Authors: Robert "Bobby" Grisso, Extension Engineer, Biological Systems Engineering; Mark Alley, Extension Agronomist & Professor, Crop & Soil Environmental Sciences; Phil McClellan, President, MapTech, Inc., Blacksburg, VA; Dan Brann, Extension Grain Specialist, Crop & Soil Environmental Sciences; and Steve Donohue, Extension Agronomist & Professor, Crop & Soil Environmental Sciences; Virginia Tech
Publication Number: 442-500, posted August 2002
Precision Farming (PF), also referred to as precision agriculture or variable rate technology, is the process used to vary management of crop production across a field. Midwestern farmers have been using PF technologies for several years and it is now becoming popular in Virginia. This publication introduces the principles and terminology used in PF. Crop producers can use this information to gain a working knowledge of PF and develop the ability to implement PF technologies in traditional crop production.
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Information
Timely and accurate information is the modern farmer's most valuable resource. This information should include data on crop characteristics, hybrid responses, soil properties, fertility requirements, weather predictions, weed and pest populations, plant growth responses, harvest yield, post harvest processing, and marketing projections.
Precisionfarmers must find, analyze, and use the available information (Figure 1) at each step in the crop system. An enormous database is available on the internet. This data is both accessible and quickly updated.
Technology
Precision farmers must assess how new technologies can be adapted to their operations. For example, the personal computer (PC) can be used to effectively organize, analyze, and manage data. Record keeping is easy on a PC and information from past years can be easily accessed. Computer software including spreadsheets, databases, geographic information systems (GIS), and other types of application software are readily available and most are easy to use.
Another technology that precision farmers use is the global positioning system (GPS). GPS allows producers and agricultural consultants to locate specific field positions within a few feet of accuracy. As a result, numerous observations and measurements can be taken at a specific position. Global information systems (GIS) can be used to create field maps based on GPS data to record and assess the impact of farm management decisions.
Data sensors used to monitor soil properties, crop stress, growth conditions, yields, or post harvest processing are either available or under development. These sensors provide the precision farmer with instant (real-time) information that can be used to adjust or control operational inputs.
Precision farming uses three general technologies or sets of tools:
Crop, soil, and positioning sensors - these include both remote and vehicle-mounted, "on-the-go" sensors that detect soil texture, soil moisture levels, crop stress, and disease and weed infestations;
Machine controls - these are used to guide field equipment and can vary the rate, mix, and location of water, seeds, nutrients, or chemical applications;
Computer-based systems - these include GIS maps and databases that use sensor information to "prescribe" specific machine controls.
Decision support (management)
Decision support combines traditional management skills with PF tools to help precision farmers make the best management choices or "prescriptions" for their crop production system (Figure 2). Unfortunately, decision support has many times been either unreliable or difficult to understand. Building databases based on the relationships between input and potential yields, refining analytical tools, and increasing agronomic knowledge at the local level are yet to be accomplished. Most agricultural researchers agree that decision support remains the least developed area of PF. Diagnostic and database development will eventually replace technologies as the real benefit of PF.
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Each of these maps contains unique data for a specific purpose (e.g. roads, soil type, contour). Most information can be acquired at little or no cost.
Obtain recent aerial photographs of your farm. Photographs taken when fields were barren and at two or three vegetative stages are especially useful. These should be available from your local office of the Farm Service Agency (FSA). Use the photographs to identify known property characteristics such as fence lines, sandy areas, poor drainage areas, livestock usage, and other features.
Use a systematic approach to storing information when collecting data. Make paper or electronic copies of your information. Store this information in different places from your usual record keeping area to prevent theft or damage from fire, water, or some other disaster.
Computers with PF and record keeping software help manage and retrieve data. GIS programs overlay geo-referenced information for further analyses. You may find working with a computer difficult at first. If so, use services that collect, handle, analyze, and interpret data for you.
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Example 1. Nutrient Management Plan.
A farmer wants to "fine tune" his nutrient management plans for optimal economic returns. He starts by evaluating the soil characteristics (the lower right corner of Figure 2) within a field. Next, the farmer classifies the field into areas or "management zones" based on common soil types or crop potentials. Within these zones, the farmer decides on the combination of operating strategies (e.g. conservation tillage with variable rate fertilizer application) needed to obtain the maximum profit from that field. He can fine-tune the nutrient management plan based on weather and market forecasts.
The fine-tuning job does not end at harvest. The farmer should gather yield data and information on the amount of residual nutrients not utilized by the crop. He should compare these results to his yield goals and economic returns to determine whether his management decision worked.
Example 2. Management Strategy to Reduce Chemical Costs.
A farmer wants to save money by applying pesticides to the correct target at the proper rate and time. The farmer selects a high accuracy applicator equipped with GPS-based controllers. Next, he obtains field scouting or remote sensing data of pest-infestation zones within a field and develops a geo-referenced map. The services of an integrated pest management (IPM) specialist may be used to determine the optimal time for pesticide application.
The farmer sprays only those areas that have both a high potential economic return and a high threshold of pest infestation. The GPS-based controls ensure that those areas receive the proper application rate. The controller also logs actual rate, time, and location data. As in Example 1, the farmer should compare his harvest to his yield goals and economic returns to determine whether his management decision worked.
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Precision Farming Tools: Yield Monitor (VCE Publication 442-502)
Precision Farming Tools: Global Positioning System - GPS (VCE Publication 442-503)
Precision Farming Tools: GIS - Mapping Geo-Referenced Data (VCE Publication 442-504)
Precision Farming Tools: VRT - Variable Rate Technology (VCE Publication 442-505)
Precision Farming Tools: Remote Sensing (VCE Publication 442-506)
Precision Farming Tools: Map-Based versus Sensor-Based (VCE Publication 442-507)
Precision Farming Tools: Soil Electrical Conductivity (VCE Publication 442-508)
Interpreting Yield Maps - I gotta a yield map, now what? (VCE Publication 442-509)
Developing a Prescription Map
Soil Nutrient Variability in Southern Piedmont Soils
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Roberson, G. 2000. Precision agriculture: a comprehensive approach. Cooperative Extension, North Carolina State University. http://www5.bae.ncsu.edu/programs/extension/agmachine/precision/index.html
Stombaugh, T.S., T.G. Mueller, S.A. Shearer, C.R. Dillon, and G.T. Henson. 2001. Guideline for Adopting Precision Agricultural Practices. Cooperative Extension Service, University of Kentucky, PA-2. http://www.bae.uky.edu/~precag/PrecisionAg/Exten_pubs/pa_2.htm
Watermeier, N. 2001. Considerations on Gathering and Interpreting Field-Based Information for Precision Agriculture Decision Making. The Ohio State University Extension. http://precisionag.osu.edu/library/decision.html
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