Transforming Agriculture Research Through Digital On-farm Research

LAURA THOMPSON, extension educator, Nebraska Extension, University of Nebraska–Lincoln Author

10/11/2022 Added

11 Plays

Description

Advancements in digital agriculture tools have increased the scale and complexity of agricultural challenges which can be addressed through on-farm research. On-farm research has the potential to center farmers in the discovery and innovation process and integrate the research, extension and teaching missions of the university. Thompson will discuss the opportunities to leverage the changing landscape of on-farm experimentation drawing examples from the 30+ years of on-farm research in Nebraska Extension.

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[00:00:00.750]The following presentation is part
[00:00:02.670]of the Agronomy and Horticulture seminar series
[00:00:05.376]at the University of Nebraska-Lincoln.
[00:00:08.630][Guillermo Balboa] Thank you for coming.
[00:00:09.870]Welcome to the agronomy seminar series.
[00:00:12.120]For those here in the room and for those online,
[00:00:16.440]thank you for joining us on behalf of the committee.
[00:00:19.650]We have the pleasure today to introduce Laura Thompson.
[00:00:22.620]She's an associate extension educator
[00:00:24.750]at University of Nebraska-Lincoln.
[00:00:26.250]She's the coordinator
[00:00:28.500]of the Nebraska On-Farm Research Network,
[00:00:30.694]which works with agricultural producers
[00:00:33.090]to connect and set up experimental research
[00:00:36.505]on their own fields
[00:00:38.010]and then they can make use of their own data.
[00:00:40.879]Laura's research interests are in reactive
[00:00:44.280]and site specific nitrogen management.
[00:00:46.020]She got her Bachelor's, Master's,
[00:00:48.604]and now she's a PhD candidate here,
[00:00:50.547]and you are now working with Dr. Laila Puntel
[00:00:53.091]in nutrient management, especially in corn.
[00:00:56.367]And she grew up in southeast Nebraska
[00:00:58.227]and a family grain farm growing corn, beans,
[00:01:01.740]and she's actively involved still with that activity.
[00:01:05.130]So we are having her today to talk
[00:01:08.520]about transforming agricultural
[00:01:09.934]through digital on-farm research.
[00:01:12.180]So the floor is yours, and thank you for coming today.
[00:01:16.410]Thank you.
[00:01:30.690]All right, well thank you, Guille.
[00:01:33.060]So thanks for the invitation to speak.
[00:01:35.400]It's great to be able to share with you
[00:01:36.837]and excited to be able to share some of the progress
[00:01:38.988]that's been going on within our on-farm research network.
[00:01:44.453]The last couple years, one activity
[00:01:47.160]that I've got to be a part of is a group of people
[00:01:51.390]participating in on-farm research from around the globe
[00:01:53.545]that got together to try to look at some commonalities
[00:01:57.937]in our on-farm research efforts
[00:01:59.621]and really try to put together some guidelines,
[00:02:03.870]some common themes of on-farm research around the globe.
[00:02:07.380]And so one of the outputs of this is this paper,
[00:02:10.327]"On-Farm Experimentation to transform global agriculture."
[00:02:13.950]It was a really positive and fun experience
[00:02:18.294]to be able to hear from everyone
[00:02:19.710]about their different projects.
[00:02:21.060]And one of the products of this collaboration
[00:02:25.830]is this diagram that I think does a really nice job
[00:02:28.936]highlighting some of the key features and things that make
[00:02:32.130]on-farm research unique.
[00:02:33.870]So these six kind of orange circles going around there
[00:02:39.304]highlight some of the unique features of On-Farm research.
[00:02:42.630]So for our talk today,
[00:02:44.398]I'm gonna go through each of those six and kind of share
[00:02:47.190]how our Nebraska On-Farm Research Network
[00:02:49.126]approaches each of those and tries to fulfill
[00:02:52.107]on-farm experimentation principles.
[00:02:56.160]So we're also gonna make it
[00:02:57.510]a little interactive for you today.
[00:02:59.130]So it's Friday afternoon,
[00:03:00.270]so we'll try to keep everybody alert here.
[00:03:02.730]So this is a participation only,
[00:03:05.250]no grade for your quizzes today.
[00:03:07.620]But we're gonna just do a few questions
[00:03:09.066]to kind of introduce each of these themes.
[00:03:11.400]So do a true false and you can just kind of indicate.
[00:03:14.907]Researcher-driven research on experimental stations
[00:03:19.590]sometimes is not relevant to farmers
[00:03:21.780]or end users of that research.
[00:03:27.600]Probably true.
[00:03:29.910]Okay, I'm getting mostly up.
[00:03:31.650]What about farmers are more likely to believe
[00:03:34.710]research results that are done on-farm
[00:03:36.479]rather than small plot or research station research?
[00:03:40.050]Oh, I've got double thumbs up.
[00:03:42.491]So, okay, well let's kind of dive in
[00:03:44.340]and look a little bit more at these.
[00:03:45.810]So the first principle here that I think is really
[00:03:49.140]at the heart of the on-farm research is farmer centric.
[00:03:52.380]And can I move this little.
[00:03:58.980]So there's kinda three words that go with each,
[00:04:00.880]or three phrases or ideas.
[00:04:02.820]So we've got local knowledge,
[00:04:04.380]locally relevant, and productive relationships.
[00:04:07.014]So within our on-farm program,
[00:04:09.570]Oh, now I messed it up 'cause I touched it.
[00:04:11.520](laughs) Yeah.
[00:04:14.564]Okay.
[00:04:15.397]So farmers are taking an active role
[00:04:16.860]in determining their research questions,
[00:04:18.327]and so that's really at the heart of it.
[00:04:20.783]Our goal, our mission is really to have a collaborative
[00:04:24.360]and statewide program in Nebraska that allows producers,
[00:04:27.180]consultants, industry or commodity organizations,
[00:04:29.640]conservation partners and UNL
[00:04:31.620]to all come together to conduct on-farm research.
[00:04:34.184]And really, we see this fulfilling
[00:04:36.930]in a really integrated way,
[00:04:39.090]the research and Extension missions of the university.
[00:04:42.240]So the farmers are very actively involved
[00:04:44.520]in producing that research data
[00:04:47.700]that we use to inform recommendations.
[00:04:49.590]And then on the Extension side, because they've been so,
[00:04:52.211]they're intimately involved in that research
[00:04:54.780]and that discovery, they're having that transformational
[00:04:57.720]learning opportunity that leads to adoption,
[00:04:59.520]so it's a really complete integration
[00:05:01.110]of that research and extension mission.
[00:05:04.368]Along with that, the second theme,
[00:05:06.338]I think these two just go hand in hand
[00:05:08.550]and kind of our hard to untangle is the real systems.
[00:05:12.330]So these are being done in field scale
[00:05:14.994]and landscape type of systems.
[00:05:18.750]So farmers are the ones that are implementing the trials,
[00:05:20.940]collecting the data, using their own equipment.
[00:05:23.520]And so we make the protocols fit each farmer's
[00:05:25.590]unique situation, their growing conditions, their soils,
[00:05:28.480]and again, their their specific interests and questions.
[00:05:33.150]So this is kinda how we would work with producers
[00:05:35.340]to set up their study.
[00:05:36.840]Of course, producers are always
[00:05:38.400]doing experimentation of some kind anyway,
[00:05:40.560]whether they're splitting a field in half
[00:05:42.660]or maybe trying something on one field
[00:05:43.926]that they're not trying on another field,
[00:05:46.230]or maybe leaving one check strip in the field.
[00:05:48.931]So we try to work with them from where they're at
[00:05:51.690]and kinda move them towards something
[00:05:54.150]that's more robust and will give them
[00:05:55.530]more confidence in their answers or in their results.
[00:05:58.920]So this is kind of I guess the most basic layout
[00:06:01.680]that we would work with a producer.
[00:06:02.940]We've just got four replications of two treatments
[00:06:06.256]in field link strips and just moving them in that direction
[00:06:09.596]so that we can have randomization,
[00:06:11.700]replication, and statistical analysis.
[00:06:15.330]So we would go through kind of those principles,
[00:06:17.344]what each of them mean, why we're doing replication,
[00:06:20.280]why randomization, and the importance.
[00:06:23.820]Here, you can see how we start adapting that
[00:06:25.890]just in a minor way here to those real fields.
[00:06:28.560]And so this is just that treatment map
[00:06:30.387]overlaid onto an actual field,
[00:06:32.490]I think this one's north of Lincoln.
[00:06:35.340]And we work with the unique field shape,
[00:06:37.410]we work with the area that we have in the field,
[00:06:39.601]we make the widths of each treatment match
[00:06:42.210]what the equipment needs to match up to.
[00:06:44.562]And so that's what that looks like in those fields.
[00:06:48.600]Along with that, since we're working with the farmers,
[00:06:50.580]using their systems, we're using their technologies.
[00:06:53.970]And so in many cases, we're using
[00:06:55.686]their GPS logging of as-applied data
[00:06:57.964]to log where these treatments were applied
[00:07:00.360]and GPS logging and yield data to assess
[00:07:02.293]the impact of those treatments.
[00:07:05.160]And I'll talk quite a bit more about this later.
[00:07:08.747]So to the question, to the quiz question,
[00:07:12.180]how likely are farmers to believe the results?
[00:07:14.700]So one of the products that we did in 2019,
[00:07:18.090]we published this article,
[00:07:19.327]"Farmers as Researchers: In-depth Interviews to Discern
[00:07:22.140]Participant Motivation and Impact."
[00:07:24.630]And to put this work together, we interviewed 40 farmers
[00:07:27.620]who had participated in the program
[00:07:29.520]dating back from 1990 to the present.
[00:07:32.160]And these were, I believe,
[00:07:34.410]20 or so minute in-depth phone interviews.
[00:07:37.410]So we got pretty in-depth discussion with people
[00:07:40.890]who had done on-farm research,
[00:07:42.480]so all of them had participated.
[00:07:45.780]We found that 95% thought that their results
[00:07:48.120]were reliable and trustworthy.
[00:07:50.490]75% had actually put those results into practice.
[00:07:54.060]So that could be by making a change,
[00:07:55.680]it could be by confirming something
[00:07:57.300]that they already suspected.
[00:07:59.978]And then we found by putting those results into practice,
[00:08:03.810]the average increase in profit was $31 an acre.
[00:08:07.170]So really powerful to see those statistics,
[00:08:11.220]not just as an aspirational,
[00:08:13.708]what do you intend to do as a result of this research,
[00:08:16.950]but actually looking back over those 30 or so years
[00:08:21.600]and seeing what people have actually done
[00:08:22.887]and what the impact was.
[00:08:25.306]Also, I really like just some of the stories,
[00:08:27.479]we get to hear lots of nice quotes.
[00:08:29.456]And so one of those, this producer said,
[00:08:31.987]"I have crop canopy sensors for years,
[00:08:34.980]but I didn't feel confident using them.
[00:08:36.690]Now that I've seen the results, I'll use them farm wide."
[00:08:39.720]So by participating, we were able to help them overcome
[00:08:44.280]some of that technology learning curve barrier
[00:08:47.940]and get more familiar with the technology
[00:08:49.470]that they'd already seen value in,
[00:08:51.870]seen enough value in that they purchased it,
[00:08:54.150]but had difficulty getting it implemented
[00:08:55.987]for themselves and feeling confident.
[00:08:58.260]And so I think that's really powerful as well.
[00:09:02.790]All right, we're gonna move on to the next one.
[00:09:05.130]Here's your next question.
[00:09:07.530]Research done on-farm is not robust, reliable, publishable.
[00:09:17.250]You see some maybe's.
[00:09:19.290]Has anyone heard this?
[00:09:21.840]You've never heard this.
[00:09:24.330]I hear this. (laughs)
[00:09:26.970]So let's look at this,
[00:09:28.290]so one of the principles is evidence driven.
[00:09:31.350]So within our on-farm research program,
[00:09:33.600]we're really working to make sure
[00:09:35.010]that we're focusing on data, that it's iterative,
[00:09:37.650]that we have recorded observations and that it's robust.
[00:09:41.241]So for an example, this is one of the on-farm
[00:09:44.040]research reports that's presented.
[00:09:45.637]Each farmer, when they do their study
[00:09:48.330]at the end of the year, we summarize that data,
[00:09:50.880]we create a report of their individual study,
[00:09:53.640]and so this is an example of what that might look like.
[00:09:56.354]At the top, we have some just background information
[00:10:00.510]of their field, weather information, introduction,
[00:10:03.449]then we move to the results,
[00:10:05.190]and then very bullet point type summary of information.
[00:10:09.540]So the results you see here,
[00:10:11.010]we do have the statistical analysis.
[00:10:13.200]In all cases, we have yield as well as economics.
[00:10:15.870]So really try to focus on helping them
[00:10:18.278]look beyond just the yield and also thinking
[00:10:21.150]about the economic implications of that management decision.
[00:10:24.720]And then there's a lot of different other things
[00:10:26.125]that are being recorded and data that's being collected.
[00:10:28.884]So in this case we have moisture,
[00:10:30.427]some nitrogen use efficiency metrics, total nitrogen.
[00:10:34.740]In a lot of cases we have stand counts,
[00:10:36.540]we have satellite imagery, NDPI, NDRE,
[00:10:40.410]disease ratings, insect ratings, just depends on the study.
[00:10:45.620]All of these get put together into our annual peer-reviewed
[00:10:49.950]Extension Circular Publications.
[00:10:51.813]So all the reports get compiled and those are available
[00:10:55.530]as hard copies or as PDFs on our website.
[00:10:59.943]Beyond Extension Publications,
[00:11:01.800]there's also a lot of research publications
[00:11:03.330]coming out of the work though.
[00:11:05.070]And so here are a few just,
[00:11:06.330]I think this is from the last three years
[00:11:08.175]of research publications that have come out
[00:11:11.310]of on-farm research work.
[00:11:13.740]So a wide variety ranging from technology
[00:11:16.140]like multi-hybrid planters, fully fungicide in soybean,
[00:11:20.432]soybean yield gaps, UAV-based nitrogen management,
[00:11:24.620]so a variety of things there.
[00:11:28.950]All right, so we can see our focus
[00:11:31.920]really is on data-driven research.
[00:11:33.723]It's resulting in Extension Publications
[00:11:36.090]and research publications.
[00:11:39.510]All right, so we'll move to the fourth one,
[00:11:41.610]another question.
[00:11:43.350]Research done on-farm may have local relevance,
[00:11:46.740]but is not broadly applicable.
[00:11:53.706]A little slower on the response.
[00:11:55.748](laughs)
[00:11:57.690]Okay, so most people say no,
[00:11:59.010]most people think there is broad applicability.
[00:12:01.290]So I think, of course it depends on all these questions.
[00:12:04.356]But in a lot of cases farmers are doing
[00:12:09.831]what seem might seem like a unique thing
[00:12:12.540]or have a unique question.
[00:12:14.880]But as we start looking generally if one farmer
[00:12:17.970]has that question, there's going to be others.
[00:12:20.250]So the fourth I think idea here that we're on is scalable.
[00:12:24.360]So we're looking at effective processes,
[00:12:26.266]broader networks, and generalizable insights.
[00:12:30.030]So our goals are to create a broad network of farmers
[00:12:32.450]to have insights that are valuable
[00:12:33.899]to non participating farmers in the area
[00:12:36.361]that have research that's conducted in many areas
[00:12:39.540]around the state and have affected processes
[00:12:42.120]in place to scale this statewide.
[00:12:44.910]So to look at the scaling of the program,
[00:12:47.310]I wanna go back to the program Origins,
[00:12:49.050]which launched back in 1989
[00:12:51.060]within Nebraska Extension in Saunders County.
[00:12:54.445]And that that effort was very successful and took off,
[00:12:58.209]and spread to surrounding counties
[00:13:00.298]and other counties started efforts
[00:13:01.970]in other portions of the state.
[00:13:03.780]And by 2012, it was decided,
[00:13:05.370]let's bring this all together and form
[00:13:07.290]the Nebraska On-Farm Research Network.
[00:13:09.540]And since then, participation's really been growing.
[00:13:11.640]So here you can see the number of studies
[00:13:13.290]that have been completed,
[00:13:14.220]starting from 1990 up to 2019 is when I last updated.
[00:13:19.588]So you can see the first 12 here,
[00:13:22.350]there was a group of 12 pilot growers
[00:13:23.910]that each did one study in 1989-1990,
[00:13:27.540]and really see how it's taken off through the years.
[00:13:31.006]One of the keys to that is the partnerships
[00:13:33.089]we have with our commodity organizations in Nebraska
[00:13:35.850]that really sustain the program.
[00:13:37.680]And so that's our Soybean Board, Corn Board,
[00:13:39.840]Corn Growers Association, and Dry Bean Commission.
[00:13:42.870]And then beyond that we also have the opportunity
[00:13:45.390]to partner with a number of other conservation organizations
[00:13:48.571]as well as industry that really helps to grow the program.
[00:13:55.110]Really key to the local growth, though,
[00:13:57.330]is that on local Extension connection.
[00:14:01.530]And so you can see here all of our Extension educators
[00:14:03.553]around the state that really provide
[00:14:05.610]the structure and support.
[00:14:06.960]They're building those close and long term relationships
[00:14:08.949]with farmers and agronomists to be able to do this work.
[00:14:13.140]And so just a few of their faces here,
[00:14:15.385]you can see Extension educators and specialists
[00:14:18.630]working with growers to do these studies.
[00:14:22.548]So this has resulted in over 1,100 studies
[00:14:26.033]in total being completed.
[00:14:27.780]You can see all the counties in red
[00:14:29.190]where a study has been done.
[00:14:30.960]We have a few little gray ones
[00:14:32.640]to try to get filled in here still,
[00:14:35.550]but a huge number of studies in total being completed.
[00:14:38.310]And each year now, routinely in the last five or so years,
[00:14:41.400]we generally now have 80 to 100 studies that are completed.
[00:14:44.430]So this is the 2020 map.
[00:14:46.620]You can see the distribution across the state
[00:14:48.180]and kinda the general categories of studies here.
[00:14:52.410]Cover crops, crop production, crop protection,
[00:14:54.990]equipment, fertility, and nontraditional products.
[00:14:58.125]So as we have a huge variety within these topics,
[00:15:01.770]we have a huge variety of different studies
[00:15:03.810]that producers are looking at.
[00:15:06.360]So one way to try to help move
[00:15:08.370]towards some generalizable insights
[00:15:10.200]is having coordinated protocols.
[00:15:12.180]So generally, as I mentioned,
[00:15:14.610]when one farmer has a question,
[00:15:15.660]there's probably someone else
[00:15:16.650]that has that same question too.
[00:15:18.450]So this is a just a protocol that we have
[00:15:21.450]for Pivot Bio Proven.
[00:15:23.430]This is a product that a lot of producers
[00:15:24.697]have been interested in in the last couple years.
[00:15:26.933]So once we start hearing kinda interest
[00:15:30.060]building around that, we'll put together a protocol
[00:15:32.040]so that we can have an organized effort
[00:15:34.254]for the dozen or so farmers across the state
[00:15:37.470]that wanna do this test.
[00:15:39.195]So we put those together and make those available
[00:15:41.490]on our website and to all the educators participating.
[00:15:45.962]As a result of all of these studies,
[00:15:48.500]we've brought them all together
[00:15:50.453]into this searchable database.
[00:15:52.590]And so that's one way we're trying to get
[00:15:54.240]these all in one place where people
[00:15:55.752]can have more insights into these.
[00:15:58.620]So that searchable database,
[00:16:00.645]you can either search or filter,
[00:16:02.790]and then you're gonna get a list
[00:16:03.623]of all the studies that meet that specification,
[00:16:06.540]and then you can click on the PDF reports.
[00:16:08.670]So it's not yet as fully integrated,
[00:16:11.220]I would like to see all the data coming together
[00:16:14.130]into some more decision support tools down the road,
[00:16:16.484]but this is going a long way towards making that accessible
[00:16:20.370]to people and letting farmers find studies
[00:16:24.000]maybe that have been done around them
[00:16:25.260]in their area of the state,
[00:16:26.310]maybe find out about a specific topic they're interested in,
[00:16:30.570]maybe just browse and get ideas for what are people trying,
[00:16:33.480]what are people curious about?
[00:16:34.800]So bringing everything together in one place this way.
[00:16:38.940]Another thing we contribute to,
[00:16:40.380]to try to further those generalizable insights,
[00:16:43.020]is this compendium of research reports
[00:16:44.910]on the use of non-traditional materials for crop production.
[00:16:48.570]And this is maintained by Iowa State University.
[00:16:51.715]These are a lot of products that don't generally get tested
[00:16:56.316]in the research setting or don't get funding to be tested,
[00:16:59.910]but farmers are generally very curious about them
[00:17:02.340]and do like to test them quite a bit.
[00:17:03.900]So as we work with them, they kind of amass
[00:17:08.032]a certain amount of studies on a specific product or topic,
[00:17:12.090]and so we'll put together a summary report
[00:17:13.650]that can be provided to this database for people.
[00:17:17.190]Another way that we bring together the data
[00:17:19.318]to have more generalizable insights
[00:17:21.330]is through our CropWatch articles.
[00:17:23.340]So these are just three that we put out this spring
[00:17:26.495]sharing some of the results from last year.
[00:17:28.380]So we had one about Xyway fungicide,
[00:17:34.080]some on soybean yield, some about Pivot Bio again,
[00:17:37.680]so a variety of different topics.
[00:17:41.910]All right, so that was about the generalizable insights
[00:17:44.910]and scaling the on-farm research program.
[00:17:47.370]Next true false question.
[00:17:50.100]On-farm research is best for answering simple questions
[00:17:53.337]and is not well suited for answering complex questions.
[00:18:00.580]Okay, I'm seeing like some mixes.
[00:18:02.670]This is maybe the most mixed one.
[00:18:04.920]Okay, so let's look into this.
[00:18:08.040]So this fifth area is specialist-enabled.
[00:18:11.580]So here, we're looking at things like digital tools,
[00:18:13.890]added perspectives and added analytics
[00:18:15.990]and what specialists can help bring to the table.
[00:18:18.443]So I wanna look at how we can do
[00:18:20.234]some more complex designs with our on-farm research
[00:18:23.670]to really answer more detailed questions.
[00:18:26.287]So first image you're seeing here
[00:18:29.160]is a seeding rate prescription that we put together
[00:18:31.650]for a producer who wanted to test
[00:18:33.300]three different seeding rates.
[00:18:35.100]And we've laid it out in his field
[00:18:37.470]where it fits with his row direction.
[00:18:39.480]And you can see that the seeding rates are changing
[00:18:41.721]along the row direction, or along the the passes.
[00:18:46.616]After we develop this in our GIS software,
[00:18:49.536]the farmer then is able to put that into his monitor
[00:18:53.226]in the tractor and the trial is put in
[00:18:55.740]using that prescription
[00:18:56.850]and the variable rate on-the-go technology.
[00:18:59.820]So those rate changes are being made
[00:19:01.650]as he moves through the field and on-the-go,
[00:19:05.970]without having to manually make those changes.
[00:19:09.622]And then at the end of the year,
[00:19:10.560]they're recording the yield data spatially,
[00:19:12.390]these data points.
[00:19:13.639]We look at how we are able to relate those yield data points
[00:19:17.250]within each of those seeding rates
[00:19:18.651]and summarize the results of that seeding rate.
[00:19:25.065]And so that, again, is happening on-the-go for the producer.
[00:19:28.350]So this provides several opportunities, one is convenience.
[00:19:31.290]The producer is able to put in these trials
[00:19:32.870]pretty automatically, they're able to harvest
[00:19:36.240]and get the results pretty automatically.
[00:19:38.940]Second, we're able to fit in more replications
[00:19:41.100]and detect smaller differences.
[00:19:42.360]We are not confined to that field length strip anymore,
[00:19:45.960]we can change the rates as we're moving through the field,
[00:19:48.992]we can have smaller areas being tested,
[00:19:51.251]we can fit more replications into some of these fields.
[00:19:54.592]Third, and I think this one's really important,
[00:19:57.874]is we're able to test lower rates
[00:19:59.748]with less risk to producers.
[00:20:02.880]For some producers, an 80,000 seeding rate
[00:20:05.370]of soybeans might be concerning, might be risky for them,
[00:20:09.330]they might not be comfortable with that.
[00:20:11.019]But in this kind of setup, we can usually have,
[00:20:13.486]let's see, six replications here
[00:20:15.411]and involve less than one acre of area
[00:20:18.333]in that lowest seeding rate.
[00:20:20.340]So the risk is greatly reduced
[00:20:21.930]and they're a lot more willing to try out
[00:20:23.580]some of these, I'll say more extreme,
[00:20:26.210]80,000 is probably not the most extreme,
[00:20:28.080]but it depends on your perspective.
[00:20:30.259]This is also really important when we think
[00:20:31.945]about nitrogen management,
[00:20:34.650]testing some lower nitrogen rates, not something people
[00:20:37.040]really want to mess with going very low.
[00:20:39.600]But when we can lay it out and say, okay,
[00:20:41.670]only one acre of the entire field is going to be impacted
[00:20:44.175]and weigh that versus benefit of the results
[00:20:48.087]and the information you're going to be getting at the end.
[00:20:52.140]The other thing we can start
[00:20:53.040]looking at is spatial responses.
[00:20:54.814]So we can start looking at for this soybean example,
[00:20:58.650]for instance, how does that optimum seeding rate
[00:21:02.250]vary based on soil type, based on elevation,
[00:21:05.177]based on topography?
[00:21:08.480]And then finally, we can start answering
[00:21:10.590]some even more complex questions
[00:21:12.180]when we really get into using this.
[00:21:13.590]So I'm going to go through two case studies
[00:21:15.775]of how we've looked at some more complex questions
[00:21:18.870]using digital and precision eye technologies.
[00:21:22.170]So this first one, the question that we're looking at
[00:21:24.456]is how does a model-based commercial nitrogen recommendation
[00:21:28.290]perform compared to my traditional management?
[00:21:31.860]And also how does it perform
[00:21:33.840]compared to the optimum nitrogen rate?
[00:21:36.570]So here we have the model-based
[00:21:38.340]commercial nitrogen recommendation.
[00:21:39.840]This is the granular nitrogen recommendation tool.
[00:21:43.050]This is a a nitrogen model that utilizes
[00:21:45.976]soil series topography, and their proprietary model
[00:21:50.580]to put out a variable rate
[00:21:53.520]nitrogen recommendation for the field.
[00:21:55.230]So the producer wants to know how does this compare?
[00:21:57.570]If I purchase this, subscribe to this,
[00:21:59.790]how does this compare to what I was normally going to do?
[00:22:01.740]And how good is it, how close is it to the optimum?
[00:22:06.750]So this is how we set up this trial.
[00:22:08.905]First, if you look at the pink and the blue strips,
[00:22:11.790]this is where we run our kind of standard strip trial.
[00:22:14.607]And the the blue strips are where we put in
[00:22:17.310]the grower's typical nitrogen management
[00:22:19.110]and the pink is where we extract
[00:22:21.380]that granular prescription for that area.
[00:22:24.990]And that's what's running through in the pink.
[00:22:28.260]Then we can look at these colored rate blocks.
[00:22:30.949]This is where we have different nitrogen rate blocks
[00:22:33.018]that are located in different zones in the field.
[00:22:35.460]So the background is elevation,
[00:22:37.290]so we have a pretty big elevation gradient in this field,
[00:22:39.647]and we've got these nitrogen rate blocks
[00:22:41.580]placed from the higher to the lower elevation of the field.
[00:22:46.050]And within these, just for perspective and scale,
[00:22:48.540]each of these cells is 30 feet wide by 400 feet long.
[00:22:53.788]So we have kind of a unique layout
[00:22:57.300]combining strip trials and these small blocks.
[00:22:59.768]And all this information gets merged together
[00:23:02.940]into one research prescription.
[00:23:05.220]So we cut these pieces up, create this in a GIS
[00:23:09.270]and put this in the the monitor,
[00:23:11.400]and all that, those rate changes,
[00:23:13.601]the commercial prescription, the nitrogen rate blocks
[00:23:16.650]are all applied on-the-go
[00:23:18.480]as the farmer moves through the field.
[00:23:21.377]So what do we get for results?
[00:23:23.382]We get the results
[00:23:25.290]of just the standard strip trial comparison.
[00:23:27.600]Here, we're looking at the granular commercial model
[00:23:31.170]versus the grower and looking at total nitrogen rate yield,
[00:23:34.750]nitrogen use efficiency and partial profit.
[00:23:37.260]In this case, very similar if you read across the numbers,
[00:23:40.530]pretty much match throughout all these graphs.
[00:23:42.760]You can see the one difference.
[00:23:45.900]Yeah, here we've got a little bit bigger error bars.
[00:23:48.420]We know there was more variability in the rate,
[00:23:50.730]the farmer was using a flat rate,
[00:23:52.350]the model was using a variable rate.
[00:23:54.630]So on a broad sense, we can look at that strip trial
[00:23:58.260]and just kinda see as whole strips, how did it perform.
[00:24:01.710]We can also look at the small nitrogen response blocks
[00:24:04.674]and look at how each of those performed.
[00:24:06.630]So we have each one corresponding below.
[00:24:10.416]The estimated optimum nitrogen rate
[00:24:13.230]on the west end of the field being 135-ish,
[00:24:16.920]moving to a much higher economic optimum nitrogen rate
[00:24:20.850]of about 240 on the east end of the field.
[00:24:23.480]So we have a huge variation
[00:24:25.430]in optimum nitrogen rate in this field.
[00:24:28.793]So was that the model able
[00:24:31.200]to capture some of that variability?
[00:24:33.330]So here's where we can start looking
[00:24:34.620]even more in depth at those spatial questions.
[00:24:37.350]So we divided the field into management zones
[00:24:39.050]based on a number of different data layers.
[00:24:42.060]And now we can look comparing the model,
[00:24:45.528]the granular and the grower
[00:24:47.638]to that economic optimum nitrogen rate.
[00:24:51.192]So we looked at total nitrogen rate yield,
[00:24:53.490]nitrogen use efficiency and partial profit
[00:24:55.170]for each of the zones.
[00:24:56.003]But I'll just zoom in here so that you can see this
[00:24:58.500]on the total nitrogen rate on the top.
[00:25:00.379]We have our tool, granular, and the grower
[00:25:06.187]performing pretty similarly, recommending pretty similarly,
[00:25:10.110]but we can also benchmark it now and see
[00:25:11.308]how did that compare to that economic optimum nitrogen rate
[00:25:14.220]in that portion of the field.
[00:25:15.520]Well, we can see they were both applying more
[00:25:17.850]than the economic optimum nitrogen rate.
[00:25:19.500]They're both applying a little bit more
[00:25:21.180]than the UNL recommendation.
[00:25:23.490]Moving to zone two, pretty similar story.
[00:25:26.092]Moving to zone three, things get a little more interesting.
[00:25:30.090]Here, the commercial model chose
[00:25:31.860]to back off the nitrogen recommendation.
[00:25:35.070]However, the economic optimum nitrogen rate
[00:25:38.070]in this area, if you remember, was the highest.
[00:25:40.290]So both the grower and the commercial model
[00:25:43.620]were applying less than the economic optimum nitrogen rate.
[00:25:47.982]And then we can of course benchmark that
[00:25:50.520]with things like the UNL nitrogen recommendation as well.
[00:25:52.980]So starting to get even more insights
[00:25:54.852]into the spacial performance of these tools as well.
[00:26:00.180]So this is one trial that's part
[00:26:02.040]of our Conservation Innovation On-Farm Trials Grants,
[00:26:04.912]looking at precision nitrogen management.
[00:26:07.085]As part of this program,
[00:26:08.460]we're looking at 40 trials per year over three years.
[00:26:11.466]The producers who participate have the opportunity
[00:26:14.280]to pick a technology that is of interest
[00:26:17.010]and relevance to their farm.
[00:26:18.360]So the example I shared was using a crop model,
[00:26:22.040]but some are looking at remote sensing,
[00:26:24.930]crop canopy sensors, enhanced efficiency fertilizers
[00:26:27.433]and biological products.
[00:26:28.890]So different technologies that might help
[00:26:30.840]improve their nitrogen management.
[00:26:32.550]And so we're now completing the second full year
[00:26:36.840]of that project, and we'll be moving into the third.
[00:26:41.400]So the second case study,
[00:26:42.690]what about multifactor experiments?
[00:26:46.170]How easily can we do those on-farm trials?
[00:26:51.151]So we've looked a lot in our on-farm research network
[00:26:54.968]at soybean seeding rates, soybean planting dates,
[00:26:58.080]soybean varieties, all of those independently.
[00:27:01.405]Producers are moving a lot towards planting earlier,
[00:27:05.760]planting lower seeding rates, experimenting with planting
[00:27:09.060]different maturity groups in different varieties.
[00:27:12.030]Maybe if they can go to a shorter season,
[00:27:14.160]that'll allow more time for a cover crop to be established.
[00:27:18.090]So there's a lot of questions around this.
[00:27:19.590]So some producers have questions,
[00:27:21.300]Well what is the impact of these things in concert together?
[00:27:25.680]What's the optimal seeding rate
[00:27:27.390]if I'm planting early versus late?
[00:27:29.220]Is it the same for the varieties,
[00:27:31.166]all the varieties I'm using?
[00:27:32.956]So if we look at this, we've got our two varieties,
[00:27:35.880]two planting dates for seeding rates make 16 treatments.
[00:27:39.116]If we replicate that 4 times,
[00:27:41.010]we've got 64 experimental units.
[00:27:42.810]This is quite a lot for an on-farm study.
[00:27:46.350]So this is how this study got put in in a farmer's field.
[00:27:51.252]This total study area
[00:27:55.050]that's in the trial there is about 20 acres.
[00:27:57.436]And you can see we are able to,
[00:27:59.550]there's all 64 of those blocks are there.
[00:28:02.699]We have the early, we have the late,
[00:28:05.310]we have two different, these are two different
[00:28:07.500]pioneer varieties, soybean varieties,
[00:28:11.430]and then the four seeding rates that are being tested.
[00:28:14.880]So to test this, the seeding rate prescription,
[00:28:17.670]again, was developed in advance using GIS software
[00:28:21.690]so that that could be put in using
[00:28:22.950]the variable rate equipment on-the-go,
[00:28:24.900]and changes as you move
[00:28:26.850]down the length of the field while planting.
[00:28:29.822]And so here, you can see just some pictures
[00:28:32.516]of that monitor in the tractor
[00:28:35.196]after each of these got added,
[00:28:39.000]or each of these parts got completed.
[00:28:40.950]So we have the two varieties.
[00:28:42.120]That, of course, required them
[00:28:43.290]to change out the variety once to test both of them.
[00:28:48.990]And then we have the two planting dates here.
[00:28:51.540]And this has really enabled with the planting dates,
[00:28:53.880]so orange was first, so they went in
[00:28:55.950]and did the orange ones to be able to skip that blue one.
[00:28:59.640]That's really facilitated
[00:29:00.840]by the GPS guidance and auto steer.
[00:29:02.580]So that really allows us to just easily skip
[00:29:06.090]over the ones that we wanna come back to,
[00:29:07.800]and keep everything lined up and planted appropriately.
[00:29:13.650]And then we have the four seeding rates here.
[00:29:15.420]So those are all being done automatically on-the-go.
[00:29:19.770]So really we're able to get all of those completed,
[00:29:22.410]all those in in a 20 acre area.
[00:29:24.720]This trial's going on this year.
[00:29:26.328]Here's some pictures of stand counts being done,
[00:29:29.520]trying to assess how that early emergence went
[00:29:32.892]for the different planting dates.
[00:29:36.232]So we'll be seeing how those turned out this fall.
[00:29:39.660]But really quite an involved study
[00:29:43.830]with a lot of factors being done on-farm.
[00:29:49.770]All right, so thinking about specialists enabled,
[00:29:52.480]we've looked at a lot of different
[00:29:56.940]information we can get, a lot of analytics,
[00:29:59.010]there's been a lot of preparation.
[00:30:01.860]I've said multiple times we developed
[00:30:03.660]this prescription in advance.
[00:30:06.090]So who are these specialists that are doing this enabling?
[00:30:09.270]It can be a variety of people,
[00:30:11.670]it could be extension educator specialists,
[00:30:14.150]it can be students, it could be the crop advisors.
[00:30:16.825]So as we think about that,
[00:30:18.840]I think a really important question
[00:30:20.610]is what are the tools and training that these people need
[00:30:22.994]to be able to enable those complicated, robust,
[00:30:28.470]and informative experimental designs and studies?
[00:30:33.001]And so we've worked to put together
[00:30:35.386]some tools that are available.
[00:30:38.190]In the top left, you're seeing
[00:30:39.240]our Grower's Guide to On-Farm Research,
[00:30:40.800]that's kind of a basic guide, comprehensive guide
[00:30:44.175]of all the basics of on-farm research,
[00:30:47.370]experimental design, things like that.
[00:30:50.130]In the bottom left, you see our digital ag on-farm,
[00:30:53.430]or Digital Ag Online Training Course.
[00:30:56.749]And in this, we have four modules.
[00:30:59.040]One is on agricultural data management software basics,
[00:31:01.890]we have one on conducting
[00:31:02.940]on-farm research with ag technology,
[00:31:04.800]one on evaluating on-farm research with ag technology,
[00:31:07.416]and then some on sensor-based nitrogen management.
[00:31:09.780]And those have been pretty heavily used already.
[00:31:13.343]We did a soft launch and have done
[00:31:17.385]almost no promoting of this training course
[00:31:21.605]while we were trying to ramp it up.
[00:31:23.910]And people are finding it and using it,
[00:31:26.820]so that's great to see.
[00:31:29.146]I know there's even some community colleges
[00:31:31.148]that are using it, so it's being used fairly broadly.
[00:31:35.580]And then in the bottom right,
[00:31:36.540]you can see a tool called FarmStat,
[00:31:39.027]And we released that this past last year, I believe.
[00:31:42.810]And so that came from the need
[00:31:44.157]that as we're visiting with producers,
[00:31:46.067]telling them of the importance
[00:31:48.240]of doing randomization replication,
[00:31:50.010]being able to have statistical analysis.
[00:31:52.290]And some of the agronomists
[00:31:53.520]in the room that are helping them.
[00:31:56.190]Well we really don't have a very easy way to do this.
[00:31:58.560]They're not wanting to learn coding,
[00:32:00.853]they don't wanna do R or SAS,
[00:32:03.164]and so how are they gonna do this statistical analysis
[00:32:05.940]and work with producers to do that?
[00:32:08.551]So this is one of those tools that we've put together.
[00:32:11.160]This is a web-based tool.
[00:32:13.260]It's very easy user interface.
[00:32:15.483]click on, click and fill in information,
[00:32:18.690]put how many treatments you had,
[00:32:20.100]how many replications, you can name the treatments,
[00:32:22.380]put what variables you've measured,
[00:32:24.000]whether that's yield or stand counts,
[00:32:26.760]whatever that might be.
[00:32:28.050]And it'll produce a complete statistical output
[00:32:30.775]as well as a very bottom line
[00:32:34.830]conclusion statement for people,
[00:32:36.420]and so that's really important as well.
[00:32:37.800]So we know that people aren't gonna necessarily know
[00:32:40.560]how to interpret that,
[00:32:41.393]we wanna provide all that information,
[00:32:43.089]but also, we wanna make it very useful.
[00:32:45.180]So at the end, we just put some bullet points
[00:32:47.910]that say starter fertilizer resulted
[00:32:51.270]in a significant yield increase,
[00:32:53.550]whatever that that conclusion might be.
[00:32:56.190]And we also have some in info bubbles on there
[00:32:58.080]that allow people to kinda make some little popups
[00:33:00.810]so they can read more and learn more
[00:33:02.430]about each of those aspects.
[00:33:04.290]So these are some of the tools that we put together.
[00:33:06.802]As the area grows and evolves,
[00:33:09.206]I think there's even more need for tools like this
[00:33:11.923]that help train these specialists
[00:33:15.420]that are gonna be working with producers.
[00:33:18.734]Right, that takes me to the last, sixth one here,
[00:33:22.964]no quiz question on this one.
[00:33:25.620]So this one, co-learning,
[00:33:27.360]joint exploration, and open innovation.
[00:33:29.940]I think this one is probably what makes on-farm research
[00:33:33.298]really unique and really special is that co-learning.
[00:33:36.720]So we have things that are traditional, like our field days.
[00:33:40.590]One of the most fun parts of the program
[00:33:44.010]and fun parts of the year is our annual meeting.
[00:33:46.440]And so at those meetings, we share and discuss
[00:33:48.810]the research results with the farmers
[00:33:50.400]who did the studies as well as neighboring farmers,
[00:33:52.770]consultants, ag industry, educator specialists,
[00:33:55.560]whoever comes to those meetings.
[00:33:57.750]And here's some of the quotes
[00:33:58.963]that we hear after those meetings in our evaluations.
[00:34:03.307]"I like farmers sharing experiences."
[00:34:05.481]They like hearing from other farmers more than us, so.
[00:34:08.617]"At annual meetings, we get to talk to others,
[00:34:11.160]share with others.
[00:34:12.270]Without that, it would be half the value."
[00:34:14.790]And then, "Good program.
[00:34:15.990]The on-farm research on my farm
[00:34:17.430]has allowed me to use less inputs
[00:34:19.350]and increase yields in the last 25 years.
[00:34:21.300]We learn a lot from each other."
[00:34:23.070]So really just showing that value of that peer to peer
[00:34:25.290]learning and bringing that out, trying to provide a venue
[00:34:28.800]and an opportunity for that to happen.
[00:34:32.070]As a result, that program generally
[00:34:34.710]has about a $6 million program value.
[00:34:37.260]That's what the producers say they give an acreage amount
[00:34:41.356]or a dollar per acre amount that that information
[00:34:44.910]that they obtained that they believe
[00:34:47.580]will have in their operation.
[00:34:49.181]We also see some increased understanding
[00:34:51.731]on different topics, I just pulled a couple of them here.
[00:34:54.327]81% had better understanding of cover crop management.
[00:34:57.357]94% had better understanding of how ag technologies
[00:35:00.490]could be used to conduct on-farm research.
[00:35:03.540]Just a couple examples.
[00:35:05.640]This statistic here, I think,
[00:35:07.140]is one of the most encouraging and exciting to me,
[00:35:10.920]that 85% said they shared their results with someone else.
[00:35:14.400]And I think that's where the real value is,
[00:35:16.230]because we can tell them, we can give answers
[00:35:19.860]or share what we think are exciting results,
[00:35:22.290]but I think that peer to peer learning
[00:35:24.598]just is going to be so much more impactful
[00:35:27.267]and meaningful and produce more behavior change,
[00:35:31.080]so it's really encouraging to see
[00:35:32.430]that that many are sharing their research results
[00:35:34.541]with their neighbors and their friends.
[00:35:39.561]Back to this long term impact study.
[00:35:42.905]I wanted to share one of the things
[00:35:45.750]that we asked about was motivations
[00:35:47.231]and their experience participating.
[00:35:51.000]So most of the people in this survey
[00:35:53.790]reported that they had a good or positive experience,
[00:35:56.430]but we wanted to know why, what was the reason for that?
[00:35:59.700]And the first was that they said they liked
[00:36:01.568]the university people they worked with,
[00:36:03.660]they described them as helpful,
[00:36:05.070]responsive, energetic, supportive.
[00:36:07.890]And the second was they found value
[00:36:09.480]in the interactions at the annual meetings.
[00:36:11.850]So really this points to that social aspect,
[00:36:14.508]the co-learning aspect, the networking aspect,
[00:36:17.294]and really the idea that providing those social
[00:36:19.590]and networking opportunities with peers
[00:36:21.045]is a really important and integral part
[00:36:23.490]of an on-farm research program and the success of it.
[00:36:26.250]So I think it's easy to overlook that,
[00:36:28.230]we get caught up in the data,
[00:36:29.488]protocols, making things robust,
[00:36:31.890]making all the insights that we can get out of it,
[00:36:35.400]all the data points that we can collect.
[00:36:37.170]But really it's about the people,
[00:36:38.995]it's about the social interactions,
[00:36:40.770]that networking and learning together.
[00:36:44.095]Finally, with co-learning.
[00:36:47.269]I generally at least think about that
[00:36:50.160]as farmers learning together or maybe
[00:36:51.990]specialist educators learning with farmers.
[00:36:54.470]So I think there's a real opportunity here
[00:36:56.270]for graduate student and undergraduate students
[00:36:59.550]to be part of that co-learning
[00:37:00.990]as they're working with extension educators,
[00:37:03.240]extension specialists, agronomists, farmers.
[00:37:05.517]And so here's a few images of students,
[00:37:07.807]grad students and interns over the years
[00:37:10.320]working with educators, working with farmers.
[00:37:14.194]I think that's really valuable part of their training
[00:37:18.150]to be able to have those interactions
[00:37:19.710]with farmers and learn what farmers are thinking,
[00:37:23.790]how do real farms work.
[00:37:25.554]And so this is a really, can be an important part
[00:37:28.530]of training the next generation
[00:37:29.640]of agronomist researchers, Extension professionals.
[00:37:33.750]So with that, I think we can do a few minutes
[00:37:36.690]of discussion and question, and then I'll have
[00:37:38.580]a couple concluding thoughts to wrap it up.
[00:37:41.827][Guillermo Balboa] We'll open the floor for questions.
[00:37:45.650]Mhm.
[00:37:49.620]Well I can tell you in that field,
[00:37:50.910]but are you wanting to know for this field or in general?
[00:37:53.310]I don't know what.
[00:37:54.720]In this field, that east end was lower elevation.
[00:37:58.950]Remember it was water logged
[00:38:01.286]for a good portion of the year, yeah.
[00:38:04.080]So we had significant nitrogen losses, yeah.
[00:38:09.062][Guillermo Balboa] Bottlenecks identifying
[00:38:11.177](indistinct)
[00:38:19.050]That's a great question.
[00:38:20.550]So I think one of the biggest bottlenecks
[00:38:23.612]is what I was talking about around the specialist enabled.
[00:38:28.569]As we move towards more digital tools,
[00:38:31.410]it can provide a lot of opportunity
[00:38:33.990]to answer more questions,
[00:38:35.160]a lot more convenience for farmers,
[00:38:36.959]but it takes a lot more time on the post processing
[00:38:39.818]on the back end after that data's collected.
[00:38:43.500]When we just used whey wagons,
[00:38:45.000]we literally left with everything
[00:38:47.215]on tabular on a piece of paper.
[00:38:49.502]The data was there,
[00:38:51.142]it just had to be typed into Excel
[00:38:53.070]and you can do this in 30 minutes.
[00:38:55.855]Now it's a lot more complicated getting that data files,
[00:39:00.330]doing that post processing,
[00:39:02.820]extracting the spatial information,
[00:39:04.710]extracting the spatial yield points.
[00:39:06.690]And along with the time that's required,
[00:39:09.180]just that skill set that's needed to do that.
[00:39:12.058]So more automation and processes to do that,
[00:39:15.960]more training, more people.
[00:39:18.572]I think all those are needed to try to facilitate that.
[00:39:22.950]Mm, yeah, so we've worked a little bit
[00:39:26.116]with a few other crops, but primarily row crops,
[00:39:29.340]like wheat, dry edible beans.
[00:39:31.590]We have worked a little bit in pasture systems as well.
[00:39:36.330]I have not worked into other things like high value things,
[00:39:39.773]orchards, vineyards, things like that.
[00:39:43.553]I know there are people working
[00:39:45.750]in on-farm research in those areas,
[00:39:47.220]but I'm not sure what specific techniques
[00:39:49.680]or methods they're using to do that.
[00:39:53.040]But I know some of those colleagues
[00:39:54.690]from that global project were working
[00:39:56.790]in those kind of environments.
[00:39:58.230]So I know that some efforts are being done in that area,
[00:40:01.238]I just don't know the details
[00:40:03.030]of what kind of adaptations
[00:40:04.560]they've had to make to work in those areas.
[00:40:07.110]Do you have any thoughts?
[00:40:12.062]Yeah.
[00:40:12.895][Audience Member 1] The ability of research to-
[00:40:16.437]Mm, sure.
[00:40:27.939][Audience Member 1] Takes a little different
[00:40:29.554]way of looking at things.
[00:40:30.977]Mhm.
[00:40:34.060][Audience Member 1] Over the years.
[00:40:37.760](indistinct)
[00:40:42.660]Right.
[00:40:46.826]Yeah, yeah.
[00:40:48.896][Audience Member 1] I could picture how it could be.
[00:40:51.219]Yeah.
[00:40:52.052]It would need some sort of.
[00:40:54.977][Audience Member 1] Take a different mindset.
[00:40:56.279]Yes, yeah.
[00:40:58.140]Interesting.
[00:40:59.940]Yeah.
[00:41:03.657][Audience Member 2] What are we seeing as the-
[00:41:07.320]Sure.
[00:41:09.120]Yep.
[00:41:13.050]Okay, the question was, in the on-farm research meetings,
[00:41:20.460]there were a lot of people,
[00:41:21.990]but how many of them were actually producers that did
[00:41:24.810]a study and how many were people who were just curious
[00:41:27.445]and wanted to come see or learn from their neighbor?
[00:41:30.599]So the answer, it really varies
[00:41:33.498]based on the location of the meetings.
[00:41:35.700]So we hold those meetings in locations,
[00:41:37.620]multiple locations around the state and in locations
[00:41:41.250]where we have a really strong history
[00:41:43.320]of on-farm research and very active
[00:41:45.306]local extension on-farm research efforts.
[00:41:48.249]There's a higher percentage that are producers
[00:41:51.180]that are doing the research and they engage
[00:41:55.740]and share their research results with the audience.
[00:41:59.143]We try to make those meetings very interactive discussion,
[00:42:03.720]not just a presenter up front.
[00:42:06.750]In areas where we haven't had
[00:42:08.880]historically as much involvement
[00:42:10.890]or as much on-farm research being done.
[00:42:13.530]We've had meetings where there was one
[00:42:16.344]or no producer in the room who had done a study.
[00:42:20.220]And those are more challenging
[00:42:21.480]because the really hallmark of those programs
[00:42:25.380]is that interaction and the producer being able to say,
[00:42:27.750]this is what I did.
[00:42:29.928]And people being able to learn from each other.
[00:42:32.160]And so that's challenging,
[00:42:33.300]but that's how it starts in an area.
[00:42:36.660]And so as we've seen, this is all before COVID of course,
[00:42:42.540]but we would go to an area where there historically
[00:42:45.386]hadn't been as much on-farm research done
[00:42:48.060]and maybe the first year we had zero
[00:42:49.670]and then one person was really interested in the program
[00:42:52.920]and so we had a couple people start doing on-farm research.
[00:42:55.167]And so then by the second year,
[00:42:57.270]maybe we have a couple people that can share
[00:42:58.980]their research results in the group.
[00:43:01.290]And so it took multiple years,
[00:43:02.940]but as we got to year four or five,
[00:43:05.400]we started having that higher percentage
[00:43:07.677]and that better interaction.
[00:43:09.060]But it really takes some patience
[00:43:10.980]and some time to build that to get there.
[00:43:15.926]I think Jed.
[00:43:23.514]So I'm just.
[00:43:35.664](indistinct)
[00:43:42.274]Yeah.
[00:43:48.607]Yeah, okay, so the question
[00:43:49.980]was about the percentages of people
[00:43:51.510]that said that they trusted the data
[00:43:53.400]that was collected and adopted the practices.
[00:43:56.250]So let me clarify, it was 95% that said they trusted it.
[00:44:00.450]So I don't know what the other 5% was doing,
[00:44:03.300]but it's a pretty small amount, I guess I'm not sure.
[00:44:06.590]There could be things that have gone wrong in their study
[00:44:09.053]that they didn't feel it was reliable.
[00:44:11.622]Maybe there was hail, wind, other events
[00:44:16.410]that made them think, this isn't broadly,
[00:44:18.150]this isn't applicable, it was too unique of a year.
[00:44:21.150]I don't know, but 5% seems reasonable
[00:44:23.100]for just things that happened.
[00:44:25.290]I think 75% were putting the results into practice.
[00:44:29.190]So the others that didn't,
[00:44:32.010]maybe they wanted more years of seeing it.
[00:44:35.160]Maybe there were other logistical challenges,
[00:44:37.500]economic challenges in actually making it happen.
[00:44:40.440]Maybe there were purchases that needed to be made.
[00:44:42.480]Maybe there was, I'll give one example
[00:44:44.430]that's fairly straightforward,
[00:44:46.055]as we move to earlier soybean planting.
[00:44:48.719]If you wanna plant our soybeans at the same time as corn,
[00:44:51.719]you might need to invest in a second planter
[00:44:53.750]and have another person that can run that planter.
[00:44:56.250]So maybe they know that it's valuable,
[00:44:58.140]but logistically it's not feasible for their operation.
[00:45:03.990]Mm, yep.
[00:45:07.350]Yes, definitely would like to continue the working
[00:45:11.520]with specialists and I think
[00:45:14.910]that's a really good connection.
[00:45:17.160]I think, Kiera.
[00:45:26.940]Mm.
[00:45:53.303]Mm.
[00:46:03.690]So the question is kind of about the motivations, right,
[00:46:07.950]of why people have chosen to participate,
[00:46:09.930]if it's just seeking yield, seeking increased profit,
[00:46:13.410]reduced input costs or more long term type of questions.
[00:46:17.400]Is that.
[00:46:18.624][Audience Member 3] So how do you make it.
[00:46:25.800]Yeah. Yeah.
[00:46:28.260]Yeah, I think it very much depends on the person
[00:46:31.484]in what they're interested in, I agree.
[00:46:35.250]I think yield is probably one of the biggest,
[00:46:38.640]input costs is really big and especially
[00:46:40.860]depending on the year and some of the input costs.
[00:46:43.350]The situation right now would lead people
[00:46:45.180]to be very interested in that.
[00:46:48.090]But we do have people that are very interested
[00:46:49.920]in those long term as well,
[00:46:51.600]and have producers that are willing to continue
[00:46:55.020]something like a cover crop experiment.
[00:46:57.370]I think we have one that's going maybe six years
[00:47:00.030]or seven years now where they've maintained
[00:47:01.650]the strips in the same place,
[00:47:02.880]and this is something they wanted to do and chose to do,
[00:47:06.697]to look at that long term impact of doing that.
[00:47:11.232]So I think it depends on the person.
[00:47:14.160]I'll say for the increase in number of studies,
[00:47:16.209]I think a lot of that is based on those local relationships,
[00:47:19.770]as well as the benefit
[00:47:23.370]that they can have by partnering with us.
[00:47:25.740]So by that I mean as they may have a more complex question
[00:47:30.275]or something that takes a little bit more to understand,
[00:47:34.857]that's where they're really gonna be interested
[00:47:37.530]in having the specialists come alongside
[00:47:40.200]and help facilitate that.
[00:47:49.011]Okay.
[00:47:49.890]I think I'll take the last five minutes then
[00:47:51.420]and kinda wrap up with a couple concluding thoughts then.
[00:47:54.510]Okay.
[00:47:55.343]So as I was preparing for the presentation,
[00:47:57.810]the last time I presented to the department
[00:48:00.030]about the On-Farm Research Program was 2016,
[00:48:02.640]so six years ago.
[00:48:03.690]So I was trying to think what has changed
[00:48:05.533]in the last six years.
[00:48:07.195]My first thought was, well, we definitely have
[00:48:09.314]more digital technologies being used.
[00:48:12.654]So I pulled up the presentation from 2016,
[00:48:16.119]and it was filled with examples
[00:48:18.150]of digital on-farm research site-specific spatial analyses.
[00:48:24.450]So I thought, well that's interesting,
[00:48:26.160]we've been using this for I guess longer,
[00:48:28.478]we've been involved in using a lot of these technologies
[00:48:31.740]and leveraging that since that time at least.
[00:48:37.260]So I started thinking some more,
[00:48:38.430]well I think we surely have still increased
[00:48:40.950]the amount that we're using these technologies,
[00:48:43.523]but I think what maybe has changed the most
[00:48:46.053]is the global perspective around this.
[00:48:48.938]And so I would say there's really a growing
[00:48:51.255]global interest that's fueled
[00:48:54.924]by these possibilities from digital agriculture.
[00:48:57.300]So what we were already using in 2016,
[00:49:00.600]I think is really a launching on a global scale.
[00:49:06.835]So you can see here, these are just the contributors
[00:49:09.870]to that paper around the globe.
[00:49:12.792]But I routinely visit with people in Canada, in the US,
[00:49:18.958]who are growing their own on-farm research programs.
[00:49:22.470]And so the number of programs that have launched
[00:49:23.952]in the last five or six years is tremendous.
[00:49:27.960]I don't have a number on that,
[00:49:29.100]but I've talked with a lot of people
[00:49:30.570]who are interested in launching a program
[00:49:32.160]and then watched their program get launched.
[00:49:33.990]And so I think that's really been fueled
[00:49:36.300]by these possibilities from digital agriculture
[00:49:38.250]and people just seeing the value
[00:49:39.229]and what we can do with this around the globe.
[00:49:42.420]So I think that's where we really can see a transformation.
[00:49:45.120]People can see how our traditional way of doing research
[00:49:48.690]can be different, can be more engaged with farmers,
[00:49:50.880]can be enabled with these technologies.
[00:49:55.260]So in conclusion, I think it helps
[00:49:59.400]to also frame this within our land grant mission.
[00:50:02.160]And so on the research side,
[00:50:04.710]on-farm research is really an opportunity
[00:50:06.540]to produce high quality publishable research
[00:50:08.910]that has relevance and applicability to end users.
[00:50:11.928]On the extension side, on-farm research
[00:50:14.310]centers the farmer and that learning
[00:50:15.810]and co-discovery process, rather than holding
[00:50:18.000]that traditional teacher to student relationship,
[00:50:20.670]and it results in high impact in behavior change.
[00:50:23.580]And then on the teaching side as well,
[00:50:24.856]whether students are participating on-farm research
[00:50:27.404]or maybe those on-farm research reports
[00:50:29.520]are being used in the classroom as case studies,
[00:50:31.938]it provides experiential learning, training in digital tools
[00:50:36.270]that students are gonna need in their future careers
[00:50:37.920]and an opportunity to learn with farmers,
[00:50:39.780]which I think is so critical.
[00:50:41.730]So I did wanna share our on-farm research website as well,
[00:50:44.790]and then my contact information.
[00:50:46.380]I'd love to continue the conversation
[00:50:47.940]with any of you afterwards.
[00:50:49.500]So thank you for listening and discussing.
[00:50:51.750]I've enjoyed it.
[00:50:54.111](audience applauding)

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Transforming Agriculture Research Through Digital On-farm Research

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