6.2 Kentucky Precision Agriculture Education Consortium
Investigators:
Murray State University
Tony
Brannon, School of Agriculture, Tony.Brannon@murraystate.edu
Dave
Ferguson, School of Agriculture, David.Ferguson@murraystate.edu
Jay
Morgan, School of Agriculture, Jay.Morgan@murraystate.edu
Cassidy Wilson, School of Agriculture, Cassidy.Wilson@murraystate.edu
Becky
Gilfillin, Department of Agriculture, Becky.Gilfillen@wku.edu
Byron
Sleugh, Department
of Agriculture, byron.leugh@wku.edu
Todd
Willian, Department of Agriculture, todd.willian@wku.edu
University of Kentucky
Scott A.
Shearer, Biosystems and Agricultural Engineering, shearer@bae.uky.edu
Thomas
G. Mueller, Agronomy, mueller@pop.uky.edu
Carl
R. Dillon, Agricultural Economics, crdillon@ca.uky.edu
Introduction
Favorable
economic conditions during the mid to late 90s and the lower cost DGPS equipment
allowed many producers to initiate site-specific management of crop production.
Perhaps most significant was the evolution of the yield-monitor, and the
attendant yield maps that illustrated the variability that exists across the
soil landscape. As we continue to educate students at colleges and
universities throughout Kentucky, it is becoming increasingly important that we
provide instruction in the area of precision agriculture. The specific target is students that will be entering
the workforce with companies or organizations that will either directly use this
technology or rely on this technology for a portion their business.
To this end we, a team of multidisciplinary and multi-institutional
educators and researchers, propose to form a consortium for the development and
delivery of educational units oriented towards answering questions posed by
precision agriculture practitioners, and to illustrate new opportunities for
adopting and utilizing appropriate precision agriculture management practices
for Kentucky agriculture.
Objective
The
overall objective of the work proposed within is to develop a precision
agricultural education consortium in Kentucky consisting of the Murray State
University, Western Kentucky University and the University of Kentucky that will
develop and share web-based educational exercises for use in educating students
on topics relating to the adoption and use of precision agricultural practices
in Kentucky.
Background
College
courses that focus on helping the undergraduate student to develop an
understanding and appreciation for site-specific crop management are just now
beginning to emerge. Shearer and
Barnhisel (1997) offered one of the first college courses in precision
agriculture. Similar efforts were underway at other four-year institutions
in the U.S. (Ess and Morgan, 1997) and at community colleges (Brase, 1997).
These courses, as well as contemporary primers (Morgan and Ess, 1997),
focus on explaining the technology to novice and would-be users.
Data to support the profitability of this technology are just beginning
to emerge. Today, we know more
about the potential returns to these management practices, and most
practitioners now recognize these returns depend heavily on the nature of the
variability that exists across the soil landscape, as well as the approach they
choose to manage this variability. Further,
the profitability of these practices vary from state to state, farm to farm, and
even field to field.
Holt and Sonka (1995) provide a framework
for transferring agricultural technology in the 21st century.
They identified a four-tier approach to research and development
(R&D). The four-tiers are basic
research, developmental research, adaptive research, and technology transfer.
With this approach they advocate an integrated approach to R&D of
which technology transfer is a key focus. They
contend that full integration of technology transfer within the R&D
structure saves time and helps R&D personnel recognize potential problems
sooner. Tim (1999) provides a model
for integrated technology in precision agriculture via the Internet. The model environment is composed of instructional materials,
study guides, activities, virtual field trips, chat pages, and links to other
sources of information.
Shearer et al. (2000) proposed to develop a
set of 15 educational modules for the Internet.
This work is now underway and the first course offering utilizing these
educational modules will occur during the Spring Semester of 2001 at the
University of Kentucky in Lexington. This
work was funded by a special grant from the USDA, and is a follow-up to Shearer
and Barnhisel (1997).
Procedures
In Kentucky we propose to create a precision
agriculture education consortium between Murray State University, Western
Kentucky University and the University of Kentucky.
The primary focus will be on establishment of a web site with educational
modules that can easily be assembled into a single college-level course on
precision agriculture, or the stand-alone modules may be selected independently
for incorporation into existing courses in agricultural sciences and
technologies. This series of
educational modules with supporting background and hands-on activities will be
developed cooperatively to foster the understanding and implementation of
precision agriculture practices for Kentucky Agriculture.
This will be a three-year effort with educational modules being packaged
for delivery utilizing a variety of data sources.
The initial basis of the work as proposed
under the consortium concept will rely on the work of Shearer et al. (2000), a
resource that includes 15 educational modules.
Specifically, the educational modules for inclusion in the consortium
will be the following:
1)
Introduction
to Precision Agriculture
- This module will introduce precision agriculture practices and provide a broad
overview of the technologies that have come together to make this management
concept possible.
2)
Coordinate
Conversion and Datums
- Students will develop a background in coordinate conversion that enables them
to manipulate GIS coverages, thereby allowing them to resolve registration
problems when using multiple layers of data from numerous sources.
3)
Boundary
Mapping and Area Determination
- Points, arcs, and polygons; the basic building blocks of GIS packages will be
discussed. This exercise will guide
practitioners through the process of calculating areas from projected
coordinates.
4)
Yield
Map Generation
- This educational module will instruct students in yield data filtering
techniques that enable them to eliminate spurious data, and then to generate
maps using a standard convention that allows for visual interpretation.
5)
Soil
Sampling -
This module is a review of possible alternatives to the more traditional grid
soil sampling approaches. Yield
maps will be used in conjunction with other sources of data to compare and
contrast "smart" sampling approaches with grid sampling.
6)
Interpolation
Techniques for Map Generation
- This exercise will detail the development of kriging, inverse distance,
minimum-curvature, nearest neighbor, triangulation, and polynomial regression
interpolation techniques. Variations
in interpolated surfaces in relation to the methods used to generate these
surfaces, and the accuracy of interpolation techniques for predicting parameter
values at unknown locations are illustrated.
7)
Land-Use
Determination from Historical Yield Data - Historical yield data will be analyzed to determine the best course
of action for a producer to pursue given the current value of grain and
production costs. Yield stability
from year to year and crop to crop will be used as a basis for making land-use
decisions.
8)
Profit
Map Generation
- This unit will focus specification of fixed and variable productions costs,
gross receipts of marketed grains, and the spatial distribution of profits.
9)
Variable-Rate
Fertilizer Recommendations - Soil fertility data will be interpolated to produce surfaces of the
respective attributes. Cooperative
Extension Service, University of Kentucky (1999) soil fertility recommendations
will then be utilized to generate application surfaces.
10) Variable-Rate
Fertilizer Application - Fertilizer application errors will be
modeled for spinner and air-boom applicators, and in turn used to predict the
actual application surfaces. Model
parameters will then be adjusted so that practitioners gain an appreciation for
how "look-ahead" rate changes, application overlap, and control
systems response affects application accuracy.
11) Economics
of Variable-Rate Fertilizer Application
- Soil parameter interpolation errors are combined with application errors to
determine the overall effect of sampling and management grid resolution on net
returns. Students will be guided
through a strategy for optimizing marginal returns by adjusting the various
management parameters.
12) Remote
Sensing - This exercise will focus on importing satellite images, registering
these with digital rectified orthoquads, field boundaries, and yield maps.
Various vegetative indices will be compared to yield monitor data to
assess the suitability of these parameters for predicting yield.
13) Variable-Rate
Seeding - Response functions will be applied to topsoil
depth maps and historical yields to determine if variable-rate seeding of corn
is warranted. Marginal return maps
will be generated to visualize the spatial variation in increased profits as
compared with fixed-rate seeding.
14) Conducting
On-Farm Investigations - This module will concentrate on conceiving
and carrying out field investigations that allow producers to draw meaningful
conclusions.
15) Variable-Rate
Nitrogen Application - Data from actual field investigations will
be presented to students, and they will be guided in the analysis of this data
using linear regression to establish a response function.
16) Soil
Conductivity Correlation with Landscape Features
- Electrical conductivity data will be presented along with soil landscape
features for correlation analysis.
These
educational modules will be developed and implemented using platforms that
include Microsoft's Excel spreadsheet, ESRI's ArcView GIS, and Golden Software's
SURFER for Windows. The intent is
to utilize analysis tools that are commonly available within the university
community. Where appropriate Avenue
scripts for ArcView will be developed to streamline data manipulation and
analysis.
All
of the educational modules will be packaged for dissemination and classroom use
by the consortium via the Internet. Each
participating institution will have the opportunity to mirror the sites at their
home institution so that they might tailor the package to the academic needs of
their students and to fit within the framework of their course offerings.
Consortium
interaction will be accomplished by all institutions sharing in the continual
development and refinement of the course modules as identified within.
Specifically, Murray State University will have responsibility for
developing the introductory educational module.
This module will be packaged for use in the college classroom, as well as
for use at the high school level and by other interested parties outside of the
university. Faculty from Western
Kentucky University and from the University of Kentucky will work jointly on
developing modules that focus on data collection, variable-rate application and
economics (e.g., Modules 4, 5, 7, 8, 9, 10, 11, 13, 14 and 15).
The
broad and diverse backgrounds of the faculty involved will necessitate holding
faculty development workshops periodically throughout the duration of the
project. Each institution will host
a single two-day workshop (one per institution for the duration of the project)
where the faculty will come together to share teaching theories and tips on
delivering the instructional materials developed for the Internet.
These workshops will be held annually on a rotational basis with the
final schedule to be determined by the consortium participants.
Expected Benefits
The
anticipated benefit of this Kentucky educational consortium will be
better-informed students and clientele groups.
The primary educational goal is to focus on practices and opportunities
to increase Kentucky producer profitability through the implementation of
spatial crop production management. Similarly,
these educational efforts are intended to help students entering the workforce
to recognize the settings in which the cost of implement precision agriculture
crop production practices may outstrip potential returns.
Deliverables
The
primary deliverable from this project will be an educational consortium that
shares in the continual development and revision of web-based educational
modules to advance the knowledge base of Kentucky's college graduates interested
in the application of precision agriculture practices to agricultural
production. Two-day training
session will be scheduled on annually so that faculty members can remain current
on the web-based materials that are available through the consortium.