From Fiber to Field: The Role of Rural Broadband in Emerging Agricultural Technology- Part IV

This post continues our Smart Rural Community series on ag tech. Please visit NTCA Newsroom for previous installments.

FACTORS IN AG TECH ADOPTION

1. Farm Size

Several factors have been identified when assessing the rate and pace of ag tech adoption. Similar to factors affecting broadband adoption, generally, these can be presumed to include cost, perceived relevance/value, and age of user.¹ An analysis of farm demographics reveals positive indicators for increased ag tech adoption. As described above, U.S. farms are evolving. Although most farms are small, most production occurs on large farms.² Inasmuch as the cost of ag tech remains a barrier to adoption,³ large farms may realize more beneficial economies of scale than small farms. Overall, farm size has been identified as a prevailing factor that determines adoption.⁴

The efficiencies of ag tech, which intends to reduce input costs while increasing productivity and yields, may manifest differently on farms of various sizes. For example, a small, owner-operated dairy may deploy automated feed, milking, and manure management technology that can reduce the need to hire outside, non-family help. In contrast, a large crop farm may deploy a battery of sensors and automated equipment to drive VRT-enabled efficiencies that multiply across the many acres farmed. Overall, many factors will contribute to anticipated outcomes, and a simple comparison of adopters to non-adopters is difficult because the analysis must contemplate many variables such as size, crops, and sufficient broadband availability to support PA applications. Nevertheless, if farm size is identified as the prevelant factor that informs adoption, then it can be reasoned that overall adoption should increase as farm sizes increase. Adoption data provided by ERS bears this point, as illustrated in the graph below.⁵

Source: USDA ERS, 2016 (Schimmelpfennig, 2010 data)

Moreover, it should be noted that the need for broadband in rural areas to support ag tech is inelastic to farm size. Farms, whether large or small, are located primarily in rural regions, and large farms are not necessarily composed of contiguous acres. Rather, large farms often include operations that manage dispersed acreage across a range of many miles. This, too, increases the imperative for ubiquitous broadband deployment in rural agricultural regions. In sum, trends toward larger farms and data indicating higher ag tech adoption in larger farms demonstrate the need for rural broadband deployments to support increasing ag tech needs.

In addition to farm size, capital costs inform adoption. And, as noted above, most U.S. farms are small farms; many are owner-operator enterprises. Capital costs for small and medium farms can be mitigated by introducing ag tech with tailored applications. While rudimentary efficiencies can be gained through basic data collection and analysis, greater efficiencies are realized through more sophisticated and comprehensive data collection and analysis, e.g., more expensive solutions. However, the benefits of PA, in addition to improved efficiencies and yield, can extend to quality-of-life improvements. For example, a farmer in a self-steering tractor can avoid fatigue as the machinery operates autonomously and use that time to monitor commodity prices. These labor efficiencies can benefit many small-scale farm operators who depend on off-farm income and who would benefit from that reclaimed time.⁶

Adoption trends can also be anticipated to correspond to developments in technology and relative pricing. As noted above, perceived value drives adoption. Value can be defined, generally, as the difference between cost and return. Stated differently, users can be expected to adopt ag tech when positive returns on investment outweigh capital costs, operating expenses, and intangible costs associated with acquisition and deployment. Notably, ag tech prices are declining over time.⁷ This is consistent with technology prices, generally as (i) processing power grows exponentially in relatively quick cycles,⁸ (ii) ongoing improvements change what is considered “state of the art,” and (iii) increased demand results in higher production, leading to economies of scale that enable lower costs and pricing. A report explains, “Due to the evolution of technology, the size and shape of sensors is getting smaller and more sophisticated, while in parallel the general cost of the IoT devices is getting lower.”⁹ Decreasing prices for technology are often demonstrated in both lower constant-dollar and nominal dollar values. These overall decreasing costs would be anticipated to presage increased ag tech adoption over time. In this vein, tech adoption can be perceived as a steady incline punctuated by spikes as adoption rates increase; this may be visualized as a graph that features time on the X (horizontal) axis and adoption on the Y (vertical) axis. Innovative developments will be represented by spikes on the upward sloping X line that reflects action by early adopters, corresponding to a higher point on the Y (vertical/adoption) axis. That spike may then temper to a more moderate incline when initial excitement wanes but as the now-common technology is adopted by a broader community of users. The X line may then spike again when either (a) prices drop or (b) a new innovation that attracts early adopters is released.

2. Age and Educational Attainment

As farms change, farmers are changing, too. The average age of a U.S. farmer in 2017 was 57.5 years, 1.2 years older than the average age of a farmer in 2012.¹⁰ Although data reveals that older users adopt technology at lower rates than younger users,¹¹ broadband adoption among “older users” is increasing over time as (a) perceived relevance among users increases as more aspects of daily life go “online,” and (b) users who were in the 50-60 demographic a decade ago (and who were broadband adopters) now populate the 60-70 age group and remain broadband users.¹² Moreover, an analysis of ag tech, specifically, should also contemplate the correlative roles of education in broadband and tech adoption, specifically, increased broadband adoption that corresponds to increased educational attainment.¹³ In these regards, then, it is instructive to assess trends surrounding young farmers. According to the USDA Farm Census, 321,000 farmers are “young farmers,” i.e., 35 years or younger.¹⁴  This cadre of young farmers increasingly obtains more post-secondary education than their predecessors. In fact, it is anticipated that nearly 69% of young farmers in the near term will have a college degree.¹⁵ These data correlate with increasing educational attainment in rural areas, generally. The ERS reports in 1970, more than half (56%) of rural adults 25 years and older did not have a high school diploma. That share dropped to 15% in 2015.¹⁶ Currently, most rural adults have a high school diploma or equivalent (GED), and nearly 30% have a bachelor’s degree or higher. In addition to data demonstrating increased adoption among users with higher rates of educational attainment, some suggest that educational attainment may correlate to adoption of new technologies, generally.¹⁷ Together, the data bode well for the increasing incorporation of technology in agriculture; young farmers show greater favorability to PA than older counterparts.¹⁸

Moreover, today’s farmers will find complete programs built around the evolving needs of the ag tech industry. For example, Wisconsin Indianhead Technical College (WITC) offers a two-year associates degree program leading to a technical diploma for Agricultural Power and Equipment Technician. Similarly, the Pennsylvania Department of Agriculture coordinates farming apprenticeship programs.¹⁹ Programs like these are often only the beginning, as continuing education is necessary to keep pace with developing technology. Farm workers are transitioning to farm technicians. As described in a report published by the U.S. Department of Homeland Security,

Where in the past farmers relied on mechanical skills to keep equipment operating, precision agriculture requires them to learn how to integrate computer systems and evaluate data integrity. . . Failure to adopt new technologies puts farmers into a competitive disadvantage. Being able to evaluate which technologies will return on their investment is a critical skill for today’s farmers.²⁰

Overall, trends reflecting age and educational attainment of farmers and farm size indicate opportunities for positive ag tech adoption growth and an ongoing need for rural broadband deployments.

RETURN ON INVESTMENT

Numerous studies have attempted to quantify the value of ag tech. Each estimate may rely on different data sets and approaches, and are further differentiated by farm size, crop and region. For purposes of this paper, some illustrative examples are offered:

• Auto-guidance systems can increase usable farm acreage from 3,000 to 3,335 acres.²¹
• VRT seeding enables gains of $12.53 per acre²²
• VRT fertilization can enable gains of $36.00 to $88.00 per acre²³

In addition to the different methodologies that guides various studies, it also bears mention that data gathered from farms of different sizes will represent different economies of scale. For example, large farms are found to adopt ag tech on a greater basis than smaller farms. Therefore, a greater proportion of data may be derived from large farms that rely on different economies of scale as compared to small farms; the average returns for ag tech may be proportionally higher on large farms than small farms. At the same time, certain operational expenses for large farms using PA may be higher than those incurred by small farms.²⁴

Although crop and yield efficiencies should be expected with PA, it is not clear that labor costs necessarily decline. On the one hand, PA may support automation that reduces costs for hired labor. On the other hand however, more sophisticated equipment can require a higher-skilled work force for operation and maintenance. Service costs must be factored, as well, and a USDA report notes differences between large and small farm costs: “Custom service costs associated with the three PA technologies are substantially different between large and small farms, partly because providers’ charges per acre decline as the number of acres serviced increases.”²⁵ The report also explains:

Hired labor costs are 60 to 70% lower with any of the three PA technologies on small corn farms (140-400 cropland acres), while hired labor costs are higher on large farms that have adopted precision mapping and guidance. The additional use of hired labor on larger farms may be for information management and field operation specialists that can help implement PA technologies. Larger farms have higher expenses for other inputs that these specialists can help control using PA. Custom service expenses are higher with mapping and guidance on both large and small corn farms under all three PA technologies. However, custom operation costs are five times larger, in percentage terms, on small farms than on large farms.²⁶

PA applications may be combined in various permutations. Farmers can combine mapping, VRT and guidance systems. Both size of farm and the manner in which these technologies are combined affect costs. Overall, the rapid development of technology and emerging literature on ag tech at this time indicate that determining ag tech ROI for small farms will require individual analyses, while large farm economics may be evaluated against published literature. It can be expected that the body of research and literature on these topics will expand over time to reflect observations for a larger data set arising out of small farms. As an immediate issue, however, increasing ag tech adoption can be expected to drive demand for higher-skilled workers who demand higher wages. In this scenario, the farm sector will be forced to compete with other sectors demanding technology skills.²⁷

On a national scale, the value of broadband for ag tech has also been demonstrated in economic studies offered by the FCC. A recent report correlated increased corn and soybean yields to increased broadband connections, specifically, 3.6% increase in corn yields and 3.8% increase in soy yields where broadband connections of 25+/3+ Mbps were doubled.²⁸ Several inputs to this study are notable and relevant to the instant discussion: (1) the study measured terrestrial and satellite broadband connections but not mobile wireless broadband; (2) the study measured only certain row crops but did not account for specialty crops, livestock/dairy or poultry/egg production; (3) the study measured household broadband adoption rather than ag tech or PA adoption. Nevertheless, the results indicate a causal relationship between broadband deployment and crop yields, allowing an inference that deployment enables adoption which in turn leads to increased usage for agricultural activities. The USDA estimates that the “full potential” of ag tech would increase gross U.S. economic benefits by $47-$65 billion.²⁹

Next Installment: Broadband and cybersecurity in ag tech.