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home pageProfessor and Chair
Biosystems and Agricultural Engineering
128 C.E. Barnhart Building
University of Kentucky
Lexington, KY 40546-0276Office Phone: (859) 257-3000 ext. 127
Voice Mail: (859) 257-7381 ext. 127
Mobile: (859) 509-5026
FAX: (859) 257-5671
E-mail: shearer@bae.uky.edu
Education
June 1986 - Ph.D. in Agricultural Engineering, The Ohio State University.
March 1983 - M.S. in Agricultural Engineering, The Ohio State University.
June 1981 - B.S. in Agricultural Engineering, The Ohio State University.
Current Vita (Scott A. Shearer Vita - March 2007 - PDF File)
Current Research Activities
CAN-Based Precision Seed Placement - Recent trends in agricultural field machinery exploit the use of embedded controls (microcontrollers) to enhance machine function. Controller Area Networks (CAN) were developed to facilitate communications between microcontrollers. The goal of the proposed research is to develop a CAN-based distributed control systems for seeding equipment. This control system will utilize dedicated microcontrollers for single row metering units. Dynamic adjustment of machine operating parameters such a seed meter air pressure and shaft speed will be made in response to feedback from seed drop sensors, ground speed radar and GPS position fixes. Precision seeding will improve farm profitability through increased crop yield and minimized seed costs through the elimination of skipped and doubled planted regions within a field, and by maintaining fixed seeding rates across the planter when planting in turns. The proposed control system represents a significant advance and is warranted in view of increasing input costs and the need for traceability.
Assessment of Grain Yield Monitoring Accuracy - Yield monitoring technologies have been introduced to Kentucky grain producers and are now becoming a mainstream tool to help these producers improve their management skills. The goal of yield monitoring activities should be to accurately measure yield variations within a field. It is this variation in yield and the ability to quantify it that has sparked the interest of producers. Once the extent of these variations is known, the next question asked is how will producers manage this variability to their benefit? Increasingly, these same producers rely on yield monitor data to validate management approaches. By accepting yield data as accurate, and generating maps that describe yield variations within a field, producers can identify the scope and magnitude of production problems. Commercially viable yield monitoring systems utilize impact-based sensors to estimate the mass flow of grain through the combine. The mass flow rates are tied to GPS field position, ground speed, harvest width and grain moisture content to estimate yield. Most attempts to verify the accuracy of yield monitors have focused on integration of the mass flow rate in the combine to determine the total mass of grain harvested. These values are then compared with scale weights of trucks or grain wagons leaving the field. Unfortunately, error terms are also integrated using this approach thereby masking deviations of mass flow sensor readings from actual mass flow rates. As an example one might envision two yield maps where the total mass of grain harvested from either field is the same. However, the range of variation of yield between either map is substantially different, illustrating problems that might arise from calibration and comparison techniques where mass flow errors are integrated. A set on field and laboratory investigations have been designed to evaluate the accuracy of yield monitoring technologies under typical field conditions.
Enhanced Grain Yield Sensing Technology - Yield monitoring technology was introduced in the U.S. in 1995. The most prevalent type of sensing technology today is the force impetus device. These devices sense the rate at which grain in the combine is elevated from the cleaning shoe to the grain tank. A primary factor affecting the errors associated grain yield estimates is crop material flow through the combine. We propose to develop enhanced sensing techniques to improve the accuracy quality of yield monitor data so that it more accurately reflects the actual yield in the field. This will be accomplished by adding load-sensing capabilities to the threshing cylinder/rotor of a combine. The load data will be utilized to redistribute the mass flow sensor data. Unlike other projects funded under this program the direct benefactors of this work will be yield monitor manufacturers. If adopted by manufacturers, the end users of this technology will benefit as a result of being able to produce yield maps that more accurately reflect yield variations across a field. Increased accuracy and confidence in yield monitor data will drive the development of management practices as researchers and agri-businesses develop more confidence with the technology
Post Processing Correction to Improve the Accuracy of Yield Monitor Data in Grain Crops - The continuing focus on assessing the accuracy of yield monitor data has been on mass flow at the exclusion of other factors that are as significant. While mass flow sensing technology continues to evolve, little if any attention is directed at sensing or correcting for actual harvest width. This manuscript presents a spatial data model designed to correct yield estimates obtained from existing yield monitor data. The model is implemented in a post-processing mode using a common GIS engine. Specifically, actual harvest area is determined for each GPS coordinate fix logged by the yield monitor through the generation and temporal clipping of harvest polygons. This approach assumes that relative accuracy of agricultural GPS receivers is at an acceptable level to support post-processing using this approach. Results from one sample field indicate that harvest area determination using the traditional approach of assuming an actual harvest width may be over estimating harvested area by as much as 9.0%. Perhaps more significant is the nearly 30.0% increase in yield standard deviation when post-processing to correct for actual harvested area.
Investigation of Machinery and Controls Limitations on Input Management Resolution - Site-specific management of crop production is limited by the cost of obtaining and characterizing the variability of parameters such as soil fertility. Often overlooked are the capabilities and limitations of variable-rate application equipment. Specification of the control criteria and development of crop response functions provide two of the three building blocks for successful and profitable variable-rate application. Both the variability characterization and equipment capabilities combine to place limitations on the management resolution. This portion of the project is intended to assess and quantify machinery limitations. Equipment concerns under investigation include: 1) accuracy and precision of positioning information; 2) accuracy, precision and distribution of inputs using variable-rate control; and 3) capital cost and life of the equipment.
Please visit the Kentucky Precision Agriculture page!!!
Teaching Responsibilities
BAE 103 - Energy in Biological Systems (2 Credits) An introduction to energy flow and transformations within biological systems that include the human environment; and the production and processing of plants, animals and micro-organisms. Topics to be covered include the engineering problem solving approach, basics of thermodynamics, psychrometrics, calorimetry and Gibb's energy.
BAE 417 - Introduction to Design of Agricultural Machinery (3 credits) A study of the operational characteristic and design features associated with the major categories of agricultural field machinery and an introduction to conceptualization analysis and design of machine components. Lecture, two hours; laboratory, two hours per week. Prereq: EM 313, ME 330, engineering upper division status or consent of the instructor.
BAE 515 - Fluid Power Systems (3 credits) Analysis and design of fluid power systems used in agricultural, industrial and processing equipment. Selected topics to include: positive displacement components, control devices, actuators, fluid transmission and system dynamics. Lecture, two hours; laboratory, two hours per week. Prereq: ME 330, ME 340 and engineering standing or consent of the instructor.BAE 517 - Off-Road Vehicle Design (3 Credits) A study of morphology, operational characteristics, and design considerations of off-road vehicles used in the agriculture and construction. This course provides an introduction to conceptualization, analysis and design of these vehicles. Topics to be addressed include: engine performance and design, vehicle testing, turbo chargers and intercoolers, drivetrains, chassis mechanics, electronic systems, hydraulic systems, and human factors. Lecture, two hours; laboratory, two hours per week. Prereq: BAE 417, BAE 515, and EM 313 or consent of the instructor.
BAE 599 - Topics in Agricultural Engineering: Precision Agriculture (3 credits) A course designed for students who desire to understand the acquisition and analysis of geographically referenced data for the management of crop production systems. Topics include: mapping, map projections, implementation of global positioning systems, data formats, geographic information systems, grid sampling, soil fertility and physical properties, herbicide management, yield monitoring, variable-rate application, crop modeling and economics.
BAE 750 - Mechatronics (3 credits) A study of mechatronics as applied to off-road machinery that is typically of agricultural, forestry and construction equipment applications. This course will emphasize the integration of mechanical and electrical components into a system to automatically perform one or more tasks. Topics to be address include: modeling, actuators, sensors, signal conditioning, microcontrollers, and control systems.