Economics of reducing antibiotic usage for clinical mastitis and metritis through genomic selection.

Antibiotics use (ABU) in animal agriculture has been implicated in the emergence of antibiotic resistance, a global public health threat. Economically justifiable antibiotic reduction strategies can motivate farmers to reduce ABU for clinical mastitis (CM) and metritis, the most common reasons for ABU on dairy farms. Our objective was to quantify the reduction in incidence of CM, metritis, and ABU, and the herd performance of a representative US herd that uses genomic selection for Lifetime Net Merit 2018 (NM$) selection index, compared with genetic selection based only on the mastitis (MAST) or metritis resistance (METR) trait or a health trait subindex (HTH$). A stochastic dynamic simulation model of a 1,000-cow herd with multi-trait genetics for 19 correlated traits included in the NM$ affected the performance of animals. The incidence of CM and metritis for each animal was affected by the genetic and environmental components of the MAST or METR, along with a standard phenotypic function that calculated the daily underlying herd probability to contract CM or metritis. Selection decisions were made based on genomic estimated breeding values of the traits of interest. A strategy named AI-NM$ based decisions on the NM$ trait so that the correlated genetic trends in MAST and METR are improved. Three other strategies named AI-MAST, AI-METR, and AI-HTH$ maximized respectively MAST, METR, and HTH$ genetic merit, but with a tradeoff in NM$ genetic merit. The cumulative true breeding values (TBV) of NM$ for 15 yr showed a difference of $4,947 per cow between the AI-NM$ (best strategy for NM$) and AI-METR (worst strategy for NM$). However, the 15-yr cumulative TBV of MAST was 26.50 percentage points (PP) higher in AI-MAST, and 18.5 PP higher for METR in AI-METR, compared with AI-NM$. As a result, the 15-yr cumulative phenotypic CM and metritis incidence was respectively 94.03 PP and 58 PP lower in AI-MAST and AI-METR compared with AI-NM$. Therefore the corresponding 15-yr cumulative ABU decreased by 42% in AI-MAST and by 53% in AI-METR. We found that AI-MAST had the lowest CM incidence across the 15 yr, whereas AI-METR had the lowest incidence of metritis and the smallest total ABU for 15 yr. To achieve the lowest incidence of CM, metritis, and ABU strategies AI-MAST, AI-METR, and AI-HTH$ had to incur 15-yr discounted cumulative losses per cow of $1,486, $1,434, and $1,130, respectively, compared with AI-NM$. Hence, AI-NM$ had the best financial performance, despite having slightly higher incidence of CM, metritis, and ABU.

Comparison between an exclusive in vitro-produced embryo transfer system and artificial insemination for genetic, technical, and financial herd performance.

The objective of this study was to implement an in vitro-produced embryo transfer (IVP-ET) system in an existing stochastic dynamic dairy simulation model with multitrait genetics to evaluate the genetic, technical, and financial performance of a dairy herd implementing an exclusive IVP-ET or artificial insemination (AI) system. In the AI system, sexed semen was used on the genetically best heifers only. In the IVP-ET system, all of the animals in the herd were impregnated with female sexed embryos created through in vitro fertilization of oocytes collected from animals of superior genetics for different traits of interest. Each donor was assumed to yield on average 4.25 transferable embryos per collection. The remaining animals in the herd were used as recipients and received either a fresh embryo or a frozen embryo when fresh embryos were not available. Selection of donors was random or based on the greatest estimated breeding value (EBV) of lifetime net merit (NM$), milk yield, or daughter pregnancy rate. For both the IVP-ET and AI systems, culling of surplus heifer calves not needed to replace culled cows was based on the lowest EBV for the same traits. A herd of 1,000 milking cows was simulated 15 yr over time after the start of the IVP-ET system. The default cost to produce and transfer 1 embryo was set at $165. Prices of fresh embryos at which an exclusive IVP-ET system financially breaks even with the comparable AI system in yr 15 and for an investment period of 15 yr were also estimated. More surplus heifer calves were sold from the IVP-ET systems than from the comparable AI systems. The surplus calves from the IVP-ET systems were also genetically superior to the surplus calves from the comparable AI systems, which might be reflected in their market value as a premium price. The most profitable scenario among the 4 IVP-ET scenarios in yr 15 was the one in which NM$ was maximized in the herd. This scenario had an additional profit of $8/cow compared with a similar AI scenario that maximized NM$, provided that surplus heifer calves could be sold at a premium price based on the superiority of the EBV of NM$. For the IVP-ET system to be at least as profitable as the comparable AI system during a 15-yr investment period, the surplus calves from the IVP-ET system needed to be sold at the premium prices. The break-even price of fresh embryos was estimated to be $84 for the exclusive IVP-ET system. This resulted in the same profit as the AI system, which maximized NM$ for a 15-yr investment period and in which heifer calves were sold at a premium price.

Stochastic dynamic simulation modeling including multitrait genetics to estimate genetic, technical, and financial consequences of dairy farm reproduction and selection strategies.

The objective of this study was to develop a daily stochastic dynamic dairy simulation model that included multitrait genetics and to evaluate the effects of reduced genetic models and various reproduction and selection strategies on the genetic, technical, and financial performance of a dairy herd. The 12 correlated genetic traits included in the 2014 lifetime net merit (NM$) index were modeled for each animal. For each animal, a true breeding value (TBV) for each trait was calculated as the average of the sire's and dam's TBV, plus a fraction of the inbreeding and Mendelian sampling variability. Similarly, an environmental component for each trait was calculated and was partitioned into a permanent and a daily (temporary) effect. The combined TBV and environmental effects were converted into the phenotypic performance of each animal. Hence, genetics and phenotypic performances were associated. Estimated breeding values (EBV) were also simulated. Genetic trends for each trait for the service sire were based on expected trends in US Holsteins. Surplus heifers were culled based on various ranking criteria to maintain a herd size of 1,000 milking cows. In the first 8 scenarios, culling of surplus heifers was either random or based on the EBV of NM$. Four different genetic models, depending on the presence or absence of genetic trends or genetic and environmental correlations, or both, were evaluated to measure the effect of excluding multitrait genetics on animal performance. In the last 5 scenarios, the full genetic model was used and culling of surplus heifers was either random or based on the EBV of NM$ or the EBV of milk. Sexed semen use and reliability of the EBV were also varied. Each scenario was simulated for 15yr into the future. Results showed that genetic models without all 12 genetic trends and genetic and environmental correlations provided biased estimates of the genetic, technical, and financial performance of the dairy herd. Average TBV of NM$ of all cows in the herd was $263 greater in yr 15 in a scenario that combined sexed semen use in heifers and culling of surplus heifers with the lowest EBV of NM$, compared with a scenario that used only conventional semen and surplus heifers were culled randomly. The average TBV of daughter pregnancy rate of all cows in the herd was 1.25 percentage points greater in yr 15 in a scenario that combined using sexed semen in heifers as well as culling of surplus heifers ranked by EBV of NM$, compared with a scenario using conventional semen only as well as culling surplus heifers ranked by EBV of milk. In conclusion, the multitrait genetics model resulted in improved estimates of genetic, technical, and financial effects and appears useful to evaluate consequences of various reproduction and selection strategies within a dairy farm.

Agreement between milk fat, protein, and lactose observations collected from the Dairy Herd Improvement Association (DHIA) and a real-time milk analyzer.

The objective of this study was to quantify the agreement between AfiLab real-time milk analyzer (Afimilk, Kibbutz Afikim, Israel) measures for fat, protein, and lactose based on near-infrared spectrum light scattering, and those collected on Dairy Herd Improvement Association (DHIA) test days and measured with the Bentley 2000 analyzer (Bentley Instruments Inc., Chaska, MN), which uses mid-infrared spectrum light. The AfiLab data were collected twice daily for each milking cow in the herd at 12-h intervals from the double-12 parlor at the University of Florida Dairy Unit (Hague, FL) from January 2010 to December 2011. Bentley data for the 23 DHIA test days in 2010 and 2011 were also obtained. Approximately 450 cows were tested each month. Tested milk was collected during 1 milking each month, alternating monthly between morning and evening milkings. AfiLab data were matched with Bentley fat and protein (n=10,273; 23 test days) and lactose (n=6,741; 16 test days). Overall means ± standard deviations (SD) of monthly mean Bentley fat, protein, and lactose were 3.74 ± 0.80%, 3.06 ± 0.37%, and 4.76 ± 0.30%, respectively. Overall means ± SD of monthly mean AfiLab minus Bentley observations were -0.08 ± 0.12 percentage points (PP) for fat (n=23), 0.02 ± 0.11 PP for protein (n=23), and -0.02 ± 0.08 PP for lactose (n=16). Overall means ± SD of monthly within-test-day SD of AfiLab minus Bentley observations were 0.66 ± 0.11 PP for fat, 0.27 ± 0.03 PP for protein, and 0.26 ± 0.03 PP for lactose. Overall means ± SD of the corresponding monthly correlations were 0.59 ± 0.09 for fat, 0.67 ± 0.04 for protein, and 0.46 ± 0.08 for lactose. Averaging the AfiLab observations from up to 6 milkings before and after the test-day milking improved the agreement for protein and lactose but not for fat. Averaging the 13 protein observations improved the mean difference to 0.01 ± 0.10 PP and the SD of the difference to 0.23 ± 0.03 PP. The correlation increased to 0.78 ± 0.04. Averaging the 13 lactose observations improved the SD of the difference to 0.23 ± 0.02 PP, but the mean of the difference decreased to -0.03 ± 0.09 PP. The correlation for lactose increased to 0.55 ± 0.05. Generally, AfiLab slightly overestimated low Bentley components and underestimated high Bentley components. We found some evidence for a systematic cow effect on lack of agreement for lactose, but not for fat and protein. The agreement between AfiLab and Bentley observations was better for protein and lactose than that for fat. Combinations of AfiLab observations from various milkings improved the agreement for protein and lactose. AfiLab real-time milk analyzers may be helpful to estimate DHIA observations.

Effect of feeding according to energy balance on performance, nutrient excretion, and feeding behavior of early lactation dairy cows.

The objectives of this study were to evaluate 2 feeding strategies for early lactation cows on performance and efficiency of nutrient utilization. Fifty-eight Holsteins cows were blocked by parity and production during the pretreatment period and then randomly assigned at 21 d postpartum to a control diet [n=29; 16.2% crude protein, 1.64 Mcal of net energy for lactation (NE(L)), 22% starch, and 19% forage neutral detergent fiber (NDF)] or a diet with caloric density manipulated weekly (precision diet; n=29; 16.2% crude protein; 1.59 to 1.68 NE(L); 18 to 26% starch; and 16 to 22% forage NDF) to promote a calculated positive energy balance of 5 Mcal/day. Diets were fed as total mixed rations and precision cows had their diets adjusted individually once a week, by feeding additional grain supplementation from 0 to 25% of daily dry matter (DM) offered, according to the energy balance of the preceding week. Energy balance was calculated daily and then averaged weekly. The study lasted from wk 3 to 19 postpartum, and nutrient digestibility, rumen fluid composition, urinary output, estimates of microbial protein synthesis, and feeding behavior were evaluated between wk 9 and 13 postpartum. Compared with controls, precision cows had similar DM intake (24.3 kg/d), but NE(L) intake tended to be greater primarily between wk 4 and 8 postpartum. Yields of milk (45.2 vs. 41.9 kg/d), milk components, 3.5% fat-corrected milk (44.0 vs. 40.8 kg/d), and energy-corrected milk (43.4 vs. 40.2) were all greater for precision than control cows, resulting in greater energy-corrected milk production per kilogram of diet DM consumed (1.79 vs. 1.72). Precision cows produced more milk calories per kilogram of metabolic weight (0.227 vs. 0.213 Mcal of NE(L)/kg), although the amount of consumed calories partitioned into milk (82.3%) and measures of energy status did not differ between treatments throughout the study. Glucose concentrations were greater throughout the day in precision cows compared with controls at 6 wk, but not 13 wk postpartum. Apparent digestibility of nutrients, composition of rumen fluid, mean and low rumen pH, and estimated rumen microbial N synthesis remained mostly unaltered by treatments. Although precision cows produced more milk true protein, measures of efficiency of dietary N use were not influenced by treatment. On wk 13 postpartum, precision cows consumed a diet with longer NDF particles, which resulted in a tendency for greater intake of NDF >8mm because of less sorting against the long particles than control cows. Meal pattern differed with treatment, and precision cows consumed feed more sparsely throughout the day, spent more time ruminating lying, and had similar meal duration (mean of 36.3 min/meal) compared with control cows, but smaller meal size (3.33 vs. 3.64 kg/meal). Results from the current study indicate that allocating dietary resources according to the individual needs of cows based on energy balance improves lactation performance compared with feeding a single total mixed ration, despite similar average nutrient intake between treatments. Improvements in performance are likely related to allocation of calories based on the needs of the cow and on shifts of feeding behavior that might favor intake of smaller meals.

Economics of reducing antibiotic usage for pathogen-specific clinical mastitis through genomic selection and disease management.

The recent introduction of the mastitis resistance trait into the US genomic selection index, Lifetime Net Merit 2018 (NM$), is expected to reduce the incidence of pathogen-specific clinical mastitis (PS-CM) incidence in U.S. dairy herds. To maximize the herd performance by reducing the PS-CM incidence, we compared the herd performance of 6 different replacement selection and PS-CM disease management strategies. We used an agent-based dairy simulation model in which the performance of individual animals was affected by the genetic traits included in the NM$. The genetic trends for the sires used affected the 15 yr herd performance. Each animal had a daily underlying base probability of contracting 5 different types of PS-CM (Staphylococcus aureus, Streptococcus dysgalactiae, Strep. uberis, Escherichia coli and Klebsiella) during lactation. On top of this base probability, the genetic and environmental components of the mastitis resistance trait (MAST) determined the actual incidence of PS-CM. Genomic estimated breeding values were simulated for each animal, based on which replacement selection decisions were made. The PS-CM associated milk loss, increased somatic cell count, decreased conception, and increased mortality and culling were accounted for in the simulated genomic estimated breeding values of different correlated production and reproduction traits included in NM$. The 6 different strategies illustrate the effects of replacement selection and PS-CM management decisions on PS-CM incidence, herd antibiotic use (ABU) and herd economics, over the course of 15 yr. Due to the genetic gain in the MAST, the incidence of PS-CM decreased on average by 10% points in 15 yr, which trickled down to overall reduction in herd ABU. Our PS-CM treatment and prevention strategies were assumed to be based on precise information about the 5 different PS-CM causative pathogens. Hence the corresponding ABU further decreased over the course of 15 years, when compared to blanket PS-CM therapies, which used antibiotics for all cases of CM. Our strategies illustrated the fact that herds combining genomic selection and following precise treatment and prevention strategies for PS-CM could reduce the 15-year cumulative ABU against PS-CM significantly. Capitalizing on the genetic gain in NM$ traits, the average profit per cow per year was higher on average by $1209 in year 15 when compared to year 0 for the 6 strategies simulated. We concluded that three decision strategies (genomic selection for NM$, selective therapy for PS-CM, and selective dry cow therapy for PS-CM prevention) when combined can reduce the incidence of PS-CM and the associated ABU, while increasing the profitability of the herd.

Cost benefit analysis of automatic lameness detection systems in dairy herds: A dynamic programming approach.

Epidemiological data establish that lameness is second only to mastitis as the dairy industry's most prevalent and costly animal welfare issue. Using an automatic lameness detection (ALD) system in which continuous, accurate detection is coupled with proper treatment, is key for reducing economic losses due to lameness. It is reasonable to assume that the cost of lameness would vary with its severity. Therefore, our first objective was to estimate the cost of different lameness severity levels as a function of milk production, lameness risk, conception probability, and treatment cost using a dynamic programming (DP) model. Our second objective was to conduct a cost benefit analysis for ALD systems which can reduce production losses through early detection and treatment of lameness, when compared to visual-detection (VD; i.e., performed by humans) systems. The default production loss parameters for the VD system used as inputs to the DP model were either sourced from the literature or were estimated based on data from a field trial. The production loss parameters for the ALD system used as inputs to the DP model were based on extrapolations of parameter values used for the VD system. The profit per present cow per year under assumed expenses and revenues decreased from $426.05 (when lameness incidence was assumed to be 0%) to $389.69 when lameness incidence was 19.5 %. Out of the 19.5 % lameness incidence in our default scenario, 9.8 % were moderate cases and 9.7 % were severe cases. Average cost of lameness was $36.36 at 19.5 % incidence. Average cost of lameness increased with increased incidence and was respectively $82.05, $195.05, and $286.87 at the low, medium, and high incidence scenarios. We used an operational framework which compared the lameness costs between the VD and ALD systems with 25 %, 50 % and 75 % net avoided costs (NAC) for the 10 year lifespan of the ALD system, at default, low, medium and high lameness incidence scenarios. The net return per cow per year from using an ALD system over a VD system was $13, at low incidence and 25 % NAC. The net return per cow per year for the ALD system was as high as $99 at high incidence and 75 % NAC. Out of 351 (3 system prices, 3 system efficiencies, 3 levels of lameness incidence and 13 different herd sizes) scenarios tested, 295 resulted in a net profit within the system lifespan of 10 years, thus justifying the investment in ALD systems.