Recipient Organization
APPLICATION INSIGHT, LLC
2519 WILSON AVE
LANSING,MI 489062737
Performing Department
(N/A)
Non Technical Summary
The problem: Most spray drift detection occurs as damage complaints long after a preventable event has occurred. Pesticide applicators, a critical link in the production of America's food, are tasked with cheap and efficient application of pesticides to protect our food and fiber. At the same time, they are tasked with stewarding our air, water, and land by making precise applications in an imprecise world filled with variables over which they have little control. It is a heavy burden and the tools to efficiently prove a responsible application free of drift damage don't exist. This leads to mistrust, expense, and litigation. Farms struggle to employ spray applicators, at least in part due to this heavy burden and the relatively low reward versus risk. Applicators need to be able to prove they did a good job and kept their spray where it belongs.Over 2.5 million acres of crops were reported to have been damaged by spray drift in 2017 (Parker 2017); many more acres, including crops, wildlands, and water courses were likely impacted and not reported. "Data on crop losses due to pesticides are difficult to obtain. Many losses are never reported to the state and federal agencies because the parties settle privately." (Pimentel et al., 1993). (Pimentel 2005) revised earlier estimates and put a value on total economic losses due to pesticide over-application on crops, including spray drift, as just under $1.4 billion dollars annually .No doubt Pimental's estimation would be low in today's dollars. In addition, with the market introduction three seasons ago of the Dicamba herbicide-resistant crop trait and the subsequent broadscale use of that herbicide, drift complaints have accelerated to the point they are a main-stream media topic. Dicamba is active on some plants in as low as parts per billion concentrations in the air (Kruger, Pers. com.) and lethal to others in parts per million. (Kittay, 2017).We often "see" drift in abstract, anthropocentric terms, i.e "I couldn't see it, so it must not have happened." However, it is impossible to make a spray without at least some small quantity of drifting particles. Good, responsible applications with spray drift below levels that would cause an effect are achievable with careful attention to weather, application speed, droplet size, and spray release height. The ability to detect and quantify spray drift operationally as it occurs, and before the drift spreads in sufficient quantity, will be a strong mitigation of risk for all involved. With present drift detection methodologies, real time detection is simply not possible, thorough it is desired by stakeholders. This is an unfilled and costly technology gap.
Animal Health Component
50%
Research Effort Categories
Basic
(N/A)
Applied
50%
Developmental
50%
Goals / Objectives
To measure the change in radar reflectivity of spray laden air versus non-spray laden air. Reflectivity measurements, combined with measurements of temperature, relative humidity, air speed and direction, account for the psychrometric effects of evaporation on the spray's volatile component and allow calculation of air volume. This information will allow us to resolve the quantity of spray drift as it passes a plane at the downwind edge of a field.Our key innovation is the concept that the total change in reflected intensity will correlate to the change in aqueous content in the air. In many radar applications, these measurements would mostly be interpreted as noise and be filtered out. While spray drift clouds are extremely dispersed compared to atmospheric aqueous clouds, which have been able to be assessed for water content for nearly 70 years, we expect that as the quantity of spray drift reaches levels that would cause concern, we will be able to detect it. Atlas reported detection to 0.1 ml/meter3 (100 parts per billion (ppb)). Bertoldo reported similar detection sensitivities with rain drops. Typical spray drift would be in the order of magnitude of 0.2 ml/m3. Dicamba drift damage can occur down to several ppb of active ingredient, but it is always sprayed at less than 1.25% concentration (OSU extension 2016) so carrier liquid would be present to facilitate detection. Therefore, radar is expected to be appropriate technology to detect relevant levels of drift in most situations.There are several means to use radar to detect the spray-laden air. 77 gigahertz is a well established frequency for which aqueous water particles exhibit strong reflectivity(Gourova et. al 2017). Bertoldo, et.al. 2018, describe the use of 77 GHz radar as a near-field rain gauge. We will also evaluate 24 GHz (K-Band) radar systems due to high electromagnetic absorption from water (H2O) (Bertie & Lan 1996).The high attenuation of 24GHz is generally unsuitable for weather applications, but can benefit the detection of drift in several ways. First, the phenomenon of radio absorption from water will limit the distance of transmission, keeping the operational distance localized to the drift measurement region. Second, the limited transmission range should reduce the chances of interference from other devices operating on the same frequencies. Third, the radio absorption of water may be observed as reflected signal power loss when observing a known target, thus providing the necessary information to detect the presence of drifting material (Chen 1975). This means that there could be two methods to validate radar sensors when measuring water droplets and vapor, one by direct reflected signal and one by reflected signal degradation to a known, highly reflective target compared to conditions prior to the presence of water. It may be possible to combine the use of 2 or more of these phenomena to create a more robust output, though that would not occur until Phase II.We propose to leverage smaller footprint radars to identify water particles and weather detection algorithms to design a system able to detect field scale drift. (Acconeer Corp, Infineon Technologies, Lufft Corp, others). Devices proposed for testing are already used in industry (Pisa et. al 2016) and their licensing requirements are mostly public ISM bands (USFCC, 2020).
Project Methods
The overarching objectives of Phase I are to validate that we can find and quantify dispersed clouds of spray drift with low energy radar devices in a laboratory environment and gain insight as to the variability inherent to real-world use. Spray drift for the purposes of this series of experiments is defined as suspended aqueous particles in the 12 to 150 micron diameter range and of varying particle and mass ratio densities in relation to the air. While smaller droplets may exist in spray drift clouds, their contribution to spray drift as a pollution problem is negligible. This will be done through a series of experiments designed to answer the following key questions related to the technical and commercial feasibility:Does the equipment detect water droplets consistent with spray drift? What mechanism(s) work for the detection given the hardware parameters?Upon successful detection of water, do these radar system options allow for the quantification of the drift itself (density of the cloud, size of the cloud, etc.)? What are the limits of each radar system measurement capabilities?What degree of variability exists in field conditions from environmental factors? Does the measured variability prevent the ability to distinguish and quantify a passing spray cloud?Technical Objective 1: Initial validation of the core detection process.Acceptance Criterion: For each candidate technology, there are three tests to determine detection of simulated spray drift simply at a presence or absence level. As detailed below, they are direct reflection, single-point signal degradation, and multi-point signal degradation. The combination of a candidate technology and test method will define a "use case". For each baseline, experiment, and post baseline, 1000 samples will be collected. 80% of the experiment samples must show differences versus the averaged baseline measurements to be considered a success. Use cases will be eliminated for future consideration if no difference is detected. Successful use cases will advance to Objective 2.Technical Objective 2: Quantification of the radar system sensitivity and validation of the ability to quantify the detected droplet cloud.Acceptance Criterion: Using the same protocol as Objective 1, each remaining use case will be evaluated in a broader and more precise range of variables to quantify the sensitivity of the device. Success for a given use case will be defined at a basic level as the ability to generate a trend on one or more variables that is useful for defining a spray drift presence threshold. Higher level success will be defined by trends that are of sufficient quality to allow the creation of a quantitative model or define geometric boundaries.