Precision Agriculture [PA], Satellite Farming, or Site-Specific Crop Management [SSCM] is a farming management concept based on measuring and responding to both within- and among-field variability in site properties and crop production. It generally encompasses using a suite of information technologies, such as soil and yield mapping using global positioning system [GPS], GPS tractor and harvester guidance systems, precision application equipment, and variable-rate application [VRA] of inputs such as fertilizers and pesticides in order to decrease input costs and labor requirements, support a more efficient use of production inputs, and potentially increase yields.
Precision Agriculture is a management philosophy that allows inputs to be tailored to meet production requirements across an entire field. This should result in a subsequent increase in net return to any applied input to that field. The combined end result thus should be optimization of input efficiency and lowered environmental risk that can be associated with PA application of some inputs.
In a publication entitled A General Introduction to Precision Agriculture from the Australian Grains Research and Development Corporation (GRDC), authors Taylor and Whelan provide definitions for PA and SSCM.
Precision Agriculture is [from the US House of Representatives] “an integrated information- and production-based farming system that is designed to increase long-term, site-specific and whole farm production efficiency, productivity, and profitability, while minimizing unintended impacts on wildlife and the environment”. Notice that PA is identified as a whole-farm strategy and not just for individual fields.
Site-Specific Crop Management [SSCM] is “a form of PA whereby decisions on resource application and agronomic practices are improved to better match soil and crop requirements as they vary in the field”. This definition narrows the concept to resource use in cropping systems.
To expand on the above SSCM definition, it is the use of yield maps, grid/zone sampling, and other precision tools to manage the variability of soil and crop parameters. SSCM is the application of information technologies in consort with production history to 1) optimize production efficiency, 2) optimize quality, 3) minimize environmental impact, and 4) minimize risk at the site- or zone-specific level. SSCM is dependent on variability at a given site; conversely, if spatial variability does not exist, then a uniform management system for the site is likely the cheapest and most effective management strategy. The aim of SSCM is to optimize crop performance and subsequent returns across a site/field that has inherent variability by optimizing production within each identified zone within that field.
In the GRDC publication, the authors also list the things that PA is not.
• PA is not yield mapping–rather, yield mapping is a first-step tool towards an SSCM strategy;
• PA is not to be confused with sustainable agriculture, but it can be used to make agriculture more sustainable
• PA tools such as machinery guidance, auto-steer, and remote sensing are part of SSCM, but by themselves are not PA.
An Oct. 2016 USDA-ERS report entitled Farm Profits and Adoption of Precision Agriculture authored by David Schimmelpfennig provides a summary of just how important Precision Ag use has become in US corn and soybean farming systems. The study results were obtained from national data on US field crop production between 1996 and 2013 from the Agricultural Resource Management Survey (ARMS).
The following survey findings are reported in the article.
• The report uses two key measures of farm profit–operating profit, or crop revenue minus variable production costs, and net returns, or crop revenue minus all costs that include overhead.
• Capital expenditures needed to implement PA could raise overhead costs, but should also allow producers to substitute these costs for those used for operating inputs and labor.
• GPS-based computer mapping of yield data from harvester-mounted yield monitors and soil maps can be used to determine VRA’s of applied inputs.
• Soil maps may come from public sources such as USDA’s National Agriculture Imagery Program (NAIP), which acquires publicly-available aerial imagery during the growing season, and from USDA’s National Cooperative Soil Survey. Data from these sources can be supplemented with results from onsite soil sampling and subsequent analyses.
• Guidance systems are most often used on tractors, but harvesters are also being fitted with these systems. Most of today’s tractors are guidance-system ready, but require additional investment for the necessary add-on equipment.
• The capital cost of VRT-equipped farm implements is high, and this has resulted in many smaller operations hiring service providers.
• Adoption rates for PA technologies on US corn farms and corn acreage, respectively, are:
Yield monitor 48% and 70%
Yield map 25% and 44%
Soil GPS map 19% and 31%
Guidance system 29% and 54%
VRT 19% and 28%
• Adoption rates for PA technologies on US soybean farms and soybean acreage, respectively, are:
Yield monitor 51% and 69%
Yield map 21% and 40%
Soil GPS map 16% and 28%
Guidance system 34% and 53%
VRT 26% and 34%
• The higher percentage of PA technologies being adopted on US corn and soybean acreage than on US corn and soybean farms indicates their adoption is higher on larger farms.
• PA investments include purchases of equipment, installation charges, and time and effort spent learning to use and maintain the technologies. These costs, unlike those for land and equipment, are generally not recoverable if the equipment is not used or its use is discontinued. These factors increase the risk associated with PA adoption; thus, outsourcing to a custom service provider is often considered an option.
• Adoption of PA technology leads to greater machinery and equipment expenditures, and these costs must be offset by increased production efficiency or greater yield, or both, for PA to be profitable.
• The modeled positive impact of PA technologies on farm operating profit and net returns, respectively, is 2.8% and 1.8% for GPS soil/yield mapping, 2.5% and 1.5% for guidance system, and 1.1% and 1.1% for VRT. This estimated impact from adopting these technologies does not include the perceived positive environmental impacts that will be realized.
Precision agriculture as a management philosophy will likely become the standard cropping practice for corn and soybeans in the US. However, a positive economic return on the investment in PA equipment must be consistently realized for this to happen.
A secondary benefit of resource protection may also result from increased adoption of PA. This can be accomplished with PA technologies that can: 1) site- or zone-specifically apply nutrients, pesticides, and irrigation water; 2) reduce over-application of agricultural chemicals; 3) reduce soil compaction through controlled-traffic farming; and 4) reduce equipment traffic effects on water infiltration and runoff.
A White Paper entitled Use of Precision Ag in US Cropping Systems is posted on this website, and provides a more detailed narrative about PA.
An offshoot of increasing use of PA is the accumulation of vast amounts of data that must be handled in such a way to ensure its privacy and maximum usefulness. The subject of such “Big Data” is covered in a White Paper on this website.
Composed by Larry G. Heatherly, Nov. 2016, firstname.lastname@example.org