WEBVTT 00:00:11.720 --> 00:00:15.060 Breaking free from the chains of the past Where 00:00:15.060 --> 00:00:18.820 truth moves faster than a Holstein calf No law 00:00:18.820 --> 00:00:21.660 waiting on some printed page We're charting new 00:00:21.660 --> 00:00:25.300 ground in the digital age From genomic codes 00:00:25.300 --> 00:00:29.120 to robot facts We cut through the noise, no hold 00:00:29.280 --> 00:00:32.460 them back not your daddy's dairy news tonight 00:00:32.460 --> 00:01:02.950 we're sparking Welcome to the Bullvine Podcast, 00:01:03.429 --> 00:01:05.629 where we challenge conventional dairy wisdom 00:01:05.629 --> 00:01:08.469 with cutting -edge insights that can transform 00:01:08.469 --> 00:01:11.930 your operation's profitability. Today, we're 00:01:11.930 --> 00:01:13.530 diving into something that's going to make a 00:01:13.530 --> 00:01:16.629 lot of people uncomfortable. We're talking about 00:01:16.629 --> 00:01:18.549 why everything you've been taught about keeping 00:01:18.549 --> 00:01:21.890 your milk sterile might actually be costing you 00:01:21.890 --> 00:01:26.269 serious money. That's right. Today... We're exposing 00:01:26.269 --> 00:01:29.370 the sterile milk myth and revealing how the trillions 00:01:29.370 --> 00:01:32.090 of microscopic workers already living inside 00:01:32.090 --> 00:01:34.549 your cows could boost your operations performance 00:01:34.549 --> 00:01:39.590 by 30%. We'll uncover university research showing 00:01:39.590 --> 00:01:42.750 that microbiome optimization can deliver $500 00:01:42.750 --> 00:01:47.390 in annual ROI per cow, discuss breakthrough probiotics 00:01:47.390 --> 00:01:49.810 that cut reproductive problems in half while 00:01:49.810 --> 00:01:52.459 boosting milk yield, and give you a practical 00:01:52.459 --> 00:01:55.459 18 -month roadmap to start capturing these advantages. 00:01:56.359 --> 00:01:59.480 But here's the thing. While we're debating this 00:01:59.480 --> 00:02:02.219 science, European operations have already been 00:02:02.219 --> 00:02:04.560 implementing these strategies for three years. 00:02:04.959 --> 00:02:07.900 The competitive advantage window is closing fast. 00:02:08.900 --> 00:02:11.860 So buckle up, because we're about to challenge 00:02:11.860 --> 00:02:14.900 50 years of industry dogma with evidence -based 00:02:14.900 --> 00:02:17.479 alternatives that could revolutionize your bottom 00:02:17.479 --> 00:02:20.550 line. Let's get started. Okay, so you've been 00:02:20.550 --> 00:02:23.069 laser focused on genetics, right? Dialing in 00:02:23.069 --> 00:02:25.289 those feed rations, tweaking every last detail. 00:02:25.409 --> 00:02:27.490 Standard practice, absolutely. Everyone's doing 00:02:27.490 --> 00:02:32.349 it. But what if the real engine driving your 00:02:32.349 --> 00:02:35.810 dairy's profits, what if it's powered by like 00:02:35.810 --> 00:02:37.930 trillions of workers you haven't even really 00:02:37.930 --> 00:02:40.370 thought of? You can't even see, yeah. And unlocking 00:02:40.370 --> 00:02:44.110 their potential. The science is starting to suggest 00:02:44.110 --> 00:02:46.469 efficiency gains, maybe up to 30%. Is that right? 00:02:46.780 --> 00:02:48.620 That's what some of the early data points towards, 00:02:48.680 --> 00:02:51.400 yes. Or, putting it another way, potentially 00:02:51.400 --> 00:02:55.560 adding over $500 per cow. per year straight back 00:02:55.560 --> 00:02:57.919 to your bottom line verifiable additions wow 00:02:57.919 --> 00:03:00.360 okay so that's not just you know wishful thinking 00:03:00.360 --> 00:03:03.379 it's becoming the new reality based on emerging 00:03:03.379 --> 00:03:06.580 science it really is and it uh it fundamentally 00:03:06.580 --> 00:03:08.419 challenges some of the ways we've been doing 00:03:08.419 --> 00:03:10.479 things the established practices in dairy for 00:03:10.479 --> 00:03:13.460 well for decades right the amount of data coming 00:03:13.460 --> 00:03:16.000 out now from serious university research it's 00:03:16.000 --> 00:03:19.400 just too significant and the the economic side 00:03:19.400 --> 00:03:22.400 of it is too profound to just carry on as usual 00:03:22.810 --> 00:03:25.590 Absolutely. And that's why we're here today for 00:03:25.590 --> 00:03:28.009 this deep dive. We're looking at a topic that's 00:03:28.009 --> 00:03:31.289 frankly accelerating, moving fast from the labs 00:03:31.289 --> 00:03:34.110 right onto farms and, you know, delivering actual 00:03:34.110 --> 00:03:37.610 results. Now, our focus, our source material 00:03:37.610 --> 00:03:40.750 for this whole discussion is an incredibly insightful 00:03:40.750 --> 00:03:42.870 article we found on The Bullvine. It's titled, 00:03:42.969 --> 00:03:45.969 Boosting Dairy Profits with Cow Microbiome Science. 00:03:46.750 --> 00:03:49.169 It's a great piece. Really pulls back the curtain, 00:03:49.210 --> 00:03:52.229 not just on the science itself, but crucially 00:03:52.229 --> 00:03:55.710 on the potential economic impact. What happens 00:03:55.710 --> 00:03:57.689 when you really understand and then start to 00:03:57.689 --> 00:04:01.030 manage the bovine microbiome? Yeah, these incredibly 00:04:01.030 --> 00:04:03.770 complex communities of microorganisms living 00:04:03.770 --> 00:04:06.330 inside and, well, even on your cows. Exactly. 00:04:06.889 --> 00:04:08.729 everywhere and our mission today it's not just 00:04:08.729 --> 00:04:10.250 to skim this bullvine article we're not here 00:04:10.250 --> 00:04:12.490 for a quick summary no we need to go deeper we 00:04:12.490 --> 00:04:14.810 want to spend our time together really unpacking 00:04:14.810 --> 00:04:16.850 the key findings it presents exploring some of 00:04:16.850 --> 00:04:19.350 the frankly surprising facts it highlights and 00:04:19.350 --> 00:04:21.930 most importantly drilling down into what this 00:04:21.930 --> 00:04:24.470 actually means for you for your operation your 00:04:24.470 --> 00:04:27.889 cows your profitability okay let's unpack this 00:04:27.889 --> 00:04:30.569 what's truly fascinating here and the article 00:04:30.569 --> 00:04:33.649 emphasizes this right from the start is how something 00:04:33.649 --> 00:04:38.209 so invisible, so tiny, these trillions of microbes 00:04:38.209 --> 00:04:41.490 can have such a massive direct impact on the 00:04:41.490 --> 00:04:44.370 whole system, the whole biological and economic 00:04:44.370 --> 00:04:47.310 system of your farm. It's mind -boggling when 00:04:47.310 --> 00:04:49.370 you think about the scale. It is. And we're not 00:04:49.370 --> 00:04:51.670 talking about, you know, tiny little tweaks here 00:04:51.670 --> 00:04:53.269 and there. We're going to look at the research 00:04:53.269 --> 00:04:55.850 discussed in the article, the hard numbers it 00:04:55.850 --> 00:04:58.329 presents, and really try to understand what this 00:04:58.329 --> 00:05:00.689 could mean for your bottom line. So let's start 00:05:00.689 --> 00:05:02.790 right there. The core idea of the Bullvine article 00:05:02.790 --> 00:05:04.550 lays out, because it really is the foundation 00:05:04.550 --> 00:05:06.850 for everything else. Okay. The central argument 00:05:06.850 --> 00:05:10.970 is basically this. For years, Decades, maybe. 00:05:11.209 --> 00:05:13.389 Producers like you have been focused, and rightly 00:05:13.389 --> 00:05:16.629 so, on genetics, using genomics, selecting the 00:05:16.629 --> 00:05:19.389 best animals, and refining feed systems. You 00:05:19.389 --> 00:05:21.930 know, precision feeding, analyzing every input. 00:05:22.149 --> 00:05:24.310 The cornerstones of modern dairy management? 00:05:24.589 --> 00:05:27.769 Exactly. But in doing that, we've largely overlooked 00:05:27.769 --> 00:05:30.310 what the article calls this, well, this massive 00:05:30.310 --> 00:05:33.470 microscopic workforce inside the cow. Trillions 00:05:33.470 --> 00:05:35.350 of them. You know, in the room, in the gut, the 00:05:35.350 --> 00:05:38.509 reproductive tract, even the mammary gland. These 00:05:38.509 --> 00:05:40.790 microbes are actually doing the heavy lifting, 00:05:40.970 --> 00:05:43.689 converting feed into milk, maintaining health, 00:05:43.850 --> 00:05:46.589 enabling reproduction. That's the critical reframing, 00:05:46.589 --> 00:05:48.629 isn't it? The article positions these microbes 00:05:48.629 --> 00:05:53.569 as, like, nature's smallest employees, but maybe 00:05:53.569 --> 00:05:56.970 the most powerful. Could be. Working 24 -7, mostly 00:05:56.970 --> 00:06:00.430 unseen, unmanaged, quietly deciding feed efficiency. 00:06:01.079 --> 00:06:03.740 health status, and ultimately how much ends up 00:06:03.740 --> 00:06:06.199 on that milk check. And the article makes a bold 00:06:06.199 --> 00:06:08.579 claim, almost provocative. It says the next big 00:06:08.579 --> 00:06:10.920 breakthrough. It's not just another genetic tweak 00:06:10.920 --> 00:06:13.939 or a new robot. It's microbial. That's a big 00:06:13.939 --> 00:06:15.879 statement. How do they back that up? Well, it 00:06:15.879 --> 00:06:17.879 highlights results from, you know, early adopters 00:06:17.879 --> 00:06:19.620 and some putting edge research that are pretty 00:06:19.620 --> 00:06:21.420 attention grabbing. Farms reporting things like 00:06:21.420 --> 00:06:23.939 a 50 % drop in post calving reproductive issues. 00:06:24.180 --> 00:06:27.379 50%. Wow. Yeah. Or increases in daily milk yield 00:06:27.379 --> 00:06:29.939 of four to six liters per cow. Four to six liters 00:06:29.939 --> 00:06:33.360 per day. per day and feed conversion improvements 00:06:33.360 --> 00:06:36.139 that according to the article are rivaling maybe 00:06:36.139 --> 00:06:38.779 even beating the gains we've seen from genomics 00:06:38.779 --> 00:06:41.620 now it's careful to say these are early reports 00:06:41.620 --> 00:06:44.660 but still it points to a scale of impact that's 00:06:44.660 --> 00:06:46.639 just different it really does and it makes you 00:06:46.639 --> 00:06:49.639 think the article points out when you spend so 00:06:49.639 --> 00:06:53.399 much time tracking tpi dmi lactation curves yeah 00:06:54.110 --> 00:06:56.689 All crucial metrics. Absolutely crucial. You're 00:06:56.689 --> 00:06:59.009 essentially managing only half the picture. You're 00:06:59.009 --> 00:07:01.050 focused on the host animal, the inputs, the outputs. 00:07:01.470 --> 00:07:04.689 But you're ignoring the complex biological machinery 00:07:04.689 --> 00:07:07.149 inside that actually does the processing. Yeah. 00:07:07.500 --> 00:07:10.000 Turns feed into milk. Exactly. And this isn't 00:07:10.000 --> 00:07:12.319 just, you know, some fringe theory anymore. The 00:07:12.319 --> 00:07:14.420 Bullvine article really stresses that the science 00:07:14.420 --> 00:07:17.259 is moving into the mainstream fast. It talks 00:07:17.259 --> 00:07:19.879 about findings from top universities across North 00:07:19.879 --> 00:07:22.800 America proving like conclusively the direct 00:07:22.800 --> 00:07:25.279 measurable link between the microbiome and those 00:07:25.279 --> 00:07:27.120 things you track every single day. Feed conversion, 00:07:27.480 --> 00:07:30.560 SCC, repro success. Okay. The analogy they use 00:07:30.560 --> 00:07:32.699 is pretty good. Think of the rumen, right? It's 00:07:32.699 --> 00:07:35.779 this incredibly high tech fermentation facility. 00:07:36.379 --> 00:07:38.899 Where all the magic happens. Right. But trying 00:07:38.899 --> 00:07:42.240 to manage that facility. optimizing the feed 00:07:42.240 --> 00:07:44.220 going in, tracking the milk coming out without 00:07:44.220 --> 00:07:46.560 understanding or managing the microbial community 00:07:46.560 --> 00:07:49.420 inside. It's like trying to run a feed mill without 00:07:49.420 --> 00:07:51.540 knowing how the mixers or the grinders actually 00:07:51.540 --> 00:07:53.379 work. You're just managing from the outside, 00:07:53.600 --> 00:07:55.740 blind to the internal mechanics. Pretty much. 00:07:55.879 --> 00:07:59.220 And the cost of that blind spot, let's call it, 00:07:59.279 --> 00:08:01.860 the article puts a number on it. For an average 00:08:01.860 --> 00:08:04.600 100 cow dairy, they estimate it's costing between 00:08:04.600 --> 00:08:08.439 $25 ,000 and $40 ,000 a year. just in lost efficiency. 00:08:08.819 --> 00:08:12.720 $25 ,000 to $40 ,000. That's serious money being 00:08:12.720 --> 00:08:15.860 left on the table every year. It is. And this 00:08:15.860 --> 00:08:18.319 leads us to maybe one of the most challenging 00:08:18.319 --> 00:08:20.560 points in the article, the whole sterile world 00:08:20.560 --> 00:08:23.779 idea. Ah, yes. The idea that cleaner is always 00:08:23.779 --> 00:08:26.259 better. Sanitize everything. Exactly. It's been 00:08:26.259 --> 00:08:27.920 drilled into the industry for decades, almost 00:08:27.920 --> 00:08:30.879 universally accepted. Kill all the bacteria and 00:08:30.879 --> 00:08:33.899 problems like mastitis, metritis, scours, they'll 00:08:33.899 --> 00:08:36.559 just disappear. Makes intuitive sense, I guess. 00:08:36.679 --> 00:08:39.679 It does, on the surface. But the article presents 00:08:39.679 --> 00:08:42.139 this counter -argument, and it's backed by evidence. 00:08:42.539 --> 00:08:45.460 That this very approach, this obsession with 00:08:45.460 --> 00:08:48.259 sterility, might actually be sabotaging profitability 00:08:48.259 --> 00:08:51.379 and animal health. How so? Because by trying 00:08:51.379 --> 00:08:54.679 to wipe out all bacteria, we've been unintentionally 00:08:54.679 --> 00:08:57.179 killing off the vast populations of beneficial 00:08:57.179 --> 00:08:59.679 microbes, the good guys. The ones that help the 00:08:59.679 --> 00:09:02.049 cow. Precisely. The ones that naturally suppress 00:09:02.049 --> 00:09:05.289 pathogens, optimize digestion, stimulate the 00:09:05.289 --> 00:09:07.409 immune system, and generally keep things running 00:09:07.409 --> 00:09:10.429 smoothly. We've been throwing the baby out with 00:09:10.429 --> 00:09:12.750 the bathwater, so to speak. The article uses 00:09:12.750 --> 00:09:15.409 another analogy too, right? The TMR mixer. Yeah, 00:09:15.450 --> 00:09:17.389 that's a good one. It's like focusing entirely 00:09:17.389 --> 00:09:19.789 on... perfecting the ingredient list for your 00:09:19.789 --> 00:09:23.409 tmr getting the ratios just right but never checking 00:09:23.409 --> 00:09:25.610 if the paddles inside the mixer are actually 00:09:25.610 --> 00:09:27.710 working properly to blend it all together for 00:09:27.710 --> 00:09:29.970 the cow so we've mastered the external factors 00:09:29.970 --> 00:09:34.389 genetics feed parlor routine but ignored or even 00:09:34.389 --> 00:09:36.850 hindered the internal biology that seems to be 00:09:36.850 --> 00:09:40.090 the argument so what changed why now good question 00:09:40.090 --> 00:09:43.240 what kicked off this shift in thinking The article 00:09:43.240 --> 00:09:46.039 points squarely at the revolution in DNA sequencing 00:09:46.039 --> 00:09:49.620 technology. Suddenly, researchers could see the 00:09:49.620 --> 00:09:52.299 whole picture, not just culture, the few bad 00:09:52.299 --> 00:09:55.179 guys they could grow in a lab, but analyze the 00:09:55.179 --> 00:09:58.039 entire microbial community, the whole ecosystem. 00:09:58.440 --> 00:10:00.779 And what did they find? The big discovery, the 00:10:00.779 --> 00:10:03.240 paradigm shift, was that healthy, high -producing 00:10:03.240 --> 00:10:06.740 cows aren't sterile. Far from it. They are absolutely 00:10:06.740 --> 00:10:09.860 teeming with diverse, abundant populations of 00:10:09.860 --> 00:10:12.899 beneficial microbes. Those microbes are essential 00:10:12.899 --> 00:10:15.379 for their health and performance. So it flipped 00:10:15.379 --> 00:10:19.110 the script from... All bacteria are bad to we 00:10:19.110 --> 00:10:21.429 need the right bacteria. Exactly. From elimination 00:10:21.429 --> 00:10:25.169 to cultivation. And that fundamental shift underpins 00:10:25.169 --> 00:10:26.909 everything else the article gets into. Okay. 00:10:26.950 --> 00:10:29.549 And nowhere does that seem more impactful, economically 00:10:29.549 --> 00:10:32.399 speaking, than feed efficiency. Right. This is 00:10:32.399 --> 00:10:34.440 where, as you said, the rubber really meets the 00:10:34.440 --> 00:10:36.620 road for producers. The Bullvine article hits 00:10:36.620 --> 00:10:38.580 hard here with a statistic. Yeah. It says the 00:10:38.580 --> 00:10:41.279 rumen microbiome composition alone can predict 00:10:41.279 --> 00:10:43.639 a significant chunk of the variation in feed 00:10:43.639 --> 00:10:46.059 efficiency between cows. Think about that. Not 00:10:46.059 --> 00:10:47.980 just genetics, not just the ration formulation, 00:10:48.259 --> 00:10:51.059 but the actual bugs in the gut. And the timing 00:10:51.059 --> 00:10:53.259 couldn't be more critical, could it? Feed costs. 00:10:54.159 --> 00:10:56.679 They're what, 50, 70 percent of total production 00:10:56.679 --> 00:10:58.899 costs? Easily. often the biggest single expense 00:10:58.899 --> 00:11:00.840 line. And the article points out the current 00:11:00.840 --> 00:11:04.559 market May 2025 Class III milk around $18 .57, 00:11:05.000 --> 00:11:08.320 U .S. production growth pretty flat at 0 .5%. 00:11:08.320 --> 00:11:10.620 Yeah, margins are tight. Every penny counts. 00:11:10.899 --> 00:11:13.500 So squeezing more efficiency out of that feed 00:11:13.500 --> 00:11:15.919 is absolutely paramount. The article mentions 00:11:15.919 --> 00:11:18.159 specific research from Washington State University. 00:11:18.460 --> 00:11:21.799 It does. WSU found that somewhere between 7 % 00:11:21.799 --> 00:11:25.330 and, get this, 30 % of the variation in feed 00:11:25.330 --> 00:11:27.409 efficiency traits could be linked directly to 00:11:27.409 --> 00:11:29.990 specific microbial populations in the rumen. 00:11:30.210 --> 00:11:34.190 7 to 30%. That's a huge range. But even the low 00:11:34.190 --> 00:11:36.850 end is significant. It is. When they crunched 00:11:36.850 --> 00:11:38.990 the numbers, these microbes had what they call 00:11:38.990 --> 00:11:41.730 significant structural coefficients. Basically, 00:11:41.730 --> 00:11:44.990 a strong direct link to how efficiently the cow 00:11:44.990 --> 00:11:46.710 converted feed. And what's the difference between 00:11:46.710 --> 00:11:48.470 the efficient cows and the inefficient ones, 00:11:48.529 --> 00:11:50.710 according to that research? It boils down to 00:11:50.710 --> 00:11:53.409 the players on the microbial team. They have 00:11:53.409 --> 00:11:56.070 fish and animals. They consistently had more 00:11:56.070 --> 00:11:58.490 of certain bacteria that are really good at breaking 00:11:58.490 --> 00:12:01.110 down fiber and producing volatile fatty acids, 00:12:01.230 --> 00:12:04.210 VFAs. The VFAs, that's the energy source for 00:12:04.210 --> 00:12:06.870 the cow, right? Fuel for milk. Exactly. Acetate, 00:12:06.889 --> 00:12:09.950 propionate, butyrate. That's what powers the 00:12:09.950 --> 00:12:12.429 milk machine. The inefficient cows, on the other 00:12:12.429 --> 00:12:15.110 hand, had different microbial communities, maybe 00:12:15.110 --> 00:12:17.950 less effective fiber digesters, maybe some that 00:12:17.950 --> 00:12:19.899 just weren't. pulling their weight effectively 00:12:19.899 --> 00:12:22.879 wasting expensive feed okay let's talk dollars 00:12:22.879 --> 00:12:25.529 and cents The article gives a concrete example, 00:12:25.710 --> 00:12:28.830 right? A 100 -cow herd. Yes. Imagine that herd 00:12:28.830 --> 00:12:32.269 has an annual feed bill of $150 ,000. Pretty 00:12:32.269 --> 00:12:34.730 standard. The article suggests that achieving 00:12:34.730 --> 00:12:38.009 a 25 % improvement in feed efficiency, maybe 00:12:38.009 --> 00:12:40.509 through targeted microbiome work, could save 00:12:40.509 --> 00:12:45.230 you $37 ,500 a year on that feed bill. $37 ,500. 00:12:45.429 --> 00:12:47.470 Yeah. It's massive. And that's not just a gross 00:12:47.470 --> 00:12:49.269 number. Even after factoring in the potential 00:12:49.269 --> 00:12:50.970 costs of these interventions, which we'll get 00:12:50.970 --> 00:12:53.409 to the net benefit, the article estimates, still 00:12:53.409 --> 00:12:57.009 be over $30 ,000 a year for that herd. Wow. And 00:12:57.009 --> 00:12:59.350 the comparison they make, saving that much is 00:12:59.350 --> 00:13:02.049 like adding 15 or 20 cows. Yeah, somewhere in 00:13:02.049 --> 00:13:05.070 that range. Equivalent economic impact, but without 00:13:05.070 --> 00:13:07.370 the huge capital cost of expanding facilities. 00:13:07.570 --> 00:13:09.850 It's like finding free capacity through pure 00:13:09.850 --> 00:13:12.450 efficiency. Now, there was an interesting point 00:13:12.450 --> 00:13:15.149 in this section, maybe a bit counterintuitive, 00:13:15.269 --> 00:13:19.629 about diversity. Ah, yes. The University of Alberta 00:13:19.629 --> 00:13:22.710 research, it challenges the idea that more is 00:13:22.710 --> 00:13:24.710 always better when it comes to rumen microbes. 00:13:25.029 --> 00:13:27.769 Right. You'd think maximum activity would be 00:13:27.769 --> 00:13:30.029 best for digestion. That's the intuitive thought. 00:13:30.090 --> 00:13:32.649 Absolutely. But this research found that sometimes 00:13:32.649 --> 00:13:36.210 the most feed efficient cattle actually had less 00:13:36.210 --> 00:13:39.110 overall diversity in their rumen microbiota and 00:13:39.110 --> 00:13:41.370 maybe even less total microbial activity compared 00:13:41.370 --> 00:13:44.169 to less efficient animals. Less diversity. How 00:13:44.169 --> 00:13:46.590 does that work? The implication, according to 00:13:46.590 --> 00:13:48.809 the article in that research, is that peak efficiency 00:13:48.809 --> 00:13:50.889 might not come from just having the most bugs 00:13:50.889 --> 00:13:53.230 or the most types of bugs. It's about having 00:13:53.230 --> 00:13:55.690 the right, highly specialized, super efficient 00:13:55.690 --> 00:13:58.830 communities doing the job. Precision over just 00:13:58.830 --> 00:14:01.679 sheer numbers. Okay, targeted efficiency. Exactly. 00:14:01.740 --> 00:14:03.620 And this is reinforced by another study mentioned 00:14:03.620 --> 00:14:06.120 from the Journal of Dairy Science. They found 00:14:06.120 --> 00:14:08.500 that combining data looking at both the cow's 00:14:08.500 --> 00:14:11.639 genome and her rumen microbiome gave a significantly 00:14:11.639 --> 00:14:14.340 better prediction of feed efficiency than just 00:14:14.340 --> 00:14:16.720 looking at genomics alone. So you need both pieces 00:14:16.720 --> 00:14:19.659 of the puzzle, genetics and microbes. That's 00:14:19.659 --> 00:14:21.740 the idea behind the Holobion effect they mention. 00:14:21.919 --> 00:14:24.559 The combined effect of the host and its entire 00:14:24.559 --> 00:14:27.059 microbial community is greater than the sum of 00:14:27.059 --> 00:14:29.539 its parts. You need to consider both together 00:14:29.539 --> 00:14:32.919 for optimal management and selection. The article 00:14:32.919 --> 00:14:35.399 uses that twin heifer example to really illustrate 00:14:35.399 --> 00:14:37.159 this, doesn't it? Oh, it's a fantastic example. 00:14:37.379 --> 00:14:39.399 Really drives the point home. So paint the picture 00:14:39.399 --> 00:14:43.039 for us. Two heifers. Identical twins. Genetically 00:14:43.039 --> 00:14:46.120 identical. Raised together, same feed, same barn, 00:14:46.259 --> 00:14:49.039 same everything. But one heifer is consistently 00:14:49.039 --> 00:14:52.220 22 % more feed efficient than her sister. And 00:14:52.220 --> 00:14:54.720 traditionally, you'd just chalk that up to what? 00:14:55.500 --> 00:14:58.340 Random chance environment. Exactly. Something 00:14:58.340 --> 00:15:01.120 vague, undetectable, unmanageable. You'd throw 00:15:01.120 --> 00:15:03.820 your hands up. But the microbiome analysis, as 00:15:03.820 --> 00:15:06.240 the article describes it, gives a clear answer. 00:15:06.399 --> 00:15:07.960 What's the difference? The more efficient twin 00:15:07.960 --> 00:15:10.159 simply has a different mix of microbes in her 00:15:10.159 --> 00:15:12.769 gut. communities that are better at extracting 00:15:12.769 --> 00:15:15.740 energy. Her sister, despite the identical genes 00:15:15.740 --> 00:15:18.419 and environment, has a less effective microbial 00:15:18.419 --> 00:15:20.919 crew, leaving money undigested. And the article 00:15:20.919 --> 00:15:23.139 provides actual numbers for this. It does. A 00:15:23.139 --> 00:15:25.879 table showing the specifics. Heifer A, the efficient 00:15:25.879 --> 00:15:29.759 one, had a feed conversion ratio, FCR, of 1 .4 00:15:29.759 --> 00:15:33.200 .1. Meaning 1 .4 units of feed per unit of gain 00:15:33.200 --> 00:15:36.860 or milk. Right. Her sister, Heifer B, was 1 .8 00:15:36.860 --> 00:15:40.179 .1. That's the 22 % difference. Heifer A ate 00:15:40.179 --> 00:15:43.840 less. 2 .4 kilograms less dry matter per day. 00:15:44.000 --> 00:15:46.320 Ate less, but performed better. In terms of efficiency, 00:15:46.539 --> 00:15:49.639 yes. She produced 2 .35 units of milk per kilogram 00:15:49.639 --> 00:15:52.580 of feed, while her sister only managed 1 .85. 00:15:52.899 --> 00:15:55.679 That's 27 % more milk bang for your feed buck. 00:15:55.860 --> 00:15:58.379 Wow. And the cost difference. Annually, based 00:15:58.379 --> 00:16:00.480 on their calculations, heifer A's feed cost was 00:16:00.480 --> 00:16:05.879 about $11 ,125. Heifer B's was $1 ,500, a $375 00:16:05.879 --> 00:16:08.600 difference per cow per year, purely down to the 00:16:08.600 --> 00:16:11.159 microbes. So the article asks the listener, if 00:16:11.159 --> 00:16:13.100 you're picking dams for your future herd sires, 00:16:13.120 --> 00:16:14.919 which data do you use? Just traditional metrics? 00:16:15.080 --> 00:16:17.309 Or do you add this microbiome insight? It really 00:16:17.309 --> 00:16:19.690 makes the economic stakes crystal clear, doesn't 00:16:19.690 --> 00:16:21.850 it? It's not just managing inputs, it's managing 00:16:21.850 --> 00:16:24.710 the biological conversion process. Okay, moving 00:16:24.710 --> 00:16:27.549 on from feed efficiency, let's tackle mastitis, 00:16:27.730 --> 00:16:31.710 another huge profit drain. And here, the Bullvine 00:16:31.710 --> 00:16:33.889 article apparently throws down another gauntlet, 00:16:33.950 --> 00:16:36.470 challenges another core belief. It really does. 00:16:36.610 --> 00:16:38.190 This one might be even more controversial for 00:16:38.190 --> 00:16:41.840 some. The claim is blunt. Sterile milk is a myth. 00:16:41.960 --> 00:16:44.759 A myth. A myth. And the aggressive pursuit of 00:16:44.759 --> 00:16:47.399 sterility, trying to kill every last bacterium 00:16:47.399 --> 00:16:49.820 in the udder and milking system, it might actually 00:16:49.820 --> 00:16:52.399 be hurting udder health and contributing to higher 00:16:52.399 --> 00:16:55.179 SCC. Okay, that flies directly in the face of 00:16:55.179 --> 00:16:57.039 everything we've been taught about mastitis prevention. 00:16:57.559 --> 00:17:00.679 Pre -dip, post -dip, sanitize everything. Exactly. 00:17:01.230 --> 00:17:03.190 But the article points to research published 00:17:03.190 --> 00:17:05.630 stuff showing healthy mammary glands are not 00:17:05.630 --> 00:17:08.369 sterile. They naturally contain bacteria. Quite 00:17:08.369 --> 00:17:11.369 a lot, actually. 10 ,000 to 100 ,000 cells per 00:17:11.369 --> 00:17:14.009 ml, even in healthy quarters. So bacteria are 00:17:14.009 --> 00:17:16.490 supposed to be there. It seems so. And critically, 00:17:16.630 --> 00:17:18.490 these studies consistently find that milk from 00:17:18.490 --> 00:17:20.569 healthy glands has greater bacterial richness 00:17:20.569 --> 00:17:23.130 and diversity compared to milk from clinical 00:17:23.130 --> 00:17:25.329 mastitis cases. More diversity is healthier. 00:17:25.490 --> 00:17:28.349 Like in the gut. That's the suggestion. A diverse 00:17:28.349 --> 00:17:31.509 balanced community might be key to utter health, 00:17:31.690 --> 00:17:34.670 not a sign of impending doom. And there was that 00:17:34.670 --> 00:17:38.089 study using PCR, Metzger et al. Yes, that's a 00:17:38.089 --> 00:17:41.190 crucial one. They used PCR, which is more sensitive 00:17:41.190 --> 00:17:43.650 than traditional culturing. They found bacteria 00:17:43.650 --> 00:17:46.750 way more often in samples taken from inside the 00:17:46.750 --> 00:17:49.230 gland, the cisternal samples, 83 % detection, 00:17:49.430 --> 00:17:52.930 compared to only 40 % detection in samples taken 00:17:52.930 --> 00:17:54.910 right at the teetot. Meaning the bacteria are 00:17:54.910 --> 00:17:57.490 really living inside, not just contaminants from 00:17:57.490 --> 00:17:59.589 the outside. That's the strong implication. There's 00:17:59.589 --> 00:18:02.049 an indigenous mammary microbiome. They're residents, 00:18:02.230 --> 00:18:04.390 not just tourists. Okay, so how does this connect 00:18:04.390 --> 00:18:07.619 to SCC and the cost of mastitis? While we know 00:18:07.619 --> 00:18:10.339 mastitis is expensive, the article cites Canadian 00:18:10.339 --> 00:18:13.420 research putting the cost at over $600 per cow 00:18:13.420 --> 00:18:17.220 per year. Lost milk, treatment, culling, it adds 00:18:17.220 --> 00:18:19.980 up fast. And specific infections, like Klebsiella, 00:18:20.039 --> 00:18:22.519 are linked to lower microbiome diversity. Right. 00:18:22.579 --> 00:18:24.839 It's like the pathogen disrupts the healthy community 00:18:24.839 --> 00:18:27.500 when it takes over. And the economic impact of 00:18:27.500 --> 00:18:31.160 high SEC is stark. The article uses data from 00:18:31.160 --> 00:18:33.799 Ireland. What do the Irish data show? A dramatic 00:18:33.799 --> 00:18:37.660 drop in net farm profit as bulk tank SEC went 00:18:37.660 --> 00:18:41.619 up. Farms with SEC under 100 ,000 averaged over 00:18:41.619 --> 00:18:46.220 31 ,000 profit. Those over 400 ,000, their profit 00:18:46.220 --> 00:18:49.259 plummeted to under 12 ,000. Wow. That's a direct 00:18:49.259 --> 00:18:51.660 link between SEC and the bottom line. Absolutely. 00:18:51.839 --> 00:18:54.259 They even calculated that just lowering the national 00:18:54.259 --> 00:18:56.920 average SCC by 10 ,000 cells, Mallory, could 00:18:56.920 --> 00:18:59.660 add 6 .6 million back into the Irish dairy economy 00:18:59.660 --> 00:19:02.019 annually. So the controversial point the article 00:19:02.019 --> 00:19:05.720 makes is our current prevention strategies focused 00:19:05.720 --> 00:19:08.039 on killing all bacteria. Might be wiping out 00:19:08.039 --> 00:19:09.660 the beneficial bacteria that could naturally 00:19:09.660 --> 00:19:12.279 help suppress pathogens and maintain low SCC 00:19:12.279 --> 00:19:14.539 and premium milk quality. Might be eliminating 00:19:14.539 --> 00:19:17.039 our allies. It makes you ask, right? Those problem 00:19:17.039 --> 00:19:20.640 cows, the chronic high SCC ones versus the cows 00:19:20.640 --> 00:19:23.140 that never seem to get mastitis, is the difference 00:19:23.140 --> 00:19:25.079 in their mammary microbiome. That's the million 00:19:25.079 --> 00:19:26.900 -dollar question, isn't it? Are some cows just 00:19:26.900 --> 00:19:28.980 better protected by their internal microbial 00:19:28.980 --> 00:19:31.059 community? And the environment plays a role, 00:19:31.140 --> 00:19:33.759 too. Barns, parlors having their own microbes. 00:19:34.140 --> 00:19:36.220 Yeah, the article mentions research showing dairy 00:19:36.220 --> 00:19:38.599 environments have complex microbial communities, 00:19:38.960 --> 00:19:42.660 including potentially beneficial ones. Could 00:19:42.660 --> 00:19:45.359 these good environmental bugs... help protect 00:19:45.359 --> 00:19:47.759 the udder if we weren't trying to sterilize everything. 00:19:48.099 --> 00:19:50.880 It really forces a fundamental rethink of mastitis 00:19:50.880 --> 00:19:53.440 control, doesn't it? Maybe moving from just killing 00:19:53.440 --> 00:19:57.519 bugs to fostering a healthy ecosystem. That seems 00:19:57.519 --> 00:19:59.140 to be the direction the science is pointing. 00:19:59.299 --> 00:20:02.039 A major shift in perspective. Okay, another major 00:20:02.039 --> 00:20:06.519 area impacting the bottom line. Reproduction. 00:20:06.599 --> 00:20:09.720 Oh, yeah. Silent profit killer. Y 'all know the 00:20:09.720 --> 00:20:13.220 pain. Every open day costs money, $3 to $5 a 00:20:13.220 --> 00:20:16.279 day. Extended calving intervals just wreck profitability. 00:20:16.720 --> 00:20:19.099 Destroys cash flow, messes up herd dynamics. 00:20:19.160 --> 00:20:21.440 It's a massive headache. And the Bullvine article 00:20:21.440 --> 00:20:24.079 suggests maybe a lot of this trouble starts with 00:20:24.079 --> 00:20:26.279 microbial imbalances in the reproductive tract, 00:20:26.440 --> 00:20:28.160 things we're not even looking at. That's the 00:20:28.160 --> 00:20:30.400 emerging picture. Issues like metritis, endometritis, 00:20:30.500 --> 00:20:33.000 poor conception. They might have a microbial 00:20:33.000 --> 00:20:35.539 root cause that we've been missing. And it highlights 00:20:35.539 --> 00:20:37.519 a specific development from the University of 00:20:37.519 --> 00:20:40.619 Alberta. Propregay. Yes, presented as a really 00:20:40.619 --> 00:20:43.339 significant breakthrough. So what is propregay 00:20:43.339 --> 00:20:46.880 exactly? It's described as a targeted probiotic. 00:20:46.880 --> 00:20:50.700 Not just a random mix, but three specific bacterial 00:20:50.700 --> 00:20:53.339 strains that researchers found were naturally 00:20:53.339 --> 00:20:55.759 abundant in the reproductive tracts of healthy, 00:20:55.900 --> 00:20:59.240 fertile cows. So giving back the good guys. That's 00:20:59.240 --> 00:21:01.660 the idea. Re -establishing or supporting that 00:21:01.660 --> 00:21:04.099 beneficial community. And the results highlighted 00:21:04.099 --> 00:21:07.180 in the article are pretty striking. A 50 % reduction 00:21:07.180 --> 00:21:10.500 in post -calving uterine infections. 50 % again. 00:21:10.619 --> 00:21:13.000 That's huge for getting cows bred back quickly 00:21:13.000 --> 00:21:15.740 and healthy. Massive. Uterine infections are 00:21:15.740 --> 00:21:18.420 a major roadblock. But the article says the benefits 00:21:18.420 --> 00:21:20.680 didn't stop there. What else do they see? An 00:21:20.680 --> 00:21:24.039 increase in milk yield. An extra 4 to 6 liters 00:21:24.039 --> 00:21:26.480 per day for the first 50 days after calving in 00:21:26.480 --> 00:21:29.059 the cows that got perpigae. 4 to 6 liters more 00:21:29.059 --> 00:21:31.700 milk. Just from improving reproductive tract 00:21:31.700 --> 00:21:34.299 health. Apparently so. It really shows how connected 00:21:34.299 --> 00:21:36.700 everything is. Reproductive health impacting 00:21:36.700 --> 00:21:39.119 early lactation performance. And the article 00:21:39.119 --> 00:21:41.579 stresses this wasn't a quick study. It was based 00:21:41.579 --> 00:21:44.220 on 10 years of rigorous testing. 10 years. Okay, 00:21:44.299 --> 00:21:46.019 so it's well -researched. Any other benefits, 00:21:46.140 --> 00:21:49.109 Mentor? Yes. Halved incidence of milk fever, 00:21:49.309 --> 00:21:52.769 reduced retained placentas, and even less inflammation 00:21:52.769 --> 00:21:55.809 -related lameness. Lameness too, wow. It suggests 00:21:55.809 --> 00:21:57.930 that a healthy reproductive microbiome contributes 00:21:57.930 --> 00:22:01.210 to the cow's overall systemic health during that 00:22:01.210 --> 00:22:03.410 critical transition period. Okay, let's crunch 00:22:03.410 --> 00:22:05.470 the numbers again, the economic impact. The article 00:22:05.470 --> 00:22:07.890 breaks it down. It does. First, the savings from 00:22:07.890 --> 00:22:10.789 fewer uterine infections. Let's say 20 % of your 00:22:10.789 --> 00:22:13.730 herd gets them, and treatment costs $300 a case. 00:22:14.279 --> 00:22:16.940 Cutting that incidence by 50 % saves you about 00:22:16.940 --> 00:22:20.460 $30 per cow across the herd annually. Okay, 30 00:22:20.460 --> 00:22:22.400 cows saved. What about the extra milk? Four to 00:22:22.400 --> 00:22:25.839 six liters a day for 50 days. That's 200 to 300 00:22:25.839 --> 00:22:28.799 extra liters per cow. The article uses a price 00:22:28.799 --> 00:22:32.119 of $0 .40 per liter, so that's an extra $80 to 00:22:32.119 --> 00:22:35.319 $120 in revenue per cow. So add the savings and 00:22:35.319 --> 00:22:38.980 the revenue, $30 plus, say, $125 for the milk 00:22:38.980 --> 00:22:41.799 using the average. You're looking at around $155 00:22:41.799 --> 00:22:45.500 total annual benefit per cow just from this one 00:22:45.500 --> 00:22:48.180 targeted reproductive health intervention. For 00:22:48.180 --> 00:22:53.380 a hundred cow herd, that's $15 ,500 a year. Potentially, 00:22:53.539 --> 00:22:56.359 yes. A significant return from tackling reproduction 00:22:56.359 --> 00:22:59.779 through a microbial lens. The article had another 00:22:59.779 --> 00:23:02.559 analogy here too, didn't it? About breeding programs. 00:23:02.859 --> 00:23:04.660 Yeah, it makes the point. You wouldn't just ignore 00:23:04.660 --> 00:23:06.799 your breeding program, bull selection, timing 00:23:06.799 --> 00:23:08.559 AI, and expect good results, right? Of course 00:23:08.559 --> 00:23:11.039 not. So why, the article asks, would you ignore 00:23:11.039 --> 00:23:13.180 the microbial environment inside the reproductive 00:23:13.180 --> 00:23:15.400 tract? Because that environment plays a huge 00:23:15.400 --> 00:23:17.980 role in whether your $50 semen investment actually 00:23:17.980 --> 00:23:20.140 turns into a calf. Makes sense. And the other 00:23:20.140 --> 00:23:23.380 research cited confirms endometritis hurts fertility, 00:23:23.640 --> 00:23:26.440 links microbes to calving problems. And importantly, 00:23:26.660 --> 00:23:28.720 that the uterine and vaginal microbiomes are 00:23:28.720 --> 00:23:31.559 different. They found only about 20 % overlap 00:23:31.559 --> 00:23:33.819 in the bacteria. Meaning you need targeted approaches, 00:23:34.000 --> 00:23:36.279 not a generic fix. Precisely. You need to address 00:23:36.279 --> 00:23:38.960 the specific microbial needs of each area. It's 00:23:38.960 --> 00:23:40.700 clear that managing these reproductive microbes 00:23:40.700 --> 00:23:43.240 offers some really solid benefits. Health and 00:23:43.240 --> 00:23:46.049 economics. And the exciting part, as the Bullvine 00:23:46.049 --> 00:23:48.210 article points out, is this isn't just theory 00:23:48.210 --> 00:23:50.430 anymore. These applications are moving from the 00:23:50.430 --> 00:23:52.549 lab to the farm. Right. You mentioned ProPreg 00:23:52.549 --> 00:23:54.710 is actually available now. Yes. The article says 00:23:54.710 --> 00:23:56.849 it's in small -scale commercial sales in the 00:23:56.849 --> 00:23:59.730 U .S., with Canada coming soon. And it stresses 00:23:59.730 --> 00:24:02.190 again, this is precision -engineered, developed 00:24:02.190 --> 00:24:04.950 over a decade for this specific purpose based 00:24:04.950 --> 00:24:07.970 on the research, not just a generic probiotic. 00:24:08.009 --> 00:24:09.369 And it's not just about reproduction, right? 00:24:09.410 --> 00:24:12.009 Other areas, too. Correct. Research is pushing 00:24:12.009 --> 00:24:14.349 forward on other fronts like respiratory health 00:24:14.349 --> 00:24:17.549 in calves. The article mentions multi -species 00:24:17.549 --> 00:24:20.170 probiotic formulations showing promise. What 00:24:20.170 --> 00:24:21.910 kind of results are they seeing with calves? 00:24:22.190 --> 00:24:25.049 Improvements in average daily gain and, crucially, 00:24:25.230 --> 00:24:28.650 reducing bovine respiratory disease, BRD, by 00:24:28.650 --> 00:24:32.150 up to 40 % in some trials. 40 % reduction in 00:24:32.150 --> 00:24:35.990 BRD, given that BRD costs $150 - $200 per calf. 00:24:36.569 --> 00:24:39.130 That's another huge potential saving. Absolutely. 00:24:39.430 --> 00:24:42.069 And it represents that shift in thinking we talked 00:24:42.069 --> 00:24:44.289 about. Moving from just treating sick calves 00:24:44.289 --> 00:24:46.970 to proactively managing their microbial balance 00:24:46.970 --> 00:24:48.690 to prevent them from getting sick in the first 00:24:48.690 --> 00:24:51.190 place. targeting the root cause the dysbiosis 00:24:51.190 --> 00:24:54.910 before pathogens take hold exactly you restore 00:24:54.910 --> 00:24:57.809 the healthy balance before disease develops the 00:24:57.809 --> 00:25:00.369 article also touches on global competition here 00:25:00.369 --> 00:25:03.049 saying others might be ahead it does make that 00:25:03.049 --> 00:25:05.410 point suggesting that international competitors 00:25:05.410 --> 00:25:08.730 maybe european operations are already adopting 00:25:08.730 --> 00:25:11.329 these kinds of technologies and gaining an edge 00:25:11.329 --> 00:25:14.829 it frames it as a competitive landscape shift 00:25:14.829 --> 00:25:18.329 late adopters might struggle to keep up so getting 00:25:18.329 --> 00:25:22.099 in could provide a real lasting advantage. That's 00:25:22.099 --> 00:25:23.819 the implication. But the article is realistic 00:25:23.819 --> 00:25:26.140 too. It talks about implementation challenges. 00:25:26.160 --> 00:25:28.019 It's not just plug and play, right? Definitely 00:25:28.019 --> 00:25:30.480 not. That's a really important dose of reality. 00:25:30.759 --> 00:25:33.819 The biggest challenge, variability. Meaning? 00:25:33.980 --> 00:25:36.839 The microbiome is incredibly complex and unique 00:25:36.839 --> 00:25:39.920 to each situation. It varies hugely between individual 00:25:39.920 --> 00:25:42.920 cows, between farms, regions, seasons, management 00:25:42.920 --> 00:25:46.299 styles. What works perfectly in one herd might 00:25:46.299 --> 00:25:48.539 not work exactly the same way as somewhere else. 00:25:48.700 --> 00:25:51.400 Environment matters a lot. Grazing versus dry 00:25:51.400 --> 00:25:54.500 lot, for example. Huge impact. The article cites 00:25:54.500 --> 00:25:56.380 University of Alberta research showing different 00:25:56.380 --> 00:25:58.680 environments affect different microbial groups 00:25:58.680 --> 00:26:02.259 like bacteria versus archaea differently. So 00:26:02.259 --> 00:26:04.599 any intervention has to mesh with your specific 00:26:04.599 --> 00:26:08.720 farm, your feed, housing, genetics, water, everything. 00:26:09.000 --> 00:26:11.200 Uses that precision ag analogy again. Right. 00:26:11.579 --> 00:26:13.640 You don't use the same fertilizer rate everywhere. 00:26:14.640 --> 00:26:16.460 Microbiome interventions need customization, 00:26:16.920 --> 00:26:20.099 tailored to your farm specifics. And timing is 00:26:20.099 --> 00:26:22.700 critical too, starting early in life. Very much 00:26:22.700 --> 00:26:25.259 so. Microbiome development starts basically at 00:26:25.259 --> 00:26:27.680 birth, heavily influenced by mom and the environment, 00:26:27.859 --> 00:26:30.940 especially colostrum. Effective long -term strategies 00:26:30.940 --> 00:26:33.400 might need to begin pre -weaning, maybe even 00:26:33.400 --> 00:26:35.680 earlier. It requires a whole life cycle view. 00:26:36.119 --> 00:26:38.660 And the idea of a farm's microbial fingerprint. 00:26:39.019 --> 00:26:40.940 Yeah, research shows dairy facilities develop 00:26:40.940 --> 00:26:43.500 their own unique microbial signature in the environment. 00:26:44.160 --> 00:26:46.440 Understanding your farm's signature, what beneficial 00:26:46.440 --> 00:26:48.599 bugs are already there, what challenges exist, 00:26:48.819 --> 00:26:51.380 could be key to choosing and implementing the 00:26:51.380 --> 00:26:53.460 right interventions effectively. So you need 00:26:53.460 --> 00:26:55.359 to know your starting point, your farm's unique 00:26:55.359 --> 00:26:57.440 microbial landscape. It seems like that will 00:26:57.440 --> 00:26:59.859 be increasingly important. Looking ahead then, 00:26:59.980 --> 00:27:02.700 the Bullvine article seems pretty bullish, calling 00:27:02.700 --> 00:27:05.000 the next five years an accelerating revolution. 00:27:05.500 --> 00:27:08.380 Early adopters gain the edge. It's definitely 00:27:08.380 --> 00:27:10.839 painting a picture of rapid advancement. One 00:27:10.839 --> 00:27:14.019 exciting area is predictive modeling, using microbial 00:27:14.019 --> 00:27:16.299 profiles to pick winners. Yeah, imagine being 00:27:16.299 --> 00:27:19.500 able to analyze a heifer's rumen microbiome at 00:27:19.500 --> 00:27:22.259 weaning and get a reliable prediction of her 00:27:22.259 --> 00:27:26.289 lifetime feed, efficiency, health. maybe even 00:27:26.289 --> 00:27:28.970 repro success potentially more accurate than 00:27:28.970 --> 00:27:31.069 genomics alone the article suggests it could 00:27:31.069 --> 00:27:33.769 be it might give a clearer picture of realized 00:27:33.769 --> 00:27:36.349 potential factoring in that microbial component 00:27:36.349 --> 00:27:39.609 and the wsu research on heritability and causal 00:27:39.609 --> 00:27:42.559 effects Suggests we might be able to breed for 00:27:42.559 --> 00:27:45.319 better microbes too. Potentially, yes. Or at 00:27:45.319 --> 00:27:47.200 least breed animals whose genetics make them 00:27:47.200 --> 00:27:49.859 more receptive to establishing beneficial microbial 00:27:49.859 --> 00:27:52.740 communities. It opens up avenues for both external 00:27:52.740 --> 00:27:55.200 interventions and genetic selection working together. 00:27:55.480 --> 00:27:57.619 Then there's sustainability. Methane reduction. 00:27:57.960 --> 00:28:00.900 A huge area. University of Alberta research, 00:28:01.160 --> 00:28:03.519 mentioned again, showing specific rumen compositions 00:28:03.519 --> 00:28:06.220 are linked to lower methane output. With carbon 00:28:06.220 --> 00:28:09.980 credits potentially paying $15 .25. per ton that 00:28:09.980 --> 00:28:12.500 could be a whole new revenue stream for dairies 00:28:12.500 --> 00:28:15.140 exactly turning an environmental challenge into 00:28:15.140 --> 00:28:17.640 an economic opportunity through microbial management 00:28:17.640 --> 00:28:20.460 but the real power the article argues comes from 00:28:20.460 --> 00:28:23.200 convergence integrating microbiome data with 00:28:23.200 --> 00:28:25.500 all the precision ag tech we already have this 00:28:25.500 --> 00:28:28.319 is a key point activity monitors robotic feeders 00:28:28.319 --> 00:28:31.599 and milkers sensors farms are swimming in data 00:28:32.000 --> 00:28:34.859 Adding microbiome data into that mix, the article 00:28:34.859 --> 00:28:37.359 suggests, could boost the predictive power of 00:28:37.359 --> 00:28:40.119 those systems by 30 -40%. Give us some examples 00:28:40.119 --> 00:28:42.400 of how that might work. Activity monitors plus 00:28:42.400 --> 00:28:44.950 repro microbes. Could dramatically improve heat 00:28:44.950 --> 00:28:47.349 detection accuracy, sure, but maybe even predict 00:28:47.349 --> 00:28:49.710 conception likelihood for a specific breeding. 00:28:49.970 --> 00:28:52.630 The article throws out a potential jump in first 00:28:52.630 --> 00:28:56.210 service conception from, say, 35 -40 % up to 00:28:56.210 --> 00:28:59.509 50 -55%. That's a game changer for repro efficiency. 00:28:59.890 --> 00:29:02.009 What about automated feeders in rumen microbes? 00:29:02.390 --> 00:29:04.829 Imagine tailoring the ration delivery not just 00:29:04.829 --> 00:29:08.289 to the cow's production level, but to her specific 00:29:08.289 --> 00:29:10.890 rumen microbiome's ability to utilize nutrients. 00:29:11.549 --> 00:29:15.190 Could boost efficiency? cut feed costs, and potentially 00:29:15.190 --> 00:29:17.549 reduce nutrient excretion nitrogen phosphorus 00:29:17.549 --> 00:29:21.589 by 15 -25%. Environmental benefits again, cost 00:29:21.589 --> 00:29:24.650 savings, and robotic milking data. Combine flow 00:29:24.650 --> 00:29:27.750 rate, conductivity, activity data from the robot 00:29:27.750 --> 00:29:31.289 with mammary microbiome analysis. You could potentially 00:29:31.289 --> 00:29:33.690 predict mastitis risk before any clinical signs 00:29:33.690 --> 00:29:36.609 show up. True predictive health management. So 00:29:36.609 --> 00:29:39.299 the future herd management software. It's not 00:29:39.299 --> 00:29:41.579 just tracking history. It's predicting the future 00:29:41.579 --> 00:29:44.200 based on integrating all this data, including 00:29:44.200 --> 00:29:46.259 microbes. That's the vision the article presents, 00:29:46.539 --> 00:29:48.700 and it feels like it's getting closer very quickly. 00:29:48.900 --> 00:29:51.019 The big question then is, are you, the listener, 00:29:51.180 --> 00:29:53.440 getting your operation ready to actually use 00:29:53.440 --> 00:29:55.180 this kind of integrated data when it arrives? 00:29:55.440 --> 00:29:57.740 A critical question for strategic planning. Which 00:29:57.740 --> 00:30:00.299 brings us back, kind of full circle, to challenging 00:30:00.299 --> 00:30:03.339 those industry norms. The sterile milk myth again. 00:30:03.579 --> 00:30:05.880 Yes, the article really hammers this point home 00:30:05.880 --> 00:30:07.920 because it represents such a fundamental mindset 00:30:07.920 --> 00:30:11.339 shift. Directly confronting that cleaner is always 00:30:11.339 --> 00:30:14.920 better dogma. And arguing with evidence that 00:30:14.920 --> 00:30:17.900 this relentless pursuit of sterility might actually 00:30:17.900 --> 00:30:21.099 be undermining utter health by killing off beneficial 00:30:21.099 --> 00:30:22.940 microbes. The ones that live in the environment 00:30:22.940 --> 00:30:25.220 too. The good bugs in the parlor or bedding. 00:30:25.299 --> 00:30:28.200 Exactly. Mapping shows these environments have 00:30:28.200 --> 00:30:30.599 complex beneficial communities that can help 00:30:30.599 --> 00:30:33.500 suppress pathogens naturally just by being there. 00:30:33.680 --> 00:30:36.859 Our scorched earth sanitizing destroys that protective 00:30:36.859 --> 00:30:39.759 ecosystem. So the evidence recap. Healthy udders 00:30:39.759 --> 00:30:43.230 have bacteria. Diverse bacteria. Mastitis milk 00:30:43.230 --> 00:30:45.509 has less diversity. Right. The argument being 00:30:45.509 --> 00:30:47.630 we've been measuring the wrong thing, absence 00:30:47.630 --> 00:30:50.029 of bugs, instead of the presence of a healthy, 00:30:50.089 --> 00:30:52.349 balanced community. Which has huge practical 00:30:52.349 --> 00:30:55.349 implications. Rethinking sanitizers, maybe antibiotic 00:30:55.349 --> 00:30:58.490 use, actively promoting good bugs. And the article 00:30:58.490 --> 00:31:00.809 mentions some farms are already experimenting 00:31:00.809 --> 00:31:03.630 with selective sanitization, targeting pathogens 00:31:03.630 --> 00:31:06.049 while preserving beneficials. It ends that section 00:31:06.049 --> 00:31:08.289 with a challenge, doesn't it? Are you brave enough 00:31:08.289 --> 00:31:10.809 to question the dogma? Pretty much. Stating that 00:31:10.809 --> 00:31:13.380 those who are... Those who embrace the evidence 00:31:13.380 --> 00:31:15.980 will gain the competitive edge. So let's get 00:31:15.980 --> 00:31:18.259 to the bottom line, the economic reality. Okay. 00:31:18.380 --> 00:31:21.099 The article frames today's dairy climate volatile 00:31:21.099 --> 00:31:24.779 markets, high costs as a pivotal moment. Efficiency 00:31:24.779 --> 00:31:27.099 isn't just nice, it's critical for survival. 00:31:27.400 --> 00:31:29.619 And while competitors chase small gains elsewhere. 00:31:29.980 --> 00:31:32.880 Embracing microbiome science now offers potentially 00:31:32.880 --> 00:31:35.140 transformative advantages that could last for 00:31:35.140 --> 00:31:39.230 decades. The research is clear. Very fine. The 00:31:39.230 --> 00:31:42.210 article is emphatic on this. Multiple universities, 00:31:42.529 --> 00:31:45.950 consistent findings. It works. And the documented 00:31:45.950 --> 00:31:48.450 results we've talked about, feed efficiency gains, 00:31:48.750 --> 00:31:52.390 50 % fewer repro issues, four, six liters more 00:31:52.390 --> 00:31:55.210 milk. These are real, not theoretical. Correct. 00:31:55.250 --> 00:31:57.529 And it reframes it nicely. You're not adding 00:31:57.529 --> 00:31:59.990 some complex new tech. You're finally managing 00:31:59.990 --> 00:32:02.549 the workforce already inside your cows. They're 00:32:02.549 --> 00:32:04.609 there anyway. Are you going to manage them? And 00:32:04.609 --> 00:32:07.970 with global pressures intensifying. The window 00:32:07.970 --> 00:32:10.450 to act is now, the next 18 months. That's the 00:32:10.450 --> 00:32:12.650 time frame suggested for early adopters to really 00:32:12.650 --> 00:32:15.529 cement an advantage. Then the ROI. The potential 00:32:15.529 --> 00:32:18.210 numbers are just compelling. Over $500 per cow 00:32:18.210 --> 00:32:21.049 annually. That's the potential aggregate benefit 00:32:21.049 --> 00:32:23.829 calculated in the article, compared to implementation 00:32:23.829 --> 00:32:27.390 costs potentially under $25 per cow for targeted 00:32:27.390 --> 00:32:30.069 interventions. Let's quickly recap that 100 -cow 00:32:30.069 --> 00:32:32.589 herd breakdown from the article's table. Feed 00:32:32.589 --> 00:32:36.390 efficiency. Worth potentially $37 ,500 a year. 00:32:38.039 --> 00:32:40.920 $375. High impact. ReproHealth. Estimated at 00:32:40.920 --> 00:32:45.599 $8 ,500 a year. 85 cow. Also high impact. Mastitis 00:32:45.599 --> 00:32:48.619 reduction. Calculated at $6 ,000 a year. 60 cow. 00:32:48.839 --> 00:32:52.819 Medium impact. Totally. $52 ,000 a year or $520 00:32:52.819 --> 00:32:55.119 per cow. Just from those three in the table. 00:32:55.240 --> 00:32:57.660 Very high impact. Plus the extra milk revenue 00:32:57.660 --> 00:32:59.980 on top of that. Right. The $8 ,000, $12 ,000 00:32:59.980 --> 00:33:02.079 from the extra four or six liters per day. It 00:33:02.079 --> 00:33:04.359 really adds up. And don't forget preventing culling. 00:33:04.640 --> 00:33:06.839 Saving just one cow from being called for repro 00:33:06.839 --> 00:33:09.619 failure with maybe $2 ,000 pays for a lot of 00:33:09.619 --> 00:33:11.819 intervention. It makes a very strong economic 00:33:11.819 --> 00:33:14.460 case. So how does a producer start? What's the 00:33:14.460 --> 00:33:17.059 roadmap? The Bullvine article lays out a practical 00:33:17.059 --> 00:33:20.240 18 -month phased approach based on early adopter 00:33:20.240 --> 00:33:22.039 experience. Okay, phase one, months one, three. 00:33:22.380 --> 00:33:24.740 Assessment and education. Talk to your vet, your 00:33:24.740 --> 00:33:27.420 nutritionist. Dive into your own data SEC, repro 00:33:27.420 --> 00:33:29.819 records, feed efficiency. Benchmark yourself. 00:33:30.099 --> 00:33:32.259 See where your biggest opportunities or challenges 00:33:32.259 --> 00:33:36.230 lie. Cost. Minimal. Mostly your time. Phase 2. 00:33:37.690 --> 00:33:41.589 Months 4 to 9. Pilot testing. Try a proven intervention, 00:33:41.910 --> 00:33:44.210 like ProPreg, which the article highlights, on 00:33:44.210 --> 00:33:48.069 a smaller group. 25 -50 animals, maybe? Keep 00:33:48.069 --> 00:33:51.170 meticulous records. What's the cost? Under $25 00:33:51.170 --> 00:33:53.250 per cow for the intervention itself, potentially 00:33:53.250 --> 00:33:55.809 payback. Could be just 4 -6 months, based on 00:33:55.809 --> 00:33:57.970 the results we discussed. And Phase 3. Months 00:33:57.970 --> 00:34:01.019 10 -18. Monitoring and optimization. If the pilot 00:34:01.019 --> 00:34:04.519 works, maybe expand. Track KPIs herd -wide. Refine 00:34:04.519 --> 00:34:06.680 your protocols. Use your precision ag tools, 00:34:06.859 --> 00:34:09.119 monitors, feeders, meters, to quantify the benefits 00:34:09.119 --> 00:34:11.420 accurately. And the key success factor throughout. 00:34:11.760 --> 00:34:13.840 Tailor it to your farm. Account for your unique 00:34:13.840 --> 00:34:16.179 microbial signature, your feed, your environment. 00:34:16.460 --> 00:34:18.519 Don't just copy and paste a generic protocol. 00:34:19.300 --> 00:34:21.400 Customize. So the article really brings it back 00:34:21.400 --> 00:34:23.719 to the producer. Lead or follow, this microbial 00:34:23.719 --> 00:34:26.380 workforce is ready. Your cows and your bank account 00:34:26.380 --> 00:34:28.300 are waiting for your decision. And the final 00:34:28.300 --> 00:34:31.260 actionable steps. Talk to your vet about assessment. 00:34:31.579 --> 00:34:34.139 Review your sanitization protocols critically. 00:34:34.639 --> 00:34:37.079 And run the numbers, calculate your potential 00:34:37.079 --> 00:34:40.440 ROI using the frameworks from the article. See 00:34:40.440 --> 00:34:42.260 what it could mean for your specific operation. 00:34:42.539 --> 00:34:45.739 Exactly. The article argues this revolution starts 00:34:45.739 --> 00:34:48.280 with individual producers embracing the science 00:34:48.280 --> 00:34:51.239 and innovating. So the final thought to leave 00:34:51.239 --> 00:34:53.820 everyone with, drawing from the article. You've 00:34:53.820 --> 00:34:55.960 managed the cow you can see, the feed you can 00:34:55.960 --> 00:34:58.559 weigh, the milk you can measure for years. But 00:34:58.559 --> 00:35:00.699 future profitability might hinge on managing 00:35:00.699 --> 00:35:02.960 these microscopic workers you've barely met. 00:35:03.380 --> 00:35:05.260 Isn't it a time you were properly introduced? 00:35:05.659 --> 00:35:07.860 It certainly seems like the time is now. That's 00:35:07.860 --> 00:35:10.380 all for this deep dive. The evidence is overwhelming, 00:35:10.539 --> 00:35:13.760 and the economics are compelling. Microbiome 00:35:13.760 --> 00:35:16.019 optimization isn't some theoretical breakthrough. 00:35:16.360 --> 00:35:19.150 It's happening right now. with documented results 00:35:19.150 --> 00:35:22.869 and verified ROI. The question isn't whether 00:35:22.869 --> 00:35:25.150 this revolution will transform dairy farming. 00:35:25.309 --> 00:35:27.530 The question is whether you'll be leading it 00:35:27.530 --> 00:35:30.650 or following it. Your action plan is simple. 00:35:30.889 --> 00:35:34.309 Start with Phase 1 assessment this month. Work 00:35:34.309 --> 00:35:36.929 with your veterinarian and nutritionist to identify 00:35:36.929 --> 00:35:40.230 intervention opportunities. Begin pilot testing 00:35:40.230 --> 00:35:44.090 proven solutions within 90 days. Remember, your 00:35:44.090 --> 00:35:46.690 cow's microscopic workforce is already there. 00:35:47.070 --> 00:35:50.269 whether you manage them or not. The producers 00:35:50.269 --> 00:35:52.730 who put these tiny workers to work will establish 00:35:52.730 --> 00:35:55.070 competitive advantages that their neighbors will 00:35:55.070 --> 00:35:58.250 struggle to match. Don't let another day pass 00:35:58.250 --> 00:36:01.469 managing only half your operation. This has been 00:36:01.469 --> 00:36:03.469 the Bullvine Podcast reminding you that your 00:36:03.469 --> 00:36:05.730 future profitability may depend on microscopic 00:36:05.730 --> 00:36:09.070 workers you've never met. Isn't it time you were 00:36:09.070 --> 00:36:14.139 properly introduced? Visit www. thebullvine .com 00:36:14.139 --> 00:36:17.380 for the complete implementation guide, ROI calculators, 00:36:17.440 --> 00:36:20.059 and links to all the research we discussed today. 00:36:20.679 --> 00:36:23.980 Until next time, keep challenging the conventional 00:36:23.980 --> 00:36:26.460 and keep building your competitive edge.