Santosh K. Pitla

In-field fuel use and load states of agricultural field machinery

Based on the CAN data, tractor states were divided in to distinct load states.NH3 application and field cultivation had three distinct tractor states.Planting operation was found to have two distinct tractor states.Specific power (kWtool-1 or kWrow-1) required by field operations were determined. The ability to define in-field tractor load states offers the potential to better specify and characterize fuel consumption rate for various field operations. For the same field operation, the tractor experiences diverse load demands and corresponding fuel use rates as it maneuvers through straight passes, turns, suspended operation for adjustments, repair and maintenance, and biomass or other material transfer operations. It is challenging to determine the actual fuel rate and load states of agricultural machinery using force prediction models, and hence, some form of in-field data acquisition capability is required. Controller Area Networks (CAN) available on the current model tractors provide engine performance data which can be used to determine tractor load states in field conditions. In this study, CAN message data containing fuel rate, engine speed and percent torque were logged from the tractors diagnostic port during anhydrous NH3 application, field cultivation and planting operations. Time series and frequency plots of fuel rate and percent torque were generated to evaluate tractor load states. Based on the percent torque, engine speed and rated engine power, actual load on the tractor was calculated in each tractor load state. Anhydrous NH3 application and field cultivation were characterized by three distinct tractor load states (TS-I, TS-II and TS-III) corresponding to idle states, parallel and headland passes, and turns, whereas corn planting was characterized by two load states (TS-I and TS-II): idle, and a combined state with parallel, headland passes and turns. For anhydrous NH3 application and field cultivation at ground speeds of 7.64kmh-1 and 8.68kmh-1, average tractor load per tool and fuel use rate per tool of the implement were found to be 7.21kWtool-1, 3.28Lh-1tool-1, and 1.31kWtool-1, 0.64Lh-1tool-1, respectively. For planting, average tractor load per row and fuel use rate per row were found to be 4.65kWrow-1 and 1.70Lh-1row-1 at a ground speed of 7.04kmh-1.

Validation of machine CAN bus J1939 fuel rate accuracy using Nebraska Tractor Test Laboratory fuel rate data

All error between the SAE J1939 and NTTL fuel rates less than ?5%.Higher fuel flow rates resulted in a lower error of ?1%.Lower fuel flow rates resulted in higher error (up to 5%).Lower fuel flow rates generated higher standard deviations in error. A pilot study concluded that there was a difference (up to a 6.22% error) between data collected using the machine controller area network (CAN) bus Society of Automotive Engineers (SAE) J1939 standard fuel rate and data collected from a physical measurement system utilized by the Nebraska Tractor Test Laboratory (NTTL). This indicated a need to perform further studies on the accuracy of the CAN fuel rate message.The SAE J1939 standard fuel rate message utilized by the machine CAN bus has a theoretical value, however little work has been done to verify the accuracy of this value. Reported fuel flow rate values are rarely measured directly on field equipment using a flow meter, instead these values are estimated from other operating parameters (e.g., engine speed, number of cylinders, injector timing and pulsation, etc.). The goal of this study was to compare fuel rate values collected from the CAN bus to the physically measured fuel rate value from tractor performance tests conducted at the NTTL. The fuel rate values were collected simultaneously and then synchronized to confirm accuracy of results. The parameters for comparison in this study were comprised of the performance test points as described in the Organization for Economic Co-operation and Development (OECD) Code 2, Section 4.1.1. The NTTL has a certified fuel rate measuring system with an accuracy of ?0.5%.Results from this study indicated fuel rate as recorded from the CAN bus resulted in a ?5% error of actual physically measured fuel rates. Errors for higher fuel rates within the torque curve were closer to ?1%. This produced knowledge of machine fuel rate accuracy for in-field efficiency and/or spatial fuel usage for additional analysis, whether used for research or grower cost analysis with an accurate knowledge of actual fuel consumed during operation.

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.

Integration of an extended octagonal ring transducer and soil coulterometer for identifying soil compaction.

The soil coulterometer is an “on‐the‐go” electro‐mechanical system which collects impedance force data at multiple depths using an oscillating coulter. During the initial testing (summer 2006), only vertical soil impedance force data was collected using a pressure sensor. To improve the performance of the coulterometer, an extended octagonal ring transducer was integrated into the system to collect both the horizontal and vertical impedance forces given by the soil. In the summer of 2007, data was collected using the revised sensor from a typical central Kentucky field setting in a 0.8‐ha (2‐acre) plot. Four passes were made with the coulterometer. Seventy five coulter oscillations between depths of 100 mm (4 in.) and 305 mm (12 in.) were obtained for each pass. Ten standard cone penetrometer measurements were taken for each pass between depths of 100 mm (4 in.) and 305 mm (12 in.) using a multi‐probe soil cone penetrometer. Three soil bulk density and water content measurements between depths of 100 mm (4 in.) and 305 mm (12 in.) in steps of 50 mm (2 in.) were taken for each pass using a nuclear soil moisture/density gauge. Simple linear regression analysis was used to find the relationship between coulter indices (kN/m), cone index (MPa), dry soil bulk density (Mg/m3) and water content (%).Coefficients of determination (R2) as high as 0.996 were obtained between coulter indices and dry soil bulk density measurements and 0.998 for coulter indices and water content measurements.

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.

Tractor hydraulic power data acquisition system

A portable tractor hydraulic power measurement system (DUT) was developed.DUT was tested at different hose bend angles, flow rates and operating pressures.Pressure deviations from the base line ranged between 10.56kPa and 32.2kPa.Flow rate differences (<167mLmin-1) were determined to be negligible (<0.5%).Calculated power differences (<33W) were less than 1% full scale power measured. Tractor hydraulic power is used on a wide range of agricultural implements; however, the availability of operational hydraulic data at points other than full engine throttle position is limited. Operators could utilize this hydraulic data to maximize field efficiency and minimize machinery costs when determining suitable machinery for field operations. A field usable hydraulic test apparatus capable of measuring tractor hydraulic pressure and flow rate data was developed. The goal of this study was to determine if a hydraulic flow and pressure measurement device could be installed on the rear of a tractor to provide implement hydraulic power consumption at different hydraulic hose orientations. The measurement system installed allowed hydraulic lines from the tractor hydraulic remote ports to be attached to the flowmeter and pressure sensors at multiple angles of 0°, 45°, and 90° in different configuration layouts. Tests were performed at different flows and pressures for each hose configuration. The pressures were compared across configurations to a base line reading from a hydraulic pressure and flow rate measurement apparatus used by the Nebraska Tractor Test Laboratory (NTTL). Pressure deviations from the base line were small and ranged between 10.56kPa and 32.2kPa. Flow rate differences (<167mLmin-1) were determined to be negligible (<0.5%). Calculated power differences (<33W) were less than 1% full scale power measured. This small power loss suggested that using the hydraulic measurement apparatus developed as part of this study would enable accurate measurements of tractor hydraulic power provided to implements regardless of hydraulic hose bend angles.

Precision Planting and Crop Thinning

Historically, the management of inputs to crop production, especially seed, on agricultural lands has been controlled by humans using “field-average” practices. This chapter presents an overview of technology, available today and in the near term, that is altering the accuracy and precision of seed singulation and placement during planting. Increasingly, the cost of genetically modified organisms (GMOs) and biological and chemical seed treatments demands high-level accuracy and precision in seeding operations. Alternately, when it is impractical to singulate individual seeds because of seed size or shape, producers may choose to overseed a crop and then thin the resulting stand to achieve an optimal stand. In either event several enabling technologies are available to enhance the likelihood of success. Characteristics of the precision planting systems (tractor and planter combination) of the future will change in three key areas, including (1) precision seed meters and methodologies that deliver and position seed within the furrow, (2) individual row stepper motor drives that index seed placement in accordance with distance traveled, and (3) seed metering capabilities that support seeding of multiple varieties/hybrids within one field.