Early prediction of oestrus for herd fertility management in cattle and buffaloes - a review.

Oestrus is defined as a period when a female animal exhibits characteristic sexual behaviour in the presence of a mature male. Oestrous manifestation in dairy animals is due to the oestrogen (E2) effect on the central nervous system (CNS). It is a critical issue to be considered on a priority basis. Inefficient oestrous detection reduces the fertility status of the herd. The primary and most reliable indicator of oestrus is standing to be mounted by a bull or another female herd mate, signalling receptivity and the pre-ovulatory state in dairy cattle. Oestrous detection is primarily a management challenge requiring skill and vigilance. To improve the efficiency of oestrous detection in dairy cattle, visual observation is one of the best methods if done three times a day; however, heat detection aids, if combined, give better results. However, techniques like using teaser bulls, tail painting, chin ball markers, ultrasound (USG) examination, hormonal analysis and examination of cervicovaginal mucus (CVM) improve oestrous detection efficiency. Moreover, the changes in production systems have reduced the expression of oestrous behaviour among cows, due to higher oestrogen (E2) metabolism. Therefore, automated systems, such as pedometers, accelerometers and acoustic sensors like infrared thermography (IRT) and image processing, have significantly enhanced reproductive performance by facilitating oestrous detection and optimizing insemination schedules. From this review, we would conclude that oestrous detection alone contributes considerably to the reproductive status of the herd; therefore, applying different methods of oestrous detection reduces the incidence of missed oestrus and improves the fertility status of the herd.

Social effects on behaviorally-scored and pedometer-detected estrus in beef cattle.

The number of cows in estrus often influences estrus behavior; however, the effects of social order are not well documented. This study examined the effects of social order on the expression of behaviorally-scored and pedometer-detected estrus, combined with the effects of the number of cows in estrus. In a herd comprising 13 or 15 beef cattle, cows with orders 1st-7th were defined as dominant and the remaining cows as subordinate. Sole or simultaneous estrus was induced by prostaglandin F2α analog injection and/or intravaginal progesterone treatment. Ovulation timing was determined using ultrasonography at 6-hour intervals. Estrous signs and steps of the cows were recorded 49 h before ovulation using video monitoring and a pedometer, respectively. Among the 59 treated cows, 56 behaviorally-scored estruses (27 sole and 29 simultaneous) were detected. In the sole estrus, 61.5% of the dominant-rank cows had no zero-point period; however, 35.7% of the subordinate-rank cows had that period. The dominant-rank cows in estrus alone had a significantly shorter duration of scored estrus than those in simultaneous estrus (P < 0.05). Among the 50 pedometer-detected estruses (24 sole and 26 simultaneous), the subordinate-rank cows in sole estrus had a shorter interval from estrus onset to ovulation than the dominant-rank cows in simultaneous estrus (P < 0.05). The effects of social order varied in response to the number of cows in estrus, which might have influenced determining the optimal time for artificial insemination.

Economic viability of using OvSynch and fixed timed artificial insemination protocol in breeding improvement of pastoral herds in the rangelands.

Though using Assisted Reproductive Technologies (ARTs) can improve oestrus detection, conception and pregnancy success, thus benefit breeding program implementation, empirical evidence of their economic viability is lacking to inform investment decisions in pastoral herds. This study assessed economic viability of using OvSynch and fixed Timed Artificial Insemination (TAI) protocol in Sahiwal upgrading breeding program under two hypothetical cases of best and worst in activity-based money allocations when pastoral herds deploy either optimal or low input husbandry practices. From herd owners' assessment of milk production, best-case scenarios attain on average 10 L/cow/day with optimal husbandry and 5 L/cow/day with low input husbandry. The worst-case scenarios attain 5 L/cow/day with optimal husbandry and 1 L/cow/day with low input husbandry. Benefit- Cost Analysis (BCA) estimated Net Present Value (NPV), Benefit-Cost ratio (BCR) and Internal Rate of Return (IRR) to establish economic viability of using OvSynch and TAI Protocol in pastoral breeding programs. Both best-case scenarios retuned positive NPVs (82,028 and 6,912), BCR values (1.68 and 1.08) and IRR (27.46% and 8.08%) while worst-case scenarios returned negative NPVs (-135,855 and -141,025), BCR values of below 1 (0.87 and 0.66) and IRR values below the minimum rate of returns. These economic parameters were sensitive to price changes in inputs and outputs, under both optimal and low input husbandry practices. Results indicate that using OvSynch and TAI Protocol is a profitable and economically viable investment under optimal husbandry practices but not under low input husbandry practices. By implications, use of OvSynch and TAI Protocol in Sahiwal upgrading breeding programs need be accompanied with improved husbandry practices and de-risking pastoral herd owners from price changes in input and output markets.

Estrus Detection and Dairy Cow Identification with Cascade Deep Learning for Augmented Reality-Ready Livestock Farming.

Accurate prediction of the estrus period is crucial for optimizing insemination efficiency and reducing costs in animal husbandry, a vital sector for global food production. Precise estrus period determination is essential to avoid economic losses, such as milk production reductions, delayed calf births, and disqualification from government support. The proposed method integrates estrus period detection with cow identification using augmented reality (AR). It initiates deep learning-based mounting detection, followed by identifying the mounting region of interest (ROI) using YOLOv5. The ROI is then cropped with padding, and cow ID detection is executed using YOLOv5 on the cropped ROI. The system subsequently records the identified cow IDs. The proposed system accurately detects mounting behavior with 99% accuracy, identifies the ROI where mounting occurs with 98% accuracy, and detects the mounting couple with 94% accuracy. The high success of all operations with the proposed system demonstrates its potential contribution to AR and artificial intelligence applications in livestock farming.

Postpartum health is associated with detection of estrus by activity monitors and reproductive performance in dairy cows.

The objective of this prospective observational study was to investigate associations of postpartum health with estrus detection (ED) by activity monitors and pregnancy outcomes in dairy cows. A total of 1,743 Holstein cows from 2 commercial dairy herds in Ontario, Canada were enrolled 3 wk before expected parturition and examined for health variables until 9 wk postpartum. Body condition score (BCS) and lameness were measured at 3 wk prepartum, and serum concentrations of total Ca, haptoglobin (Hp), and nonesterified fatty acids were measured at 2 and 6 ± 2 d in milk (DIM), and blood ß-hydroxybutyrate (BHB) and metritis were assessed at 4, 8, 11, and 15 ± 2 DIM. Cows were examined for purulent vaginal discharge (PVD) and endometritis (ENDO) by endometrial cytology at wk 5, for lameness at wk 3 and 7, for BCS at wk 9 postpartum, and for time to onset of cyclicity by biweekly serum progesterone (P4) measurements. Additional disease data were obtained from farm records. Reproductive management for first AI was primarily based on ED by activity monitors until at least 75 DIM, and cows not detected in estrus were synchronized. Data were analyzed in multivariable logistic or Cox proportional hazards regression models including blood markers, health variables, potential covariates, and herd as a random effect. Estrus was detected in 77% of primiparous and 66% of multiparous cows between 50 or 55 DIM and 75 DIM. In 1,246 cows, the model-predicted probability of ED (percentage point difference) was lower in cows that had retained placenta (-14%), ENDO (-7%), PVD (-8%), delayed cyclicity (no P4 > 1 ng/mL by wk 9; -12%), or ≥0.5-point BCS loss (-14%) compared with cows without each of these risk factors, and it was negatively associated with blood BHB at 15 DIM. Considering only variables measured on farm (not requiring laboratory analysis), the probability of ED was lower (56 vs. 81%) in cows with >1 risk factor compared with cows without risk factors. The predicted probability of pregnancy at first artificial insemination (percentage point difference) was lower in cows that had ENDO (-7%) or PVD (-7%), and negatively associated with serum Hp at 6 ± 2 DIM. In cows detected in estrus by 75 DIM (n = 888), risk factors for reduced pregnancy rate by 250 DIM (adjusted hazard ratio (AHR); 95% confidence intervals) included difficult calving (AHR: 0.67; 0.45 to 1.00), metritis (AHR: 0.79; 0.61 to 1.01), PVD (AHR: 0.79; 0.65 to 0.97), or lameness (AHR: 0.79; 0.62 to 1.01), and it was negatively associated with serum Hp at 6 ± 2 DIM. Monitoring postpartum health may be used to identify cows that are more or less likely to be detected in estrus by activity monitors and to become pregnant in a timely manner. This would support a selective reproductive management program with targeted interventions.

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.

Targeted reproductive management for lactating Holstein cows: Reducing the reliance on exogenous reproductive hormones.

Adoption of automated monitoring devices (AMD) affords the opportunity to tailor reproductive management according to the cow's needs. We hypothesized that a targeted reproductive management (TRM) would reduce the use of reproductive hormones while increasing the percentage of cows pregnant 305 d in milk (DIM). Holstein cows from 2 herds (n = 1,930) were fitted with an AMD at 251.0 ± 0.4 d of gestation. Early-postpartum estrus characteristics (EPEC; intense estrus = heat index ≥70; 0 = minimum, 100 = maximum) of multiparous cows were evaluated at 40 (herd 1) or 41 (herd 2) DIM and EPEC of primiparous cows were evaluated at 54 (herd 1) or 55 (herd 2) DIM. Control cows received the first artificial insemination at fixed time (TAI; primiparous, herd 1 = 82 and herd 2 = 83 DIM; multiparous, herd 1 = 68 and herd 2 = 69 DIM) following the Double-Ovsynch (DOV) protocol. Cows enrolled in the TRM treatment were managed as follows: (1) cows with at least one intense estrus were inseminated upon AMD detected estrus for 42 d and, if not inseminated, were enrolled in the DOV protocol; and (2) cows without an intense estrus were enrolled in the DOV protocol at the same time as cows in the control treatment. Control cows were re-inseminated based on visual or patch aided detection of estrus, whereas TRM cows were re-inseminated as described for control cows with the aid of the AMD. Cows received a GnRH injection 27 ± 3 d after insemination and, if diagnosed as nonpregnant, completed the 5-d Cosynch protocol and received TAI 35 ± 3 d after insemination. Among cows in the TRM treatment, 55.8 and 42.9% of primiparous and multiparous cows, respectively, received the first insemination in spontaneous estrus. The interaction between treatment and parity affected pregnancy 67 d after the first AI (primiparous: control = 37.6%, TRM = 27.4%; multiparous: control = 41.0%, TRM = 44.7%). The TRM treatment increased re-insemination in estrus (control = 48.3%, TRM = 70.5%). Pregnancy 67 d after re-inseminations tended to be affected by the interaction between treatment and EPEC (no intense estrus: control = 25.3%, TRM = 32.0%; intense estrus: control = 32.9%, TRM = 32.2%). The interaction between treatment and EPEC affected pregnancy by 305 DIM (no intense estrus: control = 80.8%, TRM = 88.2%; intense estrus: control = 87.1%, TRM = 86.1%). Treatment did not affect the number of reproductive hormone treatments among cows that had not had an intense estrus (control = 10.5 ± 0.3, TRM = 9.1 ± 0.2 treatments/cow), but cows in the TRM treatment that had an intense estrus received fewer reproductive hormone treatments than cows in the control treatment (2.0 ± 0.1 vs. 9.6 ± 0.2 treatments/cow). Selecting multiparous cows for first AI in estrus based on EPEC reduced the use of reproductive hormones without impairing the likelihood of pregnancy to first AI. The use of AMD for re-insemination expedited the establishment of pregnancy among cows that did not display an intense estrus early postpartum.

Identification of oestrus cows based on vocalisation characteristics and machine learning technique using a dual-channel-equipped acoustic tag.

Timely and accurate detection of oestrus in cows is an essential element of the good management of dairy farms. At present, the detection of cows in oestrus by acoustic means is impeded by the problems of filtering, incomplete feature selection, and poor recognition accuracy. To overcome these difficulties, this study proposes a sound detection method for cows in oestrus based on machine learning technology using an optimal feature combination and an optimal time window. Firstly, a dual-channel sound detection tag consisting of a unidirectional microphone and an omnidirectional microphone (OM) was developed. The Least Mean Squares adaptive algorithm based on wavelet thresholds was used to filter the signals from the OM, and the dual-channel endpoint detection algorithm was used to identify the lowing of individual cows. The Friedman analysis was then used to select the sound features with significant differences before and after oestrus in terms of time, frequency, and cepstrum, and these were used to determine the most acceptable feature combination. We then analysed the effects of Back Propagation Neural Network (BPNN), Cartesian Regression Tree, Support Vector Machine, and Random Forest classification on the accuracy, precision, sensitivity, specificity, and F1 score of oestrus discrimination. Different time windows were used, and the discrimination performance of these algorithms was evaluated using the Area under Receiver Operating Characteristic Curve to find the most satisfactory match between the time window and the recognition algorithm. The dual-channel acoustic tag's accuracy, precision, sensitivity, and specificity results were 91.25, 98.83, 91.75, and 83.68%, respectively. BPNN with the 70 ms time window and the feature combination (spectral roll-off + spectral flatness + Mel-Frequency Cepstrum Coefficients) was confirmed as the most suitable oestrus recognition method. The average accuracy, precision, sensitivity, specificity, and F1 score of this method were 97.62, 98.07, 97.17, 97.19, and 97.63%, respectively. Based on these results, the approach was shown to be a feasible means of oestrus detection in dairy cows. Based on its ability to differentiate cows and its consistency, it was demonstrated that sound has the potential to replace accelerometers as an early indicator of oestrus in dairy cows.

Effect of a targeted reproductive management program designed to prioritize insemination at detected estrus and optimize time to insemination on the reproductive performance of lactating dairy cows.

The primary objective of this randomized controlled experiment was to evaluate the insemination dynamic and reproductive performance of cows managed with a targeted reproductive management (TRM) program designed to prioritize artificial insemination (AI) at detected estrus (AIE) and optimize timing of AI by grouping cows based on detection of estrus during the voluntary waiting period (VWP). Our secondary objective was to evaluate reproductive outcomes for cows with or without estrus during the VWP. Lactating Holstein cows fitted with an ear-attached sensor for detection of estrus were randomly assigned to a TRM treatment that prioritized AIE based on detection of estrus during the VWP (TP-AIE; n = 488), a non-TRM treatment that prioritized AIE (P-AIE; n = 489), or an all timed AI (TAI) treatment with extended VWP (ALL-TAI; n = 491). In TP-AIE, cows with or without automated estrus alerts (AEA) recorded during the VWP received AIE if detected in estrus for at least 31 ± 3 or 17 ± 3 d after a 49 d VWP, respectively. Cows not AIE with or without AEA during the VWP received TAI after Ovsynch with progesterone supplementation and 2 PGF2α treatments (P4-Ov) at 90 ± 3 or 74 ± 3 d in milk (DIM), respectively. In P-AIE, cows received AIE if detected in estrus for 24 ± 3 d after a 49 d VWP, and if not AIE received TAI at 83 ± 3 DIM after P4-Ov. In ALL-TAI, cows received TAI at 83 ± 3 DIM after a Double-Ovsynch protocol. Data were analyzed by logistic and Cox's proportional hazard regression. The proportion of cows AIE did not differ for TP-AIE (71.0%) and P-AIE (74.6%). Overall P/AI at 39 d after first service was greater for the ALL-TAI (47.6%) than for the P-AIE (40.2%) and TP-AIE (39.5%) treatments. The hazard of pregnancy up to 150 DIM was greater for cows in TP-AIE (hazard ratio = 1.2; 95% confidence interval: 1.1-1.4) and P-AIE (hazard ratio = 1.2; 95% confidence interval: 1.1-1.4) than for cows in the ALL-TAI treatment which resulted in median time to pregnancy of 89, 89, and 107 d. Conversely, the proportion of cows pregnant at 150 DIM did not differ (ALL-TAI 78.5%, P-AIE 76.3%, TP-AIE 76.0%). Except for a few outcomes for which no difference was observed, cows detected in estrus during the VWP had better performance than cows not detected in estrus. Cows with AEA during the VWP were more likely to receive AIE, had greater P/AI, and greater pregnancy rate up to 150 DIM regardless of first service management. We conclude that a TRM program designed to prioritize AIE by grouping cows based on detection of estrus during the VWP was an effective strategy to submit cows for first service resulting in similar or improved performance than a non-TRM program that prioritized AIE or an all-TAI program with extended VWP. Also, AEA recorded during the VWP might be used as a strategy for identifying subgroups of cows with different reproductive performance.

The effect of progesterone length in timed AI in ewes.

This study aimed to evaluate the reproductive performance of ewes submitted to timed AI protocol with 7 (D7) or 9 (D9) days of progesterone. A total of 220 crossbred ewes (Doper × Santa Ines) were distributed in the treatments according to body weight (52.67 ± 11.76 kg), body condition score (2.5 ± 0.8; scale of 1-5), and the female category (multiparous, nulliparous and primiparous). Ewes received an intravaginal device of 0.3 g of progesterone (CIDR® Easy breed) on day 0, keeping in ewes for 7 or 9 days, which were the experimental treatments. At the time of P4 withdrawal, ewes received 300 IU of eCG (Novormon®) and 6.70 mg of dinoprost tromethamine (Lutalyse®). Insemination by laparoscopy was performed between 46 and 59 h after device removal, lasting from 1 to 5 min/ewe, which did not differ between protocols. The estrus detection rate was higher in the 9-day protocol compared to the 7-day protocol (82% and 65%, respectively, P = 0.0096). However, the 7-day protocol tended to increase pregnancy rate on the TAI compared to the 9-day protocol (45% and 33%, respectively, P = 0.09). The plasma concentration of progesterone at device removal was higher in the 7-day protocol than in the 9-day protocol (2.35 and 1.22 ng/mL, respectively, P = 0.04). We conclude that reducing the length of the estrus synchronization protocol to 7 days is recommended, which improved the reproductive response in ewes.

Evaluating automated infrared thermography and vulva exposure tracking as components of an estrus detection platform in a commercial dairy herd.

The primary objective of this study was to develop an automated infrared thermography platform (Estrus BenchMark) capable of measuring skin temperature and tail movements as a means of identifying cows in estrus. The secondary objective was to evaluate the accuracy of Estrus BenchMark to detect estrus compared to in-line milk progesterone (P4) analysis (Herd Navigator System) in a commercial dairy herd managed under a robotic milking system. Data were collected on forty-six cows from 45 to 120 d after calving. Cows were flagged in estrus when milk P4 fell below 5 ng/mL. The Estrus BenchMark true positive estrus alerts (Sensitivity; Se%) were compared to Herd Navigator System estrus alerts at different time-windows (±12 h, ±24 h, ±48 h, and ±72 h) relative to the Estrus BenchMark estrus alerts for all the estrus alerts (AE) and confidence-quality estrus (CQE; >80% quality) alerts identified by Herd Navigator System. The Estrus BenchMark captured skin temperature and tail movements resulting in vulva exposure (left tail movements, LTail; right tail movements, RTail; and pooled tail movements, PTail) for each milking event. Skin temperature tended to increase when the milk P4 concentration (Least-Squares Means ±â€¯SE) dropped for AE (estrus day [d 0]; P4; 3.51 ±â€¯0.05 ng/mL, Skin temperature; 33.31 ±â€¯2.38 °C) compared with d -7 (P4; 20.22 ±â€¯0.73 ng/mL; Skin temperature: 32.05 ±â€¯3.77 °C). The increase in skin temperature, however, was significant in cows with CQE > 80% at d 0 (32.75 ±â€¯0.29 °C) compared to d -7 (31.80 ±â€¯0.28 °C). The prevalence of tail movements to expose vulva was greater (P = 0.01) in AE at d 0 (LTail: 62.50%; PTail; 68.75%; and RTail: 56.25%) compared with d -7 (LTail: 18.75%; PTail: 9.37%: and RTail: 9.37%), and d +4 (LTail: 9.37%; PTail: 9.37%; and RTail: 12.5%). Moreover, the higher prevalence of tail movements at d 0 was observed in cows with CQE > 80% (LTail; 65%, PTail; 80%, and RTail; 70%) compared to those with CQE < 80%. The highest Estrus BenchMark Youden index (YJ; 0.45), diagnostic odds ratio (DOR; 9.04), and Efficiency (0.77) were achieved for AE in a ±48 h window and at ±72 h window for CQE (YJ; 0.66, DOR; 25.29, and Efficiency 0.76) relative to Herd Navigator System estrus alerts. The highest Estrus BenchMark resulted in 58% estrus detection rates for AE and 80% for cows with CQE compared to the Herd Navigator System.

Positive relationship of rectal temperature at fixed timed artificial insemination on pregnancy outcomes in beef cattle.

The overarching aim was to examine the relationship of rectal temperature at fixed time artificial insemination (FTAI) on pregnancy outcomes in a typical breeding season with expected pregnancy rates approaching 50% using Bos indicus and Bos taurus cattle. This represents a continuum of steps to test the hypothesis that elevated body temperature at or around insemination is functionally important to maximize pregnancy outcomes. Rectal temperature of Bos indicus cattle at FTAI ranged from 37.0 to 40.9 °C; 60.6% were hyperthermic. Positive factors impacting pregnancy outcomes were rectal temperature at FTAI, body condition, and estrus patch scores. Rectal temperature at FTAI was positively associated with pregnancy outcomes (P < 0.0001); per each 1 °C increase pregnancy odds increased 1.9 times (95% CI: 1.4 to 2.6). Highest pregnancy outcomes occurred with rectal temperatures exceeding 40 °C (P = 0.0004). Rectal temperature before FTAI in Bos taurus cattle ranged from 37.8 to 41.8 °C; 43.3% were hyperthermic. Factors impacting pregnancy were rectal temperature at FTAI, estrus activity, parity, and ambient conditions on day of FTAI. Rectal temperature of Bos taurus cattle at FTAI was positively associated with pregnancy (P = 0.0286); odds increased 1.45 times (95% CI: 1.0 to 2.0) per each 1 °C increase. Highest pregnancy outcomes occurred with rectal temperatures at FTAI exceeding 40 °C (P = 0.057). Moreover, positive relationship of rectal temperature at FTAI to pregnancy persisted in estrual females (71.25% of total; P = 0.0408; OR 1.5; 95% CI: 1.0 to 2.2). Mindful that 1) elevated temperatures observed in Bos indicus and Bos taurus cattle directly promote meiotic resumption of the oocyte in vitro and that 2) in vivo hyperthermia alters intrafollicular components which others have shown to potentiate ovulation and promote meiotic resumption, it is biologically plausible that an acute elevation in body temperature at or around time of insemination is functionally important to maximize pregnancy outcomes.

Reproductive efficiency remains a major challenge for beef producers with 35% to 55% of females failing to become pregnant after a single insemination. While basis for failure is multi-factorial, heightened estrus activity matters for pregnancy outcomes, even when synchronizing ovulation for fixed time artificial insemination. Body temperature increases of 1.5 °C+ are common during estrus. We hypothesize that higher estrous-associated temperatures (HEAT) at/near insemination are functionally important to maximize pregnancy outcomes. Elevated temperatures equivalent to what is observed in females exhibiting HEAT have been shown to induce oocyte meiotic resumption. An acute episode of hyperthermia after the LH surge alters intrafollicular components known to potentiate ovulation and affect the oocyte. Effort to examine the relationship of rectal temperature at fixed time artificial insemination with pregnancy outcomes in a breeding season with expected pregnancy rates >50% represents a next step in the continuum of hypothesis testing. The positive relationship of rectal temperature at insemination with pregnancy outcomes that was discovered adds to foundational knowledge. Because the degree of hyperthermia is related to highest pregnancy outcomes, a case is made for HEAT to be biologically and functionally important to maximize pregnancy outcomes in cattle.

Possible causes and treatment strategies for the estrus and ovulation disorders in dairy cows.

The reproductive performance of dairy cows has declined, along with an increase in their milk yield. First-service conception rates in lactating dairy cows are often lower than 50%. The precise detection of estrus is an important factor in the reproductive management of dairy cows for successful fertilization and pregnancy. However, estrus expression has been decreasing in modern dairy cows, affecting the detection rate of estrus. In addition to estrus, a high incidence of ovulation disorders affects the fertility of dairy cows. To address these problems, it is necessary to understand the changes in the endocrine functions that underlie estrus and ovulation disorders, and to develop effective treatment strategies. Recent studies have revealed that neurokinin B and neurokinin 3 receptor signaling play important roles in the regulation of the secretion of gonadotropin-releasing and luteinizing hormones, suggesting a potential clinical avenue for the stimulation of gonadal function. In this review, I have discussed the problems in estrus and ovulation disorders in modern dairy cows as well as the possible applications of neurokinin 3 receptor agonists in the treatment of these disorders.

Business analysis of IRT, Visual observation, and Ovsynch as breeding strategies in Alberta dairies.

The dairy industry is searching for new technologies to address low (<50%) estrus detection. However, the lack of information on the potential economic benefits regarding new technology implementation has led some dairy producers to continue using conventional estrus detection methods (e.g. visual observation of standing to be mounted). The objective of this study was to compare the costs of infrared thermography (IRT), visual observation (VO) and ovulation synchronization (Ovsynch: OVS) as breeding strategies at different accuracy levels (Sensitivity [Se], Specificity [Sp]) and pregnancy rates (PR). The costs associated with Breeding, Feeding, Operation Costs, Return to Equity and Culling Risk per estrus detection rate (ER; 30-100%, conception rate for OVS; 30-100%), PR [PR per Parity group; 1-2 (50%), 3-4 (43%), and >4 (41%)], and ER accuracy determined the potential financial benefit of each breeding method for a representative farm. Breeding Cost results (Canadian dollars per cow; CAD/cow) showed a higher cost of OVS (138.99) as compared to VO (115.78) and IRT (127.69). Pregnancy Costs were affected by Breeding Cost; however, ER had a significant effect on PR expense for each method, IRT (ER; 30%: 210.38; 100%: 132.19), VO (ER; 30%: 205.93; 100%: 129.39), and OVS (ER; 30%: 247.21; 100%: 155.33). The minimum Se level with a positive Financial Effect for IRT and VO was 60% with a Sp of 100%, and for the OVS was Se 65% and Sp 100%. However, when the Se was 100% a positive Financial Effect was observed with a minimum Sp of 85% for IRT and 75% for VO. Culling Risk was reduced if ER increases differently depending on the parity group. Implementing of IRT as an estrus detection method yields a competitive breeding cost compared to VO and OVS. Further, breeding methods must accomplish at least ∼60% accuracy to have a positive net return.

Effect of gonadotropin-releasing hormone administered at the time of artificial insemination for cows detected in estrus by conventional estrus detection or an automated activity-monitoring system.

The objectives of this study were to determine the effects of GnRH at the time of artificial insemination (AI) on ovulation, progesterone 7 d post-AI, and pregnancy in cows detected in estrus using traditional methods (tail chalk removal and mount acceptance visualization) or an automated activity-monitoring (AAM) system. We hypothesized that administration of GnRH at the time of AI would increase ovulation rate, plasma progesterone post-AI, and pregnancy per AI (P/AI) in cows detected in estrus. In experiment 1, Holstein cows (n = 398) were blocked by parity and randomly assigned to receive an injection of GnRH at the time of estrus detection/AI (GnRH, n = 197) or to remain untreated (control, n = 201) on 4 farms. The GnRH was administered as 100 µg of gonadorelin acetate. Ovarian structures and plasma progesterone were assessed in a subset of cows (GnRH, n = 52; control, n = 55) in experiment 1 at the time of AI and 7 d later. In experiment 2, a group of 409 cows in an AAM farm were enrolled as described for experiment 1 (GnRH, n = 207; control, n = 202). Data were categorized for parity (primiparous vs. multiparous), season (cool vs. warm), number of services (first vs. > first), DIM (>150 DIM vs. ≤150 DIM), and for AAM cows in experiment 2 for activity level (high: 90-100 index vs. low: 35-89 index). Pregnancy diagnosis was performed between 32 and 45 d post-AI (P1) and 60 to 115 d post-AI (P2). In experiment 1, there was no difference in plasma progesterone at day of estrus detection (control = 0.09 ng/mL vs. GnRH = 0.16 ng/mL), 7 d later (control = 2.03 ng/mL vs. GnRH = 2.18 ng/mL), and ovulation rate (GnRH = 83.2% vs. control = 77.9%) between treatments. There were no effects of GnRH in experiment 1 for P/AI at P1 (control = 43.3% vs. GnRH = 38.6%), P2 (control = 38.4% vs. GnRH = 34.5%), and for pregnancy loss (control = 9.8% vs. GnRH = 8.2%). In experiment 2, there were no effects of GnRH for P/AI at P1 (control = 39.6% vs. GnRH = 40.1%), P2 (control = 35.0% vs. GnRH = 37.4%), and for pregnancy loss (control = 9.5% vs. GnRH = 6.2%). There was a tendency for a parity effect on P/AI for P1, but not P2 or for pregnancy loss. High-activity cows had greater P/AI in P1 (low activity = 27.9% vs. high activity = 44.1%), P2 (low activity = 21.8% vs. high activity = 41.2%), and lower pregnancy loss (low activity = 20.7% vs. high activity = 5.1%), but there were no interactions between treatment and activity level. The current study did not support the use of GnRH at estrus detection to improve ovulatory response, progesterone 1 wk post-AI, and P/AI. More research is needed to investigate the relationship between GnRH at the time of AI and activity level in herds using AAM systems.

Comparison of reproductive management programs for submission of Holstein heifers for first insemination with conventional or sexed semen based on expression of estrus, pregnancy outcomes, and cost per pregnancy.

Our objective was to evaluate reproductive management programs for submission of Holstein heifers for first insemination with conventional or sexed semen. In experiment 1, nulliparous Holstein heifers (n = 462) were submitted to a 5-d progesterone-releasing intravaginal device (PRID)-Synch protocol [d 0, GnRH + PRID; d 5, PGF2α - PRID; d 6, PGF2α; d 8, GnRH + TAI] and were randomly assigned for PRID removal on d 5 or 6 of the protocol followed by timed artificial insemination (TAI) with conventional semen. Delaying PRID removal decreased early expression of estrus before scheduled TAI (0.9 vs. 12.2%), and pregnancies per AI (P/AI) did not differ between treatments. In experiment 2, nulliparous Holstein heifers (n = 736) from 3 commercial farms were randomized within farm to 1 of 3 treatments for first AI with sexed semen: (1) CIDR5 [d -6, GnRH + controlled internal drug release (CIDR); d -1, PGF2α - CIDR; d 0, PGF2α; d 2, GnRH + TAI]; (2) CIDR6 (d -6, GnRH + CIDR; d -1, PGF2α; d 0, PGF2α - CIDR; d 2, GnRH + TAI); and (3) EDAI (PGF2α on d 0 followed by once-daily estrous detection and AI). Delaying CIDR removal decreased early expression of estrus before scheduled TAI (0.004 vs. 27.8%); however, CIDR5 heifers tended to have more P/AI at 35 (53 vs. 45 vs. 46%) and 64 (52 vs. 45 vs. 45%) days after AI than CIDR6 and EDAI heifers, respectively. Overall, CIDR5 and CIDR6 heifers had fewer days to first AI and pregnancy than EDAI heifers which resulted in less feed costs than EDAI heifers due to fewer days on feed until pregnancy. Despite greater hormonal treatment costs for CIDR5 heifers, costs per pregnancy were $16.66 less for CIDR5 than for EDAI heifers. In conclusion, delaying PRID removal by 24 h within a 5-d PRID-Synch protocol in experiment 1 suppressed early expression of estrus before TAI, and P/AI for heifers inseminated with conventional semen did not differ between treatments. By contrast, although delaying CIDR removal by 24 h within a 5-CIDR-Synch protocol in experiment 2 suppressed early expression of estrus before TAI, delaying CIDR removal by 24 h tended to decrease P/AI for heifers inseminated with sexed semen. Further, submission of heifers to a 5-d CIDR-Synch protocol for first AI tended to increase P/AI and decrease the cost per pregnancy compared with EDAI heifers.

Economic comparison of an ear tag automated activity monitor for estrus detection with timed-AI in Holstein heifers.

The objective of this study was to compare the economic performance of an ear tag automated activity monitor system (AAM) versus a timed-AI (TAI) protocol in Holstein heifers. In total, 340 heifers were enrolled onto the study at 13.5 mo of age and randomly assigned to receive either an AAM (n = 170) or TAI (n = 170) protocol before breeding eligibility (D 0). Heifers in the AAM group were fitted with an ear tag AAM and bred based on high activity alert from the system. Heifers in the TAI group received a progesterone releasing intravaginal device on D -8, followed by device removal and prostaglandin on D -3 and gonadotropin-releasing hormone with TAI on D 0. In both treatments, the majority of heifers received sex-sorted semen for the first AI and conventional semen for subsequent AIs, with three opportunities to become pregnant. All heifers were diagnosed for pregnancy approximately 25 d post AI using transrectal ultrasonography, with confirmation at 30 and 45 d. Non-pregnant heifers in the TAI group, were resynchronized using the same TAI protocol. A partial budget was used to compare the costs and benefits of switching from a TAI to an AAM protocol in heifers, including protocol, labour, and rearing costs for each treatment, as well as estimated calf and milk value. Sensitivity analyses were also conducted to determine the effect of pregnancy per AI (P/AI), outsourcing AI, AAM tag cost and herd size on the net outcome. There was no difference in overall P/AI or days to pregnancy between treatments. However, number of AI was greater in the TAI than the AAM group. For the first AI, the P/AI was less in the TAI compared to the AAM group; however, the interval to first AI was less in TAI. There was minimal difference in performance for the second and third AI. There was a net gain of $11.97 per heifer when switching from a TAI to AAM protocol, due to the increased P/AI to the first AI and reduced cost of hormones. Several variables in the sensitivity analyses affected the net outcome. Considering only the first AI, switching to an AAM collar and a larger herd size all increased the net gain. Considering a greater P/AI to the first AI in the TAI group, outsourcing AI, using more AAM ear tags, and smaller herd sizes resulted in a net loss when switching from TAI to AAM. The AAM system resulted in exceptional P/AI and may be an economically viable alternative to improve heifer reproductive efficiency in herds with suboptimal P/AI to TAI.

Motivations and attitudes of Brazilian dairy farmers regarding the use of automated behaviour recording and analysis systems.

In this Research Communication we investigate the motivations of Brazilian dairy farmers to adopt automated behaviour recording and analysis systems (ABRS) and their attitudes towards the alerts that are issued. Thirty-eight farmers participated in the study distributed into two groups, ABRS users (USERS, n = 16) and non-users (NON-USERS, n = 22). In the USERS group 16 farmers accepted being interviewed, answering a semi-structured interview conducted by telephone, and the answers were transcribed and codified. In the NON-USERS group, 22 farmers answered an online questionnaire. Descriptive analysis was applied to coded answers. Most farmers were young individuals under 40 years of age, with undergraduate or graduate degrees and having recently started their productive activities, after a family succession process. Herd size varied with an overall average of approximately 100 cows. Oestrus detection and cow's health monitoring were the main reasons given to invest in this technology, and cost was the most important factor that prevented farmers from purchasing ABRS. All farmers in USERS affirmed that they observed the target cows after receiving a health or an oestrus alert. Farmers believed that they were able to intervene in the evolution of the animals' health status, as the alerts gave a window of three to four days before the onset of clinical signs of diseases, anticipating the start of the treatment.The alerts issued by the monitoring systems helped farmers to reduce the number of cows to be observed and to identify pre-clinically sick and oestrous animals more easily. Difficulties in illness detection and lack of definite protocols impaired the decision making process and early treatment, albeit farmers believed ABRS improved the farm's routine and reproductive rates.

Effect of synchronized breeding on genetic evaluations of fertility traits in dairy cattle.

Estrus detection has become more difficult over the years due to decreases in the estrus expression of high-producing dairy cows, and increased herd sizes and animal density. Through the use of hormonal synchronization protocols, also known as timed artificial insemination (TAI) protocols, it is possible to alleviate some of the challenges associated with estrus detection. However, TAI masks cows' fertility performance, resulting in an unfair comparison of treated animals and innately fertile animals. Consequently, genetically inferior and superior cows show similar phenotypes, making it difficult to distinguish between them. As genetic programs rely on the collection of accurate phenotypic data, phenotypes collected on treated animals likely add bias to genetic evaluations. In this study, to assess the effect of TAI, the rank correlation of bulls for a given trait using only TAI records were compared with the same trait using only heat detection records. A total of 270,434 records from 192,539 animals split across heifers, first and second parity cows were analyzed for the traits: calving to first service, first service to conception, and days open. Results showed large reranking across all traits and parities between bulls compared based on either having only TAI records or only heat detection records, suggesting that a bias does indeed exist. Large reranking was also observed for both the heat detection and TAI groups among the top 100 bulls in the control group, which included all records. Furthermore, breeding method was added to the model to assess its effect on bull ranking. However, there were only minor changes in the rank correlations between scenario groups. Therefore, more complex methods to account for the apparent bias created by TAI should be investigated; for this, the method by which these data are collected needs to be improved through creating a standardized way of recording breeding codes. Though the results of this study suggest the presence of bias within current fertility evaluations, additional research is required to confirm the findings of this study, including looking at high-reliability bulls specifically, to determine if the levels of reranking remain. Future studies should also aim to understand the potential genetic differences between the fertility traits split via management technology, possibly in a multiple-trait analysis.

Comparison of pregnancy per AI of heifers inseminated with sex-sorted or conventional semen after oestrus detection or timed artificial insemination.

The objective of the study was to compare the fertility after using sex-sorted or conventional semen either with oestrus detection (EST) or timed artificial insemination (TAI) in Holstein heifers. Holstein heifers were randomly assigned to one of the following treatments in a 2 × 2 factorial design. Heifers in the EST group were inseminated with sex-sorted (n = 114) or conventional semen (n = 100) after spontaneous or induced oestrus. Heifers in the TAI, subjected to the 5-day Cosynch+Progesterone protocol (GnRH+P4 insertion-5d-PGF2α +P4 removal-1d-PGF2α -2d-GnRH+TAI), were inseminated with sex-sorted (n = 113) or conventional semen (n = 88). Statistical analyses were performed using PROC GLIMMIX procedure of SAS 9.4 (SAS Institute Inc., Cary, NC). Overall P/AI was 60.7% for EST and 54.2% for TAI regardless of types of semen and 68.1% for conventional and 48.9% for sex-sorted semen regardless of insemination strategies. Fertility of heifers inseminated with either sex-sorted (53.5%; 44.2%) or conventional (69.0%; 67.0%) semen did not differ between EST and TAI respectively. Besides, the interaction between the semen type and the insemination strategy was not significant for P/AI. The embryonic loss was significantly greater with sex-sorted semen (17.1%) compared to conventional semen (1.6%). There was no sire effect with sex-sorted semen on P/AI (52.6% vs. 46.2%) and embryonic loss (16.4% vs. 18.0%). As expected, sex-sorted semen resulted in more female calves (89.8% vs. 51.6%) than conventional semen. Thus, sex-sorted semen can be used with 5-day Cosynch+Progesterone protocol to eliminate the inadequate oestrus detection and to increase female calves born in dairy heifers.