Podcast: 03. Keaton Krueger - Forecasting Your Field’s Future with Crop Modeling
Updated: Jul 10
Would you change your management if you knew what your yield was predicted to be on the day you plant your crop? That is the question growers who use the Field Forecasting Tool (FFT) have to answer. On Precision Points, episode 2, I sit down with Keaton Krueger from Winfield United to discuss the background and potential of FFT.
Crop modeling has been around for a couple of years, but is still pretty new technology on the farm. It is a composite of plant physiology academic research and real-life variables such as fertility, planting date, and weather. Together in an equation, these things help growers understand what to expect out of their crop and how to most effectively manage it in-season.
Keaton breaks down the power of FFT in three steps.
The first step is that it is a forward-looking model. In traditional crop models, growers are expected to provide historical yield information and an estimated yield prediction, or yield goal for their current season. The model then plans around those numbers. In FFT however, with basic field parameters entered (think crop rotation, relative maturity, etc) the model actually generates a predicted yield number that sets the tone for management throughout the growing season. Current and future weather conditions including moisture, temperature, and solar radiation then impact that prediction, making the model dynamic throughout the season.
The second step is in-season calibration. One piece of data that drives the accuracy of FFT is the calibration on tissue tests. Keaton recommends early season samples to give the model realtime information about what is available in the plant. That, combined with the historical and future outlook information in FFT, gives you power to run different scenarios that show your estimated return of an application at any given time or rate.
“That’s really the most powerful farm-level insight; allowing us to figure out what the right date and rate is, because it's not the same every year on the same field, it varies quite a bit sometimes.”
The third step is often the one growers want to jump to first, and that is the yield prediction. FFT shows you what your estimated yield is, along with what your total production potential is for that field that year. Keaton doesn’t recommend marketing your crop off of this number as some error is expected. This number does help influence our decision-making though to ensure we are being good stewards of our resources.
Crop modeling is one of the most compelling emerging technologies for in season management. The Field Forecasting Tool is one tool on the market that you will want to take a look at if you are looking for clarity around in-season decision making. To hear our full interview, go to Precision Points.
Have you used FFT? Leave a review here.
Host: Morgan Seger
Guest: Keaton Krueger is a Digital Technology Manager with Land O’Lakes (WinField United)
Morgan Seger (00:22):
Hello, and welcome to Precision Points. I'm your host Morgan Seger. In each episode, we try to bring unbiased ag tech information and ideas. And on today's show, I am joined by Keaton Krueger, a digital technology manager with WinField United. Now, Keaton and I were on the same team when we got started back in our ag tech careers, and so we've had some unique opportunities to see tools get developed and rolled out. And one thing that I always appreciated about Keaton is not only his ability to understand and explain the tools that we were working with, but also the way he was able to understand how growers could actually implement these tools and impact their operations.
Morgan Seger (01:03):
Now, today we're going to be focusing on one of the newer projects he's been working on the Field Forecasting Tool. The Field Forecasting Tool is a dynamic crop model that can help you predict your yield from the very first day of the season, and then uses end-season data to calibrate that yield estimation all the way through the season. And really what that does is help you figure out if you are maximizing the potential and how to be a good steward of the nutrients you are using. He breaks down for us in three simple steps the way this tool can transform the way we make in-season management. Here's my interview with Keaton Kruger.
Morgan Seger (01:38):
All right. Welcome to Precision Points. Today on the show, I am with Keaton Krueger. Keaton, I talked about you a little bit in the intro, but would you mind just taking a couple of minutes to introduce yourself to our audience?
Keaton Krueger (01:52):
Sure. My name is Keaton Krueger, as Morgan said. I live in Central Iowa with my wife and kids, and I spend most of my time working for Land O'Lakes in our technology department, both on our eCommerce tools as well as our ag tech tool suite. Then I also farm a little bit with both my father and then some here with her father here right around the house that we have.
Morgan Seger (02:16):
Awesome. Yeah, Keaton and I started working together about nine years ago, and we worked in a way where we kind of got to develop and also roll out some ag tech tools. And over that time, we really got to watch, not only our tools kind of evolve, but the entire industry evolves.
Morgan Seger (02:33):
And on Precision Points, we try to keep our content aligned with the growing season. And so since we're going to be releasing this episode in June, we're going to be at that point in the season where growers have probably everything in the ground, side dressing done, and now trying to decide, whether it was planned or not, should we do any other in-season management? And to me, one of the most exciting, kind of emerging technologies is crop modeling. Could you give us a little bit of information about your crop model that you've been working with?
Keaton Krueger (03:05):
Totally. You set that up really well, Morgan, and I think you hit the high points of really what I want to talk about. The crop model that we have at WinField United and with Land O'Lakes is called the Field Forecasting Tool. This tool has been in the market in a small way for four or five years, but has been growing a lot over the last couple.
Keaton Krueger (03:25):
And I mean, primarily it is exactly what Morgan just said, it's a tool that helps better optimize in-season management. At its core, it's a crop model. There's a few of them in the market back when prices were a little better than they are and there was a lot of money flowing into ag tech. On the early side of our career, there was a lot more people in crop modeling and I think a lot of companies fell out because it's a very complex thing to do. But essentially what we're trying to do is we're trying to use all the literature available about how a corn or soybean or a wheat plant develops, and then connect that literature together to create a model that helps give us useful predictions. Modeling has been used a lot historically in academia, but it's never been produced in a way that allows a grower to consume it easily and make decisions on their farm.
Keaton Krueger (04:17):
What makes our model a little bit unique is it gives you three things that make it unique. One, it gives you the ability to adjust in-season. Our model's really the next evolution of our NutriSolutions tissue testing program. It allows you to take tissue samples in the field in-season. And as long as those samples are representative of the field, you can then connect to what your plants actually have. It's a forward-looking model, so you can take the information in-season and calibrate, which is something that is really powerful.
Keaton Krueger (04:46):
Because if you think of a traditional crop model that didn't have the ability to calibrate in-season, you would enter all of your information about the field prior to the season, things like what do I have planted, how much fertilizer did I use, when did I plant it, those types of things, and then you let the model go, then the model is going to base its recommendations on how the inputs that you applied were used throughout the season. But if that model is off a little bit at the beginning, that little bit, say it's 2%, gets bigger and bigger and bigger throughout the season.
Keaton Krueger (05:19):
Allowing us to come in and calibrate in-season is a really key thing. And I think that's really the most important thing to remember is using that to see what the corn plants actually have in them for nitrogen and potassium, allows us to better adjust to what's happening in-season. A couple of other things that I think are really important to think about with our crop model or any of them is how hybrid specific is it. We know that hybrids use nitrogen in different ways. Some use it more efficiently, some use it less efficiently. And I should probably even take a step back. I think most what people are doing with crop models today is trying to optimize nitrogen timing and rate on both corn and soy... Not really soybeans, but corn and wheat. I think it's really important to know how that plant response to nitrogen.
Keaton Krueger (06:08):
And the third thing, I think here that's really important to think about just as we set the stage for what this model does or what a model can do is how that model assesses your yield potential. A lot of models that have been in this space historically that are grower-facing, have you enter your yield potential and then it bases the potential off of that.
Keaton Krueger (06:32):
If I'm averaging 180 bushels of corn on this farm here, I would enter that and then that would be the baseline yield. Where our sense it's built in a mechanistic way, which I'm not going to get into that right now, but essentially it's built in a way that the model can run independently of any historical yield data. It actually is going to project out what your yield range would be. It allows you not only to manage in an optimal way to your historical production, but also to what may be the production would be above or below average.
Keaton Krueger (07:04):
That was a long way to coast into this, but those are a few of the key things that I think are important when you just think about how a crop model may be different, at least ours.
Morgan Seger (07:13):
Yeah. Let's just walk through those three things and dive in a little bit deeper. You said "adjust in season", is that taking into consideration the weather that's happening on your field right now?
Keaton Krueger (07:27):
Yeah. The way, and I think all crop models probably work this way, but they're all going to use some sort of modeled weather data or recorded weather data. We aren't weather experts, so actually we're purchasing a package of weather data that's modeling out the most important things to the model, which are high and low temperature, rainfall, relative humidity, and then solar radiation. Those are really the five things that are the most important to our model. If you think about the way a plant grows so you can tell why those are important. High and low temp is for GDD accumulation. Rainfall's obviously important, and then solar radiation has a lot of impact on how much biomass a plant can accumulate.
Keaton Krueger (08:11):
We saw a really interesting thing. It was the year 2019 or 2018. They kind of run together. But over a lot of the country, we were seeing depressed yields all season long, and we had a really pretty good growing season over a lot of that area. And come to find out at the end of the year, the yields that were depressed were actually real. We probably produced 10 or 15% less than what we expected in those areas. And what we attributed it to was we had a much lower solar radiation total throughout that season then what we typically would. We had the heat, we had the moisture, but we just didn't have the sunlight. It was really interesting because we were a little nervous through most of that season because we were predicting yields that were much lower... Not much lower, a little bit lower than what the crops look like and that made some people nervous.
Morgan Seger (08:57):
Yeah. I actually think I remember that because we were coming off of, I think... I can't remember what year it is either, but we were coming off of a year where we had a really poor planting season, but really exceptional yields the year before. And so then everything got planted well and our yields were predicted to be depressed, and I was like, "What is causing this?"
Keaton Krueger (09:17):
I don't know what it's like in Ohio, but it's late May right now and we've had overcast for 10 days here so I somewhat suspect that we're setting up that way a little bit right now here. Because we've had heat, we've had rain, but we haven't had any sunlight. The corn plants are growing super slow.
Morgan Seger (09:35):
It's been hit or miss here. We've had a couple of sunny days, but I haven't seen, obviously, what the model is saying for my fields.
Morgan Seger (09:46):
Okay, so the next thing you said was that this is like the next step to NutriSolutions tissue testing. For our audience, can you kind of explain that a little bit more?
Keaton Krueger (09:55):
Yeah. In case you're not familiar with NutriSolutions, that's a program that was in place long before I or Morgan was around this organization. And really it was a search for like the next step of understanding fertility in a plant. Prior to that, most people took soil samples and you could get a picture of what's in your soil, but you never could get a picture of what's in your plant. And sometimes you'd see that you'd have soil levels that were good, maybe more than good, and you wouldn't see that return in the yield.
Keaton Krueger (10:28):
They started this tissue testing program where they began to take systematic tissue tests across many different crops, as well as many different timings in each crop. And what they got is this really robust data set of hundreds of thousands of tissue tests to see, if I'm at V5, what's a corn plant typically have in it, at V8 it's be 10 and so on, all the way through reproductive.
Keaton Krueger (10:52):
And that's really useful, but sometimes as a farmer you could go out and take a V5 tissue sample or a V8 tissue sample, that would be more appropriate. V5's a touch too early. And you'd see that your nitrogen was deficient and your potassium was deficient. And you knew you put nitrogen or potassium out, but what you could never really answer is, is my corn plant deficient in nitrogen because the roots haven't gotten the last inch that it takes to get down to that nitrogen or is that nitrogen no longer even there and I can't touch it?
Keaton Krueger (11:23):
The tissue sample is just a snapshot in time, which is really powerful if you going to have that information. And once you have that information, you tend to be searching for more. And that's really what spawned the idea with Field Forecasting is to take that data and then use those tissue samples to calibrate the model to connect the dots.
Keaton Krueger (11:38):
You can now begin to, say I took a tissue sample at V6, that's currently at V8. I've applied this much nitrogen and the weather over the next two weeks is wetter and warmer or drier and cooler or the other way around, and I can actually run scenarios and determine if I were to apply 50 units of nitrogen at some point, would it be best to do it today? Would it be best to do it two weeks from now based on the weather. Or the inverse of, if I'll apply anywhere between 20 and 80 units of nitrogen, I mean what's the right rate?
Keaton Krueger (12:12):
You end up with this, I'm visualizing in my head, but this factorial of dates and rates to help you determine what the right timing is for your in-season application. And that's really the most powerful farm level insight is allowing us to figure out what the right date and rate is, because it's not the same every year on the same field. It varies quite a bit sometimes.
Morgan Seger (12:35):
How soon can you start using that? Can you make this application work for side dressing or is this going to be later in the season to have that calibration?
Keaton Krueger (12:43):
It depends what you need to find this side dressing. One of the bigger hurdles we have right now is you really can't get a representative tissue sample till after V6. You can run the model before that and put in the information you have, and the model is going to be as accurate, in my opinion, as any other on the market that's not calibrated in-season. It's going to give you a yield estimate. It's going to give you some recommendations. You can run the scenarios on rate and date at that point, but I always recommend people wait till they calibrate it to what the field actually has or what the corn in the field actually has, or the soybeans in the field or the wheat in the field actually has so that way you can be the most accurate.
Keaton Krueger (13:20):
Typically what I'd say is if you can wait to V6, let's wait a little bit later to do that initial side dress and be prepared with a rate. If the season gets away, we're going to do our plan. let's use the plan that we had initially first and we'll try to wait till we can get the tissue sample. And then if that doesn't work, we'll apply to the plan and then we can go calibrate again later.
Keaton Krueger (13:45):
You can use it somewhat for an early side dress. A lot of people also use it to, say I'm going to put on a little bit more of a free plant so I can wait to hold my side dress a little bit later, then I'll do that. And there's even a lot of people that do an early side dress and then they'll use the model to figure out if the crop has enough potential this year to come in and do a second pass of something in-season.
Keaton Krueger (14:06):
And we've seen things all across the board. Some markets we've seen that they've seen a response to pushing stuff later than what they've ever done. Sometimes all the way up until almost hassle. And we see some places where it doesn't always make sense to even do a side dress that we had planned and we can remove that from the plan for the season because there's just not enough potential to manage.
Morgan Seger (14:29):
Along with the tissue tests, then you talked about hybrid-specific response. How does that play into these decisions you're making in-season?
Keaton Krueger (14:38):
I think if you have a hybrid that's tested in the Answer Plot system that we have, you're going to have a response to nitrogen score more than likely, which helps you... It's basically a delta to help us determine is this a plant uses nitrogen more or less efficiently than the standard? If you have that hybrid and you have the model, it's going to have that baked into it. It has an adjustment for nitrogen-use efficiency, somewhat nitrogen-use efficiency, but the response to nitrogen score for the hybrid.
Keaton Krueger (15:15):
But even in that case, I think it's important to understand that if you have a hybrid that isn't one that's tested, they do respond differently. And sometimes you'll find that one year a side dress works and another year a side dress doesn't work. And it's hard to know why. And I think I see the same thing with fungicide... I think that's a better example. I've talked to a lot of farmers that say either fungicide doesn't pay or fungicide does pay or it's inconsistent. Well, I think a lot of times what's confounding that in the nitrogen and fungicide piece is the fact that hybrids respond differently. I'd say seek out as much information as you can to understand how a corn hybrid response to nitrogen.
Morgan Seger (15:59):
Now, does the Field Forecasting Tool have any disease modeling?
Keaton Krueger (16:03):
We're testing some disease modeling. I would say that it's a beta version. I don't know what we'll find. What we're trying to do is begin to, both in corn and soybeans, help growers assess is there a risk for this disease at this current point and when they should begin to think about managing. We'll see how it plays out in the market. The science is, and scientific work... The model was based on good science, but we'll never really know until we get out in the field and see what happens.
Morgan Seger (16:32):
Keaton Krueger (16:33):
Which is typically the way this thing's growing. That's the way Field Forecasting Tool started also. From a corn and soybean and wheat model perspective is we used the best science we had, we used the data that we had from our Answer Plot system, then we brought it into the market and began to understand where it needs optimized and where it can evolve.
Morgan Seger (16:50):
Got you. This last thing you talked about assessing yield potential and those yield predictions, I would say this is probably one of the things that as a grower is kind of a high point or at least something to fixate on. Can you tell us a little bit more about how we can actually use that information?
Keaton Krueger (17:11):
Yeah. This is useful in all of the crops that we model because in the same way as a farmer, right, the yield number is the number I fixate to. It's in the top right corner of the screen. It's the first thing I look at when I go to the model, and anybody that's ever seen the model, it's the first thing they look at. It's a bit... dangerous isn't the right word, but we debated a lot on if we keep the number in there or not. But what we understand is if we don't give you some way to quantify the model's ability to predict your yield historically, or at least your yield potential this season, it's hard to really understand if is that extra 20 units of nitrogen really worth it or not, because I think in bushels, right?
Keaton Krueger (17:53):
It is useful. And I would say, as you get closer to the end of the season, the yield number, it gets tighter and tighter and tighter. By the end of the year, the model is really, really, really close consistently on the national scale. This early in the season, there's a lot of season left, right? Crops are just coming out of the ground. There could be a 40 or 50 bushel yield swing based on what happens with the rest of the season. We're using the best long range forecast so we can have, but those are just long range forecast. And everybody knows that weather forecast have some error built into them, right, because it's hard to predict what's going to happen.
Keaton Krueger (18:30):
I think now I would never recommend somebody go sell their crop based on the yield potential. But as you're going through the season, if you're consistently seeing numbers that are above what your typical average is, you can begin to think about the fact that we may have an above average yield or a below average yield, and we see both of them every year. I mean, there's markets... It's pretty consistent what happens. The above average yield markets love the model until it's a little bit too high at the end, which usually it moves itself back down. And the below average markets are the ones where the people are like, "This model can't be right. It can't be that bad." And typically that may move up a little bit.
Keaton Krueger (19:10):
But there's a part of the country every year that produces uses more than it's supposed to and Field Forecasting doesn't predict it, but you can see that it's above average trending. There's a part of the country where we've managed into a good season, the corn or the soybean crop looks good and Field Forecasting predicts below average, and we ended up below average. Isn't it the nature of the beast?
Morgan Seger (19:30):
Yeah. Well, I think the one thing is, for us, if you're in a position where you're trying to help a grower make decisions, depending on who you're talking to... Like you talked about before, lots of times when we're putting our plans together, we say, "All right, here's your average yield. What's your yield goal for this year?" And depending on that grower's demeanor, 180 average could be a 200 bushel yield goal. It could be 180 bushel yield goal or a 250 bushel yield goal. And so it was really hard to actually figure out where you were tapping that field's potential out. I think this kind of helps them at least level set with where they're at and be more responsible with those resources.
Keaton Krueger (20:08):
Yeah. When I think about... You're exactly right, Morgan, and we don't advertise the yield error openly. We don't hide from it. I mean, it's somewhere between 10 and 20% every year when we do the year-end analysis and 10, 20% on a 200 bushel corn crop is not... I mean, that's 20 bushels, right? Maybe 40. That's the difference between going broke and farming next year.
Keaton Krueger (20:41):
It's easy to say, "Well, how can a model be useful when we have that much error in the model?" Well, that's the average error, so there's obviously people that are tighter and there's people that are farther out. One thing we do see consistently is the better you adjust grow stage and the better you put the parameters in that you can, the more accurate your model's going to be. Some of those ones that are a larger percentage off of the accuracy, those are the ones that people didn't manage as well from a model perspective.
Keaton Krueger (21:09):
But the other thing is, is it's easy to forget that the model only knows what it's modeling and what you input. It's modeling nitrogen, potassium, water, nitrogen stress, potassium stress, water stress. You've got a little bit of weather stress because you get the solar radiation, but it's assuming there's no weeds out there, it's assuming there's no pest, it's assuming there's no disease. It's assuming your phosphorus is appropriate.
Keaton Krueger (21:37):
As an agronomist beside the model, the big opportunity there is to take what the model shows you and then adjust up or down based on how the farm is managed. Those five things I listed could easily be 40 bushels, but the model has no idea that they're even there or not there.
Morgan Seger (21:54):
No, that makes a lot of sense. As people are listening to this, they might be trying to figure out if this is something that would fit for their operation. Are there any parameters for a grower to use this as far as equipment or certain acre size where you think it really makes the most sense?
Keaton Krueger (22:12):
Oh, it doesn't take much because we use it on our farm. We don't have super fancy equipment and we don't have that many acres. But I think the big thing is you have to have the way to access it through a WinField United aligned retailer and you probably need to have tissue samples taken. But more than likely if the retailer has the tool, they're going to be taking tissue samples. That's probably one of the bigger hurdles is just, you got to make sure. And then there's lots of WinField United aligned retailers out there, but it's going to come through that channel.
Keaton Krueger (22:43):
But I think that if you're not in a mindset of managing in-season with a model at some point, you're going to get a little bit of insight, but you're not going to get that much insight. You may get a little bit of yield insight. But the real power is when you start to use this to try to figure out how to optimize in-season fertility applications to make sure that from one perspective we're stewarding the nutrients we're putting out there well. Because on our home farm, 40 units side dress is what I plan on, and we've not applied a 40 unit side dress in a year. One year we applied 60 and one year we applied 30. Stewarding those well and also financially stewarding the inputs well.
Morgan Seger (23:25):
Sure. Yeah, that makes a lot of sense. If someone wanted to learn more or figure out where they could get their hands on the Field Forecasting Tool, where would you recommend they look first?
Keaton Krueger (23:40):
I'm certain you can, you can just Google it and find information from our site, and then also tons of other people and other retailers that have talked about what they've done with it. But I think the primary place you're going to have to go, you're going to have to go to the local WinField United aligned retailer and ask them about it. They're more than likely going to have some awareness or not, and if they don't, I'm sure they can come find more information.
Keaton Krueger (24:05):
Like I said, it's still a growing tool. I think that the typical cycle is as a grower wants has to try it on a field or two a year. And then for the first year to begin to understand is it accurate, is it useful, and go farther with the rest of the operation. It's an organic growth that you really don't know the value of until you experience it once on your own.
Morgan Seger (24:27):
Got you. I have one final question for you, unrelated to the Field Forecasting Tool. But of all of the things out there, I mean you've been in the precision ag, ag tech industry now. For what, 10 years? Is there any one technology [crosstalk 00:24:42] other than yours that you find the most compelling that growers maybe should be taking a look at or something you're really following?
Keaton Krueger (24:49):
Doesn't seem like 10 years.
Morgan Seger (24:52):
I might be off a year. Nine years?
Keaton Krueger (24:53):
I don't know. That's a good question. Not the years. I could probably calculate that in my own. I think that the technology thing is something that... I think it's three buckets pop into my mind. I'll go through them real quick. I don't know the scope of the podcast, so some of these may be outside the scope and you can ignore them or edit them out if you want.
Keaton Krueger (25:14):
But I think that from a core ag technology space, this doesn't impact me probably on my operation or maybe a farmer in Ohio a lot, but I think the core opportunity in ag technology right now that I think a lot about is... It's May 2020, it's a post COVID-19 world. I think this may be the time where some of these smaller, automated-type machinery options are going to have their opportunity to expand because accessing labor on a lot of these higher value crops that have to be handpicked is much more difficult than it was. And when that labor was there, even though it's not easy to get, it was available and there was a structure that allowed that labor to occur and come in. I think a lot of these tools were too expensive to start.
Keaton Krueger (26:08):
When I think about the dairy industry, and the fruit and vegetable and the [inaudible 00:26:13] industry. Now, it's not just a math problem, like is it cheaper to have [inaudible 00:26:19] I can't have this, so I may actually have to see that. I actually think from a pure ag tech perspective, that has a really good opportunity to grow. That's one.
Keaton Krueger (26:34):
From a plant technology perspective, there's been a lot of people thinking about biological stuff a lot, but I think there's something there. I don't know what it looks like. There's a few products that are tested here in Ames, which is just a few minutes away at Iowa State. I think that we're going to figure out some biological approaches to some of our crop inputs that we've been searching for, for a long time.
Keaton Krueger (26:58):
And then I think the third one is post-COVID related at all, but I think it's the social channels. It's the technology we've had forever, right? It's in our phones. But there's a lot of farmers out there right now that are saying the world has changed. Consumers have woken up for the first time in a while about where their food comes from. It's mostly, in fact, in the meat industry, I think right now, but maybe some other ones also.
Keaton Krueger (27:27):
But I think there's a lot of opportunities for farmers to build their own brand and connect directly with our customers in a way that there hasn't been. Not ever, I'm certain at some point in history you knew the farmer you bought your food from, but it hasn't been in a while. And I'm sure that as we move past this and things, the food concerns go down a little bit. There will be some consumers that don't consider you to be as concerned as they are. But I do think that there's an opportunity for folks that want to build a brand and try to go direct to consumer to do that right now in a way that there hasn't been, or at least hasn't been as easy over the last, I don't know, up until now, I'll put it that way. Those are three different answers.
Morgan Seger (28:12):
Yeah, yeah. No, I could totally see it. That's actually a really interesting and really, really timely. I know since I left my corporate job and I've been a stay-at-home mom, I've definitely been engaging more with the people who are trying to do that type of stuff on social. It's kind of interesting to watch how it'll evolved, especially as, like you were saying, the meat industry and things have kind of been turned upside down.
Morgan Seger (28:37):
And I think where we're at today with it being May is just kind of the start. As a farmer ourselves, we don't really know how all this is going to impact us yet. We know there might be something, but until it starts to kind of reveal, we're kind of just trying to stay the course and do what we can for now. It'll be interesting to see.
Morgan Seger (28:58):
Awesome. Well, thank you so much for taking the time to be on Precision Points. If someone wanted to reach out to you, any best places to find you?
Keaton Krueger (29:08):
I think the easiest way to get a hold of me is probably seek me out on Twitter. I forgot the handle. I think it's @keaton.krueger. Go to Morgan's you'll see it, or she'll probably include it when she posts it.
Morgan Seger (29:22):
Sure. I'll go ahead and I'll put it in the show notes. I'll look it up right now.
Keaton Krueger (29:25):
Yeah, that would be the best place to connect with me. Put it in the show notes, that's the right thing. I don't get asked for it that often. I just-
Morgan Seger (29:32):
Keaton Krueger (29:32):
@keatonkrueger. Pretty simple.
Morgan Seger (29:34):
Keaton Krueger (29:36):
That's probably the best place to find me on a personal level. And I would say as far as the Field Forecasting Tool perspective, reach out to the local retailer, find your local agronomist there. They're going to know better how to use it locally. And then, we're a big organization, but it's pretty small, and especially in the ag tech space. There's a good chance if they have questions, it'll bubble right up to me anyway.
Keaton Krueger (30:00):
Anyway, I enjoyed the conversation. Thanks for the opportunity to talk about this product and also just to catch up, Morgan.
Morgan Seger (30:08):
Yeah. Yep, it was fun. Enjoy the rest of your day.
Keaton Krueger (30:11):
Morgan Seger (30:12):
I hope you enjoyed this episode of Precision Points. Like Keaton said, the Field Forecasting Tool can be scaled for growers of any acres. If you are interested, make sure you reach out to your local ag retail and ask about the Field Forecasting Tool.
Morgan Seger (30:25):
Thanks for tuning into today's episode. To hear more podcasts like this, please rate, review and subscribe to precision points. Visit precisionagreviews.com for show notes from this episode, and read expert advice on our blog, you can share your experiences with precision ag products that you have used and check out our network of farmer reviews. Let's grow together.
Host: Morgan Seger
Morgan Seger spent ten years working in ag retail, specifically in ag tech. She lives and farms in western Ohio, where she has four children with her husband Ben. Morgan has her own blog called Heart and Soil where she talks about her experience farming, gardening, and raising her family.
Guest: Keaton Krueger is a Digital Technology Manager with Land O’Lakes
Keaton Krueger is a Digital Technology Manager at Land O’Lakes as well as a beginning farmer on two multi-generational family farms in Iowa. During his career with Land O’Lakes (Winfield United) he has worked at all levels of the Ag Tech value chain. First, working at the ground level with farmers and retail agronomists helping to utilize ag technology and site specific management to make better data driven agronomic and economic decisions. More recently, he has worked more closely with the software development teams and the digital strategy group within the organization to help drive and evolve ag tech product strategy. He has worked closely on the development team of the R7 Field Forecasting tool since the very beginning of the concept in 2014. Keaton lives in rural central Iowa with his family on his wife’s family farm where they recently began a farming operation of their own, and also farms with his family in southeastern Iowa.