Joe D. Luck

Reducing Pesticide Over-Application with Map-Based Automatic Boom Section Control on Agricultural Sprayers

The use of precision agriculture technologies such as automatic guidance and map-based automatic boom section control on agricultural sprayers has increased substantially over the past few years. The purpose of these systems is to decrease pesticide application inaccuracy by reducing pass-to-pass overlaps or by turning boom sections off when the boom passes over previously covered areas or beyond field boundaries. The objectives of this study were to compare areas treated by a sprayer before and after the addition of an automatic boom section control system and determine if there was a relationship between field shape factors, specifically perimeter-to-area (P/A) ratio, and pesticide over-application. Coverage files were downloaded from a self-propelled agricultural sprayer with a 24.8 m boom divided into five manually controlled sections. Prior to the subsequent cropping season, automatic boom section control (seven sections) was installed on the sprayer. Application inaccuracy was calculated for the 21 study fields by comparing the actual sprayed area (based on boom section control state: on/off) versus the total projected field area. A comparison between the average percent over-application from fields during season one (12.4%) and season two (6.2%) revealed a significant reduction in off-target application. This reduction represents savings to agricultural producers, potentially justifying the purchase and implementation of this technology. Further analysis indicated an increasing trend in over-application for manual and automatic boom section control as the P/A ratio increased for the study fields. Over-application increased at a greater rate with manual boom section control, which suggests that as field inclusions (grassed waterways or other obstacles) increase, automatic boom section control will provide a greater opportunity for producers to reduce these errors.

Hydrologic Properties of Pervious Concrete

Pervious concrete is concrete made by eliminating most or all of the fine aggregate (sand) in the concrete mix, which allows interconnected void spaces to be formed in the hardened product. These interconnected void spaces allow the concrete to transmit water at relatively high rates. The main objective of this project was to conduct research on the potential application of pervious concrete in agricultural settings, specifically for use in animal feed lots, manure storage pads, animal manure and bedding compost facilities, or floor systems in animal buildings. Laboratory tests were conducted on replicated samples of pervious concrete formed from two rock sources (river gravel and limestone) for coarse aggregates and different size fractions to determine hydrologic relationships. Linear relationships were found between density and porosity, density and permeability, porosity and permeability, and porosity and specific yield. The results suggest that properties such as permeability, porosity, and specific yield are not significantly affected by different aggregate types. However, density and porosity can be effective methods for predicting porosity, specific yield, and permeability. In addition, t-tests were conducted to determine the effect of aggregate types on the solid/liquid separation properties of the pervious concrete after adding composted beef cattle manure and bedding to the surface of the specimens. The amount of composted beef cattle manure and bedding retained within the specimens was significantly less (p = 0.012) when samples constructed of #8 river gravel were used rather than the other aggregates. The #8 river gravel also had significantly less reduction in permeability compared to other aggregates. Although the #8 river gravel had a different effect on the compost retained and the reduction in permeability for the specimens, all four aggregates exhibited a significant reduction in the permeability after the compost was applied.

A Computational Tool for Estimating Off-Target Application Areas in Agricultural Fields

A computational method for estimating off-target application areas based on the machine-controlled section width and the field shape was developed and implemented in software with a graphical user interface written in the MatLab environment. The program, which is called the Field Coverage Analysis Tool (FieldCAT), includes three modules: data import, data preparation, and coverage analysis. Nine field boundaries were evaluated to test the software using controlled section widths from 0.5 to 27 m and various swath orientations. The estimated off-target application area from the widest section width varied from 9% to 24% depending on the shape and size of the field boundary and was reduced to less than 1% with the smallest section width. The simulated results were also compared to actual field data from 25 different fields. The FieldCAT software tool was able to provide reliable quantitative estimates of the off-target application of inputs that would occur because of limited resolution of the machine-controlled section width and the path orientation in different field shapes.

A Case Study to Evaluate Field Shape Factors for Estimating Overlap Errors with Manual and Automatic Section Control

Understanding how field shape and size may affect overlap errors during spraying operations would provide producers with better information on how to improve field operations and cut costs. The goal of this study was to evaluate field shape factors through single-variable and multivariate regression analyses for predicting overlap from a manual section control (MSC) and two automatic section control (ASC) systems. Actual field coverage data collected from three self-propelled agricultural sprayers with boom widths of 24.8 m were used in the analysis. Results of statistical analyses indicated that significant relationships existed between over-application error and multiple field shape factors. The strongest single-variable relationship existed between field perimeter-to-area ratio (P/A) and the overlap error (% of field area) for the MSC and seven- and nine-section ASC systems, with model standard errors of 4.95%, 1.45%, and 0.81%, respectively. Multivariate regression yielded strong relationships with different combinations of field shape factors and overlap error; however, multivariate models did not result in a vast improvement over the single-variable model using P/A. Errors increased at a greater rate with MSC, which suggested that as field inclusions (e.g., grassed waterways) increase, or the field boundary becomes more complex, overlap error reduction may be reduced with ASC. As expected, nine-section ASC resulted in reduced overlap errors compared to the seven-section system as P/A increased. Comparing models for the ASC systems indicated that the reduction in overlap application may not significantly improve when adding two additional control sections for fields with low P/A values (<0.0175).

Estimating off-rate pesticide application errors resulting from agricultural sprayer turning movements

Pesticide application is an essential practice on many U.S. crop farms. Off-rate pesticide application errors may result from velocity differential across the spray boom while turning, pressure fluctuations across the spray boom, or changes in boom-to-canopy height due to undulating terrain. The sprayer path co-ordinates and the status (on or off) of each boom control section were recorded using the sprayer control console which provided map-based automatic boom section control. These data were collected for ten fields of varying shapes and sizes located in central Kentucky. In order to estimate potential errors resulting from sprayer turning movements, a method was developed to compare the differences in application areas between spray boom control sections. The area covered by the center boom control section was considered the “target rate area” and the difference in these areas and the areas covered by remaining control sections were compared to estimate application rate errors. The results of this analysis conducted with sprayer application files collected from ten fields, many containing impassable grassed waterways, indicated that a substantial portion of the fields (6.5–23.8%) could have received application in error by more than ±10% of the target rate. Off-rate application errors exceeding ±10% of the target rate for the study fields tended to increase as the average turning angles increased. The implication of this is that producers may be unintentionally applying at off-label rates in fields of varying shapes and sizes where turning movements are required.

A Case Study Concerning the Effects of Controller Response and Turning Movements on Application Rate Uniformity with a Self-Propelled Sprayer

The use of precision agriculture technologies such as automatic boom section control allows producers to reduce off-target application when applying herbicides. While automatic boom section control provides benefits, pressure differences across the spray boom resulting from boom section actuation may lead to off-rate application errors. Off-rate errors may also result from spray rate controller compensation for ground speed changes or velocity variation across the spray boom during turning movements. This project focused on characterizing application rate variation for three fields located in central Kentucky. GPS coordinates, boom control status, and nozzle pressure data (at 15 nozzle locations) were recorded as the sprayer traversed the study fields. Control section coverage areas and nozzle flow rates (calculated from the nozzle pressure with manufacturer calibration data) were used to estimate application rates. Results indicated the majority of each field received application rates at or below the target rate, as only 25% to 36% of the area in the study fields received application rates within the target rate ±10%. Spray rate controller lag time appeared to contribute to lower application rates as the sprayer accelerated and higher application rates as the sprayer decelerated as the controller attempted to compensate for changes in sprayer velocity. In addition, as boom control sections were turned off, pressure increases in the remaining sections resulted in higher application rates. Conversely, as boom sections were turned on, spray rate controller lag time may have contributed to lower application rates. Estimated application rate maps were also generated from the data to allow for a visual summary of the potential errors.

Nozzle Uniformity for Agricultural Sprayers Operating Under Field Operation when Using Automatic Section Technology

The adoption of automatic section control technology is increasing since it reduces application overlap and application in unwanted areas leading to input savings and improved environmental stewardship. Spray controllers attempt to maintain the desired target application rate when implementing auto-section control but concerns exist about whether intended nozzle flow rates are sustained at all times. Therefore, a study was conducted to evaluate nozzle flow rate and control system response in maintaining target application rates during field operation. Specific objectives were to: 1) map real-time nozzle uniformity CV (%) during field operation and 2) quantify the difference between target and actual nozzle (% off-rate) flow rate. Field experiments were conducted using common self-propelled sprayers equipped with commercially available controller systems with automatic section control and guidance capabilities. High frequency pressure sensors were mounted across the spray boom to record nozzle pressure with data stamped with GPS locations. Nozzle pressure were converted to nozzle flow rate using manufacturers calibration curves and nozzle CV, off-rate and flow rate settling times were calculated. Results indicated that target application rate changed frequently with ASC engagement and ground speed changes on irregular field boundaries with no-spray zones. The nozzle off-rate beyond ±10% occurred for approximately 60% and nozzle uniformity CVs for 25% of the time when operating in irregular shaped fields using auto-nozzle control sprayer. Static experiments during ASC engagement and sprayer acceleration and deceleration demonstrated that nozzle off-rate can vary from -27.6% to 37.2%, thus complimenting the field results. Auto-boom and auto-nozzle control sprayers results indicated that ASC engagement plus sprayer acceleration will result in under-application whereas ASC engagement and deceleration will over-application. Nozzle flow stabilization time up to 20.0 s during ASC engagement and/or speed change was irrationally high and needs to be investigated further. Overall, irregular fields can amplify application errors though extent and magnitude may vary with selection of type of section control strategy selected (boom or nozzle control), control algorithms, and controller response.

Multi-Robot System Control Architecture (MRSCA) for Agricultural Production

Coordinating multiple autonomous robots for achieving an assigned collective task presents a complex engineering challenge. In this paper multi robot system control architecture (MRSCA) for the coordination of multiple agricultural robots is developed. The two important aspects of MRSCA; coordination strategy and inter-robot communication were discussed with typical agricultural tasks as examples. Classification of MRS into homogeneous and heterogeneous robots was done to identify appropriate form of cooperative behavior and inter-robot communication. The framework developed, proposes that inter-robot communication is not always required for a MRS. Three types of cooperative behaviors; No-cooperation, modest cooperation and absolute cooperation for a MRS were devised for accomplishing a variety of coordinated operations in agricultural production.

Pneumatic Control of a Variable Orifice Nozzle

A variable-orifice nozzle with droplet optimization was recently developed and introduced for use on agricultural sprayers. The VariTarget (VT) nozzle reacts to changes in the system flow rate via a metering assembly that is controlled by a diaphragm and spring. As the liquid pressure changes, the VT metering assembly attempts to control the flow rate and spray pattern exiting the nozzle. The goal of this study was to replace the spring controlled “reactive” system with a pneumatically controlled metering assembly. The proposed system would allow for the metering assembly to adjust the flow rate and spray pattern exiting the nozzle by increasing or decreasing air pressure on the diaphragm. Controlled with an electronic regulating valve, the diaphragm air pressure was tested to determine if desired flow rate variation could be achieved. Initial results indicated that increasing air pressure on the diaphragm results in a decreased flow rate through the nozzle as the input carrier pressure remained constant. The VT nozzle discharge rates for the four set carrier pressures (10, 20, 30, and 40 psi) ranged from as low as 0.2 gpm (maximum air pressure at 10 psi carrier pressure) up to 1.8 gpm (minimum air pressure at 40 psi carrier pressure). Based on these data the proposed pneumatic control system has the potential to provide a new method for variable-rate pesticide application where nozzle flow rates and spray patterns can be controlled pneumatically using sprayer system operating values and electronic regulating valves.

Sensor Ranging Technique for Determining Corn Plant Population

Mapping of corn plant population can provide useful information for making field management decisions. This research focused on using low cost infra-red sensors to count plants. The voltage output data from the sensors were processed using an algorithm developed to extract plant populations. Preliminary investigations were conducted using sensors mounted on a stationary track for laboratory testing and on a row crop tractor for field testing. Repeated measurements were taken on a manually counted corn row. Visual inspection of the data from the field test indicated the potential to identify corn stalks based on approximate physical widths of the stalks. Corn plant populations tended to be overestimated for all eight field trials, with errors ranging from +0.7% to +4.4%. Overestimation was most likely due to leaves or other objects detected by the sensors during the field trials wrongly identified as corn stalks.