▶Determining In-Season Nitrogen Availability: Indicators of Nitrogen Need

0:05
All right, thank you for that introduction, Chris, and thank you for everyone for joining us here on this webinar.

0:14
Yes, indeed, I’ll be talking about in season nitrogen availability. Before we really dive in, I just want to maybe preface my talk by saying three things.

0:26
So, number one is when we’re talking about nitrogen availability, here, for this particular talk or the studies that I will be highlighting here, we’re specifically talking about manure.

0:38
And that’s one thing and number two is I do want to acknowledge my collaborators on this, right? People who have contributed in some way, especially my graduate student, Michael, who is basically running this project.

0:54
It’s an ongoing project. So, what I’ll be presenting here is just preliminary. It’s just one year of data and it’s hard to make some conclusions from that work.

1:04
But anyways, we’ll just talk a little bit about that. And the other collaborators, including my colleague Jingyi, who will be presenting after me, Dr. Huang, and a post doc that I’m sharing with the Ruark lab has been instrumental in this work.

1:24
Also, I do want to say, OK, why, right?

1:27
Why is this in-season nitrogen availability such an important topic to talk about?

1:32
Well, first of all, we want to have an in-season nitrogen availability estimate somehow in order to adjust our nitrogen rates, right?

1:43
We want to avoid over applicating, over application of nitrogen or under application of nitrogen.

1:50
So that in season, nitrogen availability is definitely important and certainly for manure as a manure nitrogen availability is highly variable, right?

2:00
So definitely…it’s definitely an important topic to look at!

2:06
In thinking about this topic and thinking about the direction for our research as a lab, you know, I came across this worksheet initially developed out of the University of Minnesota.

2:20
And it’s a simple worksheet consisting of a couple of questions, right?

2:24
And they have a scoring system.

2:27
So each, question is assigned a number of points.

2:30
And at the end, right, you have a total number of points.

2:32
And depending on your total number of points, right, you have a certain interpretation, right?

2:37
Apply no nitrogen, apply some nitrogen or wait and do this again in a couple of days, right?

2:42
And so, but that’s not the point.

2:44
The point here is the type of questions that are being asked, right?

2:48
So if you look carefully at the questions, the questions have to do with things like temperature, moisture, right?

2:55
How the crop looks, right?

2:57
So appearance of the crop, right?

2:59
And then based on that, together they look at this and come to an interpretation, right?

3:05
And that is exactly the sum of really what this research that our lab started doing, is really looking at, right?

3:13
We’re trying to look at all these different variables and then come to a conclusion to inform our nitrogen rate, if you will, right, so or nitrogen demand, if you will.

3:25
So that is what we’ll be talking about in the next few slides here.

3:30
So in general, right, so there are some traditional approaches to estimating nitrogen availability or a crop nitrogen status, right?

3:40
So we have the soil nitrate test, right, an example of which is the pre-sidedress nitrate test (PSNT).

3:46
We have tissue testing just to see where we’re at with your nitrogen levels in the soil, right, if you’re deficient or not.

3:54
We also have crop canopy sensors, satellite data that has been used to assess overall crop health.

4:01
But what we have also seen is that institutions have used those data to develop algorithms for in-season nitrogen application, right?

4:12
And, the way it has evolved over time is that people are saying, well, yes, that’s great to have crop canopy sensors giving me the NDVI or the or the Red Edge (NDRE).

4:24
But we need more than that.

4:25
We need to look at the surrounding environment.

4:27
We need to look at weather and solve variables as well.

4:29
And that is how this technology has progressed over time going back to the pre-sidedress nitrate test.

4:38
So we do recommend it, right.

4:41
It’s an amazing tool that helps us to estimate in-season nitrogen availability and adjust our nitrogen rates based on that, based on that credit, right, that you, you get from whatever mineralized, right. Whether that is manure, the organic matter in the soil, your previous crop legumes, right.

5:00
And then make that adjustment based on what you get.

5:04
However, there are limitations, right?

5:07
There’s a time restriction in terms that between sampling, sending your soil sample in, getting your results, making that application, right.

5:18
You only have a very short window to make that adjustment, right?

5:23
That’s one thing.

5:23
The other restriction that we have with this it’s labor intensive.

5:28
So what our work is looking at is that is there a faster way?

5:31
Can we do this faster, right?

5:33
Can we come to a decision earlier, faster, right?

5:37
So, so that’s that. When we look at sensor technology, it’s been around for especially with the active sensors.

5:47
I look through literature, right, and where you really see an uptick, an increase in canopy sensor technology used in nitrogen management in particular, you really see an increase in the late 90s, I would say early 2000s.

6:05
So it’s been around for between what, 20 and 30 years now, right. That it’s been used specifically in nitrogen management, especially the active sensors. The way it has evolved, I mentioned this before, but I want to reiterate that the conclusions from those studies were like, ok, it’s very effective, especially in wheat, but we need more.

6:27
We need to look at that environment, soil, weather variables and so on in order to include those in our calculations of the nitrogen rate.

6:36
The fancy word for it is algorithms, algorithms that have been developed to calculate that nitrogen rate.

6:43
All right.

6:45
Has that technology worked?

6:47
Yeah, right.

6:49
It’s been effective adoption.

6:52
This number or this particular paper looked at numbers for the reduction in fertilizer inputs.

6:59
They also looked at nitrogen use efficiency, Aula et al. 2020.

7:04
And what they saw is, yes, there was a reduction in the nitrogen rate that was applied when sensor technology was used, right.

7:11
And then also they found a higher nitrogen use efficiency.

7:15
So it works, ok, but then where do we go from here?

7:21
I want to highlight two particular studies that we looked at in our lab.

7:29
And again, remember this is just one year of data and we’re still looking at the data, but I’ll present some preliminary or initial data that we collected.

7:41
So this particular study was on farm.

7:44
We did this in collaboration with a farmer that is part of the NOPP, Nitrogen Optimization Pilot Program.

7:52
And what we did there is basically looked at a couple of parameters or variables rather. We looked at electrical conductivity, water content, and soil temperature. And we’re basically what we’re doing here.

8:06
The objective is, is to look at proxies, right, that we may use to estimate nitrogen availability.

8:13
Okay, we’re starting here with manure, but what I’m talking about is applicable to yeah, different sources of nitrogen, including fertilizer nitrogen.

8:24
We’re starting with manure because that is really a big part of my research here, understanding that nitrogen availability, in other words, mineralization over the season.

8:34
All right, and then we want to compare it right?

8:36
We want to compare that to…how does it compare to using something like the PSNT, the pre-sidedress nitrate test. And the bigger goal here, right?

8:46
Where, where do we want to go with this?

8:48
Because you know, technology is great, but somehow we need to translate that into actionable steps, things that farmers can actually use, right?

9:01
So what we want to do with this is develop models that help us predict nitrogen availability from manure and therefore nitrogen need, okay? So that, that’s where we’re going, but that’s, so the bigger picture, that’s what the bigger picture here is.

9:18
And so what we did here, again, this was part of that NOPP, which means that the farmer had their research going right.

9:25
And what we did is that we came and we threw our research questions on top of this, this already ongoing project, if you will, right.

9:35
So they had their manure, no manure blocks and different nitrogen rates.

9:42
What we did is that we installed our soil sensors in the 0, 100, and 200 lbs. of nitrogen per acre.

9:48
What the soil sensors read were things like temperature, moisture, electrical connectivity.

9:54
In addition, we flew our drone.

9:57
We were still in training and using our drone, so we had to go to retrieving satellite data instead.

10:05
But what we looked at in particular, in this case is the NDVI.

10:11
All right, So the soil sensors, they were installed at around V4 growth stage.

10:17
We collected soil nitrate samples around V6.

10:22
All right, so looking at the results and I’ll walk us through these results and be patient with me.

10:27
I’ll bring it together for us in the end, but it will go step by step looking for first of all at the yield right.

10:34
Clearly if you compare the right to the left here of your screen where we had manure was certainly outperforming where we had no manure.

10:45
Okay, so that’s, that’s an interesting finding.

10:48
Was it in line with what we hypothesized?

10:51
Yes, right.

10:52
We, we did expect manure to outperform synthetic nitrogen or fertilizer nitrogen.

10:59
The other thing that I want to point out, however, is that we see something interesting, right?

11:04
If you look at the curves, right, especially when you look at manure, it’s supposed to be a curve.

11:10
What do we see?

11:11
Almost a straight line.

11:12
What does that tell us, right?

11:14
We had probably a lot of mineralization of nitrogen happened.

11:17
So any additional nitrogen did not result in a, you know, a sharp increase in the yield, right.

11:24
So that’s the first thing that I want to point out one of my first two points here from this slide.

11:32
The other thing, so if we look at specifically, right, the treatments that we picked to install our sensors and we focus on those right, clearly we have higher yields on the left, so where the manure was applied. On the right, we see lower yields where it was just fertilizer nitrogen.

11:51
Now we understand that the difference between the columns on the left versus the right, it’s not only because of that nitrogen, we must realize that, right, because manure is doing a lot more for us than just delivering nitrogen, right?

12:08
So there’s additional effects that simply looking at this chart do not explain it.

12:15
We don’t see it, right?

12:16
It’s not just the nitrogen difference.

12:18
So let’s keep that in mind as we move through this, right.

12:22
But yeah, clearly we see a benefit of manure.

12:26
We again see no significant response to any additional nitrogen, especially on the manure side of things. With the no manure side of things, yeah, you see a little bit of a bump when you apply 100 lbs. of nitrogen per acre, right?

12:41
So, so that’s what we see here.

12:45
So the NDVI, right, an index a vegetation index that has been widely used to develop algorithms that help us calculate in-season or variable rate nitrogen.

12:59
So, what we see here, we looked at NDVI versus these three different treatments.

13:05
What you see is as we expected you could actually walking through the fields, you could see that there would be a difference, right, manure from no manure.

13:13
You can clearly see higher NDVI values there for the manure treatments.

13:20
All right.

13:21
So, here we looked at nitrate in the soil, we pulled nitrate samples and as we expected higher nitrate levels and the manure treatments which again we expected that right to see that trend.

13:39
So, was there a relationship between nitrate in the soil and yield?

13:45
Yes, there was.

13:47
There was a clear difference in or at least a relationship between soil nitrate and yield.

13:57
Now another variable that we looked at was electrical conductivity.

14:02
Now electrical conductivity is, what we learned from that, is basically it tells us something about the ions in the soil solution, ok, the ions in the salt solution, the more ions you have, right, which could include nitrate and ammonium and all that, but a lot more ions.

14:21
It’s not just ammonium and nitrate and what not. It’s, a lot of ions.

14:26
And what we expected to find is that manure would have higher levels of or would have the higher values of electrical conductivity, again, which tells us something about the chemistry.

14:38
It tells us something about the mineralogy of the soil.

14:43
What we did not expect is to find no difference or no statistical difference.

14:48
You see a numerical difference between where you applied manure and no manure.

14:52
You see a difference, right?

14:55
We did expect more of a difference I should say, which we did not see here.

15:00
And again, a lot of other factors could be playing here because you’re not only looking at the nutrients, right, you’re looking at a whole lot of other ions including mineralogy of the soil itself.

15:12
There was no strong relationship between electrical conductivity and yield.

15:18
As you can see in the chart here on the left. When it comes to salt temperature, we found something interesting.

15:28
We found basically, so what you see here is a relationship, right?

15:33
It’s a negative relationship.

15:35
You see that as the soil temperature increases, right?

15:38
We saw a drop in the yield.

15:40
Not just that, if you look at the dots up there, right at the top part of the graph, that’s all manure.

15:49
That’s all manure.

15:51
Those are my manure treatments.

15:52
And what you see there is that.

15:54
So if I applied manure, what do we learn?

15:58
The soil temperature was cooler.

16:01
So it’s almost as if the manure that was applied kind of became like a protective layer barrier, right, to keep the soil cool, right.

16:11
So that was an interesting finding that negative relationship, not only, but to find that manure was keeping the soil cooler.

16:21
And you’re like, ok, Natasha, that’s a lot of variables, right?

16:24
A lot of data that you’re showing us, but where’s this really going?

16:28
You know, as I said it, it’s kind of hard to just one year data to go dive deep into the data, we are collecting a second year this year.

16:36
And, you know, you’re on here, right?

16:40
If you’re interested in collaborating, definitely contact me.

16:43
But what we’re looking at with these variables, let’s not forget the bigger picture here, right?

16:48
We want to be able for a producer to go in one day, right?

16:52
Have the standard data, plug it into some calculator and what it would spit out is your estimated nitrogen availability, right?

17:01
And, and so that, that’s our dream here.

17:03
So what, what have we decided as a group, right?

17:06
We will continue looking at this paying specific attention to those variables that are promising, right.

17:14
We’re continue to work with the NDVI as you can see here, this is a correlation that we ran right high correlation with yield, good correlation with nitrate in the soil.

17:26
So the NDVI is promising in that sense, right?

17:29
We also see that negative relationship with temperature, right between temperature and yield and then temperature and nitrate.

17:36
So definitely something that we want to keep exploring. And then electrical conductivity.

17:42
So we’ll look at all these variables again.

17:44
What you don’t see on here is, moisture.

17:49
And the reason why you don’t see that is because moisture was all over the place.

17:54
We found no relationship whatsoever with yield or nitrate.

18:00
So, so that’s in a way surprising, but we’ll keep looking at all these data to see again, if we can bring this together in a strong equation that would help us predict nitrogen availability.

18:13
About that I want to say, you know, if you’re doing model development, you need lots of data, right?

18:19
And lots of collaborators that want to run a trial on their field.

18:25
Anyways, so moving on from that, again, I’m presenting these as case studies, if you will or stuff that we’re working on again to answer some of the same questions that I started out with that nitrogen availability from manure to inform our nitrogen recommendations, ok.

18:43
So this, particular study, we’re basically throwing that that drone data on top of this looks at different manure types, different application timings.

18:57
And then what we did is collected NDVI data, Red Edge data and Green NDVI data to again find a correlation with nitrogen availability from manure.

19:09
And these are our treatments real quick, what we saw is that yes, there’s definitely promise.

19:16
So this is looking at the three indices that I just mentioned and looking at grain yield.

19:21
And, and what we see is definitely that each time we see that the Green NDVI really comes out as the winner, right?

19:32
As that when it comes to that relationship with yield, ok. We looked at that, the apparent nitrogen recovery again using these three indices.

19:44
And what we found is that definitely the most promising is, the Green NDVI.

19:53
All right, so, where are we at?

19:55
And, what is, I call this conclusions, but it’s basically just next steps, right?

20:01
So, as I mentioned, we’ll further explore various not only canopy indices.

20:07
But also temperature, moisture and electrical conductivity all to inform our nitrogen recommendations.

20:16
So vegetation indices, they show potential, but our need here in Wisconsin is to develop Wisconsin specific algorithms.

20:26
It’s great that it worked in places like Kansas and Oklahoma and all that, but we need to bring it here and we need to start somewhere, ok.

20:34
We cannot just say that, oh, it didn’t work there.

20:37
No, we have to try it ourselves and see if they work.

20:41
Yes, Why?

20:42
Well, they can provide guidance for mid-season nitrogen applications.

20:46
But what we want here people is actionable outcomes, right?

20:50
It’s, it’s great if we have that technology sitting on the shelf, but how do we translate it to stuff that we can actually use and implement?

20:58
So my goal is really to expand this research.

21:02
It got across multiple, multiple sites, ideally on farm trials to understand when and where sensor-based systems are reliable given weather, soil and management variability.

21:17
All right.

21:17
With that, I want to acknowledge all the contributors again, including my people in extension who have contributed to this and my students as well.

21:29
Thank you.

21:29
Yeah, thank you.

21:30
Natasha, we did get a question that came into the chat while you’re presenting.

21:34
Could you explain a little bit more about the type of manure that was used?

21:39
Was it liquid dairy manure? Was their question or if you had both?

21:45
No, it was, it was liquid dairy manure.

21:51
Excellent.

21:51
Thank you.

21:54
I guess one other follow up one is we’ve had some parts of Wisconsin that have had some drenching rains.

22:01
In your research, what kind of recommendations do you have for them if they receive, you know, some really heavy drenching rains, these last couple of storms?

22:12
Oh my gosh.

22:13
Yeah, right.

22:14
So, so when it comes to specifically to the type of research or the type of questions I’m interested in, when you have drenching rains, the question becomes right, how much of that nitrogen is still available when you have applied nitrogen?

22:28
Is that kind of the question?

22:30
Yes.

22:31
Yep.

22:32
Yeah.

22:32
Well, no, I would definitely recommend a nitrate test, right.

22:39
But if you have had drenching rings, it’s probably likely that some of it, some of that nitrogen is lost, right.

22:47
But you can only verify it if you actually take samples.

22:52
Yeah.

22:52
And good news is our corn is, if not there, very close to the perfect time for doing a soil nitrate test.

22:58
So between 6 inches and a foot.

23:01
So go out and grab some of those soil nitrate tests.

23:05
Thank you, Natasha.

23:06
I don’t see anything else in the chat right now.

23:08
We appreciate your time and Natasha’s information will be shared in the chat.

23:13
So if you do have a follow up question, you can reach out to Natasha on your own.