Combining reproductive outcomes predictors and automated estrus alerts recorded during the voluntary waiting period identified subgroups of cows with different reproductive performance potential

The objective was to compare differences in reproductive performance for dairy cows grouped based on the combination of data for predictors available during the prepartum period and before the end of the voluntary waiting period (VWP), automated estrus alerts (AEA) during the VWP, and the combination of both factors. In a cohort study, data for AEA and potential predictors of the percentage of cows that receive AI at detected estrus (AIE), pregnancies per AI (P/AI) for first service, and the percentage of cows pregnant by 150 DIM (P150) were collected from -21 to 49 DIM for lactating Holstein cows (n = 886). The association between each reproductive outcome with calving season (cool, warm), calving-related events (yes, no), genomic daughter pregnancy rate (gDPR; high, medium, low), days in the close-up pen (ideal, not ideal), health disorder events (yes, no), rumination time (high or low CV prepartum and high or low increase rate postpartum), and milk yield (MY) by 49 DIM (high, medium, low) were evaluated in univariable and multivariable logistic regression models. Individual predictors (health disorders, gDPR, and MY) associated with the 3 reproductive outcomes in all models were used to group cows based on risk factors (RF; yes, n = 535 or no, n = 351) for poor reproductive performance. Specifically, cows were included in the RF group if any of the following conditions were met: the cow was in the high MY group, had low gDPR, or had at least 1 health disorder recorded. Cows were grouped into estrus groups during the VWP based on records of AEA (estrus VWP [E-VWP], n = 476 or no estrus VWP [NE-VWP], n = 410). Finally, based on the combination of levels of AEA and RF, cows were grouped into an estrus and no RF (E-NoRF, n = 217), no estrus and RF (NE-RF, n = 276), no estrus and no RF (NE-NoRF, n = 134), and estrus and RF (E-RF, n = 259) groups. Cows received AIE up to 31 d after the end of the VWP, and if they did not receive AIE, they received timed AI after an Ovsynch plus progesterone protocol. Logistic and Cox proportional hazard regression compared differences in reproductive outcomes for different grouping strategies. The NoRF (AIE: 76.9%; P/AI: 53.1%; P150: 84.5%) and E-VWP (AIE: 86.8%; P/AI: 44.8%; P150: 82.3%) groups had more cows AIE and higher P/AI and P150 than the RF (AIE: 64.5%; P/AI: 34.9%; P150: 72.9%) and NE-VWP (AIE: 50.0%; P/AI: 38.9%; P150: 72.1%) groups, respectively. When both factors were combined, the largest and most consistent differences were between the E-NoRF (AIE: 91.3%; P/AI: 58.7%; P150: 88.5%) and NE-RF groups (AIE: 47.3%; P/AI: 35.8%; P150: 69.5%). Compared with the whole population of cows or cows grouped based on a single factor, the E-NoRF and NE-RF groups had the largest and most consistent differences with the whole cow cohort. The E-NoRF and NE-RF groups also had statistically significant differences of a large magnitude when compared with the remaining cow cohort after removal of the respective group. We conclude that combining data for AEA during the VWP with other predictors of reproductive performance could be used to identify groups of cows with larger differences in expected reproductive performance than if AEA and the predictors are used alone.

The economic effect of cow-based reproductive management programs with a systematic use of reproductive hormones

Hormone-based reproductive management programs can be beneficial to improve dairy cow's reproductive performance. This study aimed to compare the economic impact of reproductive management programs using systematic hormonal treatments to individual cows with a specific DIM range with a reproductive management program using cow-specific hormonal treatment based on a veterinary diagnosis of ovarian dysfunction during a fertility check. An existing individual cow-based, dynamic, and stochastic bio-economic simulation model, mimicking the production dynamics of a 200 cow-herd in daily time steps, was extended with ovarian dysfunction and fertility inputs. Four hormone-based reproductive management programs were modeled. In the default reproductive management program, reflecting the current reproductive management of Dutch herds, lactating dairy cows are inseminated based on detection of estrus and non-cyclic dairy cows are treated with hormones based on a veterinary diagnosis of ovarian dysfunction during a fertility check. Hormone treatments prescribed by the veterinarian for anestrus, cystic, and sub-estrus cows were an 8-d progesterone-releasing intravaginal device (PRID)-Synch protocol (PRIDsynch), an Ovsynch protocol, and a PGF2⍺ treatment, respectively. The 3 other reproductive management programs reflected systematic hormonal treatments to cows at specific DIM and included a 1) Double-Ovsynch protocol for TAI with nonpregnant cows submitted to a resynchronization protocol (FTAI), 2) Double-Ovsynch protocol for TAI with nonpregnant cows detected in estrus or submitted to a resynchronization protocol (FTAI+ED), and 3) detection of estrus with cows not detected submitted to a PRIDsynch protocol (ED+TAI). All nonpregnant cows were submitted to a resynchronization protocol based on the absence (PRIDsynch) or presence (Ovsynch protocol) of a corpus luteum (CL). The annual mean net economic return (NER) was calculated for all reproductive management programs. Compared with the default reproductive management program, the highest NER was observed for the FTAI+ED reproductive management program with €23,764 higher net revenues, followed by the FTAI and the ED+TAI reproductive management programs with €19,550 and €14,314 higher net revenues, respectively. Overall, systematic hormone-based reproductive management programs gave higher costs due to more hormones administered and higher calving and feed costs due to more pregnant cows. Nevertheless, the additional revenues of milk and calves in the systematic hormone-based reproductive management programs outweighed the total cost. For instance, the FTAI+ED reproductive management program gave €8,953 higher total cost per year compared with the default but with €32,654 higher revenues. In summary, reproductive management programs where hormones were systematically used gave economic advantages over the current default reproductive management program in which hormones are administered to individual cows based on a veterinary diagnosis of ovarian dysfunction during a fertility check.

Assessing Transition Cow Management in Dairy Cows for Improved Health, Milk Production, Pregnancy and Culling Outcomes

Understanding of the social environment has the potential to benefit dairy cow welfare and production. Our aim was to evaluate the associations of stocking density, calving density, days spent in a pre-partum group before calving (days spent in close-up, DCU) and the number of days from a pen filling event (addition of new cows to the pre-partum pen) on early-lactation health, production, pregnancy and culling outcomes in dairy cows. Data were gathered from 2780 cows in 2 herds. Herd management and reproductive records were analyzed for cows receiving treatment in the first 30 d of lactation (days in milk, DIM) for clinical mastitis, reproductive tract disease, ketosis, milk fever and displaced abomasum. Principal component analysis was used to account for the relationship between gestation length (GL) and DCU and their association with early lactation disease, milk production, pregnancy and culling outcomes. The effect of stocking density, the number of days from a pen filling event to calving and the calving density experienced by a cow in her week of calving was also evaluated. Causal inference was used to correct for confounding bias due to farm identity. The odds of disease in the first 30 DIM increased with stocking density before calving. A quadratic association was found between the first principal component (PC1), representing the combined effect of GL and DCU, and the odds of disease in multiparous cows only. Early lactation milk production and 305 d milk production in multiparous cows increased with PC1 score. Quadratic relationships were found between stocking density at d 8 to 2 before calving with both early lactation and 305 d milk production in multiparous cows but no associations were found in primiparous cows. Calving density showed a quadratic association with 305 d milk production in primiparous cows. The number of days from the last pen filling event to calving was not associated with changes in milk production. Disease occurrence was negatively associated with both early lactation and 305 d milk yield in multiparous cows but only with early lactation milk production in primiparous cows. The occurrence of disease was associated with a delayed time to pregnancy only in primiparous cows while both disease and being in lactation group ≥ 3 were negatively associated with time to pregnancy in multiparous cows. Week 4 milk (W4MK) was positively associated with reduced time to pregnancy in multiparous cows. For primiparous cows, increasing age at calving was associated with increased culling risk, while being in lactation group ≥ 3 was associated with increased culling risk in multiparous cows. Culling risk decreased with increasing W4MK in all cows. These results suggest that gestation length, time spent in close-up and stocking density are important factors influencing disease incidence in early lactation and subsequent lactation performance but had differing effects on primiparous versus multiparous cows. A better understanding of how pre-partum management factors influence postpartum health and milk production can help farms to plan facilities and organize the day-to-day management of cows and will assist in improving cow welfare and productivity.

Unmasking seasonal cycles in a high-input dairy herd in a hot environment: How climate shapes dynamics of milk yield, reproduction, and productive status

This study aimed to predict the annual herd milk yield, lactation, and reproductive cycle stages in a high-input dairy herd in a zone with prolonged thermal stress. Also, the impact of climatic conditions on milk yield and productive and reproductive status was assessed. An autoregressive integrated moving average (ARIMA) model was used in data fitting to predict future monthly herd milk yield and reproductive status using data from 2014 to 2020. Based on the annual total milk output, the highest predicted percentage of milk yield based on the yearly milk production was in February (9.1%; 95% CI = 8.3-9.9) and the lowest in August (6.9%; 95% CI = 6.0-7.9). The predicted highest percentage of pregnant cows for 2021 was in May (61.8; 95% CI = 53.0-70.5) and the lowest for November (33.2%; 95% CI = 19.9-46.5). The monthly percentage of dry cows in this study showed a steady trend across years; the predicted highest percentage was in September (20.1%; CI = 16.4-23.7) and the lowest in March (7.5%; 4.0-11.0). The predicted days in milk (DIM) were lower in September (158; CI = 103-213) and highest in May (220; 95% CI = 181-259). Percentage of calvings was seasonal, with the predicted maximum percentage of calvings occurring in September (10.3%; CI = 8.0-12.5) and the minimum in April (3.2%; CI = 1.0-5.5). The highest predicted culling rate for the year ensuing the present data occurred in November (4.3%; 95% CI = 3.2-5.4) and the lowest in April (2.5%; 95% CI = 1.4-3.5). It was concluded that meteorological factors strongly influenced rhythms of monthly milk yield and reproductive status. Also, ARIMA models robustly estimated and forecasted productive and reproductive events in a dairy herd in a hot environment.

Unravelling the impact of heat stress on daughter pregnancy rate in Mehsana buffalo through innovative breeding interventions

Heat stress profoundly affects the reproductive success of buffaloes, which are vital for the dairy industry due to their unique anatomical and physiological characteristics, necessitating careful evaluation under such conditions. Hence, this guided our search for quantifying heat stress' impact on Mehsana buffaloes using the best THI model and evaluating sires' performance. Fertility records (days open converted to daughter pregnancy rate) were collected in the span of over 24 years, w.e.f. 1989 to 2012. Finally, 3070 records of first lactation cows, daughters of 117 sires from DURDA, Gujarat, India, were used in the analysis. Meteorological data were retrieved from IMD, Pune, to understand the relationship between daughter pregnancy rate (DPR) and heat stress indicators. Several heat stress models were compared based on R2, adjusted R2, AIC, and BIC values, and the impact of heat stress was quantified. The year was classified into different heat stress zones, viz., Non heat stress zone (NHSZ), Heat stress zone (HSZ), and critical heat stress zone (CHSZ), drawing from the findings of DPR and THI. The THI 4th model based on dry and wet bulb temperature was identified as the best-fit model, and DPR significantly changed (P < 0.01) by 1.14% per unit change in THI value based on the month of calving. The average EBVs of the sires for DPR were found to be 20.78% (NHSZ), 38.09% (HSZ), and 39.08% (CHSZ) using BLUP-SM and 20.78% (NHSZ), 37.30% (HSZ), and 38.87% (HSZ) using BLUP-AM. Subsequently, the optimum sire for each of the zones was prioritized. It is noteworthy that bulls that performed better in NHSZ did not perform as well in HSZ and CHSZ, and vice versa. This supports the possibility of evaluating bulls independently in each heat stress zone.

Design of a handheld and portable fluorescence imaging system for quantitative detection of pregnancy-specific biomarkers in cattle

Reproductive management significantly impacts dairy farm productivity, necessitating accurate timely pregnancy detection in cattle. This paper presents a novel handheld and portable fluorescence imaging system designed for quantitative assessment of pregnancy-specific biomarkers, addressing the limitations of current detection methods. The objective was to develop a cost-effective, at-farm solution for detecting pregnancy-specific protein B (PSPB) in bovine plasma samples. The system integrates an imaging module and a custom software application, enabling image capture, data processing, and PSPB concentration determination. Calibration utilizing known PSPB concentrations achieved a 0.6 ng/mL limit of detection. Validation encompassed a comparison with a standard ELISA method using 100 bovine plasma samples; minimal bias and good agreement were observed within the linear range of the calibration curve for both methods. The system offers portability, user-friendliness, and potential for multiplex detection, promising real-time, at-farm reproductive management. This study demonstrates the successful development and validation of a portable fluorescence imaging system, offering an efficient and accurate approach to detecting pregnancy-specific biomarkers in cattle. Its implications extend to improving dairy farm productivity by enabling timely and reliable reproductive management practices.

The fertility of dairy heifers and cows is not influenced by the follicular wave of the ovulatory follicle

Two studies were conducted to evaluate the effects of the follicular wave on ovarian function and fertility in dairy heifers and lactating cows. In study 1, the estrous cycle of the selected Holstein heifers was initially synchronized using two intra-muscular prostaglandin F2α (PGF2α) administrations 11 days apart. Heifers in group FFW (n = 14) received an intra-muscular 500 μg PGF2α administration on day 7 after detecting standing estrus, while Heifers in group SFW (n = 14) were administered PGF2α 13 days after detecting standing estrus. The pregnancy rates of FFW (n = 98) and SFW (n = 100) heifers were also determined 35-37 days after artificial insemination (AI). In Study 2, healthy Holstein lactating cows (n = 28) were randomly assigned to either the FFW (n = 14) or SFW (n = 14) groups. The estrous cycles of the cows were presynchronized using two intra-muscular administrations of PGF2α given 14 days apart. Then, the emergences of the follicular waves were induced using an Ovsynch protocol. The pregnancy rate of FFW (n = 99) versus SFW (n = 98) cows was also determined 35-37 days after AI. The ovulatory follicle and corpus luteum (CL) resulting from the ovulatory follicle of FFW were larger than those of the dominant follicle and the CL of SFW in dairy heifers and lactating cows. However, the pregnancy rate did not differ between the FFW and SFW groups in heifers and lactating cows 35-37 days after AI. In conclusion, although the characteristics of the ovulatory follicles in FFW versus SFW animals differed, the follicular wave in dairy heifers or lactating cows did not affect fertility.

Reproduction in the era of genomics and automation

Much progress has been made in the reproductive efficiency of lactating dairy cows across the USA in the past 20years. The standardisation of evaluation of reproductive efficiency, particularly with greater focus on metrics with lesser momentum and less lag-time such as 21-day pregnancy rates (21-day PR), and the recognition that subpar reproductive efficiency negatively impacted profitability were major drivers for the changes that resulted in such progress. Once it became evident that the genetic selection of cattle for milk yield regardless of fertility traits was associated with reduced fertility, geneticists raced to identify fertility traits that could be incorporated in genetic selection programs with the hopes of improving fertility of lactating cows. Concurrently, reproductive physiologists developed ovulation synchronisation protocols such that after sequential treatment with exogenous hormones, cows could be inseminated at fixed time and without detection of oestrus and still achieve acceptable pregnancy per service. These genetic and reproductive management innovations, concurrently with improved husbandry and nutrition of periparturient cows, quickly started to move reproductive efficiency of lactating dairy cows to an upward trend that continues today. Automation has been adopted in Israel and European countries for decades, but only recently have these automated systems been more widely adopted in the USA. The selection of dairy cattle based on genetic indexes that result in positive fertility traits (e.g. daughter pregnancy rate) is positively associated with follicular growth, resumption of ovarian cycles postpartum, body condition score and insulin-like growth factor 1 concentration postpartum, and intensity of oestrus. Collectively, these positive physiological characteristics result in improved reproductive performance. Through the use of automated monitoring devices (AMD), it is possible to identify cows that resume cyclicity sooner after calving and have more intense oestrus postpartum, which are generally cows that have a more successful periparturient period. Recent experiments have demonstrated that it may be possible to adopt targeted reproductive management, utilising ovulation synchronisation protocols for cows that do not have intense oestrus postpartum and relying more heavily on insemination at AMD-detected oestrus for cows that display an intense oestrus postpartum. This strategy is likely to result in tailored hormonal therapy that will be better accepted by the public, will increase the reliance on oestrus for insemination, will improve comfort and reduce labour by reducing the number of injections cows receive in a lactation, and will allow for faster decisions about cows that should not be eligible for insemination.

Comparison of three reproductive management strategies for lactating dairy cows using combination of estrus detection or ovulation synchronization and Fixed-Timed Artificial Insemination

The objective of this study was to compare the reproductive performance of lactating dairy cows submitted to first AI after combination of estrus detection and fixed timed AI (FTAI) and FTAI only. Cows were randomly assigned to receive AI at detected estrus between 50 and 70 d in milk (DIM), if not detected in estrus, were enrolled in either Ovsynch (ED-Ov, n = 485) or PRIDsynch (ED-PR, n = 505) protocols; or received FTAI at 80 DIM after Double-Ovsynch protocol (DO, n = 501). Cows were body condition scored (BCS) at calving and at 43 DIM; and evaluated for postpartum disorders within 7 d postpartum; clinical mastitis, lameness and bovine respiratory disease were recorded until first AI. Ovarian cyclicity was monitored at 43 and 50 DIM, and at 70 and 77 DIM. Pregnancy diagnoses (PD) were performed at 32 and 63 d after AI. Overall prevalence of postpartum anovulation was 7.8%. Pregnancy per AI (P/AI) did not differ between reproductive strategies at 32 d PD (ED-Ov = 43.2%; ED-PR = 41.7%; DO= 45.3%). Primiparous cows had greater P/AI than multiparous cows (53.7% vs 36.8%). Cows on farm 1 had lower P/AI compared with their counterparts on farm 2 (42.1% vs 45.4%). Cows with BCS > 2.5 at 43 DIM had greater P/AI compared with cows with BCS ≤ 2.5 (44.5% vs 34.7%). Similar P/AI for cow's receiving AI at detected estrus and FTAI, low prevalence of disease anovulation may have contributed to the similar performance of ED-Ov, ED-PR and DO.

Effect of reproductive management programs that prioritized artificial insemination at detected estrus or timed artificial insemination on the economic performance of primiparous Holstein cows of different genetic merit for fertility

The objective of this randomized controlled experiment was to evaluate the effect of reproductive management programs that prioritized artificial insemination (AI) at detected estrus (AIE) or timed AI (TAI) during the first lactation on the economic performance of dairy cows of different genomically enhanced predicted transmitting ability for fertility. Lactating primiparous Holstein cows from 6 commercial farms were stratified into high, medium, and low fertility groups based on a reproduction index value calculated from multiple genomically enhanced predicted transmitting abilities to predict the number of days to achieve pregnancy. Within herd and fertility group, cows were randomly assigned either to a program that prioritized AIE (P-AIE; n = 1,416) and used TAI for cows not AIE for all AI services or another that prioritized TAI and had an extended voluntary waiting period for first service and prioritized TAI for second and greater AI services (P-TAI; n = 1,338). Cash flow (CF) per cow accumulated for the experimental (first) and second calving interval (CIN) and cash flow per slot per 28 mo after calving in the experimental lactation were calculated. Market and rearing heifer cost values were used for estimating CF. For cows in the high fertility group, a positive effect of delayed pregnancy on milk income during the first lactation was observed (+$248 for P-TAI) but was insufficient to generate significant differences in CF between treatments mainly because of milk income compensation in the second lactation (+$125 for P-AIE) and minor reductions in reproductive cost and gains in calf value for the P-AIE treatment. In this regard, CF for 2 CIN was greater for the P-TAI treatment by $61 and $86 for market and rearing replacement heifer cost, respectively. Similarly, CF per slot was favorable to the P-TAI treatment but only by $13 and $47 for market and rearing replacement heifer cost, respectively. For cows in the low fertility group, CF was numerically in favor of the P-AIE treatment due to a pregnancy and herd exit dynamics that resulted in gains in milk income over feed cost during the first ($29) and second ($113) lactation. Differences in CF for the 2 CIN were $58 and $47 for market or rearing heifer value, respectively, and $77 and $19 for market and rearing heifer values, respectively for the slot analysis. Differences in CF between cows of different genetic merit for fertility were consistent across treatment and estimation method. Of note, cows in the low fertility group had greater CF than cows in the high fertility group in all comparisons, ranging from $198 per cow for 2 CIN to as much as $427 per slot. For the low fertility group, greater milk production contributed directly (milk income over feed cost) and indirectly (reduced culling) to increased CF. We concluded that genetic merit for fertility and CF are associated because cows of inferior genetic potential for fertility had greater CF than cows of superior genetic for fertility despite some increased costs and reduced revenues. Also, the magnitude of the CF differences observed for cows of different genetic merit for fertility managed with the P-AIE or P-TAI program may be valuable to commercial dairy farms but did not allow to conclusively support the choice of a type of reproductive management strategy for cows of different genetic merit for fertility.

Effect of reproductive management programs that prioritized artificial insemination at detected estrus or timed artificial insemination on the reproductive performance of primiparous Holstein cows of different genetic merit for fertility

Our objective was to compare reproductive outcomes of primiparous lactating Holstein cows of different genetic merit for fertility submitted for insemination with management programs that prioritized artificial insemination (AI) at detected estrus (AIE) or timed AI (TAI). Moreover, we aimed to determine whether subgroups of cows with different fertility potential would present a distinct response to the reproductive management strategies compared. Lactating primiparous Holstein cows (n = 6 commercial farms) were stratified into high (Hi-Fert), medium (Med-Fert), and low (Lo-Fert) genetic fertility groups (FG) based on a Reproduction Index value calculated from multiple genomic-enhanced predicted transmitting abilities. Within herd and FG, cows were randomly assigned either to a program that prioritized TAI and had an extended voluntary waiting period (P-TAI; n = 1,338) or another that prioritized AIE (P-AIE; n = 1,416) and used TAI for cows, not AIE. Cows in P-TAI received first service by TAI at 84 ± 3 d in milk (DIM) after a Double-Ovsynch protocol, were AIE if detected in estrus after a previous AI, and received TAI after an Ovsynch-56 protocol at 35 ± 3 d after a previous AI if a corpus luteum (CL) was visualized at nonpregnancy diagnosis (NPD) 32 ± 3 d after AI. Cows with no CL visualized at NPD received TAI at 42 ± 3 d after AI after an Ovsynch-56 protocol with progesterone supplementation (P4-Ovsynch). Cows in P-AIE were eligible for AIE after a PGF2α treatment at 53 ± 3 DIM and after a previous AI. Cows not AIE by 74 ± 3 DIM or by NPD 32 ± 3 d after AI received P4-Ovsynch for TAI at 74 ± 3 DIM or 42 ± 3 d after AI. Binary data were analyzed with logistic regression, count data with Poisson regression, continuous data by ANOVA, and time to event data by Cox's proportional hazard regression. Pregnancy per AI (P/AI) to first service was greater for cows in the Hi-Fert (59.8%) than the Med-Fert (53.6%) and Lo-Fert (47.7%) groups, and for the P-TAI (58.7%) than the P-AIE (48.7%) treatment. Overall, P/AI for all second and subsequent AI combined did not differ by treatment (P-TAI = 45.2%; P-AIE = 44.5%) or FG (Hi-Fert = 46.1%; Med-Fert = 46.0%; Lo-Fert = 42.4%). The hazard of pregnancy after calving was greater for the P-AIE than the P-TAI treatment [hazard ratio (HR) = 1.27, 95% CI: 1.17 to 1.37)], and for the Hi-Fert than the Med-Fert (HR = 1.16, 95% CI: 1.05 to 1.28) and Lo-Fert (HR = 1.34, 95% CI: 1.20 to 1.49) groups. More cows in the Hi-Fert (91.2%) than the Med-Fert (88.4%) and Lo-Fert (85.8%) groups were pregnant at 200 DIM. Within FG, the hazard of pregnancy was greater for the P-AIE than the P-TAI treatment for the Hi-Fert (HR = 1.41, 95% CI: 1.22 to 1.64) and Med-Fert (HR = 1.28, 95% CI: 1.12 to 1.46) groups but not for the Lo-Fert group (HR = 1.13, 95% CI: 0.98 to 1.31). We conclude that primiparous Holstein cows of superior genetic merit for fertility had better reproductive performance than cows of inferior genetic merit for fertility, regardless of the type of reproductive management used. In addition, the effect of programs that prioritized AIE or TAI on reproductive performance for cows of superior or inferior genetic merit for fertility depended on the outcomes evaluated. Thus, programs that prioritize AIE or TAI could be used to affect certain outcomes of reproductive performance or management.

BullVal$: An Integrated Decision-Support Tool for Predicting the Net Present Value of a Dairy Bull Based on Genetic Merit, Semen Production Potential, and Demographic Factors

Deciding when to replace dairy bulls presents a complex challenge for artificial insemination (AI) companies. These decisions encompass multiple factors, including a bull's age, predicted semen production, and estimated genetic merit. This study's purpose was to provide a practical, objective tool to assist in these decisions. We utilized a Markov Chain model to calculate the economic valuation of dairy bulls, incorporating key factors such as housing costs, collection and marketing expenses, and the bull's probable tenure in the herd. Data from a leading AI company were used to establish baseline values. The model further compared a bull's net present value to that of a potential young replacement, establishing a relative valuation (BullVal$). The range of BullVal$ observed spanned from -USD 316,748 to USD 497,710. Interestingly, the model recommended culling for 49% of the bulls based on negative BullVal$. It was found that a bull's net present value was primarily influenced by market allocation and pricing, coupled with the interaction of semen production and genetic merit. This study offers a robust, data-driven model to guide bull replacement decisions in AI companies. Key determinants of a bull's valuation included market dynamics, semen production rates, and genetic merit.

Key performance indicators used by dairy consultants during the evaluation of reproductive performance during routine visits

Dairy farms need thorough and efficient reproduction control. Consultants specialized in reproduction use key performance indicators (KPI) to monitor the reproductive performance of farms and must be able to decipher between the approach in a first visit and routine visits. A total of 49 consultants specialized in dairy reproduction from 21 countries responded to an online survey conducted to determine the most suitable parameters during routine visits every 2 to 4 weeks. The survey was comprised of 190 questions, 178 of them rated from 0 (irrelevant) to 10 (maximum importance) points. The questions were divided into five sections: (1) consultant and farm model, (2) general data of the farm, (3) cow reproduction, (4) postpartum and metabolic disease, and (5) heifer reproduction. The median, interquartile range, minimum and maximum values, and 95% confidence interval were determined for each question. Afterward, a multivariate analysis, using between-group linkage via Ward's hierarchical clustering was conducted to generate clusters of consultants according to their response pattern. Finally, a chi-square test was conducted to assess the association between years of experience of the consultant and farm size within the clusters generated in each section of the questionnaire. The majority of the consultants considered 34 parameters to be highly important (rated 8-10) to analyze during routine visits. The consultants used several KPI (in variable quantitative range) to evaluate any of the presented sections and considered that all the five sections are critical to control. They are aware of using KPI that reflect heat detection, fertility, and farming efficiency as well as KPI that can provide information on reproductive efficiency in the near future for cows, such as postpartum and metabolic diseases. However, parameters that are relatively old and ineffective, in terms of reproductive performance control, are still highly regarded by the majority of consultants in a routine-visit scenario. Farm size and years of experience of the consultant did not influence the type or number of parameters chosen as KPI during routine visits. The parameters rated with the highest importance (rate 10) that could be considered for an easy, fast, and universal use in routine visits to assess the reproductive status were: First service CR (%), Overall pregnancy rate (%) for cows, and age at first calving (d) for heifers.

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.

The Marginal Abatement Cost of Antimicrobials for Dairy Cow Mastitis: A Bioeconomic Optimization Perspective

Maintaining udder health is the primary indication for antimicrobial use (AMU) in dairy production, and modulating this application is a key factor in decreasing AMU. Defining the optimal AMU and the associated practical rules is challenging since AMU interacts with many parameters. To define the trade-offs between decreased AMU, labor and economic performance, the bioeconomic stochastic simulation model DairyHealthSim (DHS)© was applied to dairy cow mastitis management and coupled to a mean variance optimization model and marginal abatement cost curve (MACC) analysis. The scenarios included three antimicrobial (AM) treatment strategies at dry-off, five types of general barn hygiene practices, five milking practices focused on parlor hygiene levels and three milk withdrawal strategies. The first part of economic results showed similar economic performances for the blanked dry-off strategy and selective strategy but demonstrated the trade-off between AMU reduction and farmers' workload. The second part of the results demonstrated the optimal value of the animal level of exposure to AM (ALEA). The MACC analysis showed that reducing ALEA below 1.5 was associated with a EUR 10,000 loss per unit of ALEA on average for the farmer. The results call for more integrative farm decision processes and bioeconomic reasoning to prompt efficient public interventions.

Relationships among total mixed ration nutritional components and reproductive performance in high-producing dairy herds

The main objective of the present study was to determine whether composition of total mixed ration influences reproductive performance in high-producing commercial dairy farms. Dairy producers and nutritional consultants from 48 dairy farms located in Wisconsin agreed to provide reproductive data and dietary information on high milk production pens during the main breeding period for the previous 12 mo. Dietary components (percentage of dry matter) were crude protein (CP), rumen degradable (RDP) and undegradable (RUP) protein, neutral detergent fiber (NDF), nonfiber carbohydrates (NFC), starch, and fat. Reproductive data were service rate (SR), overall pregnancy per artificial insemination (P/AI) and P/AI at the first service, 21-d pregnancy rate (PR), days open, and percentage of cows pregnant by 150 d in milk (PREG150). Participating herds had lactating Holstein cows (range = 143 to 2,717) housed in freestall facilities. Statistical analyses were performed with CORR and GLIMMIX of SAS (SAS Institute Inc.). Daily average milk production of herds was 38.9 ± 0.60 kg/d (30.0 to 50.4 kg/d). Overall SR was 58.5% (39-73) and P/AI was 36.1% (22-49). Overall 21-d PR was 20.3% (10-42%). Correlation between SR and PR was 0.59, whereas correlation of overall P/AI and P/AI at first service with PR were both 0.72. Similarly, for PREG150, correlation with overall P/AI (0.63) and P/AI at first service (0.66) were greater than with SR (0.48). There was large variation in diet composition, with CP varying from 16.0 to 18.7%, NDF from 24.9 to 35.1%, NFC from 31.7 to 46.6%, starch from 20.1 to 30.8%, and fat from 3.1 to 6.7%. Overall, there were no detectable associations of CP, RDP, and RUP with reproductive measures. The strongest relationship was a decrease in reproductive performance with increasing dietary NFC including overall P/AI (-0.48), P/AI at first service (-0.51), and PREG150 (-0.33). Starch also had a negative relationship with P/AI at first service (-0.35). Conversely, greater NDF was positively associated with P/AI at first service (0.34). Fat content was also positively associated with P/AI at first service (0.34). When NFC was divided in tertiles (<40, 40 to 42.2, and >42.2% NFC), the highest tertile had lower overall P/AI (39 vs. 36 vs. 31%), P/AI at first service (43 vs. 40 vs. 33%), and PREG150 (54 vs. 53 vs. 47%). In conclusion, farms with greater dietary NFC may have compromised reproductive performance. Correspondingly, herds with greater NDF content may achieve high milk production with potentially positive associations with reproduction. Other relationships of dietary components on reproduction were not as obvious in this herd-level analysis.

Estrus Detection in a Dairy Herd Using an Electronic Nose by Direct Sampling on the Perineal Region

Estrus detection is very important for the profitability of dairy herds. Different automatic systems for estrus detection have been developed over the last decades. Our study aimed to assess the ability of the electronic nose (EN) MENT-EGAS prototype to detect estrus, based on odor release from the perineal headspace in dairy cattle by direct sampling. The study was performed in an Italian dairy farm using 35 multiparous Holstein-Friesian cows. The cows were divided into three groups: group I included 10 lactating 5-month pregnant cows, group II included 19 lactating cycling cows, and group III included 6 cows that were artificially inseminated 18 days before the trial. Odors from the perineal headspace were collected using the MENT-EGAS prototype. In group I, odors were collected once a day for 5 consecutive days. In group II, odors were collected twice daily from day 18 until day 1 of the reproductive cycle. In group III, odors were also collected twice daily from the presumable day 18 of gestation until day 22. Principal component analyses (PCA) of the perineal headspace samples were performed. PCA in group I revealed no significant discrimination. PCA in group II revealed clear discrimination between proestrus and estrus, and between estrus and metestrus but no significant discrimination was obtained between proestrus and metestrus. PCA in group III revealed that in four cows the results were similar to group I and in two cows the results were similar to group II. On day 40 of the presumable pregnancy, the ultrasound examination revealed that only the four cows were pregnant and the other two cows were regularly cycling. On the basis of our findings, we conclude that it is possible to accurately detect estrus in dairy cattle from directly collected odor samples using the MENT-EGAS prototype. This represents the first study of estrus detection using an EN detection by direct sampling. EN technologies, such as MENT-EGAS, could be applied in the future in dairy cattle farms as a precise, non-invasive method for estrus detection.

The vaginal and uterine blood flow changes during the ovsynch program and its impact on the pregnancy rates in Holstein dairy cows

Aim

OvSynch is a hormonal protocol for synchronization of estrus and use of artificial insemination (AI) at an optimal time without adverse effects on the ovaries or uterus. This study investigated the use of noninvasive color Doppler ultrasound to assess changes in uterine and vaginal blood flow during the Ovsynch program for synchronization of estrus and its relation to the pregnancy rates in Holstein cows.

Materials and methods

The experimental cows received an intramuscular dose of 10 μg of a GnRH analogue (G1), followed 7 days later with an intramuscular injection of synthetic prostaglandin F2α (P: PGF2α) analogue (500 μg cloprostenol sodium), and given a 10 μg, injection of the GnRH analogue (G2) i.m. 48 h after the PGF2α treatment, and the cows were bred 14-16 h after. Uterine and vaginal perfusion were investigated by performing transrectal Doppler ultrasonography of both the uterine and vaginal arteries in Holstein cows at different time points during the Ovsynch program to determine: peak systolic velocity (PSV), time-averaged maximum velocity (TAMV), the volume of blood flow (BFV), pulsatility index (PI), resistance index (RI), resistance impedance (S/D) and diameters of uterine (UA) and vaginal (VA) arteries. Steroid hormones were also assayed. Transrectal ultrasonography (TUS) was performed at 32 and 60 days to confirm the pregnancy per artificial insemination (P/AI).

Results

The uterine PSV, TAMV, and PV were greater at the time of the cloprostenol sodium and second GnRH injections (p<0.05) than at the time of the first GnRH injection. The vaginal PSV, PV were greater at the time of the cloprostenol sodium than at the time of the first and second GnRH injections (p<0.05). The receiver operating characteristic curve (ROC curve) indicated a high correlation between the uterine and vaginal blood flow and the rate of the pregnancy (p<0.05). The area under the ROC curve was 0.920 and 0.87 (p<0.05) for vaginal and uterine arteries respectively at time of G2. The serum levels of progesterone, estrogen and cortisol were correlated with the P/AI (p<0.05). The P/AI significantly decreased from 43.9 % at 32 d to 35.37 % at 60 d.

Conclusion

These results indicate that noninvasive Doppler ultrasonography is a valid method to evaluate changes in the characteristics of uterine and vaginal blood flow in cows during the Ovsynch protocol. Furthermore, vaginal and uterine blood flow are two determinant factors for the higher conception rates in Holstein dairy cows.

Addition of clinoptilolite in the diet reduces uterine PMN leukocytes and open days in multiparous lactating dairy cows managed in a mountain tropical pasture-based system

This study aimed to assess the effect of adding clinoptilolite in the diet on uterine health and reproductive performance in multiparous lactating dairy cows managed in a tropical pasture-based system above 2500 m of altitude. Seventy-seven multiparous Holstein crossbred cows from two farms were allocated randomly into two groups: clinoptilolite supplemented cows (CLG, n = 42) and non-supplemented cows as control (CG, n = 35). Cows from CLG were supplemented with clinoptilolite from 30 days (50 g/cow/day) before to 60 days after calving (200 g/cow/day). In CLG cows, percentages of uterine PMN leukocytes (P < 0.0001) and proportion of subclinical endometritis (P = 0.0187) were lower than in CG. The interval calving to first corpus luteum was shorter (P = 0.0759) in CLG than CG, and calving to first service interval was similar between treatments. Cows from CLG became pregnant 35 days earlier than CG cows (P = 0.0224). On farm A, calving to conception interval was 18.1 days longer in CLG than in CG (P = 0.3750); in farm B, this interval was 86.2 days shorter in CLG than in CG (P = 0.0002). In conclusion, daily addition of clinoptilolite in the diet decreased the percentage of uterine PMN leukocytes, the proportion of cows with subclinical endometritis, and shortened the calving-conception interval in multiparous lactating dairy cows.

Key Performance Indicators Used by Dairy Consultants During the Evaluation of Reproductive Performance in a First Visit

Reproduction plays a fundamental role in the profitability of dairy farms. Consultants use key performance indicators (KPI) to monitor the reproductive performance of the farms. They must decipher between the most suitable ones to face two different scenarios that may need the analysis of different parameters: (1) approach in a first visit, and (2) routine visits. Forty-nine consultants specialized in dairy reproduction from 21 countries responded to an online survey conducted to determine the most suitable parameters in a first visit approach. The survey was comprised of 190 questions, 178 of them rated from 0 (irrelevant) to 10 (maximum importance) points. The questions were divided into 5 sections: (1) consultant and farm model, (2) general data of the farm, (3) cow reproduction, (4) postpartum and metabolic disease, and (5) heifer reproduction. The median, interquartile range, minimum and maximum values, and 95% confidence interval (CI) were determined for each question. Afterward, a multivariate analysis, using between-group linkage via Ward's hierarchical clustering was conducted to generate clusters of consultants according to their response pattern. Lastly, a Chi-square test was conducted to assess the association between the years of experience of the consultant and farm size within the clusters generated in each section of the questionnaire. Most of the consultants considered 27 parameters to be highly important to analyze during the first visit. Consultants use several KPIs (in variable quantitative range) to evaluate any of the presented sections. Moreover, consultants preferred parameters focused on heat detection, fertility, and pregnancy achievement regarding the production cycle of a dairy cow. Consultants also showed high interest in obtaining a general overview of milk production, farming efficiency, and the heifer rearing process; but the farm size and the years of experience of the consultant influenced the type and number of parameters chosen as KPI. The parameters rated with the highest importance (rate 10) that could be considered for an easy, fast, and universal first visit to assess the reproductive status were: first service conception rate, overall pregnancy rate, and 21d pregnancy rate for cows, and age at first calving for heifers.

Automated Systems for Estrous and Calving Detection in Dairy Cattle

Purpose: The objective of this review is to describe the main technologies (automated activity monitors) available commercially and under research for the detection of estrus and calving alerts in dairy cattle. Sources: The data for the elaboration of the literature review were obtained from searches on the Google Scholar platform. This search was performed using the following keywords: reproduction, dairy cows, estrus detection and parturition, electronic devices. After the search, the articles found with a title related to the objective of the review were read in full. Finally, the specific articles chosen to be reported in the review were selected according to the method of identification of estrus and parturition, seeking to represent the different devices and technologies already studied for both estrus and parturition identification. Synthesis: Precision livestock farming seeks to obtain a variety of information through hardware and software that can be used to improve herd management and optimize animal yield. Visual observation for estrus detection and calving is an activity that requires labor and time, which is an increasingly difficult resource due to several others farm management activities. In this way, automated estrous and calving monitoring devices can increase animal productivity with less labor, when applied correctly. The main devices available currently are based on accelerometers, pedometers and inclinometers that are attached to animals in a wearable way. Some research efforts have been made in image analysis to obtain this information with non-wearable devices. Conclusion and applications: Efficient wearable devices to monitor cows’ behavior and detect estrous and calving are available on the market. There is demand for low cost with easy scalable technology, as the use of computer vision systems with image recording. With technology is possible to have a better reproductive management, and thus increase efficiency.

Associations of somatic cell count with milk yield and reproductive performance in grazing dairy cows

Poor udder health status can have a detrimental effect on milk yield and reproductive performance, leading to reductions in the dairy farm profit. The objective of this retrospective longitudinal study was to assess the associations of somatic cell count (SCC) with daily milk yield and reproductive performance. A database with 1,930,376 lactations from 867 Argentinean grazing dairy herds records collected for 14 years was used. The association of the evolution of SCC (healthy vs. new case vs. cured vs. chronic; with 150,000 SCC/mL as threshold) and of the severity of SCC [mild (150,000--400,000 SCC/mL) vs. moderate (400,000-1,000,000 SCC/mL) vs. severe (>1,000,000 SCC/mL)] with the odds for conception were estimated. Finally, the associations of the linear score of SCC (LS-SCC) with daily milk yield were estimated depending on parity and milk production quartile. The odds ratios (CI 95%) for conception at first service were 0.921 (0.902-0.941), 0.866 (0.848-0.884), and 0.842 (0.826-0.859) for the new case, cured, and chronic cows compared with healthy cows, respectively. Also, the odds ratios (CI 95%) for conception were 0.902 (0.881-0.925), 0.837 (0.808-0.866) and 0.709 (0.683-0.736) for mild, moderate and severe cases compared with healthy cows, respectively. An increase of one point of LS-SCC was associated with decreases of 0.349, 0.539, and 0.676 kg in daily milk yield for first-, second-, and third-lactation cows, respectively. In conclusion, SCC is negatively associated with the risk for conception and with daily milk yield in grazing dairy cows. This negative relationship with conception is higher when SCC increase occurs after the service date and it is influenced by severity of mastitis, and in the case of milk yield, the negative association is influenced by parity, milk production quartile, and severity of mastitis.

Economic impact of adding a second prostaglandin F2α treatment during an Ovsynch protocol using a meta-analytical assessment and a stochastic simulation model

Incomplete luteal regression after treatment with a single dose of PGF_2α during an Ovsynch protocol decreases fertility to timed artificial insemination (AI). An additional treatment with PGF_2α 24 h after the first dose has been recommended to increase the proportion of cows with complete luteal regression and subsequent pregnancy per AI (P/AI). This is, however, associated with additional costs of labor and product. The objective was to develop a stochastic partial budget model to estimate the economic impact of an additional PGF_2α treatment on d 8 during an Ovsynch protocol in primiparous and multiparous cows. A systematic review of the literature and a meta-analytical assessment was performed to evaluate the effects of adding a second PGF_2α treatment during the Ovsynch protocol on P/AI in lactating dairy cows. Thirteen randomized controlled experiments from 11 published manuscripts including 9,735 cows were used. We were able to retrieve information regarding parity from 9 experiments from 7 manuscripts (2,367 primiparous cows and 5,356 multiparous cows). An additional dose of PGF_2α yielded a 5.60 risk difference in P/AI [95% confidence interval (CI) = 3.69-7.52]. In primiparous cows and multiparous cows, an additional dose of PGF_2α yielded a 4.24 (95% CI = 0.31-8.17) and a 5.31 risk difference in P/AI (95% CI = 2.75-7.87). Revenue was based on the associated improvement in reproductive performance because of an increase in P/AI multiplied by the value of a pregnancy (PGVAL). Median PGVAL was €252, ranging from €42 (fifth percentile) to €623 (95th percentile). Based on parity, median PGVAL was €205 (5th percentile = €43; 95th percentile = €651) and €264 (5th percentile = €88; 95th percentile = €598) for primiparous (n = 1,252) and multiparous cows (n = 3,003), respectively. Using a stochastic simulation model with 10,000 iterations, adding a second PGF_2α dose on d 8 was more profitable (€7.76/cow; 5th percentile = €0.01; 95th percentile = €29.40) compared with a single PGF_2α administration on d 7. In primiparous cows, adding a second PGF_2α treatment was more profitable (€1.99/cow; 5th percentile = -€3.08; 95th percentile = €22.52) in 67% of all simulated iterations. In multiparous cows, adding a second PGF_2α treatment was more profitable (€7.92/cow; 5th percentile = -€0.09; 95th percentile = €28.22) in 95% of all simulated iterations. In conclusion, there was a clear benefit of an additional PGF_2α treatment during the Ovsynch protocol on P/AI (+5.6 percentage units). Despite additional costs for hormones and labor, an additional treatment with PGF_2α on d 8 was more profitable in 95% of all scenarios because of the associated increase in fertility. It turned out, however, that adding a second PGF_2α treatment was more profitable in multiparous cows compared with primiparous cows.

Daily activity measures and milk yield immediately before and after a fertile estrus and during the period of expected return to estrus after insemination in dairy cows

The objective of this study was to characterize changes in milk yield and other physical measures during a 7-d periestrual period encompassing estrus (d 0) and during a 16-d period of expected return to estrus beginning at d 17 after artificial insemination (AI) until pregnancy status was determined on d 32. Lactating dairy cows milked thrice daily were fitted with CowManager SensOor ear tags (Agis) capable of assessing real-time eating, rumination, resting, high activity (estrus), ear-surface temperature, and heat alerts. Data were uploaded to the cloud, downloaded daily into Excel (Microsoft Corp.) spreadsheets, averaged to produce daily means for each activity, and analyzed as repeated measures relative to estrus or to d 17 after AI. Daily milk was unchanged during the periestrual period but was greater in nonpregnant cows that failed to return to estrus (NP-NR) during d 21 through 26 compared with NP cows that returned to estrus (NP-R) and pregnant (PREG) cows during that same period. Daily ear-surface temperature was greater during d 1 to 3 compared with d 0 and averaged 0.6 to 1.7°C greater from d 17 through 32 in NP-NR cows compared with NP-R and PREG cows. Daily rumination and resting times reached nadirs on d 0, with decreases occurring 48 h before estrus. Both rumination and resting times increased by 25 or 81% on the day after estrus, respectively. Rumination and resting times were less in NP-R cows during d 22 through 26 compared with NP-NR and PREG cows. In contrast, daily eating time was greatest on the day of estrus compared with 3 d before and after estrus. The NP-R cows spent more time eating during d 17 through 32 compared with NP-NR and PREG cows. High activity increased by 97% during 48 h before estrus, peaked at estrus, and decreased to a constant level during d 1 through 3. The NP-R cows had greater high activity on d 22 through 26 compared with NP-NR and PREG cows. We conclude that resting and rumination activity decreased to daily nadirs, whereas eating and high activity peaked on the day of estrus. Fertile estrus was associated with 12% greater high activity, 11% less resting time, and 6% less rumination time. In addition, cows that returned to estrus after AI had greater daily eating and high activity times and less rumination and resting time during the period of expected return to estrus after AI compared with pregnant cows and cows failing to return to estrus.

Association of days in close up, gestation length, and rumination around time of calving with disease and pregnancy outcomes in multiparous dairy cows

The purpose of this study was to evaluate the effect of rumination times and days spent in a close-up group before calving (DCU) on early-lactation health and reproductive outcomes in dairy cows. Data were gathered for 719 cows located in a single herd. Herd management and reproductive records were analyzed for cows receiving treatment in the first 30 d of lactation (days in milk; DIM) for clinical mastitis, reproductive tract disease, ketosis, milk fever, and displaced abomasum. Rumination times for each cow were downloaded daily from the herd's automated collar system used to generate heat and health alerts for each cow beginning at 21 d precalving until 14 d postcalving. During the first 30 DIM, 121 cows (18%) developed at least 1 disease-any combination of ketosis (40 cows, 5.9% of total), mastitis (17 cows, 2.5%), metritis (75 cows, 11%), milk fever (17 cows, 2.5%), or displaced abomasum (28 cows, 4.1%); 305 cows (45%) were pregnant again at 100 DIM, and an additional 139 cows (20%) were pregnant at 150 DIM. Principal component analysis was used to determine the relationship between gestation length and DCU and their association with the odds of developing disease in early lactation. We did not find any significant association between precalving rumination time and disease within the first 30 DIM. Higher rumination time in the week before calving was shown to be strongly linked to a shorter time to subsequent pregnancy, whereas rumination times postcalving were not associated with changes in the time to pregnancy. Principal component analysis showed that a curvilinear combination of gestation length and DCU (principal component 1) was significantly associated with changes in disease incidence in the first 30 DIM. Gestation length and time spent in close up are important management factors in reducing the incidence of disease in early lactation, and rumination times around calving may help predict future reproductive outcomes.

Factors That Optimize Reproductive Efficiency in Dairy Herds with an Emphasis on Timed Artificial Insemination Programs

Simple Summary

Reproductive efficiency is critical for profitability of dairy operations. The first part of this manuscript discusses the key physiology of dairy cows and how to practically manipulate this reproductive physiology to produce timed artificial insemination (TAI) programs with enhanced fertility. In addition, there are other critical factors that also influence reproductive efficiency of dairy herds such as genetics, management of the transition period, and body condition score changes and improve management and facilities to increase cow comfort and reduce health problems. Using optimized TAI protocols combined with enhancing cow/management factors that impact reproductive efficiency generates dairy herd programs with high reproductive efficiency, while improving health and productivity of the herds.

Abstract

Reproductive efficiency is closely tied to the profitability of dairy herds, and therefore successful dairy operations seek to achieve high 21-day pregnancy rates in order to reduce the calving interval and days in milk of the herd. There are various factors that impact reproductive performance, including the specific reproductive management program, body condition score loss and nutritional management, genetics of the cows, and the cow comfort provided by the facilities and management programs. To achieve high 21-day pregnancy rates, the service rate and pregnancy per artificial insemination (P/AI) should be increased. Currently, there are adjustments in timed artificial insemination (TAI) protocols and use of presynchronization programs that can increase P/AI, even to the point that fertility is higher with some TAI programs as compared with AI after standing estrus. Implementation of a systematic reproductive management program that utilizes efficient TAI programs with optimized management strategies can produce high reproductive indexes combined with healthy cows having high milk production termed “the high fertility cycle”. The scientific results that underlie these concepts are presented in this manuscript along with how these ideas can be practically implemented to improve reproductive efficiency on commercial dairy operations.

Effect of estrous detection strategy on pregnancy outcomes of lactating Holstein cows receiving artificial insemination and embryo transfer

Objectives of the current experiment were to evaluate the effects on reproductive performance of adding an automated estrous detection (AED) device to the reproductive management of Holstein cows. In addition, we aimed to determine whether the AED device would equally influence the reproductive performance of cows receiving artificial insemination and those receiving embryo transfer. Cows (n = 1,244) were observed daily for estrous detection by trained farm personnel with the aid of a tail head mounting device. Cows (n = 641) enrolled in the AED treatment were fitted with a neck-mounted automated estrus detection device, and cows enrolled in the control (CTRL, n = 603) treatment were not fitted with the AED device. Cows not detected in estrus by 54 ± 3 DIM received 1 injection of PGF_2α, and those not detected in estrus by 68 ± 3 DIM were enrolled in an ovulation synchronization protocol. The hazard of first service tended to be affected by treatment [CTRL: referent, AED: adjusted hazard ratio (AHR) = 1.11, 95% confidence interval (CI) = 0.98, 1.25], and we determined a tendency for the AED treatment to reduce the proportion of cows receiving the first service at fixed time (39.7 ± 5.7 vs. 45.5 ± 5.8%). After the first service, high-producing cows enrolled in the AED treatment were more likely to be pregnant (19.1 ± 2.4 vs. 31.8 ± 3.0%), but no differences between the AED and CTRL treatments were observed among low-producing cows (24.9 ± 2.9 vs. 24.7 ± 2.9%). The hazard of second service was affected by treatment (CTRL: referent, AED: AHR = 1.22, 95% CI = 1.01, 1.47), and the AED treatment reduced the proportion of cows receiving the second service at fixed time compared with the CTRL treatment (15.7 ± 2.2 vs. 21.9 ± 2.5%). After the second service, the AED treatment tended to increase the proportion of cows pregnant (31.0 ± 3.0 vs. 24.9 ± 2.6%) and tended to reduce the proportion of cows that lost pregnancy between the first and second pregnancy exams (9.7 ± 3.3 vs. 16.7 ± 4.6%). The interaction between treatment and type of service did not affect percentage of cows pregnant and pregnancy loss to the first and second services. The hazard of pregnancy was affected by the interaction between treatment and milk yield, in that cows with above the median milk yield in the AED treatment became pregnant at a faster rate than CTRL cows, but no difference between treatments was observed among cows with milk yield below the median. Cows with above the median milk yield had shorter duration of estrus and were less likely to have activity peak at estrus ≥89 (0 = minimum, 100 = maximum). The current experiment suggests that AED devices may improve reproductive performance not only by increasing service rates but also by improving accuracy of estrous detection. According to the current experiment, high-producing cows may benefit most from the addition of AED devices to reproductive management.

Use of on-farm milk progesterone information to predict fertility outcomes in dairy cows subjected to timed artificial insemination

The objectives of this study were to evaluate the use of a qualitative on-farm milk progesterone test to predict non-pregnancy in dairy cows. Lactating Jersey cows (n = 752) were subjected to the 5-d Cosynch-72 protocol for timed artificial insemination (AI; d -8 GnRH, d -3 and -2 PGF_2α, d 0 GnRH and timed AI). Milk was sampled on d -3, 0, 7, and 28 relative to timed AI, and progesterone concentrations were assessed using a lateral flow immunochromatographic test. Samples were classified into 3 groups indicative of high (hP4; test line not visible or lighter than reference), intermediate (iP4; test line similar to reference), and low (lP4; test line darker than reference) progesterone concentrations. Blood was sampled from a subset of cows (n = 50) on d -3, 0, 7, and 28 relative to timed AI, and plasma progesterone concentrations were determined by RIA. Cows were observed daily for signs of estrus based on removal of tail paint. Pregnancy was diagnosed by ultrasonography on d 34 and 62 after AI. Plasma progesterone concentrations across all time points were greater for hP4 (3.13 ± 0.20 ng/mL) followed by iP4 (1.12 ± 0.27 ng/mL) and lP4 (0.38 ± 0.23 ng/mL). Cows in lP4 on d -3 had lesser pregnancy per AI (P/AI) compared with iP4 and hP4 (17.4, 38.3, and 37.2%, respectively). For measurements performed on the day of AI (d 0), lP4 cows had greater P/AI compared with hP4 and iP4 (34.8, 0.0, and 15.6%, respectively), and the risk of pregnancy loss tended to be greater for iP4 compared with lP4. Cows in lP4 on d 7 after AI had lesser P/AI than those in iP4 and hP4 (12.0, 34.0, and 37.7%, respectively). Cows classified as lP4 on d 28 had the least P/AI on d 62 followed by iP4 and then hP4 (0.8, 9.2, and 59.4%, respectively) and were at the greatest risk for pregnancy loss (lP4 = 74.6%, iP4 = 8.4%, hP4 = 7.1%). Sensitivity and specificity to predict non-pregnancy on d 62 were 0.86 and 0.32 (d -3), 0.95 and 0.15 (d 0), 0.93 and 0.23 (d 7), and 0.99 and 0.53 (d 28), respectively. On-farm milk progesterone profiling using a lateral flow immunochromatographic test was able to identify cows without functional corpus luteum and to predict fertility outcomes following timed AI.

Short communication: Economic impact among 7 reproductive programs for lactating dairy cows, including a sensitivity analysis of the cost of hormonal treatments

Although hormonal synchronization programs can improve reproductive efficiency of dairy herds, some farmers question the economics of these programs based on the upfront cost of hormonal treatments as opposed to the economic value of the resulting reproductive performance. Our aim was to compare the economic impact of reproductive management programs that incorporate varying degrees of detection of estrus and timed artificial insemination (AI) in dairy herds with year-round calving in confinement total mixed ration systems. A reproductive economic analysis simulation model was used to compare the economic impact of pairs of reproductive management programs. We simulated sets of scenarios for 2 analyses. In the first analysis, we calculated the economic impact of switching from a Presynch-Ovsynch program to a Double-Ovsynch program that included a second PGF_2α treatment during the Breeding-Ovsynch portion of the program (Double-Ovsynch+PGF). In the second analysis, we conducted a break-even analysis in which the cost of hormonal treatments was incrementally increased within various reproductive management programs. Our analyses revealed that a Double-Ovsynch+PGF program, the most intensive program evaluated, was more profitable than other programs compared, including a Presynch-Ovsynch program with 100% timed AI or a Presynch-Ovsynch program that incorporated detection of estrus, despite the higher upfront cost incurred by using more hormonal treatments. This advantage remained until the cost of hormones was increased 5 to 14 times current US market prices and 2 to 6 times current European market prices. The cost of GnRH had a greater impact on net profit gain than the cost of PGF_2α. In conclusion, more intensive reproductive programs that use more hormonal treatments but result in substantially increased reproductive performance are more profitable than less intensive programs and remain so even if hormone prices are unusually high.

A lateral flow-based portable platform for determination of reproductive status of cattle

Our objective was to develop and validate a tool integrating a disposable fluorescence-based lateral flow immunoassay (LFIA) coupled with a portable imaging device for estimating circulating plasma concentrations of progesterone (P4). First, we developed and optimized a competitive LFIA test strip to measure P4 in bovine plasma. The LFIA design included a sample pad, a conjugate pad that stores R-phycoerythrin-anti-P4 conjugates, a glass-fiber spacer pad, a nitrocellulose membrane with printed test and control lines, and a cellulose-fiber absorbent pad. To perform a test, 20 µL of plasma and 50 µL of running buffer were added on the sample pad. After 3 min, 45 µL of running buffer was added to initiate sample flow. After allowing 15 min to stabilize the colorimetric signal, strips were introduced in an LFIA portable reader wirelessly linked to a laptop to determine P4 concentration based on test-to-control-line signal (T/C ratio). In a series of experiments (n = 6), the ability of the LFIA to differentiate plasma samples with ≥1 or <1 ng/mL of P4 was evaluated. For each experiment, a calibration curve was constructed using plasma with known concentrations of P4 (0.1 to 3.7 ng/mL; n = 5). The resulting linear equation was then used to determine a T/C ratio cutoff to differentiate samples with ≥1 or <1 ng/mL of P4. In addition, to evaluate the ability of the platform to assign samples to P4 concentration groups without a calibration curve for individual batches, we performed a receiver operating characteristic analysis to identify a single cutoff value for T/C ratio that could potentially be used for all batches. Overall, calibration curves showed a linear relationship between T/C ratio and P4 levels (mean coefficient of determination = 0.74; range 0.42 to 0.99). Next, plasma samples from lactating dairy cows (n = 58) were tested in triplicate to determine the ability of the LFIA system to differentiate plasma samples with ≥1 or <1 ng/mL of P4 using a RIA for P4 as reference test. Overall, the LFIA assay correctly classified 90% of the samples, with 97% sensitivity, 83% specificity, 85% positive predictive value, and 96% negative predictive value. Agreement between the tests was substantial (kappa = 0.79; 95% confidence interval 0.64 to 0.95). When using a single cutoff value for T/C ratio selected by receiver operating characteristic analysis, sensitivity and specificity to determine CL presence were 97 (95% confidence interval 82 to 99) and 79% (95% confidence interval 60 to 92), respectively. These data suggest that the developed portable LFIA system can accurately differentiate plasma samples with ≥1 or <1 ng/mL of P4.

Fertility response of lactating dairy cows subjected to three different breeding programs under subtropical conditions

Background

It is comprehensively recognized that reduced reproductive efficiency represents a great economic loss to dairy producers. Ovarian cysts and anestrus syndromes are considered the greatest significant causes of low reproductive efficiency in dairy herds worldwide as they detrimentally affect the longevity and profitability of dairy herd. Pregnancy rate is the best available single deciding parameter used for assessment of the reproductive efficiency at the herd level which measures the probability that open cows become pregnant per unit of time. So, the current study was planned to evaluate the suitability of using Ovsynch plus CIDR and G6G resynchronization protocols as an efficient treatment regimen for cystic ovarian diseased cows and anestrus cows, respectively, through comparing pregnancy rates of cystic ovarian diseased cows that subjected to Ovsynch supplemented with controlled internal drug release device with the pregnancy rate of healthy cows that subjected to a Presynch-Ovsynch synchronization protocol, as well as through comparing pregnancy rates of anestrus cows that subjected to G6G treatment protocol with the pregnancy rate of healthy cows. Moreover, possible factors such as breed, parity, and season which may affect the treatment success were also evaluated.

Results

The results of the current study revealed an overall mean pregnancy rate of 36.64%. Moreover, Simmental cows recorded a greater (p < 0.01) pregnancy rate (45.16%) than that recorded for Holstein cows (34.98%). A highly significant seasonal effect was observed, as a higher (p < 0.01) pregnancy rate was recorded for cows inseminated during cold months (39.54%) compared with that recorded for cows inseminated during hot months (29.18%).

Conclusions

No significant differences were detected in the pregnancy rates among the three breeding programs; thence, the application of the G6G synchronization protocol for anestrus cows and Ovsynch-CIDR synchronization protocol for cows with ovarian cysts could be used as effective treatment regimens as they resulted in nearly the same pregnancy rates that recorded for healthy cows. In addition, the treatment response was highly influenced by cow’s breed, parity, and season of breeding.

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.

Quantification by simulation of the effect of herd management practices and cow fertility on the reproductive and economic performance of Holstein dairy herds

The performance of dairy herds is affected mainly by factors related to cows' characteristics and herd management practices. However, these factors are interrelated, and as such, the estimation of their individual effect on the performance of dairy herds remains difficult. The aim of this study was to estimate the weight of these factors as well the interactions between them on the reproductive and economic performance of dairy farms. A stochastic dynamic model was used to simulate most physiological and management processes occurring on a dairy farm. A herd of 60 Holstein cows, with a milk yield of 8,000 L/cow-year, representative of French Holstein dairy herds, was simulated. A total of 216 scenarios were run by combining 2 levels of postpartum cyclicity resumption (average: 45 d, high: 75 d), 3 levels of 21-d conception rate of the herd (i.e., proportion of cows pregnant 21 d after insemination; low: 25%, average: 45%, high: 70%), 3 levels of probability of pregnancy loss until 120 d (low: 3%, average: 15%, high: 43%), 3 levels of sensitivity of estrus detection by the farmer (low: 20%, average: 50%, high: 90%), 2 alternative managerial goals (constant number of cows or constant volume of milk sold), and 2 types of management for the sale and purchase of animals (closed or open herd). The effect of each factor was estimated by sensitivity analysis. The parameter that had the greatest effect on reproductive performance was the sensitivity of estrus detection: a 10-percentage-point increase between the low and average levels and between the average and high levels reduced the calving interval by 16 and 5.7 d, respectively. However, the factor that had the greatest effect on economic performance was the 21-d conception rate: a 10-percentage-point increase between the low and average levels and between the average and high levels increased the gross margin by €62.2 and €22.3/cow-year, respectively. The pregnancy loss until 120 d had an effect on economic performance: an increase of 1 percentage point of this parameter decreased the gross margin by €2/cow-year. The other factors studied, and their interactions, did not have a major effect (low value of sensitivity indices). Closed herds or farms with a constant number of cows had economic losses of €58/cow-year compared with open herds or to farms with constant volume of milk sold. Altogether, our data suggest that, in a typical French dairy farm, farmers' efforts on estrus detection will be more profitable when associated with improvement of the conception rate of the cows.

Genomic merit for reproductive traits. I: Estrous characteristics and fertility in Holstein heifers

Genetic selection of dairy cattle in the United States has included reproductive traits (daughter pregnancy rate, DPR; heifer conception rate, HCR), which is believed to have partly contributed to halting the decline in reproductive performance. The objectives of the current study were to evaluate the association among genomic merit for DPR (GDPR) and HCR (GHCR) with estrous characteristics measured by an automated device. Holstein heifers (n = 1,005) were genotyped at 2 mo of age and were classified into quartiles (Q1 = lowest, Q4 = highest) according to the GDPR and GHCR values of the study population. At 10 to 11 mo of age, heifers were fitted with a collar that recorded activity and rumination and determined the occurrence of estrus according to changes in activity and rumination compared with the individual's baseline values. Estrous characteristics of spontaneous estruses (SPE) and PGF_2α-synchronized estruses (PGSE) were recorded. Heifers had their estrous cycle synchronized with PGF_2α and following detection of estrus received either artificial insemination or embryo transfer according to the herd's genetic selection program. Heifers in Q2 (17.7 ± 0.3 h) of GHCR tended to have longer SPE than heifers in Q4 (16.7 ± 0.3 h). The interaction between GDPR and GHCR was associated with the likelihood of activity peak (0 = no estrus, 100 = maximum activity) ≥80 at SPE because, among heifers in Q3 and Q4 of GHCR, those in Q1 of GDPR were less likely to have an activity peak ≥80. Heifers in Q1 and Q2 of GDPR had reduced hazard of estrus within 7 d of the first PGF_2α treatment compared with heifers in Q4 of GDPR. Heifers in Q1 (16.1 ± 0.4 h) of GDPR had shorter PGSE than heifers in Q2 (17.6 ± 0.4 h) and Q4 (17.4 ± 0.4 h) and tended to have shorter PGSE than heifers in Q3 (17.4 ± 0.4 h). Rumination nadir on the day of PGSE was greater for heifers in Q1 (-30.1 ± 0.9 min/d) of GDPR compared with heifers in Q4 (-33.7 ± 0.9 min/d). Among heifers receiving only artificial insemination, those in Q1 of GHCR (adjusted hazard ratio = 0.65; 95% confidence interval = 0.48-0.88) became pregnant at a slower rate than heifers in Q4. Genomic merit for HCR was negatively associated with SPE but tended to be positively associated with hazard of pregnancy, whereas GDPR was positively associated with PGSE and hazard of estrus. Selection of dairy cattle for DPR and HCR may improve reproductive performance through different pathways, namely estrous characteristics and pregnancy establishment.

Profitability of dairy cows submitted to the first service with the Presynch-Ovsynch or Double-Ovsynch protocol and different duration of the voluntary waiting period

The objective of this study was to compare cash flow and parameters of economic performance for dairy cows submitted to the first service using a combination of insemination at detected estrus and timed AI (TAI) in cows synchronized with the Presynch-Ovsynch (PSOv) protocol versus all TAI after synchronization of ovulation with the Double-Ovsynch (DO) protocol with different durations of the voluntary waiting period. A secondary objective was to calculate the variation in cash flow under different input pricing scenarios through stochastic Monte Carlo simulation. Lactating Holstein cows from a commercial dairy farm were randomly assigned to 3 first-service management programs. Cows in the PSOv treatment (n = 450) received first service through a combination of insemination at detected estrus after a voluntary waiting period of 50 d in milk (DIM; i.e., after second PGF_2α treatment of the protocol) and TAI at 72 ± 3 DIM. Cows in the DO60 (n = 458) and DO88 (n = 462) treatments received first service by TAI at 60 ± 3 and 88 ± 3 DIM, respectively. Individual cow cash flow was calculated for the calving interval after enrollment and for an 18-mo period after calving. Cash flow was the aggregation of daily income over feed cost, replacement cost, calf value, recombinant bovine somatotropin treatment cost, reproductive cost, and other operating expenses. All analyses were conducted separately for primiparous and multiparous cows. Continuous, binomial, and time to event outcomes were analyzed using ANOVA, logistic regression, and Cox's proportional hazard regression in SAS (SAS Institute Inc., Cary, NC). Treatments affected the dynamics of pregnancy creation, which affected time to pregnancy during lactation. As a result, we observed differences in the proportion of nonpregnant cows at the end of lactation, herd exit dynamics, lactation length, calving interval, and proportion of cows that calved again. Some of these effects varied by parity, affecting the direction and magnitude of treatment differences within parity group. For primiparous cows, maximum cash flow differences per slot for the 18-mo period were in the range of $26 (PSOv > DO60) to $29 (DO88 > DO60) but did not differ statistically. For multiparous cows, maximum cash flow differences per slot for the 18-mo period were in the range of $122 (PSOv > DO88) to $155 (DO60 > DO88) but did not differ statistically. Despite the substantial differences in cash flow (in particular for multiparous cows) caused by the effect of treatments on reproductive performance, herd exit dynamics, and calving interval, large variability in overall cash flow among individual cows and compensation between multiple outcomes resulted in lack of statistical differences in cash flow. Outcomes from the stochastic analysis indicated that similar trends for differences between treatments would be observed under varying scenarios for economic input values. In conclusion, we did not detect statistically significant cash flow differences between the PSOv, DO60, and DO88 treatments, but numerical trends and stochastic simulation indicated that the DO88 and PSOv treatments were more economically favorable than the DO60 treatment for primiparous cows. For multiparous cows, the DO60 and PSOv treatments were more economically favorable than the DO88 treatment.

Pilot Study to Evaluate the Association Between the Length of the Luteal Phase and Estrous Activity Detected by Automated Activity Monitoring in Dairy Cows

The ability of automated activity monitoring (AAM) systems to detect estrus is influenced by multiple variables. The luteal phase (LP) preceding estrus has been shown to be important for hormones release, and behavior during estrus in ruminants, but its impact on activity as measured by AAM systems has not been studied. The objective of this study was to investigate the impact of the length of the preceding LP on the intensity and duration of estrus as measured by AAM, and on the expression of estrogen receptor alpha (ERα) in the endometrium. A total of 60 cows between 46 and 53 days in milk were assigned to either a normal or a short length LP. Length of the LP was insured by the use of hormonal synchronization programs. Cows in both treatments were matched on parity, milk production, body condition score (BCS), and lameness score (assessed at enrolment). Expression of ERα receptors in the endometrium were evaluated by nuclear staining by immunohistochemistry of biopsies. Estrus was defined as the day on which the AAM system detected estrus. Cows that were not synchronized by the protocol or that were not detected in estrus by the AAM systems were excluded, which left 21 and 11 cows for analyses in the normal and short length LP, respectively. Peak activity index of estrus, duration of estrus, and expression of ERα were outcomes for multivariable linear regression models. Cows with short length LP tended to have lower peak activity at estrus, but there was no significant effect of treatment when BCS was accounted for. Cows with BCS ≤ 2.5 had less intense and shorter estrus than cows with BCS ≥ 2.75. There was no association between the length of the LP and the expression of ERα in the endometrium.

An economic evaluation of management strategies to mitigate the negative effect of twinning in dairy herds

Our objectives were to develop an economic model to estimate the economic impact of twinning in dairy cows and to evaluate management strategies to mitigate the negative economic impact of twinning in dairy herds. A probabilistic tree considering spontaneous embryo reduction, early pregnancy loss, abortion, metritis, retained placenta, and culling rate at 120 d of the second, at the end of the second, and at the end of the third lactation was developed for a single pregnancy; we also developed 3 management options upon diagnosis of a twin pregnancy: (1) do nothing, (2) induce abortion using PGF_2α, or (3) attempt manual embryo reduction. A value was given to each branch of the tree by simulating cow states on a farm for 1,400 d to encompass 4 consecutive lactations. The incomes considered in the simulations included milk income over feed cost, income from calves, and slaughter value upon culling. The expenses taken into account depending on each branch included additional inseminations and synchronization protocols, embryo reduction, induction of abortion, replacement heifers, and costs due to metritis and retained placenta. The gross value for a singleton pregnancy and the 3 management options upon diagnosis of a twin pregnancy were calculated by adding the value of all braches multiplied by their probability. The costs for the 3 management options were calculated by subtracting its gross value minus the gross value of a singleton pregnancy. The negative economic impact of a twin pregnancy ranged from $97 to $225 depending on the type of twin pregnancy (unilateral vs. bilateral), parity, and DIM when the twin pregnancy occurred. The overall negative economic impact of twinning on dairy farm profitability in the United States was estimated to be $96 million per year. Attempting manual embryo reduction early during gestation upon diagnosis of a twin pregnancy was the optimal management strategy for mitigating the negative economic impact of twinning under a wide variety of scenarios.

Reproductive Systems for North American Dairy Cattle Herds

Reproductive inefficiency compromises the profitability of dairy herds and the health and longevity of individual cows. In the average dairy herd, the combination of estrus detection and ovulation synchronization protocols yields the best economic return. Genomic selection of animals is particularly profitable in situations in which little is known about their genetic potential. Biosensor systems in milking parlors may allow for the design of reproductive strategies tailored for cows according to their physiologic needs while optimizing economic return.