Productivity, efficiency, and return on investment (ROI) are always top of mind in any agriculture business. Since manually catering for the heavy-duty and intensive chores of agriculture requires a lot of time and energy, farmers started leaning towards the use of drones to ease these hurdles. According to Fortune Business Insights’ Agriculture Drones Market Global Report, the global agriculture drone market size, valued at $4.17B in 2022, is now projected to grow from $4.98B in 2023 to $18.22B by 2030.
In DroneDeploy’s State of the Drone Industry Report 2022, the company states that farmers claim improvements in operations, as well as planning and design by using drones to digitize their farms. Apart from the obvious advantage of mapping and surveying a farm, drones are also great tools for monitoring crops and livestock, assessing and extracting soil data (all in real-time), smart spraying and seeding/planting, and more. All these benefits lead to enhanced efficiency, advanced accuracy, seamless data collection, increased safety, time-saving, and reduced investments—all of which count towards an increase in ROI.
But how do you measure that ROI? How do you make sure a drone is a benefit and not a hindrance? While a drone might provide all the advantages mentioned above, it doesn’t necessarily mean it’s a pick-up-and-play tool that’s easy to work with. Setting up a drone program requires studying and understanding how a drone may benefit your use case to, in the end, increase ROI.
For example, the choice of a drone depends on the use case at hand—do you require a spraying drone, a drone that can carry multiple payloads, a very high-accuracy mapping drone, or even a drone-in-a-box solution to perform autonomous flights from time to time? Does the drone come with proprietary software, or will you need third-party software? Do you have the necessary hardware to view, manage, and edit the drone-collected data? And on top of that, it’s also important to consider the time it might take to learn and properly analyze that data. If this sounds too complex, maybe consider taking advantage of a drone-as-a-service solution, where a company does all of this for you for a price. These are only some of the questions you need to ask yourself when setting up a drone program to take the first steps into increasing ROI with drones in agriculture.
As the saying goes, “time is money,” so it is important to know if a drone is helping to analyze a farm faster and more efficiently. In an article from Precision Farming Dealer, Bob Recker, owner of Waterloo, Iowa-based Cedar Valley Innovation and a retired engineer from John Deere, shared 17 tips for generating ROI by capturing the most practical value when taking flight with UAVs in agriculture. For instance, Recker recommends setting up a flight path and storing it, “to fly that same pattern over and over, and overlay the images to see how things change over time.” In addition, the “best time of day to fly is 15-20 minutes after sunrise because you get long shadows,” making it easier to identify if a plant is starving, injured, or missing. At high noon, you might not see it at all.
He also states that “when you see a straight line in a field, it is a manmade or equipment problem. Curved lines represent nature—problems with soil, topography, or wind. Typical manmade problems originate when an anhydrous tank ran low, the center of the planter was lighter than the ends, or if there is too much or too little tile in an area.” Finally, “if you can see a problem from the air, there will be a yield impact and it’s usually a negative one—even if it doesn’t later show up on a yield map.”
In 2017, Dusty Wilkins, a farmer from Rupert, Idaho, bought a DJI Phantom 3 and a DroneDeploy subscription to map and regularly scout his fields for signs of plant stress. After a twelve-minute flight at 190 feet altitude above a 26-acre plot, DroneDeploy’s software helped Wilkins to identify what was “the worst aphid infestation” he’d ever seen. Without drone mapping, Wilkins would have to hire a fertilizer agronomist to find the pests, “but at this point of the season, we had full leaf row closure, so walking through the field takes time and it’s really hard. The field man wouldn’t have picked up the infestation for a week,” he said. Because Wilkins caught the infestation before any real damage was done, he got a head start on treatment and prevented significant loss of sugar content to his crop. At $40 per ton, multiplied over 185 acres of beets, he could have been out at least $60,000 in lost revenue. So, in the end, it’s not just about collecting data faster, but also choosing the right payload and the right software to collect reliable data to keep a farm healthy and detect issues beforehand.
Source: commercialuavnews.com
Photo Credit: gettyimages-seregalsv
Categories: Iowa, Business, Energy, Livestock