Latest / No Dirt No Flowers Podcast / Sustainable Water Management / Ft. Mason Lanphear

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Sustainable Water Management / Ft. Mason Lanphear · No Dirt No Flowers Podcast

0:00
Hello everyone and welcome back to No Dirt, No
0:02
Flowers, Episode 5. This one's for all you hydroheads
0:06
out there as Mike will be flying solo as he interviews
0:09
Mason Landfear from Vital Agronomics. They'll
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be discussing all things water and irrigation.
0:15
So get ready to dive in and enjoy the ep. You
0:26
pre -answered last time. Land fear. Land fear.
0:30
Land fear? Yeah, just land fear. Land fear. Our
0:34
family thought that it was like a French origin,
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but now I think some of my family members have
0:42
done more of the genealogy, and it might be more
0:45
like Welsh origin. What's that genetic test?
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Oh, 23andMe? Yeah, something like that. Yeah,
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I did that a while back, and I was like 50 %
0:56
Irish. But then I've looked at it again, and
0:58
it just keeps changing as they get more data.
1:01
So I don't really know what it means. Nice. But
1:05
in retrospect, I kind of regret just giving away
1:09
that data. I think they just own my DNA now,
1:12
probably. Oh, see, now you're on board with one
1:15
of my... Yeah, the paranoia. The paranoia. The
1:18
data paranoia. The data paranoia. All right,
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we're here with Mason Lanphier from Vital Agronomics.
1:26
Yeah, excited to talk about all things irrigation.
1:29
Likewise. Yeah. Unfortunately, Drew couldn't
1:33
be with us today. He's taking a much -needed
1:36
personal day, and I guess it's questionable whether
1:40
he would have been bored by this conversation
1:41
or energized. So it's a good opportunity for
1:45
me and you to get in the weeds on some of this
1:48
stuff. Hopefully not in the weeds. We don't want
1:50
weeds out there, but get into the crop on some
1:52
of this stuff. Yep. And so we'll miss Drew, but
1:55
look forward to hearing from him on the next
1:59
podcast. Drew says water is my love language,
2:02
so one of them. Drew's or yours? Mine. Oh, yeah,
2:05
definitely. Yeah, love it. Yeah, likewise. One
2:09
of my passions. Yeah, for sure. This is a good
2:13
question. When we met, we obviously engaged around
2:17
irrigation technology when you were at your previous
2:21
company. But like, how'd you get into that? Was
2:23
it specifically irrigation technology or was
2:27
it something else that led to that? Like, I didn't
2:30
even know if I'm sure we've talked about it at
2:32
some point, but what your background was before
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that. Yeah. I mean, I didn't get into farming
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with like a specific goal of getting into irrigation
2:41
technology. You know, my, the first job out of
2:45
college was at a startup and you know, that's
2:48
how I got in touch with, with the farm. ultimately
2:51
with you and you know they were doing more like
2:54
drone monitoring especially crops looking at
2:57
monitoring variability within the fields and
2:59
you know we were working with the farm to to
3:02
you know try to address some of that variability
3:04
and you know identify some of the limiting factors
3:07
in in the crop development but you know coming
3:11
on and you know working for the farm one of the
3:14
the first things i noticed is uh that irrigation
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was just a huge challenge for you guys and so
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I saw it as a huge opportunity, and that was
3:24
ultimately what led my career path into irrigation.
3:29
Nice. Yeah, just seeing that pain point. So it
3:33
started out as kind of more of a tech background,
3:36
tech startup, and then it led to that. Yeah,
3:39
yeah. I mean, growing up in the Seattle area,
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I really didn't have any exposure to farming
3:44
whatsoever, but I've always been. you know an
3:47
outdoorsman and i knew i wanted to work with
3:49
the land in some capacity and uh so i studied
3:52
environmental sciences and and you know that
3:57
gave me you know a really good broad exposure
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to plant biology plant physiology soil science
4:04
which have been directly applicable to farming
4:07
you know i've been able to pick up a lot of the
4:10
practical skills working here at the farm yeah
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and you know i think that partnership, you know,
4:16
building Vital and also getting, you know, boots
4:20
on the ground and, you know, really becoming
4:22
the agronomist has been, you know, hugely valuable.
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Yeah. Yeah. I'm going to bookmark that the kind
4:29
of like the interaction of technology and application,
4:32
you know, and you got to have to have both of
4:35
them working symbiotically. But I mean, for the
4:38
listeners out there, I guess, disclaimer, Roy
4:41
Farms is part owner in Vital. Mason is the majority
4:46
owner, and we created this partnership because
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we had mutual interests. You know, you wanted
4:54
to grow Vital around irrigation technology and
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maybe other stuff. I don't know. That's okay.
5:01
So it's a question, but definitely around irrigation
5:03
technology right now. And Roy Farms had an interest
5:06
in having a seat at the table because we had
5:09
had some hits and misses over the years with...
5:13
our partnerships around irrigation technology
5:16
and technology implementation in general and
5:18
data ownership and you know what our say in that
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is because while the overall application and
5:27
and theory is probably not a whole lot different
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it seems like we have a little bit of uniqueness
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here in the valley or or just how we look at
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it as a farm so so we really wanted to have more
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of a partnership around building that than just
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a supplier and customer type relationship yeah
5:45
yeah and that that relationship has been so essential
5:49
to have the you know real -time feedback looped
5:52
in all the uh you know working with the the agronomy
5:56
team to you know help refine the product and
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and ultimately just figure out what what growers
6:01
actually need building software it takes a lot
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of time and even with you know advancements in
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ai it still is a tremendous amount of work and
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so having the grower right there to, to shepherd
6:15
the product roadmap and help to decide, you know,
6:19
what needs to be implemented is, is just essential.
6:22
Yep. I agree. Yeah. And we're probably gonna
6:25
get in the weeds a little bit, you know, some
6:27
of our, our stuff is, is more philosophical.
6:30
Some of it will be more scientific. This will
6:33
probably be a little bit more on the scientific
6:34
side. So, so yeah. So you left that startup and
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then came this way and split your time between
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the east side and the west side of the cascades
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and i've been spending a lot more time here over
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the last well last couple years last year in
6:52
particular and then and then this season as well
6:55
as we refine that product and really kind of
6:58
look at more of a i guess like a broader customer
7:02
base right so we got a couple hot farmers signing
7:04
on this year and you have potato grower on the
7:09
west side of the mountains am i missing anything
7:12
no yeah that's uh yeah i mean i've been you know
7:16
really just laser focused uh mainly on hops just
7:19
trying to help hop growers be as successful as
7:22
possible and you know before branching too much
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out into other other specialty crops yeah yeah
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so yeah we've talked about that a little bit
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kind of the crawl walk run mentality like don't
7:35
get let's not get too far out over our skis Yeah,
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I've learned that lesson. I have too. Yeah. Many
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times. Yeah, definitely. Yeah, so I guess talk
7:46
a little bit about what you saw when you first
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came to the ranch and your eyes were really opened
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to maybe some of the gaps between a tech company
8:02
or a tech startup or a tech provider and the
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application of that. on the farm yeah i mean
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it was an interesting first experience because
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there was still very much um in a part of the
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the farm culture was still very much kind of
8:17
a traditional approach you know going out and
8:20
checking the soil moisture manually and you know
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but at the same time there was a lot of technology
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already implemented at the farm and you know
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i think in retrospect Some of the technology
8:30
that you had implemented at the time was actually
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quite similar to what we've kind of evolved the
8:36
product into now. But there wasn't the connection
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between the traditional farming and the new technology.
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And I mean, ultimately, a lot of it just wasn't
8:46
even getting used, which seemed like a big red
8:49
flag to me. And at the same time, there was a
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lot of issues around overwatering. The farm was
8:57
using... sort of traditional et models to to
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recommend how much to to irrigate and sort of
9:04
this one size fits all recommendation model it
9:08
was ultimately really really problematic because
9:11
you know it just didn't didn't work for hops
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and you know at the time you were growing blueberries
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and and tree fruit as well but there was a lot
9:20
of a lot of challenges there and i saw those
9:23
pain points as a you know a big opportunity to
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you know kind of become the agronomist and then
9:30
build the product uh that i knew worked right
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like kind of put myself in both shoes as the
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as the developer the technology developer and
9:39
the agronomist and bridge that gap if you will
9:43
yeah and you know we've looked at a lot of different
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things over the years as part of a system and
9:50
in isolation including you know the the aerial
9:54
photography identifying weak spots and whatnot,
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which is how we originally came in contact. And
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whether that was a mostly built -out system or
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a piece of technology in isolation, I would say
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where we've struggled as a farm in the past is
10:13
really leveraging that information into decision
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-making and to where we're actually getting an
10:20
ROI on that investment. And I would say that
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part of that just had to do with the commitment
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and the mentality around it. Even though there's
10:33
layers of the organization that were 100 % behind,
10:36
you know, driving towards technology, there was
10:39
other layers that weren't, and it just broke
10:41
down the adoption. Yeah. And I think, you know,
10:44
that's also speaking of aerial imagery, you know,
10:47
one of the, the obvious limitations that you
10:50
identified, you know, looking at it from the
10:53
farmer's perspective was that it wasn't actually,
10:55
telling you what the limiting factors were. It
10:57
was telling you where you have stressed areas
11:00
in the crop. Well, yeah, and most of the time
11:02
it would be like, yeah, I know that northeast
11:03
corner of block 26 is weak. Right. Yeah, and
11:08
so the aerial imagery would, as an example, would
11:12
show that, but then how do you leverage that
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into a decision that can improve that area or
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the crop or the block? This is getting into the
11:24
weeds a little bit. What I remember with that
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aerial photography is that it would show weaknesses,
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but then once you got the fields up to capacity,
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some of the differences went away, but the impact
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still happened. And so you'd get to a point where
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things would actually look fine, but there was
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already an impact that happened that led to some
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reduced yield in that segment of the block, right?
11:50
Yeah, and I think there are... Definitely some
11:53
viable use cases for remote sensing and aerial
11:57
imagery in farming. And I've seen some really
12:00
cool use cases, mapping weed densities, mapping
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weed populations. And we can talk about it in
12:07
a bit, but bringing in satellite imagery for
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ET modeling, evapotranspiration modeling, I think
12:16
is a really great use case. And, you know, maybe
12:18
not on the drone side, but satellites, we can
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scale up to tens of thousands, hundreds of thousands
12:24
of acres and provide that to growers in an economical
12:28
price point. So we talked a little bit about
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the hurdles with the adoption. But one of the
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more technical hurdles that we had was around
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what ET model we were using. Right. And so you
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got the university stations out there, weather
12:50
stations and that are feeding it. And then you
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have, you know, we've even installed our own
12:55
regional or local weather stations. And I think
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you've pulled data in a few other ways. So talk
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a little bit about the the modeling part of it,
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because there's a lot of soil sensors out there.
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how much water you're applying, and, you know,
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just the automation of turning valves on and
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off. But like, how does all that work together
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in kind of the product that you've created now?
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And what was the limitations in the modeling
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and how have you improved on that? Yeah, that's
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a great question. You know, so just to give some
13:36
context on traditional ET models, you know, they're
13:40
typically a, you know, theoretical. model for
13:44
a grass or alfalfa reference crop of fixed height
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and so um and it's also assuming that it's a
13:52
well -watered grass crop and so you've got this
13:55
continuous canopy uh you're irrigating the entire
13:57
surface you know typically with a pivot or overhead
14:00
system so you've got a lot more soil evaporation
14:03
you got a lot more transpiration because it's
14:05
a continuous canopy and then you try to bring
14:08
that into hops and where you've got drip irrigation
14:10
a non -continuous canopy And, you know, those
14:15
grass reference ET models, they grossly overestimate
14:20
the actual consumptive need of the crop. And
14:23
so it was no wonder that we were overwatering
14:25
based on these models. And some agronomists will
14:29
tell you, well, that's why you should use a crop
14:31
coefficient. My perspective is that's just a
14:33
lot of guesswork. We had applied some different
14:36
crop coefficients over the years, and we were
14:40
still overwatering. Yeah. And I mean, and maybe
14:44
those models work if you're growing alfalfa,
14:47
but we're growing hops. And so, you know, that
14:49
was one of the first challenges that I wanted
14:52
to solve was to get a more accurate ET, either
14:57
model or measurement. You know, the farm invested
15:00
quite a bit in these weighing lysimeter trials,
15:03
which are basically these large scales out in
15:05
the field that are weighing the. the soil and
15:07
the crop and as as the crop uses water you can
15:10
measure that weight change and so we were directly
15:13
measuring it and those are kind of the gold standard
15:16
uh the most accurate but it's just not scalable
15:18
no i mean just i mean to talk a little bit about
15:21
that what we manufactured like a big like three
15:24
by three by three metal box and then put that
15:27
inside of a slightly larger metal box and then
15:30
had scales incorporated into that and then had
15:33
to like go out dig a pit in the field fill it
15:37
with dirt, put a hop plant in it and start like
15:40
measuring. Yeah. Basically like drain out and
15:43
usage and everything. It was super interesting.
15:46
Don't get me wrong, but it was, you know, not
15:49
a scalable agronomic product. Yeah. But you learned
15:52
through that process, right? Yeah. Yeah. I mean,
15:55
we learned that, you know, these models were
15:57
grossly overestimating the actual ET. And so
16:02
we knew that we needed something different. And
16:06
so, you know, we tested things like ground based
16:09
spectrometers, satellite imagery to try to get
16:13
a more empirical measurement or estimation of
16:17
what that crop coefficient is to to convert those
16:20
reference models to the actual crop water needs.
16:24
But we were still running up against these issues
16:27
of not having that direct measurement. And this
16:31
past season, we deployed. the evapotranspiration
16:36
sensors from lycor environmental and how those
16:40
work is we install this sensor above the canopy
16:44
you know like about six feet above the canopy
16:46
up on top of the trellis and it's measuring the
16:50
water vapor flux that's coming out of the field
16:52
so it's getting a direct measurement of the et
16:55
coming off of a you know particular field and
16:57
and one of the the key advantages to that is
17:00
if you try to determine how much to water based
17:04
on a moisture probe because that's kind of a
17:06
you know a typical use case for a volumetric
17:09
water content or moisture probe is to tell you
17:12
you know what the quantity of water is in the
17:14
soil and then how much you need to replenish
17:16
to get back to back to field capacity but in
17:19
a drip irrigated environment you have this non
17:21
-uniform wetting pattern and so depending on
17:24
where you place that sensor you could grossly
17:27
under overestimate the actual et or how much
17:30
water you need to replenish right and so the
17:33
real advantage of the et sensor is it's getting
17:36
a sort of ecosystem scale measurement or the
17:39
average of that field you look at the field as
17:42
kind of a small ecosystem and it helps to take
17:46
out a lot of the noise in that measurement and
17:49
and provide a much more accurate et direct et
17:53
measurement right so then if we're looking at
17:57
the modeling The automation slash input and then
18:02
the feedback loops and the adjustment and then
18:04
kind of like a rinse and repeat every week. Right.
18:07
So when you're looking at the modeling to decide
18:10
how much water you're going to apply. Are you
18:14
correlating that data with any other of the soil
18:18
sensors or how? So then talk about the next step
18:20
from basically, OK, now you got an exact number
18:23
or as exact as we can get number of. of the field
18:28
of the combined evaporation and transpiration
18:30
of that block or at least the sample size of
18:33
that block right and then what's the next step
18:35
and i and i will say that i think we talked a
18:38
little bit about satellite imagery this is where
18:40
we can use a scalable aerial imagery system to
18:46
add more granularity across like a block right
18:50
or a like a regional area right yeah for sure
18:54
so Last year, we actually had one of these ET
18:58
sensors. Based on the variety or any particular
19:03
field, you're going to have different rates of
19:07
ET. Every field is going to be pretty unique.
19:10
We had water potential sensors pretty much in
19:13
every hop yard in the operation. We had this
19:17
baseline ET measurement, which was giving us
19:20
a good foundation, but some of the yards were
19:22
pulling much harder. using a lot more water and
19:25
so we were actually increasing the recommendation
19:27
on those fields and you know you know this year
19:30
we've decided to go with more et sensors to get
19:33
kind of a better understanding of how different
19:36
varieties pull pull water at different rates
19:38
yeah and just to give an example of that speaking
19:43
about one of our varieties from latitude 46 azaka
19:46
and actually there's there's a lot of genetics
19:48
in that program that act very similarly We have
19:52
to intentionally under irrigate those at the
19:55
right times by what, roughly 20 % or something
19:59
like that. Yeah. Yeah. That sounds about right.
20:01
And the difference that we've seen in yield when
20:05
we basically irrigate, call it a normal amount.
20:10
And when we irrigate 20 % less on a Zaka is,
20:13
is about 1800 pounds, probably. if you're not
20:18
irrigating appropriately and we see as high as
20:21
like 3 ,200 pounds when we're managing that,
20:25
that, that variety appropriately. So it's a enormous
20:29
swing. Now, not every variety is going to act
20:32
that way, but there is this, it's more complex
20:38
now with all these different varieties coming
20:41
out of all these different breeding programs.
20:44
They all have some sort of, you know, nuance
20:48
or thing that you need to pay attention to more
20:52
than the other variety. Like when we had Cluster,
20:55
Cascade, Chinook, they're just robust. You can
20:59
even CTZ, you know, when we just grow massive
21:02
amounts of CTZ, you could probably like over
21:05
irrigate by 20%, under irrigate by 20%. and maybe
21:10
still be within the, and still see like the acceptable
21:15
yield levels. Now, like I just, the example I
21:19
just gave with the Zaka, it's all over the board.
21:22
Right. And maybe we'll get into this in a little
21:25
bit, but pull rates. And so when you're looking
21:27
at the evaporation transpiration sensors, and
21:29
we're looking at, you know, the pull rate of
21:31
the field, depending on the stage of growth that
21:35
that vine is in, we can see. big differences
21:39
in the pull rates that's that's another interesting
21:42
thing is it's not just about like you know 20
21:44
percent less in total water it's like when are
21:46
we applying the water and how much right yeah
21:49
and based on when you're doing burndown you know
21:52
the earlier varieties are going to be pulling
21:54
harder early in the season and you know you mentioned
21:58
satellite imagery and and i think you know the
22:01
the obvious use case there is to to get a field
22:04
level measurement of you know how developed that
22:06
field is right because et or evapotranspiration
22:10
is it's a function of uh the amount of solar
22:14
radiation uh how developed the crop is or you
22:18
know how vigorous the crop is and other other
22:21
things like temperature and wind and whatnot
22:22
but using satellite imagery we can quantify how
22:26
developed that field is and then give growers
22:30
a a much more accurate model prediction of what
22:34
the et is and and not use this one size fits
22:37
all grass reference recommendation so i'm really
22:42
excited to bring that to growers i think you
22:44
know we've built out this this network of et
22:47
sensors to get the the best ground truth data
22:50
possible and you know that that data can be used
22:54
to to train predictive models on you know how
22:58
much water you should irrigate any particular
23:00
field yeah And I think maybe we should have covered
23:03
this initially, but the reason that all this
23:07
is so important to us as a hop grower in the
23:10
Yakima Valley is because the majority of our
23:14
water, by a large margin, is from the mountains
23:19
and is from the snow melt and the annual precipitation.
23:23
And, you know, last year and this year, we're
23:26
in drought conditions. And water is the number
23:29
one input, you know. Everyone talks about labor
23:33
being the highest cost and fertilizer is next.
23:37
But as far as inputs go, you can't grow hops
23:42
without water. Right. And then we obviously want
23:47
to mitigate risk in drought years. I mean, right
23:51
now, the Rosa Irrigation District is shut down
23:55
for 10, 12 days, something like that. Could be
23:59
upwards of 13 days. Yeah, it could be upwards
24:01
of 13 days. So we just went through a big period
24:04
here on the farm where we're looking at soil
24:08
moisture and whether we've filled that profile
24:12
up and what the demand is and basically prepared
24:17
ourselves for the 13 -day shutdown. And we feel
24:21
pretty good about it, but those conversations
24:24
and actions would be a lot harder if we didn't
24:26
have this feedback loop. Definitely. Yeah. And,
24:29
you know, having not just the ET sensors, but
24:32
having, you know, two foot depth moisture sensors
24:36
has been really useful because we can get that
24:41
first irrigation down and make sure that moisture
24:44
is getting down to, you know, that two foot depth.
24:47
So we've got enough buffer going into that 13
24:49
day shutdown. that moisture profile is, is at
25:00
field capacity or slightly above field capacity.
25:03
And so, yeah, building that buffer, giving us
25:06
a lot more confidence and so that we've got enough
25:09
water to last us, you know, through the shutdown.
25:12
And then also, you know, wherever there's ponds
25:15
to irrigate with, we can use the ET data to give
25:19
the crop exactly what it needs. Nothing more,
25:21
nothing less and not waste that precious resource.
25:24
Yeah. Yeah, because we've had a project that's
25:30
still ongoing to install these ponds on the junior
25:33
irrigation district because the way that the
25:38
deliveries were designed whenever they built
25:41
the canal system, whether it was senior or junior,
25:44
is to only pull a certain amount of gallons per
25:47
hour. And when you look at the land that's serviced
25:53
by those deliveries, I would say more often than
25:56
not, the delivery rate limits you in a way that
26:02
you have to irrigate. At the peak of the season,
26:06
when you're pulling all the water that you can,
26:09
you have to irrigate the totality of that service
26:12
land over a 24 -hour period unless you have some
26:17
buffering capacity in the system. Oh, interesting.
26:21
Yeah, I didn't know that that was also the intention
26:22
behind the ponds. Yeah. so that we can take that
26:26
24 -hour delivery and we can apply it if you
26:30
have the appropriate irrigation systems apply
26:32
it in in less hours so we can put more volume
26:35
out in less hours but we're still taking delivery
26:37
over 24 hours interesting but it was also to
26:42
provide you know some buffer during shutdowns
26:46
right i mean you had them in the past so right
26:48
now when we when we aren't at full draw we're
26:53
using them as basically storage reservoirs for
26:56
the shutdown and then we can still go out there
26:58
and irrigate during the shutdown to your point
27:00
you know no more no less so we can preserve that
27:03
for as long as we can through this you know 13
27:05
day shutdown as an example but then when we get
27:09
into the peak of the season we'll identify the
27:13
call it peak demand whatever 4 p .m in the afternoon
27:16
or something you know like whenever you You probably
27:19
have a better idea, but let's just say it's like
27:21
in the afternoon. Yeah, solar noon. Yeah, solar
27:23
noon. It's like the plants are pulling the hardest.
27:26
Well, theoretically, if we could apply everything
27:29
at that time, you'd probably get better utilization,
27:32
right? And yes, you have all of the storage capacity
27:35
of the soil there, but it's still, you can end
27:39
up pushing that water down too deep and then
27:43
you're not getting full utilization of it. So
27:45
if we can irrigate in, you know, kind of making
27:48
numbers up but i think this is pretty close to
27:50
how we design the systems if we can irrigate
27:52
the 24 -hour delivery in 13 hours we get better
27:59
utilization yeah and i mean there's still quite
28:02
a bit of like night irrigation that's happening
28:05
and on the stuff that we don't have that ability
28:08
on yes right yeah yeah and then at that point
28:12
you know transpiration is basically shutting
28:14
down once this once the sun's going down yeah
28:17
So you're right. You would have much better utilization.
28:22
So that was one of the things that I think is
28:28
a carryover from some of the earlier R &D that
28:31
I still really like. Ponds are not cheap, and
28:34
so we're definitely not installing any right
28:36
now with the way the market is. But they are
28:41
fairly effective, and I think there's a happy
28:43
medium between, I would say, what... the industry
28:47
typically installs as an irrigation system and
28:51
call it the Cadillac that we've installed, right?
28:53
Like, I think we figured out, like, where the
28:56
point of diminishing returns is probably. Right.
28:59
Is it as the pond gets larger? It's kind of everything,
29:04
right? Like, when you go in and you build that,
29:06
it's like the more that you narrow down that
29:08
window of application, the more total infrastructure
29:11
you need. You need bigger ponds. You need bigger
29:14
pipes. more valves more automation on those valves
29:19
it just like keeps ratcheting up the cost you
29:23
know and then when you then when you look at
29:25
you know anti -leak systems that some people
29:28
refer to them or you know pulse irrigation you
29:31
want to limit the amount of charge up and shut
29:34
down on the system and so you know when you're
29:38
going 12 on 12 off you the system is pressurized
29:43
you know for 12 hours essentially And this is
29:47
once again in peak season. But when the system's
29:49
pressurized, everything is uniform on that block.
29:52
As soon as you shut it down and you have, let's
29:56
say, a hillside or something, you're going to
29:58
get drain out. So when you look at the drip tube
30:00
on a hillside, let's say you shut that system
30:03
on and off five times during the day because
30:05
you're trying to pulse irrigate and you're on
30:07
a hill, that lower part of that hill is going
30:09
to be like 300 % more like application rate than
30:12
the high side. even with pressure compensated
30:15
drip tape yeah and then if you don't have kind
30:18
of an anti -leak system or kind of a call it
30:21
a for maybe a more simplistic definition if you
30:26
don't have that system like holding some amount
30:28
of water or partially charged already then you
30:33
have a period of time from when you turn the
30:35
pumps on to when you to when the system is pressurized
30:39
And so like when we've done, you know, the uniformity
30:42
tests on the fields and you look at some of the
30:44
worst case scenarios, like, you know, far northeast
30:47
corner, like slight hill, you just start adding
30:50
up the variables. You can be and you start looking
30:53
at it over some period of time. You can be, you
30:56
know, 150 to 200 percent difference between the
31:01
what call it the closest drip tube to the station
31:04
and the furthest. Right. Yeah, and then you compound
31:08
that with soil variability and it becomes a big
31:12
challenge. Yeah, and one thing, the other reason
31:15
why this is important to us is, you know, we're
31:19
constantly looking at ways to be more sustainable.
31:23
And without uniform irrigation application in
31:27
our environment, and probably a lot of them,
31:30
you can't take the next steps in kind of like
31:33
biological management. and and other things that
31:39
uh like soil building organic slash regenerative
31:43
like soil techniques because i mean if you have
31:45
like one end of the field that's like a swamp
31:47
i'm over over illustrating here you know and
31:50
then like one end of the field that's you know
31:52
semi bone dry in both of those scenarios like
31:57
beneficial biological activity is going to be
32:00
limited or non -existent that's a little bit
32:04
in the weeds but yeah Okay, so talked a bit about
32:09
the ET sensors and slightly touched on how that's
32:14
helped us not only refine the vital agronomics
32:19
product, but also helped us on the farm with
32:23
more accurate application by variety and then
32:27
has really helped us in these drought scenarios.
32:31
Okay, so we're getting better modeling now. So
32:34
then when you look at that modeling and you're
32:37
looking at the other sensors, you got ET sensors
32:39
that are feeding into the modeling, and then
32:41
you have, what, two other sensors in the field?
32:45
Yeah, water potential sensors and water content
32:48
sensors. Okay, so now you're looking at this.
32:51
Let's say, I'm just saying, at the end of the
32:53
week, you're looking at next week's programming
32:56
for the... either the irrigator or the or the
33:01
irrigation automation how are you taking all
33:04
of that data and then making a decision yeah
33:08
so what i see uh you know on the market is a
33:12
lot of use of water content sensors but just
33:16
that alone is gives you kind of a limited understanding
33:19
of water in the soil because you know if you
33:23
install a moisture water content sensor in a
33:26
you know a heavier more clay type soil that moisture
33:31
content is going to be really high and then if
33:33
you install the same sensor in a really sandy
33:35
soil you know it's going to be a much lower water
33:38
content and so it really doesn't tell you anything
33:41
about the water availability that's why we've
33:45
deployed you know pretty much in every yard a
33:48
water potential sensor and and what that's telling
33:51
you is basically how hard the plants are having
33:53
to work to extract water out of the soil Um,
33:56
and, and it's pretty interesting because the
33:59
way that plants extract water from the soil is
34:02
they actually, they lower the water potential
34:04
in the roots so that water will passively move
34:07
into, move in from the soil into the roots. And
34:10
so actually measuring the water potential in
34:13
the soil is so critical because, you know, you
34:15
want to know how hard the crop is having to pull.
34:18
And even with the ET sensors telling us how much
34:21
to water, we want to have that direct measurement
34:23
out in the field. Because that's going to drive
34:27
not just yield, but quality, right? Like, you
34:30
know, your alpha acids, you know, the amount
34:32
of lupulin glands that are produced in the hop
34:34
is, you know, going to be directly tied to how
34:38
stressed the crop is. You know, if the plant
34:42
is in survival mode, it's not going to put energy
34:44
into, you know, these secondary metabolites that
34:47
the crop. The lupulin or the glands are primarily
34:52
like a defense mechanism. If they're stressed
34:55
for water, either due to low water availability
34:59
or too high salinity, the crop is going to invest
35:05
energy in maintaining basic survival. It's not
35:10
just about yield, it's about quality. Those sensors
35:14
are really critical. They also tell you... when
35:18
to irrigate right and so the water content sensors
35:21
are really useful you know particularly in the
35:23
early season to fill up that moisture profile
35:26
and get ensure that you've got enough buffer
35:29
especially in the the low application rate fields
35:33
where you know you're you can only irrigate you
35:35
know 0 .023 inches per hour and if you don't
35:39
have that buffer going into the peak demand i
35:42
mean you're not going to be able to catch up
35:46
and we saw that last year a little bit where
35:48
when we were running a bunch of analysis at the
35:52
end of the year in i mean correct me if i'm wrong
35:56
in most cases we got i would call it the bottom
36:02
to mid range of the total water but it wasn't
36:09
applied at the right timing or it wasn't applied
36:15
at the right time Yeah, I think we were replenishing
36:19
the ET, you know, for most of the operation,
36:23
but we didn't build that, you know, that initial
36:26
buffer. And so, you know, you go out in the field
36:30
and things looked like, you know, you got tons
36:31
of cones, tons of foliage, things looked great.
36:34
But the yield and quality didn't always meet
36:38
expectations, right? Yeah. And so, yeah, building
36:41
that buffer and then replenishing the ET on a
36:44
weekly basis. so that the crop never goes into
36:47
stress yeah that's the goal and you know i think
36:51
all these different sensors are very complementary
36:53
they're not it's not that one is better than
36:55
the other it's that you know the combination
36:58
of water potential water content and evapotranspiration
37:02
sensors gives you that complete holistic understanding
37:05
of how much you need to water and when you need
37:07
to water yeah maybe we'll we'll keep some of
37:11
the learnings about when like when we figured
37:15
that maybe the plants need the most water and
37:19
how that relates into crop yield is a little
37:21
bit of the secret sauce and people can reach
37:22
out to you to. Yeah. Try all the sensor to figure
37:26
that one out, but I don't want to give away everything.
37:30
Yeah, no, it's been, it's been an interesting
37:32
journey and we continue to learn when we were
37:36
looking at a better way to measure plant demand.
37:43
We had, you know, tried a lot of different stuff.
37:45
Probably some people are familiarized with it,
37:47
but you know, dendrometers, leaf temperature
37:51
sensors, and all of those gave us, I think, good
37:57
feedback in terms of how we needed to fine tune,
38:03
like kind of like the next phase. But a lot of
38:05
those had sensors had limitations in terms of
38:12
continuously getting the data because they're
38:15
they're really finicky to try and keep on the
38:18
plant or you know attached to the plant i mean
38:22
some of the stuff that we learned with with with
38:25
those was really interesting i remember as you
38:28
know on the leaf temperature i remember that
38:31
you know you can see the if the if the plant
38:34
is not in stress it's cooling itself right and
38:38
if you can apply keep applying water to it, it,
38:41
it will for the most part, like keep cooling
38:43
itself. And, and I think there is something where
38:46
like the mito, this makes sense. The mitochondria
38:49
would actually get working so fast that you would
38:52
actually see the leaf temperature exceed the
38:55
ambient air temperature for a very short period
38:58
of time. And then it would cool itself off again.
39:00
Whereas if the plant went into stress, the leaf
39:03
temperature would exceed and continue to exceed
39:05
the ambient air temperature and stay above that.
39:08
until probably until like nighttime or something
39:10
like that yeah and i can't speak to that personally
39:14
i don't i didn't you know i think we tested out
39:17
a few of those but that might have been the the
39:20
chilenos that were that were working on that
39:22
specifically yeah but yeah i mean that makes
39:24
sense you know i mean if the leaf temperature
39:27
is actually getting much warmer than the ambient
39:29
temperature that's probably a pretty severe stress
39:31
yep yeah we would see that you know from time
39:34
to time And the other one on the dendrometer
39:36
is, you know, measuring the stem diameter. You
39:39
know, you would see these micro fluctuations
39:41
between day and night. This kind of, you know,
39:45
touches on what we were just talking about with
39:47
utilization and irrigating during the day versus
39:51
at night is we would always see the stems relax
39:53
at night. So like this is on a very microscopic
39:56
scale, but the stems would relax at night and
40:01
then they would expand during the day. Or wait,
40:04
no. No, no, sorry. It was the inverse of that.
40:07
Contract during the day. Contract during the
40:08
day when they're sucking water. And if you weren't
40:12
applying enough water, you would see a larger
40:16
delta between the relaxed stem at night and the
40:20
contracted or constricted one during the day.
40:23
Right, the maximum daily shrinkage. Yeah, and
40:26
I think typically that's being used to try to
40:29
estimate the stem water potential. Yeah. And
40:34
there's some really interesting technology, specifically
40:37
microtentiometers for directly measuring the
40:40
stem water potential. But those typically only
40:43
work in tree fruit or crops with a woody lignified
40:48
stem. So I'm a huge fan of that where it works.
40:52
And I think as we branch out into tree fruit,
40:55
I think that's certainly something we ought to
40:57
explore. But in hops where you start out with
41:00
this tiny little vine. It's just, it doesn't
41:02
work. Yeah. So yeah, they worked really well
41:05
in blueberries and even better in tree fruit
41:08
because the more, you know, robust and stationary,
41:12
the stem that you're attaching it to the better.
41:15
And if anyone's been around hop vines, which
41:17
hopefully a lot of our listeners have been, they,
41:19
they move a lot, you know, and they worked better
41:23
or okay later on in the season. Like I said,
41:26
we learned a lot. Yeah. Just led us to the sensor
41:29
pack that we're using now. Very happy with it.
41:32
Yeah, and part of the way I've designed the sensor
41:36
suite is to be generalizable to the specialty
41:40
crop market. So we can install water potential,
41:44
water content probes, ET sensors, and pretty
41:47
much any specialty crop. And so that makes it
41:50
much more applicable to a broader market. Obviously,
41:55
we're not going to be going into non -irrigated
41:57
crops, but we're not going to be pigeonholed
42:00
into. you know, one particular industry. Yeah,
42:03
that's a good point. Yeah, I mean, you alluded
42:08
to the, you know, how this technology integrates
42:11
with, you know, the automation. Yeah. And, you
42:15
know, I think that's an interesting one because
42:16
it's not just a platitude. Like, I genuinely
42:19
believe that great things are never done alone.
42:22
And being able to integrate with, you know, whether
42:25
it's automation, hardware, software, analytics
42:28
platforms. You know, I think in the irrigation
42:32
space, there needs to be more collaboration to
42:36
probably not just in the irrigation. Yeah. Yeah.
42:39
Maybe in agriculture in general. Yeah. But, you
42:42
know, maybe in consumer electronics, you know,
42:44
take the Apple ecosystem, for example, like having
42:48
a closed ecosystem has been really successful
42:50
for them. But I think farming is different. And
42:53
I think we need to meet growers where they're
42:55
at and not expect them to tear out their automation
42:57
systems to deploy our closed ecosystem technology.
43:02
So I've designed it to be a system that they
43:06
can deploy our IoT telemetry systems, connect
43:09
the sensors that we're able to integrate with.
43:13
And then if the grower wants to pull data from
43:16
our API into their analytics platform, that's
43:19
something that I'm working with the farm on.
43:22
And if they want to pull in sensor data into
43:26
their automation system, they can do that. So
43:28
I'm really focused on working with other technology
43:32
providers that are very interoperable. They're
43:37
open to integration, right? Yeah. So that, yeah,
43:40
we can meet growers where they're at and build
43:42
a system, a decision support system, and an automation
43:45
system that can work for the unique needs of
43:50
each individual grower. Yeah. I think that's
43:52
really important because touching on what I talked
43:56
about earlier, which was our, you know, mindset
43:59
and adoption rate, like every farm has a different
44:02
rate of adoption. It probably looks a little
44:05
differently, you know, and everyone's got different
44:08
financial pressures. And so if they can step
44:11
into it, either mentally, operationally or financially,
44:16
then, then that just gives more options for the
44:19
grower. And some of the problems we've had in
44:23
the past as a potential customer of some of these
44:26
companies is that the data was isolated on their
44:32
platform or it had to be all their stuff. And
44:35
I mean, there's data ownership issues that I've
44:39
struggled with over the years, but staying out
44:42
of that rabbit hole. Sometimes we just really
44:47
need things integrated, and the API really helps
44:50
with that. Yeah, and I think I can work to make
44:55
the software as good as it can be, but there's
44:59
just certain things that are better suited to
45:02
bring you into other platforms. You're building
45:04
your different farming dashboards, and you want
45:07
to bring in some irrigation data, and I don't
45:10
need to do everything for you on the irrigation
45:14
space. You know, it can just be, you know, providing
45:18
the best decision support. And if you've got
45:20
other use cases for it, that's great. You know,
45:23
I think it's also it's a lot to try to to do
45:26
the decision support, but also the the automation.
45:30
I mean, that's not to say it can't be done, but
45:32
it's, you know, the grower wants to have the
45:36
best decision support and the best automation.
45:38
And I just don't I'm skeptical that that's going
45:40
to come from one company. Yeah, it's kind of
45:43
like. everyone seems to be focusing on something
45:45
else and then when you have you know the different
45:48
agendas behind the scenes sometimes not to be
45:51
a conspiracy theorist but there can just be other
45:56
driving agendas that kind of take the focus away
45:59
from the functionality of of all of that or they
46:03
have to pick one thing to focus on you know so
46:06
i mean with all of the different companies out
46:08
there a lot of people worked with different ones
46:11
and um and all the sensors there's a lot of redundancy
46:15
in the sensors um or a fair amount of redundancy
46:18
in some of the sensors what do you think is unique
46:21
to vital and what what do you think you can offer
46:24
them i mean you just talked a little bit about
46:25
it with you know kind of you know more of an
46:28
open architecture open platform openness but
46:31
like what else yeah that's a great question you
46:35
know being agnostic to the sensor hardware you
46:39
know i'm not you know married to any particular
46:42
sensor technology and so you know i can bring
46:45
in the best technology right like what i see
46:48
a lot of the times is you know platforms will
46:50
just stick with one moisture probe and that's
46:53
all they that's all they provide but we can bring
46:56
in et sensors we can bring in you know water
46:59
content sensors water potential sensors all the
47:02
best technology that's going to help growers
47:04
make the best data driven decisions and there's
47:09
no agenda behind that right it's other than Helping
47:12
growers to make the best decisions. But also
47:15
having, you know, Roy Farms as a partnership
47:17
is huge because, you know, we've got that real
47:20
-time feedback loop that is just unparalleled
47:22
access to help drive the product roadmap and
47:25
to help steer it towards, you know, real problem
47:30
solving. Yeah, I mean, I feel really good about
47:34
the partnership. And I think we've made a lot
47:39
of progress in the last... three years with the
47:42
color i mean real time back and forth of of the
47:45
product building right yeah i mean really happy
47:49
with where we're at and there's still room to
47:51
grow there for sure and i think as a well if
47:55
i put my roy farms hat on for a minute we've
47:58
always struggled with this idea of is this a
48:03
competitive advantage should we you know if we
48:06
give it out But then also really have an underlying
48:10
desire to contribute to the farming community
48:14
and help the farming community in a way that
48:17
doesn't, you know, hurt us. I think even with
48:20
us, you know, you know, we've talked about different
48:24
things like, oh, well, you know, we're maintaining
48:26
an exclusivity on the hop stuff and you can go
48:30
pursue other crops. And then that's really opened
48:35
up this year. I mean, to your point, what did
48:39
you say? Great things are never done alone. Anyway,
48:43
so it's getting out now to some other growers,
48:47
and we'll see where it goes. Yeah, no, I'm definitely
48:50
excited to branch out to other hop growers, and
48:53
I think we can learn from them. They can learn
48:55
from us. For sure. It doesn't have to be both
49:00
parties can win. So what's your elevator pitch?
49:05
Give me your elevator pitch. Yeah, so in collaboration
49:10
with Roy Farms, over the past five years, I've
49:13
been able to build HydroSync Pro, which is a
49:17
mobile software platform that enables growers
49:20
to make precise irrigation decisions using infield
49:24
IoT sensors and predictive analytics. So we're
49:28
taking the guesswork out of irrigation management.
49:32
That's good, which I really like the app, by
49:34
the way. awesome quantum leaps over yeah no i
49:38
think switching to mobile was i think a game
49:40
changer because i mean it's kind of obvious you
49:42
know you're out in the field most of the time
49:44
yeah but you know just over the past year year
49:47
and a half seeing the the adoption just go from
49:50
you know it's like day and night yep plus people
49:53
are probably getting tired of me hanging them
49:55
whenever i have full access yeah yep yeah better
50:02
visibility you know giving not just the the farm
50:06
managers access to the data but also the irrigators
50:09
right and empowering the irrigators to to see
50:13
the data and to act on it right because then
50:15
you don't have managers you know micromanaging
50:18
everyone based on the data that they're seeing
50:20
you know the people out in the field who are
50:24
who are executing on that recommendation can
50:26
can act on the data yeah but there's also a real
50:34
cost savings that comes with proper irrigation
50:37
techniques in my opinion you know if a plant's
50:40
stressed out you're gonna have more mite pressure
50:42
you have more mite sprays less cone fill less
50:47
cone fill there's a lot of interactions with
50:49
nitrogen and water and aphids and you know over
50:55
irrigation while it's not a huge deal here in
50:58
the valley can lead to More preventative sprays
51:03
over -irrigating early on in the season can lead
51:05
to more downy mildew. There is probably some
51:09
powdery mildew impacts there as well. We talked
51:15
a little bit about the biologicals and how we
51:18
really need that foundation really solid if we
51:24
want to take the next step in regenerative agricultural
51:27
practices. real real real high level is if we're
51:31
irrigating appropriately we see less chemical
51:33
usage absolutely yeah and you know that's that's
51:38
something that's near and dear to my heart my
51:40
you know my grandfather uh was in the horticulture
51:44
industry i didn't know that um you know during
51:47
the the advent of the green revolution when a
51:50
lot of these chemicals were seen as a as a silver
51:52
bullet yeah um and he ultimately passed away
51:55
from als which you know, has been linked to a
51:58
lot of these agrochemicals. We can't causally
52:03
attribute it to, you know, his experience in
52:06
horticulture, but I'd like to think that it could
52:10
have had an impact. Yeah, yeah. Yeah, I agree.
52:12
That's always been a real big passion of mine
52:15
is to try and limit some of the chemistries that
52:19
we're using, eliminate them entirely or eliminate
52:22
them as much as we can. And, you know, we look
52:25
at the whole spectrum. here on the farm between
52:28
you know where nothing is full -blown conventional
52:33
around here so it's like you know is i would
52:35
say anywhere from softer practices to you know
52:39
organic and beyond it's challenging to find the
52:44
right system and there i don't think there is
52:47
a certified system out there that checks all
52:49
the boxes and it ends up being pretty costly
52:53
to implement some of these so so i feel that
52:57
uh we can get a lot of the way there and and
52:59
one of the backbones of that i believe is is
53:02
irrigating appropriately so definitely yeah couldn't
53:06
agree more yeah yeah i think uh farmers are natural
53:10
environmentalists that was one of the coolest
53:13
things coming from an environmental science program
53:15
to you know just going straight into farming
53:18
is that um i get to help growers be you know
53:22
better stewards of the land yeah and that was
53:25
like you know one of the main reasons i you know
53:27
decided to study environmental science to get
53:30
to to help growers implement that on the ground
53:33
is just it's just so exciting yeah yeah i remember
53:36
when uh so my dad was one of the earlier pioneers
53:41
of of bringing drip irrigation to the valley
53:44
he i'm sure for different reasons saw that there
53:49
was a real opportunity to improve on the systems
53:52
that we were using at the time which is basically
53:55
you know, ditching down the fields and essentially
53:57
flood irrigating them. And there was a lot of
54:00
topsoil like movement and, you know, nutrient
54:03
movement along with that. And it was really hard
54:07
to time operations and probably we're not getting
54:12
the best crop out of it. Although that's a nuanced
54:15
discussion, but it ultimately led to easier management
54:20
and better efficiencies in certain areas. And
54:23
so. There's been a lot of, we've learned a lot
54:27
over the years. And it's funny because I don't
54:32
know if the interest and curiosity was there
54:34
before or if it was there after I made this observation.
54:42
But I remember coming back to the farm and I
54:44
remember what yard it was. It was Roy 14. It
54:49
was a CTZ yard at the time. It's now a Cascade
54:51
yard. But I was over there and I walked into
54:54
the row. I was just like, you know, new back
54:55
to the farm. And I was out walking around the
54:57
field and just kind of looking at things. And
54:59
I walked in there. I was like, what in the world
55:01
are we doing here? It's like there's a there's
55:03
massive puddles everywhere. Was it drip or? It
55:07
was drip irrigation, but it was old, you know,
55:08
42 inch spacing type stuff. Oh, wow. And so I
55:12
can't even comprehend how that even worked, quite
55:15
honestly. I mean, maybe it was just the varieties
55:18
were. could handle it better or i mean we're
55:22
irrigating you know i'm sure 12 on 12 off on
55:25
that system and but 42 inch spacing and our newer
55:29
systems now have double drip tube with 12 inch
55:32
spacing it's crazy like the the difference between
55:36
a single you know 42 and now i'm not saying double
55:41
double tubes at 12 inch spacing is yeah maybe
55:43
it's diminishing returns at a certain yeah that
55:46
might have been the diminishing returns point
55:47
i mean it works really great but you know there's
55:50
management nuances with with double 12 you know
55:53
that i would take those over the nuances of 42
55:57
right but anyway so i said man and i brought
56:01
and i started digging around and like you know
56:03
half the crown was rotted out you know and i
56:06
was like this this can't be the right way to
56:09
do this And that probably like created this curiosity
56:14
to be a nice way to say it, but kind of necessity
56:17
necessity. Yeah. Yeah. It's been interesting
56:21
to try and dig into that at times it's been frustrating
56:24
at times we've, we've been on the bleeding edge
56:28
of, of the leading edge, but still remain very
56:32
curious and excited to figure it out. Cause every
56:36
year there's a new challenge and in farming and
56:39
it's, becoming increasingly complicated to manage
56:43
these farming operations at all levels and if
56:48
there's anywhere that we can can reduce variability
56:51
or questions we need to be looking at that and
56:54
like i said like irrigation is one of the most
56:56
important things so yeah and i mean so maybe
56:59
we'd have to bring uh leslie into this to to
57:02
get his uh perspective oh he'd love to talk about
57:05
that yeah um you know, observing the shift from
57:09
real irrigation to essentially ubiquitous drip
57:13
irrigation, what do you think it's going to take
57:16
for growers to adopt sensors and a more data
57:21
-driven approach across the industry? Yeah. I
57:25
mean, I'd be really curious to hear his opinion
57:27
on that. I think it's a real hard question to
57:32
answer because we've been involved in a lot of
57:35
different crops. This is a hop -centric discussion,
57:38
so my answer will be more hop -centric. When
57:42
I look across the hop growers that I know, and
57:47
I know a lot of them, there are no bad growers
57:49
these days, right? Now, I'm sure people would
57:52
debate that, but generally speaking, if there
57:55
is a quote -unquote bad grower, it might just
57:58
be because they don't have the right tools or
57:59
information. I don't think it's because of a
58:03
lack of desire. in most cases so so it's a hard
58:07
thing because people can actually effectively
58:09
manage and crop hops a lot of ways i know growers
58:16
that have zero automation and all they do zero
58:20
automation zero sensors and they basically just
58:25
go out there and they take their historical knowledge
58:28
and what they're seeing in the field and they
58:30
make a decision and and it can work out really
58:32
great and then you have other growers like we
58:35
would be one of them you know loftus would be
58:37
another one and other ones you know that have
58:40
really tried to get under the hood of some of
58:43
this and a lot of the providers in the valley
58:46
but and i can say that we haven't always been
58:51
successful and we've probably even taken a couple
58:53
steps backwards on that journey um but i would
58:57
not want to have it any other way now and i think
59:00
that farmers are always a little quick to judge
59:05
and get defensive and so i think it's a tricky
59:10
thing to come in and say hey i can help you make
59:12
better decision making it's like what wait but
59:14
right i can do i'm doing just fine you know and
59:17
so i i see that changing with the not to like
59:23
label it as a generational thing but how do i
59:27
put this like i think that i'm slightly less
59:29
defensive than my dad and hopefully my sons are
59:34
less than me so it delete maybe it dilutes over
59:37
time and so so that's one barrier i think that
59:40
we're getting over is that the newer generation
59:42
that's coming in is maybe a little bit more open
59:45
to exploring that and i think once people can
59:55
wrap their head around the economics of it and
59:59
they have a good experience i think adoption
1:00:01
rate will increase pretty quickly but i can tell
1:00:05
you that with a lot of the companies that we've
1:00:07
used in the past it has not really led to a good
1:00:10
experience there's maybe been good experiences
1:00:13
earlier on but then they move on to something
1:00:16
else and and then you're left on your own so
1:00:20
to speak right so what do you think has led to
1:00:22
the success that we've had roy farms and vital
1:00:27
Well, I mean, one of the biggest things is just
1:00:30
that, to start with, you and I are so interested
1:00:33
in it, and you're here on the farm. So you're
1:00:36
building the product while using it, directly
1:00:42
interacting with the farm. Quite honestly, as
1:00:45
I say somewhat, but really acting as an irrigation
1:00:48
manager currently on the farm. So I think that's
1:00:53
really led to our success. Having the right goals,
1:00:58
we talk a lot about this, but I really believe
1:01:02
that there's a lot of difference in how you need
1:01:06
to manage all these different varieties. That's
1:01:08
a hard problem to solve because I've seen it.
1:01:11
I've seen it when you get the application rates
1:01:14
right, what happens to the yields. I think it's
1:01:18
not just going to happen overnight. But I think
1:01:22
once people start to play around with stuff and
1:01:24
wrap their head around the economics of it, because
1:01:26
like you and I were throwing around some of the
1:01:28
math, you know, when we're talking about rolling
1:01:31
this out this year and it wouldn't take much
1:01:35
to pay for that, like much at all, you know?
1:01:39
And so, but in a, in a challenging environment,
1:01:42
it's hard to add any cost to a system. And so
1:01:44
I don't know. I don't know if I answered that
1:01:48
very. No, that makes sense. And one of the learnings,
1:01:54
I think the past year is that the people are
1:01:56
so essential, having the people, the right people
1:01:59
who can implement the technology. Cause you know,
1:02:02
when I first came to the farm, it was, we had
1:02:05
a lot of the same technology, you know, that's
1:02:07
not to say it hasn't evolved and we brought in,
1:02:09
you know, newer, better technology, but you know,
1:02:12
having a cohesive team that can, can execute
1:02:15
on, on the data. is you know so essential because
1:02:18
you could have all the best technology and it
1:02:21
won't even be used yeah so that that's a big
1:02:24
deal i don't know how you solve that on every
1:02:26
farm like being a service provider yeah maybe
1:02:30
you can't yeah but i think we can at least partner
1:02:34
with the grower in a consultative basis to to
1:02:37
help them to take action on the data as opposed
1:02:42
to just sell them the hardware and you know once
1:02:46
we're past the honeymoon phase disengage yeah
1:02:49
so how do you scale that though i mean how do
1:02:51
you yeah so you know my vision is to have um
1:02:56
you know starting in the yakima valley to have
1:02:58
uh you know a team of technically minded agronomists
1:03:02
who can can you know work directly with the growers
1:03:05
you know to to implement these these recommendations
1:03:08
you know that's the as a foundation um and you
1:03:12
know maybe eventually we need to have a engineering
1:03:14
headquarters somewhere to to uh to scale the
1:03:18
the software side of things but i think you know
1:03:20
starting with the the agronomics and you know
1:03:24
bringing in people into the the company who you
1:03:28
know have a strong foundation in agronomy first
1:03:31
and foremost yeah and i think having a technical
1:03:34
acumen is is good but more importantly understanding
1:03:38
how how growers irrigate, how they, how they,
1:03:41
uh, fertigate and then the technology can, can
1:03:46
just aid in that. Yep. Cool. What are your last
1:03:51
thoughts and words? Yeah, I just, I just want
1:03:54
to, um, extend my, my gratitude for this opportunity.
1:03:59
I think, you know, I've always been a very entrepreneurial
1:04:01
person and the opportunity to, to bridge my passion
1:04:06
for, for plants and the environment and technology
1:04:09
and, and have this creative outlet to build something
1:04:13
for, for, for growers, but, you know, to, to
1:04:17
build something also for myself and, and ultimately
1:04:20
to be useful. I think, you know, people just
1:04:23
want to be useful. And, you know, that was something
1:04:26
I actually struggled with in the first couple
1:04:29
of years at the farm, like, you know, people
1:04:31
not using the product, sort of this feeling of
1:04:34
not, not being useful. Um, and so, you know,
1:04:38
more so than financial success, just having,
1:04:41
you know, people use the product has been just
1:04:44
so cool. Did it take you a while to kind of re
1:04:46
-engage in your enthusiasm after those first
1:04:49
couple of years? Yeah. I mean, I think, you know,
1:04:51
it was a pretty organic, you know, the, the,
1:04:54
the past two years and, you know, working with
1:04:57
Greg and the, the agronomy team has just been
1:04:59
really fruitful. So. Yeah. I just, yeah. I want
1:05:02
to thank you and the farm and everyone for giving
1:05:04
me this opportunity and sticking through with,
1:05:07
you know, through the challenges. I think, you
1:05:10
know, we've all been through a lot in the past
1:05:13
couple of years, but yeah, but yeah, just continuing
1:05:16
to persevere. Yeah. I mean, I'm grateful as well
1:05:21
because it's been really fun. And while I become
1:05:25
disengaged from time to time, because. the organization
1:05:28
pulls me in different directions. I'm really
1:05:30
excited about the progress that we made over
1:05:32
the last couple of years and kind of like where
1:05:34
I see things going and it feels like we've got
1:05:36
a really good thing going right now. And we've
1:05:38
got, everyone's bought in, we're doing it, we're
1:05:41
learning, we're growing. Like you said, we're
1:05:43
being creative. So yeah. Yeah. And then what
1:05:46
you guys said on one of the previous podcasts
1:05:48
is that, you know, It should be fun. And I feel
1:05:51
like it's really fun right now. Yeah, it is.
1:05:52
Yeah. Good. Yeah. Good point. Good point. Way
1:05:55
to pull that together. Yeah. It's good to, to
1:05:58
ground your work in something that you enjoy.
1:06:00
Yeah. Yeah. Yeah. Well, thank you. I'm very grateful
1:06:02
to you. So thanks for coming on too. Thanks Mike.
1:06:04
Yeah. All right. Thanks.