Today’s farmers now have tremendous opportunities to use new technologies to help them collect and analyze information about their farming operations, which they can use to help manage their operation more efficiently and in a more environmentally sustainable manner. Much of this technology, especially for row crop producers, falls under the broad rubric of ‘precision agriculture’, because the information they gain through its use allows them to essentially custom farm their land by the square foot rather than by the field. Specialty crop producers also use sensors to help them track soil moisture for their crops, allowing them to micro-manage the timing of when irrigation equipment is activated, which helps save on both energy and water utilization.
On the livestock side, similarly advanced technology allows dairy farmers to automate much of the process for milking their cows on a regular basis without much human intervention in what are known as robotic milking parlors, which allows them to track the daily milk output of each of their animals. Cattle producers who graze their animals in pastures or on open rangeland can use virtual fencing technology to move their animals around without having to be physically present with the herd.
Data from USDA’s Agricultural Resource Management Survey (ARMS) showed that through 2019, some form of automated guidance on farm machinery like tractors and combines was used on more than 50 percent of all U.S. corn, cotton, rice, sorghum, soybean, and winter wheat acres respectively. Other precision technologies such as yield maps, soil maps, and variable rate application technology have been adopted on only between 5 and 25 percent of total U.S. planted acreage. According to data collected by USDA under the 2022 Census of Agriculture, about 226,000 farms deployed at least one precision agriculture practice on their operations, or just under 12 percent of all 1.9 million farms recorded in that census year. The 2023 Census on Irrigation and Water Management found that about 35,000 farms used soil or plant moisture sensors, sometimes called Internet of Things (IOT) sensors, to help manage irrigation water flows, or about 15 percent of all U.S. farms using irrigation. As of 2023, a University of Wisconsin dairy researcher estimated that there are between 500 and 1,000 U.S. dairy farms who use robotic milking units, which is not very deep penetration for technology that has been available to U.S. dairy farmers since 2000.
A 2021 survey of Midwest farmers found that adopters of precision agriculture technology credited the new technology with generating at least a five percent increase in their farm’s profit from use of variable rate application of fertilizer or seed or automatic section control, while non-adopters were unaware that increased profitability was possible. Similarly, a 2020 study by Pope and Sonka at the University of Illinois reported that within a small sample of ten Midwest corn and soybean farmers projected a net benefit of $90 per acre due to adoption of an array of precision agricultural practices including soil mapping, crop monitoring through use of drones or aerial imagery, and variable rate technology.
Despite the favorable results of research on profitability impacts reported above, adoption of these technologies (and comparable technologies used by livestock and specialty crop producers) continues to lag other types of relatively new technology, such as biotech crops, which has achieved adoption rates of 90 percent or above from U.S. farmers raising corn, soybeans, and cotton, which first became available in the mid-1990’s.
It appears that the two most significant barriers to wider adoption of these technologies are the relatively high cost of the equipment and the poor availability of reliable and affordable broadband access in some rural areas. For example, a system to control and deliver seeds at a variable rate on cropland can cost several hundred thousand dollars. A robotic milking facility to serve a herd of 200 cows would require at least three robotic milking units, for a total cost of between $450,000 and $600,000. The labor savings from not having to manually milk the cows might eventually offset this cost, but it would require a lot of up-front investment to get there.
There is clear evidence that there are significant economies of scale associated with adoption of most precision agricultural or IOT-sensor based practices. A recent ERS study found that large and medium-sized farms in the U.S. are far more likely to have adopted practices like auto-steering than smaller operations are. As of 2023, 52 percent of mid-sized farms and 70 percent of larger farms were using this practice.
Data collected by the Federal Communications Commission (FCC) on access to broadband from 2023 indicate that less than 62 percent of rural households have a broadband internet connection, while the urban connectivity rate is nearly 78 percent. An examination of how FCC collects that data suggests that even that 62 percent rate is likely to be an overestimate for rural areas. Under federal law, internet providers are supposed to report to the FCC on a census block basis if at least one household in that census block has received an internet subscription from that provider. However, census blocks in rural areas are fairly large geographically, and the fact that one resident has access doesn’t mean all his or her neighbors in that area do as well. In addition, the FCC definition of broadband access does not reflect whether such access is either reliable or affordable to prospective clients.
If farmers lack any access to broadband services, it is simply not feasible for them to consider any of these precision or IOT sensor based technologies, because they won’t function as designed. If access is available but unreliable, farmers might adopt some of these technologies, but the likely benefits would be reduced until reliability is attained. There are anecdotal reports of some farmers, usually larger operations, installing their own repeater equipment to enhance broadband reliability on their operations–this sort of coping activity just reinforces the scale bias of the underlying technology as discussed above.
