Effects of limits in milking capacity, housing capacity, or fat quota on economic optimization of dry period lengths.

The economically optimal dry period length (DPL) of dairy cows remains a topic of interest. Increasing daily milk production and improved management of the transition period require frequent evaluation of the optimal DPL. The economically optimal DPL also depends on the most limiting farm resource such as milking capacity, housing capacity, or fat quota. Therefore, the objective of this study was to determine economically optimal DPL under farm constraints on milking capacity, housing capacity, and fat quota given variations in 12 input factor levels. We developed a deterministic whole herd simulation model, including a nonlinear optimizer of the DPL in the first 3 parities. The model included estimates of milk, fat, and protein yield deviations in the subsequent parity and hazard ratios of culling risk and pregnancy rates as functions of the DPL in the current parity. The DPL could vary between 20 and 90 d with step size of 1 d. In addition to a one-factor-at-a-time analysis, we used a definitive screening design and a space-filling design with Latin hypercube sampling to determine important linear and curvature effects of input factors and their interactions. Results indicated that the economically optimal DPL were typically between 35 and 50 d under a large variation in input factor levels. The opportunity costs of equal DPL in all parities were small compared with optimal policies where the DPL were allowed to vary between parities. The DPL under the parlor constraint were generally less than 5 d longer than the optimal DPL under the housing constraint. The optimal DPL under the quota constraint were between those under the parlor and housing constraints. Opportunity costs compared with 50 d dry were often small, but in some cases large. A formal global sensitivity analysis revealed important interactions of input factors that were not discovered with one-factor-at-a-time analyses. In conclusion, economically optimal DPL were often shorter than typically are recommended. Adding uncertainty about the date of calving at the date of dry-off might extend these optimal DPL by some days depending on the risk attitude of the decision maker.

Invited review: Academic and applied approach to evaluating longevity in dairy cows.

In its simplest form, longevity is defined as the ability to live a long life. Within the dairy industry, longevity has been defined and measured in many different ways, and the aim of this review is to disentangle the definitions and provide some clarity. Using a more standardized approach for defining and measuring longevity, both in academic discussions and on-farm application, we suggest using herd life (days) for time from birth until culling, and length of productive life (days) for time from first calving until culling. Despite identified benefits of extending the length of productive life, global trends in the time spent by dairy cattle in the herd have mostly been negative. Factors influencing herd life, such as health, rearing, environmental conditions, and management, are often ignored when longevity goals are evaluated, thereby underestimating the effect these factors have on defining overall longevity. Also, production efficiency, herd profitability, and welfare are not necessarily served by the longest life but rather by the optimized length of herd life instead. The majority of research has focused on the role of genetics on longevity. In this review, we provide insight into influences affecting dairy cow herd life as well as farm- and cow-level factors associated herewith. Finally, we suggest using herd life, including reproduction, production, health, and youngstock performance, for farm-level evaluation and length of productive life for time spent in the lactating herd.

Symposium review: Why revisit dairy cattle productive lifespan?

Dairy cattle productive lifespan averages approximately 3 yr after first calving. Changes in the last decade in reproductive performance, genetic merit, and societal concerns regarding animal welfare and the environmental footprint of dairy products warrant a critical review of decision making regarding dairy cattle productive lifespan. The objective of this study is to provide such a review. Economic decision making drives the majority of culling decisions and, by extension, dairy cattle productive lifespan. Historically, models focused on optimizing replacement decisions for individual cows found economically optimal productive lifespans of 40 mo or more. However, cow performance and prices have changed and the average findings of these models may no longer hold. Management and housing may affect productive lifespan through improvements in health care and cow comfort. Improvements in reproductive efficiency and the availability of sexed semen are leading to an abundance of dairy heifers on many dairy farms, which often results in shorter productive lifespans in herds of fixed sizes. There is also a growing interest in the use of beef semen in dairy cattle, which does not add to the supply of dairy heifers. Acceleration of genetic gain due to genomic testing should likely result in shorter productive lifespans. Younger herds capitalize on genetic progress but have fewer efficient mature cows and have greater replacement costs. Extending dairy cattle productive lifespan might decrease the environmental footprint of milk production because fewer heifers need to be raised. Short productive lifespans, especially as a result of much forced culling early in lactation, are often signs of reduced welfare. Possible extensions of productive lifespan through improved welfare may alleviate public concerns about dairy production, although longer productive lifespans for healthy cows are not necessarily more profitable. A simple model of the economically optimal productive lifespan illustrates the tradeoffs between herd replacement cost, maturity and aging costs, genetic opportunity cost, and calf value opportunity cost. Combined, these factors suggest that an average productive lifespan of approximately 5 yr is warranted. In conclusion, increases in genetic gain, reproductive efficiency, cow comfort, and health care will increase the opportunity of herd managers to change productive lifespan to increase profitability, improve societal acceptance of dairy production, or both.

Ranking sires using genetic selection indices based on financial investment methods versus lifetime net merit.

Current USDA selection indices such as lifetime net merit (NM$) estimate lifetime profit differences, which are accurately approximated by a linear combination of 13 traits. In these indices, every animal gets credit for 2.78 lactations of the traits expressed per lactation, such as fat and protein, independent of its productive life (PL). This formulation may over- or underestimate the net revenue from traits expressed per lactation depending on PL. The objectives were to develop 2 genetic selection indices using financial investment methods to account for differences in PL and to compare them with the 2017 NM$ for marketed Holstein sires. Selection among animals with different PL is an example of investment in mutually exclusive projects that have unequal duration. Financial investment theory says that such projects are best compared with the annualized net present value (ANPV) method when replacement occurs with technologically equal assets. However, genetic progress implies that future available replacement animals are technologically improved assets. Asset replacement theory with improved assets results in an annualized value including genetic opportunity cost (AVOC) for each animal. We developed the ANPV and AVOC and compared these with the NM$ for 1,500 marketed Holstein sires from the December 2017 genetic evaluation. The lowest Pearson correlation coefficient was 0.980 between AVOC and NM$, whereas the highest was 0.999 between ANPV and NM$ among the 1,500 sires. Correlations for the top 300 sires were lower. Although we found high correlations between indices, the 95th and 5th percentiles of individual rank changes between AVOC and NM$ were +131 and -163 positions, respectively, whereas these changes between ANPV and NM$ were +27 and -45 positions, respectively. The relative emphasis of PL in the AVOC index was half of the relative emphasis in NM$. These results show that applying financial investment methods to value differences in genetic merit of animals changes their rankings compared with the NM$ formulation. Rank changes were meaningful enough that the new indices warrant consideration for use in practice.

Epidemiologic and economic analyses of pregnancy loss attributable to mastitis in primiparous Holstein cows.

The main objective of the study reported here was to examine the association between pregnancy loss (PL) and previous exposure to clinical or subclinical mastitis before breeding or during gestation in primiparous Holstein cows. A secondary objective was to estimate the cost of clinical mastitis during gestation, including that of PL attributable to mastitis in study cows. A total of 687 primiparous Holstein cows from 1 dairy farm were included in a matched case-control study. Study cows were declared pregnant via ultrasound on d 33 after timed artificial insemination (TAI). Case cows (n = 78) were those diagnosed as nonpregnant by rectal palpation on d 47 or 75 after TAI. Control cows were those confirmed as pregnant by rectal palpation on d 47 and 75 after TAI. Case cows were matched with eligible controls according to year of calving and calving-to-conception interval ±3 d. Cows were assigned to 1 of 3 groups: (1) cows not affected with clinical or subclinical mastitis; (2) cows affected with subclinical mastitis (Dairy Herd Improvement Association somatic cell score >4.5); and (3) cows affected with clinical mastitis during 2 exposure periods, 1 to 42 d before breeding or during gestation (1 to PL diagnosis day for case cows, and 1 to 75 d for control cows). Conditional logistic regression was used to model the odds of PL as a function of previous exposure to mastitis in study cows. Mastitis before breeding was not associated with PL. The odds of PL were 2.21 times greater in cows affected with clinical mastitis during gestation (95% confidence interval = 1.01, 4.83), compared with cows without mastitis, after controlling for breeding type and lameness. The cost of clinical mastitis during gestation was $149, which includes the cost ($27) of PL attributable to mastitis. In conclusion, this study provides evidence that clinical mastitis during gestation can cause PL in primiparous dairy cows leading to economic losses.

Economic and genetic performance of various combinations of in vitro-produced embryo transfers and artificial insemination in a dairy herd.

The objective of this study was to find the optimal proportions of pregnancies from an in vitro-produced embryo transfer (IVP-ET) system and artificial insemination (AI) so that profitability is maximized over a range of prices for embryos and surplus dairy heifer calves. An existing stochastic, dynamic dairy model with genetic merits of 12 traits was adapted for scenarios where 0 to 100% of the eligible females in the herd were impregnated, in increments of 10%, using IVP-ET (ET0 to ET100, 11 scenarios). Oocytes were collected from the top donors selected for the trait lifetime net merit (NM$) and fertilized with sexed semen to produce IVP embryos. Due to their greater conception rates, first ranked were eligible heifer recipients based on lowest number of unsuccessful inseminations or embryo transfers, and then on age. Next, eligible cow recipients were ranked based on the greatest average estimated breeding values (EBV) of the traits cow conception rate and daughter pregnancy rate. Animals that were not recipients of IVP embryos received conventional semen through AI, except that the top 50% of heifers ranked for EBV of NM$ were inseminated with sexed semen for the first 2 AI. The economically optimal proportions of IVP-ET were determined using sensitivity analysis performed for 24 price sets involving 6 different selling prices of surplus dairy heifer calves at approximately 105 d of age and 4 different prices of IVP embryos. The model was run for 15 yr after the start of the IVP-ET program for each scenario. The mean ± standard error of true breeding values of NM$ of all cows in the herd in yr 15 was greater by $603 ± 2 per cow per year for ET100 when compared with ET0. The optimal proportion of IVP-ET ranged from ET100 (for surplus dairy heifer calves sold for ≥$300 along with an additional premium based on their EBV of NM$ and a ≤$100 embryo price) to as low as ET0 (surplus dairy heifer calves sold at $300 with a $200 embryo price). For the default assumptions, the profit/cow in yr 15 was greater by $337, $215, $116, and $69 compared with ET0 when embryo prices were $50, $100, $150, and $200. The optimal use of IVP-ET was 100, 100, 62, and 36% of all breedings for these embryo prices, respectively. At the input price of $165 for an IVP embryo, the difference in the net present value of yr 15 profit between ET40 (optimal scenario) and ET0 was $33 per cow. In conclusion, some use of IVP-ET was profitable for a wide range of IVP-ET prices and values of surplus dairy heifer calves.

Economic evaluation of stall stocking density of lactating dairy cows.

An increase in stall stocking density (SSD), as measured by the number of lactating cows per stall in a freestall barn, reduces cow performance, such as milk yield and fertility, but may increase farm profitability. Our objectives were to calculate effects of varying SSD on profit per stall for a range of effects on cow performances and external farm factors and store results in regression metamodels. The literature on quantified effects of SSD on cow performance that directly affects cash flow was found to be weak. We assumed effects of SSD on milk yield, probability of conception, and probability of culling. External farm factors were probability of insemination, feed price, and milk price. A herd budget-simulation model was used which mimics the performance of cows in a herd and calculates profit per stall per year and other results. The SSD varied from 100 (no overstocking) to 150% (severe overstocking) in steps of 10%. Sensitivity analyses for effects of SSD on cow performance and effects of external farm factors were performed. Three regression metamodels were developed. The first metamodel accurately predicted profitability at 100% SSD for all variations in the external farm factors. Optimal SSD varied from 100 to 150% SSD, depending on the combination of inputs, and was very sensitive to changes in the size of the milk loss and milk and feed prices. Average optimal SSD of all 2,187 combinations of inputs was 120% SSD and average maximum increase in profit was $99/stall per year. Of the 2,187 combinations of inputs, 18% were ascending (maximum increase in profit >150% SSD), 33% were descending (maximum profit at 100% SSD), and 50% had a maximum increase in profit between 100 and 150% SSD. The second metamodel accurately captured changes in profit for all combinations of biological and external inputs and SSD. A third metamodel captured breakeven daily milk losses which would result in the same profit as at 100% SSD given the same external farm factors. In conclusion, overstocking was profitable under plausible economic conditions in the United States. The 3 metamodels accurately captured the results for a wide range of values of the input variables. A tradeoff will occur between economically optimal SSD and animal welfare in some situations.