Crop Diagnostics

(Jim) Good morning folks, welcome to That’s My Farm. I’m Jim Shroyer, your host, and we’re in luck because we’re going to be speaking to Dr. Ray Acevedo. Ray is our Precision Agricultural Researcher here at Kansas State University and he’s going to be showing us some really interesting tools. We’re talking about drones and we’re talking about phones, phone applications to tell how much nitrogen that you need to apply. So, get your cup of coffee, come on back and we can get this show on the road.Closed Captioning Brought to you by Ag Promo Source. Together we grow. Learn more at

(Jim) Good morning folks, welcome to That’s My Farm. I’m Jim Shroyer, your host. And we’re in luck because we have Dr. Ray Acevedo with us and he is our Precision Ag Professor. He’s newly hired as of last year. And Ray is going to be talking to us about what he’s up to. And before I go too much further Ray, I know I was a big inspiration to you, because I think you sat there on the front row in my class and you thought, well heck if he can get a PhD, then I can too. So, I’m glad I’m an inspiration to you. (Ray) You certainly were an inspiration to me. I figured anybody from Oklahoma that could get a PhD, certainly somebody from Kansas could. (Jim) OK, I can lower your grade! But enough of that. Ray, thanks for taking time to be on the show with us. And I know in your PhD work and what you’re continuing to do it’s a lot of obviously remote sensing, precision ag types. Tell us what you’re…in this first little second give us an overall view of what you’re doing. (Ray) A large focus of what I’ve been working on, is developing nitrogen recommendations algorithms, utilizing optical sensor technology, things like GreenSeeker, Crop Circle or cameras on your drone. So, right now what we’re doing is so that you can either drive your tractor with active optical sensors on it across the field or fly your drone. The algorithm we created here at K-State will analyze what’s going on with your winter wheat, corn, grain sorghum and be able to make a yield estimation and a nitrogen recommendation, so you can make very efficient nitrogen recommendations across the field, increase NUE, optimize yield and increase your profit per acre. (Jim) Let’s talk real briefly about the optics that go on the machine. (Ray) OK, yea sure. There’s a number of different companies like, so for active optical sensors that build them, Trimble for one makes the GreenSeeker, OptRX, that’s built by Holland Scientific, which is Ag Leaders commercial version. And then of course there is TopCon CropSpec. And so the thing is that they illuminate their own light source. And they’re shining red light and NIR red light on the crop. And basically what it is doing is it’s calculating NDVI, Normalized Difference Vegetation Index and that’s giving us a gauge of how big the plant factor is by using a NIR red light. (Jim) When you say a plant factor you’re talking about photosynthetic capability. (Ray) Photosynthetic capabilities and also how much biomass is there, how many tillers. (Jim) Oh OK. Sure, sure. (Ray) So the red light gives us the gauge of photosynthetic capacity. The NIR red light gives us a gauge of how much biomass is there, how much tillers. (Jim) OK. (Ray) And so an easy way to think about NDVI for this kind of application is that we utilize it to tell us how much wheat is there and how efficiently it’s running. And so if there’s nitrogen stress reducing its efficiency and how much photosynthesis it can do, we know we need to potentially apply more nitrogen. And so that is basically what those kind of sensors do for us. The nice thing is that about active sensors, cause they’re own internal light source, they are not affected by sky conditions, which cameras on drones are. (Jim) So if it’s cloudy, that’s not going to be an issue. (Ray) It won’t be an issue. (Jim) OK.
(Ray) So, cloudy doesn’t matter, but if you’re flying a drone and using a camera system clouds will make a big difference. And so sky conditions, sun solar, zenith angle, time of day, will change your results. (Jim) Don’t go away, we’ve got to take a break right here. Folks, now’s your time to get a cup of coffee and hurry on back. We’ve got to have a word from our sponsors. See you in a second.

(Jim) Welcome back to That’s My Farm and with us we have Dr. Ray Acevedo. He didn’t run off during the break. Thanks Ray for staying with us during the break time. Ray, let’s talk, it was really interesting kind of your overview there. Tell me a little bit about the why of this technology. (Ray) Why do we even have it? And why are we even using it? (Jim) Right. (Ray) The way to think of this is because how much money do farmers put into nitrogen fertilization of their crop? Whether wheat, corn or grain sorghum? (Jim) It can be expensive. (Ray) It can be a lot of money. We know that nitrogen, what your application should be should vary across the field cause it’s a unique interaction between the soil and the weather. (Jim) Variable is the key word here. (Ray) Variables. Variable is the key word. You know if you apply a flat rate of nitrogen across the field, you’re probably not going to get a uniform yield across there unless you had absolutely beautiful uniform soil and beautiful uniform rainfall. But we’re not going to get that. And so what we are looking at doing is utilizing this technology to be able to tell that this part of the field actually needs 80 pounds of nitrogen and this field needs 30 pounds. (Jim) And another part needs 120. (Ray) Another part needs 120. And so we can optimize it for every little place within the field. So treating that big field like many little fields. So then we can get a lot higher nitrogen use efficiency and a lot more profit per acre. (Jim) You know, that reminds me, when I was at school at Iowa State, we had a professor that owned land north of town and he drove the co-op guys crazy because he had it mapped. And he would have a stake from this point to this point. He’d say, I want to put on this amount of nitrogen. Turn left and go to that flag up there and this amount. So, that was way before the remote sensing part of it. But interesting. (Ray) Well, you know what, he was probably using remote sensing to determine that. He was using his own eyes and his knowledge of the soil and the weather and put together a variable rate nitrogen map in his head. So, as you can imagine with this algorithm development for these sensors, all we’re trying to do was do the same thing. But instead of driving a co-op crazy, the sensor just does it automatically. (Jim) Right, right. (Ray) And so, I like to tell my students that basically we’re trying to put our Soil Fertility Specialist Dr. Dave Mengel on the front of your Spra-Coupe and you’re driving around and saying, 30, 40, 100, 120, that measure. But yea, it’s a wonderful technology and I’m glad to say that it’s really starting to come up in Kansas. And so, an important thing that we start to discuss now is how we actually did it. How did we go about doing this? (Jim) The how part of it is the tricky part. (Ray) Yea, the how part is the tricky part. And what we did is since 2006 we’ve been establishing nitrogen studies all across the state of Kansas and applying different nitrogen rates at different times and collecting spectral data from GreenSeeker or from camera imagery and monitoring it from start to finish, from planting to harvest. And so, what we’re doing there is that we’re collecting the necessary spectral data to see how the wheat plant or the corn plant is
responding to the nitrogen. How it displays nitrogen stress in unique environments. Because how it’s gonna display its stress in southeast Kansas where we got a lot of rainfall is going to be a lot different than southwest Kansas. So, we’ve got two totally different environments. (Jim) And northwest and the other areas. (Ray) Same thing. Kansas is a beautiful development environment. (Jim) I bet it is. I bet it is. We’ve got to take a break right now Ray. Hang with us. And folks, stay with us as well. We’ve got to have a word from our sponsors, so hurry on back and we’ll continue our talk with Ray.

(Jim) Welcome back to That’s My Farm. I’m Jim Shroyer and with us we have Ray Acevedo our Precision Ag person. And Ray as we finished up in the last section you talked a little bit about for the last 10 years we’ve been doing nitrogen studies across the state and during the break I was thinking, we’ve been doing nitrogen studies at K-State, Oklahoma State all the schools have been doing it for gosh, how long? Sixty, 70, 80, 100 years? What’s different the last 10 years as opposed to all of the research that’s been done up to this point? (Ray) Well, what’s changed in the past 100 years, or even the past 10 or five years is the technology available. (Jim) OK. (Ray) And so because the invention of different types of optical sensor technology and the price of it coming down to where it’s actually feasible to implement on the farm. We really didn’t change a whole lot with our nitrogen studies. All we did was kept doing them, but now started collecting data with consensus. (Jim) Other data. Uh huh. (Ray) Yep. Instead at a typical pull plant samples and take your yield and use plant analysis to see if those are nitrogen deficient. Now we’re collecting extra data with the sensor technology so we can build these kind of algorithms. We couldn’t do it off past old data from Oklahoma, because it didn’t have the necessary data that we needed to build it. So we’re still doing all the same old stuff, doing plant analysis, doing the yield, getting the grain protein, all those things. But now we’re just adding on the spectral data. (Jim) OK, so let’s continue the on-farm stuff. What kind of rates you’re using, what brackets you’re using, that sort of thing? Kind of explain that a little more. (Ray) Sure, typically we’ll have different nitrogen rates ranging from zero to 150 pounds of VEN usually in like 30 pound increments. And we’ll apply that at different times of in season, all pre plant or all at feekes four at just spring green up. (Jim) Right. (Ray) And then we do split treatments where we apply some pre plant and then remainder at feekes four, feekes seven, sometime after jointing or even all the way out to flag leaf. (Jim) Right. (Ray) And we see how the plant responds and collect the necessary spectral data so we can build these nitrogen recommendation algorithms. (Jim) OK, so these sensors, let’s take a particular rig, a spray rig, where do the sensors go? They’re in the front of the machine obviously. (Ray) They’re typically on the front of the machine, whether it’s on the front of the boom, just ahead of the nozzles or all the way at the nose of the machine and spread out there. (Jim) OK. (Ray) Depending on the sensors design. But it’s always in front of the nozzles. (Jim) Yes, it has to be. (Ray) Has to be right? (Jim) Has to be. (Ray) Right? Somebody went wrong in engineering otherwise. So, they typically go in the front. And outfitting a spray rig right now use good capitalism to get the competition to bid you a good price, but typically between $15,000 to $20,000 dollars seems to be the going rate to outfit a spray rig with active optical sensors. And you can just go ahead and drive through the field. And while you’re making your typical nitrogen recommendation, so if a wheat farmer right now is making their nitrogen application at Spring green up like they usually do, they just turn the sensors on, drive through the field at the speed that they normally go and they’ll make their variable rate nitrogen application. (Jim) But there’s not much foliage at this particular time. How does it know that it needs that much? (Ray) Well, that’s the fancy details of the algorithm design. And so we built up, got a lot of information and made it area specific for different areas of Kansas in order so we can properly interpret what’s going to happen with the soil and the weather in order to produce the right amount of tillers and ensure that has enough nitrogen to get through the season. (Jim) Ray, we gotta take a break here. Folks, stay tuned. We’ll be back after these words from our sponsors.

(Jim) Welcome back to That’s My Farm. I’m Jim Shroyer your host, and with us we have Dr. Ray Acevedo, our Precision Ag faculty member from the Department of Agronomy. Well Ray, we were talking…well wait a minute here I see a little toy down here. Let’s talk about this toy that you’ve been playing with. (Ray) Yea, that’s what we do in agronomy and research we play with a lot of fancy toys. (Jim) Yea, right. (Ray) And somebody writes me a check. So, I just fly this around all day and I get paid. But no, not really. What I’m focused in on is turning this toy to a tool for on farm use. So, right now there’s been a lot of hype around drones and agriculture, but the coolness factor is finally wearing off. (Jim) Right. Now we gotta put it to work. (Ray) Now it’s time to put it to work. It’s time to make it, have it make money on the farm. And right now it’s equipped with sensors that aren’t all that different from active optical sensor technology. (Jim) When you say active optical you just mean normal camera. (Ray) When I say active optical I mean that it emits its own light source. (Jim) Oh OK, I’m sorry. (Ray) So, the camera is actually a passive system that requires sunlight to actually get the light in. (Jim) OK. (Ray) And so what this camera will do is just like it will do normal color vision like we’re seeing right now, but it will also do things like near infrared, it can do NDVI, which is Normalized Difference Vegetation Index. (Jim) So, we can see if it’s stressed or not. (Ray) See if it’s stressed. We’ll have increased sensitivity. And so, but the obvious benefit of a drone is that we can fly a field rather quickly, in a sense a lot more fields. And so then we can cover more acres and potentially address stresses sooner. And so we can minimize any potential negative impact to yield. And so we’re doing the similar work to make nitrogen recommendations based on this. And this one is actually a pretty nice fancy toy turned into a tool. It’s got an on board computer on it, does all the processing right as it’s flying it. And then also it’s equipped with other sensors, so it can actually see where it’s at. So, it knows if it’s actually flying close to you not to come up and chop you up. And it can stay away. (Jim) That’s important. (Ray) It stays away. It’s got ultrasonic sonars and so we’re actually starting to get into other types of data that we could potentially use on the farm to make a better recommendation. (Jim) Can you give me an example of that other type of data? (Ray) Well say like this, I can be flying over the crop and
actually be able to detect and tell how much height the crop is. (Jim) How tall it is? (Ray) How tall it is. (Jim) OK. (Ray) Yep, and so that could be useful information especially when you’re starting to talk about calculating biomass, things of that nature. Get a lot of calls in from farmers wanting to know what we’re doing for forage development. (Jim) Right, sure, OK. (Ray) And so looking at forage yield and forage quality and so we’re not ignoring them, we’re trying to get them in there. And then at the same time bringing in thermal imagery. And so livestock, cattle, want to find out, see where they’re at in the field, count how many are there. (Jim) Well, I’ll be darn. (Ray) And also try to be able to tell if they’re sick or not. (Jim) Well, let’s let the animal science folks talk about that, but the thermal though that’s really important on stress… (Ray) Yea. (Jim) …or moisture stress, heat stress, a sick plant or a drought stressed plant is going to be a little warmer… (Ray) That’s right. (Jim) …than a well watered one. (Ray) That’s right, so using thermal imagery, like with drones is often used for being able to help schedule irrigation management and also being able to tell if there’s any issues with the actual irrigation system and helping to find leaks and things of that nature. OK, I want to do a whole show with you on this one of these days. But at any rate, we gotta take a break and we’ve got one more section to do. Folks, get your cup of coffee and hurry on back. We have to have a word from our sponsors. See you in a second.

(Jim) Welcome back to That’s My Farm. I’m Jim Shroyer and still with us we have Dr. Ray Acevedo, our Precision Ag Faculty member. And you know Ray we were talking about all this technology that you’ve been talking about here and I got to thinking maybe if you developed an app with a smart phone, that you could go to the phone, take a picture and it would tell you what the yield is going to be. (Ray) Well, you know what Jim as they always say, there’s already an app for that. (Jim) Oh no. Well good. But I kinda knew there was. (Ray) The interesting thing is that it was actually, we’ve been working on a Kansas Wheat Yield Calculator app for the past couple of years. It was actually sponsored by the Kansas Wheat Alliance. (Jim) Right. (Ray) And its initial version that came out did all the standard methods of calculating yield. You could count tillers, you count heads, things to that nature. But the past couple of years we’ve been beta testing the Picture Yield Estimation side of it. So, basically you just go up, take a picture of the crop and then it gives you a yield estimation. (Jim) OK, so hang on here. At any time of the year? What kind of angle, that sort of thing? (Ray) OK. (Jim) I mean you just take a picture? (Ray) That’s literally it. There’s no calibration boards involved. I made sure that that didn’t happen. Because if there’s any extra little details that are needed a farmer’s not going to use it. (Jim) Right. (Ray) So, all you need to do, it can be used at anytime of the year, assuming that there isn’t snow on the ground or something. (Jim) Like last week. (Ray) Like last week. As long as it the crop, and you just take the picture with the row. That’s all that’s needed. We’re getting ready to put out our next update, so the yield, so the Picture Yield Estimation side will be coming out. And the creation of that actually came from all of our sensor algorithms that we’ve been doing the past five years. During that time I was taking all the necessary pictures and coming up with new processing methods to make this happen. (Jim) OK, so what you’re saying by that is you would say a field that was going to yield 30 bushels you would take a picture of it. (Ray) Right. (Jim) A field that was going to yield 35 or 40 or 50 or so on, you would take a picture of it. (Ray) That’s right. And so when we took all those different nitrogen trials, all those different nitrogen rates, we took it on every last one of those plots and we did it all across Kansas and we have yield ranges from zero all the way up to 115, 120 bushels. (Jim) OK. (Ray) And so we have a wide yield range, a good data set and a very unique processing method to where sky conditions don’t matter any more and then also calibration boards aren’t necessary. And so it could just give a farmer a quick gauge of how well is that wheat going to do? (Jim) You know, cause I tell everybody, I can usually guess within 30 bushel, either side of what the wheat field is gonna do. This I hope, is a little better than that. How close can you get? (Ray) On the wheat tours you usually like to talk that you can get a little closer than 30 bushels. But we won’t go there. Anyways, you can get pretty close. Right now I’ve been seeing results being within around five bushel of the actual yield. (Jim) OK. (Ray) And I consider that a pretty acceptable level. Now, I’m assuming that there isn’t a plague of locust that comes in later. (Jim) Right, right. So, you can take it like you said, in the fall? You can take it in the Spring prior to top dressing and then throughout the season? (Ray) That’s right. So, you can be monitoring how well your crop is doing throughout the entire growing season. (Jim) OK. So, where can they get this app? How can the farmers get it? (Ray) You can go ahead and download it at the Apple App Store, is one of them. And also we’ve got an Android version. You can download that at Google Play. (Jim) OK, so expensive? (Ray) Free. It doesn’t cost anything, free to download. (Jim) OK, OK, good deal. Ray, thank you for taking time to tell us what you’ve been up to. And I won’t change that grade. (Ray) That’s good, that’s good. Well, they would take my PhD back. (Jim) Folks, thanks for being with us on this issue of That’s My Farm. And don’t forget, next Friday about this same time, we’re going to have another That’s My Farm show. See you then.

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