DJI Drone

Whether a producer has just a few acres or tens of thousands of acres, drones can collect and deliver lots of results from all of those fields.

Getting that bird’s eye view that you just can’t see from the road is the driving variable for the economics of drone business in agriculture, said Michael Ritter, SlantRange CEO. In a recent webinar, Ritter and company officials from DJI talked about their drone technology and new applications for their products.

“At the root of the entire enterprise is delivering data that is really a value to the grower at the end of the day,” said Ritter.

DJI and Slant Range are in the business of helping the ag community make smarter ag decisions with drone technology, he said.

To determine the value of using drones, SlantRange requires products include a high level of actionability – in other words, can the aerial data affect a decision that can positively impact the growing conditions for the producer. In addition, the drone must be readily available to provide aerial information at the time and the location where the producer needs it, and provide a return on investment.

There may be times when satellites, fixed wing airplanes or human scouts may offer a higher level of actionability – and may be able to provide information when it is needed.

At other times, drones offer a better solution.

“Drones have the advantage of being able to operate underneath the weather, where satellites are constrained, and you can deploy a small drone virtually anywhere on the planet, which is unlike a manned aircraft,” he said. “They have a great scalability where the others don’t.”

One of the challenges with the drones is the huge amount of data that is collected can be overwhelming.

Processing data with enough computing power in remote locations requires specialized services and that’s where SlantRange comes in. They developed a method to process all of the data from the drone right at the field location. No Internet connection is needed, and the data can be analyzed within a few minutes of flight. Of course, if Internet is available, the data can be pushed up to the cloud for analytics.

Some of the cases where drones have been successfully used include producing variable rate prescriptive input maps in corn. Using SlantRange and drone technology, the farmer produced a map showing variability in nitrogen uptake. Nitrogen deficiency was showing up, so the grower went to the field to see what was going on. Through soil samples, they determined there was plenty of nitrogen in the areas that looked deficient – but it had not been taken up by the plants for a couple of reasons.

Ultimately the agronomist came up with a variable rate prescription for fertilizer application. At the end of the growing season, between the cost saved on nitrogen and the increased yields, the farmer had a $35 per acre profit increase. To put into context, the breakeven for the technology and the time involved was 325 acres.

“For this particular user, this case, the technology and the time invested paid off relatively quickly,” he said.

In another case, farmers were looking at lettuce in a field in California. The farmer knew there was substantial weed growth in this field. The drone images allowed the producer to decide if they were going to hand harvest the crop or not.

With a high resolution picture, the software was able to identify plant types and separate by contrasting color. It determined the number of heads of lettuce per acre and look at the lettuce head size. The information allowed the producer to estimate the yield prior to sending a harvest team out.

They decided there were too many weeds and they decided not to harvest the field.

In another case, a multi-national company was able to track pineapple development in remote fields via drone photography.

“This enables this particular grower to visualize very quickly how yields are developing on a more granular level across their operations,” he said. “That allows them to react more quickly to changing conditions, and what practices are performing better than others, and adjust their practices accordingly.”

Plant breeders are now also using drones to characterize the development of test sites through aerial phenotyping. They can determine how different hybrids or input types will perform in real world situations, including differences in plant population, vegetation, and factors the occur throughout the growing season.

Finally, the producer can “train” drone technology to look for insights that are unique for them – for instance a watermelon grower may want the drone to identify a specific invasive weed. In another case, an alfalfa grower may be looking for saturated soil with the drone to determine soil moisture and any problems that may be occurring with tile lines or irrigation.

An insurance client can also use drones to characterize how much damage may have been done by a wind event, and to look for lodged plants.

“There is an immense range of applications in agriculture, and what we have shown is a mix of different examples, but also built into the tools is the ability for users to train to their own applications, and we have more examples of people producers using this training to their own purposes every day,” Ritter concluded.