flow-based process parameters. Nanopesticides with small sizes demonstrated good control efficacy against Tetranychus urticae, comparable to those of commercial emulsion in water formulations. This study provides an effective approach for enhancing the utilisation efficiency of pesticide droplets by reducing particle size to ensure sustainable agriculture.

A spatio-temporal analysis of environmental fate and transport processes of pesticides and their transformation products in agricultural landscapes dominated by subsurface drainage with SWAT+

Pesticides are detected in surface water and groundwater, endangering the environment. In lowland regions with subsurface drainage systems, drained depressions become hotspots for transport of pesticides and their transformation products (TPs). This study focuses on detailed modelling of the degradation and transport of pesticides with different physico-chemical properties. The objective is to analyse complex hydrological transport processes, to understand the temporal and spatial dynamics of the degradation and transport of pesticides. The ecohydrological model SWAT+ simulates hydrological processes as well as agricultural management and pesticide degradation, and can therefore be used to develop pesticide loss reduction strategies. This study focuses on modelling of three pesticides (pendimethalin, diflufenican, and flufenacet), and two TPs, flufenacet-oxalic acid (FOA) and flufenacet sulfonic acid (FESA). The study area is a 100-hectare farmland in the northern German lowlands of Schleswig-Holstein that is characterized by an spacious drainage network of 6.3 km and managed according to common conventional agricultural practice.SWAT+ modelled streamflow with very good agreement between observed and simulated data during calibration and validation. Regarding pesticides, the model performance for highly mobile substances is better than for non-mobile pesticides. While the transport of the moderately to very mobile substances via tile drains played an important role in both wet and dry conditions, no transport via tile drains was modelled for the highly sorptive and non-mobile pendimethalin.In conclusion, the model can reliably represent the degradation of moderately to very mobile pesticides in small-scale tile drainage-dominated catchments, as well as surface runoff-induced peak loads. However, it has weaknesses in accounting for the subsurface transport of non-mobile substances, which can lead to an underestimation of the subsequent delivery after precipitation events and thus underestimates the total load.

Sea urchin-like nanocarrier for enhancing pesticide retention and rain fastness on hydrophobic and hydrophilic crop foliage

Foliar washoff by rainfall is a major factor inducing the inefficient utilization of pesticides. Enhancing the adhesion and retention of pesticide on plant foliage has long been of interest. The presence of waxy platelets on most plant foliage surfaces renders them rough and hydrophobic. This reduces the area of contact between pesticide particle and plant foliage, which decreases the adhesion. In this study, we developed a pesticide nanocarrier (PANI/HACC) with sea urchin-like surface morphology based on polyaniline (PANI) doped with biodegradable 2-hydroxypropyltrimethyl ammonium chloride chitosan (HACC). Then, azoxystrobin (AZOX) loaded nanoparticles (AZOX@PANI/HACC) was synthesized by physical adsorption. It exhibited retention rates of 61.4% on rice leaves and 64.6% on cucumber leaves, which were higher than that of commercially available azoxystrobin water dispersible granules (AZOX-WDG, 42.1% and 24.5%, respectively) and suspension concentrates (AZOX-SC, 23.1% and 58.8%, respectively). Additionally, pot experiments demonstrated that the control efficacy of AZOX@PANI/HACC on rice against Rhizoctonia solani was 1.64-fold and 3.0-fold of that of AZOX-WDG and AZOX-SC, respectively. The higher retention performance of AZOX@PANI/HACC was attributed to the stable adhesion by fitting nanometer-sized spikes into the spaces between the waxy platelets. Overall, the pesticide nanocarrier with spiky surface morphology provides an effective strategy for improving pesticide retention and reducing pesticide loss in agricultural production.

Development of a 3D point cloud reconstruction-based apple canopy liquid sedimentation model

China leads the world in apple production, contributing to over half of the global total. Annually, extensive pesticide use is employed in apple cultivation, but the uncertain quantities of pesticide deposition and indiscriminate application have resulted in significant pesticide loss and residue. This poses a considerable potential risk to human health. This paper focuses on ground-based plant protection and stratifies the canopy horizontally, using 3D point cloud reconstruction technology and tree deposition experiments to explore the relationship between canopy leaf area index and pesticide deposition. By calculating the droplet penetration coefficient based on the amount of solution deposited at various canopy layers, a functional model linking leaf area index and droplet penetration coefficient has been established, with a correlation coefficient (R2) of 0.92. Based on this model, and by integrating the canopy volume with the amount of solution deposited on the outermost layer of the canopy, the total solution deposition on the entire tree can be estimated. According to the deposition model, there is a negative correlation between the amount of solution deposited on the canopy and the leaf area index of the canopy. Moreover, the experiments have shown that when the spray vehicle travels at a speed of 1.5 m/s, the maximum amount of solution is deposited while still ensuring an effective deposition rate. The establishment of the deposition estimation model allows for the visualization of canopy solution deposition and can guide fruit farmers in determining the appropriate frequency of spraying based on the severity of pest and disease infestations.

Modulating Leaching Behavior of Boscalid Fungicide in Soil Through Organic Amendments

ABSTRACT The leaching loss and movement of pesticides need to be minimized to safeguard the aquatic environment and human health. In a laboratory study, the changes in the leaching and downward movement behavior of boscalid fungicide were examined in soil (Typic Hapludoll) columns (0–30 cm) receiving no amendment (control) or with the application of farmyard manure (FYM) and pine needle biochar (PNB) in surface (0–15 cm) soil @ 5 t ha−1. No boscalid residues (<0.01 µg mL−1) were detected in the leachate under any treatment. Both FYM and PNB were effective in limiting the movement of boscalid in soil compared to control. FYM maintained the highest boscalid concentration (1.41 µg g−1) in the top (0–2.5 cm) soil while in PNB treated soil the highest sorbed boscalid (0.58 µg g−1) could accumulate at 2.5–5.0 cm soil depth. The depth-wise distribution of the boscalid concentration in soil could be well predicted by third order polynomial equations (R2 value = 0.929 to 1.000, all significant at p ≤ 0.01). The FTIR spectra show that the boscalid retention onto these amendments was through H-bonding and π–π interactions. As compared to FYM, the PNB had a relatively lower proportion of soluble- and desorbed-boscalids but a higher proportion of irreversibly sorbed boscalid and appeared to be an effective organic amendment for the areas prone to high surface run-off.

Economic driving characteristics of agricultural non-point source pollution and prevention suggestions: a case study from Shandong province in China

Agricultural non-point source pollution (ANSP) constraints on the development of the agricultural economy, grasp the interaction between the two, and develop targeted prevention and control policies in accordance with the evolution of different stages of the characteristic is essential. This study examines the economic characteristics of ANSP in Shandong Province to propose targeted countermeasures. Selected the time series data of Shandong Province from 2000 to 2020 to test the Environmental Kuznets Curve (EKC) characteristics between ANSP and agricultural economic growth (AEG), and the Vector Error Correction model (VECM) is used further to explore the dynamic relationship and mechanism. We validate the existence of an Inverted U-shaped EKC in Shandong Province, and the inflection points of pesticides, fertilizers, and agricultural films were reached in 2007 and 2008. The changes in pesticide loss and fertilizer loss have a positive impact on the dynamics of AEG in the short term, but there is an incremental inhibition in the long term. The dynamic effect of the impulse response diagram between the amount of agricultural film residues and AEG all shows a positive impact. The average explanatory contribution of pesticide loss, fertilizer loss, and agricultural film residue to AEG decreases by 12.14%, 7.7%, and 3%, respectively. Therefore, policy suggestions are proposed to realize the coordinated development of ANSP and economic development.

Pesticide volatilization in biobed systems’ potential substrates. A viable simple laboratory experiment to determine pesticide losses to the environment.

Pesticide volatilization in biobed systems’ potential substrates. A viable simple laboratory experiment to determine pesticide losses to the environment.

In vitro modeling of the post-ingestion mobilization and bioaccessibility of pesticides sorbed to soil and house dust

Soils and dusts can act as sinks for semivolatile lipophilic organic compounds and children ingest relatively large amounts of both soils and dusts. Following intake, sorbed chemicals may desorb (mobilize) and become available for intestinal absorption (bioaccessible). When chemicals are not degraded in the digestive tract, mobilization can approximate bioaccessibility. Alternatively, when gastrointestinal degradation of mobilized chemicals does occur, it can be useful to separate mobilization from bioaccessibility.In this study we used synthetic digestive fluids in a sequential, three-compartment (saliva, gastric, and intestinal) in vitro assay to construct mobilization and bioaccessibility models for 16 pesticides (log Kow 2.5–6.8) sorbed to 32 characterized soils and house dusts. To address the potential loss of mobilized pesticides due to absorption, the assays were repeated using a solid phase sorbent (tenax) added to the digestive fluid immediately after addition of the intestinal fluid components.We found that pesticide mobilization was predicted by pesticide log Kow and the carbon content of the soils and dusts. Pesticide loss measurably reduced the bioaccessibility of most pesticides, and bioaccessibility was largely predicted by log Kow and pesticide loss rate constants. Introduction of the sink increased mobilization by x̄ = 4 ± 6% (soil) and x̄ = 9 ± 7% (dust) while bioaccessibility increases were x̄ = 41 ± 21% (soil) and x̄ = 24 ± 12% (dust).The physicochemical properties of the soils, dusts, and pesticides used in this study successfully predicted the in vitro mobilization and bioaccessibility of the pesticides. This suggests that modeling of pesticide mobilization and bioaccessibility could reduce uncertainty in exposure and risk assessments.

Auto-LIA: The Automated Vision-Based Leaf Inclination Angle Measurement System Improves Monitoring of Plant Physiology.

Plant sensors are commonly used in agricultural production, landscaping, and other fields to monitor plant growth and environmental parameters. As an important basic parameter in plant monitoring, leaf inclination angle (LIA) not only influences light absorption and pesticide loss but also contributes to genetic analysis and other plant phenotypic data collection. The measurements of LIA provide a basis for crop research as well as agricultural management, such as water loss, pesticide absorption, and illumination radiation. On the one hand, existing efficient solutions, represented by light detection and ranging (LiDAR), can provide the average leaf angle distribution of a plot. On the other hand, the labor-intensive schemes represented by hand measurements can show high accuracy. However, the existing methods suffer from low automation and weak leaf-plant correlation, limiting the application of individual plant leaf phenotypes. To improve the efficiency of LIA measurement and provide the correlation between leaf and plant, we design an image-phenotype-based noninvasive and efficient optical sensor measurement system, which combines multi-processes implemented via computer vision technologies and RGB images collected by physical sensing devices. Specifically, we utilize object detection to associate leaves with plants and adopt 3-dimensional reconstruction techniques to recover the spatial information of leaves in computational space. Then, we propose a spatial continuity-based segmentation algorithm combined with a graphical operation to implement the extraction of leaf key points. Finally, we seek the connection between the computational space and the actual physical space and put forward a method of leaf transformation to realize the localization and recovery of the LIA in physical space. Overall, our solution is characterized by noninvasiveness, full-process automation, and strong leaf-plant correlation, which enables efficient measurements at low cost. In this study, we validate Auto-LIA for practicality and compare the accuracy with the best solution that is acquired with an expensive and invasive LiDAR device. Our solution demonstrates its competitiveness and usability at a much lower equipment cost, with an accuracy of only 2. 5° less than that of the widely used LiDAR. As an intelligent processing system for plant sensor signals, Auto-LIA provides fully automated measurement of LIA, improving the monitoring of plant physiological information for plant protection. We make our code and data publicly available at http://autolia.samlab.cn.

From Fruit Waste to Hydrogels for Agricultural Applications

Here, we describe and assess a method for reusing specific food waste to make hydrogels, which can be employed to improve the efficacy of agrochemicals and water. It represents an approach for tackling current challenges, such as food waste, water management, and pesticide optimization. Depending on the formulation, the hydrogels were created by crosslinking pectin and starch with CaCl2 or sodium trimetaphosphate. FTIR and SEM were employed to investigate the methylation degree of the extracted pectin, as well as the surface morphology and interior structure of the hydrogels. The swelling behavior and water retention in sandy soil have been investigated. In addition to the hydrogels’ potential to control and reduce pesticide loss, the herbicide Picloram is a model compound. The results show that the hydrogels have important swelling, up to 300%, and a capacity to retain water, preserve, and increase the water content in sandy soil up to 12 days. Picloram experiments show that hydrogels can limit herbicide mobility for up to 30 days under controlled conditions. The conversion of food wastes to highly valuable materials is a promising approach to optimize the water consumption and the loss of agrochemicals regarding sustainable agriculture.

Self-assembly of eugenol-loaded particles to regulate the adhesion of carriers on leaves for efficient foliar applications and ecotoxicological safety

Currently, there is a pressing need to develop an agrochemical-loaded system that is both uncomplicated and efficient, thereby enhancing the adhesion of agrochemical to leaf surfaces and optimizing their insecticidal efficacy, while concurrently mitigating environmental risks. The flexible eugenol-loaded particles were synthesized via a one-step polyurethane self-assembly reaction, utilizing polyethylene glycol (PEG) as the soft segment and 4,4-diphenylmethane diisocyanate (MDI) as the hard segment. The increase in the length of the soft segment enhances the flexibility of the particles, thereby improving the contact area and adhesion with the foliar surface. When flexible particles are applied on the foliar surface, they can achieve satisfactory resistance to rainfall erosion. When the PEG molecular weight is 800, the residual concentration of eugenol can still reach 42.11% after 6 washes. The carrier protects the active ingredients and improves the resistance to ultraviolet irradiation. After 5 h of ultraviolet irradiation, the concentration of eugenol remained at 59.03% when PEG with a molecular weight of 200 was employed. Greenhouse experiments showed that the flexible transformation of particles greatly enhanced the application effect of spray on the foliar surface of particles. After undergoing three washes, the mortality of the particles can be enhanced by 5.4–8.4 times compared to that of emulsion concentrate (EC) sample. The enhancement of leaf retention performance reduces environmental risks caused by pesticide loss. Meanwhile, the controlled release of particles also reduces the acute toxicity to zebrafish. The toxicity selection pressure of the EUG@P800-Ps sample is 10.6 times that of the EC sample. In conclusion, the preparation process of the system is simple, and the flexible transformation is an effective strategy to improve the foliar application effect of spray and improve the environmental safety.

Controlled release of herbicides through glyphosate intercalated layered double hydroxides and enhancement of anti-scouring ability via poly-l-aspartic acid and chitosan modification

Nanocarrier preparations could effectively improve the utilization rate of pesticides, and reduce pesticide loss. In this study, glyphosate (GLY)-loaded MgAl layered double hydroxide (GLY@LDH) was synthesized via an in-situ method. Subsequently, GLY@LDH composite samples were prepared using a layer-by-layer self-assembly approach and modified with poly-L-aspartic acid (PASP) and chitosan (CS). XRD, FT-IR, SEM, and Zeta potential characterization confirmed that GLY was successfully loaded in the interlayer of LDHs and PASP/CS were successfully encapsulated on the surface of the composite sample. The release effect in different ionic solutions and soils was studied and analyzed. The release behavior conforms to the Ritger-Peppas kinetic model, and the release mechanism was ion exchange, which was further explored by means of XRD, SEM, and molecular simulation. The results of the anti-scouring experiment and contact angle measurement indicated that the layered self-assembly material enhanced the washing resistance of the material. The practical application effect of the sample was verified through a pot experiment. This study provides new insights into the simple preparation of pesticide-controlled release formulations that reduce leaching losses.

GeoAPEX-P, A web-based, spatial modeling tool for pesticide related environmental assessment

Hydrologic models are widely used to support evaluation and decision-making of nutrient and pesticide impacts on the environment including water quality and sensitive aquatic species, yet such tools are typically designed for research purposes that are time consuming to use and require certain expertise, data, and software. In this study, a web-based tool for the Agricultural Policy Environmental eXtender (APEX) model with nutrient and pesticide prediction functions was built incorporating GIS functionality, a spatial and online database, automated modeling system, and user-friendly interface. It provides a computation platform for conducting nutrient and pesticide evaluations at small watershed and field scales with commonly used scenarios and management options. Case studies were conducted, and results demonstrate the ability of the tool to identify spatial variability of runoff and sediment, nutrient, and pesticide losses. This tool can also provide rapid and site-specific guidance to decision makers for evaluating pesticide related assessments.

Soil pitting mitigates runoff, erosion and pesticide surface losses in maize crops in the Belgian loess belt

Soils of the loess belt of Western Europe are intensively cropped and particularly prone to runoff and soil erosion, especially when planted with row crops such as maize or potatoes, characterized by a low soil cover during erosive spring storms. In this context, micro-basin tillage techniques could help mitigate these risks while being fairly easy to integrate into conventional cropping systems, yet very few studies have investigated the effectiveness of this technique in a maize crop. Soil pitting was therefore tested across 14 site*years of field trials in Belgium by a newly designed roller adapted to a seeding unit forming small depressions in-between maize rows. Runoff and surface losses of sediments and pesticides were measured on soil pitted plots under natural rainfall and compared with conventionally tilled plots. Seasonal runoff and erosion rates were reduced on average by 69% and 83%, respectively, following soil pitting. Median curve number (CN) values calibrated (λ = 0.05) on this dataset are 68 for the control, and 63 for the soil pitting treatment. Analysis of individual rainfall event data reveals that the mitigation effect remains consistent throughout the season, and is even slightly higher for highly erosive rainfall events than for light events. Whereas herbicide concentrations, and hence in-situ ecotoxicity risk indicators, were similar between control and soil pitted treatments at the experimental plot scale, at larger scales the environmental impact on water bodies would be mitigated by soil pitting thanks to the reduction in absolute runoff and soil loss. Future research should further investigate the impacts of soil pitting on crop yields under a broad range of rainfall conditions.

Promotion of droplet deposition, diffusion-wetting and retention on hydrophobic surfaces by nonionic star-shaped oligomeric surfactants

Massive wastage of pesticides has caused significant environmental pollution and economic loss. However, existing strategies to control loss of pesticides are complex or step-specific. Here, nonionic star-shaped surfactants that can simultaneously achieve comprehensive regulation of deposition, diffusion-wetting and retention are designed and synthesized, which greatly improve the utilization efficiency of pesticides while reducing environmental risks. Structure–activity relationships for the surfactants were elucidated, and their interactions with hydrophobic surfaces were studied in detail. The results show that the addition of nonionic star-shaped oligomeric surfactant to a solution decreased droplet bouncing, increased the diffusion-wetting area, slowed droplet evaporation; and the surfactant III-8b showed the best performance. On the basis of these results, III-8b was used as a synergist for Glyphosate-isopropylammonium 41 % AS. The biological activity test showed that the herbicidal activities of the surfactant III-8b-containing glyphosate solution against Pharbitis nil (L.) Choisy and Echinochloa crusgalli (L.) were substantially better than the activities in the absence of surfactant.

ADDI-Spraydrift: A comprehensive model of pesticide spray drift with an assessment in vineyards

Spray drift is a major contributor to pesticide losses in the atmosphere leading to nontargeted ecosystem exposure. An overview of currently used ground-application spray drift models highlighted gaps in the description of the processes occurring during and after spraying. The ADDI-Spraydrift model was developed to bridge some of these gaps and provide a comprehensive, yet concise description of spray drift processes. The model is based on a random walk approach that describes droplet emission, dispersion and evaporation, ground deposition and canopy interception, and accounts for atmospheric stability regimes, and in-canopy turbulence. It predicts airborne concentration, canopy interception and deposition to the ground downwind from the sprayer. The sensitivity analysis to wind speed, active matter content, leaf angle, canopy height, leaf area index, ejection angle and velocity demonstrated the consistency of the model behaviour. The model was calibrated and evaluated against the Ganzelmeier et al. (1995) sedimentary spray drift data in vineyards. The model satisfactorily predicted droplets deposition to the ground downwind from the field boundary with a mean deviation between modelled and measured deposition of 1.3%. A discrepancy was observed at 3 and 5 m downwind from the field boundary attributed to the sensitivity to spraying conditions for which several hypotheses are discussed. Bearing in mind the need to explicitly describe the emitted droplet size and velocity, the overall predictive performance of the model appeared to be sufficient for assessing and comparing application techniques efficiency, quantifying pesticide loss and bystanders or resident exposure and evaluating the efficiency of mitigation measures.

Methods comparison for detecting trends in herbicide monitoring time-series in streams

An inadvertent consequence of pesticide use is aquatic pesticide pollution, which has prompted the implementation of mitigation measures in many countries. Water quality monitoring programs are an important tool to evaluate the efficacy of these mitigation measures. However, large interannual variability of pesticide losses makes it challenging to detect significant improvements in water quality and to attribute these improvements to the application of specific mitigation measures. Thus, there is a gap in the literature that informs researchers and authorities regarding the number of years of aquatic pesticide monitoring or the effect size (e.g., loss reduction) that is required to detect significant trends in water quality. Our research addresses this issue by combining two exceptional empirical data sets with modelling to explore the relationships between the achieved pesticide reduction levels due to mitigation measures and the length of the observation period for establishing statistically significant trends. Our study includes both a large (Rhine at Basel, ∼36,300 km2) and small catchment (Eschibach, 1.2 km2), which represent spatial scales at either end of the spectrum that would be realistic for monitoring programs designed to assess water quality. Our results highlight several requirements in a monitoring program to allow for trend detection. Firstly, sufficient baseline monitoring is required before implementing mitigation measures. Secondly, the availability of pesticide use data helps account for the interannual variability and temporal trends, but such data are usually lacking. Finally, the timing and magnitude of hydrological events relative to pesticide application can obscure the observable effects of mitigation measures (especially in small catchments). Our results indicate that a strong reduction (i.e., 70–90 %) is needed to detect a change within 10 years of monitoring data. The trade-off in applying a more sensitive method for change detection is that it may be more prone to false-positives. Our results suggest that it is important to consider the trade-off between the sensitivity of trend detection and the risk of false positives when selecting an appropriate method and that applying more than one method can provide more confidence in trend detection.