Growth and Yield Losses of Roundup Ready Soybean as Influenced by Micro-rates of 2,4-D

Widespread resistance to glyphosate has made weed control very challenging. In response, new approaches to managing resistant biotypes such as the Enlist E3TM have been developed. This technology allows in-crop use of 2,4-D but there is fear associated with unintentional application of the herbicide (e.g. direct application, tank contamination, or spray drift) to sensitive crops. A study was conducted to evaluate Roundup Ready (RR) soybean growth and yield loss as influenced by 2,4-D [six micro rates of 1/5, 1/10, 1/50, 1/100, 1/500 and 1/1000 of the 1,120 g ae ha-1 label recommended dose, and a check with no herbicide applied] applied at V2, R1 and R2 growth stages. In general, RR soybean was more sensitive to 2,4-D at R1 than V2 and R2. The highest 2,4-D rate, 1/5 of the label recommended rate, caused 51% soybean injury symptom, 13 d canopy closure delay, 41.2% plant height reduction, and 68.9% yield loss at R1. Based on effective dose (ED) estimates, 37.7 g ae ha-1 2,4-D caused 5% yield loss (0.23 Mg ha-1) at R1 compared with a 2.5- and 2.0-fold higher dose at V2 and R2, respectively. With respect to number of days to canopy closure, both reproductive stages (R1 and R2) were equally less sensitive to 2,4-D than the vegetative one (V2) as the plants had already achieved maximum growth recorded. On the other hand, ED estimates for plant height have shown that both V2 and R2 were equally more sensitive to 2,4-D than R1. These results clearly indicated that RR soybean growth and yield loss were significantly influenced by the timing of exposure and amount of 2,4-D.

An Instrument for Direct Measurement of Emissions: Cooling Tower Example

Measuring emissions from stacks is challenging due to accessibility and safety concerns, and requires techniques to address a broad range of conditions and measurement challenges. One way to facilitate such measurements is to build an instrument package and then use a crane to hold the package over the emissions source. Here we describe such an instrument package that is used to characterize both wet droplet and dried aerosol emissions from cooling tower spray drift. In this application, the instrument package characterizes the velocity, size distribution and concentration of the wet droplet emissions and the mass concentration and elemental composition of the dried PM2.5 and PM10 emissions. Subsequent papers will present and analyze the wet and dried emissions from individual towers.

Drift Evaluation of a Quadrotor Unmanned Aerial Vehicle (UAV) Sprayer: Effect of Liquid Pressure and Wind Speed on Drift Potential Based on Wind Tunnel Test

Background: Unmanned Aerial Vehicles (UAVs) applied to agricultural plant protection is widely used, and the field of operation is expanding due to their high efficiency and pesticide application reduction. However, the work on pesticide drift lags behind the development of the UAV spraying device. Methods: We compared the spray drift potential at four liquid pressures of 2, 3, 4, and 5 bar ejected from the hydraulic nozzles mounted on a UAV test platform exposed to different wind speeds of 2, 4, and 6 m/s produced by a wind tunnel. The combination of the wind tunnel and the UAV test platform was used to obtain strict test conditions. The droplet size distribution under spray drift pressures was measured by a laser diffraction instrument. Results: Increasing the pressure leads to smaller droplet volume diameters and produced fine droplets of less than 100 µm. The deposition in the drift area was elevated at most of the sampling locations by setting higher pressure and faster wind speed. The deposition ratios were all higher than the flow ratios under three wind speeds after the adjustment of pressures. For most samples within a short drift distance (2–8 m), the drift with the rotor motor off was more than an order of magnitude higher than that with the rotor motor on at a pressure of 3 bar. Conclusions: In this study, the wind speed and liquid pressure all had a significant effect on the UAV spray drift, and the rotor wind significantly inhibited a large number of droplets from drifting further.

Appropriate sampling methods and statistics can tell apart fraud from pesticide drift in organic farming

Pesticide residues are much lower in organic than in conventional food. The article summarizes the available residue data from the EU and the U.S. organic market. Differences between samples from several sources suggest that organic products are declared conventional, when they have residues—but the origin of the residues is not always investigated. A large number of samples are being tested by organic certifiers, but the sampling methods often do not allow to determine if such residues stem from prohibited pesticide use by organic farmers, from mixing organic with conventional products, from short-range spray-drift from neighbour farms, from the ubiquitous presence of such substances due to long-distance drift, or from other sources of contamination. Eight case studies from different crops and countries are used to demonstrate that sampling at different distances from possible sources of short-distance drift in most cases allows differentiating deliberate pesticide application by the organic farmer from drift. Datasets from 67 banana farms in Ecuador, where aerial fungicide spraying leads to a heavy drift problem, were subjected to statistical analysis. A linear discriminant function including four variables was identified for distinguishing under these conditions application from drift, with an accuracy of 93.3%.