Hello. Welcome to the fourth of the six webinars scheduled for this year. This webinar is about amino acid balancing for lifetime performance. It is about herd longevity, advantages of involuntary culling and herd structures dynamics. It is really my pleasure today and a treat for everybody to hope to have Dr. Victor Cabrera with us. Victor was born and raised in the Incas land of Cusco in Peru. He received his master's and Ph.D. degrees from the University of Florida in 2006. Victor accepted the position of assistant professor and extension in dairy specialist with the New Mexico State University in 2008. Then he joined the faculty team of the Dairy Science Department at the University of Wisconsin in Madison. Victor since then was promoted to full professor in 2018. Dr. Cabrera is focusing his extension and research programs on dairy farm economics, decision making tools for improved profitability and sustainability. During his career, Victor has authored or co-authored more than 70 peer review publications, nine book chapters, 60 extension publications, more than 80 proceeding papers. But most importantly, he developed more than 40 tools for decision making strategies. These scientific tools are improving dairy farm profitability and environmental stewardship and long term sustainability of the dairy companies. It is a pleasure for me again to introduce Victor. Victor the floor is yours to start telling us all of some of those tools that you have been developing over the last few years. Thank you very much. Dan, I really, really appreciate the opportunity and the invitation and share with you this anniversary of Adisseo. We have been collaborating with Adisseo for years now. And I know Dan from many projects from years, and I have been glad to be able to share what we have been doing here in Wisconsin in my lab, as he has told, thanks for the introduction. My lab, basically developed tools for Decision-Making on dairy farming. So if you allow me, I will share my screen now. And give you a little tour of the center, what I consider the center of this decision support tools that have been mentioned by Dan. And now I'm going to give you a little more detail. So this is the data management website hosted at the University of Wisconsin, Madison. It has been alive for, I don't know, nowadays, like 14 years. And it has a section that it is the center of the website. That's the section of the tools. And as Dan mentioned, there are tools in different areas of management all the way from feeding to raising heifers or replacement decision making or reproduction production, even genomics, some health. And for example, the latest we have released very recently, actually this week is environment dairy print. This is a very nice tool that shows basically what is the greenhouse gas footprint of dairy farms according to different management strategies. But today we're not going to talk about that. I just want to give you an idea of all what's available and invite everyone to visit and explore. This is openly available to anyone and all the tools are free to use to anyone. So today as the title says of this very nice conversation we are going to have with Dan, is advantages of involuntary culling and herd structure dynamics. And so I want to share with you a couple of tools that I think are critical in that decision making of dairy farms. So if we go here to tools, as I mentioned, there are all these different sections and I'm kind of go just for now to the production site and I'm going to concentrate for a few minutes about the milk curve fitter, which it is a very interesting and very useful tool that shows to dairy farmers or decision makers. What's the potential projected lactation curve of dairy cows. And that, as we know, is very important for many decision making, whether it is reproduction, replacement or simply to have a projection of the net return we expect by lactation, by cow, etc. I'm not going to go into the details. What are the functions we use, but just mention that there are different models out there. One is the MilkBot, another is the Wood's Model. Probably the Wood's Model is the most widely known model for lactation curves in dairy farming. And those two are available in this tool. So the main idea of this tool is to be able to the farm, enter their own data and produce a curve like the one you are seeing here in blue. So the dots would be the data points that the farm provides at different stages of the lactation curve. Or the days, postpartum or days in milk. So those would be the orange dots. And then the blue one is what's the predicted lactation curve? If we assume these dots come from a group of animals that, for example, are in the second lactation, we can safely say for this farm, based on this data, I would expect this lactation curve for the cows in the second lactation. I can do that or I can do also specific lactation curves for every single animal. And as you will see now, this is going to be very important for many things, like, for example, to predict what's the daily milk production throughout the lactation. Right. But also we can test the model parameters and we can select here the units we want to work on, whether it is in pounds or kilos. Let's leave it in pounds because probably it's more useful for dairy farmers in the US. The model, let's leave it in the MilkBot Model. But we could change to the Wood's Model and you see there would be a little change there. Let's leave it in the MilkBot Model. Sometimes one works a little better than the other, but both are very good models to represent the lactation curves. And then we can also change the language if so desired. Okay. But one thing we can do, for example, very simple here is if I put the lactation production between day one and let's say day 305. So it's going to mark for us all this time of the lactation curve and it's going to aggregate the production during that time. For example, 25,504 pounds is expected to be produced by this cow during this lactation and under these conditions. If we expect that the parameters will change based on better conditions. If we have an additive that will promote better production, like, for example, some amino acids that will be provided with the diet, maybe we have some data from research that kind of tell us instead of being 121 here because of the data itself, it will be 125. You can see how this number will change and we can quantify how much more milk we would expect during that lactation. Also, we could change other parameters and see how that plays off. But for now, you get the idea that basically these type of curves and as you will see later, it relates to some tools that are already available and developed by Adisseo as well. That we can safely and I would say scientifically, solidly, we can estimate what those changes will represent in this case in the amount of milk. And we know that's heavily related to the profitability of the farm. This will drive the dry matter intake and both will drive the income over feed costs and that will be a big part of the profitability of the farm. So that's one tool to keep in mind. The milk curve fitter. Actually with this tool we can do another thing is explore the best pregnancy timing. We can know how much milk we will expect and what would be the milk income over feed costs like here, for example, depending on when the cow will become pregnant. But that would be a topic for a different conversation. Now I want to go back here and find another tool that is in the area of replacement or reproduction. Let's find it in replacement. And this tool is called the economic value of a dairy cow. And this tool has also been incorporated or connected with that tool that you're going to see later, developed by Adisseo, in collaboration with us. So let me open this tool and I'll give you a brief introduction what this tool is about. As the name says here on top, the economic value of a dairy cow will calculate basically the projection of how much net return I would expect from a cow in the very long term. And it will compare this value with a potential replacement. So the main idea of this tool and it is published if anyone has the interest and the time to read a paper. You will find additional information what the tool is listed in the tools section of the website. So in this tool, as I was telling you, basically depending on when the cow is right now, for example, in this case third lactation, five months after calving, and one month pregnant. We can compare this net return with the potential replacement. And in this case, for example, we know this cow will have 627 more dollars than a potential replacement. Now, if this cow that's pregnant becomes non pregnant, loses the pregnancy like aborts, for example, the value will decrease and you see the value decrease to 414, which is $213 less. And we can say safely that the value of a pregnancy loss or the cost of a pregnancy loss is $213 for this cow in this specific situation, under the herd production variables and the herd economic variables as well, all the yellow here are input variables that the user defines. So that's very interesting and very important because these quantifications, these estimates are heavily required for decision making. And I know many people are hungry to get these estimates the best possible out there. So this tool basically projects these curves that you can see down here, you have in blue here the actual cow. So I have in this case is a third lactation cow, five months after calving, and now we made this cow non pregnant. So this is what I would expect probabilistically in time from this cow, the blue one and the red one would be the potential replacement. So every time we are comparing whether we keep the cow or we replace the cow and we make a difference day to day, or month to month, all the way to the very long term. And when we do that difference, it happens. That is for $414, it's positive. So it's better to still keep the cow and keep breeding and hopefully will become pregnant if we keep this cow for a long time. And she's not getting pregnant, the value will start decreasing more and more, as you see, and at some point it will become negative. And when it's negative, it means I'm better off replacing this. That's very interesting but that hasn't been directly connected with the tool you're going to see in a moment. What is connected actually is the second part here that you're going to see in a moment. It's very important and very nice as well as a decision making tool. What happens is in order to do these projections, as you can see here, we are simulating all the probabilistic life of a cow or a potential replacement. Since we do that and we do that for all the cows in a herd, actually we can have an estimate of what is the net return of the average cow on a herd here as an additional calculation in this tool. I will highlight this to see it better, the economics on the average cow in a year. So for example, here, this value is $1969. So based on these characteristics of the farm and the herd production and reproduction variables, we expect that a cow will give us net return of $1969. And that's the sum of all the factors that you see below here. Milk sales, the feed cost, that's negative, etc. You see there the point I want to make here is that this value here is heavily responsive to the economic variables and to the herd variables. And therefore we can use this to estimate and to study what is the value of changing, for example, the reproduction of the herd in this case, for example, the 21 day pregnancy rate happens to be 18%. That has been defined by the user. Let's say the farmer says, I know historically my pregnancy rate is 18%, but I would like to have it at 25%. So I'm kind of invest on new devices for heat detection. Or maybe I will do a little more aggressive synchronization together with the heat detection, etc. And I expect I know that this will jump to 25%. So I can change this. And when I change, I will look at this number here and the change on that number. So if I put 25 now, this number jumps to $2024 (net return). So this is like $40, $65 more for seven percentage points better pregnancy rate. So again, we can say the pregnancy rate can be improved by better synchronization or heat detection programs, but it could also be improved by an additive I put in the diet. If we have the knowledge and the research that indicates that, and then we can use the tools like this to calculate what's the value of that change. Same thing if I have a pregnancy loss. And in this case, look, it's pregnancy loss after 35 days. Because that's normally the time around the time when we check the pregnancy for the first time. And if this is defined 22.6%, for example, which is it happens to be an average of Wisconsin a few years back. Let's say by using an additive, an amino acid additive, for example, we can decrease this because we know that could happen. So let's say instead of 22.6%, this will be 15%. And let's take this number once again when we do the change. So if I put 15% here, you see this has jumped even more to $2045. So I believe that's $21 more because of that decrease of seven point something percentage points, lower pregnancy loss on the cows that became pregnant. So you can see here there is a lot of scientific background behind that indicates that. But for the user, it's very simple to do this kind of analytics. And this is a very sick way to move to the tool that has been developed by Adisseo that uses these concepts and aggregate these concepts to give a good idea of what's going to be the value of using this specific product. Victor, as you mentioned, we have been working on this project and a couple of projects for several years now. And the first time I saw this tool, I thought it was pretty amazing in terms of all the calculations behind it. And the particularly, I mean, if you share back your screen because what I want to call the attention of the viewers on, at the end of the day there is an impact on the economic. But it has a whenever you change these, either the pregnancy rates or conception rates or pregnancy losses, you really have a tremendous impact on the herd dynamics in terms of how many first lactation cows you will have second lactation. And at the end overall, that impact, this very simple value that you show here, you are not I don't think you are very fair to all the work that is behind here that you did here because it ends up in a very simple number. But this number is so complex in terms of taking into account the impact because when you lose cows, depending when you lose them in the first, second or third lactation, you will have more or less this changes, the impact of the herd dynamics. And of course, we know that the milk production of those cows changes. And you have all of these numbers into consideration in this simulation program, correct? 100% correct Dan. Thanks for bringing that up. It is very interesting because this tool and actually, if I remember well in the publication, which is in the Journal of Dairy Science. It says in the first paragraph, I mean, this research contributes to both the scientific knowledge as well as the practical decision making. And I concentrated somehow when I was showing these numbers in the practical side, many times when when we talk with practitioners, the dairy farmers, the decision makers, they want to the final number and somehow they trust the researcher that has put all the best behind it. And a good evidence of that is the research paper, for those of you who would like to see more details. It's exactly right what Dan is saying. I mean, it becomes very complicated very easily because we need to follow all the probabilistic stages that a single animal moves throughout their life. And this is controlled but for what's called the transition probability. So every single cow has a risk of becoming culled out of the herd or die at any point in time. And we need to account for those. Any single animal has a probability of becoming pregnant. We control to certain extent that, and that plays a trade off with the culling rate, for example. And then the whole population dynamics changes constantly. And we need to assess the value of all that when we reach certain level of stability that we call steady state of the model. So we have behind a model that's called a Markov chain and we control all the processes through the Markov chain processes. And it's pretty amazing, another point to make here is that obviously these numbers relatively change according to the overall level of milk production of your herd because here you are obviously you are modeling on an average of 24,000 pounds and rolling average of this herd. If those numbers, if that herd goes to a 28 or 30,000 rolling her averages that you find many of those particularly in the Midwest. The impact of changing small percentages changes drastically. That change and quantify what's the impact of that, so if we look at this number here and then we put 30,000, we need to do this, it's very interesting. It's telling us that the Do-not-Breed cow needs to be increased. I will explain more in a moment, but I will change this number for now to 53, as is suggested there. And then you see the number here has jumped quite a bit. So there is a lot of value on that in this specific case, it will increase our income or feed cost even though we're going to be investing more on on feed on those animals. The difference the margin will keep increasing. And then we have $2,700 per cow per year of net return. And we started with less than 2000, for example. And obviously this will will have some interaction with some management strategies we will have like using of additives or if we have a better reproduction program of that will improve the health by any means that will also be represented and, and captured in this number here. And just quickly, just to mention why it was giving us a little error here was the fact that we control the last time of breeding the cows depending on the milk productivity. And so when we have such a big production here, it does happen that we literally run out of dimensions on the model because there are cows that keep producing and there is no space for those to go. We need to call this those animals even at £53 producing and they are not becoming they they are do not breed and they should leave and and they are leaving at a higher production rate in order to just to keep consistent this the model itself. And there it is one of the real values of this tool because sometimes you say, okay, I have a cow producing, you know, 53 pounds of milk, but it means that, if you want to keep this production or you want to increase your production or you're going to keep this level, that cow has to go, very hard decision to make rationally. But the model tells you, this is what is happening, which is very hard to actually encompass in when you see that cow producing 53 pounds of milk. But this is what the model is telling you. So this is the beauty of this tool. And to build up on that concept, Dan I think that's a very good point you make there. We can easily convert this 53 pounds of milk to dollar value, right? At any price of milk, $20 or whatever. And we can compare that price with the feed cost and it's very likely it's making money discount. So I have heard this argument and say I shouldn't cull a cow that's still making money on my herd, but I will counter-argue that position, saying that we are talking here about a whole system of production. And we need to make sure every of our elements of production and in this case our cows are the best can have at any time. And what is telling us at that point is we are better off bringing a new animal into the herd. Well, Victor this is perfect for the purpose of highlighting the importance of the tools that you are developing and continue working on. I just learned today that you just told us about this new tool that you just unleashed today about the environment. I will take a look at that. That's news to me. I will take a look at it whenever I have the time. So it's very nice. It's a very nice tool. Wrapping up in terms of what we were evolving before, Adisseo has been challenged over time by many users of our product line and say, how can I give value to this nutritional aspect and nutritional tools that we are using? And essentially, this is what, when I went first and approached Victor and say, Victor can you help me out in terms of putting all these things together in one simple tool, and this is what we develop over time in terms of in terms of what we what we evolved along with Victor actually, without his help, we would not be able to have done any about it. To put it all together a few years ago, back I went to see Dr. Cabrera and said, Victor I saw your some of your tools that you have been involved and they are fantastic. Is there a way that we can put all this together to give this simple value, cash value to this? We had been collecting over the years the impact of feeding any nutritional program that you may have look specifically of course for us it was about amino acid balancing. But any nutritional program that you use in your herd and that we did have good information, relevant information in terms of the economic value of when you increase milk production or milk composition, which is the short term effect when you apply nutritional balancing to the relations. Now with you, we did know that we had a little longer term impact on the herd in these reproductive parameters that we just discussed in terms of health, productive, reproductive, and herd longevity. And we were lacking that tool. With the help again of Victor using these very tools that he just showed you, we just put a program together that actually encompasses all of those things. And just simply show in a sense all those things together. First it's very simple, it's okay if I implement any nutritional technology in this case, of course is focused on amino acids, but anything that you can look for, you will have an impact in the cost of the feed because you are investing some money. Your cows either consume more or you have extra costs because you put in these implemented technologies. Well, they do have an impact on milk production and you can speculate or actually do it afterwards how much that technology actually made the cows produce. And this is the pink or the red color there, that you have an impact because you increase milk production and composition. The third part is the yellow part is essentially what the the model that Victor just showed you in terms of the impact on the herd dynamics when you increase or decrease culling rates and reproductive status of the herd. And the last part is about health. So each one of these had a little number. When you add those up, it gives you a final dollar value to these implementation. And these are essentially, you know, they are simulation tools that you can use. The science behind it is extremely solid but they are simulation tool tools is still and it's just help you to make a final decision at the end of the day like any of the tools that Victor just showed you. So thank you, Victor, again for spending the time with us, showing some of your tools. And I will look into your this last tool that you just developed. Thank you very much. Thanks for inviting me. I mean, this is a great to share. And at any point, if anyone I mean, this is the last thing I will mention, go visit once again, this dairy management website at the University of Wisconsin, Madison. All the tools are openly available free to use. If you have any questions, don't hesitate to contact me. Most of the tools have a paper behind, so there is a documentation which is very helpful at the time of using it. So the other thing I would like to mention to our listeners and viewers, because I believe this is a video podcast, right? So and all these parameters and all these tools we have seen are certainly related heavily to the lifetime performance of the animals. For example, the tool we have seen the economic value of a dairy cow, are being calculated based on the performance of an animal from the first day that she starts their productive life all the way until she leaves the herd. But not only that, it goes beyond because normally a cow will have occupy a spot on the herd. And that spot is being followed throughout long, long time. So if a cow leaves for any reason that's not voluntary or even if it is voluntary, we will keep track of that spot on the herd that is producing economic value so we can do the analysis per spot on the herd and per cow for the total lifetime. So all these parameters we have seen like the culling rate, the reproductive performance or the health of the animals will have a huge connotation on the lifetime performance and profitability of all the animals, and both tools we have discussed today. The lactation curve would be very important to calculate that and the economic value of a dairy cow will include and encompass and englobe a large number of variables that will calculate very well that lifetime performance and profitability of animals. Thanks, Dan, and I mean thanks also for this tool that you developed and use the concepts and some tools that we show which are behind this tool as well.