This Understory sensor, the ball on the pole, is in Argentina at the edge of a field. The company’s sensor has no moving parts and collects information that specialized software can use to manage a range of crop issues precisely.
A tool used by the seed industry is getting wider attention for enhanced crop management.
There are a lot of factors to manage on the farm, but one that often feels unmanageable is the weather. It’s the one growing factor farmers can do little about, but what if you had hyper-local information that offered in-depth plant information at peak season?
Understory, a 7-year-old start-up, is expanding into agriculture and providing a level of weather information not seen in the past, according to Darcy Pawlik, vice president, global agriculture. “We’re both software and hardware,” he explains. “When you have the hardware that can allow another degree of precision available to the industry, it makes a difference.”
The company’s baseball-sized weather sensor captures a range of factors. Match that with an advanced software suite that includes machine learning and artificial intelligence for decision-making, and the simple weather system can make a difference.
Pawlik notes that the company works with large seed companies that seek more than your basic weather station data. “The need a step change and another degree of precision to optimize their production fields,” he says. “That’s information they can use to manage harvest dates, and when to irrigate those fields.”
Seed companies are constantly looking at ways to boost productivity and enhance performance. “We work with large multinational seed companies, and they have a lot of knowledge and know-how to apply data for irrigation, spraying needs and the pests that might come up,” Pawlik says. “We find that these companies need the weather data.”
The weather-capture device Understory uses can measure a field and extrapolate what’s happening to determine when to spray or irrigate. The device is a metal ball on top of a data collection device. “It measures energy, and it allows us to capture data long term,” he says. “It has no moving parts, and it’s one of the things that gives us 10 years of longevity in the field.”
That’s good news, because the sensor can be installed in more remote areas and needs little attention. One innovation of the tool is that it can be installed the periphery of the field and still provide weather data for the farm.
“We stay out of the way,” he says. “It depends on the topography, but we can cover 4,000 to 5,000 acres per sensor. We measure all the weather parameters including rainfall, windspeed, direction, temperature, humidity, dewpoint, solar radiation, hail, evapotranspiration, growing degree units — and through extrapolation, we can create complex models.”
The sensor captures 100,000 measurements per second, Pawlik explains: “We’re getting real-time data through a web interface; and with good data, you can measure trends a lot better. We can predict plant disease or insect infestations with the information.”
Putting weather data to work
Pawlik picks a harvest timing example showing how this data gathering tool and its models make a difference for seed companies. “We can give insights to a harvest crew, which is important for seed corn,” he says. “If they are 10 days behind for a field that’s 100 miles away, they need to gear up to get all harvest ready for that field. But the seed corn may have higher moisture there; what if they wait? If you have drydown time, you’ll need gas or bins if you’re not harvesting mature corn. But 10 days later, when the crop is drier — you can see a yield increase, and you save on gas for drying. This system has paid for itself a few times over.”
This start-up isn’t ready to go directly to farmers yet but is finding success with seed companies and specialty businesses. The tech does show how hyper-local information combined with added interpretation software can offer a payback in the future.
In Argentina, the recent drought caused trouble for farmers there. Understory was working in partnership with Bayer, showing how the company’s products can predict how crops behave based on environmental conditions. The precision information could even predict the amount of leaves a plant will have at a given time, according to the company.
The drought complicated the growing season; but with Understory, data farmers could pinpoint the best harvesttime, adjusting it by two weeks and increasing yield. It shows how granular data can help with payback.