Associations of automated body condition scores at dry-off and through early lactation with milk yield of Holstein cows.

The objective of this study was to analyze the associations of body condition score (BCS) and BCS change (∆BCS) during the dry period and the first 100 d of lactation with daily milk yield. Examining the involvement of health status in the associations between BCS and milk yield was a secondary objective of this research. Data included 12,042 lactations in 7,626 Holstein cows calving between April 2019 and January 2022 in a commercial dairy operation located in Colorado, USA. BCSs were generated daily by an automated BCS camera system located at the exit of the milking parlor. The assessment points selected for this study were dry-off (BCSdry), calving (BCS1), 7 DIM (BCS7), 14 DIM (BCS14), 21 DIM (BCS21), and nadir (nBCS; defined as the lowest daily BCS from calving to 100 DIM). Subsequently, these BCS were categorized considering quartiles (Q1 = 25% lowest BCS; Q4 = 25% greatest BCS), separately for primiparous and multiparous cows. Changes in BCS were calculated from dry-off to calving (multiparous); and from calving to 7 DIM, 14 DIM, 21 DIM, and nadir and assigned into quartile categories considering Q1 as the 25% of cows with the greatest decrease of BCS. Lactations were classified based on the number of health events before nadir as healthy, affected by one event, or having multiple events. Data were examined in primiparous and multiparous cows separately using ANOVA. The least square means for daily milk at 60 DIM and 305 DIM were calculated by category of BCS and ∆BCS at multiple time points and time periods. Subsequently, lactation curves were created by BCS and ∆BCS categories and by health status. Multivariable models included calving season and BCS1 as covariables. The largest differences in milk yield among categories of BCS and ∆BCS were identified for BCS originated at nadir and for the ∆BCS between calving and nadir. The differences in average daily milk yield between cows in the lowest and the greatest nBCS category (Q1 vs. Q4) were 3.3 kg/d (60 DIM) and 3.4 kg/d (305 DIM) for primiparous cows and 2.4 kg/d (60 DIM) and 2.1 kg/d (305 DIM) for multiparous cows. During the period from calving to nadir, primiparous cows in Q1 (greatest decrease of BCS) produced 4.3 kg/d (60 DIM) and 3.8 kg/d (305 DIM) more than cows in Q4. For multiparous cows, the differences were 3.0 kg/d (60 DIM) and 1.9 kg/d (305 DIM) in favor of Q1 cows. Overall, the associations between BCS and ∆BCS categories and milk yield were not consistent across time and they depended on the parity category. Nonetheless, as the assessment of BCS and ∆BCS approached the nadir, the association between greater milk yield and lower BCS or greater reduction in BCS became more evident.

The objective of this study was to analyze the associations of body condition score (BCS) and BCS change (∆BCS) during the dry period and the first 100 d of lactation with daily milk yield. The involvement of health status in these associations was also evaluated. The relationship between BCS and ∆BCS with milk yield was more evident for nadir BCS (nBCS; defined as the lowest daily BCS from calving to 100 d in milk [DIM]) and for the ∆BCS occurring between calving and nBCS. Cows categorized in the lowest nBCS category and cows with greater loss in BCS from calving to nadir had the greatest average milk yields at 60 DIM and 305 DIM. In agreement, clear patterns for lactation curves were identified when the study cows were categorized by nBCS and ∆BCS for the calving to nBCS period. There was no evident association of health status with the reported relationships between BCS and milk yield.

Factors associated with the time and magnitude of the nadir body condition score in early lactation and its subsequent effects on fertility of Holstein cows.

The objective of this study was to identify variables associated with the time and magnitude of nadir BCS (nBCS) during early lactation and to characterize the effects of these two measurements on the subsequent pregnancy at first artificial insemination (P/AI1) and pregnancy loss of Holstein cows. A retrospective observational study was completed using data collected from 12,042 lactations in 7,626 Holstein cows calving between April 2019 and January 2022 in a commercial dairy operation located in Colorado, USA. Scores generated by an automated BCS camera system at dry-off (BCSdry), calving (BCS1), nadir (nBCS; defined as the lowest daily BCS from calving to 100 DIM), and 21 d post nadir were selected for the analyses and subsequently categorized into quartiles (Q1 = lower nBCS). Changes in BCS were calculated from dry-off to calving (multiparous cows); from calving to nadir; and from nadir to 21 d post nadir and assigned into quartile categories considering Q1 as the 25% of cows with greater loss (pre nadir) or smaller gain (post nadir) of BCS. Data were examined using logistic regression, ANOVA, and time to event analyses. Initial univariable models were followed by multivariable models that considered parity category, calving season, BCS1, and average milk yield up to 30 DIM (M30) as covariables. Sick cows and high producing cows had increased DIM at nadir, while lower BCSdry, greater M30, and occurrence of disease were associated with lower nBCS. Cows that conceived at AI1 had their nBCS earlier (45.1 ± 0.32 d) than cows that remained open after first AI (46.4 ± 0.35 d). On the contrary, DIM at nBCS did not differ by pregnancy loss status. The logistic regression analyses reported smaller odds of P/AI1 in cows in the lower nBCS categories. Likewise, cows with larger loss in BCS between calving and nadir had smaller odds of P/AI1. Although cows that lost their pregnancy had lower nBCS, this association was not consistent across the analyses. The time to and magnitude of nBCS, together with the ∆BCS from calving to nadir could be useful measures to evaluate the transition and early lactation status of dairy cows.

The transition from gestation to lactation requires adjustments in nutrient consumption that are challenging for the postpartum dairy cow. As milk energy output increases more rapidly than energy intake, most cows mobilize fat and labile protein from body energy reserves, which results in reductions in body condition score during early lactation. The objective of this study was to identify variables associated with the extent of the lossin body condition score (BCS) during early lactation and to characterize the effects of the nadir BCS on the subsequent pregnancy at first artificial insemination and pregnancy loss in Holstein cows. Parity, disease presentation, and milk yield were associated with the time and magnitude of nadir BCS. Sick cows and high producing cows had increased DIM at nadir, while lower BCS at dry-off, greater milk yield, and occurrence of disease were associated with lower nadir BCS. Overall, cows with later and lower nadir BCS and greater loss of BCS between calving and nadir had poorer fertility. Monitoring nadir BCS could be a useful tool for evaluating the transition and early lactation status of dairy cows.

Association between body condition score fluctuations and pregnancy loss in Holstein cows.

The objective of this study was to characterize the associations between body condition score (BCS) and BCS change (∆BCS), determined by an automated camera system during early lactation and close to artificial insemination (AI), and the subsequent pregnancy loss (PL) in Holstein cows. A secondary objective was to determine the impact of disease on PL, considering multiple time periods relative to AI. Data from 9,430 lactations in 6,884 Holstein cows in a commercial dairy operation located in Colorado, USA were included in this retrospective observational study. Cows were subject to first AI at about 80 DIM (primiparous) and 60 DIM (multiparous), following a double OvSynch protocol. Pregnancy diagnosis was performed via transrectal ultrasonography on day 32 ± 3 after AI and reconfirmed on day 80 ± 3 after AI. Cameras mounted on the sorting gate at each exit (n = 2) of the milking parlor generated BCS on a five-point scale with 0.1 increments. The BCS at calving (BCS1), 21 DIM (BCS21), 56 DIM (BCS56), AI resulting in pregnancy (BCSAI), and 90 d post AI (BCSAI90) were selected for the analyses and subsequently categorized as low (≤ lower quartile), moderate (interquartile range), and high (≥ upper quartile). Changes in BCS were calculated by periods of interest as change from calving to 21 DIM; change from calving to 56 DIM; change from 56 DIM to AI; and change from AI to 90 d post AI and assigned into categories to facilitate the analysis. Data were examined using logistic regression, considering parity category, season at calving and AI, DIM at AI, milk yield up to 60 DIM, and occurrence of disease as covariables. The logistic regression analyses indicated that the odds of PL were greater in cows in the low BCS category relative to cows in the high BCS category at 56 DIM (OR 95% CI = 1.41 [1.12-1.79]), AI (1.31 [1.05-1.65]), and 90 d post AI (1.38 [1.10-1.74]). Likewise, cows with large loss in BCS between calving and 21 DIM (1.46 [1.10-1.94]) and loss in BCS between AI and 90 d post AI (1.44 [1.15-1.81]) had greater odds of PL compared with cows with no loss of BCS within the same period. Occurrence of disease at all the time periods considered in the analysis had a consistent detrimental impact on maintenance of the pregnancy, supporting the concept that pre and postconceptional disease affects embryonic survival. Overall, low BCS, more pronounced reductions in BCS occurring closer to AI, and occurrence of disease resulted in greater PL in this Holstein population.

Maintenance of the pregnancy until term is a key factor for adequate fertility in dairy operations, as early embryonic mortality in lactating dairy cows is significant. The objective of this study was to investigate the association between the changes in body condition scores (BCS) during early lactation and in the proximity of artificial insemination (AI) and embryo mortality in Holstein cows. A secondary objective was to determine the impact of disease on pregnancy loss (PL), considering multiple time periods relative to AI. Our study population included 9,430 lactations in 6,884 Holstein cows that had their daily BCS determined by an automated camera system during early lactation and close to AI. Cows were diagnosed pregnant via transrectal ultrasonography on day 32 after AI and reconfirmed on day 80 after AI. Overall, the dynamics of BCS differed between cows that lost or did not lose their pregnancy. Low BCS and more pronounced reductions in BCS occurring closer to the AI, as well as concurrent disease, resulted in greater levels of PL.

Integrated Decision Support Systems (IDSS) for Dairy Farming: A Discussion on How to Improve Their Sustained Adoption.

Dairy farm decision support systems (DSS) are tools which help dairy farmers to solve complex problems by improving the decision-making processes. In this paper, we are interested in newer generation, integrated DSS (IDSS), which additionally and concurrently: (1) receive continuous data feed from on-farm and off-farm data collection systems and (2) integrate more than one data stream to produce insightful outcomes. The scientific community and the allied dairy community have not been successful in developing, disseminating, and promoting a sustained adoption of IDSS. Thus, this paper identifies barriers to adoption as well as factors that would promote the sustained adoption of IDSS. The main barriers to adoption discussed include perceived lack of a good value proposition, complexities of practical application, and ease of use; and IDSS challenges related to data collection, data standards, data integration, and data shareability. Success in the sustainable adoption of IDSS depends on solving these problems and also addressing intrinsic issues related to the development, maintenance, and functioning of IDSS. There is a need for coordinated action by all the main stakeholders in the dairy sector to realize the potential benefits of IDSS, including all important players in the dairy industry production and distribution chain.

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.

Distribution of seasonality of calving patterns and milk production in dairy herds across the United States.

Calving patterns and milk production are seasonal throughout the United States; however, the distribution of seasonality, and the extent to which this seasonality is due to direct effects of climate on milk production and reproductive performance or farm management, is not well quantified. Summer-to-winter (SW) ratios have been used as measures of seasonality, but other measures such as low-to-peak (LP) ratios have been proposed. Our objectives were (1) to describe the distribution of seasonality in calving pattern and milk production among herds in the United States, (2) to compare SW and LP ratios of calving pattern and milk production, (3) to quantify the effect of a seasonal calving pattern, parity, and percentage of dry cows on seasonality of milk production, and (4) to describe the association between seasonality in calving pattern and milk production, herd size, and daily milk production per cow. The final data set contained Dairy Herd Improvement Association lactation records from 2015 from 5,292 (calving pattern) and 5,200 (milk production) herds for 41 states in the United States. We used generalized linear regression models with 1 sinusoidal curve to model calving pattern and milk production per cow for each herd. For milk production, a model adjusting for days in milk (DIM) and the interaction of DIM and parity (ADJ) and a model that was not adjusted (NO) were run. Both models included the effect of the percentage of dry cows. We used SW and LP ratios calculated from the parameters of the sinusoidal component of the models as measures of seasonality. The variability within states for all seasonality measures was large. The median LP ratio of calving pattern was 0.61, and small herds were more seasonal (LP ratio 0.56) than large herds (LP ratio 0.75). For milk production, the median LP ratio-NO was 0.88, and the LP ratio-ADJ was 0.90. Small herds were more seasonal (0.89) than large herds (0.92) when their LP ratios-ADJ were compared. States in the south of the United States were the most seasonal for calving patterns and milk production. Adjusting for DIM and parity increased the LP ratio of milk production by 8.9% for 66% of the herds. Adjusting for the percentage of dry cows increased the LP ratio in 72.9% of the herds by a median value of 21.8%. The correlations between SW and LP ratios were weak. Herds that were more seasonal for milk production had a lower average daily milk per cow than less-seasonal herds. In conclusion, seasonality in calving patterns and milk production among herds varied greatly across the United States. Sinusoidal models with covariates allowed for quantification of the effects of calving pattern, DIM, and parity on the seasonality in milk production. The LP ratios captured the maximum seasonality better than SW ratios did.

Effectiveness of tunnel ventilation as dairy cow housing in hot climates: rectal temperatures during heat stress and seasonal variation in milk yield.

Tunnel ventilation is an increasingly popular approach to mitigate the effects of heat stress on dairy cattle. Tunnel-ventilation barns use a bank of high-power fans to move air horizontally from one end of the barn to the other at cow level. The overall objective of the present experiments was to determine whether tunnel ventilation is superior to housing with fans and sprinklers with respect to rectal temperature during heat stress and seasonal variation in milk yield. In the first study, rectal temperatures were measured for 1097 lactating Holstein cows in six freestall barns with fans and sprinklers and 575 lactating Holsteins in four tunnel-ventilated freestall barns at a time point between 14:00 and 16:00 h during the months of June to August in Florida, USA. Rectal temperatures were lower for cows in tunnel-ventilation barns than sprinkler-and-fan barns when the tunnel-ventilation barns were built de novo but not when the tunnel-ventilation barns were produced by retrofitting a sprinkler-and-fan barn (interaction, P = 0.0129). In the second study, average daily milk yield in the first 90 days in milk was examined for 8470 lactating Holsteins housed in three sprinkler-and-fan barns and two tunnel-ventilation barns. Milk production for cows calving in cool weather (October to March) was greater (P < 0.0001) than for cows calving in hot weather (April to September). The seasonal reduction in milk yield was less for cows (P = 0.037) in tunnel-ventilation barns (3.5% decrease) than for cows in sprinkler-and-fan barns (5.8% decrease). With this difference in impact of heat stress, it was estimated at a dairy farm could invest up to a $332 more per cow space in a tunnel-ventilated barn than in a sprinkler-and-fan barn. It was concluded that housing cows in tunnel-ventilation barns can reduce the impact of heat stress on body temperature regulation and milk yield.

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.

Combined effect of mastitis and parity on pregnancy loss in lactating Holstein cows.

The main objective of this study was to examine the combined effect of mastitis and parity on pregnancy loss (PL) in lactating Holstein cows. A secondary objective was to estimate the cost of mastitis including that of PL attributable to mastitis. A total of 1,774 lactation periods from 1,047 Holstein cows with different parities from one dairy farm were included in a matched case-control study. All study cows were diagnosed pregnant by transrectal ultrasonography on day 33 after timed artificial insemination (TAI). Case cows (n = 222 lactations) were those later diagnosed non-pregnant by transrectal palpation on day 47 or 75 after TAI. Control cows (n = 1,552 lactations) were those confirmed pregnant by transrectal palpation on day 75 after TAI. Case cows were matched with eligible controls according to year of calving and calving-to-conception interval (CCI) ± 3 days. Cows with different parities were classified as exposed to subclinical mastitis (somatic cell score (SCS) > 4.5 in at least one Dairy Herd Improvement Association (DHIA) test day) or clinical mastitis (with or without evidence of subclinical mastitis) during two exposure periods: 1-42 days before breeding or 1-75 days during gestation (1 to PL diagnosis day in case cows, or 1-75 day in control cows). Conditional logistic regression was used to model the odds of PL as a function of previous exposure to mastitis in different parities. Cost of PL attributable to mastitis ($/case) among cows with mastitis was estimated based on attributable risk calculated in the epidemiologic analysis. We observed a higher than expected combined effect between exposure to mastitis (subclinical or clinical) before breeding and parity 3 or ≥ 4, and during gestation and parity ≥ 4 on PL. The cost of PL attributable to mastitis was highest ($196/case) in cows in parity ≥ 4 affected with clinical mastitis during gestation. Overall, study results indicate the impact of mastitis on PL is higher in older cows (parity ≥ 3). Dairy farmers and attending veterinarians can consider the combined effect of mastitis and parity when evaluating causes for PL and strategies for optimizing reproductive performance in dairy cows.

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.

Impact of applying sex sorted semen on the selection proportion of the sire of dams selection pathway in a nucleus program.

OBJECTIVE: In a nucleus breeding scheme, the sire of dam's pathway plays an important role in producing genetic improvement. Selection proportion is the key parameter for predicting selection intensity, through truncating the normal distribution. Semen sexing using flow cytometry reduces the number of vials of sperm that can be obtained from a proved bull. In addition, a lower fertility of this kind of sperm is expected because of the lower sperm dosage in sex sorted semen. Both of these factors could affect the selection proportion in the sire of dam's pathway (pSD). METHODS: In the current study, through a deterministic simulation, effect of utilizing sex sorted semen on selection (pSD) was investigated in three different strategies including 1: continuous use of sex sorted semen in heifers (CS), 2: the use of sex sorted semen for the first two (S2) and 3: the first (S1) inseminations followed by conventional semen. RESULTS: Results indicated that the use of sex sorted semen has a negative impact on the sire of dams (SD) pathway due to increase in selection proportion. Consequently selection intensity was decreased by 10.24 to 20.57, 6.38 to 8.87 and 3.76 to 6.25 percent in the CS, S2, and S1 strategies, respectively. CONCLUSION: Considering the low effect of sexed semen on genetic improvement in dam pathways, it is necessary to consider the joint effect of using sex sorted semen on the sire and dams pathway to estimate about the real effect of sexed semen on genetic improvement in a nucleus breeding scheme.

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.

Evidence that mastitis can cause pregnancy loss in dairy cows: A systematic review of observational studies.

The objective of this study was to conduct a systematic review to identify and assess evidence and knowledge gaps in published observational studies that have investigated the relationship between mastitis and pregnancy loss (PL) in dairy cows. PubMed and ScienceDirect were used to search pertinent peer-reviewed research reports of interest. Screening of research reports was conducted at 3 levels: titles, abstracts, and full-text articles. The search identified 651 records for initial screening. The final screening process identified 8 qualified articles for review after removing 10 duplicate records, 582 titles, 31 abstracts, and 20 full-text articles. Two studies produced strong epidemiologic evidence indicating that (1) exposure to clinical mastitis during early gestation (first 45 d of gestation) is associated with subsequent PL during the following 90 d; and (2) subclinical mastitis 1 to 30 d before artificial insemination (AI) is associated with subsequent PL at 35 to 41 d of gestation. An additional study showed that exposure to clinical mastitis during early lactation in combination with low body condition can increase the risk of PL in dairy cows; however, the interaction effect between clinical mastitis and low body condition on PL was considered weak. Four other studies produced inconclusive evidence indicating that mastitis is a predisposing factor for PL in dairy cows, as the exposure risk period for mastitis overlapped with the follow-up period for diagnosis of PL in dairy cows. Finally, one study failed to identify a relationship between mastitis and PL in dairy cows. Further research is needed to (1) support the hypothesis that mastitis in combination with low body condition score (or other exposure factors) can increase the risk of PL, (2) compare the effect of clinical versus subclinical mastitis on PL, (3) compare the effect of mastitis before breeding and during gestation on PL, and (4) compare the effect of mastitis on PL in dairy cows during different lactations.

Bayesian integration of sensor information and a multivariate dynamic linear model for prediction of dairy cow mastitis.

Rapid detection of dairy cow mastitis is important so corrective action can be taken as soon as possible. Automatically collected sensor data used to monitor the performance and the health state of the cow could be useful for rapid detection of mastitis while reducing the labor needs for monitoring. The state of the art in combining sensor data to predict clinical mastitis still does not perform well enough to be applied in practice. Our objective was to combine a multivariate dynamic linear model (DLM) with a naïve Bayesian classifier (NBC) in a novel method using sensor and nonsensor data to detect clinical cases of mastitis. We also evaluated reductions in the number of sensors for detecting mastitis. With the DLM, we co-modeled 7 sources of sensor data (milk yield, fat, protein, lactose, conductivity, blood, body weight) collected at each milking for individual cows to produce one-step-ahead forecasts for each sensor. The observations were subsequently categorized according to the errors of the forecasted values and the estimated forecast variance. The categorized sensor data were combined with other data pertaining to the cow (week in milk, parity, mastitis history, somatic cell count category, and season) using Bayes' theorem, which produced a combined probability of the cow having clinical mastitis. If this probability was above a set threshold, the cow was classified as mastitis positive. To illustrate the performance of our method, we used sensor data from 1,003,207 milkings from the University of Florida Dairy Unit collected from 2008 to 2014. Of these, 2,907 milkings were associated with recorded cases of clinical mastitis. Using the DLM/NBC method, we reached an area under the receiver operating characteristic curve of 0.89, with a specificity of 0.81 when the sensitivity was set at 0.80. Specificities with omissions of sensor data ranged from 0.58 to 0.81. These results are comparable to other studies, but differences in data quality, definitions of clinical mastitis, and time windows make comparisons across studies difficult. We found the DLM/NBC method to be a flexible method for combining multiple sensor and nonsensor data sources to predict clinical mastitis and accommodate missing observations. Further research is needed before practical implementation is possible. In particular, the performance of our method needs to be improved in the first 2 wk of lactation. The DLM method produces forecasts that are based on continuously estimated multivariate normal distributions, which makes forecasts and forecast errors easy to interpret, and new sensors can easily be added.

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.