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.

Pulsoximetric monitoring of fetal arterial oxygen saturation and fetal pulse at stage II of labor to predict acidosis in newborn Holstein Friesian calves.

During stage II of parturition, the bovine fetus is at risk of oxygen deficiency caused by insufficient gas exchange between the dam and the fetus. The early detection of this critical condition, followed by assistance at calving, can help to improve the vitality of the newborn calf, or even prevent it from being born dead. By using pulse oximetry, the arterial oxygen saturation, as well as the pulse rate, can be continuously and non-invasively measured. The aim of our study was to identify critical thresholds for the parameters 'arterial oxygen saturation (FSpO2)' and 'pulse rate (PR)' that indicate a severe postnatal risk for calves to suffer from acidosis. FSpO2 and PR from 40 bovine fetuses were recorded during the last 25 min of calving with a commercially available pulse oximeter (Radius-7, Masimo Corporation, Irvine, USA). The calves were tested immediately after birth for acidosis by analyzing their blood with a portable blood gas analyzer (VetScan iStat1, Abaxis Inc., Union City, USA). Retrospectively, the pulsoximetric data were scanned for predefined patterns. The validity of these patterns to predict acidosis in newborn calves was analyzed by using receiver operating characteristics (ROC) curve analyses. In general, PR was a stronger predictive parameter for acidosis than FSpO2, with the greatest area under the curve (AUC) for the PR criteria 'Pulse rate > 120 beats per minute (bpm) for at least 2 min', with an AUC of 0.764, in contrast to an AUC of 0.613 for the best FSpO2 criteria 'FSpO2 < 40% for at least 50% of the measurement'. Further studies should investigate whether vitality after calving can be improved and fetal death rate can be reduced when obstetric assistance is performed as soon as one of these criteria apply to the bovine fetus. For more practical implementation in the field, improvement of the device's hardware would be necessary.

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.