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Hello, and thank you for joining us for a STELLA webinar with our special guest, doctor Craig Kohn.

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so, I’ll go ahead and introduce myself real quick and then introduce our our wonderful guest here, Craig Kohn.

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So my name is Mike Taylor. I’m with the Landsat communications public engagement group. And, I’m also the STELLA team lead.

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All right. And this is our amazing, amazing, wonderful, awesome guest. Craig Kohn and I’ve known him for, what, over a year now?

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I met you at the Commodity Classic, in 2024. And all the educators there were like, you got to meet this guy.

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And I did, and it’s just been amazing ever since. So with that, please go ahead, Craig, introduce yourself.

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And, go for it. All right. That’s high praise. Howdy, folks.

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So I am just getting off of teaching here. I’ve been at a full day of teaching, so I’m, like, playing catch up here.

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So if I seem a little, like, flustered, that’s why I just got done with the class and rushed over here from a different classroom.

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So the joys of teaching. So I’m going to go ahead and share my screen here in just a second.

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We want that one and it should look like that. Hopefully everyone can see it.

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I have a couple students coming in here. One of us, one of them just joined us. So in a moment you might see some faces joining me.

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These are students we have here at Waterford High School who have worked on the STELLA project with us. Yep. So if you to come around you can say hi.

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So for example, this one I’m going to look as good as here. You’ll be talking with us briefly about his experiences as well.

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So actually yeah. So you should be able to see my screen. Mike, does that look right to you?

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It’s looking pretty good to me. All right. Perfect. So let’s dive right in. So quick overview of what we’re doing here.

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This is actually a presentation that I did at a Wisconsin’s, society for Science Teachers conference.

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That’s kind of our state in star version. And this was way back in March. We did this, we were going to record it.

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Unfortunately, what happened was we lost Wi-Fi. Luckily, I already had the presentation open

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so I could go through it without being in presenter mode. But we’re doing this again, in part so we can reach more people, in part

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so we can have a recorded version, and in part because it’s such a great story, we love to tell it as often as we can.

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So I’ll briefly talk about who I am and why I’m here. We’ll give an overview of STELLA and what it involves

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and what it looks like and how it can be used. I will do a demo of how to assemble a STELLA-Q2 model and how to program it.

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I’ll show you some sample curriculum that we have, and we’ll have some time for Q&A here at the end, and have some students chime

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in about their experiences and all that sort of stuff as well. Throughout this entire presentation, if you’re interested

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in getting access to the links or anything for reuse, for resources or curriculum, all of that is publicly available.

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All of it is open source. You are welcome to use it as much as you want. Modify it, change it however you like.

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That’s why it is there. So, if you happen to have a device with you, these QR codes will take you to my website where everything is located.

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The purple QR code will take you to this presentation where all the links are found. If you happen to need it.

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I’m going to go back a slide here real quick, and you can see that our Bitly link is up here.

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So bit.ly slash t dash NASA will take you to this presentation as well.

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So we’re trying to give you as many ways to get to it. I will have these links and things at the end as well. Without further ado.

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Why would you want to do this? Well, you can learn about the spectrometers themselves, how they work, how they might help you, how they might work in your classroom.

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We’ll walk you through how to build one. They’re very simple to build, not quite as simple to program, but it’s still very feasible.

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I can do it. I’m not a programmer. We’ll talk about real world applications, especially in ecology and agriculture.

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So if we if we invite a science teachers and agriculture teacher. So I’ll be talking to two different audiences

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this very closely aligned to everything that you do. I know because I do both of those things.

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Currently in the classroom, I teach both ed classes. I have two of those and I have three science classes, so I have my feet in both worlds.

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We’ll talk about how this can be integrated in terms of what your students could do for projects. And we’ll have some of those folks coming in here

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and broaden your understanding of what these standards are and how they work. I, my doctoral advisor was one of the,

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people who was the impetus for NGSS. And so he was the, head of our research association when it was created.

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And I was one of the authors of the national AFNR Academic Standards for Agricultural Education. So I know a lot about these.

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We try to incorporate that into this as much as we can, so that people have a strong understanding of what they’re actually trying to do,

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but no one cares about that. Let’s dive into the more important things. This is also something you may not care about, but I got to say it anyway.

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So hello, I’m Craig Kohn. I am a teacher here at Waterford Union High School. I’ve been teaching for 18 years.

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You can see my background. There’s a lot of stuff I’m affiliated with. But the big thing we’re talking about here today is STELLA.

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So I also have research experience with the US Department of Energy at the Great Lakes Bioenergy Research Center.

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I was a research fellow with the National Science Foundation. I currently live on a farm here in Wisconsin, and I teach

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in a small, tiny rural school called Waterford High School. We have another one of our students with us. Do you want to wave? Hi.

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They’re going to be coming and going because we’re a school. That’s how it works. So this is Cheyenne. She’s one of our researcher extraordinaire.

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But yeah, let’s just dive in. So what is STELLA? STELLA is an acronym, stands for Science and Technology education for Land and Life Assessment.

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The idea of the project is that we’re providing low cost DIY spectrometer tours that you can build in a school for pretty affordable price.

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So it’s not cheap, but it’s pretty affordable. The idea is that we’re giving students access to opportunities

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for remote sensing data, opportunities like data collection. Right. So, how can we use this kind of data

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to address real world questions like, how should we produce food? Or are our habitats, under attack by disturbance or something like that?

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So, I mean, it’s weird that you’re back there. It’s like you’re in the oh, you’re like the ringer girl.

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Really quickly, what is spectral data? I mean, we’re assuming this is primarily an audience of teachers, but the idea is that we’re looking at electromagnetic radiation.

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So we know that light and infrared radiation are just different size wavelengths of the same moving energy or same radiation.

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Right. So we know that light energy, smaller wavelengths, infrared energy, the energy we feel this heat is larger wavelengths, but it’s all electromagnetic radiation.

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That’s as x rays, as gamma rays as is all of these stuff. And so the STELLA units are able to detect 18 bands

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of that electromagnetic radiation at those different wavelengths. So the idea is, again, we’re offering an affordable

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opportunity to collect this kind of data in schools. And this is mimicking what is found on the Landsat satellites.

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Obviously not the same quality, but it does the same kinds of things as the Landsat satellites do.

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They detect infrared and light radiation at different wavelengths to address different kinds of questions?

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The one that we really focus on is something called NDVI, which we’ll talk about here in a moment. But there’s a lot of other things we can look at as well with this data,

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these Landsat satellites. And there are now nine, I believe, if that’s correct. Right, Mike?

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That’s correct. Landsat Next due to launch 2031. Yep. So soon to be a 10th. And we can see that they’re looking at the Earth’s surface.

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And the current satellites are looking at a pixel size of about 30 by 30m. That’s about literally the size of my class.

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Well, no, just under the size of my classroom right now. Right. So just over. Anyway, it doesn’t matter.

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The Landsat Next will be looking at a much finer position. That’s going to be great. There’s also one called pace that’s primarily

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looking at ocean ecosystems but same kinds of things. What are we seeing for reflected heat and light.

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And you might be wondering, well why do we care? Well, that tells us a lot of information. And primarily the one that we’re looking at

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and we’ll be talking about in this presentation is known as NDVI or Normalized Difference and Vegetation Index.

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In a nutshell, that’s the ratio of reflected heat and light absorbed and reflected. And so if we compare the amount of light to heat that is reflected,

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we can get a sense for how well plants are functioning and performing. So for example, during photosynthesis we know that light is absorbed

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and transformed into chemical energy. That means there’s less light that can be reflected back into space.

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And so if we see less light reflected and more heat reflected, we know we have a healthier plant and we’ll have a higher NDVI score.

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So we can see that in the image here on the left, 0.72 is closer to a maximum of 1.0.

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On the other hand, if we have an unhealthy plant, it’s not going to absorb as much light during photosynthesis.

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More of that light will be reflected back into space. That will give us a lower NDVI ratio,

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and we’ll be closer to zero, or even as low as negative one. We’ll talk about that more in a moment, but that’s the gist of it.

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The less light that’s reflected generally, the more healthy the plant, because the more photosynthesis that’s occurring.

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And so we can see that in this example. So for my last presentation, when we did this in front of actual people in March, I had two plants I nicked from or snagged from Walmart.

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And lo and behold, there happened to be unhealthy plants at Walmart, which worked out really well.

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So I bought two identical ones. One that was healthy, one that wasn’t healthy, as well as one of their fake plants.

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And I took these devices and I measured in we using them, and we could see that the healthy plant at a higher value were closer to a maximum of 1.0.

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The less healthy plant had a lower NDVI and then the fake plant was way down below 0.5 because it’s obviously not photosynthesizing if it’s fake.

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And so this gives us a sense for how well plants are performing by measuring the amount of light that is reflected back in

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comparison to the amount of infrared radiation. We can do really cool things with this. With the Landsat satellites and the data they provide.

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One of them is the Earth System Data Explorer. So it might be that you’re not able to make these instruments, but you can still use that same data.

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And so, for example, if we look at the ones I already pulled up, there it is.

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Let’s make this nice and big. Mike, can you see my screen okay. Yeah. You’re good. Awesome. All right.

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So for example, what I plugged into this system was looking at the biosphere and vegetation and NDVI in May of last year, 2024.

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And then on this side I did July of last year. And so we can see as I scroll from May to July, our coloration gets greener.

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And based on the scale that tells us a better or higher NDVI level closer to one, that means that lighting it right now, because I just slit it.

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So this May because I’m not seeing it. If you are. Oh. Okay, then.

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Well, you just have to take my word for it. Yeah, yeah. And someone’s asking if you could make the screen bigger as well.

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Absolutely. So. So it’s only showing that one tab.

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And I don’t know why, but it doesn’t matter if you could see what I just saw,

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you would see the slider moving back and forth. And you can see on the left is May with lower NDVI levels.

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And on the right is, July with higher NDVI levels.

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And so you can zoom in anywhere in the planet. You can set your parameters for different things or different times or both.

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And you can see how NDVI changes as we go from season to season or year to year, or place to place or anything like that.

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One thing you might also notice in this image is that we have Lake Michigan and Superior, and they actually have negative NDVI values.

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And that makes sense, right? Because the light hits the surface of the water reflects back and the heat is being absorbed.

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So it’s just the opposite. Right. So plants absorb light and reflect heat. Water reflects light and absorbs heat.

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And so we’re gonna have negative NDVI values where that cold water is in the Great Lakes. So cool stuff.

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All right. And for some reason when I did that that screwed up my let’s try that again.

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Like, is that any better? Yeah. I mean it could be worse. Wi-Fi could be out So you know what?

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We’re just going to roll with the punches here. So okay a couple quick things to show. Again I’m not going to go into too much detail

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if you want to go back into the presentation. All of this stuff is linked. And you can get this anytime. But some examples of things we use in this way in our classes include this slide.

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So in our agri science class we talk about changes in greenness over time. And so for example we can see changes to NDVI from the 1980s to 2013.

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And we can see like for us here in Wisconsin, in the Midwest we are in the red, which means that NDVI values went down.

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We have less photosynthesis now than we did 20, 30, 40 years ago. And we can see other areas

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like California, the West coast, the South have more green. That means the NDVI values went up,

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more photosynthesis, less light being reflected. And we can start developing some hypotheses. But well, why would this be occurring in my class?

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We then look at water usage next. And we tend to see there’s a correlation between where aquifers are being depleted

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and we’re NDVI went up, and vice versa where aquifers are not being depleted, ndVi tends to go down

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and we start to form some hypotheses and questions about, okay, are these two things connected. And we can start to infer that, well, maybe excess irrigation is enabling

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more photosynthesis but at the expense of sustainable use of water. Right. So those are things we can start to investigate in more in depth with

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and actually have a real world connection for our classes. Another example here, this is students who use the devices to measure their own research.

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So in this particular case what the students did was they added caffeine to their treated radishes

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as radishes as a model organism, fast growing cheap, etc. so great for that. And they compared them to the untreated radishes without caffeine.

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And we can see that the difference in NDVI also correlated to the differences in mass and height,

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that caffeine literally stunted the growth of our radishes. So they were smaller, shorter, and photosynthesize less,

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which is kind of cool. And then we can talk more about this. We can assign quantitative assessments where we’re looking at differences in percentages, etc..

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And we have a whole format for doing this, which we’ll get into. But again, as an example of what students could do with this kind of data.

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So what do we have for options here. Well, we actually have for probably more than that now right. At least four options for STELLA.

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Like are there more. Yeah. In fact, actually there’s STELLA- 2.0 and the Q are basically retired at this point.

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But we do have, Heliophysics one. I would be remiss if I didn’t point that out.

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And the, 1.2, which is up and coming, which I sort of teased a little earlier.

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There we go. So this is already other day, but that’s okay, because science is always changing. So one we’re going to focus on

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is the Q-2 I have tried to do the one point ones before. So when Mike and I met for the first time in Houston, I was super excited about the 1.1

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for my abilities as a non electrical engineer. It’s a little bit beyond our grasp. So we tried to do it. We weren’t very successful.

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Middling results, but the Q-2 is very feasible and affordable. And that’s the one we’re going to focus on.

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So again there are other options. We’ll talk about them in a moment. But for the sake of making things feasible and these are easy.

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We’ll talk about the Q-2 primarily here. So the Q-2 which is the more feasible one detects electromagnetic radiation

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in 18 non continuous bands ranging from 410 nanometers to 940.

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So we know visible light is somewhere between 410 and 7 something 16 more of a biologist than a physicist, but you get the idea.

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So we’re going a little bit beyond the visible into the infrared, the energy we feel. Is it, one important note is that it’s 18 non continuous bands.

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So any astrophysicists out there who want to measure like spectra from stars, unfortunately we’re not really fully capable of

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doing that with this particular unit because it’s not continuous detection. And we would need continuous detection of light and infrared radiation

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to make those inferences. For example, about what kind of elements are found in different stars or in the atmospheres of different plants.

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So we can’t do that, but we can do things like NDVI which is really cool. And so this is a great introductory option.

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Doesn’t require soldering or engineering skills or anything like that. It’s really just a plug and play kind of device.

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Very feasible to program. We’ll get into the examples of how that works here in a moment. As far as the budget, the last time we did this, it cost us

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just over $150 per unit to get this to work. These are things that are generally available.

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Most of them are coming from two companies, Adafruit and SparkFun. They can have things to pretty quickly.

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Our folks here at NASA sent something to me, and I had it in about four days. It arrived yesterday. And you’re going to see some of those components here.

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So generally can be pretty feasibly done and affordably done unless they’re short on parts, which does sometimes happen.

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So if you’re planning on doing this I would say order stuff early. So if you think you’re going to do this in September

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or order stuff this summer, that way you give them plenty of time. Last year or at the start of this year when we try to order some things

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in September. We didn’t get some parts till November, so it can be hit and miss. But again, the gist of this is that it’s usually affordable and feasible.

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How do we assemble this? Well, we can get into it in a moment. I’m going to switch my camera over and stop sharing. And we’re actually going to assemble one together here really quick

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just so that we can see what it looks like. So let’s switch that around here to this camera.

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And we’re hoping that cameras going up there it comes. All right so there you go. Let’s turn on lights and we can see.

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So on the STELLA website you can print off all the components. And it looks like this. And so I have all these scattered around.

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But basically all you have to do is line up the components on the summary

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and the description and the picture of each item. So for example we have a microprocessor called the Thing.

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Plus it’s a weird name but that’s what it’s called ThingPllus 2040 microcontroller.

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So I’m just going to put that there. And I’ve already connected that to the green button right there. And then over here I have the power button and battery.

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So I’m going to do is line up each component of that.

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If you hear chips crinkling in the background, that’s because I have kids here eating after school. And I mentioned that, this layout and all the STELLA’s is were developed,

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and created by Paul Mirel who’s a genius and he’s here in the panel as well.

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So if you have any, you know, technical questions or if you’re like, wow, that’s amazing.

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That’s a lot of that is Paul, pretty much all of it. Yeah. And yeah, I don’t want to give any, confusing ideas that I had anything to do with this.

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I’m the one just figuring out how to use their brilliant idea. So just to be absolutely clear, but that’s the genius of the system

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is, again, all you have to do is line up each part. So for example, there’s only one way these can plug in. So you just look at where the pins are in that ports.

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And then you line up the holes in the cable. These are quick cables. So they just pop in really easily.

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And now we’ve just connected the clock. And then I already have the battery in the clock. Then we’ll take another wire and we will connect the triad sensor.

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This is what actually detects the infrared and light radiation.

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And we just plug that in like so if it doesn’t go in easily don’t push hard because you can easily bend the pins that are necessary for that connection.

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And then last but not least, we’re going to connect the display. And voila we have a unit.

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Now there’s a couple of things you could do. Obviously this won’t be very functional when it’s just a bunch of loose wires

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all hanging out. So one option is you can 3D print, their housing.

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So this is what it looks like when it’s all nice and fancy or

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this is what ours look like. This is what we printed in the library. Or you. What you could do is then just take a jewelry box

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and just throw everything in there. Just make sure you tape it down nicely, because if the wires jiggle, it can throw off your programing.

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But it doesn’t have to be a fancy housing. It can just be. This is probably a dollar, an Amazon, but it works just fine.

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In fact, yesterday I tested these two side by side and I got almost the exact same data and the same readings for each one.

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So it doesn’t have to be the fancy housing because you have a 3D printer that’s great. Just be aware.

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You have to be pretty precise. One mistake we made was they didn’t have like 100 millimeter cables.

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So we went with a 200. And that was just too much to try to cram into this little space. So if you want something

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that’s a little more forgiving, then just go with the jewelry boxes on Amazon, which is cardboard. It’s nice and cheap, and that can keep your costs down a little bit easier.

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Or if you don’t have a 3D printer, that’s another option. But that’s all there is to it. You just got to plug everything together and you should be good to go.

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We still have to program it, obviously, but that’s the gist of it. That’s how we put it all together.

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So with that being said, if we have a functional STELLA unit, the next thing we would have to do is program it.

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And so we’ll briefly go over the programing instructions and then I’ll do an example with you. I’m going to go ahead and re share my screen here in just a moment.

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So hang tight screen and I’m going to do this.

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So I’m going to share my window instead. That way you can see it a little bit better Mike. Is that coming across okay. Yep. Looks great okay. Awesome.

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All right so let’s start at the top here programing instructions. Now they have all of their programing instructions on their website.

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We just rewrote them to make them a little bit more feasible and updated based on the new, options. So they’re just released.

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You just said on Friday a new version of the coding released, right? Yep, yep. So they’re updating things all the time.

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So these are almost like living, breathing devices in the sense that the updates as a biologist I like to call that evolution.

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But nonetheless first things you have to do if you want to program one of these things is download three things.

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The first thing you have to download is the programing file from Circuit Python. That’s a weird looking name, but that’s just what it’s called.

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So this is the company itself selling Scott SparkFun is the company. They’re the ones who sell the sink plus, which is like the brains of this device.

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And so you have to download the program file by going to this website and then clicking that purple button that says download us to.

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Now you have to is the programing file. You also have to download something called the Moo editor. I like to call it the Moo editor because I’m from Wisconsin,

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but the Moo editor is how you do the programing for the clock. So again, all these are free. They’re easy to get.

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You just go to this website, hit download, follow the instructions. You’re good to go. The last thing you have to download are these STELLA files.

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So STELLA’s the instrument. Q2 is the instrument. Go to that website, download STELLA-Q2 files or download as a zipped folder.

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So you right click hit extract or whatever your computer system uses. And then you will have all the files you need to program your STELLA.

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And that’s it. Once you have those three things, then you go, you find your stuff.

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First step is to plug in your device. So you’re going to use a USB C drive or a port.

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You’re going to plug that into your laptop or computer. You should see it come up. It’s RP1-RP2.

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You find the the circuitPython file in your downloads, click and drag and what will happen.

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And you’ll see this here in a moment is that file will essentially rename itself as CircuitPython.

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And so it’ll look different. Your computer might say you should have rejected it. It’ll yell at you. That’s fine.

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Once you have that, then what you’re going to do is go to your downloaded files. You’re going to find something called, the STELLA-Q2 all folder,

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and you’re going to find a lib and a code.py You’re going to highlight both click and drag.

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And now you’ve added the programing instructions to your is still active. Once you do that you have to set a clock.

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So that way your device knows when it is because you’re going to need that to figure out what data was collected when.

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So if you know when it was collected, you can find it more easily. Obvious stuff. Right? So to do that you’re going to go in your STELLA files.

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There’s going to be a folder called clock set. It’s also going to be called code.py.

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You’re going to click and drag that onto there. And then you’re going to go into a program called the MU Editor that you downloaded earlier.

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And it’s going to say, what year is it? And you’re going to type in the year and it’s going to ask, what month is it? And you’re going to type in the month. And you just keep doing that

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until you have the universal time set on your device. And we’ll show you what that looks like here in a moment.

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Lastly, when you set the clock, you actually override the original files you used to program it. So you have to add those back.

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So then you’re going to click and drag the original code.py file you did before. That will replace the time file.

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And then you’re pretty much good to go. So we can do an example of what that looks like here really quick.

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Give me a moment. Because I have to take an original unit.

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So the one I assembled for you was one that I had programed earlier. So I’m going to plug that back into here.

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And then I will show you what that looks like here in just a moment. I just erased everything on it, so it should be a fresh start.

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Now, of course, because we’re doing this live, I’m sure you’ll go wrong, but hopefully not.

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So let me unshare. Actually, let’s pull up this file.

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There we go. Now, can you see my files? Okay. No. Right now, I’m still seeing just programing instructions.

24:56

All right, so let’s try stop sharing and let’s pull up this.

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It was supposed to share my. See, should share my screen window.

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Let’s do the entire screen. That probably will do it. And let’s try this one. All right.

25:19

Now you should see my files. Does that look right? Yeah. That looks very awesome.

25:24

All right, so I just plugged in my STELLA device. And if I did it right, I should say, it doesn’t say that of course, but okay.

25:31

That’s fine. We’ll make it work. So right now says CircuitPy, originally I should say RP1-RP2.

25:38

So there’s a quick fix I can do if I ever have a problem. There are buttons on the back of that thing, plus that say boot and reset.

25:46

And so if I press boot and then press reset, what it should do is completely wipe it clean.

25:53

And if I go back to my files, hey, look at that. It worked. All right.

25:59

I’ve done this a few times in the past week, so it says RP1-RP2. That means it’s a fresh drive. There’s no programing on it.

26:06

So the first thing I have to do is add the SparkFun actual programing files for you to write, you have to file.

26:15

So I’m going to go into my downloads and I’m going to find that UF2 file.

26:21

And I’m going to click and drag that on to there. And if it works now that I did it, we see it’s.

26:29

And just a note that you have to file usually does come in the, in the whole package that,

26:35

the Q2 all. Okay. So that sounds a good sign.

26:41

And now it’s renamed CircuitPy Hey, good to go. All right, so next we have to add the programing files.

26:46

So I’m going to go into my downloaded STELLA-Q2. I’m going to go to codes

26:52

and libraries and I’m going to click both. So I have to hold Ctrl on my keyboard.

26:58

Click both of these files the folder and the file. And I’m going to click and drag.

27:03

And it’s going to ask me if I want to replace. I do. And we wait patiently on

27:08

my very slow school computer. And in a moment I will have all of the program files

27:15

I need on my Q2, and it should be fairly operational at that point. And so, for example, if I bring over the MU Editor

27:23

and I click on Serial, now it’s communicating with the devices. So the coding program

27:29

and the device are talking to each other and it’s saying, okay, at these 18 bands at which we can detect things, we are getting some data.

27:36

Awesome. So we have a functional unit. The only thing is it doesn’t know what year it is. So it might take it’s 2000 and in syncs in style, I think it’s 2045

27:44

and the world is ended. Who knows. We have to add the clock information. So to do that, I go back into my STELLA files,

27:52

I go into my test codes and the top folder will say clock set.

27:57

It’s also called code.py. So I’m going to click and drag that on to there.

28:02

I’m going to replace it. And now it’s going to ask me what year it is.

28:08

Mike in a moment can you get the universal time ready. Yeah I don’t have that open just yet.

28:13

So I know the years 2025. I know the month is five from May. The date is 20.

28:20

Now we need universal time indicator. So we don’t want our local time. We want the universal time (UTC).

28:25

Mike you know what the hours. Yeah it is 20. And what’s our minute

28:32

29, 29 and what are our seconds. about 10s I usually put lead time in there. Yep.

28:39

Okay. And now we can see it has the right year. So if I kept hitting enter a cycle through the month, the year, the date, all that.

28:46

Right now it looks like it’s right. So good to go. We set the clock. Last thing we have to do then is go back and add our programing files.

28:54

Because when we set the clock it overrides that. And it’s just a thing you have to do. So we go to code libraries.

29:00

The only thing I need is that code.py file. That’s the original one I put on there. To add the programing instructions I’m going to click and drag.

29:08

I’m going to hit replace. And once that uploads I should have a functional unit.

29:13

If I go back into the MU Editor I can see it’s now communicating. It turned on the lamps. It’s talking to the sensors.

29:20

Life is good. Everything is working. We have a functional unit and we just programed one in front of you. So light it up. All right.

29:29

So can I interject real quick? Absolutely. I just wanted to say that, circuit Python is an independent nonprofit.

29:36

Not SparkFun. Nope. All right.

29:42

With that being said, so we did our programing instructions. We can move on to what can we actually do with this? So let’s do, user instructions so we can see that there are two buttons.

29:52

So if I take this one here. So first things first obviously you have to keep yours charged. Right. So it’s not going to work with a dead battery.

30:00

The quirky thing about these is they have to be turned on to charge. So you have to hit the on button which is the black one.

30:05

Then plug it into a charging cable. Otherwise it won’t charge. I know I mentioned the button. There are two buttons.

30:11

There’s the black on off button and there is the green button. That’s for data collection. So the first thing I have to do is turn it on.

30:18

If it’s functioning correctly. What will happen is will show me the date there. There will be a red and a blue light, and then a white light will briefly flash.

30:25

And then it should be red. That means it’s turning on appropriately. It’s going to cycle through some things. Tell me the battery percentage.

30:31

It’s going to tell me things like I have an SD card. It’s going to tell me how many bins there are. You’ll mention three bursts, which means when I press the green button, it’s

30:39

going to collect three points of data for all 18 bands. And then we can take the average of that. That way we get more reliable results.

30:45

And now if you look closely it’s detecting infrared and light radiation. And so that’s what this is showing us right here.

30:52

Now this isn’t super useful data. We’ll get into how to find the useful data. But what this is telling me is that this is detecting radiation as we speak, which is pretty cool.

31:01

So like if I cover my hand over that sensor, we can see that in a moment here, all of that changes.

31:06

And when I take my hand away, that’s going to change again, which tells us that it’s actually detecting light and infrared radiation.

31:14

Super cool stuff. Okay, Mike, you can see my slideshow. Okay. Right? Yep. You’re looking good. Me all right.

31:21

One other thing you’re going to note is that where this display is, there is what’s called a batch number.

31:26

So when you collect data it’s not going to be like, oh you collected spinach leaves or you collected pond water.

31:32

It’s just going to give you a number. So when you download your data, you’re going to have to know the time or date.

31:37

And that number in order to figure out what’s what. Otherwise you’re just kind of a bunch of numbers on a screen, which you’ll see here in a moment.

31:43

So that is a downside of this is we can’t get the data just from looking at the instrument. We actually have to take out the disk

31:50

and plug that into a computer to get the data. Say, look, that’s what you get for the the more lower cost entry models.

31:56

But we’ll get into all of the options in a moment here as well. All right.

32:02

One last thing. Calibration is key, so in between collecting data you always want to have some kind of like white paper or foam.

32:08

And you want to hold. You’re still a unit. So just generally speaking,

32:13

the size of the data collection area is roughly equivalent to the distance it is from that object.

32:20

So for example, if I want to collect an area the size of this disk, I need to be the diameter of that disk away.

32:27

So whenever I’m collecting data I want to calibrate to make sure that my data is accurate and not being thrown off by something.

32:34

Right. So I’m going to calibrate click that data. Then I’m going to measure my data.

32:42

Then I’m going to calibrate again simple as that. And then you just keep doing it. Calibrate collect data calibrate collect data

32:48

until you have all the data you want to collect. All right. So what does that data look like up above.

32:55

Oh and one last thing. There are two ways you can collect data. So there’s the single mode and there’s continuous mode.

33:01

So like if I want to connect this to a drone and slide over a field or a forest, I have to push the button if it’s 50ft in the air.

33:07

So then I have to switch to continuous data collection mode. To do that I just hold the green button.

33:12

Simple as that. If I want to go back, just hold it again. Mike, about how long do you have to hold that button,

33:19

to, collect data? Yep. I mean, it’s just a brief tap. Did you mention the, holding it for for three seconds?

33:26

That’s what I was getting at. So if I was between modes, it’s three seconds. Oh, no. Between modes, it’s just a tap.

33:33

Yeah. So. But if you, if you want, you know, you can turn on the lamps. If you hold it down, hold it down for about three seconds.

33:40

Okay. So I don’t really use continuous mode because we don’t have these attached to drones yet. Our goal is to eventually do that.

33:47

We have a research field. We’d love to fly it over and collect data. Still working on that. But so and it’s also early in the year, so there’s not much to collect

33:54

data for yet because nothing is growing yet. Anyway. If you want to retrieve your data.

33:59

So inside the STELLA or in my case, it is on here on the side

34:05

either works, there will be a mini flash or not. Flash drive, mini SD disc. So if I

34:13

pull that out, it looks like this. And I’m just going to plug that into my computer. And when I do so it’s going to give me data that looks like this on the side.

34:22

So you’re going to see it has our universal ID that’s the number that’s specific to your unit.

34:28

It’s going to give me the batch number. And it’s going to give me a lot of other things. Big thing that I’m interested in

34:34

is the intensity of the radiation at different wavelengths. So this is if you look at my screen, 410 nanometers, 435 460.

34:43

These are the 18 bands of radiation at which it collects data. And next to that is the intensity of that data

34:51

measured in micro watts per centimeter square. micro watts right. Right. Yes. There we go. All right.

34:57

For NDVI which measures how much photosynthesis is occurring I really only need two points of data. So it gives me all 18 bands.

35:04

But I just need 810 and 645 because that’s how we calculate NDVI We take the intensity of the radiation at 810 minus that at 650.

35:12

We don’t have a 650. So we have 645. So 810 minus that at 645 divided by 810 plus 645.

35:19

And that will give us some kind of fraction or number, which in this case was pretty low. We can see up here data we collected for

35:27

I believe this was our agriscience experiments in fall. So with different treatments, be it caffeine or fertilizers

35:35

or anything like that, and then looked at how did that affect NDVI? And I get to do that, I just plug those numbers into this formula.

35:42

I can enter that formula in Excel or Google Sheets, and that will fit me a number that’s between negative one and positive one.

35:48

Can you, can you zoom in on that a little bit? The NDVI treatment by treatment?

35:53

I don’t know if I can do that. Okay. Because I think that’s, again, if you can’t see it too well, you can get the presentation.

36:01

I’ll have the links at the end again and just. Yeah, check it out then. I can share other files too.

36:07

As we get closer to that. Again, here was the presentation data that I did back in March for August.

36:14

And so again, we just use the same unit and collected. So this is the one that collected this data and then just measured

36:21

both the healthy plant, the dying plant and the fake plant. And this was the data I got.

36:26

Now you can see I collected that data twice. There’s going to be some fluctuation. I was doing this in a hotel room. It was like a 40 degree day with like 20 degree wind chill.

36:33

I wasn’t going to go outside. Right. So was also a cloudy day. So as I was collecting this data, sometimes a cloud would move

36:39

in front of the sun. So one thing that’s really good to do is to keep a record of what the conditions were like.

36:44

Ideally, we’re doing this at exactly solar noon on a perfectly clear day, and you have a lot of money and everyone loves you, right?

36:52

That’s not in the real world. Sometimes we have to collect data under less than ideal conditions. And so this was that which meant there’s going to be some variability.

37:00

That’s okay. That’s life. We acknowledge that as we’re doing a write up and so on.

37:05

And again for data analysis, it’s going to be reporting the data in what’s known as CSV.

37:10

That’s comma separated variables. That translates really nicely to a spreadsheet. And so one thing to be aware of

37:17

there’s going to be other things in there besides the data you’re looking for. So for example there’s uncertainty that’s telling us the range of,

37:25

acceptability, I guess, for our values, if you will. That may not be relevant to you. So it might be overwhelming when you first look at it.

37:33

Really, the only thing you need is the intensity of the radiation for two wavelengths. If NDVI is what you’re focusing on, it just do other things.

37:40

Well. Soviet. All right. Lastly, there is the 1.0 and 2.0 options.

37:47

Again, these are going to be a lot more challenging. They require 3D printing. They require soldering. I’m not someone who’s good at soldering.

37:54

That’s what they look like. They can do a lot more. They will show you your data on the screen. They have the option of using the NASA data viewer, which is super cool.

38:02

So you can see the actual results in graph formats and table formats as they’re happening in real time, super engaging for students.

38:10

They really enjoy that. You just have to have a lot more skill and time and patience more than I have,

38:15

at least to make these. So the Q2 is very feasible. 1.1 and 2.0 are much more challenging, but

38:20

if you have that capability also you can go for that. So I should note, the two high school juniors did

38:27

build 40 of those, to send out as loaners across the country. And we are working on the Q2,

38:33

being compatible with the Dataviewer up and coming. That would be awesome. All right, before I dive into our sample curriculum, we have two students with us.

38:40

I don’t want to keep them here all night. So do you guys maybe recently about your experiences. Awesome. And I will dive in with our curriculum after that.

38:47

So why don’t you come on over? Will they be able

38:53

to answer questions or answer questions? Oh, sure. Let’s go.

38:58

Hello, my name is Lukas. Good. I have been working in this little Stella program for a little over half.

39:06

Half this year. I started, before 2025, but this year of my senior year, I’m a senior in high school,

39:13

and I’ve had doctor Kohn before in freshman year, and I’ve recently gotten back to them to do this STELLA project.

39:20

Excellent. Asi I said before I’m Cheyenne Lees. I’m a freshman. I have doctor is my agriscience teacher.

39:27

I started, well, I don’t know. I just really had an interest in this in the beginning of the year.

39:33

I’ve been at this all year. So you want to talk about what are some of the things like

39:38

what do you do in a typical week with this STELLA? We usually meet once or twice a week for a 30 minutes each time.

39:46

We essentially have different tasks we do in relation to the Stella apparatus instrument.

39:54

Usually the means involve us, like workshopping, trying to solve issues with, Stella,

40:02

like apparatuses because we try to make them so we can have them for, school projects for, like, important data collection.

40:11

And, for example, this is a homemade one. We’ve been workshopping things like this.

40:17

We’ve got like, two of them working. One of them still, like, malfunctioning a bit since the start of the school year because,

40:24

these things, they are somewhat complicated. So they do have a lot of the little finicky.

40:30

So a lot of it, a lot of it is all this workshopping, making sure they work properly, fixing any issues, helping them with whatever he needs.

40:40

And sometimes we and we also do tests to make sure they’re working properly. So essentially it’s constructing doing

40:46

little like demos to make sure they work properly. That’s mainly what we do in STELLA.

40:51

So when you want to talk about your or science fair project. Yeah. So going off what we were like working with.

40:57

So I had like, deep interest of them and API and like its correlations to,

41:04

crop production, especially within like different farming mechanisms like monoculture, regenerative agriculture, PMP practices.

41:12

And so was using Acres, which is essentially a platform, by now so that like those like it

41:22

show it shares the results of Olivia from the Landsat satellites over wherever.

41:27

So currently, me and my partner Logan, he’s out here where,

41:34

taking the NDVI results of all the, fields at Michigan states

41:42

experiment thing. So, yes. So eventually effectively comparing NDVI under

41:49

sustainable agriculture versus conventional or different experimental plots.

41:54

Fantastic. Are you doing, are you doing, calibration?

42:00

To get to the, reflectance from, irradiance to radiance and then reflectance through using those steps, for comparison.

42:09

So yeah, you would calibrate between every. Yeah. We do calibrate in between. Yeah.

42:15

So when we do it I typically write down like what we’re doing. So I have like

42:20

a line through the middle of paper splitting. Once I’ve been like the calibration, the curvature, the two things that we’re like measuring so that between each treatment

42:27

I write down the calibration and then the whatever we’re looking at. So for all we did, so for red for radishes.

42:34

So we put radishes there. We put the, batch number time and conditions

42:40

like cloudy, sunny, whatever. Just to stay accurate. And so they’re easy to find what words to give them that.

42:48

So a lot of the data we saw in the presentation was coming from those launch experiments where they’re coming in

42:54

collecting the data and then preparing the spreadsheets. It’s fantastic.

43:01

Excellent. Well, and then, so if you had any improvements or anything like that, for the STELLA,

43:07

what do you think you would, you would improve on it?

43:15

I would say definitely. Start with, larger

43:22

or large enough cases, a lot of it. We had troubles fitting all these, instruments, all these parts into these,

43:30

small cases. A few times they were damaged because we were trying to cinnamon. And we had to, like, remake them.

43:36

It was all big, kind of like a little hassle. So I definitely start by figuring out

43:43

how to properly, create these, I also wish

43:48

we did have more time to work on these because we don’t meet often. I mean, I’ve been really busy.

43:53

I haven’t been able to do many meetings. Still, I’d, I’d like to meet more often for this.

43:59

I know that’s not like your guys’s problem. It’s just my also busy.

44:05

But, yeah, these are very labor intensive to make and test.

44:13

Very cool. Well. Well done. That’s. That’s great. I’m glad that you’re you’re getting use out of them and enjoying them, but.

44:22

Do you have any questions, Craig? Anything that, I’ve missed so far.

44:28

Was anyone in the chat? I think it’s going to go through the sample curriculum, so. Okay, I don’t know if we have any questions

44:35

from anyone attending, that we want to address first. Otherwise, I can dive right into the sample curriculum.

44:40

I’m not seeing too, too much from the chat at the moment. Okay? I’m seeing people saying, very, very cool.

44:46

Well done students. And, I have to agree. That’s fantastic.

44:52

So I’m glad that you all are having fun with the STELLAs and enjoying yourselves and learning things. So.

44:59

And it’s all part of the process. Good job for you all from folks. So it’s

45:05

I think thank you folks. All right. Let’s dive in then to some sample curriculum.

45:10

So I’m going to share my screen again. Okay. Screen we want a window and we want this All right.

45:18

So Michael, you see in my slideshow I am seeing your slideshow. Awesome. All right, so, folks, we’re going to briefly go over

45:25

what an example of a curriculum could look like. This one is for science. We actually just had our main agro science teacher walk in, Mr.

45:33

Wicks, so we can hear from him here in a moment as well. So I’m actually not the main agar science teacher.

45:38

I was at one time, but coming back here is our main one. And so he is our FFA advisor.

45:45

He is probably the busiest person in the building and know I teach agriscience together.

45:50

So each of us teach a section of it. And that’s where we did most of the implementation of the satellite units.

45:55

This will very much translate nicely to biology. We do a similar kind of radish rates.

46:00

Experiment with them, where at the end of the first semester they have to design experiments, all, inks and all the scientific and engineering practices.

46:08

And so this lends itself really well to both things. And we’ll get into how all this works. Anyway, if you’re wondering why are we doing all these things?

46:15

We have kind of a unique context here at Waterford. So when I finished a PhD, I did a dual PhD in science education and environmental science.

46:23

My goal was to help as many teachers and students as possible, and I didn’t feel like publishing releasing papers was the way to do that.

46:30

So I actually went back to my old high school and asked if they’d be interested in hiring me half as a researcher and half as a teacher.

46:37

And so I kind of filled two roles here where I do teach multiple classes a day. Right now, because I’m filling in for a teacher who just had a baby.

46:43

I’m teaching full time, but usually I’m only teaching 2 or 3 classes a day. This guy behind me teaches probably about 17 classes a day,

46:50

and so his experiences are probably a little more relevant and valid. And we can talk about that in a moment. But the curriculum we’re going to see is taught by both of us.

46:57

And the idea is it’s open source. Anyone can get access to it. You can make your own copies of it and change it in any way you want.

47:04

The goal here is to create things that are not just classroom tested, but also classroom designed, and solely

47:09

reflect the realities of very busy people who don’t always have time to do everything from scratch. Right?

47:15

That’s the goal here. So again, this is yours to use however you want to use it. Everything we talk about can be found on my website that is Doctor Kohn.

47:24

If you go to Doctor Kohn.com, that’s a very different Doctor Cohn who’s a gynecologist in Florida. I don’t recommend it. It is educational. I don’t recommend it though.

47:31

But anyway, Doctor Kohn.org will take you to everything you need. And again the goal for this is to create things

47:36

that are not just aligned to research and academic standards, but also feasible for everyday teachers to do in their own classrooms.

47:44

The lesson we’ll be talking about is what we call our crops unit packet 1.3. And so what this does, the entire crops unit has four packets in it.

47:52

Guide students through how scientists conduct experiments using systematic inquiry in order to draw conclusions about what

47:58

things we can do to make crops produce more food. Simple as that. And so we’re in the third packet of this unit.

48:04

So 1.3 is the third packet of the first two unit. We’ll briefly talk about what the other two packets look like.

48:12

But in this particular packet they’re doing data collection. So they’re measuring plant height plant mass and NDVI

48:19

and using that to see if the treatment they applied to their radishes enabled more growth or productivity compared to the control.

48:26

Simple as that. We’re using a few things for this. We talk about careers. We won’t get into the details if you’re interested in finding more information.

48:35

Again this is linked. So up here on top where it says packet 1.3, that is a hyperlink that will take you to it.

48:41

But in the interest of time let’s dive it. So in packet 1.1 the first unit in the first packet

48:46

we talk about, we used to call this a scientific method in a sense. We talk more about scientific practices and why should we trust scientists.

48:55

And how do they get the information they have and how do they reach their conclusions. We start talking about that. So we have a couple exercises.

49:01

We also have them plant radishes. So they get two traits. One is their control that is untreated just standard potting soil and radish seeds.

49:09

And then one they have to apply a treatment to caffeine or adrenaline or extra fertilizer or something like that.

49:16

And then after a few weeks we measure the results to see if there was any difference. Packet 1.2.

49:21

We start to get to the atomic and molecular basis for explaining crop productivity. So we talk about conservation of matter and how during photosynthesis were turning

49:28

CO2 in H2O into glucose. And oxygen, and how that glucose is the basis for all plant molecules.

49:34

And it’s necessary for them to grow. So the more photosynthesis, the more plant growth, more food we have from a field

49:41

in packet 1.3. Now we’re walking them through how do scientists do what they do. So all of the standard things let’s first form our question.

49:47

So how do we do a research question. What are we wondering. Let’s turn that into our hypothesis. How do we make a prediction using an if then structure.

49:55

How do we do a rationale in order to justify why we think our hypothesis is going to be right and so on.

50:00

So very standardized, very scaffolded. And this way we’re walking students through what scientists actually do

50:06

in part two. Then we start doing data collection. So first thing we do is just measure how tall they got. Then we start getting into plant mass before we actually harvest the plants.

50:14

We have to do NDVI So we use the units, we collect our NDVI data, and then we start talking about which of these

50:20

is actually the more valid measure of plant growth and productivity. And so we get students into these questions as well.

50:26

Just because I collect numbers doesn’t mean I have something that proves or disproves an idea I have to talk about. Is this a valid measurement?

50:32

Is this a reliable measurement? Do I have enough data to form actual conclusions that are reliable?

50:38

And so we talk about all the core ideas and fundamental tenets of what makes a reliable research experiment in part three.

50:44

Then they’re going to find or draw their conclusions based on their data. They’re going to collaborate to determine if these are valid

50:51

and reliable measurements. And then we’re going to connect these two careers. So in the very first packet they have to talk about what is a plant related career they might want to pursue some day

50:59

and then get into well does this relate to it. Is this something that you still think you want to do. So on so forth.

51:05

That way we connected a little bit more to their lives. This packet has an appendix that we obviously added after the fact.

51:11

So that way we could incorporate more of the STELLA stuff. And so we’re getting into questions about what is in

51:16

how does this tell us anything about what plants are doing or how they’re performing, and how can we use this to draw conclusions.

51:22

So we have a brief reading. We do annotated reading strategies with it. We have them form hypotheses specific to STELLA and NDVI

51:30

And then we actually use the data and analyze it to form a conclusion. And that’s what that looks like. There was a slide you saw before, but this was the data from my class in fall.

51:38

And you can see the different treatments. Blue was our control, green was our treated radishes and gray was our calibration.

51:45

We can see with a little bit of variability at our calibration syllabi. That is life. And then we can work that into our explanations.

51:52

Well, we have limited reliability or validity in our data because we know our calibration was thrown off because we had change in conditions from clouds.

51:59

As we were collecting our data. We had to do it that day because that’s the only day we could do it. So that’s how it works, right? Like getting students into the reality that sometimes science isn’t perfect,

52:08

sometimes it’s messy, doesn’t usually look like a textbook, but that also prepares them to then better design experiments as they move forward

52:15

in the class. Finally, in packet 1.4, we started introducing them to science writing.

52:20

So they’re given a structure template. Everything they need to fill in is highlighted in yellow. There is a rubric that accompanies that.

52:27

That rubric is based directly on the scientific and engineering practices and the cross-cutting concepts and links.

52:33

It literally addresses every single one of them and what they do for every single project. So at the end of every unit, they’re going to do some kind of research like this.

52:41

They’re going to prepare a presentation using all the standard conventions in science for reporting the question hypothesis, rationale data, and so on.

52:49

And that’s the whole thing. So like I say, that is available on the website. All the curriculum is linked on the, menu bar on the upper right.

52:57

So if you use the QR code that will take you there or just go to doctor conduct or that will take you there as well.

53:02

Again, these are free for everyone to use. The idea is that you can make a copy for yourself, change it in any way you want, to make it relevant to your students

53:09

and that way you have access to things that might help you out and do more interesting things in your classroom if you’re looking for that sort of thing.

53:16

So that is all I have. Mr. Wicks, do you want to briefly talk about your experiences and then we can do some Q&A?

53:22

Fantastic. So I was watching on my computer in my classroom.

53:27

I figured I’d probably walk over. So anyways. Hi, everybody. My name is Mr. Michael Wicks. I am the other AG teacher here.

53:34

Like Doctor Kohn said, he was here before I was, but then he left and then he came back. And it’s kind of this ebb and flow we have with him here, but that’s pretty normal.

53:41

I’m finishing my seventh year teaching here at Waterford. And what I really enjoyed about the STELLA is obviously it’s

53:48

it was Craig’s big thing to kind of build them and put them together and do the initial work with NASA in the planning phase, but for my perspective of him coming to me

53:56

and showing me all this different stuff, it was unbelievably easy to use it in class. I mean, it was literally a click of a button,

54:03

and it couldn’t get much more simple than that. And we had really cool, unique sets of data that he had over here.

54:10

To just add on to our experiments. So like, obviously I was doing the Radish Race Lab since I started

54:15

because that was part of his old stuff from before, and traditionally it was just measuring height and it was measuring mass.

54:22

Nothing too special. But getting into plant sciences, adding NDVI adds that next level factor of okay, sure,

54:30

I think about in horticulture, sometimes I get these cool tall plants, but does that mean they’re the healthiest ones?

54:35

And then do they correlate that with other aspects just beyond that growth factor, which I thought was really fun for us to be able to add into there.

54:43

You know, and I haven’t played around with it yet too much, but I think the NDVI has really application in some sort of horticulture

54:49

or plant science class beyond just this component. It has applications in like in environmental science, natural

54:55

resources class. If you’re doing like a very, very dense something. Well I was going to show him our SSA field.

55:01

Oh our field. Yeah. Yep. Oh you did pull it up already okay. So yeah. So are you pull up the NDVI for what is our wonderful 16 acre field that

55:10

we have for our FFA, which actually I, I think I talked about this a little bit. Our leasing agency wants us to,

55:18

adopt a few more sustainable practices, which we already do, don’t tell and other things like that. But they also want to do things with,

55:25

water retention and organic layers and whatnot. So be really interesting to see. Like as we’re adopting, cover crop, we’re going to do winter wheat this year.

55:34

You know how those practices can actually change our old FFA field, but then how kids are,

55:39

you know, this is part of their saying this is their project. They’re excited to do it. I have a freshman who’s all over it.

55:45

Not sure yet. Another freshman, actually, but he was, you know, not just talking about, okay, we take NDVI but that does that correlate

55:52

with the soil horizons, the organic layer, does that correlate with all these other factors that he wants to get more involved into?

55:58

So what I think is great is they’re simple to use, but the kids do get excited about it, especially when you say

56:03

we’re using the stuff for NASA. They’re like, oh my gosh, you mean like the big space? Yeah, all that stuff.

56:08

They get excited and that’s really cool to see, especially when sometimes it’s a little hard to get kids into what you’re doing these days.

56:15

It’s really fun. So I’ve had a great experience with it. I definitely for us continuing to use it next year, and growing from it,

56:22

giving more opportunities. Like you said, the idea of hooking it up to a drone to fly it over, you know, different fields or do it like a survey of local farms

56:31

and things like that would just be, I think, a great experience for our kids. So I see a lot of promise with this.

56:36

And I’m really glad we got to use it. So thank you for your time. Oh, yeah. Fantastic. Thank you.

56:41

Thank you very much. Yeah. And to piggyback off of that, I would say so this is the Acres analysis program.

56:47

So again if you don’t have the color units you can get this right now if you wanted to. And you can just click and drag over an area

56:53

and we’ll tell you NDVI We did this as a bell ringer one day. And we never got to the content for that day.

56:58

Like, kids were so invested in this that we literally had a full hour of discussion about. So then they were like starting to look at their own property

57:05

or their like their neighbors and comparing. And they were like, well, this guy always does corn this way, and he always plows every year.

57:10

And let’s see what that looks like. And it was literally just this, like, I didn’t even do anything but just an hour of exploring, parking, discussing their ideas.

57:17

So I will, you know, piggyback off of that. Absolutely. This gets them engaged. They’re interested, you know, having the NASA logo like

57:25

kids fight over who gets to carry the briefcase, right? So like, so there’s a lot of engagement that comes from this

57:31

and it gets them thinking much more deeply. In the systems level. So like, you know, photosynthesis can be pretty straightforward.

57:38

But we start asking things like, you know, if you look on the screen here, we can see a big dip in August. And yeah, and then it rises again.

57:44

Let’s make some predictions about that. Well, it turns out that, you know it’s here says August 17th at rebound.

57:49

It turns out it rained here on August 15th. So why would that change in NDVI So we’re getting the kids to think

57:55

much more systematically, much more in terms of making connections across different kinds of content and at different scales and systems.

58:03

And so, absolutely, there’s a whole bunch of options and opportunities to get kids engaged and thinking more deeply through this opportunity.

58:11

Fantastic. That’s that’s great. Yeah. And I’m going to make sure that the acres folks know that you,

58:17

you’re using their stuff because then they’re going to be very excited about that. We do have a few questions. Yep. In the chat.

58:23

And so, the t, I believe it’s, and excuse me if I pronounce it incorrectly.

58:31

Hedi Baxter Laufer, Hedi Baxter. Laufer, asks if you were to use Wisconsin Fest plants

58:39

as your model organism instead of radishes. Learners could include number of days to flowers, number of flowers,

58:46

and number of seeds and their data collection carrying over into understanding reproductive success and linking that to

58:54

sustainability and evolution. First, plants are amazing, so I want to put out a plug for that.

59:00

So Hedi and I actually work together when I was working at the Great Lakes BioEnergy Research Center. So absolutely, so much more you could do with fast plants.

59:07

We had just happened these radishes, because we have like a bajillion of them. And it’s just kind of what we were using for a while.

59:14

But yeah, I would like to get to the point eventually where we could be, more systematic and Wisconsin fast plants would allow you

59:20

to go into much more detail, in depth with those kinds of questions. Fantastic. Okay.

59:26

Next question from, Shan Gordon. Did radish, the radish you treated with caffeine contain caffeine

59:32

in the root/bulb? Would it wake you up like a cup of coffee? Yeah.

59:37

So what we found was that radish, actually, or sorry caffeine actually inhibits root growth in radishes.

59:43

So our conclusion for that was that the main reason growth was impaired

59:48

is because they’re not developing roots to the same extent that the control radishes were.

59:54

So don’t know that for sure. We have to look into that further. Good research always brings up more questions, but that’s our premise for the moment.

1:00:03

Maybe we’ll make it taste good. I don’t know, I’m just kidding. And so from Keith,

1:00:09

is CO2 measuring, a function of STELLA? Well, Keith, we have the, STELlA-AQ, which measures

1:00:17

not only CO2, but, particulates, especially in the 2.5 and the 10 and barometric pressure and all that sort of stuff.

1:00:24

And the newest one, the 1.2, and I don’t have the, plug in with me at the moment actually also measures methane.

1:00:32

And we’re also looking at nitrogen dioxide and various other things to measure. So that’s where it is, like, you know, what do you want to measure?

1:00:39

All right. The next one, can you share the NASA Acres GEE API.

1:00:47

So maybe something I can plug in our chat here. I believe so you should be able to, let’s try that.

1:00:54

So there we are. There is the NASA acres program is awesome. Really great example.

1:00:59

So I plugged in my farm. So my farm, it’s this green little oasis in the midst

1:01:04

of the very conventional green and or sort of conventional orange and yellow. So that’s mostly because we have a woods and typically

1:01:12

forest, have higher NDVI But yeah, it’s a really great tool. So you can like, drag it over your home, you can drag it over test areas.

1:01:19

One thing that I had shown in our presentation was KBS, KBS is Kellogg Biological Research Station.

1:01:27

That’s actually where I was for part of the time when I was doing my PhD in environmental science.

1:01:32

So it is the longest ongoing ecological research experiment in agriculture.

1:01:37

It’s been going on since the 80s, and all they really do is use the same method over and over for these different plots.

1:01:43

So the blue is going to be business as usual. That’s conventional agriculture tillage, no cover crops, lack of crop

1:01:49

rotation, that sort of thing. And then red and pink are going to be more sustainable methods, things like no till cover crops, more rotation, things like that.

1:01:59

So and you can see how well it lines up with that. Right. So that’s actually the agro science fair project that Cheyenne was talking about,

1:02:05

where they’re measuring average NDVI for the last growing season. For each of these plots to see how that affects photosynthesis.

1:02:12

So super cool stuff I highly recommend is really cool. So, it actually kind of reminds me of a fuze box from a car,

1:02:19

from seeing it at this distance. But so another one from, that I mean, again, maybe I’m saying the wrong Hedi.

1:02:27

The Hedi or Hedi? Eddie, Hedi. Okay. From Hedi, are you able to use STELLA to measure,

1:02:34

anthocyanin, concentration in leaf and stem tissue?

1:02:39

That’s a good indicator of stress in fact, is part of what scientists and NASA’s Leaf project will be looking at as an indicator of stress in first, plants

1:02:47

grown on the moon would still be able to quantify that pigment concentration. That’s another variable to compare.

1:02:59

I don’t know, I don’t know. Yeah. Okay. I was I was letting the person go,

1:03:05

but I don’t think I mean, it wouldn’t be that specific. You would probably see differences in.

1:03:13

I guess it would depend on what wavelengths of light that would pertain to.

1:03:18

So I guess possibly it could, if you know that anthocyanin

1:03:25

had an effect on a particular band of wavelengths, you could see if there was a difference in stress plans versus not stress plants using those wavelengths.

1:03:33

I don’t know how that would work, though. Specifically. But potentially,

1:03:39

I mean, that’s the thing is, like, you could compare data and see, well, is there a significant difference between plants in this group versus that group at these different wavelengths?

1:03:48

And then start making inferences from that? Sounds like Hedi needs a, it needs a still to play with

1:03:55

the excellent, and, that’s the end of the questions at the moment. Does anyone else have any more questions?

1:04:01

Give you a few seconds to type it out. It’s not I mean, that was a fantastic presentation.

1:04:09

And again, you’re always great and it’s always great to chat with you. And it was fantastic to see the students and Doctor Wicks right

1:04:15

in the background and Mr. Wicks not doctor doctor Mr.. Did.

1:04:21

Yeah. No it was fantastic. Again thank you very, very much. Let’s see there. Okay.

1:04:28

And then Hedi wants to ask you more about anthocyanin as well. Offline.

1:04:35

But yeah. Okay. All right. It looks like, we’re good to go here. Oh, there we go.

1:04:41

What sorts of issues did you run into making the, the 1.1 studies? Yeah, yeah, in a nutshell.

1:04:47

And Luke kind of alluded to this, too. So, and this might come as a shock, but there is a difference

1:04:52

in the capability for precision between NASA engineers and high school students. And so, like with the casing, Luke had kind of mentioned

1:05:00

where it’s just difficult to, you know, you so, for example, we bought wires that were larger

1:05:06

because the 100 millimeter to Q2, the, well, yeah, I’m getting to both, but okay.

1:05:11

So like for this one, like you have to put the wires in exactly the right spot to get it to close. Right. So this was still feasible for the 1.1.

1:05:19

It was soldering that you kind of had to know where the soldering was going to go and how much to do. And I’m I don’t know anything about soldering, to be honest.

1:05:27

And our, our kids who are working on it were pretty good kids for that, but just a bit beyond their grasp.

1:05:35

You know, for them, I think they weren’t expecting the challenges they got. And then they got busy with AP exams and those sorts of things, and it kind of fell by the wayside.

1:05:42

So I think it could be done. You just have to know that there’s minimal room for error on those, especially when it comes to the soldering.

1:05:49

So I don’t want to discourage anyone from doing it. I would just recommend start with the Q2 get comfortable with that,

1:05:56

and then work your way up from there. If you’re interested in DIY stuff, if you’re planning on doing something like CO2 or air quality, that still is not going to help you with that.

1:06:05

You would need something like the 1.1 or the 2.0. So again, I guess part of this is knowing what you want to do.

1:06:11

But again, for us, the Q2 is a feasible entry point. And based on our experience, that’s where I would recommend starting.

1:06:18

Excellent. Yeah. And it is a good starting point. The soldering in the 1.1.

1:06:23

Yeah, was a bit more challenging for sure, especially the screen. And that’s one of the things that we fixed and, the, or I should say Paul

1:06:31

fixed in the 1.2, and it’s very elegant. And we, just did a nice little, video

1:06:39

with Paul, and he’s talking about, like, engineering and elegance and all that. Anyway, but it’s,

1:06:45

fantastic. Thanks again. Is there any other. I don’t see any other questions at the moment.

1:06:53

So if, if that’s everything, again, thank you very, very much for this.

1:06:59

And we really appreciate you. And, can’t wait to talk to you again and see, you know, how things are going.

1:07:05

What else we can help out with? Appreciate it. Have a good night. Take care.

1:07:10

Bye, everyone. Thanks for joining us.