Seeds, Water, Dirt, and Data: The Smart Farming Essentials

September 23, 2024

Blog

Farmers have relied on data for centuries. They first collected data by hand, tracking information like total seeds planted, the number of days it rained, and the total plants collected at the end of the season. With the dawn of the computer age, that data moved to spreadsheets and eventually to the cloud. While the manner of data collection and analysis has changed, the purpose hasn’t:

Data helps farmers make more accurate and timely decisions at the plant level.

Farmers rely on data because agriculture isn’t rocket science – it’s harder. Farmers deal with living organisms that are exposed to unpredictable environments. Well-thought-out strategies and actions may not work if an unexpected hailstorm hits or a new type of weed overtakes a field. Adding to the challenge, farmers today often have fewer hands available to get time-sensitive work done on the farm. Farmers need data, both from previous years and the current moment, to understand the variables better and make informed and timely decisions.

Data Helps Farmers Do Multiple Jobs at Once

Farming is a continuous cycle. For example, when farmers are harvesting one crop, they also need to prep the soil in other fields through a process called tillage. Doing two jobs at once is already a difficult task. Now imagine doing two extremely precise tasks at once over thousands of acres of land. It takes an incredible amount of time and resources to get it all done.

Technology, including fully autonomous tractors for tillage, helps address this challenge. Since tillage is a straightforward task, farmers can use historical data to map out the route the machine needs to take in the field, and then wirelessly send the route to the machine. All the farmer has to do is bring the tractor to the start of the path and swipe on their phone to start the job. As the tractor tills, the farmer can check the progress or review potential obstacles while harvesting in a different field miles away. The autonomous tractor acts as an extra set of hands, so farmers can focus their time and workers on the complex job of harvesting.

Farmers also depend on data for timely, accurate decision-making to help with harvesting. Multi-ton machines called combines can quickly pull plants out of the ground, separate the desired crop (like corn kernels) from the rest of the plant, and move the crop to a cart for transport to storage. To do all of this effectively and reliably, the machines have to process large amounts of data about the field and plants. Environmental conditions such as soil moisture can affect the speed at which a combine can harvest without damaging the crop. With access to real-time data, farmers can analyze those factors instantly and adjust specific steps to find the right balance of speed and quality.

Data Gets Every Seed Exactly Where It Needs to Be

Data is also helpful for farmers when they begin the planting process, which comes with its own set of challenges. For example, if farmers plant seeds too close together, they will steal valuable nutrients from one another. If farmers plant seeds too far apart, they won’t be able to get as many in the field, resulting in less profit.  

Farmers can use data from previous seasons to make a plan for their seeds and determine how deep and far apart to plant them. They can also use tillage maps from a few months before to understand the field conditions and which areas of the field to prioritize the most seeds in. Once they have a plan, farmers can use planters integrated with robotics to get the job done in seconds, including making a trench, placing the seed, applying the starter fertilizer, and filling the trench back with dirt.

Today’s advanced planters use sensors, cameras, and lasers to measure and track the depth and spacing of seeds, so farmers can make in-the-moment adjustments without getting out of the cab. That saves valuable time, as a large farm could be around 5,000 acres (roughly 4,000 football fields), with room for more than 750 million seeds to get into the ground.

Data Enables Target Spraying at Scale

Once the crop starts to emerge, so do weeds. Weeds steal nutrients, sun, and water from other plants, so farmers spray weeds with herbicides to allow their crops to reach their full potential. In the past, farmers had to spray the entire field to get rid of all the weeds. Now, with robotics and data-backed computer vision and machine learning models, farmers can target-spray only the weeds, reducing the amount of herbicide needed by up to two-thirds.

Smart, automated sprayers use data to know where they are in the field, analyze images captured from cameras to distinguish weeds from desired plants, and activate robotic nozzles at the exact moment to spray only the weed. With each pass over the field, the data collected through the machine builds out a weed map, which helps farmers strategize how much herbicide they might need next season and how to change planting patterns to get the most out of each seed planted. Data-based systems can even alert the farmer when a spray tank is nearing empty and needs refilling, saving valuable time and enabling the farmer to plan fill-ups and maintenance proactively.

Once the plants have grown to their full potential, it’s time to start the dual job of tillage and harvest again. It’s a never-ending cycle that depends on data.

Data is the Report Card of a Farmer’s Operations

At the end of each season, farmers get to see how effectively the data-informed and improved their decision-making and other actions. It’s like getting a report card at the end of the school year. During each phase – harvesting, tillage, and planting – farmers collect real-time data and analyze historical data to make the fastest, most accurate decisions possible.

Data can help farmers minimize variability in their operations and make the most of their resources year after year. Rather than leaving things to chance, farmers can use data to understand the current conditions of their fields, see how many seeds they planted in past seasons, make an informed decision on where to plant, analyze the areas of the field most prone to weeds, and put it all together produce the healthiest plant possible. This level of specificity and insight helps farmers get the most out of every plant, which boosts their profits and helps the world at large since we all rely on the crops they produce.