CDCB’s August release proved sensor data beats subjective scoring by 2X. Smart producers are already adjusting breeding strategies. Are you?

EXECUTIVE SUMMARY: Your parlor sensors just revealed a genetic goldmine: 42% heritability for milking speed that breeds twice as fast as milk yield. This breakthrough—requiring unprecedented data sharing among 10 competing manufacturers—can save $70/cow annually when managed correctly. But there’s a critical trade-off: faster-milking cows tend to have higher somatic cell counts, making balanced selection essential for long-term profitability. The U.S. now leads with sensor-based evaluations while other countries cling to subjective scoring, fracturing international genetics markets and potentially isolating American genetics globally. Robot dairies must wait until 2030 for reliable evaluations, and the entire system depends on fragile manufacturer cooperation that could collapse if even one major player withdraws. Smart producers will adjust breeding strategies now to capture benefits while managing risks, because sensor genetics isn’t just another trait—it’s the future running through your parlor today.

You know that morning routine—standing in the parlor at 4:30 AM watching your third group come through, and you’re thinking there’s got to be a better way to breed for efficiency.

Well, CDCB just handed us something worth talking about over coffee.

When those Milking Speed PTAs came out in August, my first reaction was pretty much like yours probably was: “Great, another number to track.” But here’s what’s interesting—we’re looking at a heritability of 42%. That’s double what we typically see with milk yield at around 20%. And it absolutely dwarfs productive life or mastitis resistance, which hover down around 8% and 3% respectively, based on CDCB’s official genetic parameters.

What I’ve found is this isn’t just another incremental improvement. Those inline sensors sitting in parlors from California’s Central Valley to the family farms across Wisconsin and Minnesota… turns out they’ve been collecting incredibly valuable genetic information for years. We just didn’t know how to use it properly until now.

Dr. Kristen Parker Gaddis, CDCB’s Genetic Evaluation Research Scientist, summed it up well during their October industry meeting at World Dairy Expo. She mentioned that the really exciting part—at least from a geneticist’s perspective—is that it has really high heritability. Because what that leads to is even with their fairly modest dataset of 146,000 records, they’re getting relatively high reliabilities right from the start.

Click the link to view the presentation: Calculating Milking Speed (MSPD) PTAs Using Sensor Data
Kristen Gaddis, Ph.D., CDCB Geneticist Slides

But as many of us have seen with new technology, there’s always more to the story than those headline numbers…

Quick Facts: MSPD at a Glance

• Heritability: 42% (vs. 20% for milk yield)
• Dataset: 146,517 lactation records from ~132,000 cows
• Herds: 215 participating farms
• Manufacturers: 10 equipment companies sharing data
• Development: 2021-2025 (4 years)
• Release: August 2025

Behind the Curtain: The Infrastructure Battle Nobody Talks About

Looking at what it actually took to get this trait to market, I’m honestly amazed it happened at all. You had USDA’s Animal Genomics and Improvement Laboratory working with CDCB, plus Dairy Records Management Systems, a specially-formed Milking Speed Task Force, 215 participating herds across the country, and—this is the part that gets me—10 different milking equipment manufacturers actually agreeing to share data. The official presentations reference those 10 original manufacturers, though folks in the industry tell me 11 were ultimately involved.

Now, if you’ve ever tried getting your DeLaval system to talk to your Boumatic feed software, or your GEA equipment to play nice with your herd management program, you know exactly what I’m talking about. These companies spent decades—I mean decades—building systems explicitly designed NOT to share information. Classic vendor lock-in that drives us all crazy, right?

People who were close to those negotiations tell me they had to create entirely new frameworks that nobody had really tried before:

So they developed Format 8—basically a standardized data specification that lets different systems finally speak the same language. About time, honestly.

They also had to hammer out legal agreements ensuring manufacturers couldn’t use the genetic evaluation data to trash their competitors. You can imagine how fun those conversations were…

And they built data-sharing structures that protect our ownership—because, let’s be clear, it’s our data—while still enabling the research we need.

Now get this—and this is what really blows my mind—they started with over 50 million sensor observations from those 132,000 cows. After quality control? They aggregated all that down to 146,517 lactation-level records. We’re talking about averaging hundreds of individual milkings per cow into usable genetic data.

Makes you wonder what else might be hiding in all that sensor information we’re collecting every single day, doesn’t it?

The Economics: When Faster Milking Actually Costs You Money

Let me walk you through a scenario that’s probably pretty familiar. Say you’re running 1,000 cows through a double-12, milking three times daily like many Wisconsin operations do now. The economic modeling around sensor-based genetic evaluation suggests that if selection bumps your average speed up by just half a pound per minute—it doesn’t sound like much, does it?—you’re looking at tens of thousands in annual labor savings. And that’s using typical labor costs around $16 per hour, though I know plenty of folks paying more than that.

Sounds great. Sign me up, right?

But wait a minute.

What CDCB deliberately left out of Net Merit—and they actually had solid reasoning here—is that Milking Speed shows a positive genetic correlation of 0.37 with Somatic Cell Score. Plus, it’s negatively correlated with Mastitis Resistance at -0.28, based on CDCB’s published genetic parameters.

So in plain English? Genetically faster-milking cows tend to have weaker udders. There’s your trade-off.

I’ve been running numbers for different scenarios, and the differences are really eye-opening:

For herds with solid udder health—I’m talking around 15% clinical mastitis and 8% subclinical, which is pretty typical for well-managed operations in the Midwest:

• That moderate half-pound per minute improvement? You’re looking at substantial annual savings
• Push it to a full pound per minute? Even better returns

But if you’re already fighting mastitis—and I know plenty of good managers dealing with this, especially with environmental challenges where you’re seeing 35% clinical and 25% subclinical rates:

• That same moderate improvement? Your returns drop way down
• Try for aggressive selection? You’re really walking a tightrope there

What the data suggests—and this is crucial—if your clinical mastitis rate’s already pushing 40% annually, even moderate selection for milking speed can trigger what the veterinary folks call cascading health problems. At that point, the math just doesn’t work anymore.

Heritability Comparison: How Traits Stack Up

Trait	Heritability	Relative Response
Milking Speed (MSPD)	42%	2.1x faster
Milk Yield	20%	1.0x (baseline)
Productive Life	8%	0.4x slower
Mastitis Resistance	3%	0.15x slower

Source: CDCB genetic parameters, 2025

The International Split That’s Developing

Evaluation Aspect	US Sensor-Based (MSPD)	International Subjective	Winner/Risk
Data Source	Inline sensors, 50M+ observations	Classifier observations, scored 1-9	US (objective)
Heritability Estimate	42% (EXTREME)	14-28% (Moderate)	US (2X higher)
Genetic Progress Rate	2.1X faster than milk yield	Slower, less predictable	US (much faster)
International Compatibility	Incompatible with subjective systems	Compatible across countries	INTERNATIONAL (compatibility)
Cost to Implement	High (requires manufacturer cooperation)	Low (existing appraisal systems)	INTERNATIONAL (lower barrier)
Data Quality	Objective, continuous measurement	Subjective, infrequent	US (more accurate)
Update Frequency	Real-time, every milking	Once or twice per lactation	US (real-time)
Market Impact	May isolate US genetics globally	Maintains global trade compatibility	RISK (market fracturing)

Here’s something that worries me for anyone selling genetics internationally—and that’s a lot of us these days. While we’re moving to these sensor-based evaluations with that impressive 42% heritability, other countries are still using subjective scoring systems. They’re generally getting heritabilities ranging from 14% to maybe 28%, depending on their approach.

A colleague of mine who’s involved with international genetic evaluation coordination—they asked not to be named, given the sensitive negotiations going on—put it pretty bluntly: “We’re basically creating incompatible systems here. International evaluations typically need substantial genetic correlations between countries—usually 0.70 or higher—to make those conversion equations work properly. Early indications? We might not hit that threshold.”

Think about what this actually means for your breeding program:

• Your U.S. bulls might not have converted milking speed values for those export markets
• That fancy European genetics you’ve been considering? No MSPD predictions are coming with them
• We could see the global Holstein population basically fragment into sensor-based and subjective-scoring camps

It’s not ideal—I’ll be the first to admit that. But honestly? The alternative was sticking with subjective scoring that doesn’t really deliver meaningful genetic improvement. Sometimes you’ve got to pick your path and commit to it.

Why Robot Dairies Are Still Waiting

If you’re running robots—and more Midwest producers are every year—I’ve got news that requires some patience. CDCB openly acknowledges that extending MSPD to automatic milking systems is their biggest challenge right now. They’ve got about 20,000 AMS cow-lactations in their database. Compare that to 146,517 from conventional parlors, and you see the problem.

But it’s not just the sample size that’s the real issue here. What’s fascinating—at least to those of us who geek out on this stuff—is that robots fundamentally change what we’re actually measuring.

In your conventional parlor, everybody milks on schedule. Three times daily means roughly every eight hours, nice and standardized. But with robots? Research on voluntary milking behavior shows some cows visit 2.2 times daily while their pen-mates are hitting the box 3.5 times.

That variation comes from all sorts of factors, as you probably know:

• Individual cow motivation—some just handle udder pressure differently than others
• Your pellet allocation strategy (I’ve seen everything from half a kilo to 8 kg, depending on what the nutritionist recommends)
• Whether you’re running free-flow or guided traffic systems

So here’s the million-dollar question that’s keeping the geneticists up at night: Is a cow milking 3.5 times at 6 pounds per minute genetically equivalent to one milking 2.5 times at 7 pounds per minute when they’re both putting the same total pounds in the tank?

Nobody knows yet. Based on what we’ve seen with similar trait development, we’ll probably need 50,000 to 80,000 AMS lactations to sort this out properly. At current adoption rates? You’re realistically looking at 2030 to 2032 before robot dairies get reliable MSPD evaluations.

Looking Ahead: The 3-5 Trait Reality

Let’s have an honest conversation about what’s actually possible versus what the tech companies are promising. CDCB and USDA combined have the capacity to develop maybe—and I’m being optimistic here—3 to 5 new sensor traits per decade. That’s just the reality of resource constraints.

MSPD took 4 years from the time they formed the task force to release. You do the math. We’re limited in what we can realistically accomplish.

Based on current research priorities, here’s what I think we’ll actually see:

Near-term stuff (2025-2028):

• Activity and rumination from those neck collars that many of us are already using
• Robot-specific evaluations for box time and actual flow rate

Medium-term possibilities (2028-2032):

• Feed intake consistency—research herds are building those datasets now
• Milk spectral traits that might predict efficiency
• Heat tolerance based on how activity changes with temperature (and boy, do we need that one)

The real challenge? Technology cycles every 5 to 7 years. By the time we validate these traits, the sensors themselves might be obsolete. It’s like chasing your tail sometimes.

The Real Economics Behind Development

It’s worth understanding what this whole MSPD development actually cost. Industry estimates suggest we’re talking millions in development costs, with annual operating expenses running in the hundreds of thousands. And the direct value capture? It barely breaks even, if that.

Makes you wonder why they did it, right?

Well, here’s the thing—the alternative was watching companies like DeLaval and Lely build their own proprietary genetic evaluation systems. Can you imagine? We’d have ended up with five different “milking speed” scores that don’t compare, and you’d be getting your genetic information from equipment dealers rather than breed associations. Agricultural economists who’ve examined this estimate say that such market fragmentation would cost our industry tens of millions of dollars annually in lost efficiency. Sometimes you’ve got to spend money to save money, I guess.

The Governance Tightrope

What really concerns me—and this is based on conversations with folks who work closely with the system—is just how fragile this whole arrangement is. These equipment manufacturers had never been part of dairy’s traditional cooperative data structure before. Why would they be? They just made the equipment. They didn’t control the data.

But inline sensors changed everything, didn’t they? Suddenly, these companies are sitting on absolute goldmines of genetic information. Getting them to share required some pretty creative solutions that, frankly, might not hold long-term:

The agreements need renewal every few years—nobody’s locked in forever here. Any company can basically walk away whenever they want. There are these non-disparagement clauses preventing anyone from publishing performance comparisons between manufacturers. And the proprietary algorithms? They stay secret. Manufacturers only share the processed data.

“The trust holding this together is tissue-paper thin. One major player pulls out, and it could all unravel.”

That’s from a technical specialist I trust who works closely with the system. And honestly? It keeps me up at night.

What This Means for Your Operation Today

After really digging into all this (probably spending way too much time on it, my wife would say), here’s my practical take for different types of operations:

If You’re Running a Conventional Parlor

With good udder health (meaning your SCC is under 150,000 and clinical mastitis below 20%):

• Look for bulls with MSPD values running +0.5 to +1.0 lb/min above breed average
• You should see meaningful per-cow savings annually within 5 to 7 years
• But keep tracking that bulk tank SCC quarterly—if it starts creeping up faster than you expected, ease off the gas

If mastitis is already giving you headaches (SCC over 250,000, clinical cases above 30%):

• Keep your MSPD selection modest—no more than +0.3 to +0.5 lb/min maximum
• Focus on fixing that udder health situation first (you know you need to anyway)
• Only chase milking speed after you’ve got mastitis under control

For Robot Operations

• Don’t expect MSPD evaluations for your system until 2030 at the earliest—I’m being realistic here
• Current conventional parlor values might not predict robot performance well at all
• For now, focus on temperament and milking frequency genetics—that’s what’s going to matter in your system

If You’re Marketing Genetics

• Bulls with exceptional MSPD values—anything over +1.0 lb/min—have real domestic marketing potential
• But those international markets? They might not recognize these evaluations. Keep that in your back pocket
• You’ll want to maintain balance with traditional traits if you’re selling globally

The Big Picture: Where We’re Really Headed

The August 2025 MSPD release is more than just another number showing up on bull proofs. What we’re witnessing—and I really believe this—is the opening move in a complete transformation of how dairy genetics works. And between you and me? It’s going to get messier before it gets clearer.

Here’s what I think really matters:

We’ve been sitting on high-heritability goldmines in our sensor data for years without realizing it. That 42% heritability for milking speed? It suggests other valuable traits are probably hiding in those data streams. If you’re already collecting comprehensive sensor data, you’re well positioned for whatever comes next.

The economics, though—they’re not as straightforward as the headlines suggest. Yes, faster milking saves labor. No argument there. But if it compromises your udder health, you’re going backwards fast. Every farm’s break-even point is different. You’ve really got to run your own numbers carefully here.

For those of you in global genetics markets—and I know there are many—the international market’s fracturing. The U.S. bet big on precision dairy genetics while others stuck with cheaper subjective scoring. Neither approach is wrong, necessarily, but they’re becoming increasingly incompatible. This matters now, not five years from now.

I also think we need to acknowledge that cooperative genetics faces a real existential moment. The structures that barely got MSPD across the finish line… well, they’re held together with baling wire and good intentions. Within 5 to 10 years, we might be receiving evaluations from multiple competing platforms rather than a single national system. That’s not necessarily bad, but it’s definitely different from what we’re used to.

And finally—technology moves way faster than validation. By the time sensor traits get through that development pipeline, the technology itself often changes fundamentally. We need to accept that some infrastructure investments just won’t pay off the traditional way. That’s the new reality.

What gives me hope is that MSPD proves sensor-based evaluation actually works. It delivers exceptional heritability and integrates into our existing breeding programs. But it also reveals these tensions between our cooperative traditions and commercial realities that, frankly, we haven’t figured out yet.

Progressive producers who understand both the opportunities and the limitations—they’ll navigate this transition just fine. Those expecting sensor genetics to plug into existing systems like traditional traits simply always have? Well, they’re in for some surprises.

The revolution isn’t coming—it’s here, running through your parlor every single day. MSPD opened that door. What comes through next will reshape dairy breeding for generations. The question isn’t whether to embrace sensor-based genetic evaluation. It’s how to use it intelligently while the ground shifts beneath the entire industry.

And that’s something we’ll all be figuring out together, one breeding decision at a time.

KEY TAKEAWAYS 

• $70/cow awaits—with conditions: Select bulls +0.5 to +1.0 lb/min above breed average for milking speed, but ONLY if your herd maintains SCC under 150,000 and clinical mastitis below 20%
• Speed kills udder health: The 42% heritability is a double-edged sword—aggressive selection (+1.0 lb/min) without monitoring SCC quarterly could trigger cascading mastitis problems costing more than you save
• Your system determines your timeline: Conventional parlors can profit NOW from MSPD, but robot dairies must wait until 2030 for reliable evaluations—plan breeding strategies accordingly
• International genetics just got complicated: U.S. sensor-based evaluations won’t translate to countries using subjective scoring—if you export genetics, maintain traditional trait balance or risk losing global markets
• The revolution is fragile: This entire system depends on 10 manufacturers continuing to share data voluntarily—smart producers will capture benefits while preparing for potential fragmentation

Complete references and supporting documentation are available upon request by contacting the editorial team at editor@thebullvine.com.

Learn More:

• New Sensor-Based Milking Speed Trait from CDCB Debuts in August – Reveals actionable steps for implementing sensor-based milking speed PTA on your farm, including best practices for data collection, cow sorting, and using these evaluations to boost parlor efficiency and profitability.
• The Milking Speed Breakthrough That Fixes Your Labor Problem – Demonstrates how producers are actually saving time and labor by breeding for optimal milking speed, with real-world results showing payback timelines and pen management tips you can adopt now.
• The Digital Dairy Barn: Inside Cornell’s CAST and Its Future – See how advanced sensor systems and machine learning are transforming modern dairies, from real-time cow monitoring to health prediction and sustainability—essential reading for staying one step ahead in dairy technology.

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