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Ag Geek Speak
GK Technology Inc Team Members, Jodi Boe and Sarah Lovas talk about precision agriculture, agriculture mapping, agronomy and drainage.
Ag Geek Speak
22. The Man Behind the Curtain: Travis Yeik pt. 1
Elevate your understanding of modern agriculture with Travis Yeik, a trailblazer in precision agriculture technology. From his ranching roots in southeastern Wyoming to his role as software developer at GK Technology, Travis' journey is a testament to creativity and hard work. Learn how his agricultural background has shaped his success in programming, blending cutting-edge technology with real-world farming needs.
Explore the fascinating world of remote sensing and its innovative applications in farming and beyond. Travis shares insights on identifying and monitoring species like sagebrush and Phragmites, leveraging the unique wavelength signatures of different vegetation. Dive into the history of remote sensing, the importance of NDVI, and how these technologies unlock critical insights during the growing season to evaluate crop maturity and health.
Helpful formulas:
Normalized Difference Vegetation Index (NDVI)
NDVI = (NIR - RED) / (NIR + RED)
Green NDVI (GNDVI) = (NIR - GREEN) / (NIR + GREEN)
GK Technology, Inc. https://gktechinc.com/
And now it's time for a Geek Speak with GK Technology's, Sarah and Jodi friends and I can't wait to get in the fields again. No, I can't wait to get in the fields again. Welcome back to Ag Geek Speak. We have another amazing guest hailing from the home office of GK Technology, remotely located all over the United States, and today the GK Technology man behind the curtain, Travis Yeik, is joining us. He's a programmer with us here at GK Technology. Honestly, he does a lot of things and I don't think people really know him well at all, so very excited to have you on today. Thank you very much, Travis, for joining us.
Travis Yeik:I am excited to be here and excited to share some of the background that absolutely, as you say, no one sees. So maybe we can shed some light on that and let people know about the programs and technology behind everything that they use for precision ag.
Jodi:Absolutely. Hopefully we can pull back that curtain a little bit today and shed some light. We mentioned that you're located remotely. Where are you at right now and where is that in relation to where you grew up?
Travis Yeik:I am in Sheridan, Wyoming, and, let's see, we got a little bit of snow on the mountains here last weekend, so everything's super green and great. I am about four and a half hours or so from where I grew up, which is in southeastern Wyoming, on a ranch outside of Veteran, Wyoming with about a population of seven people. So I'm remote, yep.
Jodi:Fantastic. Okay, and you mentioned you came from a ranch background, so you have an agriculture background. How did you go from that ag background to becoming what you are now a programmer extraordinaire?
Travis Yeik:Yeah, I think that's really important because you don't see many people who grew up on the ag and the background there to go into becoming the nerds that do all the development behind everything.
Sarah:It's so true, right? I mean, you don't think about being out there just doing like the day-to-day monotonous things and then all of a sudden you end up becoming this huge geek, this huge nerd, developing new products all the time.
Travis Yeik:Yeah. So I want to step back. I want to go into why I chose the career, I guess, and the path that I did, and how that relates to the bigger picture of Precision Ag. Just to put it into perspective. You know, I think Precision Ag are optimizing our returns on some of the inputs Ag Just to put it into perspective. I think Precision Ag are optimizing our returns on some of the inputs that we have to be able to preserve our resources. And as a developer, that means that I have the responsibility to have the means and the methods to make this practical to everyday people such as our farmers and our consultants and whatnot. That's where it started and I think Precision Ag started. Everybody thinks of Precision Ag. They think of auto steer. You know that's the basic. Where it kind of started even was trying to reduce overlap when they were applying chemicals and save money that way. You know that's what I hope. I think more auto steer was probably developed from a hired man who falls asleep at the wheel.
Sarah:But you're right, Travis, everybody loves auto steer If for no other reason than just not having to actually physically drive.
Travis Yeik:It's very practical and everybody needs it now in this day of age, but I don't know if we ever think about where it comes from in the background. There had to have been some guy behind it that developed it, put it all together. So we talked to Darin Johnson, the owner of GK Technology, several weeks ago, and kind of have the same background as him, where we had to develop something that we needed to utilize because it wasn't out there. That's how it all got started.
Sarah:You're right, though, Travis. It takes somebody to develop those technologies like auto steer. I think at this point in time in agriculture it's just really easy to take that for granted. You get in the tractor cab and it just it happens, the auto steer is there, the auto guidance is there, the section control is there, and we just take it for granted. But somebody had to be in the background with that First of all, dreaming up crazy ideas like hey, let's not actually drive the tractor. Can you imagine how nutso that must have sounded the first time around? It is important for developers to have that imagination so that we can think outside the box and dream bigger things. From that standpoint, it's super interesting the work that you do at GK.
Jodi:Technology. The one thing I was thinking as we discussed your background too is like so you are a developer for GK Technology. What exactly does that mean? Like at the end of the day, what does that mean for you in terms of what you do on a daily basis? And like where do you start with what you're working on and where do you end?
Travis Yeik:It always starts with a cup of coffee, right, and it always ends with a beer, and it always ends with a beer. That's where it has to go. Yeah, that's a good question. It usually is just a crunch from one day to the next, just like everybody else. But it's great because it's broken down into projects where it is something different. Every day it's a different project, every day it's a different problem. The good thing about it is that there is a solution at the end. Which makes it great is that you get to sit down and come and look back at what you did for the day and say, hey, I accomplished this. It'll help, whether it's the program or the people who use it. That's the great thing about it.
Sarah:That's pretty fun and let's talk a little bit more about some of the things and some of the projects that you're doing at GK Technology. But I want to take a step further back. You know you mentioned that you were raised on a ranch. Talk to us about where did you go to school, what did you study and what got you into computer programming along the way.
Travis Yeik:Yeah, so growing up on the ranch, you know, we raised our own cattle there and we did dairy and we had some beef cows. We didn't milk, we just bred them and then sold them when they're bred. We didn't have precision ag so-called on the farm where we did corn and alfalfa. I don't know about you guys. Did you guys grow up in precision ag? I mean?
Jodi:this is a funny story. So, like I now farm with my dad and brother in Western North Dakota. We've used light bar maybe since like 2003, which has been fantastic. That is a godsend just having a light bar to tell you whether or not you're on your AB line to drive and steer straight. But the second year that my dad, brother and I were farming together which is the year 2022, we had bought an auto steer system an EZ Steer from Trimble to put in our planting tractor. No offense to my dad, not to throw him under the bus, but he didn't really think about it being economical for us to use that. But after the second pass he made with it, he texted my brother and I and said "man, this thing is awesome, why didn't we do this years ago? So we don't use much of it, but we do use now and we're continuing to grow that every single year with investments, but from my experience growing up on the farm, precision agriculture is pretty new.
Sarah:I graduated from college in 2004 and I think GK Technology was incorporated in 2006. I can remember being in a tractor and it had the John Deere Brown box in it and that was great. But a lot of this stuff was pretty new and ironically I would say that my number one teacher in precision agriculture was Kelly Sharpe. So really learning how to map and all of that started for me probably around 2006. And it was GK that really started teaching me how to do things. I didn't know what a shapefile was. I didn't know why you needed a boundary, Just to let you know where I started. Call me the old fart in the conversation, but there it is.
Travis Yeik:We are all in the same shoes. Yeah, we use it for our beef. You know, for example, there is a spread between your select and your choice carcass weights, and usually it can be, you know, 10 to $20 or whatnot, and so we would ultrasound each and every one of our steers before we sent them off to the market, so that we knew the marbling that was in there. And if they weren't up to choice yet, then we could leave them in the feedlot for a little bit longer. And I think that's even right there. You know, that's precision ag in the beef industry. I guess I started in FFA. I was. I had a project. I decided that I wanted to map out the fields of our farm, just kind of digitize where everything is and how things and keep records, I guess, throughout the years, of how we were doing stuff. And at that time there was no software for doing that so, and I was in high school, so I did this all in Microsoft Paint, you know, back in 2004.
Travis Yeik:That's amazing, that was my first actual precision ag project that I probably had.
Sarah:So you? How did you? You made a map out of your fields in paint.
Travis Yeik:Yes.
Sarah:Were you able to get them geo-referenced eventually?
Travis Yeik:At that time in high school I didn't have access to, you know, to imagery. I might've overlaid it onto a DRG map. It was more for record keeping and so I had all the numbers and stuff there, but it wasn't probably accurate with the geo reference. That's so cool.
Jodi:You know that's really interesting, such a great idea, because I think about how we keep records on our farm, which, again, I know it's 2024 and we probably don't do the best job of it. But I know it's so much easier for us to sit it down with a map, like a printed out map of the area, and just write on it what we did, and it's so much more impactful having that map next to the action we took versus just having it in a list or even like a spreadsheet. I don't know why, but having that visual it helps us a lot. That's so smart that before having those digital maps you would have it in paint, right? You have that visual record of the map field that you could then reference or keep actions and keep records of things too.
Travis Yeik:I'm sure my FFA teacher thought I was nuts because it was something new at that time and I was like, hey, we need this.
Sarah:Yeah, you crazy kid who's ever going to want to have a map of their field.
Travis Yeik:Yeah, so after that I went to the University of Wyoming, which is Wyoming's only four-year university, in Laramie. I went into GIS, which is Geographic Information Science. That was really new at this time. People thought, maybe people thought that everything in the world is already mapped out. Why do we need more maps? And GIS isn't just about creating maps, it's about modeling the world that we have, putting that in maps, so whether it's your UPS driver and going around to find the best routes or, as what we do, creating models of agriculture in our fields. That way In the university there at Wyoming I got introduced to a guy who did remote sensing guy who did remote sensing and that's, I guess, when my career really took off and I gained.
Travis Yeik:My interest was in the remote sensing aspect of it. And if you don't know, remote sensing is looking at imagery in different band waves of lights and understanding how that relates to our real world, whether it's vegetation or soils or any geographic aspect of what we look at. And so with that project we ran around and we mapped out sagebrush in Wyoming. And then after that I got hooked up with another guy there at the university that was doing starting with remote sensing and agriculture. That was, I think my first project with Precision Ag was looking at these pivots in Worland, wyoming and, without ever going to the field, using the different wavelengths and the vegetation indices to map out what the production and dew zones of those fields clear. Back in I guess that would have been 2008 or so.
Sarah:In that irrigation situation you said you were mapping out different productivity areas of the irrigated field. Did it have anything to do with irrigation scheduling or how did that work?
Travis Yeik:It was strictly zone management and going back through using Landsat, we looked at the different dates and the different years and to go back and say, hey, these are the zones in that field. Do micromanaging for the different zones and parcels in that field?
Jodi:Was there an interest in doing that on irrigated land? First because there could be a potential of higher ROI because there was the rainfall there. Why was the target under the irrigation fields in the first place?
Travis Yeik:So that's a good question and it probably plays into the next part of my story, which is that, going from Wyoming to Nebraska, everything in Wyoming is irrigated is why and that's the major reason I don't know why we're farming in Wyoming, but yes, that's a simple answer and I like that a lot.
Jodi:And can I ask you about that sagebrush remote sensing? Does sagebrush like the species of plant itself? Does it have a specific wavelength or like color reflectance that makes it easy to identify what's considered sagebrush or not?
Travis Yeik:Yeah, and there's like four or five different types of sagebrush here in Wyoming. We have Wyoming Ansis and Black Sage and Mountain Sage, and then there's some other different types Silver Sage, and so, yeah, each of these different types of sagebrush has different wavelengths and we used a model to go through and we would say this in this area we did it by hectare. This area was this density of this type of sagebrush or a mix of these types of sagebrushes, and the goal was to look at the sage-grouse which was becoming an endangered species at that time and to go through. But there's probably specific signatures of like greenness for a soybean field versus a corn plant that just looking at like the difference in how those two crops reflect light.
Jodi:You could figure out what crop it is.
Travis Yeik:The profile or whatnot of the phenology, even of the plant and how it changes, but, yeah, the spectrum of light visible in the infrared and the wavelengths. After college I went to and got a graduate degree and I was looking around for I knew I wanted to go into agriculture, remote sensing, and I was looking around at the different colleges to get a graduate degree. There was two colleges, Purdue or the University of Nebraska. They were specialized in agriculture, remote sensing, and so I went to Lincoln, Nebraska.
Travis Yeik:The advisor that I had there was the guy who pretty much started, one of the first guys who started remote sensing in agriculture. I remember him telling us a story of NASA came to them with a grant to say, hey, we have this Landsat program and it makes images and what can you do with it? And I remember they sent him the data and he had just a big sheet of I think it was at that time probably eight bit data of Lansat, so numbers one through two, three, four, five, six, seven, eight was each pixel and they had to go through and kind of just circle areas and say, hey, this is forest or this is agriculture areas, and that was he made it so that NASA saw the worth the use in satellite imagery for agriculture.
Sarah:And that was your major professor that did that. Yeah, yeah, that's huge, that's amazing. And so you worked with him doing remote sensing and working with, like, different bands of light.
Travis Yeik:Yeah, and so another professor that we had there at Nebraska his name was Anatoly Gittleson and he is the guy who created the green NDVI. He was from Israel and he went into the quantitative understanding of how and why light reflects and interacts with vegetation, which was super interesting, and learning how, why at that red edge right between the red reflectance and the near-infrared reflectance, why it shifts to a different wavelength as that vegetation grows, and how that relates with the chlorophyll within the plants.
Sarah:So essentially, if that's the case at the red edge, can we sense differences in like the crop maturity If you could do enough research with a particular plant, can you see how like that crop is growing? And mat maturity If you could do enough research with a particular plant, can you see how like that crop is growing and maturing? Can you actually see the differences?
Travis Yeik:Yeah, for sure. And then the health of the crop, and I think that's why a lot of times people use NDVI and they use NDVI throughout the entire life of the crop, which, from a remote spencing aspect, is good for certain times of the year but not for the entire growing season.
Jodi:Can you go into more depth about like what is NDVI, what is green NDVI, what is red NDVI, and like where are some good uses for each of those?
Travis Yeik:I think that one of the very first indices that was ever used for remote sensing in agriculture, or even just remote sensing of vegetation in general, is just the simple red index, which is just red over near infrared. From there then it expanded a little bit and a guy named Tucker he developed NDVI. It is a normalized difference vegetation index which means that if, given that the red and the near infrared, if it's a really sunny day or it's a cloudy day, if you take out some of the differences, that it's normalized in that way. And so what happens? If you look at vegetation and why is it green?
Travis Yeik:Well, it's because it reflects high in the green and if we were to see in the near infrared vegetation would be near infrared color if they had a color, because it reflects a lot in the near infrared, up to 50, 60%, and so it absorbs all the lights in the blue infrared which is being reflected and said, as that plant ages and as it starts to senesce, that red is what most changes in the plant because it goes from being let's see it's hard to describe it without showing papers or graphing, to show it over with words here but as the plant grows, the red reflectance changes from being soil which is kind of brown and high in red, and so as the plant starts to grow, then that red slowly starts to decrease and so the amount of absorption of red is really high.
Travis Yeik:In the amount of reflectance in that red then is about 2% and so it's really low. As the plant starts to age and sness, or to stress, even, then that red goes up, and so then that difference between that red and that near-infrared, we can correlate that with how well the plant is doing.
Jodi:Wow, okay. So if I'm thinking about this, right, if I'm somebody that say is looking at NDVI? When I say NDVI, what is that assumed to be? Is that usually red NDVI?
Travis Yeik:That is. Yeah, that's the red, otherwise they'll specify that as green NDVI.
Jodi:Okay, that is really good to know. And so like thinking about that, if a plant gets more stressed, it reflects more red NDVI. So, like, if I'm going weekly and taking a look at red NDVI values for a crop throughout the growing season, if I've got some spot that's getting drowned out, like, say, in July, because of a rainstorm, I can tell that where those wet spots are, because they would have a higher red NDVI value. You know, after the rainstorm, where it's getting puddled, where it's more stressed versus, like, the areas around it, am I thinking about?
Travis Yeik:that right, kind of just the opposite, but a lower NDVI yeah.
Jodi:This wasn't on the list of like areas to get into the weeds on, but we all use these numbers but I don't think we think enough about how they actually work or like how they actually mean right. I always look at different resources to like remind myself how to use the number instead of just like knowing and understanding, and I think people feel more comfortable with these values when they understand how they work.
Sarah:So we talked about what NDVI is and you said that your major professor invented green NDVI. So what is green NDVI and where do you think it has its strengths?
Travis Yeik:So when you look at vegetation as it increases in density, that it is kind of logarithmic in that as vegetation increases about 60% of vegetation fraction or the amount of coverage then you start to get these leaves underneath of the canopy that start stacking up against one each another and as that happens the red is already being reflected only at like two or 3% anyhow. So you're not going to see any change in red reflectance hardly. But what you will see is that things become darker green, and so at that point is when green NDVI becomes important, because you see more change in the green than you do the red.
Jodi:Because you're like the thicker canopy would be absorbing more of the green light than, say, an area that has a less thick green canopy. So even though, like a really thick or like a soybean field for instance, it might already only be reflecting like two percent red, so you're not going to see much changes of it. But what really starts to change is how much it picks up and absorbs the green wavelengths. So we can use the green ndvi then to measure differences in like canopy.
Travis Yeik:Thickness. Yeah, exactly you got it, nailed it, yep do we use this for white mold mapping?
Sarah:yeah, would we use this for, like really super thick green dense canopies? Is this the place, the best place, for us to be using?
Travis Yeik:Yeah, so and that's kind of I think what a lot of the research has shown is that past 60% of vegetation, when you can't see any more soil, that's kind of where the greening and DVI. So it's especially important, like when you get to corn, like right before it tassels, and it relates to how much yield you're going to get. That the green NDVI is super important to show how the vegetation, or the health of that vegetation is changing you know, once it's fully developed.
Sarah:I think when we take a look in the software we see opportunities for downloading NDVI and green NDVI and I think sometimes our customers really have some big questions about where using each one of those products fits in better, especially into making zones. So those are some really good ideas for how we can think about those things differently and quite frankly, from somebody who's actually studied in the remote sensing area quite a bit, who knew that our computer programmer actually is a remote sensing geek.
Jodi:And on that same subject like what did you focus on when you were a remote sensing graduate student at UNL?
Travis Yeik:Yeah, my thesis was actually about a weed called Phragmites australis. If you know, it's one of the invasive wetland weeds which was super interesting learning it and I didn't add it to my thesis. But it actually does shift in that red edge in that chlorophyll and at some point it starts producing chlorophyll B instead of chlorophyll A and you can see that in that reflectance. One of the really cool things in Nebraska is that they had their own plane for doing hyperspectral imagery. And what hyperspectral imagery is? That it splits in the wavelengths into one or two nanometer differences, and so you might have 900 or 1,000 different wavelengths instead of our typical red, green, blue. It splits it up and so you can see how each wavelength inside of that changes, which is neat to be able to understand quantitatively how the different vegetation reflects in each of those wavelengths.
Sarah:So this might be a bit of a loaded question, but you were mentioning that in the weed that you studied, chlorophyll A and chlorophyll B kind of handled the red edge differently, or you could kind of tell that you're getting later in the season because the plant would use chlorophyll A and chlorophyll B at different times, right?
Sarah:Or move to the production of each one. We could see that in the light. And then we're talking about multispectral images and how that might play into weed ID. So I have long thought that at some point in time and this is coming from somebody who's crop scouted and the number one thing we need to do is positively identify those weeds, and we need to do so when they're very young. But do you ever think that there'll be a way that we'll be able to harness multispectral imaging and these different concepts of, like different amounts of chlorophyll A and B and different nuances within weeds and how weeds will reflect light, so that we can actually just run some light across there and then be able to identify the weeds?
Travis Yeik:Boy, that is a loaded question.
Sarah:Isn't it good?
Travis Yeik:And I think there's a lot of research into that and I don't know. That is one of the things that frustrated me about the university is that a lot of research goes into understanding how remote sensing works and wavelengths and doing research projects, but it never actually gets out to the real world, to production, to how businesses actually use it. It stays in the university To say that we're actually going to get to the point where we can do that. I don't know.
Sarah:Is it a bridge between actually getting that academia theoretical concepts actually applied into the real life, then, or is it just that it's that intense of research that it's complicated to get from point A to point B?
Travis Yeik:Yeah, I think it is just complicated in the way of the nature things, or that you might study what happens in North Dakota for soybeans might not apply to everywhere else. Yeah, just like anything else in farming, there's so many variables involved To make a broad spectrum analogy that will happen for everything. That's tough to do.
Sarah:And it is expensive research to conduct if you can't get it applied across a broad acreage. So that's an interesting thing to think about. I knew this was going to be a fun and in-depth conversation and so far this is not disappointed.
Jodi:I am so excited because I'm a weed scientist by training, so I didn't know you worked on a weed for your master's right.
Travis Yeik:Yes, or was?
Jodi:it that is so freaking cool and like okay, the chlorophyll A versus chlorophyll B doesn't one absorb like a different. It's about light absorption, right? Or like what difference between the two types of chlorophyll? Is there any understanding of why Phragmites does?
Travis Yeik:that I couldn't tell you because I didn't add it to my thesis and so okay, yeah, you mentioned that. Yeah, really. Maybe just you know hypothesis that this is what's going on.
Sarah:Wow, so that's pretty fun. So we've gotten so far, that we've gotten to grad school, and that's how long the conversation has gone. So that's pretty fun. Let's go from there. So you get done with your master's degree.
Travis Yeik:Yeah, so out of graduate school I lived in Omaha for a bit and my first job was with Valley Irrigation in Valley, Nebraska, and I was hired as their variable rate irrigation agronomist, which is good because it worked in with my background, you know, with looking at so I have miners and soils and they needed someone to use the remote sensing skills that I had to determine how much water needed put into each specific part of the field for use with their variable rate irrigation. So it went back to kind of what I did is getting out of field without ever going out to it and saying, hey, this is how much water is needed here, which is extremely tough to do, and they did not have a program to be able to do that.
Travis Yeik:So that's kind of where I picked up my coding skills. I needed to create some method, some program for me to be able to determine how to apply the correct amount of irrigation water to these fields.
Sarah:So wait a second. All of this time you're in school, you're working on all of this stuff and you hadn't taken had you taken a lot of computer programming courses at all.
Travis Yeik:I had taken one yeah.
Sarah:So you really are like Darin Johnson in the fact that you're pretty much a self-taught computer coder then as well.
Travis Yeik:And that's what it is. It's like you have a use or you have a need for something and there's no one out there that is going to create that program for you to be able to do that, and so you yeah, you got to make ends meet and do it.
Sarah:That is just amazing. I had no idea. I honestly thought that somewhere along the line you actually had formal training in computer coding. That is super interesting that all the powerful tools that we've got are basically created out of a couple guys' brains that are self-taught computer coders.
Jodi:That is no dig, by the way, because what they build is amazing. And I think too the folks that are coding and putting together the pieces of the software that you use to make decisions on your farms. They're basically agronomists by training or farmers that understand the practical side of it so that when you press the buttons together in ADMS to make your maps they know that you want to do something practical. They understand my whole point here. My long little side here is that Darin and Travis are a very special breed of computer programmer and I think that has helped them so much to create amazing software for agriculturalists across.
Sarah:North America. Quite frankly, from a humble standpoint, it is the most powerful software on the market today. I mean, we really do allow our software does allow people to actually do stuff with data, agricultural data. Sorry, that was my humble interpretation of having the most powerful software on the market today.
Travis Yeik:Thank, you, Travis. Sorry, that was my humble interpretation of having the most powerful software on the market today. Thank you, Travis, Thank you.
Sarah:Darin, so that's where you learned how to computer code is when you're at Valley Irrigation.
Travis Yeik:That's right. That's right, yep. And so I created a GIS program for them and I was trying to actually create an easy button for me that I could just input satellite images, maybe some soils data, and get water holding capacities and put in the different root depths of the different crops and just make a script that I could put in and just push it and I could sit back at my desk and say, yep, there we go, done. And I didn't quite make it that far. I was with Valley for a year, my wife and I. We wanted to get back closer to family, and so we moved back to Wyoming or back to I guess. We moved to Montana, we moved to Bozeman.
Travis Yeik:I couldn't find a job there for a couple of weeks. I really wanted something in remote sensing and research because I liked that aspect of it. A guy that I was working with at Valley, Jeff Branch he's up in Canada. He told me about this company called GK Technology and that they were looking for a software developer, and so I got Darin's number from him and I remember I called up Darin and I told him I have a background in agriculture and I'm remote sensing and GIS and that I know how to code and it just so happened it was the same language as what coding language is what Darin does, and Darin hired me on the spot without even looking at a resume.
Sarah:I didn't know that either. When I see the products that come out of Darin and Travis's brains and what we actually get to work with, it's pretty cool.
Travis Yeik:I think Darin had been looking for a programmer for quite a while, maybe for five years or so. There's not a lot of guys out there that has the special niche market where Darin and I are.
Sarah:Well, and to Jodi's point, you do have to understand a little bit of something that's actually going on out in the field. I do think that there are a lot of companies out there they forget about the field aspect of it. They forget about what it's like to actually try to farm to make a profit out there. They forget what it's like to make the agronomic recommendation and that these tools are supposed to enhance all of that. I feel like sometimes in today's world, precision agriculture companies get so caught up in what's going on in the stock market and making sure that their investors are happy that they forget about what's important at the ground level on the farm, and I feel like we're very much so in touch with that. Our primary programmers.
Sarah:Again, Darin had managed to fertilize your plant, and obviously Travis has big history in agriculture as well. It's pretty interesting to hear about how you got to GK. It's really fun to pull the curtain back on this For this episode. This is a good place to wrap it up. We will have more, though, next week with the man behind the curtain, Travis Yeik. So thank you so much for Travis being here and we'll talk to you next time. And GK Technology we have a map and an app for that, and I can't wait to get in the fields again.
Jodi:No, I can't wait to get in the fields again.