Breaking free from the chains of the past Where
truth moves faster than a Holstein calf No law
waiting on some printed page We're charting new
ground in the digital age From genomic codes
to robot facts We cut through the noise, no hold
them back not your daddy's dairy news tonight
we're sparking Welcome to the Bullvine Podcast,
where we deliver the insights that actually matter
to your dairy operation. I'm your host, and today
we're diving into a technology that could fundamentally
change how we evaluate dairy cattle. Holstein
Association USA is developing automated classification
cameras that promise to eliminate classifier
visits entirely. But here's the catch. This revolutionary
technology might only work for 40 % of dairy
farms. The rest? They're potentially priced out.
In today's Deep Dive, we're breaking down the
real economics, why 500 cow operations could
see $49 ,000 in annual returns, while smaller
dairies face an impossible math problem. We'll
explore what this means for traditional classification,
who benefits, who gets left behind, and most
importantly, what you need to know to make the
right decision for your operation. Let's get
into it. Welcome back to the Deep Dive. Today,
we're looking at something pretty big, shaking
up the Dairy World Holstein Association USA's
automated classification cameras. Honestly, it
feels like a total rethink. It really does. And
the conversation isn't really, can they make
this tech work anymore, is it? It feels like
it's shifted completely to, well, when is this
going to change everything? That's absolutely
the core of it now. We're kind of past the proof
of concept stage, you know. Now it's all about
the spreadsheets, the dollars and cents. Right.
Our mission today really is to dive deep into
the economic feasibility of this whole Build
a Better Cow project. We need to look at the
projected ROI, how that changes with herd size,
and maybe more importantly, the real world stuff,
the practical infrastructure problems you actually
hit on the farm. Yeah, the hurdles. And what
really grabs me is how... how much this system
aims to do. It's not just like those body condition
scoring cameras we've seen, the BCS ones that
basically just measure fat. No, it's way beyond
that. Holstein's going for the full package,
right? Comprehensive trait evaluation, what they
call linear scoring. Exactly. Linear scoring.
For anyone not familiar, that's not just a simple
checkbox. It's getting into the nitty gritty
details, measuring things like utter attachment,
foot angle, dairy strength. Scoring them precisely,
usually on like a one to nine scale. Which takes
a trained human eye right now. It's a highly
trained human classifier. Yeah. But this tech,
it aims to do that automatically, continuously.
And the timeline people are talking about, maybe
a launch around 2027, 2028, somewhere in there.
And the power here, it seems, isn't just about
getting an accurate score. It's about where that
data goes. Absolutely. You know, Dr. Jeffrey
Buehling, his team. They're not just building
a fancy camera. It's more like a data pipeline.
This system is designed from the ground up to
feed those scores directly into the genetic evaluation
system through the Council on Dairy Cattle Breeding.
So what that means for producers is you get this
steady stream of objective data flowing right
into your breeding decisions. It could seriously
speed up genetic progress. Okay, well, the proof
is always in the pudding, or maybe the paycheck
here. For this to really take off, the economics
have got to work. So let's start there. What's
the research saying about the potential annual
return per cow? Let's take that sort of ideal
starting point, the 500 cow dairy, maybe one
really focused on genetics. Right. So the projections,
when you combine that automated scoring with
the really detailed evaluation, they point to
a potential benefit somewhere between $66 and
$98 per cow per year, which is pretty compelling.
Okay, $66 to $98. Per cow. And where does that
value actually come from? Can you break that
down? Sure. It basically comes from four key
areas. The biggest piece seems to be better feed
efficiency. We're talking maybe $25 to $35 per
cow saved annually just by being able to fine
-tune feeding based on really precise ongoing
evaluations. Makes sense. What else? Second,
you obviously save on the traditional classification
cost. That's maybe $6 to $8 per cow. Third is
expected improvements in cow health and longevity
that could add another $20 to $30. And finally,
making more accurate genetic selections adds,
say, $15 to $25 per cow. So if you add all that
up for that 500 cow example, you're looking at
an extra, what, $33 ,000 to almost $50 ,000 a
year in value. Roughly, yeah. In that ballpark,
$33 ,000 to $49 ,000 a year. Okay. And if the
system itself costs, let's estimate maybe $150
,000, that seems plausible based on other precision
ag tech. That's a reasonable working number,
yes. And your payback period is looking like
three to five years. That's, well, that's pretty
attractive for a larger operation. Very attractive.
It makes a strong case financially. But, and
this is a big but. So most dairy farms in the
U .S. aren't 500 cows, right? So how does this
picture change when you look at, say, a 200 -cow
dairy? That's a much more common size. If the
per -cow benefit is the same, the total must
look very different. It looks very different.
And unfortunately, those benefits, they just
scale down directly. So for that 200 -cow herd,
the annual benefit drops to about $13 ,200 on
the low end, maybe up to $19 ,600. Okay. Now
you take that same $150 ,000 upfront cost. And
suddenly the payback isn't three, five years.
It stretches out. You're looking at seven point
five years. Best case scenario, maybe even out
to 11 years. Oof. Seven and a half to 11 years.
That's that's a much tougher sell, especially
when you think about how fast technology changes.
An 11 year payback is risky. It's incredibly
difficult to justify. And that leads us right
into the next major issue. It's not just about
the purchase price. It's about what you need
on the farm to even make it work. The infrastructure,
what I sometimes call the dirt and wires problem.
Right. The practical stuff. Yeah. The success
here really depends on having the right setup.
This kind of 3D imaging. It creates massive amounts
of data. We're talking huge files constantly.
So you absolutely need serious. enterprise -level
internet bandwidth. Which, let's be honest, a
lot of rural dairies just don't have. You're
lucky if you can stream a movie sometimes. Exactly.
And you need reliable power, probably with backup
systems. Plus, the camera system has to talk
smoothly to whatever herd management software
the farm is already using, without all that digital
groundwork in place. The system isn't really
a tool, it's just an expensive bottleneck, creating
data you can't even use effectively. OK, let
me push back a bit here, though. I mean, you
can hire a really top notch human classifier,
someone with years of experience for a few days
a year. Can a camera, even a fancy 3D one, truly
replicate that level of judgment? That experienced
eye. That's a really fair point. And look, the
argument for the tech isn't necessarily that
it's better than the absolute best classifier
having a perfect day. The value proposition is
more about consistency and objectivity. The camera
doesn't get tired. It doesn't have an off day.
It gives you objective measurements 24 -7. But
you're absolutely right. To get that consistency,
you need operational stability. And that's where
the farm environment itself starts to cause problems.
Real friction. Tell me about that friction. You
mentioned climate differences being an issue.
Yeah, we see basically two opposite problems
depending on where you are. Take cold climates,
think Wisconsin, upstate New York, places like
that. The big issue is lens condensation. During
morning milking, especially in winter, you get
warm, humid air from the cows and the parlor
hitting cold camera equipment. Moisture fogs
up the lenses. We've heard from producers who
literally have to spend time every single morning
wiping down those lenses just to get a usable
image. Such a classic farm reality check, isn't
it? Yeah. The lab prototype works perfectly,
but then you realize someone needs to add white
camera lens to their morning chores list. That
eats into any efficiency gain right there. It
absolutely does. And then you go to the other
extreme hot climates, Texas, Arizona, Southern
California, places where it gets seriously hot.
Right. When the barn or parlor temperature climbs
past, say, 105 degrees Fahrenheit, which happens,
the sensitive electronics in these systems can
overheat and shut down. We know of operations
that had to install dedicated cooling systems,
like little air conditioners, just for the camera
hardware. That's a significant, often unplanned,
extra cost. Adds thousands, maybe tens of thousands,
to the real investment. And I guess places in
the middle, like the Pacific Northwest or the
Mid -Atlantic, they probably deal with a mix
of humidity, rain, temperature swings, all creating
their own headaches for sensitive gear. Exactly.
It's rarely simple out in the barn. So, okay.
If the economics are tough, even for a 200 -cow
dairy, and you've got these significant infrastructure
and environmental hurdles, what does this really
mean for the majority of dairy farms in the U
.S., the smaller ones? This brings us to what
you call the 60 % problem. Yeah, the 60 % problem.
If you look at USDA data, it's pretty clear.
The vast majority of dairy farms in the U .S.,
something like 60%, are milking fewer than 100
cows. Right. The smaller family farms. Exactly.
And based on the current costs we're talking
about, this kind of automated classification
technology, it's basically out of reach for them.
The capital cost is too high. The payback period
stretches out way too long, becomes completely
unworkable. So you've got this potentially revolutionary
genetic tool, but it's really only accessible
to the largest, maybe 40 percent of the industry.
That seems to be the reality right now. Yes.
which creates a real issue if the goal is broad
genetic improvement across the entire national
herd. It does. But Holstein is a cooperative,
right? That's different from a typical tech company
that's maybe backed by venture capital and just
chasing the highest return. Does that cooperative
structure offer any potential ways to bridge
this gap for smaller producers? That's the hope.
Because they aren't solely driven by maximizing
profit for external investors, there might be
more flexibility. We have to start thinking about
different ways to access the technology beyond
just buying it outright. Alternative ownership
models. Like what? Well, think about how other
expensive technologies came into agriculture.
Ultrasound for pregnancy checks, for instance.
When that was new and expensive, individual farms
didn't usually buy the machine. Right. The vet
brought it out. It was a service. Exactly. Your
vet owned it and you paid for the service when
you needed it. You could see a similar model
emerging here. Maybe the classification organizations
themselves or even cooperatives own the camera
systems and provide the scanning as a service.
Or maybe shared equipment, like how some co -ops
share specialized feed analysis tools. That makes
a lot of sense. Treat it like a utility or a
service you pay for periodically rather than
a massive capital investment up front. Precisely.
Another factor is just time. Technology costs
tend to come down. We'll likely see the price
of these systems decrease over the next decade.
You might think about it entering the late majority
adoption phase, meaning more affordable and widespread,
maybe around 2032 to 2035. OK, so patients might
help. Patients and also looking actively for
support. Smaller operations really need to investigate
cost sharing programs. There are often state
or federal initiatives, grants, things like that,
designed to help farms adopt new technologies.
Sometimes they can cover 20, maybe 30 percent
of the investment. That could definitely tip
the scales, making a seven or 10 year payback
feel a bit more manageable. It could be the key
piece that makes it viable for some. And, you
know, all this talk about automated cameras.
It obviously changes the game for the traditional
human classifiers, too. It sounds like their
skills won't just vanish, though. More like.
Evolve. Absolutely evolve. Their expertise doesn't
become obsolete. It just shifts. Think about
when DHIA testing went from guys walking around
with whey jars to automated milk meters. The
job changed. People stopped doing the repetitive
data collection and moved into more analytical
roles, advising on feed, management, using the
data. It'll likely be similar for classifiers.
Their future roles will probably focus more on
system calibration, helping farms interpret the
huge amounts of data, providing advanced consulting,
and maybe still doing the hands -on evaluation
for the really elite, high -value animals where
subtle nuances still matter. So if we're wrapping
this up for you, the listener, maybe you're thinking
about this technology for your own operation.
There are really two big things to keep top of
mind from our discussion today. First, that ROI
reality check. The numbers look good. A solid
three to five year payback if you're running
a large 500 plus cow dairy. But for midsize,
say 200 cow operation, that payback stretches
out significantly, seven to 11 years, making
it a much tougher financial decision. And the
second point. The infrastructure. It's absolutely
critical and non -negotiable. Success hangs completely
on your farm's technical setup. You need that
robust, fast internet. You need reliable power,
probably with backup. And you need a plan for
dealing with your specific climate, whether that's
wiping lenses in the cold or installing coolers
in the heat. So before you even think about signing
a purchase order, you need to figure out the
total cost, right? Not just the camera price
tag. Are you going to need... $10 ,000 in network
upgrades or maybe $50 ,000 to add climate control
in the parlor? You need to ask the vendor hard
questions. How does the system really perform
under my barn conditions, not just in a controlled
research setting? What's the plan for technical
support when things go wrong? Exactly. And, you
know, thinking bigger picture, this all raises
a really fundamental question for the industry,
doesn't it? You have this powerful innovation,
something that truly promises to accelerate genetic
progress in dairy cattle like never before. Yeah.
But. will its main effect be to speed up consolidation?
Will it end up giving the largest 40 % of dairies,
the ones that could afford it, such a strong
competitive edge that the smaller 60 % just can't
keep up? That feels like the core strategic challenge,
the decision, really, that the dairy industry,
especially with its cooperative roots, needs
to grapple with as this technology rolls out.
That's all for today's episode of the Bullvine
Podcast. Remember, technology is a tool, not
a solution. Success comes from matching the right
tools to your specific operational needs and
capabilities. If you found value in today's discussion,
subscribe to The Bullvine Podcast wherever you
get your podcasts and visit us at thebullvine
.com for the full article, economic breakdowns,
and those eight critical questions you should
be asking any technology provider. We'll be back
next week with more insights that cut through
the industry noise and deliver the information
you actually need to make profitable decisions.
Until then, keep asking the tough questions.
And remember, not every innovation is right for
every operation. And that's perfectly okay. This
is The Bullvine Podcast. Thanks for listening.