In the life of a dairy cow, there is going to come a day when that cow will be removed from your lactating herd and replaced with a young heifer. But how is that decision being made? After all, culling can be voluntary or involuntary.
Voluntary culling occurs when the producer can make the decision. In many cases, this is because they have genetically superior replacement heifers with higher earning potential, ready to take over for a lactating cow that is either genetically inferior, or perhaps the cow is past its peak milk production potential and is on the downswing.
Involuntary culling occurs because the cow is severely affected by an infectious or metabolic disease, or they have already died. If a cow comes down with one of these diseases and the prognosis is poor, a dairy producer can sell the cow to use for beef. Even though this is an instance of involuntary culling, the producer can recover some of the money they have invested in that cow. If the cow dies before it is sold, it cannot be used for beef and must be rendered without recovering any costs.
The highest risk of disease and mortality for a dairy cow is during transition – specifically right around the time of calving – which results in increased involuntary culling. To put things in perspective, it has been estimated that approximately 75% of disease in dairy cows happens in the first month after calving.a Losing a cow during this period is very costly to a dairy producer. Let’s take, as an extreme example, the young cow calving for the first time. All the time leading up to lactation has been invested in boarding her, feeding her, breeding her and ramping up her feed intake to prepare her for producing high quantities of milk. If at this point, she dies or you are forced to sell her for beef, you are unable to capitalize on any of this investment, that is a no-economic value cull.
High performing dairies tend to prevent disease and manage involuntary culling. In turn, they gain more flexibility with voluntary culling, which also drives herd performance forward.
Now that we’ve covered the basics of voluntary and involuntary culling, let’s dive in deeper and look at ways you can play a proactive role in voluntary culling.
Many computer models have been developed that optimize voluntary culling decisions and rank cows for continued profitability based on how much milk they are projected to produce in the future. This is called the “retention pay-off (RPO)”b and it is a feature of many dairy cattle management software.
The RPO is defined as the net present value of keeping the incumbent cow in the herd until the optimal time of replacement, compared with replacing her with a replacement heifer now. Using this model, when the RPO is less than or equal to $0, it is time for a producer to replace that cow with an incoming heifer that promises more time and production in the dairy. On the other hand, if the RPO figure is, for example $500, that means that the incumbent cow is still profitable and replacing the cow now would result in a loss (missed opportunity) of $500.
To utilize the RPO on a transition cow management software, the user must input variables such as milk price beef price, the herd’s current production levels and cow turnover rate. It will then calculate a current value for every animal in the system. Each animal’s value will be different based on age, previous production, projected milk production, pregnancy status, etc.
Using the retention pay-off model can help dairy producers make the best decisions when it comes time to voluntarily cull a cow from the herd and bring in a replacement heifer.
The highest risk of involuntary is caused by disorders during the transition period. After calving, the demand for milk production increases substantially, and cows are unable to consume adequate energy to sustain performance. Therefore, they mobilize body reserves to maintain energy for milk production and post-calving recovery, causing them to be in a negative energy balance. Even though negative energy balance at this stage is expected and natural, we manage cows to help them recover as soon as possible. Otherwise, it can cause metabolic disorders like ketosis and hypocalcemia.
These disorders can lead to higher susceptibility of infectious diseases like mastitis and metritis. Around the time of calving, the cow is often juggling milk production, adaptation and immune challenges. When that happens, it needs to have enough energy to fuel an appropriate inflammatory response, or it will be more prone to these infectious diseases and involuntary culling.
Proper nutrition, including trace minerals, has a tremendous impact on reducing both voluntary and involuntary culling by improving performance and improving health and wellbeing.
Giving milk to the calf is what guarantees the survival of the species. Dairy cows are willing to divert nutrients away from other physiological functions to fuel milk production. The energy that she is putting out into milk production is so much that she will never be able to have enough feed to cover those needs. Our goal should be to help dairy cows cope with these changes and challenges, protect them and prevent disease before it happens. Therefore, feeding performance trace minerals in the transition cow diet is critical.
The impact of Zinpro Performance Minerals® in the transition cow diet is often underestimated in the industry. Since they are more bioavailable than inorganic sources, cows can absorb more of these critical nutrients to support high milk yields and their own maintenance and immune function, even around the time of calving when they are not consuming as much feed.
Ensuring a successful transition period and helping cows thrive through the first 30 to 60 days post-calving is critical for avoiding involuntary culling and helping the cows in your herd reach their full milk-production potential.
Contact a Zinpro representative today to learn more about formulating your transition cow diet.
a LeBlanc, S.J., K. D. Lissemore, D.F. Kelton, T. F. Duffield, and K.E. Leslie. 2006. Major Advances in Disease Prevention in Dairy Cattle. J. Dairy Sci. 89:1267-1279
b D. Liang,* L. M. Arnold,† C. J. Stowe,‡ R. J. Harmon,* and J. M. Bewley*1 2017. Estimating US dairy clinical disease costs with a stochastic simulation model. J. Dairy Sci. 100:1472–1486