6.0      RESEARCH METHODS - Overview

            This Phase II proposal consists of 11 sub-projects in support of the overall project objectives as listed in Section 4.0.  Specifically, the alignment of the Phase II sub-projects with the project objectives is summarized in Table 1.  Further, a majority of the sub-projects are multidisciplinary in nature with linkages between sub-projects in Phase II, and to sub-projects in Phase I.  Section 8.0 outlines a scheme to coordinate project activities for the specific express purpose of disseminating research findings directly to producers in the Commonwealth via the Internet, with backup to be provided using the traditional contacts through the county agriculture agents, meetings and field days.  The following sub-projects summaries provide an overview of work proposed for Phase II.        

Explaining Spatial Variability in Grain Yield - Historical grain yield maps are of great value to growers in Kentucky; however, producers lack the tools and knowledge base to fully utilize them.  The objectives of this study are; I) To develop an information base for use in yield map interpretation and II). To develop an economically feasible approach for producers to create management opportunity maps.  The information base will be generated from a study of the relationship between grain yield and topography, soil physical, soil chemical, soil morphological characteristics, precipitation, and pest patterns in three Kentucky agricultural fields for two and a half years.  Management opportunity maps are maps that define limitations to yield within agricultural fields.

Evaluating Nutrient Removal as a Basis for Nutrient Management - Precision nutrient management requires consideration of the unique combinations of crop and soil responses within a field.  Soil sampling protocols for nutrient management have proven expensive. The advent of yield monitoring, and with it the prospect of using yield to estimate nutrient removal, has given new life to variable rate nutrient management.  Directed sampling is emerging as a consequence of quantitative descriptions of the relationships between terrain attributes and static soil properties that affect soil nutrient supply, crop growth and nutrient demand.  Research is needed to evaluate these new approaches and to illuminate the landscape factors of interest, should either directed sampling or nutrient removal be promising approaches to variable rate fertilization of soils.  Choosing between nutrient removal and soil sampling as a paradigm for nutrient management has tremendous implications for agriculture in the next century.

Quantitative Soil-Landscape Modeling to Define Landform Management Segments - The crux of precision agriculture is in knowing and accounting for the variability of site characteristics within a field. Common methods for characterizing within-field soil variability, such as grid sampling, are data dependent and do not account for the primary causes of the soil variability—processes of soil formation. Instead of characterizing the observed patterns, a more valuable outcome is to link observed patterns to processes of soil development. We will develop soil-landscape models that can predict the spatial patterns of A-horizon thickness, soil organic carbon content, and clay content from spatial patterns of terrain attributes derived from a digital elevation model. We will also examine whether these soil-landscape relationships are similar among landscapes of similar soils within a physiographic region. This work will provide producers with a means to quickly and easily assess the nature of soil variability in their fields and divide the field into meaningful management zones.

Remote Sensing of Pasture Mass and Quality - Grasslands are the best land use for much of Kentucky and currently occupy more than half of agricultural land in the state. Sales of livestock make up more than $1.98 billion of the $3.63 billion in farm receipts received by Kentucky farmers in 1997. Pressures of input costs and trends in livestock and milk prices require livestock producers to constantly look for improvements in productivity and/or efficiency of production to remain competitive. Remote sensing and terrain attribute information available for large areas at a low cost could be valuable management tools for pasture and hay crops. In this work we will: (1) use soil:plant spatial relationships to develop more efficient forage management systems for Kentucky grasslands and (2) improve forage utilization by using remotely sensed spectral data to provide livestock producers with accurate, timely information on forage availability and quality. The information gained will be directly applicable to Kentucky grassland agriculture.

Dynamic Testing of Force-Impetus Yield Monitors Under Rough Terrain Conditions - The traditional combine yield monitor used in the United States is a force impetus system. Consequently, dynamic motion in the clean grain elevator could have a significant effect on instantaneous grain yield prediction. Field experiments will be conducted to establish the ranges of acceleration experienced by combine yield monitor sensors. Modification of the combine yield monitor test facility will be completed to accommodate dynamic simulation of undulating terrain. Yield monitor accuracy will be evaluated using dynamic terrain simulation with the experimental parameters established from field studies.  The results of these tests will identify potential yield prediction errors experienced when transversing rough terrain. The results will be published in refereed journal articles, disseminated to cooperating manufacturers for product improvement, and documented in extension publications to alert grain producers of any observed sources of error, so that yield monitoring practices can be improved.

Evaluation of Topography Attributes on Corn Yield - Topographic attributes, such as slope and aspect, are important contributors to soil formation.  Soil types are often mapped according to these parameters.  The topographic position also influences the water availability (runoff and run-on), which contributes to variations in corn yield.  Topography also influences erosion, which was especially important prior to the adoption of the no-till farming practice.  In a current study, both seeding and nitrogen rates were varied according to topographic position and/or topsoil thickness.  Corn yields were affected by varying these parameters.  Approximately $15/acre greater net return was obtained.  The proposed study is an expanded version of the previous study on a whole-field scale.  This study is needed since the strips we chose exhibited the upper range in topographic differences in the respective fields and did not represent the entire field.  In addition, the effect of micro-depressions occurring in creek or river bottom fields will also be evaluated in fields selected with and without tile drainage systems.

Variable Rate Nitrogen Using Yield Maps - This project will help determine if variable rate nitrogen could be successfully and profitably applied to upland corn producing areas of Kentucky.  It would also determine if a quick and inexpensive method could be used to determine the areas in the field where different nitrogen rates should be applied.  A history of past yield maps will be used to determine the low, medium and high producing areas in the field.  This information will be used to determine the areas of the field receiving low, medium and high rates of nitrogen.  A Trigg County farmer’s NH₃-N applicator will be modified to be variable rate ready.  Grain yield, soil NO₃-N, chlorophyll measurements and corn stalk NO₃-N will be used to help determine profits and the proper rate of N fertilizer for the 3 different yield potential areas.  Past research indicates that this method has a strong possibility of succeeding and could be profitable enough for farmers to cause a rapid adoption of the technique if the farmer has significant upland corn acreage.

Comparison Two NIR Monitors for Corn and Wheat - The grain industry is moving towards a value-enhanced marketing system where market premiums are based on specific grain quality traits.  Grain buyers are currently using near infrared (NIR) instruments to determine the fiber, moisture, oil, protein, and starch content of corn.  This study will compare grain quality values from an independent lab with two NIR instruments--a mobile experimental unit mounted on a combine and a commercial laboratory unit.  Grain samples will be collected during harvest within five different fields and analyzed by each instrument to determine the chemical components of corn and wheat.  DGPS and yield data will be collected at the time of harvest to measure the range of spatial variability and possible influence of yield.  The study will be conducted over a three-year period to determine year-to-year (temporal) variation.  Test results will be shared with all stakeholders in the grain industry through journal and trade magazine articles and extension publications.

Low Cost GPS-Based Sensors for High Speed Agricultural Vehicle Guidance - One of the major hindrances to adoption of automated guidance technology for agricultural field machinery is the cost and complexity of the sensors used to measure vehicle position.  The goal of this project is to develop a low cost sensor array that can be used for guidance of high-speed agricultural vehicles.  A Differential Global Positioning System receiver, similar to those already widely used on Precision Agriculture machinery, will form the foundation of the sensor array.  Detailed analyses of the performance of a human operator will help identify additional components of the sensor array.

Precision Farming Adoption in Kentucky: The Role of Capital Costs and Farm Size - Precision farming encompasses a broad array of technologies that have potential for improving the profitability of agricultural production, particularly field crops. These technologies vary both in complexity and in cost. The proposed project represents an effort to determine the extent to which capital acquisition costs will limit the adoption of alternative precision farming technologies for Kentucky farmers and to measure the potential output-increasing or cost-reducing benefits to Kentucky farmers. Efforts will be directed toward estimating the acquisition costs needed for adoption of a variety of precision farming technologies under alternative purchase/custom hire and lease-rental options, and to determine if these technologies will be cost effective on Kentucky farms of various sizes.

Spatial Applications for Agriculture: Educational Case Studies - This proposal details the development and delivery of 15 educational modules intended to train college students and practitioners in the acquisition of spatial data analysis skills required for assessing the profitability of precision agriculture practices.  The focus of this educational effort will be on crop production in Kentucky.  A minimum of five modules will be developed each year over the three-year duration of this project.  These modules will be packaged for delivery to undergraduate students through coursework at University of Kentucky, and for use in workshops dedicated to county agents, services providers and producers.  Exercises will be developed using Microsoft's Excel spreadsheet, ESRI's ArcView GIS package with dedicated Avenue scripts, and Golden Software's SURFER for Windows.  All educational module materials will be made available via the Internet with downloadable versions of spreadsheets, example data files, and PDF documentation to support each learning activity.  Emphasis will be placed on assessing the potential profitability of various precision agriculture management practices adopt by Kentucky producers, along with promoting an understanding of generation, manipulation and analysis of geographically referenced data.  This educational effort is intended to aid the dissemination of research findings from the University of Kentucky to end-users.