Top 5 Precision Agriculture Technologies for Agritech Leaders in 2023

BIS Research
6 min readApr 11, 2023
Precision Agriculture Technologies

Precision agriculture is transforming the agriculture industry by introducing cutting-edge technologies, such as global positioning system (GPS), remote sensing, drones, and advanced data analytics.

These technologies optimize crop yields and reduce waste and costs, enabling farmers to make more informed decisions about how they manage their land and resources.

The global population is projected to reach 9.9 billion by 2050, which will require a significant increase in food production to meet the growing demand.

This challenge is complicated by the need to simultaneously address sustainability concerns related to climate change, natural resource depletion, and biodiversity loss.

To achieve these goals, the agriculture industry must become more productive and sustainable through increased investment, adoption of productivity-boosting technology, and participation from young people and smallholder farmers.

In this article, we will explore the most advanced technologies in precision agriculture that are crucial for agritech leaders to integrate into smart farms.

1. Guidance Technology

The guidance technology in precision agriculture involves the use of global positioning system (GPS) and global navigation satellite system (GNSS) technologies.

Satellites orbiting the earth transmit signals to the GPS or GNSS receiver on the ground, which uses this information to determine the precise location of the equipment or vehicle.

With the help of these technologies, farmers can accurately locate their fields, track livestock movements, monitor crop growth, detect crop stress or disease, and manage field operations more efficiently.

GPS or GNSS equipment and software can be used for a range of applications such as automated record keeping, vehicle navigation, inter-vehicle communication, and precision application of inputs such as seeds, pesticides, and fertilizers.

Moreover, by applying these inputs precisely, farmers can reduce overlapping and avoid wasting resources, which can lead to significant cost savings.

Furthermore, effective connectivity with networks such as Long Range Wide Area Network (LoRaWAN) and longer battery life can ensure the continued effectiveness of guidance technology in precision agriculture in the future.

For instance, Trimble’s GFX-750 display system uses GPS technology to provide automatic steering and guidance for tractors, as well as variable rate control for crop inputs such as fertilizers and seeds.

Similarly, Hemisphere’s A222 GNSS-enabled smart antenna technology provides high-precision positioning data for precision agriculture applications such as guidance, mapping, and yield monitoring.

2. Sensing Technology

Sensing technology is revolutionizing the agricultural sector by enabling data-driven farming and has become a crucial component of precision agriculture that aids farmers in efficiently monitoring and controlling their farm operations.

Sensing technology is used to measure various production factors such as soil temperature, soil moisture, air temperature, solar radiation, soil nutrients, harvest, soil pH, and weed density, helping farmers to make informed decisions while minimizing environmental effects.

For instance, CropX, an agriculture analytics company based in the Netherlands, used sensing technology such as advanced sensors and cloud-based precision irrigation tools to provide its customers with in-soil data and farm management analytics to support them in decision-making.

Moreover, the company’s acquisition by Amazon has helped it to explore using Amazon Web Services (AWS), such as AWS Internet of Things (IoT), to drive its expansion and enable sustainable agriculture.

Furthermore, the integration of sensing technology with data analysis software enables farmers to process the extracted farm information quickly.

With extensive data, sensing technology also supports other agriculture technology functions, such as guidance and variable rate technologies.

3. Variable Rate Application Technology

Conventional farming practices are challenged with problems such as excessive use of fertilizers and pesticides, depletion of soil nutrients, and water and energy wastage.

However, with variable rate application (VRA) technology, farmers can apply inputs at variable rates, thereby ensuring that only the required amount of nutrients are applied to each area of the field. As a result, the soil becomes more productive, and the yield per unit area increases.

VRA technology can be implemented in various categories, such as planting, spraying nutrients and pesticides, and irrigation.

By using VRA technology in planting, farmers can ensure that seeds are planted at the optimal depth and spacing, resulting in uniform crop growth.

In spraying nutrients and pesticides, VRA technology helps farmers to apply the right amount of inputs in the right areas, reducing waste and ensuring effective pest control.

In irrigation, VRA technology helps farmers to apply the right amount of water to different areas of the field, depending on their water needs, thereby reducing water wastage and ensuring optimal crop growth.

For instance, VRA technology such as John Deere ExactApply uses pulse width modulation (PWM) to control spray output and adjust the rate of application in real-time, providing precise coverage and reducing overlaps.

Furthermore, Variable rate planters/seeders (VRP/VRS) are precision agricultural technologies that modify the planting and seeding rate during application based on the specific needs of the field.

The VRP or VRS system typically involves a GPS system and a planter/seeder equipped with a suitable control mechanism.

The GPS system provides location data and allows the planter/seeder to precisely adjust the planting/seeding rate according to the specific needs of each location in the field.

The control mechanism disconnects the planting/seeding system from the ground drive wheel, which keeps the planting/seeding rate constant when the tractor’s speed varies.

Moreover, the planting map used in the VRP/VRS system is based on various factors, such as soil maps, topography, irrigation, and long-term yield history.

The system uses this data to determine the optimal planting/seeding rate for each specific location in the field and adjusts the planting/seeding rate accordingly.

4. Data Analytics and Intelligence

Data analytics and intelligence solutions are leading to an increase in revenue in the precision agriculture market due to their ability to provide valuable insights into crop management.

According to data insights from BIS Research, the global precision agriculture market was valued at $7.89 billion in 2022 and is expected to reach $14.61 billion in 2027, following a CAGR of 13.12% during 2022–2027.

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Moreover, data analytics and intelligence solutions are offered under the software-as-a-service (SaaS) model and utilize artificial intelligence (AI) and machine learning (ML) technologies to aggregate trends, assess risk and reward, track supplies, increase yields, and generate predictive models.

With the rise in the implementation of cloud services, offering data analytics and intelligence software services has become convenient for precision agriculture service providers.

For instance, Cropin, an ag-ecosystem intelligence provider, offers an interconnected data platform to farmers, which records multiple high-quality data points during the crop lifecycle.

The largely collected agronomic data includes soil data, harvest quality and quantity, crop images, plot data, irrigation details, pest and disease incidents, geotags and land record IDs, fertilization and chemical input details, seed variety, sowing date, all-weather parameters, and satellite data.

Cropin utilizes Amazon SageMaker to handle the heavy machine learning workloads and employs serverless frameworks with AWS Lambda to train the models, which ultimately assists farmers in making more informed data-driven decisions.

This technology helps bridge the gap between data and decision-making, resulting in a better understanding of potential risks and opportunities throughout the entire supply chain.

5. Hardware Telematics

Hardware telematics involves installing sensors and communication devices on farm machinery such as tractors, combines, and sprayers.

These sensors collect data on various parameters such as engine performance, fuel consumption, and soil conditions.

The data is then transmitted to a central server, where it is analyzed using machine learning algorithms to provide insights into machine performance and potential problems.

For instance, Fendt, a company owned by AGCO Corporation, offers a telemetry solution called Fendt Connect, which provides real-time information on machine location, fuel consumption, and maintenance needs.


With advancements in technology, such as artificial intelligence, machine learning, drones, and autonomous robots, farmers will be able to collect and analyze vast amounts of data about their crops, soils, and weather conditions.

As a result, more farmers will embrace precision agriculture, and we can look forward to a future of sustainable, efficient, and productive farming practices that can meet the growing demand for food while preserving our natural resources.

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