Introduction

Plantos aims to provide small and medium-sized agricultural operations with a user-friendly and low-cost approach to harnessing hardware, data, and AI for farming practices. Precision Agriculture Technologies (PATs) are key to enabling farmers with cost-effective and environmentally sustainable farming practices. With growing populations, finite resources, and dwindling margins, implementing efficient farming practices has become more relevant than ever.

From little things, big things grow.

Why Plantos?

With the global population projected to reach 10 billion by 2050, the farming industry faces a critical challenge. It must adapt significantly to meet the needs of this growing population while simultaneously minimizing environmental impact and maintaining financial viability. With the increase in agricultural output comes a plethora of new obstacles and new ways to solve them. PATs are revolutionizing how farmers can scale to meet population needs, making it easier to optimize inputs, detect diseases, and predict crop yields—all of which serve to reduce input costs and conserve resources.

PATs come with their own set of obstacles that make implementation difficult for a major portion of small to medium-sized farming operations. Primary barriers to entry among small farms include costs, ease of use, and reliability/range. Farmers who are already operating on minimal margins find it difficult to take risks on new technology that has an unproven track record. Accurate and reliable hardware tends to be quite cost-intensive and operationally complex, which is why PATs are historically more frequently deployed in large-scale farming practices. Large swaths of the farming population are missing out on the efficiencies that PATs can offer due to these barriers.

Finding Solutions in Data

Plantos provides a co-op based forum to navigate these barriers to entry and explore new methods for reasoning about technology in the smallholder farm. The goal is to create a a low-cost and user friendly stack of tools through focusing on major technological advancements.

Combination of two key tech concepts:

  1. Remote sensing (RS)
  2. Machine Learning (ML)

Internet of Things (IOT) devices provide us with a low-cost method for collecting data in the field and relaying it to a network for analysis. Where low-cost RS lacks in accuracy, ML will be able to standardize data and maintian data integrity. Then predictive models will be able to digest the input data and provide users with actionable information right to their phone or computer.

Join the Discussion

Plantos stands at the intersection of agricultural necessity and technological innovation. By addressing the critical barriers of cost, complexity, and reliability that have traditionally prevented small and medium-sized farms from adopting tech, we're democratizing access to tools that can transform farming operations.

Our cooperative approach combines the power of remote sensing, machine learning, and IoT devices to create an accessible ecosystem that turns data into actionable insights. Farmers using Plantos don't just gain technology—they gain a pathway to increased efficiency, reduced environmental impact, and improved profitability without the prohibitive investments typically required.

As we face the challenge of feeding a growing global population with limited resources, Plantos offers a practical solution that aligns with both economic realities and environmental responsibilities. We believe that sustainable agriculture shouldn't be a luxury reserved for large-scale operations but a fundamental approach available to all farmers.

By empowering agricultural communities with affordable, user-friendly technology, Plantos is sowing the seeds for a more resilient and productive farming future. Because when farmers thrive, we all benefit—and from little things, truly big things grow.

Picture of Success

Envision a future where farming uncertainties are minimized through precise, real-time predictive analytics accessible via smartphones. In this world, successful farming no longer relies solely on generational wisdom and costly trial-and-error approaches. Instead, farmers can proactively identify potential challenges and implement preventive measures, thanks to data-driven insights that guide their decision-making. This technological advancement democratizes farming expertise, enabling both seasoned and novice farmers to optimize their operations with greater confidence and efficiency.

Imagine a world where access to effective technology is not synonymous with absurd costs and confusing interfaces. This is a world where data is owned by the farmers and any hypothesis or efficacy concerns can be tested through experimental design. Users have protected rights over the data they produce and share in the collective benefits of data aggregation when they choose to collaborate

The path to this agricultural renaissance lies not in further technological innovation alone, but in our commitment to ensuring these tools serve the many rather than the few. As we navigate this critical transition, we must deliberately shape policies, marketplaces, and community networks that uplift smallholder farmers rather than leaving them behind. The democratization of agricultural technology represents our best chance to preserve the diversity, resilience, and local connection that small farms provide while addressing the productivity challenges of feeding a growing population. In this vision, precision agriculture becomes not just another competitive advantage for the largest operations, but the foundation of a more equitable, sustainable, and abundant agricultural future—one where technology serves as the great equalizer rather than the dividing line between those who will thrive and those who will fade away.

Precision Agriculture Primer

Commonly referred to as PATs or PAs, the term Precision Agriculture Technology refers to a growing school of data-driven tools for collecting input information from crops to optimize their yield and minimize resource use/costs. PATs are nothing new to the agriculture community but with ongoing advancements in hardware and AI, they are rapidly evolving how we approach farming:

"[...] precision agriculture has emerged as a crucial innovation in combating food insecurity by enhancing the efficiencies and sustainability of farming practices. Utilizing cutting-edge technologies such as GPS, remote sensing, and data analytics, precision agriculture optimizes resource use, reduces environmental harm, and enhances agricultural productivity."

Factors Influencing Precision Agriculture Technology Adoption Among Small-Scale Farmers in Kentucky and Their Implications for Policy and Practice

PATs are used to tackle a wide-variety of different obstacles faced by farmers, some relevent implementations today are:

  • GPS monitoring and automations
  • Drone imaging to predict crop yields
  • Remote sensors for measuring soil nitrogen
  • AI imaging to detect diseases in crops

The Current Landscape of Precision Agriculture

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]:

  1. Cost
  2. Ease-of-use
  3. Interoperability
  4. Power consumption
  5. 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.

Join Us

If you find precision agriculture and similar topics interesting, stay close to Plantos’ co-op as we reason through the research, practical implications, and future of technology on the smallholder farm

References

  1. Factors Influencing Precision Agriculture Technology Adoption Among Small-Scale Farmers in Kentucky and Their Implications for Policy and Practice
  2. Exploring Barriers to the Adoption of Internet of Things-Based Precision Agriculture Practices
  3. Integration of Remote Sensing and Machine Learning for Precision Agriculture: A Comprehensive Perspective on Applications
  4. America’s Farms and Ranches at a Glance: 2022 Edition

Technology's Home in Agriculture

  • Published:
  • Updated:
  • Author: Tyler Dennis
  • Discussion:

The Internet of Things (IoT)

How do devices talk?

IoT is a gernalized term that refers to the network of communication created between devices, sensors, applications, etc. talking back and forth to each other. One might speculate that IoT devices share data by connecting to the internet; a large portion of devices do operatate this way, but there are numerous other types of communication protocols like bluetooth and LoRa that allow for IoT devices to communicate.

IoT in Plantos

IoT plays an essential role in gathering data in the field, especially when it comes to performing the real-time analytics required for successful precision agriculture. Plantos creates an IoT network between micro-controllers connected to sensors and a centralized gateway which relays data to a cloud database.

image

Remote Sensors

LoRa (Long Range Radio Communitcation)