• Precision Ag Reviews

Podcast: 14. Alysa Gauci - On-Farm Research Data to Drive Decisions, Part 2


One of the best ways to learn about new products or methods on your farm is to create an on-farm trial. But how do you know how to set it up and how much area is enough to really understand the impact of that trial? In episode 14 of Precision Points, I sit down with Alysa Gauci, who is pursuing a dual master’s degree at The Ohio State University, to discuss her research and unpack our questions about trial size.


The main question Alysa is hoping to answer with her research is, “To what scale or block size can yield monitor data be used to support field-level research?” According to Alysa, around 80% of growers that have precision ag equipment are setting up on-farm trials and yield monitor data is a key data layer. As of right now, however, there is no standard or protocol for the size of trial needed to have confidence in the data being collected.


The research she is working on is set up on 12 acres planted to corn in South Charleston, Ohio. There are six different lengths in the trial – 12.5 foot, 25 foot, 50 foot, 100 foot, 200 foot, and 400 foot. In the field, there are intentional yield differences created by two different treatments: one has no nitrogen and the other has 180 lbs. of N. In the aerial imagery, the trial is very visible in part to the extreme differences in management style. This will allow for clear information returned at the end of the season when both a commercial and a research combine harvest the plot. The two harvesters are going to be used to ground truth and provide a second form of measurement on the trial.


There is inherent variability in all field trials due to different soil types and Mother Nature. To guard against this, there are three replications of the trial across the field. They have also taken into account buffer zones and added a row in between treatments. They applied the nitrogen in a serpentine method – since they were applying in such short distances – and added more buffers on the side to ward against compaction skewing their data.


Alysa has been able to spend a lot of time in the field this summer, out in the trial. She anticipates being able to know where the plot line is and is pretty confident that the 400-ft. plot is going to have more reliable data than the 12.5-ft. plot. However, where the data flatlines and at what resolution is the exciting information we are waiting for upon harvest. To follow along with this research project, check out @OhioStatePA on Twitter.


What yield monitor do you use? Leave a review here.

Transcription:

Host: Morgan Seger

Guest: Alysa Gauci, Master’s Student at The Ohio State University in Agricultural Engineering and Horticulture and Crop Science


Morgan Seger: (00:22)

Welcome back to Precision Points – an ag tech podcast from precisionagreviews.com. I'm your host, Morgan Seger, and in each episode, we strive to bring you unbiased ag tech information and ideas. And on our last episode, we had a conversation about on-farm research with Dr. John Fulton, and he hinted that they were working on some research themselves about what growers need to do to actually quantify and have confidence in the data they are creating out in their own fields.


Morgan Seger: (00:53)

So, to follow up last episode, today I have Alysa Gauci – who is pursuing a double master's degree at Ohio State – to talk through the research that she is working on, looking at different plot sizes and lengths to determine what size your plots need to be, to have confidence in your data and to have accurate data. So we all know we're trying to create things out in our field that can help us make decisions for the following year. She's breaking down for us what they are doing to make sure that that is possible.


Morgan Seger: (01:27)

Welcome back to Precision Points. Today on the show, I am joined by Alysa Gauci, who has been working on some harvest data research that John Fulton was telling me about in the last episode. So we are excited to have you on Alysa. Thanks for joining us.


Alysa Gauci: (01:42)

Thanks for having me on, Morgan. I'm pretty excited to have the opportunity to be on, yes.


Morgan Seger: (01:48)

Can you get us started...before we dive into the data, share some of your background and how you got interested in precision ag?


Alysa Gauci: (01:56)

Of course. So I grew up in a really small town in south Alabama and so passing tractors on the way to school and just always being around agriculture. It's always been a part of who I am and I knew, upon graduating high school, that I didn't want that passion to stop. So I got my undergraduate degree at Auburn in Biosystems Engineering. And then, upon graduating from there, I also knew I wanted to continue this passion that I had. And I'm currently doing a double master's here at Ohio State in agricultural engineering and also in horticulture and crop science. I'm starting my second year on that.


Morgan Seger: (02:34)

Okay. Well that sounds like no small feat. How has that been going with COVID and everything kind of forcing you to maybe be more remote? Has it changed since a lot of your work is in the field?


Alysa Gauci: (02:46)

It's definitely been different. We've had to plan our projects a little differently and our field work's been a little bit different, just fewer people in the field and just a lot more planning and protocols to make sure we all stay safe and healthy.


Morgan Seger: (03:02)

Yep. That's the main thing right now is just making sure everyone stays healthy and that we can continue to progress and move forward with these ideas we have. So can you share what you are working on? I know when I wrapped up with my conversation with John Fulton last week, he had to show me an aerial image of your trial. And now I see it going around on Twitter. He's pretty excited about it. So what do you have going on?


Alysa Gauci: (03:29)

Oh, yeah. Our whole research team is pretty excited about this project. So, just in short, we're really trying to answer the question of what scale or even what block size that yield monitor data can be used to support field-level research. And this is super important because over about 80% or so of our farmers using precision ag, they conduct on-farm research and that yield monitor data, it serves as one of those key data layers. And for that on-farm management decisions and just in precision ag, in general. But as of right now, there's not really any standard or any protocol or information about the size of plots that we can have before conducting these on-farm trials. So there's studies that are five-by-five meter grids, or there's just a big range, but we just don't know how good or how accurate that data is represented between those different sizes.


Alysa Gauci: (04:26)

So we had the opportunity to kind of look at those different sizes from 12-and-a-half-foot, ranging up 400-foot. And so that's kind of given us the opportunity to see as, we increase plot size, how's that data going to vary? Is it going to be accurate throughout or when kind of cut off or when does it taper off; where we can have the confidence to know that our data is accurately represented? We can be confident in our results and we can share that to our growers and our researchers too.


Morgan Seger: (05:03)

Yeah. So it seems like, as technology has progressed, we've gotten more and more precise, but our equipment has also gotten larger and larger. So, do you think that that type of information is going to play an impact on how your research turns out?


Alysa Gauci: (05:19)

For sure. So right now, there's so many different types of equipment. There's different sizes. There's a lot of diversity within precision ag, just within the agricultural industry, but it all goes down to how accurate and what confidence can we have when we do these trials and just to be able to share those results and be confident that data is represented.


Morgan Seger: (05:48)

Okay. So this equipment is obviously getting much larger and our data should be getting better, but are there things that you see or that you've noticed through research, like watchouts, things that could be happening in the growing season that could be affecting our data or things that growers could try to work around to make sure their data is as good as possible?


Alysa Gauci: (06:10)

I think the first step in any of precision ag or using any piece of equipment is just to make sure it's calibrated correctly. I know we talk a lot about that – precision ag and a lot of our research team – we really try to push our farmers and growers to make sure that the very first thing in season, whether it's combine plan or whatever part of the season we're in, just to make sure that you take the time to run through. It does take a little bit of extra time, which we know is really valuable, but you know, that can save a lot on the tail-end of it. Just that calibration procedure.


Morgan Seger: (06:52)

Sure. So when you're looking at your research specifically, like I said, we've seen the aerial image and the pattern looks really interesting. Could you walk us through how you got the idea to set it up like that and what exactly you'll be looking at or trying to extract?


Alysa Gauci: (07:09)

So I have about 12 acres out at the Western Horticultural Research Station in South Charleston, and we have the six different lengths, so 12-and-a-half-foot, 25-foot, 50-foot, 100-foot, 200. And then our longest plot is 400-feet. And so, out in the field, we created intentional yield differences. So we did that by doing no nitrogen versus 180 pounds per acre. So more of a higher nitrogen and aerial imagery, that's kind of the doses that you see that creates that checkerboard pattern.


Alysa Gauci: (07:45)

So, whenever harvest comes, we'll be able to run a field combine through and hopefully we'll see the step function of the data. And then, also, I think another really cool part of this study is we'll also be running a plot combine room, is that kind of be able to ground truths and you to have a second form of measurement for this study and compare that, against the weigh wagon at the end of harvest.


Morgan Seger: (08:10)

Okay. So do you think that this would help companies that have plot combines figure out what that length is and growers that are using commercial combines, or is that really just kind of like your check at the end of the season?


Alysa Gauci: (08:24)

It's more so a check, but I think the overall goal for this project is to help guide in the process of creating a standard for that minimal plot size or how fine of resolution can we get and saw the confidence that the data that we're pulling from the yield monitor is accurate of that. If it's a 15-meter or five-meter plot, what size do we need to be able to accurately represent that? So I think it can go for both researchers and industry, as well as the growers that are conducting those on-farm trials on their own personal farms.


Morgan Seger: (09:05)

So do you have any early predictions of what the research is going to say, or is that not what we do when it comes to field research?


Alysa Gauci: (09:14)

Luckily this field I've been able to go out there, just about every other week and can keep checking on it and may be able to fly a drone out there and get the aerial imagery. And so far it's looking really promising. We haven't had any big errors or issues come up, thankfully. Because it's been a really intensive study having those smaller plots and a ton of flagging and just a ton of preparation went into this project and which is always good to be able to go out there and check on it. Hopefully we'll be able to tell where that flat line is. But as of right now, that 400-feet is most likely going to have a lot more reliable data than the 12-and-a-half-foot plot. But that's part of the exciting aspect of the study is at what resolution does that kind of start to flat line.


Morgan Seger: (10:07)

Yep. So then, when we're dealing with Mother Nature, there's obviously a lot of other variables. How are you taking into account just like natural field variability and possible weather variability and things like that?


Alysa Gauci: (10:21)

Right. So part of that, we have three replications out there across the field. And so, just having the replications, that kind of helps minimize the impact of the variability. We've also taken into account buffer zones. So, in between treatments, there's a row of buffer on each side. And then whenever we were applying the nitrogen, we had to go more on like a serpentine pattern through the field, just because it was on/off as we were applying in short distances, like the 12-and-a-half-foot, the 25-foot plots. So, to make sure that we didn't cause any variability from compaction or things like that, we created additional buffers on the sides too. So hopefully between the buffer zones and then the buffer rows, that'll help minimize that variability too.


Morgan Seger: (11:13)

Sure. And then, this may be a stupid question, but do you think this will be able to reflect appropriate zones for all crops? Because we're mostly just looking at the equipment or do you think you'd see any variation if you're looking at soybeans or wheat?


Alysa Gauci: (11:27)

I think there would be some variation. I think having corn to start with is a great place to start. We're also looking at maybe doing a soybean trial next year. I think it'll vary a little bit, but I think the overall pattern will give us a good idea of where to start for this general idea of trying to nail down what plot size we can recommend for on-farm research.


Morgan Seger: (11:52)

Yeah. Because I just, thinking through, like, with soybeans, like obviously you can play with potash and different things, but I didn't know if you would be able to draw out as conclusive of information as you probably will be with corn, having no nitrogen compared to 180 pounds of nitrogen.


Alysa Gauci: (12:07)

Right. Yeah. I think for soybean, for the site to work, we would probably change the planting rate. So we would do a low seeding rate versus a really high seeding rate as we do with the nitrogen, for the corn, just a little bit different for the soybean.


Morgan Seger: (12:22)

I see. That would make more sense that way you get that bigger response you're looking for. That makes a lot of sense.


Alysa Gauci: (12:29)

Yeah. Just really kind of looking at the crop to figure out how we can create those intentional yield differences in the field that way, as we go through and we get the data, we'll know what part of the field we're at and we'll be able to compare.


Morgan Seger: (12:44)

So one question that I like to ask people who are on the podcast is, if there is one technology, whether it's in agriculture or not, that you are most excited about?


Alysa Gauci: (12:54)

Well, that's a tough question. The technology is always just, it's constantly evolving. I don't know if I have one in particular. I think I'm most excited about the progress and about the precision that we're able to have with this new technology and just the savings, the cost savings, the input savings, just how we're really starting to be able to now nail down precision agriculture and the improvements that we see year by year from the studies that we do. I think that's personally what I'm most excited about.


Morgan Seger: (13:31)

Sure. How they all come together in general to help us progress towards better agriculture. So what's next for you, maybe soybean research next year or what's your plan?


Alysa Gauci: (13:46)

So obviously harvest is coming up. So this project will be wrapping up over the next few months and then we'll be diving into more of analysis. And then after that maybe a soybean trial with this. I'm hoping to stay on for my PhD. So there'll definitely be some more opportunities to continue this kind of work. And depending on the results we get from this particular study, I think that can also open the doors for similar studies in the future, as well.


Morgan Seger: (14:17)

Gotcha. Well, you have some big goals and I'm excited to watch as this all kind of unfolds. So if someone is interested in following along with your research and the data that you're going to get this fall, where would you recommend they go so they can find that information?


Alysa Gauci: (14:34)

As of right now, they can contact me directly. I'm more than happy to share – sorry my dog's barking in the background – but I'm more than happy to send any current updates or discuss the research further if anybody has any super specific questions or anything like that. As of right now, that's probably the best way just because we're kind of starting to get ready for harvest within the next month.


Morgan Seger: (15:05)

Okay, Great. I can link out to your email address then in the show notes. So if anyone wants to reach out and see what's going on, you can reach Alysa there and will this be part of the book, the eField's book that Ohio state puts together?


Alysa Gauci: (15:21)

It is still to be determined on this specific trial may not end up in eFields this year. Okay. To be determined.


Morgan Seger: (15:30)

To be determined. So more to come on that. Well, I appreciate you taking the time to chat with us about your research and I wish you all the luck as you continue through this fall.


Alysa Gauci: (15:41)

Thanks, Morgan.


Morgan Seger: (15:43)

Well, thanks to Alysa for taking the time to be on the podcast and share that information with us. And we cannot wait to see her research at the end of harvest. And thank you for tuning into another episode and spending this time with us. If you like what you're hearing, please hit the subscribe button and leave us a rating and review that helps other growers, like you, find our information. I also encourage you to check out precisionagreviews.com. We do two things on our website. The first thing is we have our dataset of grower-sourced reviews. So basically what that is is a list of different technologies that we're using in agriculture and what growers who have used them have to say. The good, the bad, what their experience was like and their rating.


Morgan Seger: (16:24)

If you are using precision ag technology, we would love to hear what you have to say, as well. If you're considering a new technology, we hope this is a really good spot for you to come and get some unbiased information about other people's experiences with those products to help you make the best decisions for your operation. We also have a blog that we post, not only the show notes from each episode of the podcast, but we also dive deeper into conversations with growers and manufacturers about that technology. So if you're looking for a bigger explanation than just what you're seeing in the reviews, you can go to the blog and find more information about different technology there. And, until next episode, this has been the Precision Points podcast. Let's grow together.

Host: Morgan Seger

Morgan Seger grew up on a small farm in northwest Ohio before studying agriculture at The Ohio State University. She spent 10 years working with ag retail, specifically in ag tech, before coming to PrecisionAgReviews.com to host Precision Points Podcast. She lives and farms in western Ohio, with her husband Ben and their four children. Morgan has her own blog called Heart and Soil where she talks about her experience farming, gardening, and raising her family.



Guest: Alysa Gauci

Alysa grew up in a small town in south Alabama and, although she did not grow up on a farm, she grew up around farming – passing tractors on the way to school. She was very active in FFA and identified agriculture as being a part of who she is. She completed her bachelor’s degree in Biosystems Engineering at Auburn University. During her time at Auburn, she was heavily involved in research which opened the door to furthering her education. She is now at Ohio State, pursuing a double MS in Agricultural Engineering and in Horticulture and Crop Science. Her current research is focused on precision agriculture, specifically determining the scalability of yield monitor data for on-farm research.



Growing trust in agricultural technology, Precision Ag Reviews is a non-biased, independent resource to help farmers make decisions about precision ag equipment.

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