As the globe’s population continues to grow consuming more and more resources, and available land decreases, farmers need to maximize their efficiency. From 2014 to 2018, the United States lost over 14 million acres of farmland. Precision Agriculture (PA) is a farm management concept based on observing, measuring, and responding to variability in crops, both inside a field (intra-field) and outside (inter-field). PA solutions often include specialized sensors, software, and cloud-based services. PA sensors in fields can measure parameters such as moisture content, air and soil temperature. Satellites and unmanned aerial vehicles (drones) can provide growers with real time multi-spectral imaging of their fields and even individual plants. This information can be processed with the assistance of artificial intelligence and machine learning to assist a farmer in making decisions, such as how much soil additives and irrigation to apply in order to increase profitability and sustainability.
The Challenges of Precision Agriculture Adoption
Farmer adoption of PA technologies is still fairly low across the U.S. agriculture industry, with about 50% of corn growers using PA systems and a much smaller rate across other crops. Large farms (3,800+ acres) are more likely to embrace PA practices. The average farm size in the U.S. in 2016 was 444 acres. There are 670,000 small and medium farms and about 46,000 large farms. Lower adoption of PA in smaller farms can be attributed to several reasons:
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High cost: PA technology generally requires a large upfront investment which is simply unaffordable for small and medium sized farms.
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Extensibility: Many existing PA solutions today focus on broad acre row crops (such as soy and corn), which have relatively consistent growing conditions. Growers of specialty crops in areas with variable micro-climates and soil conditions are unable to have the density of sensors to properly measure the nuances across their land.
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Specialized labor requirements: Numerous existing PA solutions require specific agronomic expertise to maximize their value, requiring an agronomist or consultant on staff, and putting them out of reach of small producers.
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Market fragmentation: smaller farms and specialty crops compose a fragmented market that is difficult for a PA company to enter.
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Connectivity issues: especially in developing nations and rural areas, connectivity problems and data costs to implement cloud computing have produced affordability challenges to PA adoption.
Unlike field crops, which require little nuance across broad acreage, specialty crops have huge variability versus on crop type and growing conditions. As a result, most solutions historically focused on building products for a single crop type rather than a solution that works across all crops and conditions. According to a 2007 study, field crops made up 96% of farmland in the U.S., but only 63.2% of total revenue, while high-value/specialty crops only consume 4% of total farmland, but create 36.8% of total revenue.
Precision Agriculture Investment Dynamics
There is a market gap for PA technologies that are extensible globally across various geography, crop types, and agronomic practices with a focus on specialty crops. The domestic and international specialty crop market is expected to reach $1.8 trillion in value by 2026. Companies that can provide hardware and software solutions that fill this niche while remaining affordable for small and medium size farmers are best positioned to excel in this space.
Many large agriculture companies have invested in research and development to create PA solutions and are also making strategic acquisitions of PA start-ups. This activity provides strong opportunities for potential investor exits.