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 --> 00:01:03.570 we're sparking Welcome back to the Bullvine Podcast, 00:01:03.770 --> 00:01:05.750 where we cut through the dairy industry noise 00:01:05.750 --> 00:01:07.989 to get you the insights that actually matter 00:01:07.989 --> 00:01:10.930 for your operation. And today, we're diving deep 00:01:10.930 --> 00:01:14.409 into a feature piece. It's called Precision Transition, 00:01:14.450 --> 00:01:18.230 the new economics of ketosis management. Honestly, 00:01:18.310 --> 00:01:21.069 looking at the research pile we have for this 00:01:21.069 --> 00:01:23.810 one, this isn't just a gentle nudge to tweak 00:01:23.810 --> 00:01:26.189 a protocol. No. This is going to ruffle some 00:01:26.189 --> 00:01:29.629 serious feathers. We are taking a hard look at 00:01:29.629 --> 00:01:32.750 that sacred cow of fresh cow protocols, the 1 00:01:32.750 --> 00:01:36.469 .2 BHB cut point. Yeah, ruffle feathers is probably 00:01:36.469 --> 00:01:40.599 putting it mildly. For years, for decades really, 00:01:40.780 --> 00:01:43.200 the golden rule in that fresh pen has been so 00:01:43.200 --> 00:01:45.519 simple. It's automatic. It's total muscle memory 00:01:45.519 --> 00:01:48.000 for most of us producers. You see a fresh cow, 00:01:48.219 --> 00:01:50.799 you prick her ear, the meter says 1 .2 or higher, 00:01:50.920 --> 00:01:53.620 and bam, you reach for the drench gun. She gets 00:01:53.620 --> 00:01:55.859 the propylene glycol. Every time. Yeah. It's 00:01:55.859 --> 00:01:58.140 just, it's what you do. And now you're telling 00:01:58.140 --> 00:02:00.819 me that this article and the data behind it is 00:02:00.819 --> 00:02:03.760 suggesting we just stop. That we rethink it, 00:02:03.799 --> 00:02:06.400 yeah. Because to me, honestly, that sounds like 00:02:06.400 --> 00:02:08.960 a recipe for a complete train wreck. It sounds 00:02:08.960 --> 00:02:11.159 totally counterintuitive, right? It feels like 00:02:11.159 --> 00:02:13.379 walking a tightrope without a net. But here's 00:02:13.379 --> 00:02:16.719 the thing. The data is suggesting that the blanket 00:02:16.719 --> 00:02:20.479 rule that treat everyone over 1 .2 rule is actually 00:02:20.479 --> 00:02:24.000 costing you more money than the propylene glycol 00:02:24.000 --> 00:02:29.259 itself. More how? We aren't saying ignore ketosis. 00:02:29.280 --> 00:02:31.319 We are not saying it isn't real. What we're saying 00:02:31.319 --> 00:02:33.580 is that treating every single cow that hits that 00:02:33.580 --> 00:02:37.180 number is outdated. It's expensive. Okay. And 00:02:37.180 --> 00:02:40.319 it is potentially harming your operation's efficiency. 00:02:40.960 --> 00:02:43.000 Harming efficiency. Now, that's the part I'm 00:02:43.000 --> 00:02:44.539 struggling with. I thought treating them was 00:02:44.539 --> 00:02:46.319 saving money. I thought we were catching them 00:02:46.319 --> 00:02:48.620 before they crashed. Right. The whole point of 00:02:48.620 --> 00:02:50.919 the fresh cow protocol is prevention, isn't it? 00:02:51.000 --> 00:02:53.120 You know, we catch the smoke before the fire. 00:02:53.259 --> 00:02:55.780 That is the hook. That is the assumption we all 00:02:55.780 --> 00:02:58.060 operate on. But when you actually run the numbers. 00:02:58.139 --> 00:03:00.439 Okay. And I mean, really dig into the economic 00:03:00.439 --> 00:03:04.479 modeling. In a standard 500 cow Holstein freestall, 00:03:04.539 --> 00:03:07.020 sticking to that old blanket rule is likely leaking 00:03:07.020 --> 00:03:11.379 anywhere from $25 ,000 to $35 ,000 a year. Wait, 00:03:11.580 --> 00:03:14.659 hold on. $25 ,000 to $35 ,000. Just from following 00:03:14.659 --> 00:03:17.000 the standard protocol. The one everybody recommends. 00:03:17.259 --> 00:03:20.580 Just from that one decision point. I mean, that's 00:03:20.580 --> 00:03:22.840 the price of a decent used pickup truck. That's 00:03:22.840 --> 00:03:25.740 a whole lot of semen. It's real money. And it's 00:03:25.740 --> 00:03:27.919 from the leak. That is what we need to unpack 00:03:27.919 --> 00:03:30.680 today. Because the latest data says we are systematically 00:03:30.680 --> 00:03:34.759 overdosing healthy cows and, ironically, potentially 00:03:34.759 --> 00:03:36.879 undermanaging the sick ones because we're too 00:03:36.879 --> 00:03:39.180 busy chasing numbers. So we're focused on the 00:03:39.180 --> 00:03:42.319 wrong thing. Exactly. The controversy here is 00:03:42.319 --> 00:03:45.139 that the number 1 .2 isn't a diagnosis. It's 00:03:45.139 --> 00:03:48.560 just a risk marker. And treating a risk marker 00:03:48.560 --> 00:03:51.580 like a confirmed disease is where the money starts 00:03:51.580 --> 00:03:54.500 disappearing. Okay, that is a bold claim. Leaking 00:03:54.500 --> 00:03:57.060 30 grand is enough to get my attention, and I'm 00:03:57.060 --> 00:03:58.800 sure everyone listening just turned the volume 00:03:58.800 --> 00:04:00.659 up. It should have. So let's get into it. Walk 00:04:00.659 --> 00:04:02.740 me through this. How in the world do we get to 00:04:02.740 --> 00:04:04.379 that number? Well, let's start with the morning 00:04:04.379 --> 00:04:07.620 routine. You know it well. Paint the picture 00:04:07.620 --> 00:04:10.080 for me. What does that look like on your place? 00:04:10.319 --> 00:04:12.319 Oh, absolutely. It's, what, 5, 1 point a .m.? 00:04:12.319 --> 00:04:14.639 Coffee is still hot in the travel mug. You're 00:04:14.639 --> 00:04:16.939 in the fresh pen. Right. You've got your lockups 00:04:16.939 --> 00:04:19.000 full. You go down the line with that ketone meter. 00:04:19.379 --> 00:04:22.939 You prick the ear. Beep. 1 .3. Drench. Boom. 00:04:23.040 --> 00:04:25.500 She gets drenched. Next one. Beep. 1 .1. Okay. 00:04:25.540 --> 00:04:29.360 She's safe. Move on. Next one. Beep. 1 .4. Drench 00:04:29.360 --> 00:04:32.019 again. Drench again. It's binary. It's totally 00:04:32.019 --> 00:04:33.639 black and white. You don't really think about 00:04:33.639 --> 00:04:35.579 it. You just do it. Because that's the protocol. 00:04:35.800 --> 00:04:37.819 Because that's what the VET protocol says. It's 00:04:37.819 --> 00:04:40.100 efficient, or at least, you know, it feels efficient. 00:04:40.379 --> 00:04:42.379 It feels efficient because it's decisive. You 00:04:42.379 --> 00:04:45.420 feel like you're doing something, but that binary 00:04:45.420 --> 00:04:48.920 approach is the problem. Let's look at the economic 00:04:48.920 --> 00:04:52.600 reality of what a case of subclinical ketosis, 00:04:52.600 --> 00:04:56.339 or SCK, actually costs. Right. Because it's not 00:04:56.339 --> 00:04:58.420 just the five bucks for the glycol or the labor 00:04:58.420 --> 00:05:00.899 to drench her. Right, right. It's the lost milk, 00:05:00.920 --> 00:05:02.680 the breeding issues down the road. It's all the 00:05:02.680 --> 00:05:05.220 invisible stuff. Correct. So there was a major 00:05:05.220 --> 00:05:07.360 Canadian model. This came out of the University 00:05:07.360 --> 00:05:10.740 of Guelph back in 2016. I think I remember hearing 00:05:10.740 --> 00:05:13.279 about that one. They looked at real herd data, 00:05:13.500 --> 00:05:17.240 thousands of cows, and they pegged the cost of 00:05:17.240 --> 00:05:21.980 a single SEK case at about $203 Canadian dollars. 00:05:22.389 --> 00:05:24.930 So 200 bucks, basically. Roughly. And that includes 00:05:24.930 --> 00:05:28.269 the lost milk, the increased risk of other diseases 00:05:28.269 --> 00:05:30.850 like metritis, the fertility hits. Like extra 00:05:30.850 --> 00:05:32.910 days open and that kind of thing. Exactly. And 00:05:32.910 --> 00:05:35.689 the risk of her being cold early. OK, so roughly 00:05:35.689 --> 00:05:39.250 200 bucks a cow if she's subclinical. That hurts. 00:05:39.509 --> 00:05:42.930 But I mean, it feels manageable. It does. But 00:05:42.930 --> 00:05:44.870 then if you look at the U .S. model, this one 00:05:44.870 --> 00:05:47.230 was developed by a team, including Dr. Christopher 00:05:47.230 --> 00:05:50.170 McCart at Cornell. A big name in this space. 00:05:50.350 --> 00:05:53.490 A very big name. Their model for early lactation 00:05:53.490 --> 00:05:56.089 hyperketonemia, which is just the fancy term 00:05:56.089 --> 00:05:59.129 for high BHB in the first couple weeks, they 00:05:59.129 --> 00:06:02.490 put the cost at around $289 U .S. dollars per 00:06:02.490 --> 00:06:05.910 case. Wow. Okay, so almost $300. Why is the U 00:06:05.910 --> 00:06:08.170 .S. number so much higher? Is that just the currency 00:06:08.170 --> 00:06:10.329 exchange, or are they counting something the 00:06:10.329 --> 00:06:12.910 Canadians missed? It's not just exchange rates. 00:06:13.050 --> 00:06:16.069 The U .S. model, it explicitly includes the downstream 00:06:16.069 --> 00:06:19.550 costs of metritis and displaced abomasum DAs. 00:06:19.589 --> 00:06:21.629 Ah, so they're connecting the dots. Exactly. 00:06:21.709 --> 00:06:24.149 They factor in the probability that a cow with 00:06:24.149 --> 00:06:26.790 high ketones is way more likely to end up with 00:06:26.790 --> 00:06:30.230 a twisted stomach or a uterine infection. So, 00:06:30.230 --> 00:06:32.910 you know, whether you use the Canadian math or 00:06:32.910 --> 00:06:34.990 the American math, you are looking at a massive 00:06:34.990 --> 00:06:39.670 cost per case. A huge cost. Now, do the prevalence 00:06:39.670 --> 00:06:41.870 math with me. Okay, I've got my mental calculator 00:06:41.870 --> 00:06:44.490 out. Go ahead. Global surveys, and we're talking 00:06:44.490 --> 00:06:47.949 nearly 9 ,000 cows across 12 different countries. 00:06:47.970 --> 00:06:50.389 So these are big data sets. They show that the 00:06:50.389 --> 00:06:54.430 average SCK prevalence using that 1 .2 cut point, 00:06:54.569 --> 00:06:58.870 it's about 24 .1%. So basically one in four fresh 00:06:58.870 --> 00:07:02.089 cows. Roughly. In a 500 cow herd, that's 125 00:07:02.089 --> 00:07:05.829 cows a year. Okay, so let me do that math. 125 00:07:05.829 --> 00:07:09.350 cows times. Yeah. Let's be conservative. Say 00:07:09.350 --> 00:07:13.009 200 bucks. That's $25 ,000 right there. If you 00:07:13.009 --> 00:07:15.509 use that Cornell number, the almost 300, you're 00:07:15.509 --> 00:07:18.769 pushing $36 ,000. Exactly. That is the money 00:07:18.769 --> 00:07:21.069 you are losing to this disease complex. That 00:07:21.069 --> 00:07:23.649 is real money walking out of the checkbook. Okay. 00:07:23.670 --> 00:07:25.430 Let me play devil's advocate here for a second. 00:07:26.009 --> 00:07:28.389 If one in four cows has it and the global average 00:07:28.389 --> 00:07:32.839 is 24%, isn't that just normal? Ah, the normal 00:07:32.839 --> 00:07:35.160 question. I mean, seriously, maybe that's just 00:07:35.160 --> 00:07:37.360 what high producing Holsteins do. Maybe that's 00:07:37.360 --> 00:07:39.480 the tax we pay for making 100 pounds of milk 00:07:39.480 --> 00:07:42.540 a day. It is common, but it absolutely shouldn't 00:07:42.540 --> 00:07:45.300 be accepted as normal. That mindset is the leak. 00:07:45.459 --> 00:07:48.779 How so? Because if you can cut that prevalence 00:07:48.779 --> 00:07:53.060 from 25 % down to say... 15%, which is very, 00:07:53.160 --> 00:07:56.120 very doable. Okay. You are saving $10 ,000 to 00:07:56.120 --> 00:07:59.459 $15 ,000 immediately. That is pure profit you 00:07:59.459 --> 00:08:01.639 are leaving on the table by just shrugging your 00:08:01.639 --> 00:08:04.319 shoulders and accepting 25 % is just what happens. 00:08:04.399 --> 00:08:05.620 Okay. I see where you're going. You're saying 00:08:05.620 --> 00:08:07.060 we're too comfortable with the prevalence, but 00:08:07.060 --> 00:08:11.939 how does changing the 1 .2 rule help lower that? 00:08:12.180 --> 00:08:14.360 That's the key question. I mean, isn't testing 00:08:14.360 --> 00:08:16.620 and treating how we manage it? If I stop treating 00:08:16.620 --> 00:08:19.600 the cows over 1 .2, aren't I just ignoring the 00:08:19.600 --> 00:08:21.800 problem and letting it get worse? Testing and 00:08:21.800 --> 00:08:23.939 treating is how you put a bandaid on it. It doesn't 00:08:23.939 --> 00:08:26.860 stop the leak. And more importantly, the 1 .2 00:08:26.860 --> 00:08:30.180 line itself is completely misunderstood. We need 00:08:30.180 --> 00:08:32.480 to do a reality check on where that number even 00:08:32.480 --> 00:08:34.620 came from. Yeah, where did it come from? It feels 00:08:34.620 --> 00:08:36.720 like it just appeared on a stone tablet one day. 00:08:36.820 --> 00:08:38.820 It really does, but it came from smart people 00:08:38.820 --> 00:08:40.440 in white coats at universities. You're right 00:08:40.440 --> 00:08:42.860 about that. Okay. Over the last two decades, 00:08:43.059 --> 00:08:45.779 researchers linked blood BHB levels to the things 00:08:45.779 --> 00:08:50.690 we hate. right da's retained placentas all the 00:08:50.690 --> 00:08:53.190 fresh cow disasters all of them and they found 00:08:53.190 --> 00:08:56.039 that these cut points Somewhere in the 1 .2 to 00:08:56.039 --> 00:08:59.980 1 .4 range were a solid tripwire. They correlated 00:08:59.980 --> 00:09:02.460 really well with herd level risk. Right. So if 00:09:02.460 --> 00:09:04.820 the whole herd is running high, you've got a 00:09:04.820 --> 00:09:06.799 systemic problem. The alarm bill is going off. 00:09:06.860 --> 00:09:09.659 Precisely. It was designed to describe herd level 00:09:09.659 --> 00:09:12.779 risk. It acts like a smoke alarm. If 30 or 40 00:09:12.779 --> 00:09:16.019 percent of your fresh cows are over 1 .2, your 00:09:16.019 --> 00:09:18.440 transition program is on fire. Right. But it 00:09:18.440 --> 00:09:20.860 was never intended to dictate that every single 00:09:20.860 --> 00:09:23.980 individual cow who touches 1 .2 is sick and needs 00:09:23.980 --> 00:09:27.690 help. But wait a minute. If she's over 1 .2, 00:09:27.850 --> 00:09:30.649 she is physiologically under stress, isn't she? 00:09:30.769 --> 00:09:33.330 I mean, her body is mobilizing fat. That's what 00:09:33.330 --> 00:09:35.409 ketones are, right? A byproduct of burning fat. 00:09:35.570 --> 00:09:38.190 She is mobilizing fat, yes. But here is where 00:09:38.190 --> 00:09:41.250 the physiology update comes in. The 2024 reviews 00:09:41.250 --> 00:09:45.389 and these multiomics papers where they look at 00:09:45.389 --> 00:09:48.080 every single metabolite in the blood. Wow, okay. 00:09:48.159 --> 00:09:51.179 They show that truly, clinically, ketotic cows 00:09:51.179 --> 00:09:55.100 have a distinct fingerprint. They have high nifer, 00:09:55.340 --> 00:09:58.120 non -asperified fatty acids. They have high liver 00:09:58.120 --> 00:10:00.220 fat, and they have high inflammation markers. 00:10:00.559 --> 00:10:02.519 Okay, so their whole system is chemically a mess. 00:10:02.600 --> 00:10:05.840 They're on fire internally. Right, but, and this 00:10:05.840 --> 00:10:09.399 is the absolute key, a cow can hit 1 .3 on the 00:10:09.399 --> 00:10:12.039 meter without having that full toxic fingerprint. 00:10:12.799 --> 00:10:15.379 The number 1 .2 means something completely different 00:10:15.379 --> 00:10:17.559 depending on the cow's context. Context. Okay, 00:10:17.620 --> 00:10:19.039 that's a word consultants love to use. Give me 00:10:19.039 --> 00:10:20.860 a real world example. What do you mean by context? 00:10:20.980 --> 00:10:23.320 Because when I'm in the barn at 5 a .m., a number 00:10:23.320 --> 00:10:24.840 is a number. Let's play a game then. I'm going 00:10:24.840 --> 00:10:26.259 to give you two cows. We'll call it the tale 00:10:26.259 --> 00:10:28.320 of two cows. All right, hit me. I'm ready. Both 00:10:28.320 --> 00:10:32.539 of them this morning read exactly 1 .3 millimolel 00:10:32.539 --> 00:10:34.980 on your meter. You have the drench gun in your 00:10:34.980 --> 00:10:37.000 hand. You tell me if you treat them. Okay, 1 00:10:37.000 --> 00:10:41.700 .3. Got it. Cow A. She is day five in milk, fourth 00:10:41.700 --> 00:10:45.269 lactation. Oof. Okay, red flag number one. The 00:10:45.269 --> 00:10:48.330 old ones. She calved heavy. Let's say she was 00:10:48.330 --> 00:10:51.830 a body condition score of 3 .75 or even a 4 .0. 00:10:51.970 --> 00:10:54.669 Ugh, a fat cow. Red flag number two. And she 00:10:54.669 --> 00:10:57.269 has a history. She had a DA in her last lactation. 00:10:57.409 --> 00:10:59.309 Okay, that's three strikes. You look at her. 00:10:59.389 --> 00:11:02.029 Her rumen looks flat, kind of empty. She's hanging 00:11:02.029 --> 00:11:03.990 back at the bunk while the fresh feed is being 00:11:03.990 --> 00:11:07.289 dropped. The meter says 1 .3. What do you do? 00:11:07.509 --> 00:11:11.169 Oh, she gets the drench. Immediately. No question. 00:11:11.429 --> 00:11:13.210 Honestly, I might be calling the vet too. She 00:11:13.210 --> 00:11:15.690 looks like a walking disaster. Tell me why. What 00:11:15.690 --> 00:11:18.169 specifically worries you? Because day five is 00:11:18.169 --> 00:11:19.970 the danger zone. That's when everything goes 00:11:19.970 --> 00:11:22.769 wrong. She's old. She's fat, which means she's 00:11:22.769 --> 00:11:24.929 just melting that fat off rapidly because she 00:11:24.929 --> 00:11:27.490 has no appetite and she's not eating. That 1 00:11:27.490 --> 00:11:29.990 .3 is just the start. It's the tip of the iceberg. 00:11:30.289 --> 00:11:32.350 Exactly. She's going to be the 3 .0 or higher 00:11:32.350 --> 00:11:34.870 by tomorrow if I don't do something. She's crashing. 00:11:34.929 --> 00:11:36.990 And that number is my first warning sign. Bingo. 00:11:37.110 --> 00:11:41.809 You nailed it. For cow A, that 1 .3 is just the 00:11:41.809 --> 00:11:44.669 smoke. Neat the surface. She likely has fatty 00:11:44.669 --> 00:11:47.230 liver, oxidative stress, the whole nine yards. 00:11:47.370 --> 00:11:49.909 She's spiraling. Yeah. Immediate intervention 00:11:49.909 --> 00:11:52.409 is absolutely the right call. You save that cow. 00:11:52.610 --> 00:11:54.769 Okay. So the rule works for her. I'm with you 00:11:54.769 --> 00:11:57.750 so far. What's cow B? Cow B, she's day 15 in 00:11:57.750 --> 00:11:59.789 milk. Okay. So she's past that initial danger 00:11:59.789 --> 00:12:02.210 zone. Right. Second lactation. She calved at 00:12:02.210 --> 00:12:06.899 a perfect BCS, maybe a 3 .0 or a 3 .25. Clean 00:12:06.899 --> 00:12:09.559 history, no issues last year. It's like a good 00:12:09.559 --> 00:12:12.399 cow. You look at her, and she is aggressively 00:12:12.399 --> 00:12:14.980 eating. She's pushing other cows out of the way 00:12:14.980 --> 00:12:18.179 to get to the fresh feed. She is milking 95 pounds, 00:12:18.259 --> 00:12:21.240 and her components are sky -high lots of butterfat. 00:12:21.360 --> 00:12:23.240 She sounds like a moneymaker. The cow I want 00:12:23.240 --> 00:12:25.679 a whole herd of. But the meter says 1 .3, the 00:12:25.679 --> 00:12:29.519 protocol says drench. What do you do? Yeah, strictly 00:12:29.519 --> 00:12:31.519 speaking, the binder on the wall says I'm supposed 00:12:31.519 --> 00:12:34.850 to drench her. Yep. But my gut... My eyes, everything 00:12:34.850 --> 00:12:37.070 about being a cowman tells me she's fine. She's 00:12:37.070 --> 00:12:39.269 just working hard. Your gut is right. She is 00:12:39.269 --> 00:12:41.509 what the researchers call a high output adapter. 00:12:41.870 --> 00:12:44.769 A high output adapter. I like that. That 1 .3 00:12:44.769 --> 00:12:46.690 isn't a sign of sickness. It's just metabolic 00:12:46.690 --> 00:12:49.649 dust. She's driving a Ferrari engine. She is 00:12:49.649 --> 00:12:52.169 processing a massive amount of energy to make 00:12:52.169 --> 00:12:55.169 that 95 pounds of milk. The ketones are just 00:12:55.169 --> 00:12:57.529 a byproduct of high performance, not a sign of 00:12:57.529 --> 00:13:00.769 system failure. So if I grab her, wrestle her 00:13:00.769 --> 00:13:03.490 into the headlock. And force a drench down her. 00:13:03.669 --> 00:13:05.350 You're wasting your time, you're wasting money 00:13:05.350 --> 00:13:07.830 on the glycol, and you're disrupting a cow that 00:13:07.830 --> 00:13:10.490 is busy eating and making you milk. You are literally 00:13:10.490 --> 00:13:12.649 fixing a cow that isn't broken. And stressing 00:13:12.649 --> 00:13:15.110 her out for no reason. For no reason at all. 00:13:15.149 --> 00:13:17.049 So that's the leak you're talking about. The 00:13:17.049 --> 00:13:19.730 labor, the stress of locking her up, the cost 00:13:19.730 --> 00:13:21.830 of the product, and the fact that I'm spending 00:13:21.830 --> 00:13:23.690 five minutes on her when I should be spending 00:13:23.690 --> 00:13:27.000 ten minutes on Coway. Exactly. You hit it. Treating 00:13:27.000 --> 00:13:29.480 Calbee is a waste of resources. Treating Coway 00:13:29.480 --> 00:13:32.620 is a rescue mission. But the 1 .2 blanket rule 00:13:32.620 --> 00:13:35.259 treats them exactly the same. That's a massive 00:13:35.259 --> 00:13:38.299 distinction. But is there actual data to back 00:13:38.299 --> 00:13:40.620 up that Calbee is fine? Because I can hear some 00:13:40.620 --> 00:13:42.360 people listening right now saying, better safe 00:13:42.360 --> 00:13:44.720 than sorry. Of course. You know, what if Calbee 00:13:44.720 --> 00:13:47.159 is just about to crash and I miss it? There is 00:13:47.159 --> 00:13:49.340 data, and some of it is pretty surprising, actually. 00:13:49.519 --> 00:13:53.220 There was a big study out of Derry and Zee in 00:13:53.220 --> 00:13:55.100 New Zealand. Okay, pasture -based, right? It 00:13:55.100 --> 00:13:56.879 was a pasture study, yeah. So we have to translate 00:13:56.879 --> 00:13:58.600 a bit for our team our words, but the underlying 00:13:58.600 --> 00:14:01.799 physiology holds up. They followed nearly a thousand 00:14:01.799 --> 00:14:05.000 cows. A good -sized group. What did they find? 00:14:05.200 --> 00:14:08.399 They found that the cows with at least one test 00:14:08.399 --> 00:14:12.779 over 1 .2 millimole actually produced 4 % more 00:14:12.779 --> 00:14:15.580 milk solids in the first 15 weeks than the cows 00:14:15.580 --> 00:14:18.039 that stayed low the whole time. Wait, back up. 00:14:18.080 --> 00:14:20.259 Did you just say the ketotic cows made more milk? 00:14:20.419 --> 00:14:23.019 The moderate ketotic cows, yes. The ones in that 00:14:23.019 --> 00:14:26.200 1 .2 to 2 .9 range. That makes no sense. How 00:14:26.200 --> 00:14:28.100 is that possible? Because think about it from 00:14:28.100 --> 00:14:31.500 a biological standpoint. Ketones are fuel. They 00:14:31.500 --> 00:14:34.559 are energy. In a healthy, high -producing cow, 00:14:34.679 --> 00:14:36.580 seeing some ketones means she is successfully 00:14:36.580 --> 00:14:39.460 mobilizing her body tissue to support high milk 00:14:39.460 --> 00:14:41.779 production. It's an expected part of the process. 00:14:42.179 --> 00:14:44.779 So we've been demonizing a fuel source. We've 00:14:44.779 --> 00:14:46.879 been treating the gas in the tank like it's water 00:14:46.879 --> 00:14:49.659 in the oil. To an extent, for some cows, yes. 00:14:49.860 --> 00:14:52.059 The study also showed that when they took these 00:14:52.059 --> 00:14:56.490 moderate healthy cows, just showing some numbers 00:14:56.490 --> 00:14:58.769 on the meter, and they treated them with propylene 00:14:58.769 --> 00:15:01.909 glycol, they saw no consistent improvement in 00:15:01.909 --> 00:15:05.009 milk or reproduction. None. So drenching them 00:15:05.009 --> 00:15:07.509 did absolutely nothing for performance. It lowered 00:15:07.509 --> 00:15:09.809 the ketones, sure. The number on the meter went 00:15:09.809 --> 00:15:12.129 down, so you felt like you fixed it. Right. You 00:15:12.129 --> 00:15:13.889 get the satisfaction of seeing the number change. 00:15:14.230 --> 00:15:15.629 But it didn't make them give more milk, and it 00:15:15.629 --> 00:15:17.409 didn't make them get pregnant any faster. So 00:15:17.409 --> 00:15:19.490 from an economic standpoint, the treatment had 00:15:19.490 --> 00:15:23.129 zero ROI. That is the literal definition of burning 00:15:23.129 --> 00:15:26.470 money. You're paying to fix a number on a screen, 00:15:26.570 --> 00:15:30.549 not to improve the actual cow. Precisely. Ketones 00:15:30.549 --> 00:15:33.789 are signaling molecules, not just toxins. In 00:15:33.789 --> 00:15:36.590 a healthy eating cow, especially one past day, 00:15:37.110 --> 00:15:39.929 10 moderate ketones, often just means she is 00:15:39.929 --> 00:15:42.950 working her tail off for you. Okay, so I'm sold 00:15:42.950 --> 00:15:45.330 on the concept. The biology makes sense. But 00:15:45.330 --> 00:15:47.610 practically speaking, I can't have my herdsman 00:15:47.610 --> 00:15:50.350 doing a full physical exam and checking a history 00:15:50.350 --> 00:15:53.090 chart on every single fresh cow at 5 a .m. Of 00:15:53.090 --> 00:15:55.570 course not. We need a system. Protocol drift 00:15:55.570 --> 00:15:58.350 is a real thing. How do we make this actionable 00:15:58.350 --> 00:16:01.529 without needing a Ph .D. in every pen? It comes 00:16:01.529 --> 00:16:04.080 down to two main things. Timing and creating 00:16:04.080 --> 00:16:06.700 risk lists. Let's talk about what we can call 00:16:06.700 --> 00:16:08.840 the new playbook. All right, lay it out for me. 00:16:08.879 --> 00:16:11.120 How do we rewrite the protocol so it's simple 00:16:11.120 --> 00:16:13.590 enough to follow? First... The timing pivot. 00:16:13.710 --> 00:16:16.009 You mentioned day five versus day 15 earlier. 00:16:16.230 --> 00:16:18.830 That is absolutely crucial. Let's define days 00:16:18.830 --> 00:16:21.490 three through nine as the danger zone. Yeah, 00:16:21.590 --> 00:16:23.789 that tracks with what I see. That's when the 00:16:23.789 --> 00:16:26.110 DAs happen. That's when the metritis hits. That's 00:16:26.110 --> 00:16:28.610 when the cows just look sad. Right. Most of the 00:16:28.610 --> 00:16:31.090 fatty liver and DAs get their start in that first 00:16:31.090 --> 00:16:35.210 week. So a 1 .2 or 1 .4 reading in that day three 00:16:35.210 --> 00:16:37.250 to nine window is serious. You should react to 00:16:37.250 --> 00:16:39.809 that. Okay. But once you cross day 10, the risk 00:16:39.809 --> 00:16:43.080 drops off a cliff. A mild elevation. say 1 .2 00:16:43.080 --> 00:16:45.740 to 1 .7 legend and a healthy looking cow at day 00:16:45.740 --> 00:16:48.279 12 is often just noise. Okay, so the rule is 00:16:48.279 --> 00:16:50.860 tighten the screws and be more aggressive in 00:16:50.860 --> 00:16:52.919 the first week, but then relax a bit in the second 00:16:52.919 --> 00:16:55.340 week. Exactly. Focus your energy and your resources 00:16:55.340 --> 00:16:57.659 where the fire is most likely to start. Makes 00:16:57.659 --> 00:17:00.000 sense. What's the second part? The second part 00:17:00.000 --> 00:17:02.879 is building a risk list. You asked how to do 00:17:02.879 --> 00:17:04.700 this without a supercomputer. It's actually pretty 00:17:04.700 --> 00:17:07.440 simple. You identify the cows before they even 00:17:07.440 --> 00:17:09.940 calve who are the most likely to crash. So we're 00:17:09.940 --> 00:17:12.200 flagging the troublemakers ahead of time. Who 00:17:12.200 --> 00:17:14.700 are they? Who makes the list? The criteria are 00:17:14.700 --> 00:17:16.859 very straightforward. Number one, third lactation 00:17:16.859 --> 00:17:19.000 or older. The grandmas. Always the grandmas. 00:17:19.059 --> 00:17:23.140 Exactly. Number two, a BCS greater than 3 .75 00:17:23.140 --> 00:17:27.240 at calving. The fat cows are metabolic time bombs. 00:17:27.579 --> 00:17:30.599 Always. They have no appetite and way too much 00:17:30.599 --> 00:17:33.339 fat to burn. It's a bad combination. And number 00:17:33.339 --> 00:17:36.200 three, a history of DA or a clinical ketosis. 00:17:36.480 --> 00:17:38.660 If she had it last time, she's got a much higher 00:17:38.660 --> 00:17:40.539 chance of having it again. Okay, so I've got 00:17:40.539 --> 00:17:43.480 my watch list. Old, fat, or a history of trouble. 00:17:43.619 --> 00:17:45.579 I can pull that from my herd management software 00:17:45.579 --> 00:17:48.180 in about five minutes. Right. So here's the strategy. 00:17:48.579 --> 00:17:51.599 Watch these cows like hawks. Test them frequently, 00:17:51.859 --> 00:17:54.259 maybe every other day in that first week. Be 00:17:54.259 --> 00:17:56.900 aggressive with treatment. If one of these cows 00:17:56.900 --> 00:18:00.579 hits 1 .2, you shoot. You treat. No questions 00:18:00.579 --> 00:18:03.900 asked. And everyone else. The heifers. The perfect 00:18:03.900 --> 00:18:06.640 looking second lactation cows with a good BCS. 00:18:07.109 --> 00:18:09.890 That's your low -risk group. Test them once, 00:18:10.109 --> 00:18:12.829 maybe on day 7 or day 10, just as an audit for 00:18:12.829 --> 00:18:15.690 the whole herd. But you only treat them if they 00:18:15.690 --> 00:18:19.289 show clinical signs. If a heifer is eating, looks 00:18:19.289 --> 00:18:21.930 bright, and is milking well, put the drench gun 00:18:21.930 --> 00:18:24.250 down. That actually saves a tremendous amount 00:18:24.250 --> 00:18:27.009 of work. Because the heifers are always the hardest 00:18:27.009 --> 00:18:29.369 ones to lock up and treat anyway. They fight 00:18:29.369 --> 00:18:31.710 you, they jump, it's a complete rodeo. And they 00:18:31.710 --> 00:18:33.710 are the ones least likely to need it. We spend 00:18:33.710 --> 00:18:35.849 so much energy wrestling heifers who are just 00:18:35.849 --> 00:18:37.970 trying to eat solely because a number on a meter 00:18:37.970 --> 00:18:40.829 said 1 .2. This brings up an interesting point 00:18:40.829 --> 00:18:43.829 about technology. Because a lot of farms, mine 00:18:43.829 --> 00:18:46.470 included, are putting rumination collars on everything. 00:18:46.710 --> 00:18:49.490 Or we have robots testing milk. How does that 00:18:49.490 --> 00:18:51.390 fit into this new playbook? Great question. Is 00:18:51.390 --> 00:18:53.230 the robot going to replace the herdsman here? 00:18:53.349 --> 00:18:55.759 The rule should be... Tech is a spotter, not 00:18:55.759 --> 00:18:58.200 a shooter. I like that. A spotter, not a shooter. 00:18:58.359 --> 00:19:00.339 Explain what you mean. Take those rumination 00:19:00.339 --> 00:19:03.279 callers, SCR, Allflex, Cow Manager, whichever 00:19:03.279 --> 00:19:05.940 brand you have. The studies are very clear that 00:19:05.940 --> 00:19:08.660 they detect drops in rumination often a full 00:19:08.660 --> 00:19:11.690 24 hours before clinical signs appear. Yeah, 00:19:11.710 --> 00:19:13.970 I've seen that. You'll see the graft tank a day 00:19:13.970 --> 00:19:16.529 before she actually looks sick. The caller knows 00:19:16.529 --> 00:19:19.630 before I do. Right. So don't let the robot or 00:19:19.630 --> 00:19:22.690 the caller decide the treatment. Let them generate 00:19:22.690 --> 00:19:26.630 the to checklist. Instead of bleeding every single 00:19:26.630 --> 00:19:29.670 cow, you only check the cows the callers have 00:19:29.670 --> 00:19:33.269 flagged for you. The tech says, hey, cow 405 00:19:33.269 --> 00:19:36.740 dropped her rumination by 20 % last night. You 00:19:36.740 --> 00:19:39.680 go find her. Then you use your eyes and maybe 00:19:39.680 --> 00:19:42.059 your meter to make an informed decision. So it 00:19:42.059 --> 00:19:44.680 filters the work. Instead of walking 100 fresh 00:19:44.680 --> 00:19:47.180 cows, I'm just checking the 10 that the system 00:19:47.180 --> 00:19:50.480 flagged plus my pre -made high -risk list. Exactly. 00:19:50.700 --> 00:19:53.059 That could save hours every single morning. It 00:19:53.059 --> 00:19:55.640 makes you incredibly efficient. And there's other 00:19:55.640 --> 00:19:58.160 tech coming too with MIR that's mid -infrared 00:19:58.160 --> 00:20:00.900 spectroscopy. From the milk test. Right. Using 00:20:00.900 --> 00:20:03.019 your routine milk recording samples to predict 00:20:03.019 --> 00:20:06.150 hyperketonemia. The algorithms are getting better 00:20:06.150 --> 00:20:08.269 and better at predicting which cows are at risk 00:20:08.269 --> 00:20:10.309 based on their milk components. And what about 00:20:10.309 --> 00:20:12.369 genetics? I've heard rumblings about that. Can 00:20:12.369 --> 00:20:15.150 we just breed our way out of this problem? Slowly, 00:20:15.349 --> 00:20:18.210 yes. We are starting to see ketosis resilience 00:20:18.210 --> 00:20:21.809 as a selectable trait. It turns out some bloodlines 00:20:21.809 --> 00:20:24.529 are just genetically prone to high BHB and poor 00:20:24.529 --> 00:20:27.369 fertility. They're the fragile ones. Over time, 00:20:27.390 --> 00:20:29.809 you can absolutely breed away from that. That's 00:20:29.809 --> 00:20:31.829 the long game for sure. Yeah. Let's talk about 00:20:31.829 --> 00:20:33.990 the root cause. Let's do it. Because if I'm being 00:20:33.990 --> 00:20:36.910 honest, even if I have a risk list, if I have 00:20:36.910 --> 00:20:40.650 40 % of my cows hitting 1 .2, I'm still running 00:20:40.650 --> 00:20:43.390 around like a headless chicken. At some point, 00:20:43.470 --> 00:20:45.750 filtering doesn't matter if the whole herd is 00:20:45.750 --> 00:20:49.329 sick. 100%. If your prevalence is high, no amount 00:20:49.329 --> 00:20:51.670 of targeted treatment or fancy technology will 00:20:51.670 --> 00:20:53.390 save you. You can't drench your way out of a 00:20:53.390 --> 00:20:55.670 management problem. So if I want to stop drenching 00:20:55.670 --> 00:20:57.730 altogether, or at least get it down to a bare 00:20:57.730 --> 00:21:01.240 minimum, what do I do? How do I stop the fire 00:21:01.240 --> 00:21:05.660 from ever starting? The 60 days before she calves. 00:21:05.779 --> 00:21:07.940 The boring stuff. The profitable stuff. The single 00:21:07.940 --> 00:21:09.660 biggest lever you can pull is body condition 00:21:09.660 --> 00:21:12.500 score. We talked about the fat cows. You have 00:21:12.500 --> 00:21:14.700 to be religious about keeping calving cows between 00:21:14.700 --> 00:21:19.240 a 3 .0 and a 3 .5. A cow calving at 3 .75 or 00:21:19.240 --> 00:21:22.220 4 .0 has a suppressed appetite. She physically 00:21:22.220 --> 00:21:24.619 cannot eat enough to support her milk, so she's 00:21:24.619 --> 00:21:27.039 forced to burn fat. It's just physics. We all 00:21:27.039 --> 00:21:29.440 know we shouldn't have fat, dry cows, but man, 00:21:29.519 --> 00:21:31.980 they can sneak up on you. What else is on that 00:21:31.980 --> 00:21:34.700 list? Stocking density. This is the one everyone 00:21:34.700 --> 00:21:36.819 hates hearing because it often involves concrete 00:21:36.819 --> 00:21:39.900 and capital investment. Your fresh pen and your 00:21:39.900 --> 00:21:43.180 close -up pen must be under 100 % capacity, preferably 00:21:43.180 --> 00:21:46.759 closer to 80. 100%. Come on, be real. In the 00:21:46.759 --> 00:21:49.559 spring flush, when all the heifers calve at once, 00:21:49.779 --> 00:21:52.980 we're running 120, 130 % easy. It gets tight. 00:21:53.200 --> 00:21:55.980 And that is exactly where your $35 ,000 is going. 00:21:56.079 --> 00:21:58.420 When you overcrowd the fresh pen, the shy cows, 00:21:58.660 --> 00:22:01.160 the heifers, the sick ones, they don't eat. They 00:22:01.160 --> 00:22:03.099 just stand and wait. And every hour they wait, 00:22:03.390 --> 00:22:05.650 It's an hour they are mobilizing fat and making 00:22:05.650 --> 00:22:08.789 ketones. And bunk space. Minimum 24 inches per 00:22:08.789 --> 00:22:11.670 cow, ideally 30. If they have to fight for a 00:22:11.670 --> 00:22:13.710 spot at the dinner table, the vulnerable ones 00:22:13.710 --> 00:22:17.309 always lose. Always. And finally, heat stress. 00:22:17.970 --> 00:22:20.430 Cooling your dry cows is probably the single 00:22:20.430 --> 00:22:23.029 highest ROI investment you can make on a dairy. 00:22:23.450 --> 00:22:26.009 If a cow is heat stressed when she's dry, she 00:22:26.009 --> 00:22:28.190 enters lactation with a damaged immune system 00:22:28.190 --> 00:22:30.579 and a lower drive to eat. So basically, if you 00:22:30.579 --> 00:22:32.940 treat them like queens before they calve, they 00:22:32.940 --> 00:22:35.339 won't need the drench after. That's pretty much 00:22:35.339 --> 00:22:38.000 it. Prevention is boring, but treatment is expensive. 00:22:38.519 --> 00:22:40.880 All right. We've covered a ton of ground here. 00:22:40.980 --> 00:22:43.859 We've busted the 1 .2 myth. We've looked at the 00:22:43.859 --> 00:22:46.519 staggering cost of being normal. And we built 00:22:46.519 --> 00:22:48.859 a whole new playbook. Let's bring this home for 00:22:48.859 --> 00:22:50.859 everyone listening. Let's do it. A farmer is 00:22:50.859 --> 00:22:52.640 listening to this in the tractor right now or 00:22:52.640 --> 00:22:55.390 driving to the feed store. What are the three 00:22:55.390 --> 00:22:57.309 concrete things they need to take away from this 00:22:57.309 --> 00:22:59.769 deep dive? OK, let's break it down. Immediate, 00:22:59.769 --> 00:23:02.190 medium term and long term. Start with this week. 00:23:02.369 --> 00:23:05.710 What can they do tomorrow? Immediate. Immediate. 00:23:05.710 --> 00:23:08.589 The audit. Tomorrow morning, go out and grab 00:23:08.589 --> 00:23:11.869 10 to 12 clinically normal fresh cows. I'm talking 00:23:11.869 --> 00:23:14.450 cows between day three and day 14. Just a random 00:23:14.450 --> 00:23:17.170 sample of normal looking cows and test their 00:23:17.170 --> 00:23:19.690 BHB. OK. And what am I looking for in those numbers? 00:23:20.089 --> 00:23:22.849 If one or two of them are high, so over 1 .2, 00:23:22.950 --> 00:23:25.210 you're probably okay. That's in the mid -teens 00:23:25.210 --> 00:23:27.769 for prevalence. You're doing fine. But if three 00:23:27.769 --> 00:23:30.250 or more are high. So 30 % or more of my sample 00:23:30.250 --> 00:23:33.069 group. Exactly. Then you have a greater than 00:23:33.069 --> 00:23:36.210 20 % prevalence problem. Your transition program 00:23:36.210 --> 00:23:37.990 is leaking and you need to know that number. 00:23:38.029 --> 00:23:40.289 That's step one. Okay, that's easy enough. The 00:23:40.289 --> 00:23:43.430 audit. Now, medium term. The next three to six 00:23:43.430 --> 00:23:46.309 months. Implement the risk list. Sit down with 00:23:46.309 --> 00:23:48.509 your vet and your team and literally rewrite 00:23:48.509 --> 00:23:51.529 the fresh cow protocol. Stop the treat everyone 00:23:51.529 --> 00:23:54.269 rule. Set up your software to automatically flag 00:23:54.269 --> 00:23:57.369 the high risk cows for you old fat history of 00:23:57.369 --> 00:23:59.490 DA. And then you tell the team, these are the 00:23:59.490 --> 00:24:01.910 cows we worry about. The others, we just watch. 00:24:02.269 --> 00:24:04.650 Precisely. Shift your labor and your focus to 00:24:04.650 --> 00:24:07.009 the cows that actually need it. And finally, 00:24:07.109 --> 00:24:10.190 long term. What's the one to two year plan? Fix 00:24:10.190 --> 00:24:12.750 the pen. You have to address the physical environment. 00:24:13.130 --> 00:24:15.579 Go out there with a tape measure. Check the bunk 00:24:15.579 --> 00:24:19.359 space. Count the stalls and count the cows. If 00:24:19.359 --> 00:24:22.680 your fresh pen is constantly at 115 % stocking 00:24:22.680 --> 00:24:26.079 density, that is your $25 ,000 loss right there. 00:24:26.240 --> 00:24:29.480 No amount of propylene glycol or fancy supplements 00:24:29.480 --> 00:24:32.960 fixes a lack of bunk space. And maybe start paying 00:24:32.960 --> 00:24:35.960 closer attention to those genetic indices for 00:24:35.960 --> 00:24:38.240 ketosis resilience when you're picking bulls. 00:24:38.400 --> 00:24:40.779 Absolutely. Start building a herd that doesn't 00:24:40.779 --> 00:24:42.519 want to get sick in the first place. It sounds 00:24:42.519 --> 00:24:44.640 so simple when you lay it all out like that, 00:24:44.680 --> 00:24:46.740 but I know it takes a lot of discipline to change 00:24:46.740 --> 00:24:48.759 a protocol that's been in place for 10 or 15 00:24:48.759 --> 00:24:51.619 years. It does. It's a mindset shift. But looking 00:24:51.619 --> 00:24:55.500 at these costs, almost $300 a case, it's just 00:24:55.500 --> 00:24:58.000 money we can't afford to keep losing. Especially 00:24:58.000 --> 00:25:00.420 not with today's feed prices. It is. And remember, 00:25:00.500 --> 00:25:02.680 the goal isn't just to be better at finding ketosis. 00:25:02.720 --> 00:25:05.519 The goal is to have cows that don't get it. Amen 00:25:05.519 --> 00:25:07.799 to that. Well, this has been another Bullvine 00:25:07.799 --> 00:25:10.440 podcast from The Bullvine Podcast. For more straight 00:25:10.440 --> 00:25:14.420 -talking industry analysis, head to www .thebullvine 00:25:14.420 --> 00:25:17.339 .com. And make sure to subscribe wherever you 00:25:17.339 --> 00:25:19.700 get your podcasts. We're out with new episodes 00:25:19.700 --> 00:25:22.519 every day. And next time, we're going to be looking 00:25:22.519 --> 00:25:25.480 at why your heifer raising costs might be lying 00:25:25.480 --> 00:25:27.819 to you. Ooh, that's another can of worms. You 00:25:27.819 --> 00:25:29.920 won't want to miss that one. See you then. Bye 00:25:29.920 --> 00:25:30.299 for now.