Thanks very much for joining us to watch this webinar. Jessica and I are gonna cover benchmarking the future of your dairy herds post weaning to first lactation. A little introduction about Jess and I, so Jess is my colleague at the University of Nottingham.
She graduated in 2017 and then spent time in mixed practise and farm practise before coming back to the university to complete her residency and master's in dairy herd health and production. She's a European and RCVS recognised specialist in bovine health management and is currently a clinical assistant professor at the University of Nottingham. Her subject areas of interest include young stock management and dairy fertility.
For myself, I did in 2013 and spent some many happy years in production animal practise in Shropshire in Derbyshire. I then started doing my Cert AVP and swiftly moved over to doing my residency at the University of Nottingham, which I finished in 2022. Again, this afforded me European and RCVS specialist in bovine health management.
I am a clinical associate professor at the University of Nottingham. And my interests include career choices, non-technical aspects of successful farm careers, as well as clearly the Nottingham herd health approach. The learning objectives that we're gonna cover with you today include feeling confident with an approach to communicating with clients on the topic of post weaning heifer performance, being comfortable with which data sources are available on farm for post weaning heifer performance monitoring, and how to both assess the quality of these and advise the farmer on collecting these data appropriately.
Be aware of literature targets for daily live weight gains and be able to formulate farm specific targets based on individual farm management. Be able to use production and fertility performance indicators to benchmark heifer first lactation performance, and be able to apply these examples outlined to your own farms and create an individual narrative for your clients. Thinking about the literature for young stock then, do farmers perceive there to be an issue?
Well, there was a nice paper published by Bobby Hyde in 2020 and the team here at Nottingham that looked at pre-weaned heifer mortality, and they found that actually it stayed at approximately 4% for the last 10 years. When they looked in further detail, actually there was a significant difference between dairy and beef calves. So dairy calves experienced a significantly higher 3 month mortality rate at around 6% compared to non-dairy beef calves at just under 3%.
There were sex differences, so maybe unsurprisingly, male calves had a higher mortality rate than female calves across the data set. There was a timeline aspect, so out of all of the historical on-farm deaths analysed, roughly 25% of those occurred within the 3 months of life. So of all the deaths occurring on farm, a quarter of them were in calves less than 3 months of age.
And then they looked at avoidable deaths and actually they looked at matching the mortality rates against the best environmental conditions and the optimal birth months that they've calculated within this study and realised that actually by applying these, then potentially there would be the opportunity to reduce deaths by 37.500 per year. So that is a significant number of calves.
Looking at the study done on by John Mee on demoralising poor dairy young stock management and dealing with farm blindness, actually what he identified was that there was a desensitisation out there, and what he meant by that was that there was an accepting of the abnormal as normal. There was a failure to know the true in instances of morbidity and mortality, a gradual decline in health, making it less noticeable, and an underestimation through the inaccuracies of detection and recording. And there was a cognitive bias, so underestimating the pain and the economic loss of issues blending into the daily routine.
And we've seen that highlighted in research in other areas such as lameness. The other bit of literature that I'd like to draw your attention to is the work done by Ilana Bolton and her team. She did an empirical analysis of the cost of rearing dairy heifers from birth to first calving, and the time taken to repay these costs.
So what they did is survey 101 dairy farms, and they looked at the cost of rearing heifers from birth to first calving in Great Britain. Including the cost of mortality, investigating the main factors influence these, and the costs across different farming systems, and how long it would take the heifers to repay this cost. And what they found was that there were inefficiencies and variations between different farms across Great Britain.
Where does the vet come into this then? Well, unfortunately, there are several different pieces of literature out there that identify that effective change is sometimes hindered by veterinary surgeons. And what do we mean by this?
Well, actually, things that have been identified in the literature include monopolising the conversation, using overly technical and non-accessible language, aligning with other ag representatives over your own clients, so this might be other paraprofessionals on farm. Framing of barriers differently, and a less practical on farm approach, and then not engaging with data collection, processing use, and hopefully today we're gonna make that a little bit more accessible for you when it comes to young stock management. One of the quotes from Elana Bolton's paper that I thought was particularly relevant for the discussion that we're gonna have today, I've put on the slide here.
So a one figure fits all approach is unrealistic and unhelpful to dairy farmers when they're comparing their own cost of rearing against what is considered to be an industry average. And this is further by the conclusions from John Mee's paper, which, where he actually identified that external auditing, i.e., bringing in the vets and data tracking to catch performance drops, were really helpful for avoiding this farm blindness.
How do we formulate an individual approach then, and what support is there for that in the literature? Well, actually, Jansen and Lamb did a really lovely paper a few years ago that was looking at the role of communication in improving other health. It was a Dutch study, so not performed here in the UK but it aimed to understand the dairy farmers' behaviour and mindsets regarding other health management and actually how to describe the efficacy of various communication strategies.
And what they highlighted within farmer mindsets was that actually we needed to establish whether there was a perceived threat and what the perceived efficacy of this was. In order to do this and to be effective, then we needed to give more than just technical information, we needed to integrate these communication strategies into our information delivery. When they were thinking about perceived threats, then what they said was that farmers only acted when they viewed mastitis as a genuine personal and economic risk to their herd.
When they talked about perceived efficacy, what they meant was adoption of best practises, depending on whether the producers believed their recommendation tools from their vets would work specifically on their farms. So they combined these mindsets to actually. Create a pattern of action, a call of action for the clients to preventative behavioural changes and actually getting that effective change there.
They typed their farmers into 4 different types, and these were proactivists, do it-yourselfers, wait and seer, and reclusive farmers. Ritter and Al's team actually then took this a little bit further and applied this health belief model that was formulated by Jansen and Lamb into another pharma typing system, but this time used on Yoni's disease. And actually the object of this study was to assess perceptions of farmers participating in Yoni's disease prevention and control programmes and explore the factors that influenced whether or not the farmers adopted these risk reducing measures and change for transmission.
And they categorise their, their farmers as proactivists, unconcerned, disillusionists, and deniers. The proactivists were our clients, the ones that we absolutely loved spending time with, because they were accountable, they were engaged, they acknowledged the responsibility for what was occurring on their farm. They stayed on top of things and they liked to be well informed, and they made changes as soon as they were able.
Their own concerns, so the clients that believed in the proposed strategies, but just didn't think that Yoni's disease was important, had decided that this issue wasn't a priority for them. They acknowledged the management strategies, but they didn't make the changes. The disillusionists then thought that Yoni's disease was important, but they didn't believe the strategies proposed by their veterinary surgeon.
So they were interested in the available research, they wanted guidance from their vet for these management decisions. They were well informed, but they criticised the feasibility of the suggestions and them working on their farms or them being able to complete them on their farms. The deniers then were often frustrated with the industry and very resistant to change, so they were the people that didn't believe in the proposed strategies, and they didn't believe in the importance of Yoni's disease.
And I think thinking back to this and the Jansen and Land model, we can all probably all imagine clients that fit into these categories. And what this does is. It explains that actually decision making with regards to these big hood health approaches require more than just rational decision with the technical information that we deliver, that there is a social element and a psychological element built into this as well as that technical element.
Looking at motivations of farmers, then Bhuval and and their team did a paper called Understanding Farmers' behaviour and their decision making process in the context of cattle disease, and they did a review of the theories and approaches available. And they utilise the comp B model which we'll go into in a little bit more detail in a couple of slides to categorise behaviours into reflective, so those that are conscious evaluations and plans and automatic motivations, so those that are habits and emotions. The reflective motivation components had a conscious element, so deliberate consideration of the pros and cons of an action, as well as a planning and intention element, so goal setting, self-conscious decisions to act based on perceived values and beliefs, and you can see, looking down this list, there are a few that are perceived risk, perceived cult control, perceived efficacy of measures, perceived practicality.
Job satisfaction, sometimes one that surprises people but has big impact. Being by pharmaceutical companies, perceived time, normative beliefs, and perceived customer education and good farmer identity, which I think we can probably all agree has become a much bigger component of farm vetting and farming in the UK. Automatic then, actually we've said they were the habits and routines, so behaviours that performed routinely without active thought, emotional impulses and responses, so unconscious reactions, desires, visceral feelings driving daily practise.
So so much more there than just this financial aspect to farming. Thinking about Proshka and de Clement's, stages of change, this is a model that was put forward in 1977, but it's still very relevant, it's still discussed today, and actually it discusses five different stages of behavioural change. So if we start at 12 o'clock and work our way clockwise round, then pre-contemplation is the first stage.
So the person has no intention of changing their behaviour or attitude. They don't think that they've got a problem. Moving forwards then we have the contemplation stage, so the person has an awareness of the problem, but they lack the commitment, the intention, or the way to implement behavioural or cognitive change, so they're not doing anything about it at this stage.
Next we have the preparation phase, when a person has desired to change and looks to implement it, and I would say that this is most often the stage that our farmers get us involved with, although there's a definite argument that we should be getting involved earlier on in this cycle. Next we move on to action, so when the person takes the steps needed to achieve the change, and then finally our maintenance, the person is continuing to carry out the behaviours needed to maintain and enhance their change and prevent relapse. And the idea of relapse is the 6th stage that isn't projected in the cycle because really it would be arching off to the side because we want to avoid, Relapse, and that is why this maintenance and actually our repeated monitoring and coming back to these clients, even after we've put these changes in place is so, so important.
I said that we'd come back to the com B model, so this slide demonstrates that for us, and you can see that it's a Venn diagram where capability, opportunity, and motivation all overlap to create our behavioural changes. So when we're discussing capability, what we're talking about is, are our clients able to do it? Do they know how to do something?
Have they got the knowledge and the skills and the stamina to be able to put those changes into place? When we talk about opportunity, we're discussing, does the environment allow them to do it, and by environment, we're talking about the social and the physical environment. And then have they got the motivation?
Do they actually want to do it? Are they making reflective plans? What are their impulses and des desires?
What is inspiring action for them? What is motivating them to make these changes? And we can combine all of this information together to put some example behavioural change techniques in place.
So what do I mean by behavioural change techniques? Well, I've listed several on the slide here. We'll start with pros and cons.
So pros and cons lists are great for clarity and empowerment, but they tend to oversimplify, and they don't provide answers for how to actually action that change on farm. For this reason, they're really helpful in the motivation stage. They can be useful for decisional balance or self reevaluation in terms of determining that that change needs to occur.
And they can be very, very good for doing cost benefit analyses. Goal setting, so I've put smart targets here as an idea for goal setting. Smart targets are really good for turning intention into clear and realistic actions that can be monitored and to check that the desired change is actually occurring, so we, we're talking about making things specific, making them actionable, holding people accountable, and smart targets can be very useful for these.
Action planning, so we know that all farms have got a herd health plan, but actually, I think the action plans need specific detail, they need to be precise, they need time, place and frequency. They need how we're gonna implement these things on farm, not just that we should be doing them. Environmental restructuring, and what I mean by this is forming habits, so what already happens on farm that this can align, align with.
We know that our farmers are very, very busy, that labour is difficult to come by and costly, so how can we embed these behaviours into everyday routine that's already occurring on farm? And then feedback on performance, so as I said on the slide, looking at the behavioural change stages, this is so important. Are we reviewing and recording progress?
Are we achieving what we want to? Are we testing and adjusting accordingly and picking up if we are getting that drop in performance? Application on farm then is putting all of these things together, so considering our farmers' perceptions of the issue that we're talking about here, their perception of their young stock management, are they motivated to change and to have the best young stock management possible?
Can we combine that combi, that concept together to get effective change? And how do we achieve this on farm? Well, actually we need that individualised approach, that individual plan for each client, and we need to utilise the behavioural change techniques that I talked about previously.
But that requires confidence with the data. So the next few slides are gonna discuss actually what data do we need and how can we use it. Thank you very much.
So really as Emily has said, a fantastic overview of the context of what this kind of work can look like on farm and how it's really, really important to try and move things forward and actually affect the change from when we've done all of this work up. But where do we actually start when we're thinking about our heifer's journey from birth to first carving? So for me, it's a bit of a timeline, and we're really working through a lot of phases here from birth right through to first carving, trying to aim for our ideal age at first carving at 22 to 24 months.
But to actually get to that point, we've got a lot of phases that we've got to get right here. And some of these today is what we're going to try and unpack and talk about it in a little bit more detail. But why are we so bothered about first calving at 22 to 24 months?
Why is this our end goal? So a lot of this is from the literature. We're very lucky to have research from Ginny Sherwin within an hour group.
Also Etham over in the Liverpool group, and then Alex Back's group in Europe. And all of these, research groups have told us that heifers that calve in at this age are significantly more likely to survive their first lactation. They're significantly more likely to have a reduced somatic cell count and also very interestingly have an increased daily average lifetime yield, and this is quite significant, so we're talking 15 kg a day, average lifetime yield compared to 12 for those heifers that actually managed to carve in at the right time.
So it goes without saying really that every day over this age of first calving bracket that we want them to be in will cost our clients. And actually, the Bolton Group that Emily's already spoken about over at the Royal Veterinary College have done some modelling work on this over 101 dairy farms. They've taken into account all of the costs of rearing and a cost of production, and they've estimated that it will cost our clients on average around 2 pounds 87 a day for every day that our heifers don't calve in that age at first calving bracket.
So, There's a lot of economic gain to this as as well as some of the other aspects that Emily's spoken about. So when we come to thinking about benchmarking this process, again, another lovely timeline from me, but today we're going to start from the post weaning process onwards. And there are indeed many aspects that we can benchmark.
So today I'm just going to focus on a few of these that are particularly important. We're starting off with daily life weight gain. This is something that we can look at throughout the lifetime of the animal from birth to first calving, but of course we're well aware that a lot of people will focus their, their weight and their growth analysis really on that first pre-weaned period.
But if we look in the traditional literature, if we look for targets for this, we would have typically talked about aiming for an industry recommendation of this linear rate of growth. So trying to grow at 0.8 kg a day from birth to first calving and that landing us at the kind of ideal weight for that first calving.
However, we now know that this is not economically the most viable approach, and we know this does not make the use of some of those epigenetic relationships with management that we will see in calves and young stock at different life stages. So what I mean by this, and this is a lot of this is from Alex Back's research group over in Europe, that actually calves in this early life stage from sort of early birth right through to just after post weaning phase, they're really, really efficient at converting their feed into energy. And so we can measure this by looking at something called the feed conversion efficiency ratio.
So this is basically how many kilos of dry matter intake can a calf convert into lean growth. And although this may not look great to you, this is actually pretty good, as you will see as we carry on this slide, that early on in this early first few months of life, we can achieve 2 to 4 kg of dry matter intake going into 1 kg of lean growth. So calves are really, really efficient.
So in terms of cost of growing calves at this point, it's actually a really good time in terms of cost of kilo of lean growth put on that we actually put some money into these guys now and actually try and push them for growth. So we would suggest a kind of a new target of 1 to 1.2 kg a day for these younger animals to make the most of this efficiency of growth at this time point.
However, there are also some important epigenetic relationship accelerated feeding, particularly at this point of life that we need to think about. So we know from other work that around 5% of our heifers' future milk production in their first lactation, so that can be as much as 400 litres, is as a result of early life growth and development. We think from research that this is something to do with metabolic pathways being turned on in the mammary gland, increasing the amount of oestrogen expression.
So it is actually from an economical perspective as well, in terms of future performance, well within our wheelhouse to try and push for accelerated growth at this point. However, and there's always a but, isn't there? As our animals get older and they move from being transitional ruminants to full ruminants later in life, and I'm talking about when we really head down this sort of teenage phase right up to 1516 months, our feed conversion efficiency will drop significantly.
OK, so really from sort of 4 to 1 down to 7 to 1. And therefore our daily live weight gain targets will decrease. It's not as economically viable now to push our animals for that increased growth.
It will take more feed to achieve that same 1 kg of lean growth. But also in terms of efficiency, it's perhaps not as sensible, so we know that our calves have a propensity to develop at least 50% of their frame and their lean growth in that 1st 6 months of life. This will decrease significantly after puberty and certainly under the influence of progesterone whilst these guys are pregnant.
So lean tissue deposition when we're pushing these animals for growth later on is not as likely. It's much more likely that they will deposit adipose tissue. If we're going to put some targets on weights and body weights, we're really looking for around 60% of mature body weight at bulling and a little bit more than at our first calving.
So just, you know, leading up to that first calving in the 18 to 24 months, you know, just when we're really ready to drop, again, much less feed efficient now. So really going from 7 to 1 down to 15 to 1 in terms of feed conversion efficiency. So really at the level that we will see our mature cattle, you know, continuing on at.
So in terms of our daily life weight gain targets for this particular age range, again significantly reduced, you know, this is not the time to be pushing these animals and again we will see deposition of adipose tissue if we do. So if we are to benchmark their body weight at this stage, we should be aiming for around 90% of mature body weight. And of course, as we'll talk about at the end when we talk about the sort of data that you need for this, clearly we need to know what mature body weight is to be able to benchmark our animals.
So that gives us a bit of a an idea top down about what we're looking at in terms of weight and growth. But there clearly are lots of other things we can benchmark too. So we're already pretty good at doing this as in as clinicians, we can benchmark disease incidents, particularly in this kind of teenage phase when we tend to see more of it.
We could also benchmark body condition score, and this is a really sensible thing to do, particularly with those changes metabolically as animals get older. And we can certainly do this really from around the time of puberty, iteratively leading up to our first calving. As for mature animals, we can also benchmark and analyse fertility data so we can see are our maiden heifers actually getting in calf, and if they're not, why not?
And that's relatively simple to do. But as a nice top down set of measures for this whole process, probably our biggest benchmark to look at is actually when are these guys carving in. So looking at a distribution in a histogram is normally ideal for your cohort of heifers rather than just looking at an average and seeing, right, how many are in this golden 22 to 24 month window, but where is everyone else?
What's our highest, what's our lowest, and, and what's our range. And then related to this is a really nice metric from Alex Back's group again in Europe, this idea of rearing efficiency. So what percentage of those animals that were born on farm have then actually carved down at that 22 to 24 month bracket, and we're wanting more than 85% of them to do that.
So that would be reasonable performance. Certainly if we're heading at, you know, 8, 92% or more, that would be excellent performance for this cohort. So that's our younger animals, but then when we think about our first lactation heifers and beyond, really we're trying to benchmark production based metrics.
So we can benchmark fertility. There are no real targets in our literature for first lactation heifer conception rate, but certainly within the Nottingham group, we talk a lot about aiming for around 10% points higher than your average mature cow conception rate. And this gives us, you know, the idea that our heifers will mirror their performance but should be significantly better.
We can also benchmark first lactation milk yield, and this is really simple to do, you know, most of our farmers that we're working with now are milk recording, and we can look at this on most softwares, and it's actually very know often that we find most people managing our ideal target. So we're aiming for, you know, a target of around 80% of our mature cow, 3 or 5 day milk yield for our first lactation heifers. Certainly if they're less than 70%, this is a significant concern and this would normally direct us that either they've got an issue, you know, with rearing here and we're not making the right body weight or frame size in our first lactation to produce the level of production record we're required to, or perhaps there are some issues with stresses on heifers as they transition into the herd.
So really, really important metric to look at and, and pretty easy to do as well. But both of these metrics roll down really nicely into some more top-down metrics, so essentially looking at what proportion of our heifers are actually surviving their first lactation and are going on to calf for a second time. There's no real target in the literature for this as such, so there's a real range of UK performance, and we would expect most herds in the UK, particularly looking at Ginny's work, from Nottingham to fall between the 80 to 85% bracket.
And then again, another KPI from Alex Back's group, so this idea of heifer effectiveness. So what proportion of our heifers that did actually carve in at the target age of first calving the first time. How many of them went on to survive 3 full lactations, and this is quite hard to achieve, you know, we're expecting more than 3/4 of this cohort to achieve that.
If we look anecdotally in the literature, we would say most farms are, you know, more around the sort of 60 to 70% mark. So that gives you a bit of an overview of some of the metrics we're gonna talk about in a bit more detail now. So we will focus on some specifics.
So I've chosen to start with our bullying heifer. It's quite an important time point and think about some of the aspects that will impact her. So we'll think a bit about disease, then of course body condition scoring, and then how we can analyse fertility data as well.
So firstly with disease, we'll all be well aware that disease, you know, really can impact future growth and with that impact our future production potential as well. There's lots of work out there now telling us certainly in the first few months of life, and then indeed later on we will have an impact on future milk production if we don't grow well enough. But if we actually separate out the big disease processes that we see as farm vets, so for us that would be bovine respiratory disease or BRD or scour.
There is a wealth of growing body of literature now, so certainly there's a really nice, meta-analysis from Sebastian Buckzinski over in Canada, trying to kind of segregate out what is the impact of one case of BRD in an animal at some point in its life before first calving, and it's a significant amount of milk there that we, we will, you know, lose there in our first lactation. So the economic benefit really is there. But then if we look at some other work again from Alex Back's group there in Europe, looking at the longitudinal impact of BRD cases before first calving on our productive life in first lactation, and in this graph you can see as the number of BRD processes increase, so we can see there, you know, 123, or more than 4, you can see a significant drop there in productive life or days in milk of that first lactation animal.
So it really does show the important impact that disease can have early on. And then similar associations have been found probably earlier in life than what we're saying for for BRD in terms of impact of scour with first lactation milk production. So this is the number of days that calves have had a scour at less than 4 months old.
Can certainly impact all of our first lactation milk production indices there. And again, another forecast of, you know, nearly 400 litres of milk less in first lactation. So I think we can all be happy that this is very economically significant to our clients, even if we're just talking about one animal.
But if we focus on just BRD here, what about the impacts on fertility specifically? So we know that BRD itself will reduce growth and therefore if we're reducing growth, we will need, we will take longer to essentially hit our bullying weight and and reach cyclicity. There are some nice more recent studies out there, so the Oliveira and Andrade work published over the last couple of years, demonstrating that BRD alone will increase the number of months to first conception and will mean animals require more inseminations.
And the same work has also showed that if we have a comorbidity, so if animals are unlucky enough to have scour at the same time, there is a significant drop in conception rate in addition to these metrics. So again, just showing the impact of disease, particularly on fertility. But what I think is very interesting, and this is really way back from 2011, again from Alex Back's group, that just if a heifer needs more serves at this maiden heifer stage, she is significantly less likely to survive her first lactation, and I think this group weren't quite sure why, but it's clear that disease has an impact on the number of serves.
So it's, it's likely to be related to something along those lines, or at least growth. So we can see on the right hand side here in this figure. Each line is a heifer needing certain numbers of serves, so the line I've highlighted in red there is a heifer that requires 5 or more serves as a maiden heifer, and you can see her survival is significantly less than everyone else, it drops away really quickly.
So hopefully this is some really kind of sobering of the impact of disease, whether the disease is scour or BRD. So now on to body condition score, and I've already alluded to this can be quite a tough thing to control. Something that I think we do a lot more of on a regular basis when our maiden heifers actually carve in and join the mature milking herd.
We're pretty good at tracking this. But what we're not very good at is actually working out how they've got to that point. So, OK, you know, our heifers might be carving in too too fat, but actually how many of us are going back and tracking when this is happening and iteratively scoring our heifers earlier on.
And I think the answer is, is not many, and there's certainly a lot more that we could really be doing. I think at this point it's important to note from our literature search, we can't find a validated scale of the body condition scoring, scale for young stock, but it's still something that we would use a lot clinically, and we think it's really important to try and engage our clients and actually managing and monitoring body condition scoring at this stage. Yeah, at this point, it's really, really important to try and get their buy-in.
So we would normally use the 5 point scale at the Penn State scoring scale that most people probably watching this will use for adult cattle. So we would start doing this from around 9 months old and we're aiming for our heifers to be in this optimal range of 2.5 to 3.25.
And really we need to be keeping this scoring going nice and regularly so we can plan, you know, if our heifers are not in that right body condition score ready for service or for bullying, we can do something about it. It's not a massive shock. And equally if our heifers do start to gain condition as they lead up to calving, we can do something about this before it's too late and our heifers are essentially in that dry period beforehand.
So it's a really, really good idea to try and do this early on. In terms of what we see, I would say it's more common for us to see underconditioned heifers in this kind of range, you know, when we're heading up to service and bullying, we maybe haven't managed to get that level of growth that we expected or that we wanted, and so our heifers are much more likely to have a delayed cyclicity and and anest stress and therefore resultant reductions in conception rates at this point. But unfortunately this thing often goes hand in hand that if our heifers take longer to actually get in calf the first time, they're more likely to pile on condition and then be over conditioned at their first calving.
Of course we're all very used to dealing with over overconditioned cows, so the story is very similar for maiden heifers. Essentially, we will see more mobilisation of body fat and nepher in this cohort. Of course we know nephers are toxic to our developing follicles in our foetuses, and so therefore we will often see reductions in conception rates in these animals which are overconditioned too, alongside all of the normal metabolic diseases we'd expect as well.
So In summary, we're aiming for really less than 20% of our cohort to be outside of this ideal range, which, as you will see, can be easier said than done. So as a nice example, it's a real life herd that we work with here at Nottingham to show how this data can actually be used in real life. So this is an autumn block calving herd, er they were vaccinated against all the normal infectious diseases that can impact fertility.
The maiden heifers themselves were housed with the rest of the herd then from mid October onwards they were fed a grass-based silage ration and they had a good few weeks to kind of get settled before thinking about mating start date. It's also important to note that AI was used for all of these heifers, so no swivels, so nice and easy to track back AI operator, timing, which bull was used, that kind of thing as well when we're trying to monitor fertility and conception rate. So when analysing the fertility data for these guys, it became very, very apparent that the 2023 cohort there were hitting that target more or less of 60% for maiden heifer conception rate.
But when we looked at the 2024 cohort, this absolutely wasn't the case, and know, particularly first service conception rate there is significantly less than 60%. So we will talk about some of the general differentials for low conception rates in maiden heifers in more detail in a bit. In this particular herd, all of some of those other avenues were explored and that herd did actually record body condition score and body weight data.
So that was where we kind of ended up, and this was what was assessed next. So if you can see the scatter graph of body weight data for these maiden heifers on the left hand side, so each dark blue data point is a heifer and her body weight. The dashed line is set at the 390 kg, so that's a target of 60% of the mature cow body weight for these heifers in this herd.
And what you'll notice is that, you know, at least 2/3 of those heifers are below that target line, so not where we want to be in terms of body weight or frame. But then what we didn't know was, you know, OK, they might not have enough frame size, but what was their condition like? So but the condition score, again, you can see in the red bars there that at least 2/3 of our heifers are outside our expected range of 2.75 to 3.25 per body condition score.
So this would have been putting a large proportion of these animals at significant risk of anestus and lower conception rates. So I guess the next obvious question will be what do we do about this, and unfortunately it is a historical game. Of backtracking and thinking about where were these guys in terms of their feeding management over summer, likely out at pasture, thinking about pasture management, intakes, do we have any associations with parasitic disease, anything like that, even stresses, you know, moving groups, that kind of thing.
Trying to do a bit of detective work to work out what has gone on so it doesn't happen again with the next cohort next summer. So Last but not least then, before we think about moving on to our first lactation heifers, we can think about analysing the fertility data for our maiden heifers, and we can do this in exactly the same manner that we do for mature milking cattle, and we can assess both submission and conception rate in turn. And it's, you know, we can look at all of those impacting factors such as things like bulls use, timing of insemination, etc.
Etc. As we can for our older animals. A good place to start when we're assessing reasons for poor conception rate in maiden heifers is a differentials list like the one I'm about to show you.
So this for in some cases is quite similar to adult cattle, and we can still see poor management, particularly things like service. This might be related to AI operator or semen quality or even some bull related factors. I think it's important to reflect that often heifers may be kept away from home in separate groups, and they may be subject to different reproductive management.
So it's really important that as vets, we're not assuming this is the same as the milking herd we normally do with, and that actually, you know, everything is fine. So ask those questions, you know, be, be awkward and find those things out because actually that may be the answer to why the heifers are not doing as well. We also need to consider those infectious diseases which should also be on your list that can impact fertility, but again, in a group that may be kept away from the main site and kept with other animals of unknown status, this is really, really important that we are aware of what their infectious disease status is and that we're covering our animals with appropriate management if not.
Again, relating to the fact that animals are often away from home or in far flung fields, incorrect timing of insemination is a really, really kind of relatively valuable thing here, isn't it? And we need to be thinking about making sure that the teams looking after this group have heat detection training, but also do we need to prioritise heat detection aids for this group, and that might be a really sensible thing to do. Particularly thinking about some of the technology grants that are on offer at the moment, maybe putting in a bid for tech collars, for example, if we're struggling with this particular group.
But for me, by far the biggest differentials to consider are these final two for our maiden heifers. So this is either not being at that correct body weight or body condition score at the time of breeding, and this would often be, you know, being too thin, and we see that delayed onset of cyclicity and esters. Or second to this in my opinion, would be the presence of stresses.
So we're very good at prioritising everyone else on the farm other than our maiden heifers, aren't we? So we're pretty good now at looking after our baby calves, very good at looking after our milking herds in most places, but we will often see stresses relating to poor nutritional management of pasture or even frequent group changes as our heifers are moved around the farm in a leader follower system. So it's remembering these guys and actually asking the questions about what they've been through before they get to this point.
So without further ado, I will now go on to our first lactation heifers and talk a little bit more about how we can benchmark how they're doing once they enter the milking herd. So it is really very similar to our mature herd in essence. After we've carved in, we're looking at how have we got on, have we had any level of postpartum disease or dystopia, and then once the voluntary wait period ends for our herd, have we actually managed to be served and get back in calf again?
And then after this point, really it's actually what milk production have we come to? Yeah, so these are all the things that we should be looking at for our mature herd anyway. And all of these aspects will have inherently, you know, impacted whether our heifers have actually remained in the herd or not.
So have they exited? If they have, when? And if they have remained, have we actually seen those heifers dried off and make their second calving?
So I will focus more detail really around milk production and herd exits, but just very quickly just to cover postpartum disease. So it's a fairly straightforward one, what incidence of postpartum disease do we have, particularly in this first lactation heifer group. But for me, it's important to reflect on this, so it's only useful if our farmers are actually recording this, and this is where we come in to try and engage our clients in writing this down.
A lot of the time, you know, when we'll be asking at our annual reviews, how many many milk fevers have you had, and people will say a few, and I'm actually no, yes, important that we're actually making it easy for them to write that down and and this is a lot related to some of the subjects Emily's spoken about already. But the second part of this is actually what is that client's definition of that postpartum disease. So I'm sure my definition of a retained foetal membrane might be very different to someone else's who thinks it's only after 7 days, shall we say.
So just making sure we're all on the same page and we think about those aspects. We can also look at conception rate for our first lactation heifers, and often a really nice time to do this and make that comparison is when we're already looking at the mature herd fertility, so we might be reviewing this on a quarterly basis or maybe after our service block in block carving herds. So actually making those comparisons and comparing those first lactation heifers to everyone else because we know those first lactation heifers should be doing better.
And you know we've put a target of around 10% points higher than mature cow conception rate for this. But of course we have now got to add in the challenges of our heifers being a milking animal into the mix. How well have they transitioned into our herd.
So now I'm gonna talk a little bit more in detail about benchmarking milk production and as we've already talked about this in terms of 3 or 5 day yield and our idea that our heifers really should be giving around 80% of our mature cow yield. So we can also do this with peak peak yield as well, but it's normally a bit more straightforward and economically interesting for clients if we do this for 3 or 5 day yield. So I'm taking an example set of herds here.
So there's 6 separate herds that we work with as part of the Nottingham Group, farms A to F. And what you can see already is there is a real variation between the herds in the percentage of the mature cow yield that their first lactation heifers are actually managing to achieve. So a range from around 74% there to 79%.
So if we look at the projection for what our heifers in litres should be producing, if they're producing 80%, that's a range between sort of 4 7000 litres up to nearly 7000 litres a heifer, so a reasonable variation there. But then if we actually look at what the heifers were producing, it's quite significantly different, isn't it, in some herds, so particularly looking at this herd A, as you know, it's nearly 300 litres in terms of the deficit, or just, just over 300 litres actually, what they, what they could be producing. So if we put this into economic terms.
So these guys were around sort of 43 pence per litre at the time of doing this work, and I'm well aware that this probably has dropped quite significantly for a lot of people now, but even if we're down nearer the 30 or 35 pence per litre mark, this is still a significant amount of money. And when we multiply this up by the number of heifers that were in each cohort for each farm. That's a lot and that's enough money that really actually we could justify some of those changes to improve maiden heifer and first lactation heifer management and know that we will probably get a proportion of this money back relatively quickly.
So finally then onto exits, which for me really is the culmination of all this performance, you know, have our heifers got back in calf, have they produced enough milk? Have they had many diseases? Normally these things lead to exits if things haven't gone quite well as we'd expect.
So we would talk a lot about this in terms of survival. It really splits into two main things for me. So, A, first, when are our heifers actually leaving the herd?
If they're leaving relatively early on, this normally would tell us that they may have had an issue with postpartum disease or dystopias, or even they hadn't come to much milk, or they're just not very milkable, and we'll all know, you know, we've had conversations with farmers where they've just said that heifer just didn't suit the parlour, and sometimes those heifers do need to see a career change. And then later on, it tends to be more fertility or production related culls. But probably the most useful thing is actually again to engage our clients to write down why are the heifers leaving the herd, and it takes away the mystery.
So, you know, is it a voluntary or is it a forced cull? And actually if we've got a reason there, then we can try and take some steps to try and improve the management of this particular cohort of heifers going forward. So we've spoken an awful lot about individual metrics, but how do we bring all of these together in addition to presenting these individual metrics to clients?
So we can add all of this information together and put some percentages on it. So this is another example farm that we work with, and we've had to go quite a few years back to get enough data, because of course our heifers have had to have been born on the farm, but they also have to have completed 3 full lactations. So normally, going back 4 or 5 years ensures all the information is there.
So firstly, looking at our first overall benchmark, which is heifer survival rate. So what percentage of our heifers that were born on the farm actually made it to the first adaptation in some form or other. So this, in this example, is that 100 that survived the first calving divided by 112.
So 89%, which seems relatively good. If we then look at rearing efficiency, so what proportion of those heifers actually made it to first calving within our target, so 22 to 24 months. Again, same numbers, so 100 that carved in actually made it to first calving in that part, which is fantastic.
So a rearing efficiency of 89%, which is above our target of 85%, and puts us nearer to those top herds who are normally achieving 92% or above. So, so far, so good for this herd. But then if you looked lower down the table, you'll probably see things don't end up as well as we've moved through the milking herds.
So first lactation survival rate then, so the percentage of heifers that actually then make it through to second lactation. So for these guys that would be that 80 divided by 100, so 80%. Thinking back to the beginning of our presentation, that would be around average for UK performance, so not terrible, but perhaps not brilliant.
And then if we carry on and we think about the effectiveness of our heifers when they've actually moved through 3 full lactations and they're going to calve again, how many are left there? So we can see there's only 54 animals that completed their third lactation in 2025. And so actually we would put a percentage on this, this is only 54%.
Way off that 75% target and actually blow what we would anecdodotally say is average, you know, around 60%. So this tells us this farm is pretty successful in rearing calves generally, of course, there's always room for improvement, but particularly after that first lactation, we're not doing well at all. So what we could really do with is some reasons for exit to tell us where and why these losses are happening and how we can try and improve things.
So how can you use all this information in practise er when you're out there doing this yourself with your own clients? Hopefully by now you've realised you need an awful lot of data, and I think this can, I'm sure Emmy and I would agree on this, can be the challenging point because some clients are better at providing this than others. And I think in terms of yourself, you also need that information to be in a good quality.
So what we mean by that is it's accurate, we can trust it if we're gonna make farm level decisions and spend lots of money potentially. But also it's in a format that you can work with, you know, you don't want to be spending lots of extra time formatting spreadsheets, and, and trying to put data into a usable format or taking pictures of things written down. So we need to be engaging our clients and going back to what Emily spoke about earlier in the presentation so they understand the importance of this point to make this work for us as a farm team.
In terms of actual data and the quality, it's really, really variable, so. In green, first are the things that we've found pretty easy to collect, so typically these green things, our fertility metrics, our PD results and other yield data should all be normally tethered to a milk recording and most of our farmers these days, I say optimistically, are milk recording. I would say it's gonna be quite difficult to do a lot of this if they're not, so trying to engage people in this it is a really important first step I would say for an awful lot of reasons.
Amber data then is variable. OK, so we need average mature cow body weight data so we can benchmark our heifers to work out percentage of body weight at bulling and at calving. We can't be guessing, and I think a lot of clients have actually been quite surprised when they've weighed a mature sort of 2nd or 3rd lactation cow, actually what she weighs, so it can be quite an educational exercise and worth doing a cohort of them, of, of normal average size animals to the eye, so you can see where you're at.
Again, herd exit data, so people clearly legally have to report exits, but writing down the reason for why they've gone can be missing. So as we've already talked about, we have to guess otherwise, which can be really inaccurate. So wanting to know why they've gone and then where we can improve is really, really important.
And then finally in reds, I would say very often not there, and this is really our job now to try and improve this. So body condition scoring animals that are not yet in the milking herd, super important, often very rare for us to have this data at all. Again, weight data often much more common that our pre-weaned calves will be weighed or weigh taped, which is fantastic, but we need to try and continue on this trajectory with our older animals and thinking about what practical things do we need to put in place so farmers can actually do this, how are they gonna do it, when are they gonna do it?
Can we actually put it in with any of the management changes such as, we, you know, weaning or worming or field move or whatever. And then really disease data for from postwean stage onwards, we know these animals maybe aren't looked at as often as other cohorts on the farm. So just making sure what we're looking at is an accurate representation of what has actually happened.
So that gives you an idea of some of the stumbling blocks we've certainly had when we're looking at this data. But what do you need? And I guess the the big one here is basic data handling skills.
So you'll be, I'm sure, well aware that you can import your milk recording data and often your farm management data from things like uniform agri into whatever data software you use to analyse data. So that might be something like total vet, which we use a lot here at Nottingham. It could be something like Heard Companion or Inter Heard Plus, made by NMR or there are various other softwares also.
So whatever you need to be able to do this and interpret that. But what you'll also find rather annoyingly is a lot of the information that you've asked for often doesn't turn up in any of those software. So you need to try and learn to analyse and interpret and kind of monitor weight data, treatment data, things like this.
Normally an Excel spreadsheet would be a good place to start. So really learning to create an output for that data. So a graphical output, so a good example for this for weight data might be a box and whisker plot, showing the variation of the animals that you've got in each cohort.
But we also need to be able to manipulate the data and sometimes in some herds there can be large, large volumes of it, so this is not a case of doing this manually. So learning to make things like pivot tables and use formula can be really, really important. And then it goes without saying patience and time, and I think it can be quite a steep learning curve.
So being patient with yourself, allowing yourself enough time in practise on the diary there to actually learn to do these things. There are various courses online that we can do in terms of data handling that can be really, really helpful. Just once you get going, you'll be grand, but it's just giving yourself some time to start.
We do also have a few helpful kind of hints and tips, so the herd health toolkit, if you scan the QR code, will take you to a toolkit that we've made within the the farm team here at Nottingham. There's various different pages there that cover cow calf health and cow health. An example with the young stock page is you can actually upload your, your calf weights and it will create some daily life weight gain graphs for you.
There's also the ability to benchmark and forecast mortality er depending on the environmental conditions that your pre-weaned calves are in, so there's lots of really handy things there, particularly for young stock as well as adult animals. But essentially to wrap up, I'm, I'm really hoping that today we've managed to cover more of an individualised approach to consisting of looking at all of the data we've spoken about. So whether this be your milk recording data, so your fertility and your production data, or whether that be the data that we don't commonly look at as much.
So body condition score data, your weight data and your exit data. And as Emily really nicely went over earlier, it really is about keeping that monitoring going and making sure that once we start, it becomes that iterative process and we become part of that farm team, keeping that collaborative relationship going because that is the key. What we don't want is to do a fantastic job initially and that everything kind of pales off into insignificance, so it's keeping, keeping up that good work.
So without further ado, thank you a huge amount for joining us for this webinar. Hopefully it's been useful. But as always, if you've got any questions or comments, our email addresses are there, just drop us a line.
We're happy to help with anything, including if you've got any awkward farms and not quite sure which way to turn next, we'd be more than happy to, to give you a hand. So thank you very much for your attention.
