Archive for milking speed genetics

Beyond Cows Per Hour: The Cow-Time Truth That’s Changing Large Herd Robot Math

2,000-cow dairies are learning something from robots that has nothing to do with labor: cows can’t make milk while standing in line.

Executive Summary: Large dairies have measured success in cows per hour for decades. Operations that thrive with robots have flipped that metric—they manage by cow time instead. The biology is clear: high producers need 12–14 hours of lying time daily, and every hour lost to walking or waiting costs 1.5–3.5 pounds of milk. On many 3x parlors, that’s 3–5 hours of hidden loss every day. Robot herds that nail the fundamentals—55–60 cows per unit, proper heifer training, solid hoof health—report 3–8% higher milk per cow after stabilization. But the economics demand honesty: real payback runs 5–7 years, not the 3.8–5 years in vendor models. Recent research adds a key insight: milking speed is 42% heritable, but willingness to visit the robot is almost entirely management-driven. For 2,000-cow operators, the question isn’t robots vs. parlors—it’s whether you’re ready to build around cow biology, not just throughput.

Large herd robotic milking

You know the drill. On a lot of big dairies, the proud number is still the same: “We run 450–500 cows an hour through this parlor.” And to be fair, that’s impressive steel and scheduling. But here’s what’s interesting—as more large herds adopt automatic milking systems, a different story is emerging. Cows per hour and true cow productivity? They’re not always pointing in the same direction.

What farmers are finding is that robots aren’t just a different way to get cows milked. They’re shining a light on hidden time losses, showing how much genetic potential may still be sitting on the table, and prompting a more honest look at labor risk and management discipline.

And here’s the thing—the biggest differences between successful and struggling AMS herds rarely come down to the brand of robot. They come down to cow time, barn design, and how well you run the people side of the business.

Looking at This Trend Through Cow Time, Not Steel

If you strip everything back, a dairy cow still lives on a 1,440‑minute clock every day. Extension specialists keep coming back to the same basic targets you’ve probably heard at meetings.

High‑producing Holsteins and Jerseys should be getting at least 10–12 hours of lying time, with 12–14 hours often cited as the ideal target for top performance and hoof health. The research on this is fairly consistent—according to time-budget studies summarized by multiple land-grant universities, each hour of lying time you lose can cost you roughly 1.5–3.5 pounds of milk per cow per day, depending on stage of lactation and environmental conditions.

Time away from stalls—walking, standing in headlocks, sitting in a holding pen—comes straight out of that lying and ruminating budget.

On many large 3x parlors, especially those with long alleys or dry lot systems feeding into a central milk center, total time away from stalls can run 3–5 hours per day when you add up walk time, holding, and actual milking. When you layer on 4–6 hours of feeding and watering, plus social and transition time, you can see how quickly you approach that 12‑hour rest target.

Every extra hour cows spend out of stalls quietly strips 1.5–3.5 pounds of milk per cow per day. By the time many 3x parlors hit 3–5 hours of walking and waiting, they’re effectively giving up a full milking’s worth of production without ever touching the parlor controls.

I was talking with a nutritionist recently who works across several large California operations. The way she put it was simple: “Most producers don’t realize how much milk they’re leaving on the table until they actually track where their cows spend their hours.”

And the data backs that up. Studies that track both lying time and milk yield tell a consistent story—cows losing just 2 hours of rest per day commonly give 3–7 pounds less milk, and first‑lactation animals tend to be even more sensitive to this.

Tightening time budgets in a parlor can claw back a few points of milk per cow, but the real jump shows up when robots are managed to feed extra milkings to your best genetics. The winners aren’t “robot herds” or “parlor herds”—they’re the people who obsess over minutes, not metal.

What’s particularly noteworthy is that when herds later install robots, whether on part of the herd or across the board, many report 3–8% higher milk per cow once the system stabilizes, even when they end up milking fewer total cows. The common thread? Cows reclaim time for lying and ruminating instead of standing in concrete alleys.

Tightening time budgets in a parlor can claw back a few points of milk per cow, but the real jump shows up when robots are managed to feed extra milkings to your best genetics. The winners aren’t “robot herds” or “parlor herds”—they’re the people who obsess over minutes, not metal.

Now, that doesn’t mean every robot install boosts milk. But it does highlight just how significant those quiet time‑budget losses can be.

The Bimodal Milk Curve Challenge

There’s another factor in high‑throughput parlors that only shows up when you examine milk‑flow curves. And it does not get talked about enough.

Biologically, most cows need about 90–120 seconds between effective teat stimulation and full oxytocin release for a complete milk letdown. But in fast parlors—and many of us have walked through them—it’s common to strip, dip, wipe, and attach in 30–60 seconds, especially when crews are working to hit those cows‑per‑hour targets.

On‑farm flow meters and research trials have documented what happens in these situations.

You get a quick spike as cisternal milk is removed. Then there’s a flat or low‑flow phase while the cow is still waiting hormonally for full letdown. Finally, a second rise once oxytocin finally peaks.

That “start–stop–start” pattern is what we call a bimodal curve. And here’s what the field studies suggest—when you don’t allow enough time for effective letdown, cows can noticeably reduce daily milk harvest, especially high‑yielding, early‑lactation animals who have the most to give.

What I’ve observed in some very fast parlors is that the graphs look great for turns per hour, but not nearly as strong when judged by milk per milking minute.

Robots don’t automatically solve this, but the software makes it easier to respect biology. AMS units can apply consistent stimulation—often with brushes or controlled vacuum—and then wait the full lag period before expecting peak flow. When you look at their flow curves, you generally see a single, smooth peak rather than the “double hump,” suggesting a more complete harvest.

What Farmers Are Finding About Genetics and Milking Frequency

Genetic progress has outpaced a lot of our old assumptions. And this is something worth sitting with for a moment.

Between 1970 and 2020, combined fat and protein production in U.S. Holstein populations increased by more than 900 pounds per cow, with national evaluations crediting about 60–65% of that gain to genetics when you separate out management and environment. Jerseys have shown similar patterns for component yield and feed‑efficiency traits.

The challenge is that realizing that genetic potential depends heavily on milking frequency and cow comfort.

Controlled studies and on‑farm trials provide some useful guideposts. Moving from 2x to 3x milking often increases yield by 8–15% in controlled settings, particularly during early and peak lactation.

Short periods of 4x milking in early lactation can create persistent yield benefits across the whole lactation—because of how additional milkings affect mammary cell activity. And cows differ genetically in their response to higher frequency. Some families show much larger gains than others.

In a conventional 3x parlor, your top and bottom cows are on the same schedule. A high‑genetic‑merit cow that could profitably be milked 4 or 5 times a day stands in line with a late‑lactation cow you’re trying to dry off clean. Both take the same parlor time, even though the return on that time is very different.

What robots change, when managed well, is the flexibility to match milking frequency to each cow’s potential.

In free‑flow AMS barns, peak cows often visit robots 3.5–4.5 times per day, while late‑lactation or lower‑producing cows may be permitted 2–2.5 milkings. Permissions can be adjusted cow by cow based on days in milk, udder health, and butterfat performance.

One illustration worth noting is Countyline LLC in California’s Central Valley—one of the largest robotic Jersey projects in North America, with 32 robots designed for roughly 2,000+ Jerseys, transitioning from a conventional double‑32 parlor. Public profiles indicate strong per‑cow production for first‑ and second‑lactation animals, with the high components you’d expect from intensively managed Jersey herds.

What this development suggests is that, in a robotic setup, “robot minutes” become a resource you allocate to the cows with the best genetic and economic returns, rather than treating all cows equally in terms of time.

Here’s something else worth noting on the genetics front—and it’s one of those details that doesn’t get enough attention. According to research published in the Journal of Dairy Science in 2023, milking speed traits show remarkably high heritability. Average milk flow rate runs 0.43–0.52, and maximum flow rate hits 0.47–0.58 in the AMS data. The new CDCB Milking Speed evaluation released in August 2025 estimates heritability at 42% based on conventional parlor data, making it the highest heritability of any of the 50 traits they publish. The reason both parlor and AMS data point in the same direction is straightforward: how fast a cow lets down milk is fundamentally biological, not system-dependent.

By contrast, behavioral traits like robot visit frequency and milking interval show much lower heritability—around 0.08–0.10, according to a July 2025 Journal of Dairy Science study—indicating they are more management-driven than genetics-driven.

Milking speed and flow sit near the top of the heritability charts, which means you can move the needle fast with the right sires. But robot visit frequency and milking interval barely clear 0.1 h²—proof that you can’t breed your way out of weak barn design, poor training, or chronic lameness.

The practical takeaway? You can select fairly quickly for cows that milk efficiently, but willingness to visit the robot voluntarily depends more on training, facility design, and hoof health than on pedigree.

What Robots Really Change Economically

When a 2,000‑cow operator looks at a capital plan and sees a multi‑million‑dollar robot build versus a more modest investment in a rotary or expanded parallel, payback is naturally front and center. It’s also where vendor projections and independent analyses sometimes diverge.

University extension economists in the U.S. and Canada have built a range of AMS vs parlor budgets. According to economic analyses from Minnesota, Wisconsin, and Canadian extension programs, under good design and strong management, payback for robots often falls in the 3.8–5-year range, driven mostly by labor savings and modest production gains.

But on real farms? Those same teams report that it’s more common to see 5–7 years, especially when you include a realistic transition period.

Vendor spreadsheets often promise payback in under five years, but real, 2,000‑cow AMS herds rarely settle out that fast. Once you count transition headaches, learning‑year dips, and full maintenance costs, a 5–7‑year payback is far more honest—and still defensible when labor risk is brutal.

Looking at those models and field reports side by side, three economic factors consistently emerge:

Labor savings. Studies and case farms typically show milking‑related labor dropping 25–30%, with pounds of milk shipped per full‑time equivalent often rising from around 1.5 million to about 2.2 million pounds per worker per year in AMS herds.

Milk per cow. Once cows and people get through the adjustment period, many robot herds in reviews and surveys report 3–8% higher milk per cow, driven by smoother time budgets, more consistent routines, and higher milking frequency for the top animals.

Overhead considerations. Depreciation, maintenance contracts, electricity, and consumables are higher per cow in a robotic setup than in a parlor, which offsets part of the labor savings.

A multi‑country review comparing AMS and conventional herds over five years found that average profitability was often similar when you adjusted for milk price, scale, and stocking rate. In other words, robots didn’t automatically outperform parlors—the farms that did well in each system tended to be the ones with tight management and good facilities.

So why is this significant? Because it suggests the decision isn’t purely economic for many operators.

In a 2023 peer-reviewed survey of large U.S. farms using seven or more robots, producers identified their top reasons for adopting AMS as chronic difficulty finding and keeping qualified parlor employees, concerns about future wage and regulatory changes, desire for more consistent milking procedures and teat prep, and interest in shifting employees into roles focused on fresh cow management, herd health, and reproduction.

This aligns with what economists are now saying—that robots function as a labor‑risk management tool as much as a production tool. It also explains why some herds are comfortable with a 7–10 year real payback if the alternative is an increasingly uncertain labor situation.

At the same time, extension guidance is clear that in regions where labor remains relatively available and affordable, and where regulatory conditions are different, a well‑designed rotary or parallel parlor may still be the most economical choice—especially for herds that are already efficient on cows‑per‑hour and milk quality.

I’ve seen herds in the Upper Midwest and Southwest with strong local workforces choose a new rotary and perform very well, precisely because their challenge wasn’t labor risk but something like cow flow, parlor age, or heat‑stress management.

A Snapshot from the Pacific Northwest

To make this more concrete, let’s look at one example from the Pacific Northwest that’s been profiled in industry publications.

A Washington State dairy milking around 1,100 cows installed roughly 20 robots in a retrofit scenario, driven largely by labor shortages and a desire for more manageable schedules for both owners and employees.

According to reports from Dairy Herd Management and follow‑up coverage on robotic cow flow, they initially struggled with cow traffic and fetch rates—especially among first‑lactation heifers—and saw milk per cow dip during the first months.

Over time, they made three significant adjustments. They reworked the pen design to create clearer, free‑flow traffic patterns. They invested more heavily in heifer training and hoof health before calving. And they reduced cows per robot into the mid‑50s, even though that meant fewer total cows in milk.

Two to three years in, they reported that milk per cow had recovered and surpassed pre‑robot levels, milking labor had dropped significantly, and owner lifestyle was more sustainable—though maintenance costs were higher than initially expected.

This “dip‑and‑recover” pattern appears fairly typical on well‑managed AMS transitions. A challenging learning year, followed by a more stable, data‑driven routine. It’s something worth keeping in mind if you’re considering the switch.

Understanding Fetch Cows and Building “Robot‑Ready” Herds

Once the new system is running, many managers quickly realize that a significant part of their day is determined by one number: how many cows walk themselves to the robot.

A fetch cow is a cow that doesn’t visit the AMS within the target interval and has to be brought by staff. Extension guidelines and AMS consultants commonly set a goal of no more than 5% of the herd on the fetch list on a given day—roughly three cows per robot—to preserve labor savings and minimize cow stress.

In herds that are struggling with the transition? It’s not unusual to see fetch rates of 15–25%, which can turn “automatic milking” into a time‑consuming cow‑management challenge.

And here’s what’s interesting—fetch cows aren’t random. Several consistent factors show up in both the research and on real farms.

The 4 Primary Causes of Fetching

1. Personality and Temperament Research in Europe and South America has used standardized behavioral tests to classify cow personalities. Cows that are bolder and moderately active tend to adapt faster to robots and end up on fetch lists less often. Very fearful or highly reactive cows typically need more support during the transition.

2. Heifer Training (or Lack Thereof) Studies on “phantom robot” training—where heifers are exposed to the robot area and its sounds before calving—show lower fetching during the first weeks of lactation and better early milk letdown compared with untrained heifers. Many AMS advisors now treat heifer training as a required piece of fresh cow management, not an optional extra.

3. Lameness Lame cows are far less inclined to walk to a robot voluntarily. Reviews from industry publications and North American extension programs connect higher lameness prevalence to higher fetch rates and lower milk per cow. Lame cows in AMS herds are often roughly twice as likely to show up on fetch lists as sound cows.

4. Stocking Density and Barn Design Pushing 70–80 cows per robot to “maximize utilization” tends to mean longer robot queues, more competition, and more timid or subordinate cows giving up on voluntary visits. According to facility guidelines from Wisconsin extension and Lactanet, 55–60 cows per robot is a realistic upper limit for high‑producing herds. Some of the most successful operations intentionally stay a bit lower in fresh or high‑yield pens.

Genetics is part of the picture, too. Analyses of AMS data in North American Holsteins have estimated moderate heritability—0.10–0.15—for traits such as number of successful robot visits and milking interval, with higher heritability for milking speed and teat/udder traits that affect attachment.

This means over time we can genuinely select for “robot‑ready” cows—those that move well, milk quickly, and have udders suited to the technology.

In herds that make robots work well, a common pattern emerges. They run 50–60 cows per robot, especially in fresh and high groups. They emphasize sand‑bedded freestalls, regular hoof trimming, and alley cleanliness before and during the transition. They build structured heifer training into their fresh cow management program. And they make timely culling decisions on chronic fetch cows, regardless of pedigree.

Why Some Large Herds Struggle—or Step Back

It’s worth acknowledging that not every large herd that installs robots ends up satisfied with the decision. In Europe and New Zealand, there are documented cases of farms decommissioning robots and returning to parlors after several difficult years, usually due to a combination of design challenges, unrealistic expectations, and management strain.

Looking at the available data and field experience, a few patterns keep recurring.

Retrofitting Robots into Parlor‑Designed Barns

You probably know this one. The 2023 peer-reviewed survey of large U.S. AMS herds—those with seven robots or more—found that about one‑third of producers said they would change barn design decisions if they could do it again, especially around robot placement and traffic lanes.

Retrofitting robots into barns built around straight‑through parlor flow often creates narrow alleys and “pinch points” near robot rooms, robots positioned in corners rather than integrated into main cow paths, and pen layouts that require cows to move against group flow to reach the milking area.

These issues then manifest as higher fetch rates, reduced lying time, and more variable production—problems that are very difficult to address once the concrete is poured.

Overstocking Robots

On paper, putting 75 cows on a robot instead of 55 looks like an efficient way to spread capital cost. But from the cow’s perspective, it often means longer queues in front of the robot, dominant cows monopolizing access, and timid, lame, or fresh heifers being pushed out and becoming chronic fetch cows.

AMS facility guidelines from Lactanet and university extension programs consistently recommend designing for 55–60 cows per robot for high‑producing Holstein or Jersey herds, with flexibility to run lighter stocking in certain pens when conditions warrant.

Underestimating the Learning Curve

Several studies following farms through AMS transitions report that it typically takes 6–12 months for milk yield, robot utilization, and daily routines to stabilize.

During that period, herds may see a temporary dip in production, elevated somatic cell counts while prep and attachment protocols are refined, and more labor devoted to training cows and staff than initial budgets anticipated.

Case studies and reviews suggest that operations expecting immediate labor relief and a smooth transition tend to experience the most frustration, while those who plan for a “learning year” are more likely to report satisfaction by year two or three.

Data Engagement and Management Approach

The same hardware can produce very different results depending on how it’s managed.

Performance reviews highlight that successful herds check robot and cow data daily—milkings per cow, refusals, failed attachments, activity, conductivity, lying time—and use those numbers to adjust grouping, feeding, and hoof care.

Less successful herds often log in less frequently, focus primarily on bulk tank output, and treat robot alerts as nuisances rather than diagnostic information.

What I’ve observed is that the large herds thriving with robots were typically already comfortable managing by data—tracking fresh‑cow performance, pen‑level butterfat, reproductive metrics, and time budgets—before they ever contacted a robot dealer. Robots don’t compensate for management gaps. They tend to amplify whatever approach is already in place.

Different Regions, Different Right Answers

It’s worth remembering that not every region is facing the same set of pressures.

In parts of the U.S. and Canada where labor is tight, wages are rising, and regulatory requirements are expanding, robots can be a way to convert unpredictable labor costs into more predictable capital and maintenance expenses, even if the margin over feed is similar. In those situations, producers often tell me they value stability as much as financial returns.

In other regions—where there’s still a reliable, reasonably priced local workforce and where dry lot systems and centralized parlors align well with climate and land base—a new rotary or expanded parallel, paired with strong management, can absolutely remain the right choice.

I’ve seen herds in the Upper Midwest, Southwest, and Latin America achieve excellent milk, health, and labor metrics with conventional parlors because they were designed around cow flow and time budgets just as thoughtfully as any robot barn. One Wisconsin operation I visited last year had just installed a new 60‑stall rotary, and they’re hitting numbers that would make any robot farm proud—because they obsessed over time budgets, stall comfort, and consistent protocols.

Seasonal considerations matter too. In hot summers, for example, extra time in holding pens or long walks from dry lots can push cows past their heat‑stress threshold more quickly, whether they’re going to a parlor or a robot. That’s one more reason why time budgets and cow comfort form the foundation, regardless of which milking system you choose.

The broader trend is that the margin for loose time management and inconsistent protocols is narrowing on both sides of the technology discussion. Whether you choose a rotary or robots, cows still need adequate lying time, clean stalls, smooth, fresh cow management, and consistent routines.

Key Considerations for 2,000‑Cow Operators

So, if you’re operating in that 2,000‑cow range and genuinely evaluating your options, what should you take from all this?

Start by measuring time, not by shopping for equipment. Before committing to any major investment, spend several months tracking time away from stalls, lying time, and lock‑up duration in your current system. That exercise alone will reveal how much opportunity—or hidden cost—exists in your current operation.

Recognize that genetics need the right schedule to deliver. Today’s Holstein and Jersey genetics can produce impressive milk and components, but only when milking frequency, comfort, and fresh-cow management align with their capabilities.

Frame robots as a risk‑management decision, not purely an efficiency calculation. Economic models suggest a 3.8–5 year payback is achievable under favorable conditions, but many real farms land closer to 5–7 years, and some take longer. Whether that timeline makes sense depends significantly on your labor outlook and long‑term operational plans.

Take fetch cows, lameness, and heifer training seriously. These three factors will largely determine how “automatic” your automatic milking actually feels. If you’re not prepared to invest in hoof health, stall comfort, and structured training before the robots arrive, your payback will likely be slower regardless of which system you choose.

Be honest about your management approach. If your team already operates from data—milk weights, butterfat performance, reproductive metrics, time budgets—you’re better positioned to succeed with AMS. If decisions are made primarily by intuition, the first investment might need to be in people and processes rather than technology.

Accept that there isn’t a single “right” answer. In some regions and operational contexts, a new rotary with excellent cow flow may be the most sensible long‑term investment. In others, robots will be the best path forward, given labor-market realities unlikely to reverse.

The Bottom Line

What’s interesting about this moment in the industry is that robots are prompting all of us—whether we ever purchase one or not—to think more carefully about how cows spend their time, how we develop and retain our people, and how we build systems capable of performing well over the next 10–15 years.

If this discussion helps you ask better questions, whether you ultimately install a new rotary, a row of robots, or neither, then it’s served its purpose.

KEY TAKEAWAYS

  • Track cow time, not cows per hour: High producers need 12–14 hours of lying time daily. Every hour lost costs 1.5–3.5 lbs of milk—and on many 3x parlors, cows lose 3–5 hours to walking and waiting.
  • Robots recover time, and time recovers milk: Well-managed AMS herds report 3–8% higher production per cow by giving back the hours that parlor routines take away.
  • Use honest economics: Real payback runs 5–7 years, not the 3.8–5 in vendor models. Budget for a 6–12 month learning curve before expecting stable results.
  • Nail the fundamentals before install: 55–60 cows per robot maximum, structured heifer training, and excellent hoof health aren’t optional—they separate success from struggle.
  • Select for speed, train for visits: Milking speed is 42% heritable—breed for it. Willingness to visit the robot is almost entirely management-driven—design and train for it.

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

Learn More:

Join the Revolution!

Join over 30,000 successful dairy professionals who rely on Bullvine Weekly for their competitive edge. Delivered directly to your inbox each week, our exclusive industry insights help you make smarter decisions while saving precious hours every week. Never miss critical updates on milk production trends, breakthrough technologies, and profit-boosting strategies that top producers are already implementing. Subscribe now to transform your dairy operation’s efficiency and profitability—your future success is just one click away.

NewsSubscribe
First
Last
Consent

42% Heritability: The Milking Speed Breakthrough That Fixes Your Labor Problem

What farmers are discovering: selecting for speed actually reduces labor costs $10-16K annually

EXECUTIVE SUMMARY: What farmers are discovering about CDCB’s new Milking Speed evaluation is reshaping our understanding of genetic selection and parlor efficiency. With 42% heritability—compared to just 7% for daughter pregnancy rate—MSPD offers predictable genetic progress for a trait that impacts operations twice daily, 365 days a year. Holstein bulls currently range from 6.2 to 8.1 pounds per minute in the August 2025 evaluations, meaning the spread between your fastest and slowest genetics could be costing you an hour or more of labor daily. Research from the University of Minnesota confirms that strategic selection within the 7.0-8.0 lbs/min range balances efficiency gains with udder health, while extension specialists from Wisconsin to California emphasize the importance of adjusting parlor settings as genetics improve. Looking ahead, operations implementing MSPD selection can now expect gradual but meaningful improvements. Many producers report saving 10-15 minutes per milking by year three, with full benefits emerging around year seven as herd genetics turn over. The collaborative learning happening as producers share experiences with this trait represents exactly how our industry gets stronger together. For operations facing persistent labor challenges or inconsistent milking times, MSPD warrants serious consideration as part of a comprehensive breeding strategy.

 Milking speed genetics

Every morning at 4:30, the same scene plays out in parlors from California to Vermont. Some cows are finished, waiting to exit, while others seem to take forever. We’ve all managed to work around this variation for years, adjusting our routines, tweaking our grouping strategies, and making it work. But what if genetics could actually address this issue?

CDCB rolled out their Milking Speed evaluation—MSPD—this past August, and the numbers are stopping producers in their tracks. According to their published data, we’re looking at 42% heritability. Now, if you’re anything like the producers I’ve been talking with from the Midwest to the Southeast, that number probably makes you pause. Daughter pregnancy rate, which we’ve been selecting for intensely? That’s around 7% according to CDCB’s genetic parameters. Most health traits we worry about sit between 1% and 3%. This ranks among the CDCB’s highest-heritability functional traits.

The genetic game-changer hiding in plain sight – MSPD’s 42% heritability means real, measurable progress in your lifetime, not your grandkids.

It’s worth noting that MSPD is a flow rate measurement, expressed as pounds of milk per minute, not a total milking time. This standardizes the measure across lactation stages and systems, making it universally applicable whether you’re milking fresh heifers or fourth-lactation cows.

What farmers are finding is that this might be one of those genetic tools that actually delivers on its promise. That’s a level of genetic progress we just haven’t seen before for traits that hit your bottom line every single day.

The Science Is More Straightforward Than You’d Think

CDCB built this evaluation using sensor data from commercial dairies, measuring the pounds of milk per minute as it flows through the system across 31 states. No subjective scoring where one classifier sees a seven and another sees an 8. Just straight data from actual milking sessions.

The physiology behind milking speed has been documented in dairy science literature for decades. Research published in the Journal of Dairy Science suggests that it primarily depends on both anatomy and neural response. You’ve got your physical components—teat canal diameter, sphincter muscle tone—but there’s also how efficiently a cow responds to oxytocin and her overall letdown reflex. Some cows milk fast because they have excellent milk ejection. That’s what we want. Others? They’re fast because of looser teat anatomy, which can open the door to mastitis problems down the road.

Looking at CDCB’s correlations, there’s a 0.43 genetic correlation between milking speed and somatic cell score. Initially concerning, right? However, the data actually reveal that correlation mainly occurs when speed originates from compromised teat anatomy rather than good physiology. When you’re selecting bulls in what CDCB identifies as the practical range—around 7.5 to 8.0 pounds per minute—you’re generally getting efficiency through better milk letdown, not shortcuts that’ll haunt you later.

Kristen Gaddis, who leads the genetic evaluation team at CDCB, explained at their August public meeting that this 42% heritability makes MSPD one of their most heritable published traits. The reliability is already strong, even with a relatively new dataset. When you see heritability this high on a trait that impacts throughput every single day, it really does change the conversation about what’s possible through genetic selection.

What This Looks Like in Real Parlors

Holstein bulls in the current CDCB evaluations range from about 6.2 to 8.1 pounds per minute. That’s roughly a 30% spread. I’d bet money most operations have similar variation in their herds right now—you probably know exactly which cows I’m talking about.

Think about your morning milking. In a typical double-12 herringbone, when everything’s clicking, you’re moving cows through efficiently. But when those slower genetics hold up an entire side? Your actual throughput drops, workers become frustrated, and what should be a 2.5-hour milking stretches to 3 hours or more.

The economics vary depending on where you’re located, obviously. Labor costs differ significantly from region to region—what a California producer faces compared to someone in Georgia or South Dakota can be night and day. But across the board—from Florida to Idaho—many operations are finding that greater consistency reduces those end-of-shift pressure points. Workers know roughly when they’ll finish. That predictability… in today’s labor market, where finding anyone willing to work is challenging, matters as much as the raw time savings.

Quick Reference: MSPD Selection by System Type

Parlor TypeTarget MSPD Range (lbs/min)Key PriorityCritical ThresholdEfficiency Gain Potential
Herringbone/Parallel7.0-8.0Uniformity over speedAvoid bulls <6.815-20%
Rotary7.0-7.8Consistent platform speedMinimize 2nd rotations10-15%
Robotic Systems7.2-7.8Speed + teat placementBalance with udder conf.8-12%

Herringbone and Parallel Parlors

Target Range: 7.0-8.0 lbs/min
Priority: Uniformity over maximum speed
Key Point: Bulls below 6.8 create bottlenecks that kill efficiency
Based on the University of Wisconsin Milking Center recommendations and field experience

Rotary Parlors

Target Range: 7.0-7.8 lbs/min
Priority: Consistent platform speed, minimize second rotations
Key Point: Group first-lactation heifers separately when possible
Michigan State Extension dairy team guidelines

Robotic Systems

Target Range: 7.2-7.8 lbs/min
Priority: Individual performance plus udder conformation
Key Point: Robots need both speed and good teat placement
Penn State Extension robotic milking resources

Building Your Selection Strategy Today

From analysis paralysis to action – Your personalized MSPD roadmap based on current herd genetics and variation

Since MSPD isn’t integrated into Net Merit yet—CDCB’s still working through the index weighting debates—producers are developing their own approaches. Here’s what’s working based on early adopters and extension recommendations from Cornell to UC Davis:

Start with your current selection criteria. Then layer in MSPD targeting, aiming for bulls in that 7.0 to 8.0 pounds per minute range based on CDCB’s guidance. If you’re pushing toward the higher end—say 7.6 or above—make sure those bulls have strong SCS values, like -2.5 or better. University of Minnesota’s dairy genetics team emphasizes this as important protection against potential udder health issues down the road.

Corrective mating within families is showing real promise. Long-term research led by Bradley Heins and colleagues at the University of Minnesota, published in the Journal of Dairy Science in 2023, demonstrates that this approach is particularly effective. Got cow families that consistently produce those 8-minute milkers? Target them with higher MSPD bulls. With 42% heritability, this trait actually responds to selection pressure—genetic theory says it should, and early results seem to confirm it.

The Seven-Year Reality (And Why It’s Worth It)

Patience pays – While neighbors chase quick fixes, smart producers are building unstoppable genetic momentum that compounds every generation
YearHerd % with MSPD GeneticsTime Savings per DayAnnual Labor Savings (500 cows)Worker Impact
Years 1-20%0 minutes$0Planning phase
Years 3-430-35%10-15 minutes$2,000-3,000First improvements noticed
Years 5-660-70%30-45 minutes$8,000-12,000Predictable shift times
Year 7+90%+60+ minutes$15,000-20,000Full transformation achieved

Let’s be honest about the timeline here. Genetic improvement doesn’t happen overnight, and anyone who tells you different is selling something.

Years one and two, you’re making different breeding decisions but milking the same cows. Minimal visible change. This tests your patience.

In years three and four, your first MSPD daughters arrive. With typical U.S. replacement rates around 30-35% annually, according to the USDA’s National Agricultural Statistics Service, about a third of your herd carries improved genetics. Many operations notice some improvement—maybe saving 10-15 minutes per milking. Not revolutionary yet, but you’re starting to see it.

Years five and six bring the real changes. Most of your herd now carries selected genetics. Those problem cows become exceptions rather than the rule. This is when producers often report actually seeing the payoff they’ve been waiting for.

By year seven and beyond, with most of your herd carrying these genetics, parlor performance becomes remarkably more uniform. And here’s the beautiful part—improvement continues compounding. Each generation gets bred to progressively better MSPD bulls.

A Practical Economic Example

The $18,000 sweet spot – Push past 8.0 lbs/min and watch health costs eat your labor savings.

Let’s run through some basic math for a 500-cow operation (and remember, your results will vary—talk to your consultants and run your own numbers):

Current Situation:

  • 3 milkings daily × 3 hours each = 9 hours parlor time
  • 2 workers × local wage rate × 9 hours = your daily labor cost
  • Annual parlor labor: varies significantly by region

With MSPD Selection (Year 5+):

  • Even modest improvements in turn time—saving just an hour per day—can multiply into several thousand dollars in savings each year
  • The real value depends entirely on your local labor costs and schedules
  • Plus: Better worker retention, less overtime, potential to add cows without extending shifts

Operations with larger spreads in current genetics or higher labor costs naturally have a greater impact. And we’re not even counting the value of predictable shifts on worker satisfaction—something that’s hard to put a dollar figure on but matters enormously.

Critical Management Adjustments

Several things can make or break your MSPD implementation:

Parlor Settings Matter: As detailed in the University of Wisconsin Extension’s milking management guides, many operations find that as their fastest-milking cows become the genetic norm, periodic review of parlor vacuum and pulsation settings helps optimize udder health. You might need to reduce the vacuum as cow milking speed increases modestly—consult your local extension for detailed guidance specific to your setup.

Meter Calibration Is Essential: If it’s been more than two years since calibration (and for many of us, it’s been longer), you can’t accurately track progress. Penn State Extension’s dairy team consistently stresses this—you need accurate data to verify genetic improvement.

The Transition Gets Messy: As new genetics mix with old during years 3-4, variation might temporarily increase. Smart managers group MSPD-selected animals together initially, maintaining more consistent parlor sides until a critical mass is reached.

What About Jerseys and Brown Swiss?

CDCB indicates that breed-specific evaluations are forthcoming, likely within the next 12 months. But producers aren’t waiting.

Long-term research from Bradley Heins and his team at the University of Minnesota, published in the Journal of Dairy Science in 2023, shows Jersey-Holstein crosses often demonstrate favorable milking characteristics while maintaining component advantages. These crossbreeding strategies can capture efficiency benefits now.

Brown Swiss producers are leveraging existing, subjectively scored evaluations while planning for the transition. And operations with sensor-equipped parlors—regardless of breed—should start collecting baseline data now. When official evaluations launch, you’ll be ahead of the curve.

The Bigger Industry Picture

Labor challenges aren’t going away. USDA Economic Research Service reports from 2024 document ongoing workforce issues across all agricultural sectors; however, dairy faces unique challenges due to the 365-day-per-year, twice-daily (or more) milking requirement. From Texas to Maine, finding reliable parlor help remains a top challenge.

What makes MSPD compelling is that it’s a genetic solution to what’s traditionally been viewed as a management problem. Rather than constantly tweaking protocols, adjusting groups, or chasing equipment fixes, we can actually breed for the efficiency we need.

International markets are watching too. With different countries reporting varying heritability levels for milking speed traits, the U.S., with a heritability level of 42%, creates interesting dynamics in the global genetics marketplace, according to the National Association of Animal Breeders’ 2024 export report.

Making Your Decision

As we move ahead, MSPD presents a genuine opportunity to address operational challenges through genetic selection. Will it transform your operation overnight? No. Will it gradually but meaningfully improve parlor throughput, reduce labor needs, and create more predictable working conditions? The early evidence from operations across the country suggests yes.

Those who wait will continue to manage current challenges, while early adopters will gradually pull ahead. It’s not dramatic—it’s incremental. But in an industry with tight margins, incremental advantages compound into competitive differences.

The collaborative learning happening right now is exciting to watch. As more operations implement MSPD selection and share their experiences, we’re collectively figuring out what works best in different situations. Producers comparing notes, extension specialists gathering data, geneticists refining recommendations—that’s how our industry gets stronger.

The trait is real, the heritability is remarkable, and it’s available now. The question isn’t whether milking speed genetics work—the data from CDCB confirms they do. The question is whether you’ll be among those who capture the advantages now, while labor challenges intensify and every minute counts. For operations dealing with parlor efficiency issues, inconsistent milking times, or persistent labor challenges, MSPD deserves serious consideration. Don’t wait for “more proof”—by the time everyone’s convinced, the early adopters will have already locked in their competitive advantages and smoother morning routines.

KEY TAKEAWAYS

  • Select bulls between 7.0-8.0 lbs/min for optimal results—this range balances efficiency gains with udder health based on CDCB’s data and extension recommendations, avoiding the mastitis risks associated with extreme speed
  • Expect 10-15 minutes saved per milking after 3 years, with full benefits emerging around year 7 as genetic turnover reaches 90%—patience during the transition pays off in $10,000-16,000 annual labor savings for typical 500-cow operations
  • Adjust parlor vacuum and pulsation settings as genetics improve—University of Wisconsin Extension research shows dropping vacuum from 14.5 to 13.5 inches helps prevent teat-end damage as milking speeds increase
  • Group MSPD-selected animals together during transition years 3-4 to maintain parlor consistency while genetic variance temporarily increases—smart pen management helps capture benefits sooner
  • Jersey and Brown Swiss producers can start collecting baseline data now using sensor-equipped parlors, positioning themselves ahead of breed-specific evaluations expected within 12 months, according to CDCB

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

Learn More:

Join the Revolution!

Join over 30,000 successful dairy professionals who rely on Bullvine Weekly for their competitive edge. Delivered directly to your inbox each week, our exclusive industry insights help you make smarter decisions while saving precious hours every week. Never miss critical updates on milk production trends, breakthrough technologies, and profit-boosting strategies that top producers are already implementing. Subscribe now to transform your dairy operation’s efficiency and profitability—your future success is just one click away.

NewsSubscribe
First
Last
Consent

New Sensor-Based Milking Speed Trait from CDCB Debuts August 2025

Ditch subjective milking scores. New sensor genetics deliver $13K savings while conventional methods become obsolete August 2025.

EXECUTIVE SUMMARY: The dairy industry’s century-old reliance on subjective milking speed scoring is about to become obsolete, thanks to CDCB’s revolutionary sensor-based Milking Speed (MSPD) trait launching August 2025. Built from an unprecedented dataset of 50 million individual milking observations across 300 herds and 31 states, this isn’t another incremental genetic improvement—it’s a complete paradigm shift from guesswork to precision. While traditional MSP traits depend on classifier opinions during type evaluation, MSPD harnesses real-time data from in-line sensors to deliver objective Predicted Transmitting Abilities measured in pounds-per-minute. The implications are staggering: with Holstein averages at 7.1 pounds per minute, even modest genetic gains could dramatically improve parlor throughput and reduce labor costs across millions of milkings annually. However, the 0.37 genetic correlation with Somatic Cell Score reveals why selecting for speed alone could backfire—successful implementation requires integrated breeding strategies that balance efficiency with udder health. For progressive producers ready to abandon subjective assessments and embrace data-driven milking efficiency, the August launch represents a critical competitive advantage. The question isn’t whether you’ll adopt sensor-based milking speed genetics, but whether you’ll be among the first to capitalize on this revolutionary selection tool.

KEY TAKEAWAYS

  • Objective Data Trumps Human Opinion: MSPD’s foundation of 50 million sensor-recorded milkings from 250,000 cows across 11 equipment manufacturers eliminates the subjectivity plaguing traditional speed classifications, delivering 69% average reliability for proven bulls—a massive improvement over subjective scoring systems.
  • Parlor Efficiency Revolution: With Holstein milking speeds averaging 7.1 pounds per minute, genetic selection for optimized flow rates could reduce milking time per cow by 15-20%, directly translating to increased throughput capacity and reduced labor costs in existing facilities without capital investment.
  • Balanced Selection Critical for Profitability: The 0.37 genetic correlation between MSPD and Somatic Cell Score demands integration within comprehensive indexes like Net Merit rather than standalone selection—producers focusing solely on speed risk increased mastitis treatment costs that could offset efficiency gains.
  • Data Flow Determines Success: Implementation success hinges entirely on consistent submission of novel data points (milking duration, equipment manufacturer, session timing) from participating farms to the National Cooperator Database—making early adoption contingent on robust data collection protocols.
  • Global Competitive Positioning: U.S. entry into Interbull evaluations alongside 14 other countries positions American Holstein genetics for enhanced international competitiveness, potentially opening new export markets for bulls with superior sensor-verified milking efficiency genetics.

The dairy industry stands on the cusp of a significant advancement in genetic selection with the Council on Dairy Cattle Breeding’s (CDCB) upcoming release of two groundbreaking traits. Most notably, the new sensor-based Milking Speed (MSPD) trait for Holsteins promises to revolutionize parlor efficiency when it debuts in August 2025. Alongside this innovation, new genetic evaluations for calf health resistance are also in development, both representing critical steps forward in breeding more efficient and resilient dairy herds.

A New Era in Milking Efficiency Measurement

The new Milking Speed (MSPD) trait for Holsteins marks a substantial departure from traditional subjective scoring methods. Unlike the existing Milking Speed (MSP) trait available for Brown Swiss and Milking Shorthorn breeds, which relies on producer-assigned scores during classification, MSPD utilizes objective data collected directly from in-line sensors in milking systems.

“This trait is designed to increase efficiency in parlors and milking facilities across the country,” explains Dr. Asha Miles, Research Geneticist at USDA’s Animal Genomics & Improvement Laboratory (AGIL). “Predicted Transmitting Abilities for MSPD will represent the average pounds of milk per minute a cow or bull’s offspring is estimated to produce.”

The average milking speed for Holsteins is currently 7.1 pounds per minute, providing producers with a clear benchmark against which to evaluate potential breeding stock. By selecting for optimal milking speed—neither too slow nor too fast—dairy farmers can significantly improve parlor throughput, reduce labor costs, and potentially enhance udder health.

From Subjective Scores to Sensor Data: A Scientific Evolution

The development of the MSPD trait followed a comprehensive research approach that began in October 2021, when CDCB established a Milking Speed Task Force chaired by Dr. Miles. The research team outlined four key objectives: assembling diverse data, characterizing milking speed across different systems, examining biological effects, and standardizing the trait definition.

The foundation for MSPD development was an extensive dataset comprising approximately:

  • 300 herds across 31 states
  • 250,000 cows and 320,000 lactations
  • 50 million individual milking observations
  • Data from 6+ breeds and 11 Original Equipment Manufacturers

This shift from subjective scoring to sensor-based data represents a significant advancement in the science of genetic evaluation. “If quantitative milk flow rates were available, classification data were intentionally discarded,” noted researchers, underscoring the preference for objective measurements over subjective assessments.

Technical Foundation and Genetic Parameters

The proposed MSPD trait is based on a robust dataset of 50,406 lactation records from 1,642 bulls. The data underwent rigorous cleaning to ensure quality, with filters removing erroneous recordings such as milking durations outside reasonable ranges and extreme milk yield values.

Key genetic parameters for Holstein MSPD include:

  • PTA range: -0.95 to 1.17 pounds per minute
  • Mean PTA: 0.09 pounds per minute
  • Standard deviation: 0.31 pounds per minute
  • Mean reliability: 69.07%

For young Holstein animals, MSPD predictions averaged 47% reliability—a solid starting point for a new trait, though lower than the typical 70% reliability seen in more established traits. This highlights the importance of continued data collection to enhance prediction accuracy.

The Critical Data Flow Challenge

Despite the rigorous scientific methodology and formal approval by the CDCB Genetic Evaluation Methods Committee and Board of Directors, routine data flow from farms remains the primary hurdle for successful implementation.

“With the Board approval of new data flow, CDCB is one step closer to releasing Milking Speed for Holsteins in August,” states a recent CDCB announcement. “As with the release of all new traits, this timeline is still tentative until new data is flowing into the National Cooperator Database and a test run of the trait has passed review.”

For MSPD evaluations to succeed, specific novel data points must be consistently submitted from dairy operations, including:

  • Observation date and milking session time
  • Milking frequency and attachment method
  • Equipment manufacturer information
  • Milk yield and duration per individual milking
  • Flags for abnormal milking events

To address this challenge, CDCB has developed a new data format in cooperation with Dairy Records Processing Centers (DRPC) to streamline integration into existing systems.

Balancing Efficiency with Health: Understanding Genetic Correlations

An important finding during MSPD development was its genetic correlation with other traits. Notably, MSPD showed a 0.37 correlation with Somatic Cell Score (SCS) for Holsteins, suggesting that selecting solely for faster milking speed could potentially impact udder health over generations.

This finding underscores the importance of balanced breeding strategies. Rather than selecting for MSPD in isolation, producers should integrate it within comprehensive selection indexes like Net Merit $ indicates a positive contribution to overall profitability while highlighting the need for careful consideration.

Parallel Development: New Calf Health Traits

Alongside MSPD, CDCB is also advancing genetic evaluations for calf health traits, specifically focusing on resistance to diarrhea (DIAR) and respiratory problems (RESP). These traits address a critical need, as 75% of pre-weaned calf mortality is attributed to these two conditions.

Preliminary research shows promising genetic parameters:

  • DIAR: Heritability of 0.026 based on 207,602 observations
  • RESP: Heritability of 0.022 based on 681,741 observations

While these heritability estimates appear low, they are deemed sufficient for evaluation purposes. More importantly, researchers found favorable correlations between genetic resistance to these diseases and overall heifer livability—DIAR showed a 0.13 correlation with heifer livability, while RESP showed a stronger 0.35 correlation.

“CDCB is asking producers and the industry to affirm that calf health data is flowing from farms into the National Cooperator Database,” notes a recent announcement. “As new traits move from research to operational implementation, access to contemporary data in the national database is imperative.”

The Power of Producer Participation

Both the MSPD and calf health traits highlight a fundamental truth in dairy genetic improvement: progress depends on producer participation in data collection and submission. The success of these new traits relies on farms across the country regularly submitting high-quality data to the National Cooperator Database.

“Together, dairy producers, the industry at large, and CDCB ensure that accurate data flows into the engine that produces genetic evaluations and fuels valuable resources that create better cows today and into the future,” explains a recent industry publication.

This collaborative effort involves more than 60 organizations spanning the dairy industry, from on-farm data collection and milk testing labs to breed associations and genomic nominators. In 2024, the database reached a significant milestone with the recording of the 100 millionth animal linked to performance data.

Looking Ahead: Timeline and Industry Impact

If all proceeds according to plan, the new MSPD trait for Holsteins will debut in August 2025. The immediate next step is a test run being conducted this month, which will be reviewed by the Dairy Evaluation Review Team and Genetic Evaluation Methods Committee.

The introduction of MSPD is expected to significantly benefit dairy producers through:

  • Improved parlor management and efficiency
  • Reduced labor costs through optimized milking times
  • Enhanced utilization of milking facilities
  • Greater overall farm profitability

Furthermore, the U.S. will join fourteen other countries participating in Interbull evaluations for milking speed, including Australia, Canada, and various European nations. This global alignment underscores the growing recognition of milking efficiency as a key component of dairy profitability.

The Bottom Line: Data-Driven Breeding for Tomorrow’s Dairy Industry

The upcoming introduction of the sensor-based Milking Speed trait and calf health evaluations represents more than just new selection tools—it signifies a broader shift toward data-driven decision-making in dairy breeding. By harnessing objective measurements from advanced milking systems and comprehensive health records, these traits promise more precise genetic selection for economically important characteristics.

However, the full potential of these innovations hinges on one critical factor: consistent data flow from dairy farms into the national database. As these new traits transition from research to practical implementation, producer participation becomes the determining factor in their success.

For dairy farmers looking to prepare for these new selection tools, now is the time to ensure that milking system data and calf health records are being captured and submitted through appropriate channels. The investment in data collection today will pay dividends in more efficient, healthier herds tomorrow.

Learn More:

Join the Revolution!

Join over 30,000 successful dairy professionals who rely on Bullvine Weekly for their competitive edge. Delivered directly to your inbox each week, our exclusive industry insights help you make smarter decisions while saving precious hours every week. Never miss critical updates on milk production trends, breakthrough technologies, and profit-boosting strategies that top producers are already implementing. Subscribe now to transform your dairy operation’s efficiency and profitability—your future success is just one click away.

NewsSubscribe
First
Last
Consent
Send this to a friend