Spray Drift Research Articles

Adsorption of spray droplets reduced adsorption of dicamba spray droplets on leaves as droplet size increases

Abstract Off-target movement of growth regulator herbicides can cause severe injury to susceptible plants. Apart from not spraying on windy days or at excessive boom heights, making herbicide applications using nozzles that produce large droplets is the preferred method for reducing herbicide drift. Although large droplets maintain a higher velocity and are more likely to reach the leaf surface in windy conditions, their ability to remain on the leaf surface is poorly understood. Upon impact with the leaf surface, droplets may shatter, bounce, roll-off, or be retained on a leaf surface. We examined how different nozzles, pressures, and adjuvants impact spray droplet adsorption on the leaf surface of common lambsquarters and soybean. Plants were grown in a greenhouse and sprayed in a spray chamber. Three nozzles (XR, AIXR, and TTI) were evaluated at 138, 259, and 379 kPa. Dicamba (0.14 kg ae ha⁻¹) was applied alone and with methylated seed oil (MSO), a non-ionic surfactant, silicone-based adjuvant, crop oil concentrate, or a drift reduction adjuvant. A 1, 3, 6, 8-pyrene tetra sulfonic acid tetra sodium salt was added as a tracer. Dicamba spray droplet adsorption when using the XR nozzle, which produced the smallest spray droplets, was 1.75 times greater than when applied with the TTI nozzle with the largest spray droplets. Applying dicamba with MSO increased adsorption on leaf surfaces nearly four times the amount achieved without an adjuvant. The lowest application pressure (138 kPa) increased dicamba spray volume adsorbed more than 10% compared to the higher pressures 259 and 379 kPa. By understanding the impacts of these application parameters on dicamba spray droplet adsorption, applicators can select application parameters, equipment, and adjuvants that will maximize the amount of dicamba spray volume retained on the target leaf surface while minimizing dicamba spray drift.

Evaluating spray drift from Uncrewed Aerial Spray Systems: A machine learning and variance-based sensitivity analysis of environmental and spray system parameters

Uncrewed Aerial Spray Systems (UASS), commonly called drones, have become an important application technique for plant protection products in Asia and worldwide. As such, environmental variables and spray system parameters influencing spray drift deserve detailed investigations. This study presents the data analysis of 114 UASS drift trials conducted between December 2021 and December 2022 in China. Study design was based on the ISO 22866:2005 protocol for spray drift trials and considered different UASS platforms, nozzles, and release heights, and specifically continuously measured weather conditions. The relative importance of the environmental variables and spray system parameters was evaluated by a random forest (RF) feature importance analysis, a Sobol sensitivity analysis and partial dependence plots. This approach was preferred to linear ranking techniques such as ANOVA (analysis of variance) due to the non-linearity of the system. In addition, partial dependence plots are proposed to visualize the relationship between specific input parameters within the system.Drift deposition curves calculated from the 114 trials show good agreement with previous UASS trials reported in the literature. As reported in previous studies, spray drift following UASS applications is lower than for manned aerial vehicles, greater than for ground spray applications, and similar to drift observed from orchard air blast applications. In addition, 9 trials were conducted on corn fields in order to evaluate the potential effect of crop cover on spray drift. Spray drift was observed to be reduced over the cropped soil, suggesting that plant cover might possibly reduce spray drift. These findings could help supporting drift mitigation policies, stewardship advice and product labelling around the world.

Proposals for new spray drift exposure values in orchards and vineyards for residents and bystanders

In the EU, predicted exposure to spray drift for residents and bystanders from applications in orchards and vineyards is based on data from one study published in 1987, where one downwind distance (8 m) was considered. CropLife Europe conducted sixteen new GLP compliant studies in 4 EU countries, 8 in orchards, 8 in vineyards with early and late season applications, using adult and child mannequins located 5, 10 and 15 m downwind from the last row to measure dermal and inhalation exposures. The resulting “Bystander Resident Orchard Vineyard (BROV)” database comprises 288 observations and offers a more comprehensive option for exposure prediction.There were differences between adult and child, crop type, leaf cover and distance from the sprayer, supporting the derivation of mean, median, 75th and 95th percentile exposures for each subset. Exposures did not generally correlate with wind speed, wind direction, sprayer type, spray quality, spray concentration or amount applied. Dermal and inhalation exposure were lower in vineyards than in orchards and further analysis is required to understand why.

Increased outlet design of flat-fan nozzle improves octocopter unmanned aerial vehicle sprayer's efficiency

Increased interest in unmanned aerial vehicle (UAV) sprayers leads to identifying the factors affecting their efficiency. This study aimed to check and introduce a factor that has not been considered so far – the outlet design of a flat-fan nozzle. In a field experiment, spray drift potential and chemical weed control efficacy (sulfosulfuron against spontaneous barley) from an octocopter UAV sprayer was evaluated as a two-factor randomized complete block design including nozzle type (standard, anti-drift, and air induction) and nozzle outlet design (single, twin, and triplet-orifice). When averaged over nozzle outlet design, 22.9, 31.0, and 39.6% in-swath spray deposition and 66.0, 73.6, and 93.5% spontaneous barley control were obtained for standard, anti-drift, and air induction nozzles, respectively. Also, a similar trend from out-swath spray coverage was observed up to 8 m. In the standard, anti-drift, and air induction nozzles, an outlet design change from single-to triplet-orifice changed in-swath spray coverage by −30.8, +16.4, and +39.4% and herbicide efficacy by −27.1, +27.7, and +19.3%, respectively. The results showed that the outlet design of flat-fan nozzles had a significant interaction effect with the nozzle type. It was suitable with the anti-drift and air induction nozzles but unsuitable with the standard nozzle.

Tank-mix adjuvants improved spray performance and biological efficacy in rice insecticide application with unmanned aerial vehicle sprayer.

The use of unmanned aerial vehicles (UAVs) for the application of plant protection products (PPPs) in paddy fields is becoming increasingly prevalent worldwide. Despite its growing usage, UAV spraying for rice pest control faces practical challenges, including limited canopy penetration, uneven deposition, and significant spray drift. This study investigated the impact of two tank-mix adjuvants, Wonderful Rosin (Adjuvant-1) and Tiandun (Adjuvant-2), at six volume concentrations, on the spray liquid's physicochemical properties, spray drift, plant deposition, and the biological efficacy of rice insecticides using a quadrotor UAV sprayer. The physicochemical characteristics of the spray liquid influenced spray performance and biological efficacy. Incorporating Adjuvant-1 and Adjuvant-2 led to a decrease in surface tension and contact angle while increasing the viscosity of the spray solution. These alterations in surface tension and viscosity contributed to an optimized droplet size distribution, reduced spray drift, enhanced deposition uniformity and penetration, and improved control efficacy against the rice planthopper in UAV applications. The highest control efficacy was observed at a concentration of 0.5%, showing an improvement of 35.12% (Adjuvant-1) and 20.23% (Adjuvant-2) over applications without tank-mix adjuvant 7 days after treatment. The judicious selection of tank-mix adjuvants for UAV PPP applications can significantly enhance spray performance and biological efficacy in controlling rice insects. This study's findings offer valuable insights for integrating tank-mix adjuvants into UAV spraying applications. © 2024 Society of Chemical Industry.

Developing agricultural pest management strategies with reduced-risks to surface water: An economic case study of California's Central Coast region

Pesticides are critical for protecting agricultural crops, but the off-site transport of these materials via spray drift and runoff poses risks to surface waters and aquatic life. California's Central Coast region is a major agricultural hub in the United States characterized by year-round production and intensive use of pesticides and other chemical inputs. As a result, the quality of many waterbodies in the region has been degraded. A recent regulatory program enacted by the Central Coast Regional Water Quality Control Board set new pesticide limits for waterways and imposed enhanced enforcement mechanisms to help ensure that water quality targets are met by specific dates. This regulatory program, however, does not mandate specific changes to pest management programs. In this study, we evaluate the economic, environmental, and pest management impacts of adopting two alternative pest management programs with reduced risks to surface water: 1) replacing currently used insecticide active ingredients (AIs) that pose the greatest risk to surface water with lower-risk alternatives and 2) converting conventional arthropod pest management programs to organic ones. We utilize pesticide use and toxicity data from California's Department of Pesticide Regulation to develop our baseline and two alternative scenarios. We focus on three crop groups (cole crops, lettuce and strawberry) due to their economic importance to the Central Coast and use of high-risk AIs. For Scenario 1, we estimate that implementing the alternative program in the years 2017–2019 would have reduced annual net returns on average by $90.26 – $190.54/ha, depending on the crop. Increased material costs accounted for the greatest share of this effect (71.9%–95.6%). In contrast, Scenario 2 would have reduced annual net returns on average by $5,628.12 – $18,708.28/ha during the study period, with yield loss accounting for the greatest share (92.8–97.9%). Both alternative programs would have reduced the associated toxic units by at least 98.1% compared to the baseline scenario. Our analysis provides important guidance for policymakers and agricultural producers looking to achieve environmental protection goals while minimizing economic impacts.

Digital twins for mitigation of orchard spray drift

Digital twins for mitigation of orchard spray drift

Sampling, quantification and mathematical modeling in agricultural spray drift: A review

An effective spray of agrochemicals is inevitable for crop production for viable agriculture. Spraying inherently suffers from drift, which has always been one of the major concerns in agriculture, affecting the intent of agrochemical spraying and posing serious environmental hazards. Complete elimination of spray drift is impractical under field conditions but can be minimized using precision spraying techniques. Agricultural spray drift has several detrimental effects, such as environmental damage, polluting water bodies, human and animal health risks, chemical exposure, and economic losses, and may also lead to conflicts between neighboring farmers. Hence, the assessment of spray drift is a salient part of the design process of plant protection equipment to achieve maximum deposition in both chemical and biological pesticide applications. The different methods used to study the drift of a sprayer include test bench, wind tunnel and phase Doppler particle analyzer (PDPA) methods. In the field-level assessment, the fluorometric tracer sampling method conforming to ISO-22866:2005 was used. Plume dispersion, particle tracking and computational fluid dynamics (CFD) are the major mathematical modeling approaches for spray drift simulation studies. Among various methodologies and techniques, an appropriate method for spray drift assessment should be adopted in accordance with factors such as crop parameters, mode of application, and environmental conditions.

Combined application of surfactants and iron-based metal–organic framework nanoparticles for targeted delivery of insecticides

With the development of smart delivery systems for pesticides, many studies revealed that nanodelivery methods have great potential for use in efficient and sustainable agriculture; however, field application of the nanopesticides is still a challenge. In this study, the application of a chlorfenapyr (CF)-loaded iron-based metal–organic framework (CF@MIL-101-SL) to maize and its control efficacy for Spodoptera frugiperda were investigated in detail. The results showed that, compared with a suspension concentrate of CF (CF-SC), a solution of CF@MIL-101-SL with the surfactant aerosol OT exhibited excellent wetting, deposition and adhesion with maize leaves. The CF@MIL-101-SL NPs exhibited bidirectional translocation in maize, which significantly enhanced the transport of CF to the target tissues. Field trials revealed that CF@MIL-101-SL maintained > 75 % control efficiency after 21 d of spraying, indicating significantly greater insecticidal activity and persistence than CF-SC. Spray application of CF@MIL-101-SL gave high initial deposition rates, long half-lives on tender and old leaves and significantly reduced pesticide drift into the environment. Based on a biosafety assessment, spraying with CF@MIL-101-SL reduced the negative effects of CF on plants during the growth period. In addition, CF@MIL-101-SL increased the survival rate of Harmonia axyridis larvae and reduced the impacts of CF on the growth and intestinal damage of Harmonia axyridis. In summary, these results highlight the advantages of metal–organic framework delivery systems for multidimensional enhancement of pesticide efficacy, persistence, and safety and provide data on field application and the environmental risks of nanodelivery systems.

A Hybrid Modeling Approach for Estimating the Exposure to Organophosphate Pesticide Drift in Sangamon County, Illinois

According to estimates from the World Health Organization (WHO), organophosphate pesticides are responsible for approximately 300,000 deaths worldwide. In the United States, documented cases of organophosphate pesticide exposure number around 8000, with a small number of fatalities occurring annually. The health risks associated with these pesticides affect those living in agricultural areas, as well as farmers and pesticide applicators. Despite the intervention of government agencies in Illinois to regulate pesticide application, studies have shown that these pesticides remain present in the soil, crops, water, and air. Urban-agricultural interface communities around Sangamon County exhibit significant levels of air pollution due to pesticide spray drift, although the lack of reliable pesticide data poses a challenge in estimating the extent of the problem. Therefore, developing novel strategies to reduce the impact of pesticides on environmental health is a critical and effective research area. Currently, new, dependable models and methods are being developed to calculate spray drift and mitigate its effects. The primary objective of this study was to investigate whether and to what extent organophosphate pesticide spray drifts into urban-agricultural interface communities in Sangamon County, Illinois. To achieve this, the current study employed an integrated approach that combined the capabilities of the HYSPLIT and AgDRIFT models to evaluate organophosphate pesticide spray drifting at both the field- and county-level scales. In the absence of precise pesticide quantity data, this novel approach allowed for field simulations within identified exposure drift zones. The preliminary findings indicate that all residential areas close to agricultural areas are at risk of pesticide drift, as buffer zones do not exceed 25 m. Furthermore, of the 34 water bodies (rivers, lakes, streams, and drains) in the 30,200-acre study region, 12 are within the high-drift zone for pesticide spray drift from corn and soybean fields. Finally, the potential for organophosphate pesticide drift was present in approximately 106 buildings, covering an area of 10,300 km2.

Spraying performance and deposition characteristics of an improved air-assisted nozzle with induction charging.

Electrostatic spraying technology can improve the efficiency of pesticide deposition on the surface of leaves and reduce the environmental pollution caused by pesticide drift, which has an important prospect in agricultural pesticide application. To improve the deposition and penetration of droplets in the crop canopy, we designed and optimized an air-assisted electrostatic nozzle and conducted the spraying performance experiment. Parameters, such as charge-to-mass ratio (CMR) and particle size, were tested and analyzed to obtain the suitable operating parameters of nozzle. The results proved that the improved air-assisted electrostatic nozzle has good atomization and chargeability. There is a good charging effect with a charging voltage of 3,000-5,000 V, the CMR increased 127.8% from 0.86 to 1.97 mC/kg as the charge voltage increases from 1,000 to 4,000 V, at an air pressure of 1.0bar and liquid flow rate of 200 ml/min. Furthermore, we designed a multi-factor orthogonal experiment, which was conducted using a four-factor, three-level design to investigate the effects of operational parameters and canopy characteristics on droplet deposition and penetration. Analysis of variance (ANOVA) and F-test were performed on the experiment results. The results showed that the factor effect on droplet penetration, in descending order, was as follows: spray distance, leaf area index, air pressure, and air pressure × spray distance. The factor effect on abaxial leaf deposition, in descending order, was as follows: air pressure, spray distance, air pressure × charge voltage, spray distance × charge voltage, and charge voltage. For optimal droplet penetration and abaxial leaf deposition, option A 3 B 1 D 2 (air pressure 1.5bar, spray distance 0.2m, charge voltage 2,500 V) is recommend. The spray nozzle atomization performance and deposition regulation were studied by experimental methods to determine the optimal values of operating parameters to provide a reference for electrostatic spray system development.

The challenge of proving causality in lawsuits for pesticide contamination

Despite the long history of research into the risks caused by the extensive use of pesticides to the environment and human health, it is still challenging to identify the causal link between the event and the damage, that is, proving that a specific product, on that occasion, caused that damage. The present study aims to analyze this difficulty in liability suits for pesticide contamination, as this evidence is essential for the lawsuit to be successful. Authors such as Bombardi (2017) and Pignati et al. (2017), among others, contributed to the writing. Jurisprudential research was carried out in the states of Mato Grosso, São Paulo, Pernambuco, and Paraná, as well as interviews with judicial experts and a public labor prosecutor. In jurisprudence, it is clear that damages to human health and crops mainly trigger the judiciary which, in approximately half of the decisions, the causal link was not established, with the main obstacles being the failure to prove the relationship between pesticides and diseases, and pesticide drift to locations other than where it was applied. During the interviews, the complexity of these products was reported, as they are only identified under particular temporal, spatial, and quantity conditions. The combination of these analyses demonstrates the need for investment in inspection and monitoring policies, as well as laboratory structures, so the judiciary can be more effective in its actions, in addition to reviewing the pesticides allowed in Brazil and their maximum tolerated quantities.

Effects of insecticide spray drift on arthropod prey resources of birds in grasslands in Minnesota

AbstractSoybean aphid (Aphis glycines) insecticides are used throughout the Upper Midwest and Great Plains regions of North America, including the farmland region of Minnesota, USA, to combat insect pests. These broad‐spectrum, foliar spray insecticides have the potential to drift beyond target fields into nearby grassland cover where birds and other insectivores forage. Arthropods serve important roles in grassland ecology and are susceptible to mortality and sublethal effects from exposure to these pesticides. Our objective was to assess effects of soybean aphid insecticides on grassland arthropods, especially those that are important in grassland bird diets. We measured the abundance, consumable biomass, and family richness of insects and spiders in grasslands adjacent to soybean fields in an agricultural landscape. Soybean fields were treated with chlorpyrifos and lambda‐cyhalothrin, which were the 2 most common foliar pesticides used to control soybean aphids in Minnesota. We compared measures at focal sites to samples collected at reference sites adjacent to corn fields not sprayed for aphids during 3 periods in mid‐to‐late summer: 1–3 days before spraying, 3–5 days post‐spraying, and 19–21 days post‐spraying. The abundance of arthropods in focal grasslands was lower 3–5 days after pesticide applications. Coleoptera family richness at focal sites was also lower than at reference sites 3–5 days after pesticide applications. These measures 19–21 days after application were similar to pre‐spraying levels, indicating that arthropod populations rebounded during this period. Measures of consumable dry biomass, bird prey abundance, bird prey biomass, family richness of Araneae, family richness of Hemiptera, and family richness of Orthoptera were not different between focal and reference sites after spraying. Our results reveal that reductions in arthropod food abundance for grassland birds are associated with pesticide applications up to 5 days after spraying. We suggest that natural resource managers factor proximity to row crop fields and susceptibility to pesticide drift into decisions about where to add grassland cover to landscapes.

"Peanut (Arachis hypogaea) Response to Fungicides and Herbicides Applied using Different Spray Nozzles"

Late leaf spot [caused by Nothopassalora personata (Berk. & M.A. Curtis) U. Braun, C. Nakash, Videira & Crous] is an economically important disease in peanut (Arachis hypogaea L.) and fungicides are used routinely to protect peanut from infection and the resulting yield loss. Herbicides are an important component of effective weed management in peanut. Concern over particle drift of pesticides exists in the farming community, especially after stewardship issues associated with synthetic auxin application in herbicide resistant crops in the United States. Spray nozzles that deliver larger droplets that are less prone to drift is a possible solution to this issue. However, fungicides may be less effective in penetrating the crop canopy and covering foliage for protection from pathogens with these nozzles compared with nozzles delivering smaller droplets. Research was conducted to compare suppression of late leaf spot disease when chlorothalonil, prothioconazole plus tebuconazole, azoxystrobin, pyraclostrobin, and chlorothalonil were applied sequentially every 14 days using hollow cone nozzles (fine droplet size), regular flat fan nozzles (medium droplet size), air induction flat fan nozzles (coarse droplet size), and turbo teejet induction nozzles (ultra-coarse droplet size). Regular flat fan and hollow cone nozzles were slightly more effective in delivering fungicides based on canopy defoliation at harvest compared with turbo teejet induction nozzles and in some cases air induction nozzles. However, suppression of pathogens by fungicides applied using all four nozzle types prevented canopy defoliation adequately to protect peanut from yield loss. In a separate experiment, peanut yield and control of common ragweed (Ambrosia artemisiifolia L.) and late leaf spot did not differ at harvest when herbicides and fungicides were applied with air induction or turbo teejet induction nozzles throughout the cropping cycle. These results indicate that farmers can apply fungicides and herbicides to peanut using nozzles that limit potential for particle drift with minimal concern over reduced pesticide efficacy and protection of yield from pests.

Toward a remote sensing method based on commercial LiDAR sensors for the measurement of spray drift and potential drift reduction

Spray drift is inevitable in chemical applications, drawing global attention because of its potential environmental pollution and the risk of exposing bystanders to pesticides. This issue has become more pronounced with a growing consensus on the need for enhanced environmental safeguards in agricultural practices. Traditionally, spray drift measurements, crucial for refining spray techniques, relied on intricate, time-consuming, and labor-intensive sampling methods utilizing passive collectors. In this study, we investigated the feasibility of using close-range remote sensing technology based on Light Detection and Ranging (LiDAR) point clouds to implement drift measurements and drift reduction classification. The results show that LiDAR-based point clouds vividly depict the spatial dispersion and movement of droplets within the vertical plane. The capability of LiDAR to accurately determine drift deposition was demonstrated, evident from the high R2 values of 0.847, 0.748 and 0.860 achieved for indoor, wind tunnel and field environments, respectively. Droplets smaller than 100 μm and with a density below 50 deposits·cm−2·s−1 posed challenges for LiDAR detection. To address these challenges, the use of multichannel LiDAR with higher wavelengths presents a potential solution, warranting further exploration. Furthermore, we found a satisfactory consistency when comparing the drift reduction classification calculated from LiDAR measurements with those obtained though passive collectors, both in indoor tests and the unmanned air-assisted sprayer (UAAS) field test. However, in environments with less dense clouds of larger droplets, a contradiction emerged between higher drift deposition and lower scanned droplet counts, potentially leading to deviations in the calculated drift potential reduction percentage (DPRP). This was exemplified in a field test using an unmanned aerial vehicle sprayer (UAVS). Our findings provide valuable insights into the monitoring and quantification of pesticide drift at close range using LiDAR technology, paving the way for more precise and efficient drift assessment methodologies.

Droplet deposition of agrochemical spraying: Comparison of results from a random‐walk model and CFD simulations

AbstractThe effectiveness of agricultural spraying processes depends considerably on the ability of the atomized droplets to reach the target site in the desired amount. In this work, two mathematical models to study the trajectories and deposition of atomized droplets are implemented and compared. On the one hand, a computational fluid dynamics (CFD) coupled with discrete phase model (DPM) is implemented to calculate the trajectories of atomized droplets and determine distances at which the droplets are deposited. The continuous phase (atmospheric air) is modelled by continuity, momentum, and energy equations. On the other hand, a Lagrangian random‐walk (LRW) model based on force and energy balances to predict the pulverization process of a nozzle is formulated and implemented in Python. Both models take into account the effects of drag, gravity, buoyancy, and evaporation on individual droplets, as well as the impact of atmospheric stability and dispersion. By tracking a large number of trajectories, meaningful estimates of dispersal statistics can be obtained. The LRW model accurately replicated the trajectories, deposition distances, and final diameters of atomized droplets for three atmospheric stability cases, compared with CFD simulation results. The results of both models agreed that 100 μm droplets were most susceptible to wind‐induced spray drift, depositing at the furthest distances from the nozzle. In addition, 50 μm droplets exhibited a significant tendency to evaporate entirely before reaching the ground. The LRW model is found to be a cost‐effective alternative for estimating spray drift compared to the computationally intensive CFD approach.

Mixed-Methods Assessment of Farmworkers’ Perceptions of Workplace Compliance with Worker Protection Standards and Implications for Risk Perceptions and Protective Behaviors

ABSTRACT Introduction The Environmental Protection Agency (EPA)’s Worker Protection Standards is the primary set of legislation aimed at protecting farmworkers from occupational pesticide exposure in the United States. Previous studies suggest that worker adoption of Pesticide Protective Behaviors (PPBs) promoted by WPS is associated with lower urinary pesticide concentrations. However, adoption of PPBs is often outside of the control of individual farmworkers and dependent on workplace factors such as employer provisioning of Personal Protective Equipment (PPE) and access to trainings/resources. Methods We conducted a mixed-method study including urinary pesticide biomonitoring, surveys, and interviews with 62 Latinx farmworkers in southwestern Idaho from April to July 2022. We integrated findings across the various data sources to identify emergent themes relating to farmworkers’ perceptions of workplace compliance with WPS and potential implications for their pesticide risk perceptions, protective behaviors, and urinary pesticide concentrations. Results Participants reported some indications of poor workplace compliance with WPS regulations, notably inconsistent access to clean handwashing stations and notification of pesticide applications. Some farmworkers, particularly pesticide applicators, viewed herbicides to be categorically safer than other classes of pesticides such as insecticides; these perceptions appeared to influence protective behaviors, such as the relatively low use of PPE while applying herbicides. These findings are underscored by the higher concentrations of biomarkers of herbicides, but not insecticides, among pesticide applicators compared with non-applicators (e.g. median 2,4-D concentrations = 1.40 µg/L among applicators and 0.69 µg/L among non-applicators). Participants further reported concerns regarding the inadequacy of pesticide safety training, pesticide drift, and the lack of communication regarding pesticide applications on and near fields where they are working. Discussion Participants’ perceptions that herbicides are categorically safer than other pesticide classes is in direct conflict with WPS training, raising concerns about discrepancies between WPS instruction and other on-the-job training, as well as the inadequate provisioning of PPE during the application of certain pesticides. Our findings also suggest that current WPS regulations may not sufficiently address farmworkers’ concerns, particularly in regard to pesticide drift.

Real-Time Droplet Detection for Agricultural Spraying Systems: A Deep Learning Approach

Nozzles are ubiquitous in agriculture: they are used to spray and apply nutrients and pesticides to crops. The properties of droplets sprayed from nozzles are vital factors that determine the effectiveness of the spray. Droplet size and other characteristics affect spray retention and drift, which indicates how much of the spray adheres to the crop and how much becomes chemical runoff that pollutes the environment. There is a critical need to measure these droplet properties to improve the performance of crop spraying systems. This paper establishes a deep learning methodology to detect droplets moving across a camera frame to measure their size. This framework is compatible with embedded systems that have limited onboard resources and can operate in real time. The method leverages a combination of techniques including resizing, normalization, pruning, detection head, unified feature map extraction via a feature pyramid network, non-maximum suppression, and optimization-based training. The approach is designed with the capability of detecting droplets of various sizes, shapes, and orientations. The experimental results demonstrate that the model designed in this study, coupled with the right combination of dataset and augmentation, achieved a 97% precision and 96.8% recall in droplet detection. The proposed methodology outperformed previous models, marking a significant advancement in droplet detection for precision agriculture applications.

Sensitivity analysis of variables affecting spray drift from pesticides for their environmental risk assessments on agricultural lands

Sensitivity analysis of variables affecting spray drift from pesticides for their environmental risk assessments on agricultural lands

Spray Drift, Operator Exposure, Crop Residue and Efficacy: Early Indications for Equivalency of Uncrewed Aerial Spray Systems with Conventional Application Techniques

Highlights Initial data shows UASS spray drift is greater than ground, less than aerial, and similar to an airblast application. Operator exposure with UASS is less than that of a backpack sprayer. No current data shows that residues on crops from UASS applications would be different than conventional applications. UASS applications generally have similar efficacy as their conventional counterparts. Abstract. Uncrewed Aerial Spray Systems (UASS) are being adopted at a rapid pace in agricultural applications of crop protection products. The data required to effectively regulate their use must be gathered to position UASS in terms of equivalency with other conventional practices. In Fall 2021, the CropLife America Drones Working Group initiated an effort to collect published information on establishing the equivalency of UASS applications with conventional application types as it relates to spray drift, operator exposure, crop residue, and efficacy. Based on the published literature, our comparison demonstrated that UASS spray drift is lower than aerial, higher than ground boom, and similar to orchard airblast applications. However, this comparison is based on limited data and needs further confirmation. Individual use cases and other application variables will need to be considered to determine if this generalization applies (e.g., adjuvant use, rotor and nozzle configuration, etc.). For operator exposure, this work supported the current consensus that applications with UASS have less potential for exposure in some respects (e.g., compared to backpack applications), but for other job steps that are unique to UASS (such as mixing and loading) more information is needed. With respect to crop residue, UASS applicators follow the label for conventional application techniques with the same directions for use (i.e., application rate, pre-harvest interval, and number of applications), but there is no evidence that pesticide residues resulting from a UASS application are any different to conventional application techniques. In terms of efficacy, applications with UASS tend to be equivalent to conventional methods; however, more information is needed, especially where good coverage is a requirement. The assessment of published literature on UASS demonstrates potential equivalency in certain key areas and supports the responsible use of this emerging technology, while more information on spray distribution within the target zone, off-target droplet movement, operator and bystander exposure, and pesticidal efficacy continues to be generated. Keywords: Drone, Efficacy, Emerging technology, Operator exposure, Pesticide, Residue, Spray drift, UASS.