DTN/PF: Tell us about the 2021 update of AFS Connect.
Wesley: Our vehicles today, starting with the AFS Connect Magnums, moving to the AFS Connect Steigers and (Axial-Flow) Combines; they all come from the factories as connected vehicles for five years. The information coming from the vehicle is visualized (by AFS Connect). One of the big features is not what is going on in my cab, but what is going on with other people working for you, the guy doing the tillage or the planting. It gives you a bird’s eye view, a level of observation where you don’t have to get on the radio and ask for information. There are alerts. (Farmers) can set up parameters for planting, for example. If the machine is going slower than 3 1/2 miles per hour or faster than 7 mph for more than 10 seconds on either side of those limits, the (farm manager) gets a text. This is a way to stop having to be out with the operators or in the field 24-7.
DTN/PF: In terms of field awareness, what are producers asking for from manufacturers such as Case?
Wesley: It is the ability to be in touch with machines. The ability to have members of a farming operation be where you want to be, or where they have to be. That doesn’t always have to be for business. Maybe it’s baseball practice or a football game on a Friday night. They have everything in the palm of their hand and they have the ability to reach out (to their operators) without having to leave their seat. That’s a big part of our message ‘Farm Your Way.’ This ability to confirm what’s going on out there. Or, I can select an application map and share it with my agronomist or my dad down in Florida and show them what we’ve started and what we’ve finished. We sprayed this field. Here’s the acres we covered, the gallons we applied. Here’s the exact product and tank mix we have out there. And, by the way, here’s the weather (summary) because we can track wind speed and humidity.
DTNPF: So these days the operator, the farm operation, is collecting a lot of data, tons of it. How does the manager manage all that?
Wesley: All the data can be exported to the Cloud. The manager can go back to particular calendar dates. He can see how many hours it took to put a crop in, the weather or how long it took to move from point A to point B. We can do a much, much better job of making decisions. I wake up in the morning and I’ve got a list of insect and weed pressures that are in my latest crop report and I can check on my Growing Degree Days to determine the stage of my crop, and know if I should be concerned that action is needed for any of my fields. This timely action shows up as yield in the tank versus missing my opportunity for application and rescuing my crop. I can get that extra 12%, 15% 30% yield just by being timely. Knowing I can identify immediate crop needs allows me to use the data for better marketing, to get a higher percentage of the crop marketed with comfort.
DTNPF: Case IH plans to introduce access to NDVI satellite imagery for its customers. Normalized Difference Vegetation Index measures the difference between visible and near-infrared light reflectance from vegetation to give users an understanding of photosynthetic vigor. You were an agronomist. Tell me about the value of this technology?
Wesley: It is something that’s on its way, probably next six months or so. (Case IH) is already turning it on for some Beta customers. NDVI allows you to act quickly. Imagine when that image hits the agronomist’s computer. He can look at it and determine that (his customer) needs to get out into the field with an application. Because we have file transfer built into these machines he could send (the work product) directly to the machine.
DTNPF: Beyond NDVI what else is coming from Case IH?
Wesley: You saw our splash back in 2016 with our autonomous vehicle. What we learned from that project we are releasing right now out into the marketplace. For example, AFS AccuTurn. AccuTurn was a necessary feature we needed to figure out for that autonomous vehicle so that vehicle can (steer) autonomously. We are incorporating (other autonomous functions into our manned machines). For example, look at fuel use out in a field. Look at terrain. You can see what happens when a tractor is pulling a heavy load up a hill. It is using more fuel. When gravity is taking it downhill, you use less fuel. So, you see this pattern repeat. When I see the steep part of the field and I know I will use more fuel to go up that slope, why can’t I come up with a traffic pattern where I’m going up shallow areas and on the more steep areas I’m going down? You could start to build this logic into the machines. You are going to start to see the machine and the data we are collecting work together (in real time).
For information: www.caseih.com
Dan Miller can be reached at firstname.lastname@example.org
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