The Data It Takes to Build a More Resilient Cow

Big data and strategic collaborations are the way of future when it comes to solving genetic challenges in the beef business. This episode covers work that is happening now to inform tools of the future. Christine Baes gives a peak into a multi-disciplinary project she works with on behalf of the Canadian dairy industry, and Andre Garcia draws parallels to what could be possible in the U.S. beef industry. Fertility, efficiency and methane emissions are among the traits that could see new ways for selection pressure in the future. 

HOSTS: Miranda Reiman and Kelli Retallick-Riley 

GUESTS: 
Christine Baes, department head and Canada Research Chair in Livestock Genomics for the University of Guelph, was born and raised on a dairy farm in Southwestern Ontario. She has a bachelor’s degree from Guelph, a master's in animal welfare from Universität Hohenheim, and a PhD in quantitative genetics from the Leibniz Institute for Farm Animal Biology and the Christian Albrechts Universität zu Kiel in Germany.

She and her team are involved in various large-scale livestock breeding projects (swine, horses, dairy cattle, goats) and bridge the gap between cutting-edge research and practical application of new knowledge. Baes has extensive knowledge in the areas of quantitative genetics and statistical genomics as it relates to the genetic and genomic evaluation of livestock. 

In her spare time, she runs a small farm outside of Maryhill.

André Garcia, senior geneticist for Angus Genetics Inc. (AGI), grew up in southern Brazil with a diversified agriculture background. 

In 2015, he earned his animal science degree from Margina State University and followed it with a master’s program in animal breeding and genetics. He earned his PhD from the University of Georgia, where he also took on a postdoctoral research position with a strong emphasis on quantitative genetics and the use of genomic information for genetic evaluation. 

Garcia came to AGI as a research and development geneticist in 2021. He works on genomic evaluation and in an educational role, helping producers understand the technology available to improve their herds. 

Don't miss news in the Angus breed. Visit www.AngusJournal.net and subscribe to the AJ Daily e-newsletter and our monthly magazine, the Angus Journal.

Transcript

Miranda Reiman (00:03):
Welcome to the Angus Conversation. I'm your host Miranda Reiman with my co-host, Mark McCulley, CEO of the American Angus Association. And Mark, we are going to talk a little bit about Beef Improvement Federation, which is kind of interesting because you weren't even there this year.

Mark McCully (00:20):
 I know, I know, I wasn't. I missed it. I missed it. And that's why this is exciting. I'll be enjoying this podcast with the listeners, and I heard it was just a great conversation. Unfortunately, I got sick and had to bail last minute, but always enjoy going to Beef Improvement Federation. I always think it's the thought leaders around genetic selection and genetic improvement are usually in the room, and those are always fun conversations to be in the middle of. Those are fun meetings to be a fly on the wall for.

Miranda Reiman (00:56):
When you talk about some of those innovative thought leaders we have in the room, we've got one of those right here on the podcast because she actually picked up the slack for you, Mark. Kelli Retallick-Riley is my co-host for this episode, and we wanted to get Kelli in this intro a little bit to kind of frame up the conversation, I guess you'd say, Kelli, so thanks for joining us today.

Kelli Retallick-Riley (01:17):
Yeah, absolutely. I always love to fill in for Mark when he can't be there, Miranda. We always have a lot of fun on these, and so I hope everyone enjoys this episode.

Mark McCully (01:25):
It's threatening my position as co-host, so I always get a little nervous when you step in, Kelli.

Kelli Retallick-Riley (01:31):
I don't think there's any real threat, Mark. It'll be all right.

Mark McCully (01:34):
And Kelli also serves on the board of directors for the Beef Improvement Federation. So you are wearing a couple hats there. One representing the obviously Angus and AGI and then also collectively as a group of leaders for the bigger organization to BIF.

Kelli Retallick-Riley (01:50):
Yeah. Yeah, that BIF committee is something that I've served on for a few years now, and it's nice to be in the boardroom with those folks that while we all serve different entities from that standpoint, our mission is genetic improvement of the beef industry. So it's fun to get all your like-minded friends in one room and working towards the goal of kind of just standardizing genetic programs for improvement across the industry.

Miranda Reiman (02:14):
So when we think about this podcast, we recorded it way back this summer, and one thing that kind of stuck out to me is an overarching theme of it was just like, there's some really cool stuff we could do in the future. There's some traits that we'd like to solve for that we can't today. There's some other, if we look across at other maybe species or in other industries, things that they're able to do that we're not just because of maybe the way our business is set up and some of those kind of things. But I kind of geeked out at this conversation, but I mean, Kelli, what did you kind of think was some of the highlights of a conversation like this?

Kelli Retallick-Riley (02:54):
Yeah, I just think the whole model that Christine Baes and her group has built there in Canada around cow resiliency and how they're working really across the table with multiple different entities. I think one thing obviously that comes out of this podcast is around all those cool new traits that we could look at and how we could explore different areas, which maybe we've explored in the past, but we haven't made it all the way there or completely new areas. I also think the theme throughout her talk, and we talk a little bit about it on the podcast, is just the value of really good partnerships and working collectively towards the same goal. I thought that was super interesting, and obviously that's where we live with the American Angus Association and why we've been, as AGI is successful at delivering tools back to breeders is because of the collective good that members work together through a national cattle evaluation and harnessing their data as a group and bringing that back together and trying to put good tools back out to the industry. And so, I just think the spirit of collaboration really rings true in this talk, which I always think is fun. We love to collaborate here within the walls of 3201, and I know that our members love to collaborate out in the field.

Mark McCully (04:08):
I think about, and I know some of the topics that get covered in here in this discussion are probably a little Star Wars maybe sounding for some of our listeners, some maybe kind of out there kind of technologies. But I think when you start looking at some of these things from a historical framework of thinking about how our data collection has advanced over the years from some very simple measurements we took back with birth weights and weaning weights and yearling weights to evolution up, obviously a great technology in ultrasound, a technology that advanced us significantly in our ability to collect phenotypes that were able to be turned into selection tools for EPDs to make progress in carcass merit. And I think about some of the phenotypes where our breeders are collecting now, like teat and udder scores and foot scores and hair shedding scores and PAP measurements for our high altitude friends. I mean, all of that data collected those phenotypes have been able in time to be able to be turned into valuable tools. And so while some of these things may sound a little bit out there, when you start thinking about the potential, if we can collect some of this valuable data and now put that in the hands of our breeders, you think about the progress that we can make down the road in the near term and maybe even further down in the future. So it gets pretty exciting.

Miranda Reiman (05:39):
So what are some of those things, Kelli, that you would say we're just on the cusp of, or things that we're working on that we have some practical steps today, but maybe we're working towards an end goal of giving producers tools like X, Y, Z?

Kelli Retallick-Riley (05:56):
Yeah, I thinksome of the things internally. One of the things that, and we've talked about it for several years, but at the same time, the work is never done is just some of the data squeezes that we can get out of the data that's already in-house. And I think that around our big genomic database, Miranda, we always talk about how many genotypes we bring into this organization. And I'm just always amazed about the investment, right? Breeders making genomic testing and one of the things we know it does, it enhances the value of their genetic evaluation from an accuracy standpoint so much to increase the pace of genetic improvement. But moreover, it's like, okay, we have almost 2 million genotypes captured. What else can we learn from those genotypes? What else can we do? And that's where some of this work where it's pretty new and novel, right.

(06:44):
For the beef industry around fertility haplotypes and looking for selection signatures in the DNA to be able to tell us what are some things that we may not have just a strictly, Mark to your point, peer phenotypic measurement. Maybe it's not something we can go out and we can measure with the scales, or we can go out and we can score with the scoring guide, but things that are kind of hidden in that genetic code and what can we uncover there? And that's super exciting for us. I think when we think of more practical things outside of that big genomic database, Miranda, what we've tried to do with this heart health initiative, we talk about trying to make sure we have cattle that are adaptable to stressors in the environment. I think, Mark, you mentioned the PAP EPD and what we've been able to do with high altitude disease.

(07:28):
How do we take those similar thought processes and say, Hey, how do we match cattle to other environments or how do we ensure these cattle are more resilient to stress? I think that's where your heart health comes in and obviously heart scores when we're taking them on the kill floor and things like that, those aren't necessarily things that are traditional seedstock channels. Our traditional seedstock breeders are going to be able to capture on their own. And so that's what we've identified is where can we plug in with the relationships we can build in the industry and help producers capture something that they can't get their hands on.

Miranda Reiman (08:04):
And one thing I think about from a producer standpoint, every time I hear that it's a phenotype that a producer can't take themselves, I think it's also like they don't have to take it themselves either. So maybe everybody says, that's good, you can just take care of that one for us, and that'd be great. But I do think that in a lot of those conversations I've heard at BIF probably over the past couple of years, there's been a lot of talk about, and I don't know if you just call it passive phenotypes or phenotypes that collect themselves technology that allows for some of this stuff to get easier than being out there, your computer in hand, pen and paper when everybody is squeezed for time too. So in addition to maybe new traits that you couldn't get available, there's also the technology to maybe make some of that collection easier, which is exciting too. I think.

Kelli Retallick-Riley (08:52):
Yeah, new ways to capture the data, which is always fun, and honestly, that probably leads to new things we never thought about before from that standpoint. And so I think it makes it easier. I think it makes it fun, and I think it makes us be able to get down in the weeds and kind of understand a little bit more about a trait. Honestly, I think because all this technology is at our fingertips, it's really been a catalyst for change for us in the beef industry. I think we're going to go as fast as we've ever gone Miranda and Mark with these new traits and genetic improvement because quite frankly, the technology's here to help us. And I think historically, the technology has never been as good as it is right now. And so there's a world of opportunities, I think for Angus and for us to continue to drive on genetic improvement in different ways. And I think we'll hear Christine talk about some of those ways they're trying to harness those things in the dairy industry.

Miranda Reiman (09:46):
As we've talked to your team a lot in the last couple of podcasts, because we're just so excited to have a full team there at AGI. I will note that André Garcia, our senior geneticist on the AGI team also joined us for this podcast. So it was fun to hear him ask questions back and forth. And again, I say I kind of geeked out, but listening to two really smart scientists talk back and forth, it was a fun conversation. So today on the podcast, we've got some different kind of guests where oftentimes we're sitting across the table from breeders. Today, we've got some of the smartest minds in the genetic business, don't we, Kelli?

Kelli Retallick-Riley (10:24):
Absolutely, we do. We have two really good guests today. One internal, one external. I'm really happy to have both of these people on this podcast today. I think it'll be a fun conversation.

Miranda Reiman (10:32):
So Christine, we'll start with you. Christine Bayes, am I saying your last name right? Yep. Christine Bayes with the University of Guelph. Why don't you just tell us a little bit about yourself and what you do there?

Speaker 4 (10:42):
Sure. My name is Christine Bayes. I am the department chair of the Department of Animal Biosciences at the University of Guelph, and I hold a Canada research chair in Livestock Genomics. So I do a lot of research on livestock, but I also am responsible for the administration of our department at Guelph. I came from a dairy farm in southwestern Ontario. I did a lot of my master's in PhD work in Germany, and I moved to Switzerland before coming back to Canada in 2015. I really like this cutting edge translation of research into applicable methods to improve the industry. So I'm really excited to be here today with you and ready to go.

Miranda Reiman (11:29):
Perfect. So you grew up on a dairy farm? I

Speaker 4 (11:31):
Did, yeah. So I spent a lot of time milking cows stacking hay. We do still have small square bales in Canada. I know that you guys don't do that here,

Miranda Reiman (11:38):
Big stackers though, right?

Speaker 4 (11:40):
Well, we should or you didn't, but my father was a firm believer in sweat. He invested in family labor, elbow grease. That's why I am the youngest of five. Yeah.

Kelli Retallick-Riley (11:49):
Well, and you were recently awarded the J Lush Award, right?

Speaker 4 (11:53):
Yes,

Kelli Retallick-Riley (11:53):
At the dairy science meeting. So congratulations on that.

Speaker 4 (11:56):
Thank you. It's interesting. I'm not an awards person, but this year we, well, the team and I received the Jay Lush Award, but also the Turkey Federation Breeding Award for the Turkey Federation of the USA. So we're really happy about that as well, doing important work. It's great.

Miranda Reiman (12:12):
And we have Andre and Garcia on the other side. Now, many of you have probably seen Andre either at Angus Convention or various other places, giving updates. Webinars. Webinars. That's right. Yeah, he's kind of a star on our team. Kelli.

Speaker 5 (12:25):
Yes. Well, thank you for having me. It's exciting. This is a first on the podcast line for me. But yeah, excited to be here and talk to Christine. I've known Christine from my graduate school time and reading all the papers and listening to presentations at different conferences. So he's exciting to be sitting at the same table and having some good discussion.

Miranda Reiman (12:45):
Andre is this senior geneticist on our team and been with us for

Speaker 5 (12:50):
Three years and a half now on our research team and doing work on our research, internal and external with our collaborators, and also helping a lot with our genetic evaluations with our IS team. So

Kelli Retallick-Riley (13:02):
Yeah, he's very important to breeders. He makes sure those EPDs get out every single week. So I was FRA to what we do.

Miranda Reiman (13:08):
Yeah, I was refraining from saying, so if you don't like something with the EPDs, it's probably Andre's fault.

Speaker 5 (13:14):
Untrue. Untrue. Trying to make them better every time.

Miranda Reiman (13:18):
So one of the topics that we thought we would bring up for this podcast today was really that idea of cow resilience and how that's maybe defined across the globe and what genetic tools we have that are able to get at that a little bit more. I had written down your definition of cow resiliency, which is an animal that's able to adapt rapidly to changing conditions without compromising productivity, health or fertility while becoming more resource efficient and reducing its environmental burden. So I think that's something all of us can get on board with, whether we're a Turkey dairy or beef producers. So maybe just talk a little bit about your work in that area, Christine.

Speaker 4 (13:56):
For sure. Yeah, it's really nice to be able to have your cake and eat it too. When you're doing genetics and genomic work, you've got kind of a palette of different traits that you can work with and optimize according to the relationships. And I think that's the key, right? If you've got different dials to turn, you can optimize and you can have all of those things, fertility and health and efficiency. So what we've been doing in Canada is we've been trying to collect as many close to biology phenotypes really as we can. We've got a really good system set up now for integrating automated fertility traits, things like activity monitor data, et cetera. We've seen that that's really correlated highly with actual conception rates, which is fantastic. So we're working on getting those into a national evaluation system, but also looking carefully at health traits.

(14:49):
So calves are kind of the missing link in our data system. We've kind of ignored them. You breed your heifer or your cow and then you just wait until they become a cow. And that's not really very smart because there's a lot of information that gets lost there. And by grasping that, harnessing it, and really incorporating it into genetic evaluations, we can see what the connection is between fertility and health, but also these new efficiency traits. So we've been working really hard on getting data collected on commercial farms across Canada. Moving forward, we're going to have 65 sniffers installed in robotic milking systems across the country. And with all of that data, I think we can optimize and make sure that we have really a cow that's fit for the future. So that's pretty exciting. I think

Miranda Reiman (15:38):
Back up a little bit and explain a sniffer.

Speaker 4 (15:40):
So yes, a sniffer. So a lot of people are used to the green feed system. I think it's widely used in beef as well.

(15:47):
We found that it's a fantastic piece of equipment, but it's just too expensive. And the way that we use the green feeded machine in our research is we actually have students working with individual cows, so they drive the machine up to the cow. It's not like in beef where you put it out in a grazing field. So it's really a lot of work and the machine is expensive. So we had to find a different way of collecting real methane emission data. So we're working together with a company from Italy called Technos Sense, and they've developed a sniffer, and this sniffer gets installed into a robotic milking system. So the cow goes to get milked just as she normally would, and it's a pretty non-invasive way of really upping the number of phenotypes that we can collect very cheaply. We're working on sort of standardizing those across the country, which is pretty tough, but I think we're going to get there. No risk, no fun. So the sniffer, it just sucks. In the methane of the cow while she's milking, we connect with the RFID reader of the robotic milking system. We connect the data so that we know which cow is

Speaker 6 (16:51):
Which,

Speaker 4 (16:51):
And then when the cow exits the robotic milking system, we've actually tied into the robot so that the sniffer sneezes when the cow leaves. So it actually pushes air out on one hand to clean the cleans the palette. Totally, totally. It snuffs out any junk that gets sucked into the sniffer, but also it helps us to differentiate between individual cows. We've got a mark between animals. I hope that that's going to be a really great way of collecting a lot of data.

Kelli Retallick-Riley (17:19):
Absolutely.

Miranda Reiman (17:19):
Sort of a passive way of doing it. It doesn't require the producer to stand there and take notes.

Speaker 4 (17:25):
It's also really interesting because working with a bunch of people in Switzerland and in Europe who have a lot of alpine systems, so that becomes a lot more similar to what I'm guessing that the beef industry is facing with You don't see your cows very often.

Kelli Retallick-Riley (17:39):
Exactly. We don't see 'em three times a day.

Speaker 4 (17:41):
Exactly. So we're really interested in how to collect data from grazing systems, but also from alpine systems and more extensive kind of systems so we can also get that information and see what the differences are to the intensive systems that we have in Canada for milking cows.

Kelli Retallick-Riley (17:54):
Yeah, and I think it's so interesting because these methane conversations, obviously they've been taking place for a long time, and when we think about sometimes methane capture, we can get people that are very passionate on one side or the other, but I think it's really about the efficiency of the cow. If we can make her more efficient, why not? But some of the limitations are the fact that this equipment's really expensive, they're kind of hard to use at times. And so how do you think, I mean, obviously this sniffer is one way that hopefully we can capture, at least in the dairy industry, a lot of phenotypes, probably a little bit more affordably for genetic evaluations.

Speaker 4 (18:27):
Absolutely. I've seen cows with SF six canisters strapped to their back and all kinds of mechanical stuff that you can do to a cow. But I think this is a really good strategy.

Kelli Retallick-Riley (18:38):
Yeah, it's an exciting time for sure. These things are getting more within reach, which is cool.

Speaker 5 (18:43):
I think also as you talk about those research projects that you presented today, the more people that we get involved in those topics, the more the technology will develop and come out with different solutions and be more affordable and more applicable to different segments of different industries. Most definitely. I

Miranda Reiman (19:01):
Think you hit the nail on the head though, Kelli with I think sometimes beef producers will tune out that methane conversation as sort of like that's that sustainability thing, and we're not worried about that, but there is actually pretty good correlations with some of those other traits that matter to their bottom line maybe a little more closely. Right?

Speaker 4 (19:19):
For sure. And it's really interesting because I've talked to a lot of producers who say, this is all garbage, this is stupid. I don't like any of those discussions. We're not the problem, and I really don't think that we are the problem. But what I do think is that there is genetic variation between individual animals and if there's a good story to tell and if there's a way to incorporate that into our evaluations, why on earth wouldn't we?

Kelli Retallick-Riley (19:43):
Yeah, exactly.

Speaker 4 (19:44):
I think it's a fantastic opportunity for us to really show that animals are an integral part of a much larger ecosystem and the food system in general. So we just have to keep making sure that those messages are really positive and that we're doing the best that we can. Yeah, absolutely.

Miranda Reiman (20:05):
We're going to take a quick moment to hear from our sponsor. Westway Feed products liquid supplements increase forage utilization when seasons cause forages to decline in value, our products deliver effective and efficient nutrition to your herd. To learn more about the best way to raise beef, please call 807 5 1 7 or visit westway feed.com. Now back to the conversation. So that wasn't the only phenotype we talked about getting. Talk about. I think it's true. I think you said something like you have 67 traits or something you're measuring

Speaker 4 (20:43):
In the national evaluation in Canada for dairy. Yes, there are a ton of very different traits. Traits like functional traits, longevity traits, of course, milk production, fat and protein, those sorts of things. But also fertility traits are really tough to get, and we have to see that system as a whole. So we can't just look at one individual trait. I know that I spoke with a few producers last night who were saying, wow, this is stupid. We should just measure weaning weights or growth rate or something like that. And I'm like, yeah, but you can do so much more and the interaction between these traits, you can actually get more response to selection if you've optimally balanced all of those traits, all the, we don't even select for milk production in Canada at all. I don't think you do in the states either. All in the, we're actually selecting for fat and protein content, which is right. We don't need water, we need milk with fat and protein. So there's this really nice relationship between these individual traits and that's how you really make sure that you are sustainable in the sense of getting everything improved at once. And you might have to deal with a few less big steps, I guess, in improvement of specific traits, but as long as you're going in the right direction, genetics is cumulative and permanent way to improve your animals, and that's what we have to stick to. Yeah,

Miranda Reiman (22:06):
That's a great point. When you do a management thing, it's once and then you've got to do it again and again and again.

Speaker 5 (22:11):
And I like that idea too in your presentation, you going through those topics when you're talk about fertility, you're not talking about one phenotype or one trait. You're measuring many different things and you go at it with all those traits in the evaluation.

Speaker 4 (22:25):
For sure. Otherwise you're missing out. I think one of my PhD students recently did some work on anogenital distance, and it's kind of a weird thing, but that itself has a heritability of 39%, and if it's easy to measure and if you don't have all of the automated sensors that some people might have, maybe that's a really good way to improve your fertility and your conception rates as well.

Miranda Reiman (22:49):
I actually wrote that one down because I'd never heard of that before. It being a possibility to measure

Kelli Retallick-Riley (22:55):
And it's a structural trait, so structural traits in general usually have a higher response to selection. The heritability is a bit higher, so that's kind of cool. I'll be interested. What is the correlation or do you know the correlation yet between that trait and what you're currently measuring? For fertility,

Speaker 4 (23:08):
We don't that we're still working on, but with that heritability and because it's so different from, for example, days open or calving, the first service, I think it's going to fit well. And I'm hoping to actually replace some of the older traits because you might as well literally select the producers that you're working with as opposed to the animals that you're working with because you're probably going to have more success there.

Miranda Reiman (23:32):
Yeah, absolutely. So one thing you talked about that I thought was interesting and also probably not super applicable in the beef industry just because was the mere data. So explain that first before I try to remember what MEIR

Speaker 4 (23:45):
Stands for. So ME stands for mid-infrared spectroscopy data, and in dairy cattle you get animals that are registered and that are on dairy herd improvement. You get a sample about every month, a milk sample from those cows. And what me data me is just the acronym for mid infrared spectroscopy. What you get with that is kind of a wave pattern when you shine light through the milk and why this is potentially applicable for beef as well is that beef are bovine as well. And they actually share quite a large percentage of the DNA. So the bovine genome has about 3 billion base pairs, 3 billion letters in it. And the differences between the individual breeds are actually not as large as you think they are. So I'd be with our new project, we're really looking at whether or not we can take the information from the dairy industry, make our snip evaluations or estimates, and then see what happens when we apply them to the

Miranda Reiman (24:45):
Beef somewhere

Speaker 4 (24:45):
Else. To a beef population. Absolutely.

Miranda Reiman (24:48):
So it could be, we could use that data without having to actually milk beef cattle.

Speaker 4 (24:52):
I don't want to make any promises, don't quote me on that, but I think there's an opportunity there. And I know that there's a lot of naysayers, there's a lot of, but I'm pretty pragmatic. I think that there's a lot in common that we might just have to have a closer look at. We're going to have a really big population of beef cattle coming into this new project. We've also got some beef on dairy, which is going to help with the connectedness of the pedigree. And who knows? That's the fun part about research. You do things and if it works out, it's fantastic, and if it doesn't, you try something else.

Miranda Reiman (25:25):
I want to know who decided to shine light through the milk and see what it would tell you.

Speaker 4 (25:29):
Weird, right? I've been doing this, but that's actually how people get paid for fat and protein. It's this solid approach. It's just never been used for these other, for anything else people have tried. And they're starting to look at ketosis, which is probably not a problem in beef cattle I don't think.

Kelli Retallick-Riley (25:45):
Not too much

Speaker 4 (25:45):
Other metabolic diseases because it does have a lot to do with the metabolism of the cow, the fat digestion and the fat, turning the fat really into milk, the fat from the diet into milk. So maybe could be something.

Speaker 5 (25:59):
Now I'm curious on the mirror, and since we're talking about the technology, do people use, let's say meat samples or could we try MI on meat samples and see what we can find on the beef side?

Speaker 4 (26:10):
It would be really interesting. I know that there's some people in Oklahoma apparently who are milking beef cows. I would love to get my hands on those samples just to see how if

Kelli Retallick-Riley (26:20):
It works. And I think they're running those cattle through green FETs too, on high roughage diets, so fantastic. You might have a whole nother project there.

Miranda Reiman (26:29):
She said that was job security. I think for a researcher, more projects,

Kelli Retallick-Riley (26:33):
It's true.

(26:34):
I think one place where our members, you had mentioned health phenotypes and particularly in the calves, so obviously you have things like you mentioned ketosis or some of those other metabolic diseases that you're getting at in your mature dairy females. But what are you thinking about around calf phenotypes for health and disease? Right? I think that's the part where for us in genetics we get a little like, dang, we haven't made as much progress there probably with genetics as we'd like to. So where do you see that body of work going or what are some of the things you're looking at?

Speaker 4 (27:01):
That's a good question. We have a lot of respiratory disease in Holstein calves, and we have a lot of diarrhea

(27:10):
And we haven't been able to harness that information. So we're relying now on management data. There's a lot of producers who actually do record whether or not they treat calves for respiratory disease or diarrhea. And we've somehow gotten a ton of this data. It's pretty rough. We have to work a lot on cleaning it up and making sure that it's standardized, but it's really turned into an exploration and a path that I wasn't expecting before because we've seen there is actually heritability to susceptibility to these diseases, and that heritability is a little less than 10%, which is still workable. I mean, for the dairy industry we're using, our current fertility traits are like 2% or 3% heritability. We

Kelli Retallick-Riley (27:53):
Can relate to that. Right on.

Speaker 4 (27:54):
Yes. So it's pretty cool. But what we're moving towards is actually honing down even on trying to figure out which calves were exposed to specific pathogens. Interesting. Got a fantastic PhD student working on that right now. Hopefully it'll be published soon, but we're seeing that there is a difference of course to exposure. So I'm a geneticist. I don't like to work with vets, but sometimes you have to. I'm just kidding. No, I really do. There are a few great vets around and we really have to start breaking these barriers between individual fields so that we can get more informed decisions. And working with vets, we've seen, yeah, we have to take into consideration this exposure to specific pathogens that makes the genetic evaluations a lot better. Yeah,

Miranda Reiman (28:42):
Absolutely. And wouldn't that make perhaps the heritability go up if you're considering that right now you're thinking that this population got it out of the entire population, or if you're like, oh, only 50% of them were even exposed.

Speaker 4 (28:55):
Absolutely. Absolutely. You're reducing the environmental noise that is around that genetic variation, so that's really cool.

Miranda Reiman (29:03):
We don't have any environmental noise in our data, do we? Andre?

Speaker 5 (29:07):
It's definitely interesting, and I think you talk about crossing those lines right across disciplines. I think that's right on point there because at the end of the day, we're all trying to make more resilient, more efficient, better, healthier animals. And so that goes, of course, I'd like to claim all the progress through genetics, but I think we do reach out into other disciplines and as many hands as we can get to make that move forward.

Miranda Reiman (29:34):
Yeah, sure. One thing I thought was interesting in your talk is the amount or the percentage of the herd that you have in Canada that you have phenotypes on. I mean, some of those were 90% of the cattle you had certain traits collected on or things like that.

Speaker 4 (29:52):
Yeah.

Miranda Reiman (29:53):
Talk about how you've gotten to that. I mean, some of that is based on your production system and things that we can't get at in the beef industry, but

Kelli Retallick-Riley (30:01):
How have you been so successful at making sure that quality, we still, your playbook actually how those quality phenotypes continue to come in? I think from a beef perspective, with the enhancement with genomic testing and some of those things, as we're delivering genetic predictions, we see some people who may say, well, if I can get this trait with a sample of blood, maybe I don't need to collect the phenotype this year, right? I'll get it next year. And then they kind of come back into the fold. But how do you motivate them to ensure you're getting the right phenotypes?

Speaker 4 (30:31):
We really try to listen to producers because they're asked for so many things,

(30:36):
And at the end of the day, they're the ones with skin in the game. It's their bottom line. If I mess up my evaluation, I'm not going to lose. I hope I'm not going to lose my job. I might, but I probably won't. But if they make wrong breeding decisions, it's really, it affects their bottom line and it affects their ability to move on and function in this industry. And one of the major key messages is that we're all on the same team. If we can work together, and we do have to make compromise sometimes when we speak with producers of like, I'm not going to collect that or that's stupid, you've got to figure out why. Because maybe it is asking too much and maybe it is not reasonable to ask them to collect specific data, but if they're willing, those are the ones that we kind of have to work with. And there is benefits across the entire industry. And in Canada, we're really fortunate because it's quite a small population and we've got a history, a very long history of this collection, this kind of collective good I guess we have. And I do realize that that's very different to a lot of the beef industry because it's not really vertically integrated. It's not really,

Kelli Retallick-Riley (31:50):
It's a little segmented

Speaker 4 (31:51):
Totally. But really at the end of the day, agriculture itself as a whole is under pressure,

(31:59):
Under a lot of pressure. And if we don't start changing our ways and really working together for a common goal, I think we're going to be in trouble. There's a lot of really big investors who are investing a lot of money in alternative proteins and all of this other stuff, and we have an opportunity, I think animal products and animal agriculture is and should be an intrinsic part of being a human, whether or not it has to do with dealing with your animals or eating protein, high quality protein. I think that's helped a lot. But also these traits have to affect the bottom line. They have to be profitable for people to select for it. And you can see the difference. We've done a lot of work, a lot of extension work, showing producers what changes they can make in order to see the actual genetic gain. And it's so much cheaper than in the case of health traits, it's so much cheaper than buying pharma products. It's so much cheaper than buying antibiotics. And it's so much of a better story. We have really resilient animals that are in quota marks naturally resilient. That's where we need to go because there's nothing that anyone can complain about if you do it that way.

Kelli Retallick-Riley (33:16):
Yeah. So if it's important to you as a breeder or as a producer, collecting that data for selection is probably a good idea.

Speaker 4 (33:23):
Absolutely not probably. For sure, for sure.

Miranda Reiman (33:27):
So I starred that that was your sort of superpower that you had a small enough heard that you could collect some of this, but we always talk about in Angus that our superpower is the size of our database is the size of our population. So is that still our superpower?

Speaker 5 (33:43):
Is that I think so. And I think you draw the parallel with the presentation. I think it's interesting that everything starts from that phenotypic data where if we want to discover new things and predict new traits, got to measure those phenotypes. And I think in our case, right, by having a lot, some of the other traits that we have breeders have measured for a long time, and a lot of the pedigree data and a lot of the genotypes, that's only going to make that database stronger the more phenotypes we continue to collect.

Kelli Retallick-Riley (34:11):
Yeah, it's kind of our superpower when we get to go out and have a call for data or be able to rally the troops. We have a lot of people that want to continue to see genetic improvement in the Angus breeded and the beef industry overall. So I think, yeah, I would agree with you, Andre. It's still our superpower for sure, if we can get them rallied and moving in a direction that they're passionate about. But I think, Christine, you hit it, right? If it's important to them, they're much more willing to hop on board. And if it's not important to them, we shouldn't be working on it.

Miranda Reiman (34:36):
Yeah, that's a great point. So what has surprised you most in this kind of big multidisciplinary project that you've had going on or connected project that you've had going on?

Speaker 4 (34:47):
I'm surprised that it actually works. You're not supposed to say that on air. You geneticists know everything. No, it's not. I am a thousand percent sure that the genetics part works. That's clear to me. But I am so grateful and surprised that we can have really an elegant solution for multiple countries, literally, right? We've got this fantastic collaboration of the willing who are each doing their own project and we're not affecting what they want to do in their own particular countries or anything like that. It's more of a situation where one plus one is equal to five, not two.

Miranda Reiman (35:25):
You did say you weren't good at math

Speaker 4 (35:27):
Stage.

Miranda Reiman (35:27):
No. See, I told you there's proof. No, I love that though. That's a great analogy.

Speaker 5 (35:33):
It's good. I like that. In your presentation, you talked about maybe individual countries might have a hard time collecting enough phenotypes, but when you go across and you create those collaborations, that's where the benefits and we can be better together. And I relate back to our world Angus evaluation work where we work with the Canadian Angus Association, the Australian Angus Australia, and that's really the goal. Once we combine those databases across those different countries, I think together we'll do better. And the two plus two become five or six or 10. So I second that math too.

Miranda Reiman (36:11):
We've maybe touched on this just a little bit already, but what do you think that we could take, and this is a question for any of you guys, what could we take and apply from the work? What could we copy from their playbook? What could we apply? As you were sitting there, what things were you thinking that might be low hanging fruit we could actually get at without an entire change in our production system?

Kelli Retallick-Riley (36:30):
Yeah, I mean, I've, I love listening to Christine present her work on the Resilient Dairy Project. It gets me jacked up. How can Angus be a hub in a bigger project like that and bring more people together? Because we talk about, right, how do we get into the commercial cattle industry, the commercial cow calf industry? Because obviously we have this large cohort of pure red seed stock producers that are creating phenotypes and are doing what they need to do, and they send in such good data for us to utilize. But how do we leverage our spokes a little bit deeper, not just with different people in the beef industry, but also who are our strategic partners? I think you said it best, right? The reason why this works is because you make sure you have the right partners upfront. And I think that's really important to make sure that at the end of the day, you don't get to a crossroads where it just blows the entire thing up. And so I think that to me always continues to, it was good for me to hear this one again today because it's always good for me to be reminded that you can find those right partners and you can work together and you can come up. Because ultimately, we all just want to make beef cattle better. Well, ultimately, you all just want to make agriculture flourish and see the next generation take over. And so at least that's what I'm passionate about. I don't know if that hits home to anybody else, Andrea, is that why

Miranda Reiman (37:41):
You work here every day?

Kelli Retallick-Riley (37:41):
I get excited. Yeah.

Speaker 5 (37:44):
I think that's it. And especially right as we go into now, it feels like the low hanging fruit of traits we've been selecting on and making progress on, but some of those more challenging, more expensive traits to measure that those are some phenotypes that it's probably going to come through some collaborations throughout the industry and across disciplines sometimes. And so I think that those partnerships will definitely be key as we continue to collect and especially those more hard to record traits for sure, more expensive traits.

Speaker 4 (38:15):
For me, it's really interesting because when I think about genomics and the opportunities that are made available through genomics, you don't need to have phenotypes on your entire population. Exactly. You can have phenotypes, really good phenotypes on a smaller number of animals, but still have the benefit for the rest of the group. And what else struck me was that traits like fertility or health traits or even efficiency or methane emissions, those are all traits that actually cross between beef and dairy. We might do it in a little different way, but it doesn't mean that we can't learn from each other and that we can't maybe benefit from the work that we see in other areas. So that part to me is like, oh, I was preparing my slides and I was like, oh man, I don't know what to talk about because we're not working on beef cattle right now, but we will be soon. And then I talked to a bunch of producers and I realized it is exactly the same thing. We go about it a different way, but it's the same DNA, it's the same genome even of the same bovine animal. We just have to figure out where are the synergies and how do we use them Optimum.

Kelli Retallick-Riley (39:26):
Absolutely. Well, and we have a relationship with lactate too, as we're trying to help them bring in our Angus on dairy values to deliver to their dairy producers so they can select better bulls for their beef on dairy segment. And so I think that's just one small, and obviously that's not a research collaboration, but that's one small way where where's our synergies? We have this large Angus database with a bunch of genotypes and pedigrees and information and data, and you guys have the dairy half, so it only makes sense to kind of come together and work on it.

Speaker 4 (39:53):
We're actually going to start collecting some beef on dairy carcass data as well with genotypes, I think about 8,000 animals. So that should be really, really useful as well. Really beneficial for sure. For reference populations.

Miranda Reiman (40:05):
And you mentioned everybody does it a little bit different and whatever, but the final thing is the profit, right? Absolutely. We all have that same goal. You shared some economic impact slides there at the end, and I didn't, you went through them so quickly. I didn't get a chance to write it down, but I'm hoping you remember exactly what was on those

Speaker 4 (40:22):
For sure. So what we saw before we implemented genomic selection, we were already making through the index selection based on pedigree information. We were probably making monetary genetic gain of about $50, $54 per cow per year benefit. So every year they would earn $54 more, which is pretty good. But after incorporation of genomic selection and with the results of these new projects that we've been working on, we're up to $148 per cow add management onto that. And the benefits that you can glean from doing a good job and you're back up to something that you can be really proud of, and that is indeed profitable, and who knows what the government has planned in terms of carbon credits and all of these additional aspects that people are going to have to start dealing with. So I think in order to place ourselves at the poll position for the future, we really do need to be very aware of what this costs, but also what are the potential genetic, monetary benefits that we can offer to our producers, because really they are the ones who are doing literally all of the work.

Kelli Retallick-Riley (41:34):
Yeah, absolutely.

Miranda Reiman (41:35):
We wouldn't be here without them. So we always end on a random question of the week. So random question of the week. This is the best part of our process. I'm going to give you guys a softball one. If you could wave a magic wand and solve something with genetics, some challenge that producers have today, what challenge would you like today? You could solve it.

Speaker 6 (41:58):
Oh, that's a

Miranda Reiman (41:58):
Big one. I thought it was a soft bomb. You guys don't lay awake at night thinking about this.

Speaker 4 (42:04):
I do actually. She just has so

Kelli Retallick-Riley (42:05):
Many things she can't

Speaker 4 (42:06):
Choose. There's so many things. No, there are so many things. We're apart from this methane feed efficiency, fertility, health stuff. We're actually also doing work on homozygosity. So in the dairy industry, we've got a few genomic bulls that are being used really widely. And I would love for us to fully understand what is wrong with high levels of homozygosity, what causes detrimental congenital defects, that sort of thing. Because I think that's the achilles heel of livestock. If we know that intense directional selection could cause some problems down the road for us, we have to get ahead of that and make sure that we've got a system in place to manage that. Because nobody wants to have a sick calf born. Nobody wants to deal with ill animals. And the more work that we can do to avoid that, the better.

Miranda Reiman (43:03):
Perfect. That's a good one. Yeah, right. Andre?

Speaker 5 (43:05):
Answer. Okay. Sum up. So I'm going to go the route of disease resistant traits a little bit different from the genetic variation or the kind of inbreeding consequences of selection, but I think disease resistant is really challenging in any different species, really, right? Because they're kind of difficult phenotypes to collect, and sometimes the incidence is very low, but still very important. And we want the animals to be helped. So if I have some magic that I could use, I think disease resistant traits, I think that would be my pick. Of course, since we don't have magic, right? We'll go about the genetic evaluation, use our brains. I suppose we'll collect the phenotypes and come up with genetic evaluations to improve those traits as well. But yeah, that's a good one too,

Speaker 4 (43:54):
Right,

Kelli Retallick-Riley (43:54):
Kelli? Well, I mean, he just took the whole gamut of disease resistance. I was just going to say BRD, right? I think awards would be given out if we could solve BRD for sure, especially in the beef cattle industry here in the us. We know when you look across our segments, that's the number one disease that we're fighting every single day. But I will say that is a little bit of a caveat. I would say solve BRD without increasing, right? The prevalence is something else. As we solve one thing, we don't want to necessarily make something else worse. And so that's the other tricky part about disease, right?

Speaker 5 (44:23):
Yeah. Not giving up any of the progress in the other traits, which is breaking those antagonistic relationships. That's the challenge sometimes.

Miranda Reiman (44:32):
Well, that's of course the number one I've spent so much time at feedlots in the early part of my career was certified Angus beef, and that was their number one challenge then. And it's still our industry insight survey that the Angus Beef Bulletin team did. That's still the number one profitability, whether they win or lose on that scale, along with when they're picking which calves they're going to buy. So I think that's so tied to the economics as well as the labor factors, as well as, so that would be mine too. I know you didn't ask what mine would

Kelli Retallick-Riley (45:01):
Be. I was going

Miranda Reiman (45:02):
To ask, but you already answered, so that's good. You knew that I wouldn't have a magic wand, so that

(45:07):
Untrue. Well, we actually have to let Christine get back for questions because she's needed on the main stage probably at some point in here. So thank you so much for taking the time to visit with us. Andre, thank you for all the work that you and Kelli's team do on behalf of Angus Breeders, and thanks for joining us on the Angus Conversation. Thank you so much. Thank you. Thank you. Is always fun to think about the future, but if you want updates in real time, be sure and follow us on social media. The Angus Journal team is on Facebook, Instagram, and X. And if you see us out and about at events, be sure to stop by and say Hi. This has been the Angus Conversation and Angus Journal podcast.