An Analytic Perspective In Precision Agriculture

An Analytic Perspective In Precision Agriculture

There is a fascinating depiction of the human body from the perspective of how the brain senses touch. The body is shown as large hands, lips, and tongue, and a relatively small torso, legs, and feet. This exaggeration is due to the fact that the density of nerve endings is greater in hands, lips, and tongue compared to other body organs. This concentration of nerve endings is not surprising given that humans are predominantly tactile in that we touch everything and use our mouth for chewing food and gripping objects.


The exaggeration of parts to emphasize some attribute of a system, such as touch in the human body, can be thought of as an “analytic perspective.” This special kind of perspective brings to the forefront parts of a system that are associated with an attribute that has been singled out.

Who’s Using Water?

The United States Geological Survey (USGS) in a report on the “Estimated Use of Water in the United States in 2010” provides category statistics of national water withdrawal from all sources and types. Water usage categories include 45% for thermoelectric power, 33% for irrigation, 12% for public supply, 4% for industrial, 3% for aquaculture, 1% for mining, 1% for livestock, and 1% for domestic. From an analytic perspective, thermoelectric power, irrigation, and public supply representing 90% of total water usage would disproportionately stand out compared to the other categories. Any decisions related to water efficiency would target these three categories due to their relatively large water withdrawals.

The same USGS report provides agricultural irrigation water usage at the state scale. Most water withdrawal for irrigation is in the climatically drier, 17 Western states of the U.S. The five states of California, Idaho, Colorado, Nebraska, and Texas account for more than half of the irrigation water usage in the Western region. Only Arkansas in the remainder of the nation had a water withdrawal comparable to the five high usage Western states. In a map of irrigation usage, the five Western and one Eastern state would disproportionately stand out across the country. Future decisions about water needs would focus on these six states, especially where there are dwindling sources and the high risk for climate change.


The second attribute that will be considered for the analytic perspective is energy. It will be examined at the farm scale. The Economic Research Service (ERS) of the USDA published in 2013 an Economic Information Bulletin (No. 112) entitled “Agriculture’s Supply and Demand for Energy and Energy Products.” In this bulletin, changes in both direct and indirect energy usage were tracked over an 11-year period (2001-11). Direct energy refers to the use of fuels and electricity to run farm operations, while indirect energy refers to the off-farm energy used to manufacture equipment or an agricultural input, such as fertilizer.

In the last year (2011) of the tracked period, the USDA-ERS reported that direct energy accounted for 63% of total energy usage on a farm compared to 37% for indirect energy. Within direct energy, fuel to run machinery for field operations, dry crops, livestock use, and transport goods was by far the largest contributor, followed by electricity, and other minor sources. Within indirect energy, fertilizers accounted for slightly more than half of the total, with pesticides being the next major contributor followed by other minor sources. In an analytic perspective, fuel would be disproportionately represented in direct energy and fertilizers would stand out for indirect energy. Clearly, decisions about usage would focus on fuels in the case of direct energy and fertilizers in the case of indirect energy.

The third attribute chosen to illustrate the analytic perspective is currency. Currency is divided between costs to produce a crop and returns for selling it. It is commonly reported in units of dollars per acre. The USDA-ERS provides historical and current estimates of costs and returns for major commodities in the U.S.

Costs for corn production were organized as operating expenses or allocated overhead. Operating expenses consisted of seed, fertilizer, chemicals, custom operations, fuel and electricity, repairs, purchased water (for irrigation), and interest on operating capital. Allocated overhead consisted of hired labor, opportunity cost of unpaid labor, capital recovery of machinery and equipment, opportunity cost of land (rental rate), taxes and insurance, and general farm overhead.

In 2015, costs for operating expenses and allocated overhead were about equal. However, under operating expenses, fertilizers accounted for 41% and seed for 30% of the total cost. Similarly, two entries dominated the allocated overhead cost. Opportunity cost of land accounted for 52% and capital recovery of machinery and equipment for 30% of the total cost. In an analytic perspective, seed and fertilizers would dominate a picture of operating expenses, while cost of land and capital recovery of machinery and equipment would dominate a picture of allocated overhead. A decision maker interested in reducing costs would focus on seed and fertilizers, machinery and equipment, and land rentals.

The Need For Information

The fourth and final attribute to illustrate an analytic perspective in crop production is information. Of course, this attribute is at the heart of precision agriculture. Information can come from experience, text, observations, physical samples, imagery, onsite and remote measurements, software, and derivative products from data. It can be categorized by source. For example, experience can be passed by a person through oral history or recorded as text in handwritten notebooks. Formal research can be communicated as text in journals and in extension publications. Observations can be manually collected in the field. A soil sample is a well-known example of a physical sample. Imagery can be captured as photographs with an in situ camera or derived from a multispectral instrument carried on an overhead drone. Onsite measurements can be made with sensors buried in the ground, located on machinery, or sheltered in a nearby station. Remote measurements can be taken with satellite or aerial-borne sensors. Software can aid in the organization and analysis of data and creation of derivative products, such as a work order for a field operation.

It is difficult to assess which form and source of information stands out from an analytic perspective because they change over time, especially during the past decade. Moreover, with the Internet extending to smartphones and portable computers, information in the form of text, data, products, and images is available to anyone, anywhere, and anytime. While technology is making it faster, cheaper, and easier to get information, there are a few forms and sources that continue to play major roles in crop production decisions. The first is publications based on experience and formal studies. Good decisions are based on knowledge, which is quickly accessible through publications. A close second is field observations. Observations put knowledge to work and are the basis for timely decisions. Observations have become increasingly important when they are collected using applications (apps) for mobile devices. Such applications can combine recorded observations with other forms of information. The third form, accessible through the Internet and increasingly embedded in machinery, is software. Software is gradually becoming the most important source of information in precision agriculture programs, especially those supporting production decisions. In summary, publications, field observations, and software disproportionately stand out from other forms and sources of information and are receiving the most attention when making a decision.

Leave a Reply