Evaluation of Oestrous Detection in Dairy Cattle Comparing an Automated Activity Monitoring System to Visual Observation

Michaelis, I.; Burfeind, O.; Heuwieser, W.

doi:10.1111/rda.12337

Cited by 34 publications

(32 citation statements)

References 43 publications

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“…Alerts based on activity measurements have been shown to improve reproductive performance, even in detecting up to 54% of estrous events without standing mounts (Galon, 2010). Previous research reported a significant (P < 0.05) increase in walking activity on the day of estrus compared with a baseline with pedometers or accelerometers (Liu and Spahr, 1993;Roelofs et al, 2005;Michaelis et al, 2014).…”

Section: Variable Percent Changes At Estrusmentioning

confidence: 99%

“…Trimberger's (1948) view for the need for continuous recordings of standing estrus is still used in research today. Quantifying behavioral and physiological variables with automated estrous detection improves estrus detection rates (Rorie et al, 2002;Michaelis et al, 2014;Stevenson et al, 2014) compared with visual observation. Completed research on commercial PDMT used for detecting estrus, however, is limited to one or a few systems in the same group of cows (reference was standing estrus) or varying sample sizes (Ginther et al, 2013;Rutten et al, 2013;Rorie et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

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Automated estrous detection using multiple commercial precision dairy monitoring technologies in synchronized dairy cows

Mayo

Silvia

Ray

et al. 2019

Journal of Dairy Science

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Estrus in dairy cattle varies in duration and intensity, highlighting the need for accurate and continuous monitoring to determine optimal breeding time. The objective of this study was to evaluate precision dairy monitoring technologies (PDMT) for detecting estrus. Estrus was synchronized in lactating Holstein cows (n = 109) using a modified G7G-Ovsynch protocol (last GnRH injection withheld to permit expression of estrus) beginning at 45 to 85 d in milk. Resumption of ovarian cyclicity at enrollment was verified by transrectal ultrasonography for presence of a corpus luteum. Cows were observed visually during 30 min (4 times per day) for behavioral estrus on d −1 to 2 (d 0 = day of estrus). Periods peri-estrus were defined by the temporal blood plasma progesterone patterns on d −5, −4, −3, −2, −1, 0, 2, 4, 6, and 8. Estrous detection by PDMT, an estrous behavior scoring system, and by visual observation of standing estrus were compared with the reference (gold) standard. Only 56% of cows that ovulated were observed standing by visual observation. Sensitivity and specificity for estrous detection were not different among all PDMT. Devices in this study measuring activity in steps, neck movement, high activity of head movement, or a proprietary motion index increased on the day of estrus 69 to 170% from the baseline before estrus. The change in rumination time on the day of estrus decreased for both neck and ear-based technologies (−2 to −16%). Temperature of the reticulorumen, vagina, and ear skin were not different on the day of estrus than day peri-estrus. Daily lying times decreased on average to 24.6% on the day of estrus for IceQube (IceRobotics Ltd., Edinburgh, Scotland). In contrast, lying time increased 15.5 and 33.1% for AfiAct Pedometer Plus (Afimilk, Kibbutz Afikim, Israel) and Track a Cow (ENGS Systems Innovative Dairy Solutions, Rosh Pina, Israel), respectively. All PDMT tested were capable of detecting estrus at least as effectively as visual observation. Four of the 6 PDMT that reported estrous alerts correctly detected 15 to 35% more cows than visual observation 4 times per day. Use of temporal progesterone patterns correctly identified more cows than visual observation alone. Dairy producers considering PDMT should focus on (1) the reference (gold) standard used to test efficacy of a device's alerts and (2) the device that will have the fewest false readings in their operations.

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Section: Variable Percent Changes At Estrusmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Automated estrous detection using multiple commercial precision dairy monitoring technologies in synchronized dairy cows

Mayo

Silvia

Ray

et al. 2019

Journal of Dairy Science

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“…Based on these data, confirmation of the onset of estrus was established in two different ways: (1) increased uterus tonus, showing a well contracted uterus upon rectal palpation (Bonafos et al, 1995) and absence of a CL, together with the presence of a preovulatory follicle of at least 13 mm diameter on one of the ovaries, which disappeared and was replaced by a CL on the same ovary 7 to 11 days later (method 1), in analogy with the method used by Michaelis et al, (2014); (2) the expression of standing heat (method 2) (Roelofs et al, 2010). All cows standing to be mounted were found to show metestrous bleeding 2 to 3 days later.…”

Section: Methodsmentioning

confidence: 99%

A novel system for online fertility monitoring based on milk progesterone

Adriaens

Saeys

Huybrechts

et al. 2018

Preprint

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Timely identification of a cow’s reproduction status is essential to minimize fertilityrelated losses on dairy farms. This includes optimal estrus detection, pregnancy diagnosis and the timely recognition of early embryonic death and ovarian problems. On farm milk progesterone (P4) analysis could indicate all of these fertility events simultaneously. However, milk P4 measurements are subject to a large variability both in terms of measurement errors and absolute values between cycles. In this study, an innovative monitoring system based on milk P4 using the principles of synergistic control is presented. Instead of using filtering techniques and fixed thresholds, the present system employs an individually updated online model to describe the P4 profile, combined with a statistical process control chart to identify the cow’s fertility status. The inputs for the latter are the residuals of the online model, corrected for the concentration-dependent variability which is typical for milk P4 measurements. The objective of this paper is to present the developed methodology and give an indication of its use on farm. To this end, the system was validated on the P4 profiles of 38 dairy cows. The positive predictive value for luteolysis followed by estrus was 100%, meaning that the monitoring system picked up all estrous periods identified by the experts. Pregnancy or embryonic mortality was characterized by the absence or detection of luteolysis following an insemination, respectively. For thirteen cows, no luteolysis was detected by the system within the 25-32 days after insemination, indicating pregnancy, which was confirmed later by rectal palpation. It was also shown that the system is able to cope with deviating P4 profiles having prolonged follicular or luteal phases, which may suggest the occurrence of cysts. Future research is recommended for optimizing sampling frequency, prediction of the optimal insemination window and the establishment of rules to detect problems based on deviating P4 patterns.INTERPRETIVE SUMMARY. Progestrone-based online fertility monitoring. Adriaens.Milk progesterone based monitoring systems can be valuable for indicating fertility events in dairy cows, as the evolution of the milk progesterone levels can be related to acyclicity, estrus, pregnancy, and ovarian problems. We developed a system to translate raw progesterone measurements into clear information for the farmer, based on a mathematical model and a statistical control chart. In this way, a detailed image of a cow’s reproduction status on-farm can be obtained and fertility-related losses minimized.

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“…Visual observation of standing estrus is often cited as the industry standard for estrus detection; however, it has a 54.5% average estrus detection rate (At Taras and Spahr, 2001). Visual methods rely on observations of cows standing to be mounted, which is easily facilitated in freestall housing but is limited to when cows are let out for exercise in tiestall housing systems (Michaelis et al, 2014). Alternatives to visual observation for estrus detection include the use of various electronic aids, many of which have also been found to be more accurate in freestall housing systems (At Taras and Spahr, 2001).…”

Section: Introductionmentioning

confidence: 99%

Infrared thermography and behavioral biometrics associated with estrus indicators and ovulation in estrus-synchronized dairy cows housed in tiestalls

Marquez

Ambrose

Schaefer

et al. 2019

Journal of Dairy Science

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Most Canadian dairy herds operate in tiestall housing (61%), where average estrus detection rates may be lower than 54%. The objective of this study was to evaluate infrared thermography and behavioral biometrics as indicators of estrus in dairy cows. Eighteen cyclic multiparous cows (Synch) were subjected to an estrus synchronization protocol, and 18 pregnant cows (control) received a sham protocol on the same schedule and frequency as the cyclic cow treatment. A decline in plasma concentrations of progesterone and the appearance of a dominant follicle using transrectal ultrasonography were used as indirect indicators of estrus, and the disappearance of a dominant follicle was used to confirm ovulation. All cows were monitored via visual cameras to determine the frequency of treading, drinking, neighbor interaction, tail movement, lying, and shifting behaviors. Infrared thermograms were recorded at the eye, muzzle, cheek, neck, front right foot, front left foot, rump, flank, vulva area, tail head, and withers. To evaluate the accuracy of behavioral and thermal parameters, a predefined minimum acceptable value (i.e., threshold) for estrus alerts (>0.30 Youden J index and >0.60 area under the curve) was used. Ovulation was confirmed in 14 (77.7%) out of 18 Synch cows. Eye, cheek, neck, rump, flank, vulva area, and wither thermograms exhibited higher temperatures at 48 h [cycle threshold (Δt) = +0.30 to 1.20°C] and 24 h before ovulation compared with 4 d prior to ovulation (Δt = 0.06 to 0.11°C) and during ovulation day (Δt = 0.03 to 0.32°C) in the Synch group. In addition, control cows exhibited greater treading activity per day compared with Synch cows (20.84 ± 0.39 vs. 16.35 events/5 min ± 0.34), and tail movement frequency was greater in Synch cows compared with control cows (14.84 ± 2.7 vs. 10.11 ± 4.7 events/5 min). However, within Synch cows, tail movement was the only behavior that significantly increased in frequency 2 d before ovulation (11.81 ± 1.71 events/5 min) followed by a decrease in frequency 1 d before ovulation (4.67 ± 1.05 events/5 min) compared with ovulation day (0 d; 6.10 ± 1.25 events/5 min) and during luteolysis (3 d before ovulation; 6.01 ± 1.25 events/5 min). Upon evaluation of all variables (thermograms and behavior frequencies) as estrus indicators at 48 and 24 h before ovulation, treading and tail movements before milking and 9 thermal locations satisfied the predefined minimum acceptable value for estrus alerts. This study demonstrates that fluctuations in radiated temperature measured at specific anatomical locations and the frequency of tail movements and treading behaviors can be used as a noninvasive estrus alerts in multiparous cows housed in a tiestall system.

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Evaluation of Oestrous Detection in Dairy Cattle Comparing an Automated Activity Monitoring System to Visual Observation

Cited by 34 publications

References 43 publications

Automated estrous detection using multiple commercial precision dairy monitoring technologies in synchronized dairy cows

Automated estrous detection using multiple commercial precision dairy monitoring technologies in synchronized dairy cows

A novel system for online fertility monitoring based on milk progesterone

Infrared thermography and behavioral biometrics associated with estrus indicators and ovulation in estrus-synchronized dairy cows housed in tiestalls

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