A stochastic model simulating the feeding-health-production complex in a dairy herd

Effects of herd management decisions on dairy cow longevity, farm profitability, and emissions of enteric methane - a simulation study of milk and beef production

Sustainable dairy and beef production provides environmental, economic, and social values that can potentially be maximized by optimizing herd management strategies. The length of a dairy cow's life is affected by, and affects, all three pillars of sustainability. Longevity in dairy cows is multifactorial and strongly dependent on herd management. Despite genetic improvements, the average time of culling for Swedish cows has barely changed and is currently at 2.6 lactations. This culling rate requires a high number of replacement heifers, generating high rearing costs for farmers. This study evaluated different herd management strategies to improve cow longevity and assessed the effects on enteric methane (CH4) emissions from the herd and the profitability of milk production and beef production from the dairy cows and their offspring. The base scenario, an average Swedish Holstein herd of 100 cows, was compared with seven scenarios simulated using a stochastic herd simulation model (SimHerd). Two of these scenarios involved improved health and survival of cows in the herd, three involved improved reproduction, one considered the consequences of keeping all surplus heifers in the herd, and one considered maximizing the use of X-sorted dairy semen and inseminating the rest of the herd with unsorted beef semen, to avoid surplus replacement heifers. Improved fertility had the greatest effect in increasing the productive life per cow, to 3.8 years compared with 2.8 in the base scenario, allowed for more use of beef semen, reduced the number of replacement heifers, and generated the highest herd profit (€98 per cow-year higher than base scenario). Keeping all surplus heifers instead of producing beef × dairy cross calves decreased the number of productive years by 0.8 and reduced profit by €22 per cow-year. The profit was highly associated with costs related to replacement heifers. The highest beef output (3 369 kg per year more than base scenario) was achieved by keeping all heifers and culling a high share of dairy cows, but this scenario also generated much higher enteric CH4 emissions (+1 257 kg per year). Improving health, survival, or fertility reduced enteric CH4 emissions by 90-255 kg per year, while total yearly beef production ranged from 59 kg less to 556 kg more than in the base scenario. Reducing the number of replacement heifers needed by improving cow reproductive performance is thus key to increasing cow longevity and profitability, while reducing enteric CH4 emissions from the herd without compromising milk and meat production.

A stochastic animal life cycle simulation model for a whole dairy farm system model: Assessing the value of combined heifer and lactating dairy cow reproductive management programs

This analysis introduces a stochastic herd simulation model and evaluates the estimated reproductive and economic performance of combinations of reproductive management programs for both heifers and lactating cows. The model simulates the growth, reproductive performance, production, and culling for individual animals and integrates individual animal outcomes to represent herd dynamics daily. The model has an extensible structure, allowing for future modification and expansion, and has been integrated into the Ruminant Farm Systems model, a holistic dairy farm simulation model. The herd simulation model was used to compare outcomes of 10 reproductive management scenarios based on common practices on US farms with combinations of estrous detection (ED) and artificial insemination (AI), synchronized estrous detection (synch-ED) and AI, timed AI (TAI, 5-d CIDR-Synch) programs for heifers; and ED, a combination of ED and TAI (ED-TAI, Presynch-Ovsynch), and TAI (Double-Ovsynch) with or without ED during the reinsemination period for lactating cows. The simulation was run for a 1,000-cow (milking and dry) herd for 7 yr, and we used the outcomes from the final year to evaluate results. The model accounted for incomes from milk, sold calves, and culled heifers and cows, as well as costs from breeding, AI, semen, pregnancy diagnosis, and calf, heifer, and cow feed. We found that the interaction between heifer and lactating dairy cow reproductive management programs influences herd economic performance primarily due to heifer rearing costs and replacement heifer supply. The greatest net return (NR) was achieved when combining heifer TAI and cow TAI without ED during the reinsemination period, whereas the lowest NR was obtained when combining heifer synch-ED with cow ED.

Evaluation of activity meters for estrus detection: A stochastic bioeconomic modeling approach

Although estrus detection makes a relevant contribution to the reproductive performance of dairy cattle, studies on the economic evaluation of automatic estrus detection systems are rare. The objective of the present study is to provide an economic evaluation of activity meters used for estrus detection. The effect of different estrus detection rates on gross margins was modeled with SimHerd (SimHerd A/S, Viborg, Denmark). The analysis considers all costs associated with the investment in activity meters. The economic evaluation was carried out through simulation of Simmental herds with yearly milk yields of 7,000 or 9,000 kg and Holstein Friesian herds with yearly milk yields of 9,000 or 11,000 kg, each with herd sizes of 70 or 210 cows. Furthermore, we distinguished between 2 investment scenarios. In scenario 1, only cows are equipped with activity meters for estrus detection, whereas scenario 2 assumes that cows and heifers are equipped with activity meters. Because existing empirical information for some variables shows significant variability (estrus detection rates, time for estrus detection), they were modeled with distributions using the Monte Carlo method in @RISK (Palisade Corporation, Ithaca, NY), allowing us to model a probability distribution of net returns (NR) of investment in activity meters for estrus detection. The simulation results show that the average NR of investment in activity meters for estrus detection over all scenarios ranges from +€7 to +€40 per cow per year for the Simmental breed, and from +€19 to +€46 per cow per year for the Holstein Friesian breed. Generally, the NR depends on the milk production level assumed. For the Simmental breed, depending on the scenario, the simulation results show a 54 to 200% larger average NR of investment in activity meters for estrus detection with a milk yield of 9,000 kg/yr compared with 7,000 kg/yr. For the Holstein Friesian breed, the effect of the modeled milk yield on the NR is much less pronounced. Average NR of investment in activity meters are greater for larger herd sizes because of cost degression effects. An additional equipping of heifers has, on average, a positive effect on the economics of activity meters for estrus detection because of the resulting reduction in the age at first calving. Considering all scenarios, the probability of a positive NR of investment in activity meters ranges between 74 and 98% for the Simmental breed and between 85 and 99% for the Holstein Friesian breed.

The effect of Mycobacterium avium ssp. paratuberculosis infection on clinical mastitis occurrence in dairy cows

Endemic diseases can be counted among the most serious sources of losses for livestock production. In dairy farms in particular, one of the most common diseases is Johne's disease, caused by Mycobacterium avium ssp. paratuberculosis (MAP). Infection with MAP causes direct costs because it affects milk production, but it has also been suspected to increase the risk of clinical mastitis (CM) among infected animals. This might contribute to further costs for farmers. We asked whether MAP infection represents a risk factor for CM and, in particular, whether CM occurrences were more common in MAP-infected animals. Our results, obtained by survival analysis, suggest that MAP-infected cows had an increased probability of experiencing CM during lactation. These results highlight the need to account for the interplay of infectious diseases and other health conditions in economic and epidemiological modeling. In this case, accounting for MAP-infected cows having an increased CM occurrence might have nonnegligible effects on the estimated benefit of MAP control.

Economic opportunities for using sexed semen and semen of beef bulls in dairy herds

Dairy farmers can increase the number of dairy heifer calves born in their herd by using sexed semen. They can reduce the number of both dairy bull and heifer calves by using beef semen. Long before sexed semen became commercially available, it was believed that it would provide opportunities for increasing genetic level in both herds and populations. In this study, we studied the potential for increasing the genetic level of a herd by using beef semen in combination with sexed semen. We tested the hypothesis that the potential of increasing the genetic level and the overall net return would depend on herd management. To test this hypothesis, we simulated 7 scenarios using beef semen and sexed semen in 5 herds at different management levels. We combined the results of 2 stochastic simulation models, SimHerd and ADAM. SimHerd simulated the effects of the scenarios and management levels on economic outcomes (i.e., operational return) and on technical outcomes such as the parity distribution of the dams of heifer calves, but it disregarded genetic progress. The ADAM model quantified genetic level by using the dams' parity distributions and the frequency of sexed and beef semen to estimate genetic return per year. We calculated the annual net return per slot as the sum of the operational return and the genetic return, divided by the total number of slots. Net return increased up to €18 per slot when using sexed semen in 75% genetically superior heifers and beef semen in 70% genetically inferior, multiparous cows. The assumed reliability of selection was 0.84. These findings were for a herd with overall high management for reproductive performance, longevity, and calf survival. The same breeding strategy reduced net return by €55 per slot when management levels were average. The main reason for the large reduction in net return was the heifer shortage that arose in this scenario. Our hypothesis that the potential for beef semen to increase genetic level would be herd-specific was supported. None of the scenarios were profitable under Danish circumstances when the value of the increased genetic level was not included. A comparable improvement in genetic level could be realized by selectively selling dairy heifer calves rather than using beef semen.

Evaluation of two dairy herd reproductive performance indicators that are adjusted for voluntary waiting period

Background

Overall reproductive performance of dairy herds is monitored by various indicators. Most of them do not consider all eligible animals and do not consider different management strategies at farm level. This problem can be alleviated by measuring the proportion of pregnant cows by specific intervals after their calving date or after a fixed time period, such as the voluntary waiting period. The aim of this study was to evaluate two reproductive performance indicators that consider the voluntary waiting period at the herd. The two indicators were: percentage of pregnant cows in the herd after the voluntary waiting period plus 30 days (PV30) and percentage of inseminated cows in the herd after the voluntary waiting period plus 30 days (IV30). We wanted to assess how PV30 and IV30 perform in a simulation of herds with different reproductive management and physiology and to compare them to indicators of reproductive performance that do not consider the herd voluntary waiting period.

Methods

To evaluate the reproductive indicators we used the SimHerd-program, a stochastic simulation model, and 18 scenarios were simulated. The scenarios were designed by altering the reproductive management efficiency and the status of reproductive physiology of the herd. Logistic regression models, together with receiver operating characteristics (ROC), were used to examine how well the reproductive performance indicators could discriminate between herds of different levels of reproductive management efficiency or reproductive physiology.

Results

The logistic regression models with the ROC analysis showed that IV30 was the indicator that best discriminated between different levels of management efficiency followed by PV30, calving interval, 200-days not-in calf-rate (NotIC200), in calf rate at100-days (IC100) and a fertility index. For reproductive physiology the ROC analysis showed that the fertility index was the indicator that best discriminated between different levels, followed by PV30, NotIC200, IC100 and the calving interval. IV30 could not discriminate between the two levels.

Conclusion

PV30 is the single best performance indicator for estimating the level of both herd management efficiency and reproductive physiology followed by NotIC200 and IC100. This indicates that PV30 could be a potential candidate for inclusion in dairy herd improvement schemes.

A stochastic model simulating paratuberculosis in a dairy herd

Paratuberculosis (PTB) causes severe economic losses to farmers and the infection has very complex effects (many indirect) on the production of a dairy herd. These indirect effects have not or only briefly been described by earlier PTB-simulation models, and therefore they were included in a new model called PTB-Simherd. Our aim was to develop the basis for a decision-support tool which can predict herd-specific production-related effects from introduction of different control strategies against PTB. The PTB-Simherd is a dynamic, stochastic, and mechanistic Monte-Carlo model simulating a dairy herd including young stock. Paratuberculosis and relevant control strategies against this infection were built into an existing herd simulation model. The model simulates epidemiological and production related consequences of PTB and control strategies against it in the herd. It also reflects indirect effects of PTB and control strategies through effects on replacements and herd demographics. Every animal in the herd is specified with biological parameters (including PTB state and test results) and it is updated in weekly time-steps. Management is specified at herd level with 353 parameters of which 78 are related to PTB. To demonstrate the basic characteristics of the model, scenarios with varying infection risks (sensitivity analyses) plus scenarios with seven different control strategies in two herds with good and poor reproduction were simulated for 10 years. Breaking of infection routes turned out to be the only strategy predicted to reduce the true prevalence of PTB in a herd. Supplementing this strategy with test-&-cull strategies had limited effect on prevalence and using test-&-cull alone just delayed the increase in prevalence. The effects of different PTB-control strategies on the production (especially sale/purchase of heifers, feed consumption and prevalences of other diseases) were predicted to be affected by other conditions like heat-detection success, replacement% and herd demographics--which were again affected by PTB infection of the herd. These links and indirect effects of control strategies thus seem important to include when modeling and predicting effects of PTB control in dairy herds.

A stochastic model simulating milk fever in a dairy herd

A simulation model was developed to evaluate the long-term effect of control strategies against milk fever (MF); here, we present the base model and sensitivity analyses. The representation of the within-herd dynamics was based on the existing SimHerd II model. Because of the relationships between MF and other diseases, the new model (called "SimHerd III") includes diseases common in a dairy herd. The cow level risk factors modelled were: base risk in the herd, parity, milk-yield potential, lactational disease recurrence, disease interrelationships, body condition and season. The diseases include clinical cases of MF, dystocia, downer-cow syndrome, retained placenta, metritis, displaced abomasum, ketosis and mastitis. The effects of diseases were represented by daily milk yield, daily body weight, daily feed intake, risk of stillbirth, conception probability, decision on culling, death and immediate removal. Simulated technical results showed that the herd effects of reduced risk of MF differed according to the reproductive efficiency in the herd. These interactions between reproduction efficiency and the effect of reduced base risk of MF were related to differences in how the simulated herds reacted to the reduction in replacements caused by MF. In the sensitivity analysis, eight potential key parameters were changed to their lowest and highest expected values retrieved from the literature. When measuring the sensitivity on milk production in the herd (as the economically most important technical effect), the model seemed most sensitive to the uncertainty of effect of MF on death risk and MF-recurrence risk.

Expert opinions of strategies for milk fever control

Dairy cows have several risk factors for milk fever. The most-suitable strategy to control milk fever in a specific herd will depend on herd-specific circumstances such as the attitude and skills of the farmer, the opportunities available in the production system and the economic consequences of a certain strategy. To develop feasible strategies in a modern loose-housing dairy herd, we carried out an expert opinion study. Animal husbandry advisors and veterinary practitioners were used as experts. The experts quantified the effect on milk fever and time needed by the farmer for two preselected options: Ca-gel fed orally peripartum and a low dietary cation-anion-difference in the dry-cow ration. The estimated mean relative risk (compared to no strategy) was 0.45 and 0.42, respectively, and the median time needed by the farmer was 7 and 33 min, respectively, per cow year. The experts also suggested 12 control strategies. The two control strategies, which were predicted to be the most, relevant were Ca-gel fed orally peripartum used alone and used in combination with a low Ca dry-cow diet.

Short communication: associations between blood calcium status at calving and milk yield in dairy cows

The purpose of the present study was to estimate the effect of total blood plasma calcium (TBPCC) concentration at calving on milk yield in dairy cows. Data originated from 153 dairy cows in 27 herds from a single veterinary practice. For each cow, data included calcium concentration in a blood sample taken within 12 h postpartum, monthly test-day milk yield until 300 d in milk, calving date, parity, breed, and herd. The TBPCC ranged from 0.69 to 2.73 mmol/L, with a mean value of 1.80 mmol/L. The statistical analysis adjusted for the fixed effects of parity and lactation stage, random effects of herd and cow, and the correlation between repeated measures of test-day milk yield. The results showed that TBPCC at calving was not significantly related to fat- and protein-corrected milk yield at any lactation period. The present study indicates that hypocalcemia (low TBPCC) at calving is not an important risk factor for decreased milk yield.