If you asked most farmers 10 years ago for their definitions of precision agriculture, they would’ve likely included the terms variable-rate technology, satellite imagery or yield mapping. Today, that definition is far more fluid because there are many ways to collect a variety of data, and just as many ways to interpret and apply it to crop and livestock production.
Today’s data collecting tools include yield monitors, weather stations, satellites, drones and an array of sensors that can measure everything from subsoil temperature to leaf surface moisture.
Identify areas of high and low productivity within fields using ag data collection and analysis tools to help inform farm management decisions and drive profits.
The biggest hurdle is analyzing and interpreting collected data in a way that makes it useful to farmers; however, with digital technology now omnipresent on the farm as it is everywhere else in society, that nut is being cracked fast — it’s only a matter of time before farmers will have all the information they could possibly want about their farms at their fingertips, 24-7.
New systems to analyze and interpret data
The agriculture industry has come a long way in developing applications and software platforms that aggregate farm and production data in one place, which is the first step to making it more useful for producers.
An example is the Climate FieldView platform from Bayer Crop Science, a digital data management system that allows producers to visualize and analyze crop production data and parcel maps to assist with management decisions at different times of the year — from seeding through to harvest and crop plans for the following years.
“A lot of the tools, like FieldView, that you see rolled out to these digital platforms are about using the reams of data to help drill down closer without removing some of the margin of error,” says Derek Freitag, market development lead with Bayer Crop Science.
“It uses all the data to make informed decisions for your fields, create management zones and track what you’re doing and the results. You can create zones and an application map, but if you can’t go back at the end of the season and see the results of what you did in a field, how do you know if you are managing those zones the way they should be managed and making the right decisions using the right products in the right areas.”
There are three basic types of data available to farmers: publicly sourced data that is freely available, such as legal land surveys and topographical and soil zone maps; grower-generated data from equipment such as seeding or yield monitors; and sensory data from weather stations, soil sensors or probes.
“There is an endless supply of different sensors that can be plugged in and feed information,” says Devin Dubois, CEO of FieldAlytics, another platform that aggregates and interprets farm data. “Within each of those categories there are other digital things like localized drone imagery or aerial imagery, which is another form of user-generated information that either you get somebody to do or have to get the tools to do it yourself.”
Getting value from the data
The true value of that data is in its analysis through a spatial lens, says Dubois. “To me, the higher value is from putting your farm into a spatialized, digital system, so you can measure your production and see where you are losing money and where you are gaining money,” he says.
What often happens with farm planning and analysis is producers at the end of the year take all their costs and revenue information to the accountant and have either a field, farm or crop variety margin. However, when farm managers only consider overall margins, they won’t know what problems they need to address on their farms or which tools they need to help with this.
“Generally, when you do a field, farm or crop unit analysis, you’re seeing a global number, and it might not look that bad from an economic perspective if, for example, you have a 13 per cent positive margin on your canola,” says Dubois.
However, if producers apply a spatial lens, they might find that 20 per cent of their acres actually lose money, as was the case in a recent U.S. economic study that found almost 20 per cent of seeded corn and soybean acres were unprofitable.
“Despite that the whole field generates a 13 per cent margin, there are portions of that field that are bleeding money,” says Dubois. “You don’t find those opportunities or issues unless you look at it through a spatial lens. The bad production and the great production doesn’t occur in 160-acre or 320-acre blocks. They occur in 10 acres here, or four acres there, interspersed in that production. If you can identify where the bleeding is, and where the grand successes are, then you can start to make decisions that attend to that. That’s where the value of the data is.”
Don’t get caught up in the gadgets
All too often, says Dubois, producers can get caught up in the gadgets: the tools and equipment used to generate the data.
“It seems to me that’s skipping the notion and the value, because they need to digitize and analyze their production to understand what problems they should be trying to solve,” says Dubois. “I get the sense that very few people understand that properly.”
If producers are losing money every year on areas of their fields, it adds up. When they can see the problem, they can make decisions about how to handle it and potentially save themselves money.
“If we look at this U.S. study as an example, and talk about one-fifth of your acres losing money, if you cut out that loss, that’s a huge potential return on margin,” says Dubois. “It’s an immediate turnaround in profitability. If you look at the biggest problem through that spatial lens, you may find that to improve those situations is actually quite simple and doesn’t require a bunch of fancy tools or anything else. It just requires your ability to see the problem.”
Boots on the ground still needed
Precision ag and the data it produces is valuable when it’s being used in the right place and it’s in the right hands; however, it won’t replace the need for ground-truthing through in-field scouting, soil sampling and other traditional, sound agronomic tools any time soon.
“People will put a tremendous amount of faith into imagery, but every time we look at a picture, it doesn’t matter whether you take it with your phone or a drone, it’s always history,” says Matt Fagnou, lead digital agronomist for Nutrien Ag Solutions. “Our machines cannot take the place of being in the fields because we can’t predict the future and we never know what next week or next year will bring us.”
“Boots on the ground are still very important because there are still a lot of nuances, and big data is going to help be more refined in our decisions and allow us to offer growers pricing models potentially that suit their risk tolerance and the production within their fields,” he says.
“There are all kinds of opportunities in how you approach agronomic recommendations and production decisions with all of this data and these tools, and there is going to be the right product, at the right time and the outcome of that will be measurable. But we’re always going to have boots in the field to help make those decisions because everyone’s going to have their own take on the data. In the end, the growers are going to have control of their data and be able to make those decisions that are best for their farms.”