Factors affecting expression of estrus measured by activity monitors and conception risk of lactating dairy cows

The Influence of Selected Factors on Changes in Locomotion Activity during Estrus in Dairy Cows

The objective of this study was the evaluation of the locomotion activity of heifers and Holstein dairy cows during estrus. We have analyzed the locomotion activity using the Heatime RuminAct device on 180 cows (32 heifers and 148 dairy cows) and we evaluated a total of 633 estrus cycles during the reference period of 3 days before estrus, 3 days after estrus, and on the day ofestrus occurrence. The datawere analyzed using the DataFlowTM II program. The locomotion of cows was expressed in the units of locomotion activity in 24 h (u.24 h-1). During the reference period of 3 days before estrus, the cows showed locomotion activity of 558 u.24 h-1, with an increase in locomotion activity on the day of estrus of 836 u.24 h-1, and, during the reference period of 3 days after estrus, the level of locomotion activity decreased to 537 836 u.24 h-1, which is a similar level of locomotion activity to the reference period before estrus. Through the statistical analysis, we evaluated the impact of parity, lactation stage, milk yield, and individuality on changes in locomotion activity during estrus and throughout the reference period, and we found a significant effect of parity (F = 13.41, p < 0.001) on changes in the locomotion activity of dairy cows during estrus. Based on these results, this research offers fresh perspectives on assessing specific factors affecting the locomotion activity of dairy cows during estrus through the practical application of electronic systems for estrus detection on dairy farms.

Relationship of length of the estrous cycle to antral follicle number in crossbred beef heifers

Length of the menstrual cycle was positively associated with antral follicle number in women. If this pattern is consistent in cattle, a value-added benefit to using automated activity monitors to determine estrous status could be the ability to predict antral follicle count (AFC). We, therefore, hypothesized that as inter-estrous interval increased ultrasonographic AFC would be greater in crossbred beef heifers. Over 3 yr, crossbred beef heifers (n = 1,394) were fitted with automated activity monitors for 81 d. From days 42 to 46, heifers were submitted for ultrasonographic examination to determine AFC. From days 60 to 81, heifers were visually observed twice daily for 45 min for signs of behavioral estrus. Heifers that had a behavioral estrus that coincided with a sensor-based estrus and had a previous sensor-based estrus between 15 and 26 d earlier were used for the analysis (n = 850). A combination of regression analyses and correlation analyses were applied to understand the association between data collected by sensors and follicle number determined by ultrasonographic examination. Antral follicle count was analyzed using the GLM procedure of SAS with estrous cycle length (15 to 26 d) as a fixed effect. Estrus was more likely to initiate in the early morning hours and peak activity was greater (P < 0.0001) when estrus initiated between 0200 and 0800 hours then when estrus initiated at other times of the day. Antral follicle count did not differ due to length of the estrous cycle (P = 0.87). Thus, length of the estrous cycle obtained from three-axis accelerometers cannot be used to predict follicle number in crossbred beef heifers; however, machine learning approaches that combine multiple features could be used to integrate parameters of activity with other relevant environmental and management data to quantify AFC and improve reproductive management in beef cows.

Interval from Oestrus to Ovulation in Dairy Cows-A Key Factor for Insemination Time: A Review

This review describes the oestrus-to-ovulation interval, the possibility of predicting the time of ovulation, and the optimum time for insemination relative to oestrus in dairy cows. The duration of oestrus in dairy cows is approximately 8-20 h, with differences possibly related to the methods of oestrus detection and the frequency of observations. Most cows ovulate approximately 24-33 h after the onset of oestrus and 15-22 h after the end of oestrus. The interval from the preovulatory luteinising hormone (LH) surge to ovulation is approximately 4-30 h. Ovulation occurs when follicle diameter averages 18-20 mm. When it is possible to correctly determine the beginning of oestrus, artificial insemination can be performed utilizing the "a.m.-p.m. rule", and only one insemination may be applied. In cows with too long or too short oestrus-to-ovulation intervals, fertility can be compromised. One important factor that can alter the oestrus-to-ovulation interval is acute or chronic heat stress during the warm season. When there is a risk that insemination may occur too early or too late with respect to the time of ovulation, GnRH administration can be considered.

Association between genomic daughter pregnancy rate and expected milk production on the resumption of estrus behavior in Holstein cattle

The objective of this observational study was to evaluate estrous expression at the first estrus occurring between 7 to 30 d in milk (DIM), as detected by an automated activity monitor (AAM), and its association with genomic daughter pregnancy rate (GDPR) and genomic expected milk production (GEM) in lactating dairy cows. A total of 4,119 lactations from 2,602 Holstein cows were included. Cows were enrolled as first lactation (n = 1,168), second lactation (n = 1,525) and third and greater lactation (n = 1,426). Hair samples were collected from the tail switch, and cows were genotyped using an SNP platform (Clarifide, Zoetis, São Paulo, SP, Brazil). Postpartum cows were examined daily by the farm personnel from calving until 10 DIM. Calving was classified as assisted (forced calf extraction) and unassisted (normal calving). Retained fetal membranes (RFM), hyperketonemia (KET), and left displaced abomasum (LDA) were also recorded. Mean GDPR (± SD) was -0.29 ± 1.4, and the intensity and duration of the first estrus event was 15.9 ± 13.1 x-factor (intensity unit measurement) and 11.1 ± 3.8 h, respectively. Cows that had greater GDPR had greater intensity and longer duration of estrus at the alert, independent of parity. Overall resumption of estrous expression, between 7 to 30 DIM, was 41.2% (1,695/4,119), where 58.8% (2,424/4,119) did not have an estrus event, 31.0% (1,274/4,119) of cows had one event of estrus, and 10.2% (421/4,119) of cows had 2 or more events of estrus early postpartum. Mean DIM (± SD) at first estrus event, detected by the AAM, was 19.4 ± 4.4 d. Days in milk at first event for cows with one event was 20.7 ± 1.6 d and 15.9 ± 3.1 d for cows with 2 or more events of estrus. First lactation cows were more likely to have an estrus event early postpartum when compared with second and third and greater lactation cows (45.2 ± 1.4% [530/1168] vs. 41.6 ± 1.3% [636/1525] vs. 37.2 ± 1.3% [529/1426], respectively). There was an interaction of parity and GDPR on the proportion of cows demonstrating an early postpartum estrus. There was no difference in the proportion of cows with an early postpartum estrus between those with assisted or unassisted calving, RFM, or LDA. However, cows that had KET were less likely to have an alert early postpartum when compared with cows that did not have KET. Mean genomic expected milk production (± SD) was 256.8 ± 600.1 kg. There was no interaction between GEM and parity on estrous expression (i.e., intensity and duration). There was no interaction between GEM and GDPR on the proportion of estrus early postpartum.

The role of the oviduct environment in embryo survival

CONTEXT

Declining fertility is an issue in multiple mammalian species. As the site of fertilisation and early embryo development, the oviduct plays a critical role in embryo survival, yet there is a paucity of information on how the oviduct regulates this process.

AIMS

We hypothesised that differences in steroid hormone signalling and/or immune function would be observed in a model of poor embryo survival, the peripubertal ewe.

METHODS

We examined expression of steroid hormones in systemic circulation, oviductal expression of oestrogen receptorαand genes important in steroid hormone signalling, and immune function in pregnant and cyclic peripubertal and adult ewes on day 3 after oestrus.

KEY RESULTS

Concentrations of progesterone, but not oestradiol, were decreased in the peripubertal ewe compared to the adult ewe. Oestrogen receptorαprotein expression was increased in the peripubertal ewe, but pathway analysis of gene expression revealed downregulation of the oestrogen signalling pathway compared to the adult ewe. Differential expression of several genes involved in immune function between the peripubertal and adult ewe was consistent with an unfavourable oviductal environment in the peripubertal ewe lamb. Oestradiol concentration was positively correlated with the expression of multiple genes involved in the regulation of immune function.

CONCLUSIONS

Differences in the immune environment of the oviduct, potentially linked to differential modulation by steroid hormones, may partially underly the poor fertilisation and early embryo survival observed in the peripubertal ewe.

IMPLICATIONS

A unfavourable oviductal environment may play an important role in limiting reproductive success.

Analyzing Cattle Activity Patterns with Ear Tag Accelerometer Data

In this study, we equip two breeds of cattle located in tropical and temperate climates with smart ear tags containing triaxial accelerometers to measure their activity levels across different time periods. We produce activity profiles when measured by each of four statistical features, the mean, median, standard deviation, and median absolute deviation of the Euclidean norm of either unfiltered or high-pass-filtered accelerometer readings over five-minute windows. We then aggregate the values from the 5 min windows into hourly or daily (24 h) totals to produce activity profiles for animals kept in each of the test environments. To gain a better understanding of the variation between the peak and nadir activity levels within a 24 h period, we divide each day into multiple equal-length intervals, which can range from 2 to 96 intervals. We then calculate a statistical measure, called daily differential activity (DDA), by computing the differences in feature values for each interval pair. Our findings demonstrate that patterns within the activity profile are more clearly visualised from readings that have been subject to high-pass filtering and that the median of the acceleration vector norm is the most reliable feature for characterising activity and calculating the DDA measure. The underlying causes for these differences remain elusive and is likely attributable to environmental factors, cattle breeds, or management practices. Activity profiles produced from the standard deviation (a feature routinely applied to the quantification of activity level) showed less uniformity between animals and larger variation in values overall. Assessing activity using ear tag accelerometers holds promise for monitoring animal health and welfare. However, optimal results may only be attainable when true diurnal patterns are detected and accounted for.

Magnitude and persistence of higher estrus-associated temperatures in beef heifers and suckled cows

Higher estrus-associated temperatures (HEAT) are a hallmark feature in sexually active females. The overarching aim of this study was to characterize the variability, magnitude, and persistence of HEAT in heifers and suckled beef cows as well as identify associated factors when occurring during thermoneutral conditions at the onset of the spring breeding season. In both heifers and cows, estrus was induced using a 7-d controlled internal drug release (CIDR)-PGF2α protocol. Vaginal temperature after prostaglandin F2α administration was recorded every 5 min using a Thermochron iButton affixed to a blank CIDR (containing no progesterone). Estrus was defined as when a heifer first stood to be mounted or when a cow had an Estrotect patch score of 3 or 4. Level of HEAT varied among individual animals. When comparing common HEAT variables using a mixed model with date nested within a year, maximum HEAT (39.9 ± 0.1 and 40.0 ± 0.1 °C) and duration (15.5 ± 0.8 and 15.4 ± 0.7) were similar in heifers and cows, respectively. However, the magnitude and persistence of HEAT differed. Total area under the HEAT curve was 117.1 ± 13.5 and 158.7 ± 12.3 for heifers vs cows, respectively (P = 0.0571). Further, 42.9% of heifers and 49% of cows had maximum HEAT ≥ 40 °C which persisted up to 6.5 and 10 h, respectively. When ambient conditions were predominantly thermoneutral, temperature humidity index had minimal impact on HEAT (mixed model, repeated measures over time). Toward identifying associated factors with different aspects of HEAT using best fit hierarchical linear regression models, baseline vaginal temperature and baseline duration were the most highly associated independent variables. Follicle size, estradiol and progesterone levels, and other available animal-related variables (e.g., age, weight, hair coat score) explained only a small amount of variation in HEAT. In summary, level of HEAT varies in estrus females even under thermoneutral conditions. Because HEAT can persist for an extended time, direct effects on fertility important components are unavoidable. Whether HEAT is a good or bad component of the periovulatory microenvironment is the basis of ongoing and future studies.

Reduced period from follicular wave emergence to luteolysis generated greater steroidogenic follicles and estrus intensity in dairy cows

The onset of productive life in dairy cattle, concomitant to parturition, is accompanied by a substantial decrease in fertility in comparison with non-lactating, nulliparous heifers. Follicular growth patterns differ between parous and nulliparous dairy cattle. Nulliparous heifers ovulate follicles with reduced antral age (RAA). This study aimed to exogenously reduce ovulatory follicle age in lactating dairy cows from 7 to 5 days old. Cows (n = 80) had their estrous cycles synchronized with the Double-Ovsynch program. At the final portion of this program, luteolysis was induced at either 5 (RAA) or 7 (Control) days following follicular wave emergence. RAA outcomes were estimated in comparison with Controls. RAA resulted in smaller follicles 2 days post-treatment. Despite lower serum concentrations of 17β-estradiol before treatment compared with Controls, the rate of increase in this hormone was greater for the RAA treatment. There was no difference in luteolysis rates between treatments. Proestrus (luteolysis onset to estrus onset) was prolonged in RAA cows. Cows with RAA had more intense estruses. Collectively, these results indicate that decreasing the age of the ovulatory follicle may improve the steroidogenic capacity of the dominant follicle and estrus expression intensity in lactating dairy cows.

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 β-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.

The effect of progesterone concentrations during superovulation of Holstein heifers in a randomized trial

The aim of this study was to evaluate the effect of different progesterone (P4) concentrations during the follicular growth on the intensity of estrous expression, ovarian response to the superovulatory treatment, and embryo production and quality in superovulated heifers. A total of 63 Holstein heifers were randomly assigned into 2 experimental groups: Low P4 (n = 31) and High P4 (n = 32). Animals received a pre-synchronization protocol followed by a protocol of superovulation that included the allocated P4 treatment. Activity was monitored continuously by an automated activity monitor, and estrus characteristics (maximum intensity and duration) were recorded. Embryo collection was performed 7 d post artificial insemination (AI). Embryos were counted and graded from good or excellent (1) to degenerated (4). The outcomes of interest were: number and diameter of follicles at the time of AI, ovulation success (confirmed 7 d post-AI), time to estrus event, maximum intensity and duration of estrus, number and quality of embryos. Data were analyzed according to the type of outcome variable using logistic, linear, or Poisson regression models. A total of 105 embryos (High P4: n = 42; Low P4: n = 63) were graded for quality. Different P4 levels did not affect the maximum intensity (High P4 = 497.8 ± 23.9%; Low P4 = 542.2 ± 23.5%) or the duration (High P4 = 13.5 ± 1.5 h; Low P4 = 14.3 ± 1.4 h) of estrus. Heifers in the High P4 treatment had greater number of follicles at time of AI (High P4 = 16.6 ± 1.6 follicles; Low P4 = 13.9 ± 1.2 follicles), but with smaller diameter (High P4 = 11.3 ± 0.1 mm; Low P4 = 12.0 ± 0.1 mm) compared with Low P4. High P4 heifers tended to have better embryo quality compared with Low P4 heifers (odds ratio = 1.98; 95% CI = 0.90-4.35). High P4 heifers had less embryos than Low P4 heifers, but this was modified by the CIDR (intravaginal implant of P4) removal to estrus interval (interval 0-21 h: mean ratio = 1.15, 95% CI = 0.42-1.87; interval 22-46 h: mean ratio = 0.58, 95% CI = 0.27-0.96). Although estrous expression was not associated with embryo quality, as the duration and the maximum intensity of estrous expression increased, the number of embryos recovered 7 d post-AI increased (duration: mean ratio = 1.04; 95% CI = 1.03-1.05; maximum intensity: mean ratio = 1.50; 95% CI = 1.42-1.58). In conclusion, P4 during the follicular growth, and intensity of estrus, are playing a role in regulating the quality and the number of embryos produced by superovulated heifers. This study was supported by contributions from Resilient Dairy Genome Project and the Natural Sciences and Engineering Research Council.

Intensity of estrus expression - valuable obvious determinant of fertility in Bos indicus cows

This study aimed to characterize estrus response and to establish relationships between intensity of estrus, preovulatory follicle (POF) size and estradiol (E2) concentrations on day of AI, luteal profiles and pregnancy outcome in lactating Hariana breed of cows. 200 cyclic cows were subjected to Ovsynch (n = 54) and Pre-OV treatment (n = 146). Ovsynch: Buserelin acetate (BA; 10 µg), Cloprostenol (500 µg) and BA (10 µg) were injected i.m. on day 0, 7 and 9, respectively, irrespective of treatment. Pre-OV: BA (10 µg) and Cloprostenol (500 µg) was also injected i.m. simultaneously 7 days prior to initiate Ovsynch. On the basis of estrus behavior, the cows were classified into three groups: weak, moderate and intense. Artificial insemination performed at 18-24 hours after 2nd BA of Ovsynch in both treatments. The average duration of estrus did not differ (p > 0.05) between Ovsynch and Pre-OV treatment. A positive correlation was observed between estrus response and POF size, concentration of E2 on day of AI and luteal profiles on day 12 post-AI. First service conception rate was higher in cows exhibited intense (45.46%) and moderate (42.56%) estrus response than weak (28.57%) estrus response. In conclusion, intensity of estrus expression could be considered as important determinant for deciding pregnancy outcomes in Bos indicus cows.

Timing of Artificial Insemination Using Sexed or Conventional Semen Based on Automated Activity Monitoring of Estrus in Holstein Heifers

Investigations on the optimum timing of artificial insemination (AI) following automated activity monitoring (AAM) depending on different types of semen in heifers are limited and in part show controversial results. Therefore, the objective of this observational study was to determine the association between the timing of AI using different characteristics of estrus (i.e., the onset, peak, and end of estrus) and pregnancy per AI (P/AI) in Holstein heifers. Heifers were fitted with a neck-mounted AAM system and inseminated with frozen conventional and sexed semen. The pregnancy per AI (n = 4159) from 2858 heifers from six commercial dairy farms in Germany inseminated upon the alert of an AAM system was evaluated. Estrous intensity was classified based on peak activity into low (35 to 89 index value) and high (90 to 100 index value). We detected a quadratic association between the interval from the onset of estrus to AI and P/AI (p = 0.02). The greatest P/AI was observed for heifers inseminated from 9 to 32 h after the onset of estrus. The intervals from the peak of activity to AI and the end of estrus to AI were not associated with P/AI (p ≥ 0.05). Heifers inseminated with frozen conventional semen (50.1%) had a greater P/AI compared with heifers inseminated with frozen sexed semen (43.3%; p = 0.03). There were no interactions between the intervals from the onset, peak, or end of estrus to AI or the type of semen and the P/AI (p ≥ 0.05). The pregnancy per AI was not associated with estrous intensity (50.5% for low intensity vs. 53.0% for high intensity; p = 0.37). In conclusion, inseminating heifers between 9 and 32 h after the onset of estrus, as detected by the AAM, optimized the P/AI regardless of semen type.

Applications of livestock monitoring devices and machine learning algorithms in animal production and reproduction: an overview

Some sectors of animal production and reproduction have shown great technological advances due to the development of research areas such as Precision Livestock Farming (PLF). PLF is an innovative approach that allows animals to be monitored, through the adoption of cutting-edge technologies that continuously collect real-time data by combining the use of sensors with advanced algorithms to provide decision tools for farmers. Artificial Intelligence (AI) is a field that merges computer science and large datasets to create expert systems that are able to generate predictions and classifications similarly to human intelligence. In a simplified manner, Machine Learning (ML) is a branch of AI, and can be considered as a broader field that encompasses Deep Learning (DL, a Neural Network formed by at least three layers), generating a hierarchy of subsets formed by AI, ML and DL, respectively. Both ML and DL provide innovative methods for analyzing data, especially beneficial for large datasets commonly found in livestock-related activities. These approaches enable the extraction of valuable insights to address issues related to behavior, health, reproduction, production, and the environment, facilitating informed decision-making. In order to create the referred technologies, studies generally go through five steps involving data processing: acquisition, transferring, storage, analysis and delivery of results. Although the data collection and analysis steps are usually thoroughly reported by the scientific community, a good execution of each step is essential to achieve good and credible results, which impacts the degree of acceptance of the proposed technologies in real life practical circumstances. In this context, the present work aims to describe an overview of the current implementations of ML/DL in livestock reproduction and production, as well to identify potential challenges and critical points in each of the five steps mentioned, which can affect results and application of AI techniques by farmers in practical situations.

Precision technologies for the management of reproduction in dairy cows

Precision livestock farming (PLF) utilizes information and communication technology (ICT) to continuously monitor, control, and enhance the productivity, reproduction, health, welfare, and environmental impact of livestock. Technological advancements have facilitated the seamless flow of information from animals to humans, enabling practical decision-making processes concerning health, reproduction management, and calving surveillance. With the increasing population of livestock per farm, it has become impractical for farmers to individually track every animal within these large groups. Historically, cattle management decisions heavily relied on human observation, judgment, and experience. However, it is impossible for a single individual to gather reliable audio-visual monitoring data round the clock. Presently, dairy cows exhibit subtler indicators of estrus, resulting in a substantial chance of missing an estrus cycle. Furthermore, calving complications sometimes go unnoticed on farms, resulting in a higher number of culled cattle. In addition, an increasing number of crossbred cows experience delayed return to estrus after calving due to low body condition scores (BCS). The decline in BCS during the dry period is associated with a reduced likelihood of pregnancy following the first and second postpartum inseminations. Precision technologies enable the monitoring and tracking of an individual cow's physiological behavior and reproductive parameters, thereby optimizing management practices and farm performance. Despite the exploration of various technologies, there are still some common challenges that need to be addressed, including battery lifespan, transmission range, specificity and sensitivity, storage capacity, and economic affordability. Nonetheless, the demand for these tools from farmers and researchers is growing, and the implementation of PLF in grazing systems can yield positive outcomes in terms of animal reproductive welfare and labor optimization. This review primarily focuses on the different aspects of reproduction management in dairy using sensors, automated cameras, and various computer software.

Peri-estrus activity and mounting behavior and its application to estrus detection in Hanwoo (Korea Native Cattle)

This study was conducted to investigate the change in activity and mounting behavior in Hanwoo (Korean Native Cattle) during the peri-estrus period and its application to estrus detection. A total of 20 Hanwoo cows were fitted with a neck-collar accelerometer device, which measured the location and acceleration of cow movements and recorded the number of instances of mounting behavior by the altitude data. The data were analyzed in three periods (24-, 6-, and 2-h periods). Blood samples were collected for 5 days after the prostaglandin F2α (PGF2α) injection, and the concentrations of estradiol, progesterone, follicle-stimulating hormone, and luteinizing hormone were determined by enzyme-linked immunosorbent assays. Activity and mounting behavior recorded over 2-h periods significantly increased as estrus approached and were more efficient at detecting estrus than over 24- and 6-h periods (p < 0.05). Endocrine patterns did not differ with the variation of individual cows during the peri-estrus period (p > 0.05). Activity was selected as the best predictor through stepwise discriminant analysis. However, activity alone is not enough to detect estrus. We suggest that a combination of activity and mounting behavior may improve estrus detection efficiency in Hanwoo. Further research is necessary to validate the findings on a larger sample size.

Association of activity and subsequent fertility of dairy cows after spontaneous estrus or timed artificial insemination

The objective of this observational study was to evaluate the association between increased physical activity at first artificial insemination (AI) and subsequent pregnancy per AI (P/AI) in lactating Holstein cows following spontaneous estrus or a timed AI (TAI) protocol. We also wanted to identify factors associated with the intensity of activity increase (PA) captured by automated activity monitors (AAM) and fertility. Two experiments were conducted, in which cows either were inseminated based on the alert of the AAM system (AAM cows) or received TAI following a 7-d Ovsynch protocol (TAI cows) if not inseminated within a farm-specific period after calving. Experiment 1 included 2,698 AI services from AAM cows and 1,042 AI services from TAI cows equipped with the Smarttag Neck (Nedap Livestock Management) from a dairy farm in Slovakia (farm 1). In the second experiment, 6,517 AI services from AAM cows and 1,226 AI services from TAI cows fitted with Heatime (Heatime Pro; SCR Engineers Ltd.) from 8 dairy farms in Germany (farms 2-9) were included. Pregnancy diagnosis was performed on a weekly basis by transrectal ultrasound (farms 1, 3, 7, 8) or by transrectal palpation (farms 2, 4-6, 9). Estrous intensity was represented by the peak value of the change in activity. In experiment 1, PA was categorized into low (x-factor 0-20) and high (x-factor 21-100) PA, and in experiment 2 into low (activity change = 35-89) and high (activity change = 90-100) PA. In TAI cows from both experiments, PA was additionally categorized into cows with no AAM alert. Data were analyzed separately for AAM and TAI cows using multinomial logistic regression models for PA in TAI cows and logistic regression models for PA in AAM cows and P/AI in both groups. In experiment 1, P/AI of AAM cows was greater for AI services performed with conventional frozen semen (57.6%) compared with sexed semen (47.2%), whereas type of semen only tended to be associated with P/AI in TAI cows (54.4% conventional frozen semen vs. 48.9% sexed semen). In experiment 2, P/AI was greater for fresh semen (AAM cows: 44.4% vs. TAI cows: 44.2%) compared with conventional frozen semen (AAM cows: 37.6% vs. TAI cows: 34.6%). In both experiments, pregnancy outcomes were associated with PA. In experiment 1, AAM cows with high PA (55.1%) had greater P/AI than cows with low PA (49.8%). Within TAI cows, cows with no alert (38.8%) had reduced P/AI compared with cows with low (54.2%) or high PA (61.8%). In experiment 2, AAM cows with high PA (45.8%) had greater P/AI compared with cows with low PA (36.4%). Timed AI cows with no alert (27.4%) had decreased P/AI compared with cows with low (41.1%) or high (50.8%) PA. The greatest risk factors for high PA were parity (experiment 1) and season of AI (except for TAI cows from experiment 1). We conclude that high PA at the time of AI is associated with greater odds of pregnancy for both AAM and TAI cows. In both experiments, about 2 thirds of AAM cows (experiment 1: 69.9% and experiment 2: 70.7%) reached high PA, whereas only approximately one-third or less of TAI cows (experiment 1: 37.3% and experiment 2: 23.6%) showed high PA. Although we observed similar results using 2 different AAM systems for the most part, risk factors for high PA might differ between farms and insemination type (i.e., AAM vs. TAI).

Effects of additional gonadotropin-releasing hormone and prostaglandin F2α treatment to an estradiol/progesterone-based embryo transfer protocol for recipient lactating dairy cows

This study was designed to evaluate whether the utilization of a second PGF_2α treatment at the end of an estradiol/progesterone (E2/P4)-based protocol with or without GnRH at the beginning of the protocol would improve pregnancy rates of lactating Holstein cows assigned to timed embryo transfer. A total of 501 lactating Holstein cows in 5 farms were enrolled in the experiment. Within farm, cows were blocked by parity and, within block, were assigned randomly to (1) insertion of an intravaginal P4 device (controlled internal drug-releasing device; CIDR) and estradiol benzoate on d -11, PGF_2α on d -4, CIDR withdrawal and an injection of estradiol cypionate on d -2, and timed embryo transfer on d 7 (1-PGF; n = 164); (2) the same treatments as 1-PGF, but with PGF_2α administered on d -4 and -2 (2-PGF; n = 171); and (3) 2-PGF with the addition of a GnRH treatment on d -11 (GnRH⁺2-PGF; n = 166). Ovaries were scanned by transrectal ultrasonography on d -11, -4, and 7, and blood samples were collected on d -11, -4, 0, and 7 for P4 determination. Treatment comparisons were performed using contrasts. The proportion of cows with a new corpus luteum on d -4 was greater in GnRH⁺2-PGF cows. Cows in 1-PGF had a greater P4 concentration on d 0 but lesser P4 on d 7 compared with cows in the other groups. Cows assigned to receive 2-PGF (2-PGF and GnRH⁺2-PGF) had greater estrus expression, and a greater proportion of cows ovulated to estradiol cypionate. No further contrast effects were observed for follicle diameter, double ovulation rate, pregnancy per embryo transfer (P/ET) on d 32 and 60, or pregnancy loss. As P4 concentration on d -4 increased, P/ET on d 60 tended to increase. Cows with P4 ≥3.66 ng/mL on d -4 had greater P/ET on d 32 and 60 than those with P4 below that threshold. Regardless of treatment, cows with P4 concentration ≥3.66 ng/mL also had a greater pregnancy per synchronized protocol (P/SP) on d 60. Also, a P4 concentration on d -4 (low or high) × follicle diameter (continuous) interaction tendency was observed when evaluating P/ET. Although P/ET did not differ among cows with different follicles sizes with reduced P4 concentration on d -4 (<3.66 ng/mL), it increased in cows with larger follicles exposed to increased P4 concentration (≥3.66 ng/mL). When P4 on d 0 was evaluated, P/ET on d 32 and 60 was greater for cows with low (≤0.09 ng/mL) versus high (>0.21 ng/mL) P4; as P4 concentration on d 0 increased, P/ET linearly decreased. In summary, cows with increased P4 concentrations during growth of the ovulatory follicular wave had improved P/ET. Administering a second PGF_2α dose reduced P4 concentration on d 0 and increased ovulatory response to the protocol, but no benefits were observed on P/ET or P/SP.

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.

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.

Symposium review: Use of multiple biological, management, and performance data for the design of targeted reproductive management strategies for dairy cows

As the reproductive efficiency of dairy cattle continues to improve in response to better management and use of technology, novel reproductive management approaches will be required to improve herd performance, profitability, and sustainability. A potential approach currently being explored is targeted reproductive management. This approach consists of identifying cows with different reproductive and performance potential using multiple traditional and novel sources of biological, management, and performance data. Once subgroups of cows that share biological and performance features are identified, reproductive management strategies specifically designed to optimize cow performance, herd profitability, or alternative outcomes of interest are implemented on different subgroups of cows. Tailoring reproductive management to subgroups of cows is expected to generate greater gains in outcomes of interest than if the whole herd is under similar management. Major steps in the development and implementation of targeted reproductive management programs for dairy cattle include identification and validation of robust predictors of reproductive outcomes and cow performance, and the development and on-farm evaluation of reproductive management strategies for optimizing outcomes of interest for subgroups of cows. Predictors of cow performance currently explored for use in targeted management include genomic predictions; behavioral, physiological, and performance parameters monitored by sensor technologies; and individual cow and herd performance records. Once the most valuable predictive sources of variation are identified and their effects quantified, novel analytic methods (e.g., machine learning) for prediction will likely be required. These tools must identify groups of cows for targeted management in real time and with no human input. Despite some encouraging research evidence supporting the development of targeted reproductive management strategies, extensive work is required before widespread implementation by commercial farms.

Application of PGF2α at the moment of fixed-time artificial insemination in crossbred beef cows

Although studies have shown positive effects of gonadotropin releasing hormone (GnRH) or prostaglandin F_2α (PGF_2α) at the moment of fixed-time artificial insemination (FTAI) in the conception rate (CR) of cattle, its effects on treatments based on progesterone (P4) and estradiol benzoate (EB) is still not conclusive. The objective of this study was (1) to evaluate the effect of a PGF_2α analogue at FTAI in the CR of crossbred beef cows submitted to a 11d FTAI protocol based on P4 and EB; and (2) to describe the CR between PGF_2α-treated and control cows in different body condition scores (BCS) and parity categories. Crossbred (½ Nellore and ½ Angus) beef cows were submitted to a synchronization protocol and randomly assigned into 2 groups: Control (n = 163), at FTAI cows received 2 mL of saline solution as a placebo, and PGF_2α (n = 163), at FTAI cows were treated with PGF_2α analogue (10 mg of dinoprost tromethamine). Pregnancy diagnosis was performed 33d post-FTAI. Binary logistic regression model was used to analyze the effect of PGF_2α treatment on CR. There was no difference in CR between PGF_2α and control groups (P > 0.05; odds ratio (OR) = 0.92; confidence interval (CI) = 0.59-1.4). A greater CR was found in heifers (P = 0.0006, OR = 2.65, CI = 1.61 - 4.38) and multiparous (P = 0.0006, OR = 2.12, CI = 1.04 - 4.3) when compared to primiparous cows. Cows with low BCS (4; 9-point scale) showed lower CR when compared with moderate BCS (5-6; 9-point scale) (P < 0.05; OR = 0.10; CI = 0.06 - 0.18). There was no numerical difference on CR between PGF_2α-treated and control cows in different BCS and parity categories. The results suggested that the CR in this study was not influenced by 10 mg PGF_2α analogue at FTAI.

Impact of GnRH administration at the time of artificial insemination on conception risk and its association with estrous expression

Cows with reduced estrous expression have compromised fertility. The aim of this study was to determine whether the administration of GnRH at the time of artificial insemination (AI) would affect ovulation rates and the fertility of animals expressing estrous behavior of lesser intensity. Cows were enrolled at the time of estrus from 3 farms (n = 2,607 estrus events; farm A: 1,507, farm B: 429, farm C: 671) and randomly assigned to receive GnRH at AI or not (control). The intensity of estrous expression, monitored through leg-mounted activity monitors, was determined using the maximum activity during estrus; estrous expression was categorized as greater or lower relative to the farm median. On farm A, cows were assessed at alert, and 24 h, 48 h, and 7 d post-alert for ovulation using ultrasonography. Pregnancy per AI was confirmed at 35 ± 7 d post-estrus for cows that were inseminated. Differences between treatments were tested using the GLIMMIX procedure of SAS. Treatment with GnRH at the time of AI increased pregnancy per AI (41.3 ± 1.6 vs. 35.7 ± 1.7%). An interaction between treatment and estrous expression on pregnancy per AI was found. Control cows with greater estrous expression had greater pregnancy per AI than those with lesser expression, whereas GnRH administration increased pregnancy per AI for cows with lesser estrous expression but not those with greater expression (GnRH, greater intensity: 43.5 ± 2.1; GnRH, lesser intensity: 37.8 ± 2.2; control, greater intensity: 42.6 ± 2.2; control, lesser intensity: 31.0 ± 2.2%). A higher proportion of cows with greater estrous expression that were administered GnRH at AI were found to ovulate by 48 h and 7 d post-estrus; however, ovulation of cows with lesser estrous expression was unaffected by GnRH administration. In conclusion, fertility of cows with reduced estrous expression may be increased using GnRH at the time of AI; however, increased ovulation rates do not seem to be the direct mechanism behind this relationship.

Estrous activity in lactating cows with divergent genetic merit for fertility traits

This observational study aimed to determine the effect of genetic merit for fertility traits on estrous expression and estrous cycle duration in grazing dairy cows, as measured by an activity monitoring device. A secondary aim was to describe changes in expression of estrus that occur during successive estrous cycles postpartum. Neck-mounted, activity-monitoring devices (Heatime, SCR Engineers Ltd.) were fitted to nulliparous Holstein-Friesian heifers with positive (POS FertBV) or negative genetic merit for fertility traits (NEG FertBV) to capture activity data during their first and second lactations (POS FertBV: n = 242, n = 188; NEG FertBV: n = 159, n = 87 in lactation 1 and 2, respectively). An estrous event was identified when the activity change index exceeded 26 activity units (AU) for 4 h. A total of 1,254 and 892 estrous events were identified in lactation 1 and 2, respectively. Estrous duration was defined as the interval between when the threshold was first exceeded and when activity dropped below the threshold, with no new event starting within 24 h of the end of the previous event. This definition of estrus included cows in which activity crossed the threshold multiple times in a day and were classified as a single estrous event. A second measure, high activity duration, was defined as the total hours that activity exceeded the threshold. To characterize estrous activity, peak activity (above baseline) and total activity (area under the curve of activity above baseline) were measured. Compared with NEG FertBV cows, POS FertBV cows had more active, longer estrous events. In lactation 1, the POS FertBV group had a mean estrous duration and a high activity duration of 12.5 and 12.4 h compared with 11.4 and 11.3 h for the NEG FertBV group [standard error of the difference (SED) = 0.5 and 0.4 h, respectively]. This significant difference also occurred in lactation 2, with a mean estrous duration of 13.1 versus 11.8 h (SED = 0.5 h) and a high activity duration of 13.0 versus 11.8 h (SED = 0.4 h) in the POS and NEG FertBV groups, respectively. Total activity and peak activity were greater in the POS compared with the NEG FertBV group in lactation 1 (peak activity: 65.5 vs. 55.8 AU, SED = 2.4 AU; total activity: 588 vs. 494 AU, SED = 25 AU) and lactation 2 (peak activity: 72.5 vs. 61.2 AU, SED = 2.9 AU; total activity: 648 vs. 541 AU, SED = 30 AU). Estrous cycle duration did not differ between the POS and NEG FertBV groups (lactation 1: 20.4 vs. 20.6 d, SED = 0.25; lactation 2: 20.8 vs. 21.0 d, SED = 0.28). Less estrous activity of the cow was associated with the first postpartum estrus. In contrast, the number of previous estrous events did not consistently affect the duration of the subsequent estrous cycle. The outcomes of this study provide evidence that positive genetic merit for fertility traits is associated with more overt estrous expression. Selection for these traits may improve estrous expression and thus estrous detection in commercial herds.

Effect of GnRH 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.

Occurrence and greater intensity of estrus in recipient lactating dairy cows improve pregnancy per embryo transfer

The aim of this study was to determine the association between occurrence and intensity of estrous expression with pregnancy success in recipient lactating dairy cows subjected to embryo transfer (ET). Two observational studies were conducted. Holstein cows were synchronized using the same timed ET protocol, based on estradiol and progesterone in both experiments. At 9 d after the end of the timed ET protocol only animals that had ovulated were implanted with a 7-d embryo [experiment 1 (Exp. 1); n = 1,401 ET events from 1,045 cows, and experiment 2 (Exp. 2); n = 1,147 ET events from 657 cows]. Embryos were produced in vivo (Exp. 1 and Exp. 2) and in vitro (only Exp. 2), then transferred to recipient cows as fresh or frozen-thawed. Pregnancy was confirmed at 29 and 58 d after the end of timed ET protocol. In Exp. 1, animals had their estrous expression monitored through a tail chalk applied on the tail head of the cows and evaluated daily for chalk removal (no estrus: 100% of chalk remaining; estrus: <50% of chalk remaining). In Exp. 2, cows were continuously monitored by a leg-mounted automated activity monitor. Estrous expression was quantified using the relative increase in physical activity at estrus in relation to the days before estrus. Estrous expression was classified as no estrus [<100% relative increase in activity (RI)], weak intensity (100-299% RI), and strong intensity (≥300% RI). Data were analyzed by analysis of variance using mixed linear regression models (GLIMMIX) in SAS (SAS Institute Inc.). A total of 65.2% (914/1,401) and 89.2% (1,019/1,142) of cows from Exp. 1 and Exp. 2, respectively, displayed estrus at the end of the ovulation synchronization protocol. In Exp. 1, cows expressing estrus before to ET had greater pregnancy per ET than those that did not [41.0 ± 2.3% (381/914) vs. 31.5 ± 2.9% (151/487), respectively]. Similarly, in Exp. 2, cows classified in the strong intensity group had greater pregnancy per ET compared with cows in the weak intensity and no estrus groups [41.3 ± 2.2% (213/571) vs. 32.7 ± 2.7% (115/353) vs. 11.3 ± 3.5% (26/218), respectively]. There was no effect of ET type on pregnancy per ET in Exp. 1. However, in Exp. 2, cows that received an in vivo-produced embryo, either fresh or frozen, had greater pregnancy per ET compared with cows that received in vitro-produced embryo. Cows receiving embryos in the early blastocyst and blastocyst stage had greater fertility compared with cows receiving embryos in the morula stage. There was an interaction between the occurrence of estrus and the stage of embryo development on pregnancy per ET, cows which displayed estrus and received a morula or early blastocyst had greater pregnancy per ET than cows that did not display estrus. In conclusion, the occurrence and the intensity of estrous expression improved pregnancy per ET in recipient lactating dairy cows and thus could be used as a tool to assist in the decision making of reproduction strategies in dairy farms.

Comparison of 5 Versus 7-Day Ovsynch + Progesterone Releasing Intravaginal Device Protocols (PRID) and a Modified G7G with an Option of Heat Detection Protocol for 1st Service in Lactating Dairy Cows

The aim of this study was to evaluate the efficacy of two timed-AI (TAI) protocols (Group G5D, GnRH and PRID -5d- PGF2a -1d- PGF2a -1d- GnRH, n = 105 and Group G7D, GnRH and PRID-7d- PGF2a -1d- PGF2a -1d- GnRH, n = 98) and a modified G7G protocol combining heat detection (HD) and AI or TAI if HD failed (Group HD, GnRH and PRID -7d- PGF2a -1d- PGF2a -5d- HD or 5d TAI if no HD, n = 92). Pregnancy per AI (P/AI) did not differ between G5D and G7D protocol (G5D: 33.8% vs. G7D: 35.2%, P = 0.85). Cows assigned to G5D and G7D group were pooled as TAI group (GTAI) and further compared to GHD. Within the GHD, more primiparous cows exhibited estrous signs compared to multiparous cows (70.4% vs. 46.2%, P = 0.03). Furthermore, 49 cows (53.3%) were served after HD, whereas 43 cows (46.7%) were served after TAI. There was no difference in P/AI between cows served after HD (51.6%) or after TAI (43.0%, P = 0.49). GHD showed higher P/AI at 1st service compared to GTAI (49.1% vs. 36.4%, P = 0.04), whilst, median days to pregnancy did not differ between the two groups. Overall, P/AI of primiparous cows tended to be better in comparison with multiparous cows (48.3% vs. 37.2%, P = 0.06). In conclusion, there was no significant difference regarding the efficacy of 5- and 7-day Ovsynch + PRID protocols. Moreover, a modified G7G protocol, with intermediate heat detection, resulted in overall better P/AI compared to TAI protocols and appears as a promising strategy to optimize estrus detection for 1st AI.

Effects of GnRH and hCG administration during early luteal phase on estrous cycle length, expression of estrus and fertility in lactating dairy cows

Our objective was to determine the effects of a single treatment of human chorionic gonadotropin (hCG) or GnRH from d 5 to 7 of the estrous cycle on cycle length, expression of estrus and fertility in lactating dairy cows. Lactating Holstein cows (n = 354) located in Farm 1 and lactating Jersey cows located in Farm 2 (n = 210) detected in estrus by an Automated Activity Monitor (AAM) system from 27 to 50 days in milk (DIM) were randomly assigned to receive one of three treatments from d 5 to 7 of the estrous cycle: control (untreated; CON; Holstein, n = 111; Jersey, n = 66), GnRH (86 μg gonadorelin acetate im; Holstein, n = 116; Jersey, n = 75), or hCG (3,300 IU im; Holstein, n = 127; Jersey, n = 69). Ovaries were scanned with ultrasound in a random subgroup of cows (Holstein/Farm 1, n = 147; Jersey/Farm 2, n = 94) on the day of treatment and 3 or 4 d later to determine ovulation. Estrus was detected after treatment by an AAM, and peak activity and heat index were recorded. A random subgroup of cows observed in estrus after treatment received first AI from 51 to 80 DIM (Holstein, n = 208; Jersey, n = 138). Pregnancy diagnoses were performed by transrectal ultrasonography at 37 ± 3 d post-AI. Holstein and Jersey cows treated with GnRH and hCG had an increased (P < 0.05) ovulatory response compared with controls. Human chorionic gonadotropin decreased (74%; P = 0.05) and GnRH tended to reduce (75%; P = 0.07) the proportion of multiparous Holstein cows returning to estrus compared with CON (86%). Cows treated with hCG had a longer (P < 0.01) estrous cycle length (24.6 ± 0.3 d, Holstein; 23.0 ± 0.3 d, Jersey) compared with CON cows (22.7 ± 0.3 d, Holstein; 21.3 ± 0.3 d Jersey) and GnRH (22.9 ± 0.3 d, Holstein; 21.1 ± 0.3 d Jersey). The percentage of cows with high (≥80) peak activity and heat index did not differ (P > 0.50) between treatments, and milk production did not affect (P > 0.65) the duration of estrus. Pregnancy per AI (P/AI) was not affected by treatments in Holstein (P = 0.93; CON: 34.3%, GnRH: 35.4%, and hCG: 31.5%) and in multiparous Jersey cows (P = 0.35; CON: 34.3%, GnRH: 35.4%, and hCG: 31.5%), but hCG had greater (P = 0.03; 55%) P/AI than GnRH (30.0%) and a trend (P = 0.06) for greater P/AI than CON (33.3%) in primiparous Jersey cows. In summary, inducing the formation of an accessory corpus luteum from d 5 to 7 of the estrous cycle with hCG reduced expression of estrus in multiparous Holstein cows. Moreover, hCG increased estrous cycle length in Holstein and Jersey cows, and it did not affect first service P/AI at 37 ± 3 d post-AI in Holstein and multiparous Jersey lactating cows. However, hCG increased P/AI in primiparous Jersey cows. Future research with a larger number of cows is needed to confirm these intriguing fertility results.

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.

Plasma concentrations of progesterone in the preceding estrous cycle are associated with the intensity of estrus and fertility of Holstein cows

The aim of this study was to determine the association between concentrations of progesterone (P4) during previous the estrous cycle with the intensity of spontaneous or estrogen-induced estrous expression and pregnancy per artificial insemination (P/AI). A total of 1,953 AI events from lactating Holstein cows were used, consisting of 1,289 timed AI events from experiment 1 (Exp. 1) and 664 AI events from experiment 2 (Exp. 2). In Exp. 1, cows were bred after a timed AI protocol based on estradiol and P4. In Exp. 2 animals were bred upon spontaneous estrus detection. In both experiments cows were continuously monitored by an automated activity monitor (AAM), in Exp.1 a relative increase of activity was calculated (i.e., percentage of increase activity at estrus compared to cow's baseline activity) and in Exp.2, activity data from each cow were computed into an index value that ranged from 0 to 100. In Exp.2 duration (hours) of estrus were calculated and defined as the total time above the threshold (35 index). The intensity of estrous expression was determined for each event and classified as either high or low intensity using the median of each experiment. Blood samples were collected for P4 analysis in Exp. 1 at -4 d, 0 d, and 7 d relative to timed AI, and in Exp. 2 immediately following estrus (0 d), 7 d, 14 d, and 21 d post-AI. Concentration of P4 was classified as greater or lower according to the median value in each experiment. Cows with lower concentrations of P4 at AI had greater estrous expression in Exp. 1 (363.6 ± 5.2 vs. 275.9 ± 8.0% relative increase) and Exp. 2 (76.7 ± 1.9 vs. 67.4 ± 4.7 index; and 12.5 ± 0.5 vs. 9.3 ± 1.8 hours). Cows with a greater intensity of estrous expression at timed AI had greater concentrations of P4 at -4 d than cows with lower intensity estrus or no estrous expression (4.6 ± 0.2 vs. 3.6 ± 0.2 vs. 3.7 ± 0.2 ng/mL). Cows with greater concentrations of P4 at -4 d had greater P/AI (32.8 ± 4.4 vs. 22.4 ± 4.5%), whereas cows with lesser concentrations of P4 at d0 for either timed AI (35.2 ± 3.4 vs. 19.6 ± 4.6%) or spontaneous estrus (31.8 ± 2.8 vs. 23.4 ± 3.2%) had greater P/AI. Cows with greater concentrations of P4 7 d post-timed AI had greater P/AI compared with cows that had lower concentration of P4 (39.1 ± 2.9 vs. 24.7 ± 2.6%). Similarly, cows that had lower concentrations of P4 at 7 d, 14 d and 21 d post-spontaneous estrus tended to have lower P/AI when compared with cows with greater concentrations of P4. Overall, concentrations of P4 prior to and at AI were associated with greater estrous intensity and P/AI at both spontaneous and timed AI events.

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.

Evaluation and characterization of estrus alerts and behavioral parameters generated by an ear-attached accelerometer-based system for automated detection of estrus

Our objectives were to evaluate the performance of an ear-attached automated estrus detection (AED) system (Smartbow; Zoetis) that monitored physical activity and rumination time, and to characterize AED system estrus alert features (i.e., timing and duration). Lactating Holstein cows (n = 216) commenced a protocol for the synchronization of estrus at 50 ± 3 DIM or 18 ± 3 d after artificial insemination. For 7 d after induction of luteolysis with PGF_2α (d 0), we used visual observation of estrous behavior (30 min, 2 times per day) and data from an automated mounting behavior monitoring system based on a pressure-activated tail-head sensor (HeatWatch; Cowchips LLC) as a reference test (RTE) to detect behavioral estrus. Concomitantly, estrus alerts and their features were collected from the AED system. Progesterone levels confirmed luteal regression, and transrectal ultrasonography confirmed the occurrence and timing of ovulation. Performance metrics for the AED system were estimated with PROC FREQ in SAS, using the RTE or ovulation only as a reference. Performance was also estimated after the removal of cows with a discrepancy between the RTE and ovulation. Continuous outcomes with or without repeated measurements were evaluated by ANOVA using PROC MIXED in SAS. Based on the RTE, 86.6% (n = 187) of the cows presented estrus and ovulated; 1.4% (n = 3) presented estrus and did not ovulate; 6.4% (n = 14) did not present estrus but ovulated; and 5.6% (n = 12) did not present estrus or ovulation. We found no difference in the proportion of cows detected in estrus and with ovulation for the AED system (83.4%) and the RTE (86.6%). Compared with estrus events as detected by the RTE, sensitivity for the AED was 91.6% (95% CI: 87.6-95.5) and specificity was 69.2% (95% CI: 51.5-87.0). Using ovulation as reference, sensitivity was 89.6% (95% CI: 85.3-93.8) and specificity was 86.7% (95% CI 69.5-100). For all cows with agreement between the RTE and ovulation, sensitivity was 92.5% (95% CI: 88.7-96.3) and specificity was 91.7% (95% CI: 76.0-100). The mean (±SD) interval from induction of luteolysis to estrus alerts, estrus alert duration, and the onset of estrus alerts to ovulation interval were 72.2 ± 18.1, 13.5 ± 3.8, and 23.8 ± 7.1 h, respectively. We concluded that an ear-attached AED system that monitored physical activity and rumination time was effective at detecting cows in estrus and generated few false positive alerts when accounting for ovulation, cow physiological limitations, and the limitations of the RTE.

Factors associated with estrous expression and subsequent fertility in lactating dairy cows using automated activity monitoring

The objective of this observational study was to identify factors associated with estrous duration (DU) and intensity measured as the peak of activity (PA) change and subsequent fertility in lactating Holstein cows using a neck-mounted automated activity monitor (Heatime Pro, SCR Engineers Ltd., Netanya, Israel). Ambient temperature and relative humidity were recorded hourly to calculate the temperature-humidity index (THI). A total of 5,933 estrus events from 3,132 cows located on 8 commercial dairy farms in Germany were used for this study. Farms participated in monthly DHIA testing. Pregnancy diagnosis was performed either by transrectal palpation [farm 1: 42 ± 3 d; farm 3: 40 ± 3 d; farms 4 and 8: 38 ± 3 d; farm 5: 43 ± 3 d after artificial insemination (AI)] or transrectal ultrasonography (farms 2, 6, and 7: 30 ± 3 d after AI). Estrous intensity was categorized based on peak activity of estrus into low (35-89 index value), and high (90-100 index value) PA. Overall, 73.5% of estrus events were of high PA. The mean (± standard error of the mean) DU was 14.94 ± 0.06 h. There was a strong correlation between DU and PA (r = 0.67). In the final statistical model, only PA was associated with pregnancy per artificial insemination (P/AI), with 1.35 greater odds of pregnancy for cows with high PA compared with cows with low PA. Increased THI 1 wk before AI was associated with shorter DU, lower PA, and decreased P/AI. A small percentage of cows (4.7%) showed short interestrus intervals (i.e., more than 1 activity peak within 7 d close to the event of estrus), resulting in reduced DU, PA, and P/AI. The change of weighted rumination was associated with DU and PA, as a lower nadir was associated with a greater risk for high PA and long DU. There was no association, however, between the nadir of change of weighted rumination and P/AI. Whereas milk yield and somatic cell count from the DHIA test date before AI were negatively associated with estrous expression, neither milk yield nor somatic cell count was associated with P/AI. Surprisingly, multiparous cows expressed estrus with longer DU (13.15 ± 0.31 h) compared with primiparous cows (12.52 ± 0.32 h), whereas PA did not differ among parities. Pregnancy per AI was greater for primiparous (29.4%) than for multiparous (22.1%) cows. An estrus event with long DU or high PA was more likely later in lactation. Milk fat, milk protein, milk urea nitrogen, and lactose from the DHIA test date closest to AI had no association with estrous expression or P/AI. In conclusion, DU and PA were highly correlated, and cows with high PA were particularly associated with greater odds for pregnancy. A negative association between estrous expression and P/AI was identified for increased THI 1 wk before AI and cows with short interestrus intervals using automated activity monitor.

Reproductive performance of early- and late-calving dairy cows artificially inseminated after ovulation synchronization and estrous resynchronization or artificially inseminated after observed estrus

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Late-calving cows had lesser fertility than cows that calved early in the calving season

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An Ovsynch program with progesterone (P4) improved reproductive performance for both early- and late-calving cows

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A Resynch program based on P4 supplementation alone and AI after detected estrus failed to improve second AI submission rates

Within seasonal dairy systems, cows that calve late in the calving season are less likely to become pregnant and maintain a yearly calving interval. Very few studies have examined effective strategies for reproductive management of these late-calving cows. The objectives were to evaluate the reproductive performance of early- and late-calving dairy cows that were either inseminated after observed estrus (control) or enrolled in a timed AI and resynchronization protocol [progesterone (P4) Ovsynch Resynch)]. Early-calving cows calved during the first week of the calving season, whereas late-calving cows calved after 6 wk but were at least 10 d in milk at study commencement. Three dairy herds participated in the study with 391 cows total. Within each calving group, cows were randomly assigned to P4 Ovsynch Resynch or control (no treatment) in a 2 × 2 experimental design. Artificial insemination continued for 6 wk after mating start date (MSD) and was followed by 6 wk of natural service. The interval from MSD to AI was shorter (11.7 vs. 14.7 d) and the 3-wk pregnancy rate (49.5 vs. 21.2%) and the 6-wk pregnancy rate (60.8 vs. 42.4%) were greater in the early-calving compared with the late-calving control cows. By design, synchronized cows received timed AI on MSD and were not included in the statistical analysis of submission rate and interval from MSD to AI. The proportion of cows that received a second AI was not increased by the progesterone-based resynchronization strategy but was greater in early-calving compared with late-calving cows. The 12-wk pregnancy rate was greater (64.5 vs. 45.0%) in the early-calving synchronized cows compared with the late-calving synchronized cows. The interval from MSD to pregnancy was 6 and 12.6 d shorter for synchronized compared with control cows in the early- and late-calving groups, respectively. The results demonstrated reduced reproductive performance of late-calving cows compared with early-calving cows. Nonetheless, a major improvement to reproductive performance was achieved by targeting late-calving cows with a synchronization program, even when cows were only 20 to 50 DIM at first AI. Resynchronization of estrus with a progesterone device only, however, was not sufficient to increase the proportion of nonpregnant cows that received a second AI.

Timing of artificial insemination using fresh or frozen semen after automated activity monitoring of estrus in lactating dairy cows

The objective of this observational experiment was to determine the association between the time of artificial insemination (AI) and pregnancy per AI (P/AI) in lactating Holstein cows inseminated with either fresh or frozen semen considering different characteristics of an estrus event (i.e., onset, peak, and end) using an automated activity monitoring system. A total of 3,607 AI services based on the alert of an automated activity monitoring system (Heatime; SCR Engineers Ltd., Netanya, Israel) were evaluated from 4 commercial dairy farms in Germany. Pregnancy diagnosis was performed by transrectal palpation 38 ± 3 d after AI or by transrectal ultrasonography 30 ± 3 d after AI. Estrus intensity was categorized based on peak activity of estrus (PAE) into low (35-89 index value) and high (90-100 index value) intensity. The mean (± standard deviation) duration of an estrus event was 14.3 ± 4.6 h. The mean (± standard deviation) interval from onset of estrus (OE; moment where index value was ≥35) to AI was 16.8 ± 8.0 h, from PAE to AI was 11.9 ± 8.1 h, and from end of estrus (EE; moment where index value returned to <35) to AI was 2.5 ± 8.7 h. Primiparous cows had greater P/AI than multiparous cows, whereas first AI postpartum yielded greater P/AI compared with subsequent AI services. Type of semen was not associated with P/AI. Cows with heat stress 1 wk before AI had decreased P/AI. Cows with low estrus intensity (26.0%) were less fertile compared with cows showing high estrus intensity (32.8%). Cows with intermediate 100-d milk yield had decreased P/AI compared with cows with either low or high 100-d milk yield. There was a quadratic effect of the interval from OE to AI on P/AI. At 38 d after AI, P/AI was greatest for cows inseminated from 7 to 24 h after OE, within 18 h after PAE, or from 5 h before EE to 12 h after EE. There was no interaction between the interval from OE to AI and type of semen. There tended to be an interaction between the intervals from PAE to AI and type of semen and from EE to AI and type of semen. Cows inseminated with fresh semen within 5 h before EE had greater P/AI compared with frozen semen, whereas cows inseminated with frozen semen from 13 to 18 h after EE had greater P/AI compared with fresh semen. In conclusion, inseminating cows from 7 to 24 h after OE or 1 to 18 h after PAE yielded greatest P/AI irrespective of type of semen. In addition, high estrus intensity was positively associated with P/AI.

Effects of ambient temperature and humidity on body temperature and activity of heifers, and a novel idea of heat stress monitoring

Context Heat stress has led to a serious reduction in dairy cows production performance, thus increasing the stress of feeding and reproduction management. Aims Heat stress arises when cows are unable to dissipate excess body heat, we aimed to investigate the effects of ambient temperature (AT) and humidity on diurnal body temperature and activity. Methods For improving the technology for rearing dairy cows, the vaginal temperature (VT) and activity of 60 Holstein heifers in summer (n = 20), autumn (n = 20), and winter (n = 20) were measured using the oestrus monitoring system. Key results We found that VT fluctuated slightly (~38.22–38.32°C) when AT and temperature-humidity index (THI) were lower than 20°C and 68, respectively. However, when this threshold is reached, VT increased significantly with increasing AT and THI, whereas activity decreased significantly. Conclusions Heat stress may be caused when THI is above 68 and cow’s VT reaches 38.32°C. Evidently, when the THI exceeds 68 and VT is more than 38.32°C, suitable measures for reducing the effect of heat stress on the productivity of dairy cows should be taken. Implications The combined monitoring of VT and THI might provide accurate guidance for preventing and controlling heat stress.

Rumen-Reticular Temperature During Estrus and Ovulation Using Automated Activity Monitors in Dairy Cows

This study aimed to determine changes in rumen-reticular temperature (RRT) at estrus or ovulation and determine if these changes are associated with the intensity of estrous expression. Cows were equipped with an automated activity monitor (AAM) and a rumen-reticular bolus thermometer. A total of 190 estrus episodes were used where physical activity data was recorded using the AAM and ovulation was determined via ultrasonography of the ovaries at alert and twice daily, for a maximum of 60 h. Estrous expression was assessed using the maximum activity and duration in which activity remained above the AAM threshold; both characteristics were categorized using the median. Temperature data was collected for the duration of estrus, as well as for the interval of time where ovulation was determined to occur. Three measures of temperature were calculated: (1) positive area under the curve (AUC), (2) maximum positive temperature change (PTC), (3) maximum negative temperature change (NTC) at estrus (AUC_E/ PTC_E/ NTC_E) and around ovulation (AUC_O/PTC_O/ NTC_O). Both AUC and PTC were greater during estrus than around ovulation (2.7 ± 0.2 and 1.1 ± 0.3°C² for AUC_E and AUC_O; 0.55 ± 0.03 and 0.26 ± 0.04°C for PTC_E and PTC_O, respectively). In contrast, NTC was lower around ovulation than estrus (-0.28 ± 0.05 and -0.60 ± 0.06°C for NTC_E and NTC_O). Cows with greater estrous expression had greater AUC and PTC during estrus than around ovulation, but cows with lesser estrous expression had similar AUC and PTC. Increases in AUC [High THI (Temperature Humidity Index): High activity: 4.7 ± 0.5, Low activity: 1.5 ± 0.4; Low THI: High activity: 3.1 ± 0.2, Low activity: 1.4 ± 0.2 °C²] and PTC (High THI: High activity: 0.79 ± 0.08, Low activity: 0.36 ± 0.07; Low THI: High activity: 0.60 ± 0.04, Low activity: 0.47 ± 0.04°C) associated with estrous expression were found to be greater on days with higher THI. Alerts created using standard deviations from the mean were unable to detect estrus or ovulation with acceptable precision. Further research is required to determine how changes in RRT can be used successfully to predict estrus and ovulation.

Short communication: Simultaneous measurements of estrus behavior and plasma concentrations of estradiol during estrus in lactating and nonlactating dairy cows

Estrus is an important behavior that can potentially be subjected to genomic selection. Circulating estradiol concentrations at estrus may be a useful phenotype if the absolute concentrations of estradiol are associated with overt phenotypes for estrus (activity, rump touches, or both; e.g., mounts, chinrests) that can be easily observed. The objective was to measure plasma estradiol concentrations at estrus and associate these measurements with the increase in activity (steps per hour) and rump touches received at estrus. We also tested the effect of lactation on the estrus traits that we measured. Cows (n = 11 lactating and n = 9 nonlactating) were treated with PGF_2α to synchronize estrus. A jugular vein was cannulated to collect blood every 2 h for plasma estradiol measurement. Plasma LH was measured during the periestrual period to determine the time of the LH surge. Cows were fitted with an accelerometer to measure activity (steps per hour) and a capacitive touch sensing device to measure the number of rump touches and total touch time. Plasma estradiol concentrations were poorly correlated with overt signs of estrus during the period leading up to maximum estrus activity. After peak estrus activity (when cows were going out of estrus and plasma estradiol concentrations were decreasing), a stronger correlation was detected between overt signs of estrus and plasma estradiol concentrations. Effective selection for improved estrus expression based on plasma estradiol concentrations will depend on whether the cow is coming into or going out of estrus at the time of blood sampling. An association existed between lactation and fewer number of hours in estrus when estrus was defined by an increase in activity (steps per hour). Lactating cows had a shorter interval from the onset of estrus to the LH surge, and the shorter interval to the LH surge may have reduced the period of elevated estradiol during estrus in the lactating cows. Understanding mechanisms that control the sensitivity of the cow to estradiol and making appropriate selection decisions based on these mechanisms will likely increase overt signs of estrus in dairy cows.

Estimates of intra- and interclass correlation coefficients for rump touches and the number of steps during estrus in postpartum cows

Estrus traits have economic value in dairy production systems and could be incorporated into genetic selection indices. In an effort to further understand selection responses, 2 studies were performed to estimate the intra- and interclass correlation coefficients for estrus traits. Holstein-Friesian cows (n = 1,197; study 1) across 5 pasture-based grazing dairy herds were fitted with a capacitive touch sensing (CTS) device on the rump (FlashMate, Farmshed Labs Limited, Hamilton, New Zealand). The daily number of rump touches were subjected to a peak detection program to objectively identify periods of increased rump touches above baseline (indicative of estrus). The number of times touched and the sum of the touch duration were used to compare farms and estimate the intraclass correlation (repeatability). For study 2, postpartum Holstein (n = 85) and Guernsey (n = 5) cows in a confinement-style dairy were used. Cows were fitted with an IceQube accelerometer (IceRobotics Ltd., Edinburgh, United Kingdom) to measure steps taken per hour and a CTS device was applied to both rumps. The interclass correlation for the number of rump touches and number of steps taken during estrus was calculated. Data collected from 5 herds (study 1) demonstrated a 2- to 3-fold difference between herds in the number of rump touches and total touch time during estrus. The intraclass correlation (repeatability; estimates of maximum heritability) for rump touches during estrus was 0.22. For study 2, the number of steps and the number of rump touches during estrus increased in a synchronous manner. The intraclass correlation (repeatability) for number of steps during estrus was 0.26. The interclass correlation (r) for the number of rump touches and the number of steps was 0.46 (R² = 0.21). Based on the R², at least 20% of the variation in the number of steps during estrus was explained by the number of touches to the rump of the cow. Selecting cows for the number of steps taken during estrus could increase the number of rump touches (mounts, chin rests, and so on, received from other cows) if a genetic correlation exists for the phenotypic correlation that we observed.

Symposium review: Linking activity-sensor data and physiology to improve dairy cow fertility

Several studies have demonstrated that the intensity of estrous expression is associated with ovulation, ovarian and uterine function, and fertility, and is dependent on social hierarchy and the housing system used. Data from recent studies involving spontaneous and induced estrus have shown that a greater relative increase and longer estrus (captured by different automated activity monitors; AAM) are both associated with improved pregnancy per artificial insemination (AI; around 10 to 14% increase) and decreased pregnancy losses. Intensity and duration of estrus were surprisingly weakly associated with preovulatory follicle diameter and concentrations of plasma estradiol at estrus, whereas ovulation failure was associated with low estrus intensity. Studies have also shown that the display of estrous behavior near AI was associated with the modification of expression of genes related to the immune system, adhesion molecules, and prostaglandin synthesis in the endometrium. Transcripts in leukocytes and in the conceptus tissue associated with maternal recognition of pregnancy as well as conceptus elongation were all associated with differences in the intensity of estrous expression. Most recently, studies from the United States and Canada have demonstrated that reproductive programs emphasizing detection of estrus using AAM can be successful and comparable to intensive timed AI protocol-based programs that incorporate GnRH and PGF_2α treatments. Further, one study concluded that the administration of GnRH at AI for spontaneous estrus events greatly improved pregnancy per AI, but only for cows with reduced intensity of estrous expression, showing the potential to use AAM data as a tool in targeted reproductive programs. Quantitative information from estrus events could be used to improve estrus detection and develop decision-making strategies at the farm level. Future studies in this field should aim to better understand ovarian, conceptus, and endometrial mechanisms associated with either the expression or the intensity of estrus, and to refine the identification of phenotypes related to estrus (relative increase, absolute increase, baseline levels, duration, and repeatability within cow) to improve data usage, estrus detection, and possibly genetic selection.

Effect of delaying the time of insemination with sex-sorted semen on pregnancy rate in Holstein heifers

The objective of the study was to evaluate the interval from onset of oestrus to time of artificial insemination (AI) to obtain the optimum pregnancy rate with sex-sorted semen in Holstein heifers. Heifers in oestrus were detected and inseminated only by using heat-rumination neck collar comprised electronic identification tag at the age of 13-14 months. Heifers (n = 283) were randomly assigned to one of three groups according to the timing of insemination at 12-16 hr (G1, n = 97), at 16.1-20 hr (G2, n = 94) and at 20.1-24 hr (G3, n = 92) after reaching the activity threshold. The mean duration of oestrus was 18.6 ± 0.1 hr, and mean peak activity was found at 7.5 ± 0.1 hr after activity threshold. The mean interval from activity threshold to ovulation was 29.4 ± 0.4 hr. The overall pregnancy per AI (P/AI) was 53.0% at 29-35 days and 50.9% at 60-66 days after AI. There was a significant reduction between G1 (13.8 ± 1.4 hr) and G3 (7.9 ± 1.4 hr) related to the intervals from AI to ovulation time. Sex-sorted semen resulted in significantly higher P/AI at 29-35 days when heifers inseminated in G3 (60.9%) after oestrus than those inseminated in G1 (49.5%) and G2 (48.9%). In terms of fertility, when the temperature-humidity index (THI) was below the threshold value (THI ≤65) at the time of AI, there was a tendency (≤65; 57.2% vs. > 65; 47.1%) for high pregnancy rate. There was no effect of sire on P/AI. In addition, the interaction of the technician with the time of AI was found significant, and three-way interaction of technician, sire and time of AI was tended to be significant on pregnancy rate. Thus, in addition to delaying the time of insemination (between 20.1 and 24 hr) after oestrous detection, THI and experienced technician were also found to be critical factors in increasing fertility with the use of sex-sorted semen in Holstein heifers.

New approaches to diagnose and target reproductive failure in cattle

Reproductive failure and pregnancy loss in cattle are some of the largest economic burdens to cattle producers and one of most perplexing factors influencing management decisions. Pregnancy loss may occur at any point during gestation with the largest percentage of loss occurring in the first 30 days and, subsequently, decreasing as the pregnancy progresses. Losses may be attributed to numerous factors, predisposed issues or environmental conditions such as nutritional stressors or disease. From a research perspective, determining the exact causes of pregnancy loss or embryonic mortality in cattle have been difficult, due to limitations of accurately determining early gestation pregnancy status. Until methods that precisely determine embryo success early in gestation are available, our understanding of in vivo pregnancy loss will lack clarity necessary to develop management strategies to decrease such loss. In this review, we will briefly discuss the pivotal periods of pregnancy loss affecting beef and dairy cattle, methods and technologies to determine pregnancy status and embryo viability and potential opportunities to decrease reproductive failure.

Metabolomic Profiling of Bos taurus Beef, Dairy, and Crossbred Cattle: A Between-Breeds Meta-Analysis

Cattle breeds may differ substantially in their metabolism. However, the metabolomes of dairy and beef cattle are not well-known. Knowledge of breed-specific metabolic features is essential for biomarker identification and to adopt specific nutritional strategies. The muscle hypertrophy (mh), a beef cattle phenotype present in Asturiana de los Valles (AV) but absent in Asturiana de la Montaña (AM) and Holsteins, may underlie such differences. We compared the plasma metabolomes of Holstein, AV, AM, and crossbred cattle recipients selected for meta-analysis within an embryo transfer (ET) program. Blood samples were collected on day 0 (oestrus) and day 7 (prior to ET) (N = 234 samples × 2 days). Nuclear magnetic resonance quantified N = 36 metabolites in plasma, and more metabolic differences between breeds were found on day 0 (N = 19 regulated metabolites) than on day 7 (N = 5). AV and AM largely differed from Holstein cattle (N = 55 and 35 enriched metabolic pathways, respectively); however, AV and AM differed in N = 6 enriched pathways. Metabolic activity was higher in AV than in Holstein cattle, as explained in part by the mh phenotype. The metabolomic characterization of breeds facilitates biomarker research and helps to define the healthy ranges of metabolite concentrations.

Estrous detection with an activity and rumination monitoring system in an organic grazing and a low-input conventional dairy herd

The objective of this study was to evaluate estrous detection using a physical activity and rumination monitoring system in a seasonal calving organic grazing (GRAZ) and a low-input conventional (ZEROGRAZ) dairy herd. The study was conducted from June 2014 to August 2017. During each breeding season, physical activity and rumination were monitored electronically using an activity and rumination monitoring system (HR-LD tags; SCR Engineers Ltd., Netanya, Israel). Signals resulting from the activity and rumination monitoring system for individual cows were used to determine consistency of the values using this system with the breeding date of cows. Breeding dates were determined using Estrotect^TM patches. The study included 1,463 breeding dates from 531 cows. Within the GRAZ herd, during the summer breeding season the monitoring system was less sensitive for estrous detection (33.8 %) than during the winter breeding season (79.8 %).The activity and rumination monitoring system had a sensitivity of 56.7 %, specificity of 99.3 % and positive predictive value of 59.8 % for the GRAZ herd, and sensitivity of 70.1 %, specificity of 99.2 % and positive predictive value of 66.3 % for the ZEROGRAZ herd. For cows that were determined to be pregnant and subsequently calved as a result of the mating, the sensitivity for estrous detection was slightly greater for the GRAZ (60.7 %) and ZEROGRAZ (72.5 %) herds. The activity and rumination monitoring system evaluated in this study has potential for estrous detection in grazing herds during the winter breeding season and in small-input dairy herds during both, winter and summer breeding seasons.

Economic Viability of Adoption of Automated Oestrus Detection Technologies on Dairy Farms: A Review

Simple Summary

The accurate and timely detection of oestrus is a central element of good dairy herd management as it ultimately determines the level of milk production and is core to the economic viability of the farm business. However, the traditional method of oestrus detection, which occurs by observing the dairy cows standing immobile while being mounted, is usually time-consuming, repetitive and requires considerable skill and experience on the part of the farmer to attain a reasonable level of efficiency. Given the limitation of the traditional method of oestrus detection, a number of automated oestrus detection (AOD) technologies have been developed. However, the rate of adoption of these technologies remains low. One reason that has been proposed for farmers’ low adoption of such technologies has been their lack of knowledge around the potential economic returns from investing in AOD technologies. In this paper, we review the empirical literature on the viability of investment in AOD technologies from an economic perspective. The conclusion of this study provides evidence from which farmers can make more informed decisions in relation to investing in AOD technologies. The review and analysis is also of importance for informing policy, as it provides an examination of the incentives and levers that could improve productivity on dairy farms.

Abstract

The decision for dairy farmers to invest in automated oestrus detection (AOD) technologies involves the weighing up of the costs and benefits of implementation. In this paper, through a review of the existing literature, we examine the impacts of investment in AOD technologies in relation to the profitability and technical performance of dairy farms. Peer-reviewed articles published between 1970 and 2019 on the investment viability of AOD technologies were collated and analysed. We capture the different measures used in assessing the economic performance of investment in AOD technologies over time which include net present value (NPV), milk production, Benefit-Cost Ratio (BCR), internal rate of return (IRR) and payback period (PBP). The study concludes that investment in AOD technologies is not only worthwhile but also contributes to farm profitability.

Comparison of behavioral patterns of dairy cows with natural estrus and induced ovulation detected by an ear-tag based accelerometer

Dairy farms face many challenges and changes. With increasing herd sizes and fewer farmers or employees per cow, new strategies to maintain or improve reproductive management are required. One of the major challenges is to detect cows in estrus and to estimate the perfect time for artificial insemination (AI). Several estrus and ovulation synchronization programs with timed AI as well as estrus detection aids, e.g., tail-paint, pedometer, accelerometer, and others are available. A combination of ovulation synchronization programs and technical solutions, however, has rarely been tested. This study was designed to gain insights into behavioral patterns of cows subjected to an Ovsynch program and to test if behavioral data could be used to optimize the timing of insemination within an Ovsynch program. In this study, we used an ear-tag based 3D-accelerometer system (SMARTBOW, Smartbow GmbH, Weibern, Austria) to generate data of behavioral patterns, i.e., rumination and activity. In Part 1 of this study, behavioral patterns during the peri-estrus period were compared between cows with physiological estrus and cows subjected to an Ovsynch protocol. On the day before estrus and on the day of estrus/AI, cows with natural estrus showed a clear drop in rumination and "inactivity" and an increase in "high activity", based on an algorithm of the accelerometer system, whereas, cows in the Ovsynch protocol showed only minor changes in behavioral patterns. In Part 2, we analyzed behavioral patterns between synchronized cows that became pregnant after AI and synchronized cows that remained open. As a result, no differences were detected between these two Ovsynch groups before AI. Thus, in this study we found no evidence that behavioral patterns can be used to improve conception rates within an Ovsynch protocol.

Machine-Learning Techniques Can Enhance Dairy Cow Estrus Detection Using Location and Acceleration Data

The aim of this study was to assess combining location, acceleration and machine learning technologies to detect estrus in dairy cows. Data were obtained from 12 cows, which were monitored continuously for 12 days. A neck mounted device collected 25,684 records for location and acceleration. Four machine-learning approaches were tested (K-nearest neighbor (KNN), back-propagation neural network (BPNN), linear discriminant analysis (LDA), and classification and regression tree (CART)) to automatically identify cows in estrus from estrus indicators determined by principal component analysis (PCA) of twelve behavioral metrics, which were: duration of standing, duration of lying, duration of walking, duration of feeding, duration of drinking, switching times between activity and lying, steps, displacement, average velocity, walking times, feeding times, and drinking times. The study showed that the neck tag had a static and dynamic positioning accuracy of 0.25 ± 0.06 m and 0.45 ± 0.15 m, respectively. In the 0.5-h, 1-h, and 1.5-h time windows, the machine learning approaches ranged from 73.3 to 99.4% for sensitivity, from 50 to 85.7% for specificity, from 77.8 to 95.8% for precision, from 55.6 to 93.7% for negative predictive value (NPV), from 72.7 to 95.4% for accuracy, and from 78.6 to 97.5% for F1 score. We found that the BPNN algorithm with 0.5-h time window was the best predictor of estrus in dairy cows. Based on these results, the integration of location, acceleration, and machine learning methods can improve dairy cow estrus detection.

Performance and optimization of an ear tag automated activity monitor for estrus prediction in dairy heifers

The objectives of this study were to evaluate the performance of the SCR eSense ear tag automated activity monitor (AAM) to detect estrus behavior in Holstein heifers and to determine the optimal time from estrus alert to artificial insemination (AI) using sex-sorted or conventional semen. In total, 281 heifers were fitted with the AAM once eligible for breeding (>13.5 m of age). For the first AI, estrus was synchronized using 500 μg of cloprostenol (PGF), given 14 d apart, and heifers were given estrus detection patches (Estrotect™) after the second PGF. Heifers were inseminated at randomly attributed times after high activity alert from the AAM system or if the estrus patch had ≥ 50% colour change. Most heifers received sex-sorted semen for the first AI and conventional semen for subsequent inseminations. Pregnancy diagnosis was performed at 30 d post AI and heifers had four opportunities to become pregnant. In a subset of heifers (n = 149), ovaries were scanned every 12 h from the time of AI until ovulation (OV). The system recorded a heat index (measure of estrus strength), maximum activity change, maximum rumination change and duration of high activity. The sensitivity was 91.0%, with a false positive and false negative rate of 8.0%, and the positive predictive value to detect true estrus events was 83.5%. Pregnancy per AI to first AI was 67.6% and 97.9% of heifers become pregnant after four inseminations. Most false positive estrus events had a heat index < 45 and a rumination change < -20, while false negative events had a rumination change ≥ -20. Odds of pregnancy was not associated with any estrus characteristics measured by the system. However, pre-ovulatory follicle diameter had a weak correlation (r < 0.25) with all estrus characteristics. The average (range) interval of onset of high activity, peak activity and end of high activity to OV was 28 h (16-46 h), 22 h (10-40 h) and 16 h (0-36 h), respectively. For conventional semen, each hour increase in interval from activity onset or peak activity to AI reduced the predicted probability of pregnancy by 3.8 and 4.2%, respectively. For sex-sorted semen, the relationship between activity onset or peak activity to AI and predicted probability of pregnancy was quadratic, but not significant. Overall, the SCR eSense ear tag AAM performed well and strategies to identify false positive and false negative estrus events, along with optimization of timing of AI, should further improve performance in Holstein heifers.