and the Future of Plant Health
By Dan Jacobs, Senior Editor, AgriBusiness Global and CropLife
As technology continues to get more sophisticated, it’s easy to forget that those solutions are only effective if the hands wielding them can accurately interpret the data the tools provide.
In that sense, while biologicals, plant growth regulators and soil amendments continue to flourish, “Not a lot has changed, when it comes to collecting the data to help drive a recommendation,” says Brent Wiesenburger, Director of Ag Technology Services, Agtegra Cooperative.
Formed in 2018 from the unification of two farmer-owned cooperatives — 95-year-old South Dakota Wheat Growers (Aberdeen, SD) and 102-year-old North Central Farmers Elevator (Ipswich, SD), Agtegra Cooperative uses FieldReveal to manage their patrons’ precision farming data.
“Most ag retailers generally have unique methods to create management zones, grid soil missions, or drive plant tissue testing from digital data sources like Veris EC or satellite imagery. However when it comes right down to it, we are still collecting the data the old-fashioned way, with our hands,” Wiesenburger says. “While companies are developing equipment to automate soil sample collection with Utility Task Vehicles and even tissue sample collection with UAVs, these are still operations that require supervision when it comes right down to it.
“Varying soil conditions like wet depressional areas paired with our 2-depth sampling practices really provide unique challenges that automated equipment isn’t ready to deal with just yet,” he says.
Once the samples have been collected technology can take over. Several companies offer decision models that consider localized weather, soil conditions, satellite imagery, and many other environmental factors into driving recommendations. Wiesenburger describes these systems as “Unsupervised” models meaning machine learning and advanced algorithms decide an outcome. However, when it comes right down to it the last and most important step is the supervised decision. “This is where the agronomist and the grower work together to make decision to apply a fungicide or post application of a crop nutrition product. Adding that the human touch is key.”
“There's a lot of technology out there, but it still takes that relationship between a grower and an agronomist understanding the [needs] on that farm to [develop a plan] to reach that farmer's goals on that particular field,” says Brad Ruden, Agtegra’s Manager-Agronomy Tech Service.
“We've got the technology to help us know where to sample; we've got the technology to help us know how to gather those initial numbers, and even provide a suggested treatment based on a refined algorithm, but we still have to interpret that and put that plan into action on the field, and that still [requires] human involvement,” Ruden says. “There's great input there. We still must have that human factor factoring executing on the goals.”
Localized data, even down to specific regions of a field, allows growers to focus plant health activities where they’re needed.
“However, localized data also improves our recommendations from the cooperative level. If we have that localized data set, we'll be able to provide more stable answers relative to our region,” Wiesenburger says. “It allows us to have a lot better agronomic conversation at the local level and provide agronomists with the tools to go and sell a product. We're trying to empower our sales team with the analytics to help them make a more confident decision when it comes to helping these farmers succeed.”
It’s not just software and handheld devices that provide data. Satellite imagery has been available for decades and, more recently, we have access to unmanned aerial vehicles (UAVs).
“Many companies are coming into that space with more satellites taking pictures,” Wiesenburger says. “There're companies that are providing daily images of the globe. So, we can see status changes in crops over time.”
Another imaging technology has come into focus in the past several years. UAVs or drones can fly a few feet above a crop and using embedded artificial intelligence can help agronomists identify nutrient or disease stress, Wiesenburger says.
With the right modeling tools and the right interpreting of that data, growers can make more informed decisions about how to treat their fields or parts of fields.
Technology has also led to changes in the application of crop nutrients. Tissue sampling provides growers with immediate feedback on a crop’s needs. This “just-in-time crop nutrition,” Ruden says, has more growers “moving away from the model of applying all the crop nutrition upfront and moving more toward in-season crop nutrition to fulfill the remainder of crop demand based on what weather the season provides and what the crop potential can do.
“Beyond technology, crop input manufacturers are delivering a variety of new tools for nutrient management in agriculture,” Ruden continues. “Breeders continue to provide excellent new varieties and hybrids that increase nutrient use efficiency. Effective additives are available to maintain availability of crop nutrients added to the soil. Additionally, newer inputs such as the rapid expansion of biological products that aid in nutrient availability, are becoming commonplace. All these technologies are improving crop production potential.”
“Technology is and will continue to help us track and analyze the value of these inputs, allowing agronomists to better guide growers in choosing inputs for their specific farms,” Ruden says.
In short, maximizing tech means balancing tech with good old human know how.
“It's an exciting time to be in agriculture,” Ruden says. “We've got good commodity prices right now. The tools are available to help our farmers and agronomists learn more and more about their fields, analyze input decisions, and take their farms to the to the next level of productivity and return on investment.”
