Is Site-Specific Management Leading Nebraska Growers Towards Higher Nitrogen Use Efficiency?

Laila Puntel, Assistant Professor and Precision Ag Specialist, Department of Agronomy and Horticulture, University of Nebraska–Lincoln Author

05/03/2022 Added

28 Plays

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This seminar presents results about how different precision ag technologies for site-specific nitrogen management perform in corn and wheat cropping systems in Nebraska.

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[00:00:00.800]The following presentation
[00:00:02.240]is part of the agronomy and horticulture seminar series
[00:00:05.830]at the University of Nebraska-Lincoln.
[00:00:08.730]Good afternoon all.
[00:00:09.563]Thank you very much for joining us today.
[00:00:12.543]It is my great pleasure to introduce Dr. Laila Puntel,
[00:00:17.200]who is a assistant professor
[00:00:19.367]at the Department of Agronomy and Horticulture at the UNL.
[00:00:23.350]Laila got her BS in Agronomy
[00:00:26.210]at the University of La Plata, Argentina
[00:00:28.940]in agricultural engineering.
[00:00:30.790]After that, Laila moved to the US
[00:00:35.510]to first get her master degree on crop production
[00:00:39.937]and crop physiology at Iowa State University,
[00:00:43.860]subsequently followed by a PhD on the same major
[00:00:47.780]at the same institution.
[00:00:50.270]Laila has this unique set of skills
[00:00:52.810]that includes very strong analytical skills
[00:00:56.270]and something that I found very unique from her background
[00:00:59.960]is that she has been doing both basic and applied research,
[00:01:04.750]and she also has experience working in the private sector.
[00:01:09.640]Laila program at the UNL focuses on soil fertility,
[00:01:15.360]precision Ag, digital Ag technologies,
[00:01:17.613]and nutrient recommendations,
[00:01:19.110]and she promotes adoption of data driven
[00:01:21.120]and digital Ag tools across the US Midwest
[00:01:23.300]to reduce nitrogen footprint.
[00:01:26.582]And besides that, for those who don't know that,
[00:01:29.960]Laila is the late chair for the C-3 Crop Ecology Division
[00:01:36.137]at the Crop Science Society of America.
[00:01:38.190]So Laila, it's a pleasure to have you with us
[00:01:40.450]and the floor is yours.
[00:01:42.642]All right, thanks Patricio for the great introduction.
[00:01:45.590]Thanks for giving me the opportunity
[00:01:48.310]to present some of the work
[00:01:50.670]that I've been doing for the last three years
[00:01:53.366]at the University of Nebraska.
[00:01:54.990]And I appreciate all the ones joining today.
[00:02:00.251]To get it started, today my idea is just to give you
[00:02:03.200]a little bit of background about site-specific management,
[00:02:07.480]specifically for nitrogen in Nebraska,
[00:02:10.430]as well as show you two major projects
[00:02:13.120]that one concluded a year ago,
[00:02:16.140]and another one started last year
[00:02:18.510]on how we are trying to test
[00:02:20.660]some of the site-specific management practices
[00:02:23.650]for wheat growers and as well as how we are intending
[00:02:26.370]to promote some of these technologies.
[00:02:30.340]And then answer this question
[00:02:32.865]if we are guiding growers into the right direction,
[00:02:36.380]if we wanna increase higher nitrogen use efficiency
[00:02:39.880]in our crop systems.
[00:02:41.670]So with that being said,
[00:02:44.450]just to give you a little bit of background,
[00:02:47.540]for those that are not familiar
[00:02:48.800]with the term site-specific or precision Ag,
[00:02:52.050]they tend to be exchangeable.
[00:02:55.010]They tend to be used as the same thing.
[00:02:58.670]And as international convention,
[00:03:02.040]a lot of scientists around the world
[00:03:04.560]came up with this long definition,
[00:03:07.180]but I will try to summarize.
[00:03:08.910]But the idea of precision agriculture
[00:03:10.610]or site-specific management
[00:03:12.330]is putting processes
[00:03:13.580]and analysis of temporal and spatial data
[00:03:16.700]that help us to understand the variability
[00:03:19.560]that is present in the field,
[00:03:22.790]and then try to manage it
[00:03:24.060]in a way that we can increase
[00:03:25.190]efficiency, productivity, quality profitability.
[00:03:28.110]So a lot of those things really
[00:03:31.200]encompass a lot of the things
[00:03:32.610]that we wanna attain with current cropping systems
[00:03:35.650]and the use of inputs as well.
[00:03:38.820]And for a more simplistic one,
[00:03:40.317]the USDA in 2007, came up with this one
[00:03:44.890]that I think really captures
[00:03:46.430]a lot of what the other one says as well.
[00:03:49.070]Use every acre within its capability
[00:03:51.480]and treat it accordingly to its needs.
[00:03:53.790]And it seems to be very simple,
[00:03:56.000]but it's more complex than it actually looks like.
[00:03:58.530]So understanding what is happening in every acre
[00:04:01.720]and reacting to it to adjust crop management,
[00:04:06.242]it is a challenge, at the same time, it's an opportunity.
[00:04:10.560]So for most of you will be kind of something
[00:04:16.730]that you have heard a lot of times,
[00:04:18.460]but the importance of nitrogen
[00:04:20.120]is not (indistinct) in cropping systems.
[00:04:22.410]And so if we wanna sustain high yields
[00:04:24.900]and maintain farmer profitability,
[00:04:26.740]we do need the use of nitrogen fertilizer
[00:04:28.990]as one of the main inputs.
[00:04:30.550]And sometimes, this is being seen as one of the weaknesses
[00:04:34.580]that we have in food production systems,
[00:04:36.710]and that's perhaps because of the dependence
[00:04:41.380]that we have of nitrogen or synthetic fertilizer
[00:04:45.730]to maintain these high yields,
[00:04:47.460]as well as managing these high volumes of fertilizer,
[00:04:50.410]of course, along with a higher risk for environmental loss.
[00:04:55.590]So precision nitrogen management,
[00:04:57.770]this is where it comes into play
[00:04:59.520]because you can contribute to a more sustainable
[00:05:01.760]intensification of these cropping systems
[00:05:04.340]by being more precise,
[00:05:06.920]understanding the dynamics that we have in the field
[00:05:09.660]and being capable to increase yields
[00:05:11.800]as we increase use efficiency,
[00:05:13.600]while reducing that environmental impact.
[00:05:16.060]As I said before, I consider this as a huge opportunity
[00:05:19.400]to start better utilizing the technologies
[00:05:21.303]that we have out there to meet the goals that we have,
[00:05:25.090]including food production systems.
[00:05:28.930]But I wanna be optimistic, but as well,
[00:05:32.500]I wanna be realistic.
[00:05:34.010]So when it comes to precision Ag technology adoption,
[00:05:38.310]we know that it has been in the last 20, 30 years,
[00:05:41.520]have been a lot of emphasis in data and technology focus.
[00:05:45.330]And that's great from a perspective of development
[00:05:49.480]and increase the technology available for growers
[00:05:53.563]as well as crop consultants or agronomists.
[00:05:56.830]But on the other side, has been over promised
[00:05:59.020]and under delivered.
[00:06:00.010]What I mean with that is there has been a lot of buzz
[00:06:02.840]about how much precision agriculture can do
[00:06:05.550]and little in terms of tracking of impact
[00:06:09.770]in the major metrics.
[00:06:11.080]And what I mean by that,
[00:06:12.530]increasing yield, increasing efficiency, increasing profit.
[00:06:15.790]And under delivered because in some way
[00:06:18.890]has been heavily pushed by industry rather than by science.
[00:06:23.020]And I think that was the major flaw.
[00:06:25.970]And so part of my motivation here
[00:06:29.130]is how do we overcome some of these limitations?
[00:06:33.230]And so despite decades of research and development,
[00:06:36.890]less than 20% of many acreage across the US
[00:06:40.390]is managed under some sort of precision Ag technology
[00:06:44.720]in the US.
[00:06:45.960]And this is really, I would say, generous
[00:06:49.440]because 20% might include the use of yield monitors or GPS,
[00:06:53.620]and it's not necessarily reflecting
[00:06:56.300]how many growers are doing actually management decisions
[00:07:00.150]based on the technology.
[00:07:03.970]But I wanna put another positive highlight
[00:07:07.350]to counterpart these negatives
[00:07:09.900]on the precision Ag technology
[00:07:11.760]by saying that there's a lot of literature out there,
[00:07:14.020]and I'm just citing two of my favorite papers,
[00:07:18.070]but there's more out there pointing out
[00:07:21.100]that actually when we compare all the science
[00:07:25.040]and understanding of how different zones
[00:07:28.220]in field behave and the dynamics,
[00:07:30.140]and then we couple it with the right technology,
[00:07:32.600]we can deliver economic and environmental benefits
[00:07:35.270]from site-specific management.
[00:07:38.150]So that's where I guided part of my program,
[00:07:42.930]and those are the promises.
[00:07:44.480]So a lot of what I do, it gets connected to this point.
[00:07:49.210]So in short, what we're trying to do
[00:07:51.633]when we apply this to site-specific nitrogen management,
[00:07:55.100]it will be to maximize that synchrony
[00:07:57.410]between the nitrogen supply and the crop demand
[00:08:00.600]across the field.
[00:08:01.920]So when we look at this image
[00:08:03.650]and we realize that we have high yielding areas on a field
[00:08:07.260]lowering yielding areas on another portion of the field,
[00:08:11.260]we know that the controlling factors
[00:08:13.210]that are affecting nitrogen supply
[00:08:15.540]and crop nitrogen demand could be completely different.
[00:08:20.210]And that understanding,
[00:08:21.580]will definitely guide the correct nitrogen management
[00:08:26.710]approach for an entire field.
[00:08:29.370]And that includes, it could be a better adjusted flat rate
[00:08:32.560]for the entire field,
[00:08:33.810]or it could be a viable rate application
[00:08:36.190]that kind of linkage, or try to do a better synchrony
[00:08:39.737]of that demand to maximize yields and profit.
[00:08:44.490]And so what's the main challenge?
[00:08:48.000]Not only is understanding what factors are underlying
[00:08:51.890]that variability in yield
[00:08:53.320]and their yield response to nitrogen,
[00:08:55.460]but also, I would say, that some of the other assumptions
[00:08:59.310]that have been done
[00:09:00.390]is that all the factors remain the same
[00:09:03.390]or they're constant across the field.
[00:09:06.010]So when we think about managing nitrogen site-specific,
[00:09:10.820]we need to understand that, that yield response to nitrogen
[00:09:14.260]can change depending on the landscape position.
[00:09:17.210]And so, for example, in this picture
[00:09:19.756]from a grower here in Nebraska,
[00:09:22.140]I'm showing you a high hill position, more elevation,
[00:09:27.060]our assumption is that it might be a course texture,
[00:09:30.650]lower organic matter, and then the bottom part of the field
[00:09:33.570]that you can see more towards the bottom of the picture,
[00:09:36.293]that might be more highly productive
[00:09:38.700]and might have more organic matter.
[00:09:40.910]And a lot of the assumption is that,
[00:09:44.210]well, maybe because we have a lower holding capacity
[00:09:47.880]in the hill, we are gonna under-apply nitrogen
[00:09:51.300]because you might not respond.
[00:09:53.490]And then on the bottom, I'm gonna say,
[00:09:55.160]I'm gonna apply a lot of nitrogen
[00:09:56.900]because that's gonna response to nitrogen.
[00:09:59.220]And this is a major challenge
[00:10:00.750]because if you look at the curves
[00:10:02.020]that I'm showing you there as an example,
[00:10:03.610]this happen a lot of times,
[00:10:05.580]that actually environments that we think
[00:10:08.590]that might not respond to nitrogen, actually they do.
[00:10:11.886]And they have the potential to attain exactly the same yield
[00:10:16.160]as the bottom fields that are always higher yielding
[00:10:19.580]with actually more nitrogen than the more productive areas.
[00:10:23.050]So in this first part of the curve,
[00:10:26.290]you can see that the gap between the non-fertilized
[00:10:29.490]and the maximum fertilizes treatment
[00:10:32.250]is smaller than the hill or the top part of the field.
[00:10:39.300]As it sounds simple,
[00:10:41.000]it is something that actually gets assumed
[00:10:43.780]in every site-specific management
[00:10:47.370]or in a lot of the service providers
[00:10:49.990]that growers across Nebraska could access.
[00:10:52.540]So this (indistinct) some of the statements
[00:10:57.550]that have been staying true out there
[00:11:00.600]is also important for the success of this technology.
[00:11:03.520]And so really what we're trying to do
[00:11:05.850]is utilize to our favors,
[00:11:09.050]this concept of (indistinct) by matching the right time,
[00:11:13.030]rate, source, and place across the field.
[00:11:15.950]So that's our goal.
[00:11:18.630]And so what's the landscape for producers today?
[00:11:21.970]And I really like to keep adding tools into this big bubble,
[00:11:26.300]that I'm showing you towards the right
[00:11:27.726]on what we call today, the digital Ag.
[00:11:30.300]But in the 1980s, we started with very simplified approaches
[00:11:34.470]based on yield goals.
[00:11:35.910]And then we progressed into these really big development
[00:11:39.200]of more complex tools that go from crop models being adapted
[00:11:43.610]and being released in the market after the 2000s,
[00:11:47.530]and then commercialized.
[00:11:48.880]And you will see a lot of logos
[00:11:50.170]and probably I'm missing a lot of names here.
[00:11:53.460]And then more recently,
[00:11:55.480]we have new technologies or techniques
[00:11:58.130]that are helping us to better utilize
[00:12:00.510]some of the information
[00:12:01.620]that is being collected in our farms.
[00:12:04.110]So this is the landscape,
[00:12:05.740]and so complexity is increasing as we move to the right,
[00:12:09.510]but at the same time,
[00:12:10.440]I have the hypothesis that a lot of these tools
[00:12:12.580]are gonna have to become simplified
[00:12:14.800]in order to increase
[00:12:17.090]some of the adoption across our growers.
[00:12:21.999]And the landscape is even worse for a growers perspective,
[00:12:26.070]because this is how it looks like,
[00:12:27.969]the farm tech landscape in 2020,
[00:12:31.770]and probably got bigger by 2022.
[00:12:35.220]And so really, our goal and some of my motivations
[00:12:39.440]is to help growers to make a better decision
[00:12:41.430]in terms of what is the cost effective technology
[00:12:45.150]that can be adopted to their cropping system.
[00:12:47.960]And so a lot of us,
[00:12:50.040]we are working in this space,
[00:12:51.430]and it's a pleasure to be in academia
[00:12:54.210]to be bringing some clarity about what works,
[00:12:57.480]and what doesn't.
[00:13:00.100]All right, more recently,
[00:13:02.140]well, actually a couple of years ago,
[00:13:05.090]this is a topic of debate.
[00:13:06.870]A lot of the literature has been contrasting different tools
[00:13:10.236]of proposing site-specific versus sensor
[00:13:14.460]versus the empirical approaches that already exist
[00:13:17.160]and are being supported from land grant universities.
[00:13:20.866]So the common or the agreement that is out there
[00:13:26.520]is sometimes they do work better, sometimes they don't.
[00:13:30.240]So it really varies their capability side by side
[00:13:34.220]and year by year.
[00:13:35.970]And so that's a challenge that remains there.
[00:13:38.467]And more recently in 2021,
[00:13:41.770]a colleague did some study in Illinois
[00:13:46.700]and they come up with this conclusion
[00:13:49.000]that the more complex tools
[00:13:51.300]that will be the case of crop model based tools
[00:13:54.350]that include a lot of the weather management,
[00:13:57.326]soil characteristics, and more complex dynamics
[00:14:00.250]to understand the spatial and temporal variability,
[00:14:03.828]they say that incorporating that variability
[00:14:06.570]actually make the system more efficient.
[00:14:11.080]In this case in Illinois,
[00:14:12.150]they quantified almost a 13% of reduction
[00:14:14.990]in nitrogen leaching without reducing profits.
[00:14:18.620]So again, that's very eye opening for me
[00:14:22.400]because if you are trying to demonstrate to growers
[00:14:25.370]that technology is always gonna increase yield,
[00:14:28.120]perhaps that's not gonna be the only route
[00:14:31.330]that we need to take in order to promote adoption.
[00:14:35.070]So really trying to quantify the impact
[00:14:37.923]that it has in the environment
[00:14:40.110]is gonna be very relevant looking forward.
[00:14:44.910]All right, so there's some remaining questions
[00:14:46.903]that's particular for Nebraska.
[00:14:49.080]We wanted to answer if precision nitrogen technologies
[00:14:51.690]are improving nitrogen use efficiency, yield, and profit.
[00:14:55.400]We also wanna know if so,
[00:14:57.340]how can we promote more effective
[00:14:59.510]the adoption of these tools
[00:15:01.580]as we see fits across different environments in Nebraska?
[00:15:06.140]And also have a better understanding
[00:15:07.860]on what's the spacial and temporal variability
[00:15:09.890]of optimal N rates?
[00:15:11.900]Although we have some research experiments
[00:15:14.350]looking in different parts of the state,
[00:15:16.955]what's the economic optimum,
[00:15:18.997]and how those optimal N rates change it,
[00:15:21.550]we don't know what's the spatial/temporal variability
[00:15:25.444]that we presently have
[00:15:26.677]and how that varies from East to West.
[00:15:29.520]So that's also part of the questions that remain open.
[00:15:33.060]And in addition to that,
[00:15:34.390]as I highlighted in the introduction,
[00:15:37.660]we really need to understand what factors
[00:15:39.690]are influencing the performance of these technologies.
[00:15:42.240]And that goes along to understanding
[00:15:44.480]what processes are affecting the dynamics of the crop
[00:15:48.610]and the soil to understand the strengths of these tools
[00:15:52.830]when they get implemented.
[00:15:55.150]So now switching off to one of the two main projects
[00:16:00.310]that we have been working on
[00:16:03.150]related to site-specific management
[00:16:04.960]and the impact on nitrogen use,
[00:16:07.570]the first one started even before I joined the university,
[00:16:11.110]and actually at the bottom,
[00:16:12.290]I'm citing some of the people
[00:16:13.137]that have been working in the Department of Engineering
[00:16:17.460]and some of the extension people,
[00:16:18.810]as well as the Economic Department.
[00:16:20.760]And I can cite probably 20 more extension educators
[00:16:23.740]and graduate students that completed masters and PhD
[00:16:26.790]off from this project.
[00:16:28.270]So I'm not by any mean taking all credit of this effort,
[00:16:32.220]but I want to push this out
[00:16:36.240]and get more polished conclusions
[00:16:39.020]about what was the impact of using canopy sensors
[00:16:42.880]or remote sensing to direct in-season side-dress
[00:16:47.685]in corn based cropping systems in Nebraska.
[00:16:50.780]And so for that, there were conducted in 80 fields,
[00:16:55.550]and you can see the distribution in the map on the left.
[00:16:59.050]And then the project acquired an applicator
[00:17:03.620]that you can see on the top.
[00:17:05.990]We're mounting sensors that actually use the crop
[00:17:08.850]to direct the nitrogen application.
[00:17:10.950]And then we use very well tested algorithms in Nebraska
[00:17:16.250]to translate how the crop status is looking like
[00:17:20.330]into an nitrogen recommendation.
[00:17:22.870]And so this is kind of the overall approach of the project.
[00:17:26.910]And I really like these concept of benchmarking
[00:17:29.980]or comparing side by side
[00:17:32.410]what the grower is implementing in the field
[00:17:35.860]against this new approach,
[00:17:37.940]in this case was the idea of using a side-dress
[00:17:41.150]and in-season directed with sensors.
[00:17:43.990]And so this is how it got implemented
[00:17:47.780]across 80 fields on those years.
[00:17:51.450]So this is just a little bit of background
[00:17:54.400]for those that are not familiar with remote sensing.
[00:17:57.050]But the idea is we use a sufficient reference
[00:18:01.570]in the field, and then we compare the sensing
[00:18:04.840]of some of the common indexes like NDBI or NDRE.
[00:18:08.280]We can compare that sufficient or that references strip
[00:18:12.010]with our target area, which could be any strip in the field
[00:18:16.410]or over apply the entire field.
[00:18:19.420]And with that, we translate the sufficient index.
[00:18:21.910]So how much percent of greenness I'm missing
[00:18:25.600]to kind of target the highest.
[00:18:27.770]So that's the concept behind some of these tools.
[00:18:30.680]And so that's how we determine the nitrogen N rate.
[00:18:33.550]And then at the end of the growing system,
[00:18:35.400]we can collect the yield monitor data,
[00:18:38.380]we can compare how much nitrogen the grower applied
[00:18:41.560]and how much these technology apply
[00:18:43.700]to make some of the investigations
[00:18:46.590]of the performance of these tools.
[00:18:49.050]And so I'm gonna highlight just a segment of this project
[00:18:55.000]to give you an idea about the impact
[00:18:58.700]that had across the state.
[00:19:00.860]And so one of the things that we all found from this project
[00:19:05.380]is that there was a huge impact
[00:19:07.150]on the total saving of nitrogen.
[00:19:09.780]You can see a significant difference
[00:19:11.520]across all sites and years
[00:19:13.780]between the Project SENSE and the grower,
[00:19:16.550]so really motivated there.
[00:19:18.900]And then second, we see that there's no dependency on yield,
[00:19:23.360]and that's actually our goal.
[00:19:25.100]We wanna push out a technology
[00:19:27.170]that we know that it can be more effective
[00:19:29.750]at reducing the nitrogen
[00:19:31.260]or being more efficient at applying that,
[00:19:34.110]and not reduced nitrogen...
[00:19:36.620]Sorry, yield.
[00:19:37.740]Of course, here we are testing two concepts,
[00:19:40.700]and it's really hard to tease out the two,
[00:19:43.840]because in-season, we are already changing the timing,
[00:19:47.520]probably depending on where the grower did the application.
[00:19:50.970]And second, we are also doing the viable rate application,
[00:19:54.210]that contemplates the variability of the field,
[00:19:56.730]as well as all the factors
[00:19:58.110]that are affecting that particular year.
[00:20:00.850]So there's a lot of factors embedded there,
[00:20:03.810]but it's a good and promising result
[00:20:06.540]that some of these technologies
[00:20:08.250]are actually performing very well for Nebraska.
[00:20:12.270]And then, least but not least important,
[00:20:16.370]increasing nitrogen use efficiency,
[00:20:19.550]comparing the two management across all these sites.
[00:20:22.960]Of course, again, I will highlight that cooperative farmers,
[00:20:27.200]and especially in the On-Farm Research Network,
[00:20:29.170]they tend to be on the more efficient site.
[00:20:32.630]And so perhaps this is not 100% representative
[00:20:35.680]of the average across the entire state,
[00:20:38.410]but again, if there is impact at this level,
[00:20:41.950]I would expect that would have impact as well
[00:20:44.820]in the growers that are not producing
[00:20:48.340]at that high of efficiency.
[00:20:52.330]And I wanna highlight two examples.
[00:20:55.150]One of the sites were conducted in 2020
[00:20:58.550]on a loamy, fine...
[00:21:00.660]Sorry, fine sand soil profile.
[00:21:03.400]And so here, what I wanna just highlight is that,
[00:21:07.230]especially in particular with those fields
[00:21:09.470]that are having high variability
[00:21:11.390]or more course soil textures,
[00:21:14.180]the impact on nitrogen use efficiency,
[00:21:16.990]you can see here was an increase of 20%.
[00:21:19.840]And we have seen these repeatedly across years
[00:21:23.130]where we have more challenges, soils to manage,
[00:21:26.940]then these kind of technologies
[00:21:29.070]can really help producers to be more efficient.
[00:21:33.570]And in another situation
[00:21:34.910]with more silty clay, loam soil types,
[00:21:40.220]then we can see that the grower was already performing
[00:21:42.803]at a really high nitrogen use efficiency.
[00:21:45.790]However, we still have room for improvement
[00:21:48.720]when we apply side-dress application using sensors,
[00:21:52.460]and without penalty on profit.
[00:21:54.570]So this, I know is a flash of results,
[00:21:58.390]but I think this will connect very well
[00:22:00.770]to the follow up analysis
[00:22:02.340]that we conducted on this database.
[00:22:05.330]And so I don't wanna lose you
[00:22:07.907]on the regression analysis or anything.
[00:22:11.230]The main message here is that we couple all the database
[00:22:16.140]with other data layers that were available,
[00:22:18.340]like texture, organic matter,
[00:22:21.110]some of the management factors that growers implemented
[00:22:25.050]in those fields.
[00:22:26.410]And what we find out is that the biggest difference
[00:22:29.130]between this site-specific technology
[00:22:31.810]and what the growers were doing,
[00:22:33.165]entirely related with the organic matter content,
[00:22:36.240]the texture, in particular, the sand content.
[00:22:39.150]And then whatever base nitrogen management they were doing.
[00:22:43.420]And that's something very important.
[00:22:45.110]We cannot pretend that technology is gonna perform great
[00:22:48.820]if we don't actually know how can we set it up for success.
[00:22:54.000]And so if we know
[00:22:54.920]that we are gonna split nitrogen application
[00:22:57.559]and let the sensors kind of direct that application,
[00:23:01.210]really our base nitrogen N rate,
[00:23:03.290]it doesn't have to exceed the nitrogen demand
[00:23:06.870]that we are gonna have at the time of the sensing.
[00:23:10.000]And that sounds trivial,
[00:23:11.900]but that also will set some of these technologies
[00:23:15.100]for success in the future.
[00:23:18.000]And another finding,
[00:23:19.370]and this is being part of the publication coming up soon,
[00:23:23.130]is the fact that we could use the yield variability
[00:23:27.180]that these growers had present in their field
[00:23:30.560]as a predictor of how well these kind of site-specific
[00:23:34.530]management technologies will perform.
[00:23:36.890]And so in the Y axis here,
[00:23:38.880]you see the coefficient of variation,
[00:23:40.760]so how variable are yields
[00:23:42.600]in the sensor strips of those fields.
[00:23:46.050]And then on the bottom axis,
[00:23:47.380]you can see the variation of the growers.
[00:23:49.660]And so we determined that when we pass
[00:23:51.940]that eight to nine or 10% of variation across the field
[00:23:56.700]in the growers, then we can reduce the spatial variability
[00:24:00.710]in yield by adapting the management of nitrogen.
[00:24:04.270]So that was one of the main findings
[00:24:06.640]and things that we are starting to understand
[00:24:08.850]for the use of this technology.
[00:24:11.830]So that was a project that concluded last year.
[00:24:15.680]And we kind of re-relaunched it
[00:24:18.560]as part of this bigger effort initiated
[00:24:22.910]with the support of the USDA, NRCS, and the CIG Project.
[00:24:29.353]So these grants are about implementing conservation
[00:24:33.490]innovation practices.
[00:24:35.130]And so as part of this, canopy sensors
[00:24:37.750]or the use of remote sensing technology
[00:24:39.303]is part of one of the tools
[00:24:40.603]that we wanna keep evaluating across Nebraska.
[00:24:44.930]But we also couple more tools
[00:24:46.864]that farmers are implementing that we wanna test them.
[00:24:50.240]And they go in all these spectrums of complexity.
[00:24:55.470]So in the middle,
[00:24:56.580]I have the sensors or variable rate technology.
[00:25:01.750]These could be the use of images.
[00:25:03.810]This could be some of the canopy sensor technology
[00:25:08.230]mounted into the applicators.
[00:25:10.160]And then we kind of jumped into more complexity
[00:25:12.400]when we think about crop simulation models
[00:25:15.240]that are embedded in some of the detailed platforms
[00:25:17.710]that growers are getting access today.
[00:25:20.280]And although they look simplistic
[00:25:22.576]from a grower perspective sometimes, in the background,
[00:25:26.070]they run really complex soil and crop dynamics
[00:25:28.820]in order to determine what are the needs of nitrogen
[00:25:32.340]in different parts of the field,
[00:25:34.190]and what would be the perfect timing
[00:25:36.250]to get that nitrogen apply in the field.
[00:25:39.540]And so I would say that this is the more complex tools
[00:25:44.160]that we have available today.
[00:25:46.080]And then all the way
[00:25:47.554]to special fertilizer and biologics
[00:25:50.655]that are also some of the strategies
[00:25:53.240]that can be used site-specific
[00:25:55.270]to increase the efficiency of nitrogen.
[00:26:00.010]As I said before, it's an effort supported by $1.2 million,
[00:26:05.793]and that it's gonna be until 2023
[00:26:09.590]with the idea of running 40 trials every year,
[00:26:13.730]testing some of these tools,
[00:26:15.350]but also collecting a lot of key information
[00:26:18.140]for us to understand what's the level
[00:26:21.930]of spatial variability in the fields in Nebraska,
[00:26:24.810]what are the factors affecting yield response to nitrogen,
[00:26:28.810]and then again, guiding better growers
[00:26:32.670]towards tools that are really affecting across the state.
[00:26:37.190]And in these efforts, I'm part of a big team of specialists,
[00:26:43.800]extension educators, and other specialists
[00:26:45.960]across all the departments
[00:26:47.660]in order to execute all these trials across the state,
[00:26:50.440]as well as collect data.
[00:26:52.270]And I won't forget also to mention
[00:26:55.530]that there's four full time grad students
[00:27:00.200]collaborating in this project
[00:27:01.770]while getting their graduate programs done
[00:27:05.030]based on the data collected into this project.
[00:27:07.570]So Laura and Jose, that you may be familiar with.
[00:27:11.250]They're both conducting their PhDs.
[00:27:13.590]And Christian and Seth,
[00:27:15.170]they're both getting the master's program
[00:27:18.730]based on some of the tools
[00:27:19.910]that are also implemented in this project.
[00:27:23.400]And just to dive a little bit
[00:27:24.730]about the results collected from the initial formal year
[00:27:29.650]of this project in 2021,
[00:27:31.800]more than 35 experiments were run across the state
[00:27:36.660]for wheat and corn.
[00:27:37.890]And you can see a really nice distribution across the state,
[00:27:41.580]which at the end of the project,
[00:27:42.860]allowed us to tie back the performance of these tools
[00:27:46.680]with different soil,
[00:27:48.070]environmental and management conditions.
[00:27:50.550]And so are pretty excited
[00:27:52.080]to put all these database together.
[00:27:55.620]And this is for you to give you an idea
[00:27:57.240]about the design and process for the data collection.
[00:28:02.700]And again, I'm excited
[00:28:05.130]of these on-farm research type of approach,
[00:28:08.650]where we can actually benchmark the next technology
[00:28:11.610]or the next nitrogen technology against the grower.
[00:28:15.820]And so that's what you see highlighted here
[00:28:18.830]in pink and blue.
[00:28:21.110]That's part of the replicated comparison across the field.
[00:28:26.280]And that could vary depending on what the grower
[00:28:29.410]is wanting to test.
[00:28:32.455]Most of the times, they have a selection.
[00:28:35.530]They could go from something complex
[00:28:37.500]to something very simplistic,
[00:28:38.900]but the idea is to match up as a tier approach
[00:28:42.570]what tool can actually better fit it in their logistics
[00:28:46.810]and their socio-economical environment.
[00:28:51.480]And also one of the innovative parts of this project
[00:28:57.160]that would allow us to fulfill that first question
[00:29:00.460]that introduced early on,
[00:29:02.620]is what is the spatial variation on the is optimal N rate,
[00:29:07.170]and how does it vary across the field?
[00:29:09.290]So those are nice looking small plots
[00:29:12.980]distributed across the field
[00:29:14.870]and intended to be located
[00:29:16.930]in really contrasting zones in the field
[00:29:19.430]that were predetermined based on the yield variability
[00:29:22.510]and the topographic differences.
[00:29:24.510]So at the end of the growing season,
[00:29:25.960]we can come back and actually benchmark these tools
[00:29:29.170]and growers management, and again, a potential observed true
[00:29:33.780]of what was the optimal N rate for this particular field
[00:29:37.137]and how it varies across the field.
[00:29:39.410]I think this is a very unbiased way
[00:29:42.960]of trying to benchmark technologies
[00:29:45.330]and also get some more insights back to the grower.
[00:29:49.990]So now I'm gonna walk you through a couple of examples
[00:29:52.620]and then wrap up with some of the overall conclusions
[00:29:55.390]that we came up in 2021.
[00:29:57.770]And so just to point out, for example,
[00:30:00.780]this is a grower that wanted to evaluate Adapt-N model,
[00:30:04.410]so a more complex site-specific tool against canopy sensors,
[00:30:09.670]what we call the in Project SENSE
[00:30:12.040]and against his own management.
[00:30:15.250]In this case, this grower already
[00:30:16.650]have viable rate application type of approach
[00:30:20.100]that was done by the crop advisor.
[00:30:22.420]So he was already more Ag plans adopter
[00:30:26.180]or high adopter of technology.
[00:30:29.030]This is how the experiment looks like.
[00:30:30.890]So again, same concept replicated a strip trial
[00:30:35.330]with a small plots.
[00:30:39.481]And so a lot of the data is collected in these small plots,
[00:30:43.543]and then through the yield monitor and the (indistinct)
[00:30:47.360]from the machinery,
[00:30:48.690]we can actually start analyzing the data.
[00:30:53.410]This is how an Adapt-N prescription
[00:30:56.240]based on a generation of simulations
[00:31:00.630]during the growing season using all the weather
[00:31:03.580]and some of the forecasted weather,
[00:31:05.610]including soil characteristics
[00:31:07.460]and all the management from the field is being utilized.
[00:31:10.770]And then we click this prescription
[00:31:13.060]to implement it in the layout that I just showed you.
[00:31:16.500]So for this particular field in the middle of June,
[00:31:19.670]a side-dress application looped from zero
[00:31:22.640]to 80 pounds of nitrogen per acre
[00:31:25.380]according to Adapt-N prescription.
[00:31:28.130]And so again, very tied to high yielding areas,
[00:31:32.950]perhaps difference in soil properties,
[00:31:35.120]but quite stunning to see that half of the field
[00:31:39.860]is almost coming from no zeros...
[00:31:42.400]Sorry for zero side-dress.
[00:31:45.320]And then I would say that we also use
[00:31:47.330]a lot of the principles that I highlighted in introduction
[00:31:50.940]in terms of understanding some of the mechanisms
[00:31:53.890]and the understanding of some of the zones
[00:31:57.890]and how we expect them to behave in terms of productivity,
[00:32:02.020]as well as response to inputs.
[00:32:03.880]So there's a lot of science behind,
[00:32:06.430]and how do we combine on this into the model
[00:32:09.710]to make sure that it's being run with good data
[00:32:13.300]and good setup in order to come up with that prescription?
[00:32:18.450]And these are all the overall results
[00:32:21.150]that I just wanna point out that this grower
[00:32:24.580]was already operating at a high efficiency,
[00:32:28.030]attaining a deal of 250 bushels,
[00:32:30.870]really high for the 2021 year
[00:32:33.320]with a total amount of nitrogen of 166.
[00:32:36.620]And I'm gonna just point out that among the technologies,
[00:32:39.700]was no difference between three managements,
[00:32:43.300]no difference in profit,
[00:32:44.820]but there was still a room for improvement
[00:32:48.050]into that nitrogen use efficiency
[00:32:50.410]when we compared grower with the modeling approach.
[00:32:53.800]And so back to the idea of that recent paper
[00:32:58.250]where they also found that more complex approach
[00:33:01.310]that are more dynamic
[00:33:02.960]are actually having a bigger impact
[00:33:05.170]on these nitrogen use efficiency,
[00:33:07.040]or actually the utilization of the synthetic fertilizer.
[00:33:11.920]So kind of nice to find some confirmation there.
[00:33:17.530]And then I wanna show you the innovated approach
[00:33:20.270]that we are taking to analyze this data.
[00:33:23.110]Once we combine all the data from the grower and everything,
[00:33:27.610]we calculate the economic optimum rate across the field.
[00:33:31.570]And so what you see highlighted there in the box in green,
[00:33:35.610]at the top is the economic optimum.
[00:33:37.670]And there we are benchmarking total nitrogen rate yield,
[00:33:41.640]nitrogen use efficiency, and profit,
[00:33:44.830]with the UNL recommendation,
[00:33:46.580]as well as the EONR for that particular zone
[00:33:49.800]that is coming for those small plots
[00:33:51.670]that I showed you before.
[00:33:53.860]So I'm not gonna get into the details,
[00:33:56.000]but the idea here is that we are starting to understand
[00:34:00.430]how these students are performing in a zone base,
[00:34:03.710]and trying to understand what are the factors
[00:34:05.840]that actually are misleading some of these recommendations.
[00:34:08.800]So you can see that there is some overestimation,
[00:34:12.740]depending the case from some of these tools.
[00:34:15.810]We can say that in particular for the zone two,
[00:34:19.340]in this case, really Adapt-N was within 10 pounds
[00:34:23.410]of what it was the optimal N rate.
[00:34:25.570]And that's what I think we see reflected a lot of impact
[00:34:28.910]in the final results in favor of the crop model based tool.
[00:34:35.030]So I wanna jump in into another contrasting case.
[00:34:39.790]Here, another grower was evaluating granular model,
[00:34:44.030]another platform, against their full application.
[00:34:47.320]So this is a grower that usually applies
[00:34:49.320]all the nitrogen upfront in default.
[00:34:52.170]And we are talking of very silty, loamy and clay/loam soils
[00:34:59.440]that usually, or occasionally get flooded.
[00:35:02.450]So I can give you that as a background.
[00:35:05.150]And here, what I'm showing you is in the background,
[00:35:08.550]sort of like the variation in elevation,
[00:35:11.710]going from the West to East in a decreasing slope.
[00:35:17.550]And again, the layout here is the same.
[00:35:21.322]In pink and blue are the contrasting
[00:35:23.920]or replicates to compare granular model against the farmer.
[00:35:28.330]And then located in the middle of the field,
[00:35:31.410]some of the blocks to characterize
[00:35:33.510]the economic optimum N rate.
[00:35:37.200]This is how the prescription will look like for this grower.
[00:35:40.030]So you can tend to see some of the variation
[00:35:43.820]for the side-dress application.
[00:35:45.740]And so we have variation from 160 to 200 pounds.
[00:35:50.430]And so the model was accounting
[00:35:54.950]for some of the yield variability,
[00:35:56.690]as well as some of the soil variability
[00:35:58.590]that was present in the field.
[00:36:01.126]And so here is a summary of the results.
[00:36:04.852]And so what we found in this field
[00:36:06.700]is there were no significant difference
[00:36:08.960]in any of the metrics that we look into it.
[00:36:12.310]And actually, the grower and the models
[00:36:16.560]perform exactly the same.
[00:36:18.950]And even though there was some variation
[00:36:21.660]in the nitrogen N rates,
[00:36:22.940]that didn't cause any variation in the yields.
[00:36:29.039]And I wanna point out some of the things,
[00:36:30.843]this field, as you saw in the elevation map,
[00:36:33.930]there's some change in topographic factors.
[00:36:36.340]There's also variation in yields,
[00:36:38.450]and that's how the field got divided into main
[00:36:41.380]or three main cells.
[00:36:43.280]And so what we knew by collecting that small plot data
[00:36:48.690]is that the economic optimal rate
[00:36:50.140]for this field actually varied more
[00:36:53.140]than what the prescription
[00:36:54.098]or the site-specific management pointed out.
[00:36:57.300]So for this field, using some of the prices
[00:37:02.220]for that particular year vary from 136 pounds of nitrogen
[00:37:07.100]up to 243, and you can actually follow the pattern
[00:37:11.040]in the landscape.
[00:37:12.290]And so, as we move to the East,
[00:37:15.440]the optimal N rate was increasing.
[00:37:19.480]And we know that because we were collecting the data
[00:37:22.220]and there was no way that the grower,
[00:37:25.920]if wouldn't have done these kind of testing,
[00:37:27.850]wouldn't know actually what would be the optimum N rate
[00:37:31.100]for that field.
[00:37:32.300]And so when we benchmark now these (indistinct)
[00:37:37.540]or the reality against what was predicted by the model
[00:37:42.470]or recommended, we find out that some of the areas
[00:37:49.220]of the field were under-predicted or over-predicted.
[00:37:52.940]And so one of the key things that we are studying
[00:37:56.170]is the idea that there are some key factors
[00:37:58.000]that are affecting the spacial variability,
[00:38:01.240]not only in the soil supply,
[00:38:02.540]but also in the crop nitrogen demand
[00:38:04.660]that are potentially missing in some of these tools.
[00:38:07.540]And so kind of looping back to the concept
[00:38:10.530]that I introduced earlier,
[00:38:12.500]some of the complexity of these tools
[00:38:15.130]are being simplified to make it more friendly
[00:38:17.820]and to make it more scalable.
[00:38:20.040]But at the same time,
[00:38:21.010]there's very localized conditions
[00:38:23.830]that are being omitted or not included
[00:38:28.540]in some of these tools
[00:38:29.820]when we want to refine some of the recommendations.
[00:38:33.370]And so part of our work
[00:38:35.210]is understanding what were the main factors
[00:38:38.360]that affected, for example, these first area over here,
[00:38:42.400]making it completely different to zone three
[00:38:44.743]that had a really high economic optimum nitrogen rate.
[00:38:49.630]And so that ties back to some of the work
[00:38:52.250]that we are using in more detail with the APSIM platform,
[00:38:56.420]another crop simulation model.
[00:38:58.960]And the idea here is to get into more depths
[00:39:03.470]of the dynamics in crop and soil
[00:39:05.860]to understand what are the factors
[00:39:08.440]that are primarily influencing these difference
[00:39:11.570]in yield response to nitrogen.
[00:39:13.420]And so that's part of the Laura Thompson PhD,
[00:39:16.800]and we are calibrating models
[00:39:18.990]with more precise in-season data
[00:39:22.430]in order to understand the dynamics
[00:39:25.140]that are governing some of these differences.
[00:39:27.770]And so one of the main findings,
[00:39:29.790]and one of the things that are happening
[00:39:31.860]in this particular field is the presence of water table.
[00:39:35.840]And so the inclusion of water table
[00:39:38.810]change completely the dynamic of nitrogen.
[00:39:41.730]And it was probably not captured
[00:39:44.230]by granular model at that time.
[00:39:46.890]And this is a figure that nicely Laura put together
[00:39:51.080]after we finalized our calibration of water table in APSIM.
[00:39:55.820]Pointed out on how nicely these platforms
[00:39:59.610]can help us to understand some of the dynamics
[00:40:01.990]that are going on in the landscape.
[00:40:04.180]And water table for those that are not familiar,
[00:40:06.840]really moves with the elevation.
[00:40:08.660]And so we expect that in that field
[00:40:11.020]had a really nice variation in topography,
[00:40:13.690]we're gonna have different levels
[00:40:15.140]of influence of the water table,
[00:40:18.850]and that changes the whole cycle of nitrogen losses,
[00:40:22.200]but also the yield potential
[00:40:25.208]in those different contrasting zones.
[00:40:28.340]And so this is how we are working out
[00:40:31.843]by matching some of the reality.
[00:40:34.540]So in this graph, this is an output
[00:40:36.550]from water table in the APSIM interface,
[00:40:41.330]and then matching up with some of the events that occur
[00:40:44.949]at these field location from 2013 up to 2021,
[00:40:50.840]and pointed out at how well
[00:40:52.780]we can capture some of those events occurring in the field.
[00:40:56.700]And so I have a lot of faith
[00:41:01.500]that these tools will help us
[00:41:03.610]to understand better how we can actually give a feedback
[00:41:07.250]back to all these industry partners and collaborators
[00:41:10.480]that are providing tools
[00:41:11.550]that perhaps are missing some of the relevant factors
[00:41:15.300]that maybe not really relevant
[00:41:18.320]across the whole entire state of Nebraska,
[00:41:20.800]but for other areas of the Midwest,
[00:41:22.930]that could refine nitrogen accommodations
[00:41:26.150]and be even more dynamic to improve nitrogen use efficiency.
[00:41:31.860]So now wrapping up some of the results from 2021,
[00:41:34.560]I'm not gonna go over all the 37 sites.
[00:41:38.220]But I wanna highlight what is the direction
[00:41:41.680]that we are heading from this project.
[00:41:44.460]Compiling all the sites that got analyzed,
[00:41:47.200]36% of the participants improved nitrogen use efficiency.
[00:41:52.368]27% heading to that no change.
[00:41:57.350]So there was either increase or decrease,
[00:42:00.020]and then 36% of them decrease and most likely,
[00:42:04.130]or what I have seen in the data so far
[00:42:06.660]is by an increase of nitrogen,
[00:42:10.050]perhaps in some of the more productive areas.
[00:42:12.730]So again, that's where I think
[00:42:14.760]there's a lot of room to understand
[00:42:16.560]more of the science behind
[00:42:18.047]and see how far we can refine these tools
[00:42:21.370]to better match that.
[00:42:22.640]So our goal is to pump up that 36%
[00:42:26.300]and see how it behaves
[00:42:27.240]in the next two years of research.
[00:42:30.140]Another highlights from this project,
[00:42:32.610]again, one year of research
[00:42:34.920]on average, we found six bushel per acre increase in yield.
[00:42:39.640]This includes wheat and corn.
[00:42:42.470]And then promising when we look at the profit,
[00:42:47.560]because we saw a range of five to $80 per acre
[00:42:51.310]increase in 72% of the cases
[00:42:54.060]when nitrogen technology was implemented.
[00:42:57.480]So again, we are kind of being picky
[00:42:59.810]and trying to kind of check all the boxes,
[00:43:05.390]increasing yield or maintaining yields,
[00:43:07.910]as well as increasing the nitrogen use efficiency
[00:43:11.170]while maintaining the profit.
[00:43:13.170]So a lot of things to check out,
[00:43:14.745]but I'm totally confident that some of these tools
[00:43:18.360]when they're a really coupled
[00:43:20.830]with the right place in management,
[00:43:23.770]can have a lot of impact.
[00:43:27.630]Sorry.
[00:43:28.463]Another highlight here that I think is important
[00:43:31.430]to keep in mind
[00:43:32.650]is that a lot of these growers,
[00:43:35.650]you can see in this table,
[00:43:37.170]I'm highlighting the average across all the growers
[00:43:40.270]in terms of nitrogen use efficiency for corn and wheat,
[00:43:44.010]and kind of the average
[00:43:45.320]for our next level of nitrogen technology.
[00:43:48.950]You can see that the growers or the average grower
[00:43:52.070]participating in this trial in 2021
[00:43:54.930]was on the efficient side.
[00:43:56.870]And so again, pushing that middle
[00:44:00.420]even to break that threshold to even farther,
[00:44:05.060]it's probably harder than bringing a producer
[00:44:08.800]that is already efficient
[00:44:10.990]and bringing it down or to make it more efficient
[00:44:14.860]in the nitrogen use.
[00:44:18.450]So with that, I wanna introduce some final remarks
[00:44:21.900]and I have some other final messages
[00:44:25.250]that I wanna share with you.
[00:44:28.460]I do think that site-specific nitrogen management practices
[00:44:32.090]have really high potential
[00:44:33.540]to improve NUE yield and profit in Nebraska,
[00:44:37.130]but those changes are gonna be site-specific.
[00:44:39.740]And so if we don't couple a really nice understanding
[00:44:42.410]on the dynamics that are occurring within our fields,
[00:44:46.040]and what are exactly those technologies doing for us,
[00:44:50.675]I think that we're gonna limit the capacity
[00:44:52.993]and the impact that we can bring into our cropping systems.
[00:44:57.740]Secondly, I think there's promises, impact, or good future
[00:45:06.474]by knowing that some of things like texture, organic matter,
[00:45:10.720]yield variability could actually be good predictors
[00:45:13.750]on how much impact a site-specific management could have.
[00:45:17.430]And again, this is all potential
[00:45:19.300]because I think there's a lot to develop here.
[00:45:21.880]And based on the sensor based approach
[00:45:23.610]that I showed you from Project SENSE,
[00:45:28.551]the more variability the field has
[00:45:30.570]in terms of these three parameters,
[00:45:32.480]the more likelihood the producer will have
[00:45:35.880]in terms of adopting it
[00:45:37.180]and having good results in terms of yield
[00:45:39.530]and use efficiency of nitrogen.
[00:45:43.270]And then lastly, I do think
[00:45:45.231]that this side by side comparison and on-farm,
[00:45:49.750]getting the farmer involved in all of the steps
[00:45:53.220]of the adoption of something new
[00:45:56.420]is really allowing us to accomplish a lot of things.
[00:46:00.520]Perhaps, these are not the most important for you.
[00:46:04.220]Those are the ones that came first to my mind,
[00:46:07.170]but we are really doing a good job at diagnosing
[00:46:09.980]what are the current status of nitrogen management practices
[00:46:14.260]evaluating what's the impact
[00:46:16.240]of the next level of management
[00:46:18.310]no matter what that is.
[00:46:20.090]If it's transitioning from (indistinct)
[00:46:21.730]to a split application,
[00:46:23.280]or if it's the adoption of a more complex tool,
[00:46:25.880]I think this project is really accomplished that.
[00:46:28.940]And then also, we are generating a statewide data
[00:46:32.660]to characterize optimal N rates.
[00:46:34.770]So that's something that is a legacy for upcoming projects
[00:46:39.410]to validate or test new upcoming technologies
[00:46:42.510]or different approaches and keep tracking
[00:46:45.730]the progress of growers across the state of Nebraska.
[00:46:50.540]And something that usually is not efficient captured
[00:46:54.680]by a project results is actually the growers experience
[00:47:01.000]when they get on board on some of these projects.
[00:47:03.390]So I really wanna bring to you some of the farmers quotes
[00:47:07.340]that we have the opportunity to hear
[00:47:10.960]after we share every year at the end,
[00:47:13.200]we share a report and we sit one on one with them
[00:47:15.830]to share how the technology perform in the field.
[00:47:19.760]So I wanna share some of those quotes with you to wrap up.
[00:47:23.620]One of the growers says,
[00:47:24.927]"I did not know I was producing corn
[00:47:27.337]"at 1.1 pounds of nitrogen per bushel.
[00:47:30.087]"Now, I do not have to buy more nitrogen."
[00:47:33.290]So very timely for high nitrogen prices this year.
[00:47:37.510]So he was happy to realize what was the efficiency
[00:47:41.170]in which he was producing corn.
[00:47:43.070]And so in that sense, we are producing a change already,
[00:47:46.830]no matter that he adopt it moving forward,
[00:47:48.940]the technology that maybe we propose.
[00:47:51.800]Another farmer, he bought active sensors for his sprayer,
[00:47:57.050]never had the chance to actually do a good job
[00:47:59.730]at using them.
[00:48:00.870]He met with us, we conducted a trial,
[00:48:03.190]and then in 2022, he said,
[00:48:05.557]"I will run these sensors farm wide this year."
[00:48:10.040]To me, there's nothing more satisfying
[00:48:11.473]than hearing a grower saying, "You helped me with this.
[00:48:14.937]"And now I wanna apply it across the entire field."
[00:48:18.850]And the third one, another grower used Adapt-N model
[00:48:23.550]for an in-season nitrogen management in 2021.
[00:48:26.755]And he told me in my office,
[00:48:28.827]"Yeah, I did don't know that we can save that much nitrogen.
[00:48:32.587]"Now we know we can reduce the nitrogen rate up front
[00:48:35.747]"and then for the fields that is possible,"
[00:48:37.990]and he was mentioning related to the logistics,
[00:48:40.597]"Now we can monitor nitrogen for a side-dress.
[00:48:43.207]"Great use of the data that we already have."
[00:48:46.490]So again, these are valuable things
[00:48:49.320]that perhaps, they're not often reflected in the results
[00:48:52.760]or the numbers that we get from the project,
[00:48:57.350]but we are really doing an impact,
[00:48:58.940]and that's really satisfying for the whole team.
[00:49:02.140]So I hope that you enjoy it as well.
[00:49:04.370]And with that, I'm opening for questions
[00:49:07.670]and any comment that you might have for me.
[00:49:11.817]So thank you very much, Laila, for sharing the results
[00:49:16.750]from your exciting projects in Nebraska,
[00:49:19.380]dealing with the pressure to produce more,
[00:49:24.237]but at the same time, trying to do so in a way
[00:49:26.610]in which is compatible with the environment.
[00:49:28.770]I do have a question to break the ice here.
[00:49:31.070]Sure.
[00:49:31.903]Laila, at the very beginning,
[00:49:33.028]you mentioned a recent paper from last year
[00:49:36.690]where somebody in Illinois reported a 12% reduction
[00:49:40.250]in nitrogen losses due to option
[00:49:41.820]of some of these precision Ag technologies, that's great.
[00:49:46.750]I don't wanna underestimate what a 12% reduction means,
[00:49:50.980]but also it calls my tension that there is another 90%
[00:49:54.280]of the natural losses
[00:49:55.113]that seems to be not that much manageable.
[00:49:57.770]So can you elaborate a little bit more about the 90%?
[00:50:01.420]And do you have any guess about how much further
[00:50:03.810]that amount of nitrogen losses can be produced?
[00:50:08.880]Sure.
[00:50:09.920]And I would say that the comparison was between MRTN,
[00:50:15.830]so a land grant recommendation
[00:50:18.410]versus a dynamic approach would be a crop model.
[00:50:22.860]And so there's a lot of assumptions
[00:50:24.970]that made into the configuration of some of the fields.
[00:50:27.970]And so the 12% is the ballpark.
[00:50:30.540]And I agree that there's a lot of that efficiency
[00:50:34.730]that is still room for improvement.
[00:50:36.810]And so I think some of these tools
[00:50:39.750]are being implemented in large scale
[00:50:41.830]or across the entire field,
[00:50:44.040]but the setting up and the data
[00:50:45.590]that goes into some of these tools
[00:50:47.430]is not necessarily at the same resolution.
[00:50:50.060]So there's a gap in actually mimicking what are the losses
[00:50:54.590]in some of those parts of the field.
[00:50:59.800]So I can see that, that's one of the things
[00:51:02.640]that we still have opportunity to make improvements,
[00:51:05.840]as well as there's a lot of efforts
[00:51:07.840]going into better capture the dynamics
[00:51:10.680]of some of the losses.
[00:51:11.900]So from a modeling perspective,
[00:51:13.880]that's also a room for improvement.
[00:51:18.165]Okay, thank you very much.
[00:51:19.750]There are some questions in the chat,
[00:51:21.640]which I can read.
[00:51:23.960]The first one from Giermo,
[00:51:25.850]he asked about how familiar are the growers
[00:51:28.160]to take a look at to the nitrogen use efficiency?
[00:51:31.230]You show a few examples of improving NUE
[00:51:33.600]with no impact on profits.
[00:51:35.470]They recognize the possible benefits of being more efficient
[00:51:38.140]from an environmental point of view,
[00:51:40.620]given the same profit in some cases?
[00:51:43.730]Great question.
[00:51:45.470]I would say that there is a mix of growers
[00:51:50.300]being familiar with the term of nitrogen use efficiency.
[00:51:53.610]And I think that we have a lot of roles into that
[00:51:56.400]and educate and promote how to calculate that,
[00:52:00.780]how easily it could be.
[00:52:03.240]And then, I do agree that some of those growers,
[00:52:09.990]it almost feel like a competition,
[00:52:11.730]when it comes to get better metrics.
[00:52:14.230]So even though it's not impacting the profit,
[00:52:17.150]the fact that they see that they could do better
[00:52:19.440]in terms of nitrogen use efficiency,
[00:52:21.996]that promotes further change.
[00:52:26.416]But having said that, if I may Laila.
[00:52:29.010]Sure.
[00:52:29.940]Every time the farmers do something wrong,
[00:52:33.800]they're ready to put some regulations.
[00:52:35.400]So in this case, you showed that farmers
[00:52:38.440]are improving their performance with no extra benefit.
[00:52:43.130]So don't you think that they should be rewarded somehow?
[00:52:45.720]Definitely, I do.
[00:52:48.400]And so I do think that a system
[00:52:50.850]that can also reflect the good performance across the state
[00:52:55.970]is something that is gonna benefit some farmers.
[00:52:59.870]So definitely.
[00:53:00.970]I don't know what will be the perfect system.
[00:53:05.350]All right.
[00:53:06.183]Next question on the chat is from Teamo Vitty.
[00:53:07.930]He ask why you focus only on nitrogen if it varies
[00:53:12.920]because it's the only nutrient
[00:53:15.470]that can be detected with sensing tool
[00:53:17.560]or because of another reason?
[00:53:23.100]Why the focus is on nitrogen--
[00:53:24.827]Why nitrogen?
[00:53:25.660]And not on other nutrients.
[00:53:28.340]To the question, no I do think that other tools
[00:53:30.890]can be used to detect or to guide site-specific management.
[00:53:36.220]And one of the common examples
[00:53:38.860]could be (indistinct) rate
[00:53:40.520]or adjusting plant population
[00:53:42.330]depending on your limited factors.
[00:53:44.550]So these techniques are being applied to different areas,
[00:53:48.940]including use of other inputs, or pesticides, or herbicide.
[00:53:55.840]Nitrogen is the focus
[00:53:57.200]because it's a concern across the state,
[00:53:59.380]and that's where the focus of my program
[00:54:02.100]is in right now.
[00:54:04.750]But in the coming future,
[00:54:06.500]it might translate into an interaction of other factors.
[00:54:11.010]Good question.
[00:54:13.480]The next question is from Daniel Shotman.
[00:54:17.710]He asked the $1 million question.
[00:54:20.660]If this works so wonderfully,
[00:54:22.820]why only less than 25% of the farmers across the US
[00:54:26.540]have adopted these technologies?
[00:54:29.230]Yeah, I think we haven't done,
[00:54:31.787]and I hope that I gave a clear message
[00:54:35.670]on some of the gaps behind the site-specific management
[00:54:39.377]and precision Ag.
[00:54:40.890]And one of them is the associated knowledge
[00:54:43.690]and understanding of the science
[00:54:46.170]behind and some of the concepts.
[00:54:49.170]So I think we kind of burned the first try
[00:54:55.030]by just pushing something
[00:54:56.840]that we did not know where and when it would work,
[00:55:00.380]and so to come back and have a fresh start,
[00:55:04.900]I think we need to change
[00:55:06.038]the way that we show the effectiveness
[00:55:08.510]of some of these tools.
[00:55:10.040]And so get it to the same language
[00:55:12.250]that growers can understand like my increasing yield,
[00:55:15.250]how efficient I am, without making more complex,
[00:55:19.050]the current logistics that they have.
[00:55:21.110]I feel like those are factors
[00:55:22.143]that really alter that number of adoption.
[00:55:27.050]And so I think it's our job to promote it better.
[00:55:33.480]Okay, there is another question here from Linia M
[00:55:37.120]which is about regulation.
[00:55:39.900]Sometimes people lack not because of motivation,
[00:55:41.760]but rather than because of fear.
[00:55:43.060]So are farmers considering to have some of these practices
[00:55:46.270]because of fear to regulation?
[00:55:49.510]That's a great question.
[00:55:50.827]I never had someone saying that to me,
[00:55:54.640]or I never had the impression of growers
[00:56:01.590]feeling pushed to adopt that for regulations,
[00:56:05.650]but they do feel,
[00:56:07.496]they are conscious that a lot of the things
[00:56:12.230]are now looking to be more efficient,
[00:56:15.260]not necessarily get them into action.
[00:56:20.510]I'm gonna ask the same question at the end here,
[00:56:22.287]but on the positive side
[00:56:23.570]from the point of view of incentives.
[00:56:26.030]When you put these technologies in a much broader context
[00:56:29.800]and you compare it with, let's say, cover crops
[00:56:33.257]or fertilizer sources
[00:56:36.461]and whatever is out there claiming to help farmer
[00:56:39.640]to reduce nitrogen losses,
[00:56:43.860]how would you rank your approach
[00:56:47.570]and compare with those other technologies
[00:56:49.670]in the context of probability
[00:56:52.020]for impact and timeline for impact?
[00:57:01.710]And please don't say that everything is the same.
[00:57:04.930]No, I do think that no, everything is not the same.
[00:57:08.920]I'm gonna put it in practical terms.
[00:57:11.410]I think that there's more simple things
[00:57:13.870]that can be adjusted in our current systems
[00:57:17.610]that would have a bigger impact
[00:57:19.740]than pushing uniform management practices
[00:57:22.840]across the whole state.
[00:57:25.429]What I mean by that is there's no one single bullet
[00:57:28.480]or silver bullet that is gonna solve the issue.
[00:57:31.280]So perhaps cover crops works in some of the scenarios,
[00:57:35.010]but to me, adjusting the nitrogen timing
[00:57:37.187]and nitrogen rate could have a more effective
[00:57:41.110]and short-term impact.
[00:57:44.040]And perhaps I'm biased because that's what I work on.
[00:57:47.400]Fair enough.
[00:57:48.540]There was a question from Daniel, I think,
[00:57:50.220]if he's still on.
[00:57:51.700]I think he is.
[00:57:54.100]Do all the nitrogen technologies require side-dressing
[00:57:56.720]and how willing are growers to side-dress?
[00:58:00.970]I would say no, not all of them require side-dressing.
[00:58:04.680]However, there's more to increase the...
[00:58:07.687]He's still here.
[00:58:09.236]Increase the efficiency.
[00:58:12.000]It's kind of how to set the technology for success
[00:58:16.040]and the grower.
[00:58:17.210]So that's why we are pushing on the side-dress application.
[00:58:21.800]Are they willing to do it?
[00:58:24.130]Well, I didn't mention that in the project,
[00:58:27.700]but as it is right now,
[00:58:29.500]we are funding any extra expenses that the grower might have
[00:58:33.790]for trying something that is totally new for them.
[00:58:36.590]So we will pay for the side-dress application
[00:58:39.769]as well add any extra paths that they have to do.
[00:58:42.710]And so that removes some of these questions
[00:58:46.430]that they might have before they try it,
[00:58:49.310]but they're definitely willing to try it.
[00:58:51.850]So that's a good start.
[00:58:55.325]Sorry, if I may add something there,
[00:58:57.440]I think it's important to work
[00:58:58.817]on the risk of aversion attitude of farmers,
[00:59:04.290]sometimes ready with side-dress
[00:59:05.880]because it is my experience
[00:59:07.620]that sometimes when you suggest side-dressing
[00:59:10.870]or you ask those farmers who side-dress
[00:59:13.020]how much nitrogen they apply,
[00:59:14.010]they will tend to increase the nitrogen (indistinct)
[00:59:17.050]the overall nitrogen rate.
[00:59:18.609]Nitrogen rate.
[00:59:19.442]With the side-dress.
[00:59:20.275]So then you lose the benefits of side-dressing.
[00:59:23.093]Definitely.
[00:59:23.926]So I think that when we talk about side-dressing,
[00:59:25.730]we need to talk about keeping the same rate, not increasing.
[00:59:29.650]Yeah, definitely.
[00:59:30.930]Definitely.
[00:59:32.647]All right, any other question?
[00:59:34.480]Wow, there is a big picture question there
[00:59:37.230]about if you see site-specific management
[00:59:39.340]as the future of agriculture.
[00:59:43.400]I think that probably has to pivot
[00:59:48.826]in a way that it gets more embedded
[00:59:51.670]into the cropping systems
[00:59:53.560]and getting some of the knowledge that we already have
[00:59:58.730]in terms of how to manage crops a little bit better.
[01:00:02.950]So probably, it might not site-specific management per se,
[01:00:06.670]it might be something more integrated in the future.
[01:00:10.060]But I do think that it's a well proven concept.
[01:00:14.610]So if you adjust by the demand
[01:00:16.840]and the supply per part of your field,
[01:00:19.760]you should expect to have a more efficient cropping system.
[01:00:25.808]I have one question.
[01:00:26.641]I know that there are about 40, $30 of subsidies
[01:00:30.210]for farmers wishing to grow cover crops in their fields.
[01:00:33.830]Is there any subsidy for farmers who want to adopt
[01:00:36.820]some of the technologies that you are proposing here?
[01:00:40.857]Not directly, there's not.
[01:00:44.010]There is something that had launched
[01:00:46.300]or was launched last year, I think,
[01:00:48.650]to support growers that wanna do a side-dress,
[01:00:52.290]but not necessarily to promote the use of the technology.
[01:00:56.400]Sorry, I didn't mean subsidy.
[01:00:57.560]That's about all, I mean, incentives.
[01:00:59.710]Yeah, incentives, so like programs or support.
[01:01:03.400]Yeah, exactly.
[01:01:04.233]No, there's no.
[01:01:06.180]Not that I know of, let's put it that way.
[01:01:10.740]But I'm wondering what would cost
[01:01:12.600]if that would actually exist.
[01:01:15.341]Well, that's my question,
[01:01:16.530]if there is somebody willing to incentivize cover crops,
[01:01:19.800]why not to grow an approach
[01:01:21.480]that directly cuts nitrogen input?
[01:01:24.090]That's much easier than trying to sequester nitrogen
[01:01:26.360](indistinct)
[01:01:27.750]But anyway, personal opinion.
[01:01:29.550]Thank you all very much for joining us today.
[01:01:31.870]Again, if you want to follow up with Laila,
[01:01:35.400]feel free to do so.
[01:01:36.850]And Laila, once again, thank you very much
[01:01:39.070]for your willingness to present today
[01:01:41.177]and to teach us about nitrogen
[01:01:43.617]in our cropping systems in Nebraska.
[01:01:46.250]Excellent.
[01:01:47.083]Thank you, Patricio.

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Is Site-Specific Management Leading Nebraska Growers Towards Higher Nitrogen Use Efficiency?

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