The Current Landscape of Precision Agriculture

Published: 2025-04-18
Updated: 2025-04-22
Author: Tyler Dennis
Discussion: 14-03-2025

Is Technology Threatening The Small Farm?

Precision Agriculture Technologies (PATs) are currently a catalyst to the growing disparity between large-scale farming operations and small to medium sized farms. While the agricultural industry is not a zero-sum game, large-scale farming practices clearly benefit from systematic advantages, widening the resource gap experienced by small to medium-sized farming operations. High barriers to entry, such as costs and complexity of use, result in the benefits of PAT implementation to be primarily realized by large-scale farms. The edge gained by utilizing PATs is compounding; resources saved from implementation one season can be reinvested into the crop and farming infrastructure the next season, allowing for an exponential increase in yield year after year.

Small Farms, Big Impact

Ensuring the future of smallholder farming is synonymous with ensuring the future of food security, environmental stability, and wide-spread economic affluence. According to the USDA, small family farms are defined by gross cash farm income below $350,000 annually and make up about 89% of the population of farmers in the US [4]. These small family farms create food security and diversity through the variety of crops they generate, establishing agricultural biodiversity and reducing dependence on monocultures. In times of crop failure, diversity enhances food security by providing alternative non-effected crops. This diversity plays a role in environmental stability by cultivating soil health, supporting food-webs, and promoting pollination; in general, local farming practices are associated with taking better environmental stewardship over land. These smallholder farmers tend to employ and support local communities and their interests to a further extent than industrial farming.

Competition with large scale farming, cuts to government grants and subsidies, and rising expenses of resources and land are only a few of the factors preventing smallholder farmers from staying afloat. Just as we as a community cannot afford to let these farms fall behind the in the agricultural industry, smallholder farmers cannot afford to forgo PAT implementation. Rapid advancements in hardware and artificial intelligence are enabling the creation of cost-efficient and user-friendly PAT tools. These developments have the potential to transform the current reality of farming, making these technologies more accessible to a broader range of agricultural operations.

Numbers Reveal the Divide: Analyzing the PAT Adoption Pattern

Smallholder farms demographically make up a huge portion of the agricultural landscape yet experience an asymmetrical amount of crop productivity per area of land, the lack of PAT integration plays a significant factor in this statistical inbalance.

[...] about 89 percent of all farms were small family farms. Small family farms operated 45 percent of U.S. agricultural land and produced 18 percent of the total value of production.

America’s Farms and Ranches at a Glance: 2022 Edition

Socio-demographic variables (i.e., age, gender, education, farming experience, income, and farm size) and their correlation with PAT adoption can help explain the current state of precision agriculture in small to medium-sized farms. Studies show that individuals most likely to adopt PATs are between 25-50 years old, have post-secondary education, extensive farming experience, and manage large acreages [1]. Small-scale farmers are significantly underrepresented in this demographic compared to industrial farming operations. Examining the barriers to entry can help us identify areas of improvement to increase PAT integration to small and medium sized farms.

The top 5 setbacks for smallholder farmers in deploying PATs are [1] [2]:

Cost
Ease-of-use
Interoperability
Power consumption
Signal range

High costs present the greatest barrier to entry, driven by the novelty of technology and the need to purchase multiple units to achieve scale. The high prices are not perceived as a favorable cost-reward tradeoff for smallholder farmers who are not in a position to take on additional input costs. Setup, onboarding, user interface, and data interpretation can result in a depletion of precious time and cause unnecessary frustration for farmers who decide to implement PATs.

The rapidly evolving nature of technology results in the accumulation of varying tech from different companies. The lack of interoperability between these different systems can render devices unusable, even though they may be only one or two generations old. Even with newer models, high-powered systems force developers to choose between optimizing signal ranges, power sources, and accurate sensing components, leaving room for inconsistency.

All these factors, among others, diminish the urgency to integrate PATs into small to medium-sized farms. This results in a missed opportunity for these farms to improve resource management, profits, sustainability, and labor efficiency.

These challenges are more manageable for industrial farming operations due to their substantially higher risk tolerance compared to smallholder farms. The high costs associated with PATs mean that returns are realized more quickly at scale, making the payoff less appealing for local farmers. Farming is inherently a risk-averse industry, and when external factors have made the prospect of a thriving farm increasingly unattainable for smallholder farmers, taking on the risk of new and expensive technology can seem impractical.

The Turning Point

Cost and ease-of-use were by far the greatest barriers to entry for small-scale farms implementing PATs. Rapid advancements in computing, hardware, and AI make these existing obstacles a thing of the past. The combination of low-cost remote sensors and machine learning offers an opportunity to drastically lower unit costs while maintaining data accuracy [3]. Here researchers combined soil nitrogen data collected from sensors costing less than a $0.01 per a unit and normalized the otherwise inconsistent data with machine learning; the result, they were able to create predictive models with an R-squared coefficient of 0.65 (a high accuracy in the realm of ML).

LoRa-enabled IoT devices allow for straightforward user interfaces and sensor pairing workflows, all while transferring high-throughput data over extended distances at minimal cost. These technological advances work together to lower the primary barriers to entry for PATs, enabling small-scale farms to leverage their advantages and remain competitive with large-scale operations.

With growing populations, diminishing environments, and rising food costs, there is an urgency to integrate PATs into smallholder farms as soon as possible. PATs offer a solution to tackle impending global issues in the agricultural industry, and ongoing developments in hardware and AI will be key to reducing barriers to entry for their use. Without the implementation of these technologies, smallholder farms face not just stagnation but potential decline in both productivity and long-term viability. As these critical technologies become more accessible, the rise of digitized agriculture simultaneously brings many new open-ended questions around data privacy, policy and regulation, market dynamics, and more that will need to be carefully addressed as the industry evolves alongside smallholder farmers.

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