Potential of connected devices to optimize cattle reproduction

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.

Accidental laceration of the vaginal wall by an intravaginal thermometer as a calving detection device in a Japanese black cow

An intravaginal thermometer was inserted into a 59-month-old Japanese black cow to predict calving. After calving, the thermometer penetrated the vaginal wall and could not be removed by farm staff. Surgery to remove the thermometer was successful. The cow left the animal hospital without hospitalization. In the follow-up, the cow remained healthy on the farm for more than one year and is now pregnant. No symptoms related to damage to the vagina or infection developed. This is the first case report of a vaginal laceration caused by an intravaginal thermometer in a Japanese black cow. Insertional vaginal devices may cause vaginal lacerations in cattle.

Innovations in Cattle Farming: Application of Innovative Technologies and Sensors in the Diagnosis of Diseases

Precision livestock farming has a crucial function as farming grows in significance. It will help farmers make better decisions, alter their roles and perspectives as farmers and managers, and allow for the tracking and monitoring of product quality and animal welfare as mandated by the government and industry. Farmers can improve productivity, sustainability, and animal care by gaining a deeper understanding of their farm systems as a result of the increased use of data generated by smart farming equipment. Automation and robots in agriculture have the potential to play a significant role in helping society fulfill its future demands for food supply. These technologies have already enabled significant cost reductions in production, as well as reductions in the amount of intensive manual labor, improvements in product quality, and enhancements in environmental management. Wearable sensors can monitor eating, rumination, rumen pH, rumen temperature, body temperature, laying behavior, animal activity, and animal position or placement. Detachable or imprinted biosensors that are adaptable and enable remote data transfer might be highly important in this quickly growing industry. There are already multiple gadgets to evaluate illnesses such as ketosis or mastitis in cattle. The objective evaluation of sensor methods and systems employed on the farm is one of the difficulties presented by the implementation of modern technologies on dairy farms. The availability of sensors and high-precision technology for real-time monitoring of cattle raises the question of how to objectively evaluate the contribution of these technologies to the long-term viability of farms (productivity, health monitoring, welfare evaluation, and environmental effects). This review focuses on biosensing technologies that have the potential to change early illness diagnosis, management, and operations for livestock.

Prediction of 24-h and 6-h Periods before Calving Using a Multimodal Tail-Attached Device Equipped with a Thermistor and 3-Axis Accelerometer through Supervised Machine Learning

Simple Summary

Routine visual observation of signs of imminent calving, such as softening of ligaments around the tailhead and udder distension, is time-consuming, and the resulting calving predictions are relatively unreliable. To address this issue, we used a multimodal tail-attached device (tail sensor) and developed calving prediction models through supervised machine learning. The tail sensor is equipped with a thermistor and 3-axis accelerometer, and can monitor tail skin temperature, activity intensity, lying time, posture changes (standing to lying or vice versa), and tail raising behavior. Using the sensor data with a non-sensor-based data (days to the expected calving date), we developed calving prediction models for 24-h and 6-h periods before calving and evaluated their predictive ability under two distinct housing conditions, tethering (tie-stall) and untethering (free-stall and individual pen). Our results demonstrated that calving prediction models based on tail sensor data with supervised machine learning have the potential to achieve effective calving prediction, irrespective of the cattle housing conditions.

Abstract

In this study, we developed calving prediction models for 24-h and 6-h periods before calving using data on physiological (tail skin temperature) and behavioral (activity intensity, lying time, posture change, and tail raising) parameters obtained using a multimodal tail-attached device (tail sensor). The efficiencies of the models were validated under tethering (tie-stall) and untethering (free-stall and individual pen) conditions. Data were collected from 33 and 30 pregnant cattle under tethering and untethering conditions, respectively, from approximately 15 days before the expected calving date. Based on pre-calving changes, 40 features (8 physiological and 32 behavioral) were extracted from the sensor data, and one non-sensor-based feature (days to the expected calving date) was added to develop models using a support vector machine. Cross-validation showed that calving within the next 24 h under tethering and untethering conditions was predicted with a sensitivity of 97% and 93% and precision of 80% and 76%, respectively, while calving within the next 6 h was predicted with a sensitivity of 91% and 90% and precision of 88% and 90%, respectively. Calving prediction models based on the tail sensor data with supervised machine learning have the potential to achieve effective calving prediction, irrespective of the cattle housing conditions.

Accuracy to Predict the Onset of Calving in Dairy Farms by Using Different Precision Livestock Farming Devices

Simple Summary

If the onset of calving can be accurately detected as well as appropriate calving assistance can be performed on a dairy farm, at that time, the prevalence of dystocia, stillbirth, vaginal laceration, retained fetal membranes, and consequent clinical metritis/endometritis can be decreased significantly. Therefore, in order to reduce these losses, our primary task must be to predict the onset of calving accurately and provide timely and professional calving assistance. This review focuses on the diagnostic possibilities and limitations of detecting the onset calving in the field.

Abstract

Besides traditional methods such as evaluation of the external preparatory and behavioral signs, which even presently are widely used also in large dairy farms, there are several new possibilities such as measuring body (intravaginal, ventral tail-base surface, ear surface, or reticulo-ruminal) temperature, detecting behavioral signs (rumination, eating, activity, tail raising) or detecting the expulsion of the device inserted into the vagina or fixed to the skin of the vulva when allantochorion appears in the vulva to predict the onset of the second stage of calving. Presently none of the single sensors or a combination of sensors can predict the onset of calving with acceptable accuracy. At the same time, with the exception of the iVET^® birth monitoring system, not only the imminent onset of calving could be predicted with high accuracy, but a significantly lower prevalence rate of dystocia, stillbirth, retained fetal membranes, uterine diseases/clinical metritis could be reached while calving-to-conception interval was significantly shorter compared with the control groups. These results may confirm the use of these devices in dairy farms by allowing appropriate intervention during calving when needed. In this way, we can reduce the negative effect of dystocia on calves and their dams and improve their welfare.

Clinical Overview of Luteal Deficiency in Dairy Cattle

Simple Summary

Luteal deficiency is defined as reduced progesterone production by the corpus luteum, either in the amount or duration, or both. The clinical manifestations include primary infertility and pregnancy loss during the late embryonic/early fetal period (30–50 days post-AI). This work provides a clinical overview of the current understanding of luteal deficiency and its association with low fertility in dairy cows.

Abstract

Luteal deficiency is defined as reduced progesterone (P4) steroidogenesis by the corpus luteum (CL), either in the amount or duration, or both. This work provides a clinical overview of the current understanding of luteal deficiency and its association with low fertility in dairy cows. Low plasma P4 concentrations during the luteal phase post-artificial insemination (AI) are associated with lower conception rates. Treatments post-AI with P4, gonadotropin-releasing hormone (GnRH) or human chorionic gonadotropin (hCG) improve fertility in some conditions. Sub-luteal function during the late embryonic period (at pregnancy diagnosis, i.e., 28–34 days post-AI), is just one factor among other factors associated with pregnancy loss. Treatment with P4 in cows with one CL favors pregnancy maintenance, while GnRH treatment does the same in cows carrying twins. The diagnosis of sub-luteal function can be made clinically on the basis of plasma or milk P4 concentrations. Automated in-line milk P4 analysis systems to diagnose luteal activity emerge as a very interesting tool in dairy herds. Monitoring plasma or milk P4 concentrations with the help of Doppler ultrasonography to assess the CL function would allow individualizing the luteal phase support.

Automated Systems for Estrous and Calving Detection in Dairy Cattle

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

«The role of reproductive biology in SDGs» Global warming and cattle reproduction: Will increase in cattle numbers progress to global warming?

The livestock industry produces a large amount of greenhouse gases (GHG) that cause global warming. A high percentage of GHG emissions are derived from cattle and has been suggested to be a factor in global warming. With the global increase in the consumption of livestock products, the number of farm animals has increased. In addition, the reduction in productivity and reproductive capacity of cattle has resulted in accelerated GHG emissions. In a high-temperature environment, the pregnancy rate decreases, leading to an increase in animals that do not contribute to production. Consequently, GHG emission per unit product increases, thereby accelerating global warming. To reduce this environmental impact, it is important to improve the breeding efficiency of cattle by the use of reproductive technology and, thus, reduce the number of non-productive animals. Thus, reproductive biology plays a major role in mitigating global warming related to the livestock industry.

Estrus Detection Using Background Image Subtraction Technique in Tie-Stalled Cows

Simple Summary

With increasing herd sizes and labor costs in recent decades, visual estrus detection by farmers has become more difficult because of the reduced manpower input per cow. To address this problem, various wearable devices have been developed for automatic estrus detection in cows, such as neck- or leg-mounted activity meters for monitoring estrus-associated increments in the amount of activity. However, these animal-contact devices have several limitations; namely, it can be dangerous to attach or remove the device and it can cause discomfort. Recently, a background image subtraction technique has been proposed as a non-contact method for monitoring activity changes in livestock animals. In this study, a new method was developed by combining the background subtraction technique and the thresholding method to detect estrus-associated activity increases in tie-stalled cows. Using this method, a substantial increase in activity in estrus was detectable, and the estrus detection sensitivity reached as high as 90% with a precision of 50%, where the sensitivity and precision were calculated as: (true-positive/[true-positive + false-negative]) × 100% and (true-positive/[true-positive + false-positive]) × 100%, respectively. This result may indicate that activity monitoring using the background subtraction technique has the potential to be a non-contact estrus detection method in tie-stalled cows.

Abstract

In this study, we determined the applicability of the background image subtraction technique to detect estrus in tie-stalled cows. To investigate the impact of the camera shooting direction, webcams were set up to capture the front, top, and rear views of a cow simultaneously. Video recording was performed for a total of ten estrous cycles in six cows. Standing estrus was confirmed by testing at 6 h intervals. From the end of estrus, transrectal ultrasonography was performed every 2 h to confirm ovulation time. Foreground objects (moving objects) were extracted in the videos using the background subtraction technique, and the pixels were counted at each frame of five frames-per-second sequences. After calculating the hourly averaged pixel counts, the change in values was expressed as the pixel ratio (total value during the last 24 h/total value during the last 24 to 48 h). The mean pixel ratio gradually increased at approximately 48 h before ovulation, and the highest value was observed at estrus, regardless of the camera shooting direction. When using front-view videos with an appropriate threshold, estrus was detected with 90% sensitivity and 50% precision. The present method in particular has the potential to be a non-contact estrus detection method for tie-stalled cows.

Recent Possibilities for the Diagnosis of Early Pregnancy and Embryonic Mortality in Dairy Cows

Simple Summary

Pregnancy diagnosis plays an essential role in decreasing days open in dairy farms; therefore, it is very important to select an accurate method for diagnosing early pregnancy. Besides traditional pregnancy diagnoses made by rectal palpation of the uterus from 40 to 60 days after AI and measuring the serum or milk progesterone concentration between 18 to 24 days after AI, there are several new possibilities to diagnose early pregnancy in dairy farms. However, it is very important to emphasize that before introducing any new diagnostic test, we need to make sure the accuracy of that particular test to be able to decrease the rate of iatrogenic pregnancy losses caused by prostaglandin or resynchronization treatments. This review focuses on the diagnostic possibilities and limitations of early pregnancy diagnosis in the field.

Abstract

One of the most recent techniques for the on-farm diagnosis of early pregnancy (EP) in cattle is B-mode ultrasonography. Under field conditions, acceptable results may be achieved with ultrasonography from Days 25 to 30 post-AI. The reliability of the test greatly depends on the frequency of the transducer used, the skill of the examiner, the criterion used for a positive pregnancy diagnosis (PD), and the position of the uterus in the pelvic inlet. Non-pregnant animals can be selected accurately by evaluating blood flow in the corpus luteum around Day 20 after AI, meaning we can substantially improve the reproductive efficiency of our herd. Pregnancy protein assays (PSPB, PAG-1, and PSP60 RIA, commercial ELISA or rapid visual ELISA tests) may provide an alternative method to ultrasonography for determining early pregnancy or late embryonic/early fetal mortality (LEM/EFM) in dairy cows. Although the early pregnancy factor is the earliest specific indicator of fertilization, at present, its detection is entirely dependent on the use of the rosette inhibition test; therefore, its use in the field needs further developments. Recently found biomarkers like interferon-tau stimulated genes or microRNAs may help us diagnose early pregnancy in dairy cows; however, these tests need further developments before their general use in the farms becomes possible.

Sensitivity and specificity of a tail-activity measuring device for calving prediction in dairy cattle

Efficient calving surveillance is essential for avoiding stillbirth due to unattended dystocia. Calving sensors can help detect the onset of parturition and thus ensure timely calving assistance if necessary. Tail-raising is an indicator of imminent calving. The objective of this study was to evaluate a tail-mounted inclinometer sensor (Moocall Ltd., Dublin, Ireland) and to monitor skin integrity after sensor attachment. Cows (n = 157) and heifers (n = 23) were enrolled at 275 d post insemination, and a sensor was attached to each cow's tail. Investigators checked for signs indicating the onset of stage II of parturition, verified the position of the sensor, and evaluated the skin integrity of the tail above and below the sensor hourly for 24 h/d. We used 5 different intervals (i.e., 1, 2, 4, 12, and 24 h until calving) to calculate sensitivity and specificity. Sensors continuously remained on the tail (i.e., within 3 cm of the initial attachment position) after initial attachment until the onset of calving in only 13.9% of animals (n = 25). Sensors were reattached until a calving event occurred (51.6%) or the animal was excluded for other reasons (34.4%). In 31 animals the sensor was removed because the tail was swollen or painful. Heifers were significantly less likely than cows to lose a sensor but more likely to experience tail swelling or pain. Depending on the interval preceding the onset of parturition, sensitivity varied from 19 to 75% and specificity from 63 to 96%.

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.

Prepartum change in ventral tail base surface temperature in beef cattle: comparison with vaginal temperature and behavior indices, and effect of ambient temperature

Prediction of parturition is essential for sustainable production in beef and dairy cattle, yet the present methods are limited by their high invasiveness and low utility. Here we compared prepartum changes in ventral tail base surface temperature (ST) with changes in vaginal temperature (VT) and behavioral indices. We analyzed 22 parturitions from 22 beef cows. Changes in daily values of ST, VT, and behavioral indices over the 7 days before parturition were investigated. Hourly values were calculated as the actual values minus the mean values for the same hour over a 3-day period, and the changes in hourly values over the 48 h before parturition were investigated. To test the effect of ambient temperature, tested cows were assigned to two season-groups based on the ambient temperature to which they were exposed (warm: n = 13; cool: n = 9), and the daily and hourly values of the indices were compared between seasons. A decrease in ST occurred approximately 30 h before parturition, which was similar to the time of the decrease in VT and earlier than the increase of behavioral indices. In addition, a unique fluctuation of ST observed in the last few hours before parturition indicates that ST could provide a sign for parturition not only in the long-term like VT, but also in the short-term like behavioral indices. Although ST was more sensitive to ambient temperature than VT or the behavioral indices, the day of parturition could be predicted from ST in both the warm and cool seasons.

Evaluation of an ear-attached accelerometer for detecting estrus events in indoor housed dairy cows

Precision dairy farming technologies have tremendous potential to improve and support farmers in herd management decisions, particularly in reproductive management. Nowadays, estrus detection in cows is challenging and several supporting tools are available. In this study, a 3D-accelerometer integrated into an ear-tag (SMARTBOW, Smartbow GmbH, Weibern, Austria) was used for the detection of cows in estrus. Movement pattern based on accelerometer data were analyzed and processed by algorithms and machine learning, resulting in estrus alerts. For the evaluation of the system, reproductive performance data of 579 estrus events of multiparous cows were used to retrospectively evaluate the accuracy of estrus alerts generated by the accelerometer-based system and the overall performance of the system. Estrus events were classified as 'gold standard' events, if an estrus followed by AI resulted in pregnancy, and as 'recorded estrus' events, if two estrus events with an interval of 18-25 d were in the herd records, independent of whether estrus was followed by AI or pregnancy. In total, 316 'gold standard' events were matched with estrus alerts generated by the accelerometer-based system, resulting in a sensitivity of 97%. Furthermore, 263 'recorded estrus' events were compared with correct or incorrect estrus alerts by the system. Sensitivity, specificity, positive and negative predictive values, accuracy, and error rate for 'recorded estrus' events were 97%, 98%, 96%, 94%, 96%, and 2%, respectively. In summary, the SMARTBOW system is suitable for an automated detection of estrus events of multiparous cows in indoor housed dairy cows.