Digital Agriculture Part One

September 22, 2019

(gentle music) – [Mark] Hi, I’m Mark Hall with the Alabama Cooperative Extension System, here with Ohio State’s bright and shining star, Dr. John Fulton. Our next lesson on advanced
precision agriculture series is digital agriculture. John, as we look ahead to
precision agriculture, the importance of data is growing
and has a larger significance. Can you tell us how this how this evolution is going to work out? – [John] Mark, what farm
press doesn’t report today on something about not only technology but has the word data in it? And as we think, not only today,
but really what’s happening kind of in front of us,
just to kind of keep things progressing here, we’re
starting to call it digital ag. And so you know we had
talked about just kind of thinking ahead, where
we’re at and thinking ahead and digital agriculture is
where I think we’re heading. And so, just kind of going through. But as we look, you know, this is kind of, there’s not a company out there. It doesn’t matter what
continent, or type of company providing ag that doesn’t
have something like this that they’ve shown. And
so this gives you insight about where things are going
and for some growers, you know that maybe they’ve already got
quite a bit of connectivity on their farm but the use
of apps, leveraging consumer devices like our smartphones
and iPads, that’s just growing. I mean, I can’t think of the
number of apps today that you can utilize, either for
information or connect right to the machine, or visualize
data or get access to data. But one of the questions,
not only for farmers, I mean, Mark, you’ve been in
Extension for many years. – [Mark] Long time. – [John] Where do you see yourself,
you know, in that picture? – [Mark] Looking at a smartphone, talking to farmers about what they’re doing. When I go to party and farmers are there, you know what we do, we
get our our smartphone “Hey Mark have you seen this? “It shows the radar, it shows
what the weather’s doing, wherever you want to look,
it shows this, it shows that.” Boy this technology is
making life better, John. And everybody, old guys, young guys, everybody is “give it to me.” – [John] And there’s not a
probably commodity meeting that you don’t go to that they
probably all got smartphones and 70% of them have a
tablet or iPads with them. And so, you know this is real. This whole idea around digital ag is real. We’re at the forefront of this. I pin 2012 as a real key
where the industry said, you know what, we’ve talked
about it, we’ve tried this multiple times, but today in
2012, or that year they made a commitment and the industry
has just kind of followed. And so I don’t think the idea
around data and the components of technology being embedded
in machines is going away. This thing is here, and it’s here to stay. And so I think whether we’re Extension, we’re in the industry, you
gotta be thinking about where you’re going to plug in and
how you’re going to supply information or help growers
make money in a digital way. – [Mark] John, the data, one thing that just baffles me, is the amount of data. I was talking to Christian
yesterday, and he was talking to the IT guy for your
old system, Biosystems, talking about terabytes of information. Needed a thumb drive or an
external drive with terabyte. Man, that, wow! So much data, how are
we going to manage that? – [John] And that’s the thing,
it’s a bit overload today and if you take that terabyte
and try to upload it, we’re talking about some
of this cloud technology, it takes a while to do that. And so, we’ve got some
things to still overcome. We think about rural
coverage of wireless and even cellular connectivity,
I mean once that happens I think this will even accelerate. But, you know, this is,
the ability, like I said, we’ve talked about this, I
mean as people were connected almost 24/7, these machines
are now connecting, connected, and it’s just a matter of time
where we start to see more sensors; moisture, temperature,
similar type devices that are going to be in the
field connecting the field. But I think the thing is
apps, and kind of thinking if you’re going to serve
this industry, whether it’s here in the US, South
America, Europe or wherever. I mean, there’s some countries
today in Africa that we’ve worked with, that they
don’t have all the nice machines and things, but do you
know what they have? – What? – They have smartphones and they have cellular connectivity and they’re taking advantage of apps and so
this thing is worldwide. And so, let’s just explore,
this is how I kind of based upon a report out of Iowa a couple years ago, kind of pulled this out, and
this is how I kind of begin to explain what digital ag
and let’s just step through and talk about this. And so I
see it as kind of four buckets. We talked a lot about big data – Yes – But in reality, when we
look at some of the things in the medical profession,
the retail profession, they’re utilizing big data,
but big data really is not here in ag yet, we just have not aggregated. And we’ll talk a little
bit about that in a second. But we’ll start with precision
agriculture, we’ve been at that for a long time, Mark. We’ve been at that since the early-mid 90’s in a lot of areas of the country. But precision ag, and we’ll talk… The other thing that’s
probably the fastest growing area in this country is
prescriptive agriculture. If you go and you listen
to the precision seeding, prescriptive seeding, we
touch on that a little bit, but it’s really utilized in the data to be informed or to make recommendations. The other third part of
the leg, and you’re seeing companies provide this is
really enterprise agriculture. And that’s really bringing the business. And in that case, I think about
it’s not enterprise level, but it’s field by field understanding. It’s management of logistics,
of your machines, your grain. Bringing all that in and an
important ingredient to that is, it’s being informed by
the precision ag technology. Pulling data from it to do a better job of characterizing fuel and
things of that nature at a true cost on a field by field basis and the prescriptive agriculture. This is what I’m doing now
and the feeding that in. And so it’s kind of a
field, what I would say, it’s business, but it’s really
getting down to the detail of field by field, what
kind of money am I making. And then, as I mentioned, big
data is where we’re heading. There’s promise, we’ll talk
lightly on that in a little bit. But those are the four
buckets as I explain, that when you put them all together, that’s the world of digital agriculture. Kind of to bring some definition, to me precision agriculture is
quite simply this technology that we’ve talked about in
many of our sessions, Mark that just the technology
itself, we’ve been at this for nearly 20 years, of bringing
technology to the farm. Now it’s embedded in these machines. – [Mark] Farmers are used to doing it,
they’re comfortable with it. – [John] And whether I buy or lease a new machine it’s already there, it’s
readily available for me to use just like we talk about
air conditioning in a car. You know, I don’t check that
box anymore, it just comes. – Yes. – And then the other thing is
really basic, site-specific services and as an example
it’s going out and either grid or zone sampling and putting
a recommendation of that. That’s very basic. I measure and I react,
or I determine how much. And so that’s precision agriculture, Mark, in just very simple terms. Today we talk about this, this
is in a North America market and I think even in
Australia and Europe you’re seeing growth in this
prescriptive agriculture. But that’s where we’re
really utilizing data, collecting it, to drive
information, drive recommendations. A lot of time we think
about prescriptions. But also, being able to make
these site-specific decisions. And so really it’s getting
down to that sub-field level of being able to manage the variability. And I would say, you know,
a grower in a lot of areas of the country today,
they’re probably sharing data with three people in their area. You know, they’ve got their
seed person, they got their retail cooperative that’s
providing potentially fertilizer. They could have their dealership and they could have their agronomist. I mean, there’s easily
three or four people that are taking that data and
are generating prescriptions or some kind of information from it. That’s what I would call
prescriptive agriculture today. Kind of to the third, and
this is just as an example. In the United States
it’s very common to hear folks are implementing variable-rate seeding in the prescriptive world. Variable-rate nitrogen
is becoming popular, especially in corn. And then that adaptive
nutrient management. Maybe as an example, as I’m
taking my yield maps and generating removal maps, I’m
coupling that with my precision sampling schemes and looking at that. And so all of a sudden I’m
using the data and I’m refining my fertility application program
at a site-specific level. So those are just some very common, there’s many more out there,
fungicides and et cetera that we see, but those are, to me,
those are the three main ones that you see folks really
starting to utilize out there as relates to prescriptive agriculture. The other thing in enterprise
agriculture, we talk about ERP and again, this is kind of the business, field level management at the farm. Bringing that to the forefront
I can look at things like not only cost, and if I add,
if I mix up my crop rotation I can model that, I can look at scenarios and decide what I want to do. If I add a planter or I add a
combine or I add another truck I mean these are things that
I see again that we can do. But this is a heavily growing
field, at least in the US you’re starting to see larger
farmers take advantage of this for them to better
manage their bottom line. And so that’s kind of the
enterprise agriculture. And then the thing that
gets a lot of attention especially since 2012, is this
thing about big data, Mark. We’ve got a lot of data,
in fact you were saying, “Well how much data are we generating?” Well I can tell you, based
on some of our projections, today a corn grower can contribute a half kilobyte of data
per corn plant, per year. – Wow And you say, kilobyte, but
how many plants are out there? – [Mark]42,000 an acre. – [John] You know or 35,000, you know,
and I’m doing 2,000 acres, you know you’re talking
about thumb drives earlier about the size, well, you
take a two gig thumb drive I could fill her up real quickly with just, you know, annually. But, big data is this idea that
where it’s just not my farm it’s the aggregation of data
and then beginning to query and learn from it in different
ways than ever been. If you can pull it up in a spreadsheet, like Excel, that’s not big data. Using some of our traditional databases, that’s not big data. This requires all new kinds
of cloud technology and such. But big data, as an
example, the retail sector you know, uses it to see trends. The likes of Google, the medical
profession is beginning to do it but it brings a whole
higher order of learning and value potentially, but
we’re not quite there today. I thought this would be kind
of one good answer to that. Officially when we get to
the big data, you think about when we work on projects, Mark,
I send you the data, right? – Right – Hey you give me the summary
and analyses and send it back. Well, once the data gets
aggregated and it gets so big you’re going to have to bring
those analytic pieces to the data, because you just can’t
efficiently and effectively transmit that anymore and so
we’re going to have to take the analytical tools to
the data, versus what we’ve traditionally done, is taking
the data to the, you know, loading it into Excel, or
loading into R or SAS or GIS. So that’s good way to measure
what the difference is. – [Mark] John, do you see artificial
intelligence coming in and looking at all this big
data and being able to say, that’s problem A and that’s
problem B and that’s this and get that back to the farmer? Because it’s just so
much data, how’s anybody, how are we going to deal with it? – [John] Yeah, absolutely, and I
think you’re seeing companies trying to do that, but
the requirement there is you have to have an aggregated data set in order to explore and begin to learn. And so, it’s going to take time. I think we see those tools
being built today by companies. We call it machine learning.
– Yeah. – Those are the processes the analytical pieces that are being implemented on it. But we’re still, I think,
trying to get it to a level and learn how to really
draw value out of some of these datasets once they are built. So that’s the four components
as I see it of digital ag. And so that kind of brings us to this. You know, again, I think about this. So now farmers as they look
at, they’re using all this technology, they could be
using like the telemetry pieces technology, and now all of
a sudden I got all this data so where am I going to store
it, how am I going to share it? And if I am sharing it I’m
doing it in a big data scheme. How do I remain anonymous
if I don’t want others. You know, I’m willing to share and I’m willing to learn from it. These are now the questions, you know, and I talk even now that
a farm it’s a business, you know needs to sit down and talk about what’s your digital ag strategy. You need to, where am I going to store? We were talking about using
DropBox and Box and you know, there’s all these cloud
storage, but you know we’ve got companies all offering
their own platforms. – Yes – But, you know, that’s
something that you’ve kind of sit down and think about today. Even as an individual, right,
as a consumer out there. So, that kind of, the first
part of this discussion comes to an end, I think we’ve kind of covered, at least as I define it,
what digital agriculture is. And now we’re starting to move in all these issues around data today. – [Mark] This is exciting stuff, John. Thank you so much for sharing with us and please watch all
our precision ag videos. And we’re going to have another
one on dealing with data. So watch that, thank you. (gentle music)

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