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Efficiency, specificity and accuracy of oestrus detection by electronic heatmount detectors in dairy cows
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Heat detection is a key factor in the profitability of dairy herds. However, this detection demands a significant part of the breeder’s working time and is made difficult by the short duration and the discrete behavioural changes associated with oestrus in modern dairy cows. Progress has been made in monitoring cow with electronics, biosen...
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... activation triggers a radiowave transmission (0.4- km range), and the mounting data (cow ID, date of mount, time and duration of the sensor activation) are forwarded via a fixed radio antenna to a central computer in which a software algorithm analyses the mounting profile of each cow. The efficiency of oestrus detection for electronic heatmount systems is usually more than 85% with a high accuracy (87-100%; Table 1) ( Xu et al. 1998;At-Taras and Spahr 2001;Saumande 2002;Cavalieri et al. 2003a,b). The rate of detection with the HeatWatch Ò system, however, may be lower than desirable when used on commercial farms. ...
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... RFID systems have been used to measure feeding behaviour in feedlot steers [9] as well as activity levels in dairy cows [10]. In dairy production, it is a valid method for detecting the ovulation date [11] by measuring activity. One common system uses UHF RFID antennas, which are placed in different spots around the barn, and cows equipped with sensor ear tags. ...
Animal welfare strongly influences the health and performance of cattle and is an important factor for consumer acceptance. One parameter for the quantification of health status is the lying duration, which can be deployed for the early detection of possible production-related illnesses. Usually, 3D-accelerometers are the tool to detect lying duration in cattle, but the handling of bulls sometimes has special requirements because frequent manipulation in daily farming routines is often not possible. An ultrahigh-frequency (UHF) radio-frequency identification (RFID) system was installed in a beef cattle barn in Germany to measure the activity and lying time of bulls. Such UHF RFID systems are typically used for estrus detection in dairy cows via activity level, but can also be considered, for instance, as an early detection for lameness or other diseases. The aim of the study was to determine whether the estimations of activity level and lying duration can also be traced in husbandry systems for fattening bulls. Two groups of bulls (Uckermärker cattle, n = 10 and n = 13) of the same age were equipped with passive UHF RFID ear transponders. Three cameras were installed to proof the system and to observe the behaviour of the animals (standing, lying, and moving). Furthermore, accelerometers were attached to the hind legs of the bulls to validate their activity and lying durations measured by the RFID system in the recorded area. Over a period of 20 days, position (UHF RFID) and accelerometer data were recorded. Videos were recorded over a period of five days. The UHF RFID system showed an overall specificity of 95.9%, a sensitivity of 97.05%, and an accuracy of 98.45%. However, the comparison of the RFID and accelerometer data revealed residuals (ԑ) of median lying time (in minutes per day) for each group of ԑGroup1 = 51.78 min/d (p < 0.001), ԑGroup2 = −120.63 min/d (p < 0.001), and ԑGroup1+2 = −34.43 min/d (p < 0.001). In conclusion, UHF RFID systems can provide reliable activity and lying durations in 60 min intervals, but accelerometer data are more accurate.
... Real-time data collection and automated data transmission to base stations facilitated continuous monitoring [23]. A previous study reported that this technological intervention can enhance estrus detection accuracy by up to 80%-90%, surpassing the capabilities of traditional methods [24]. By facilitating breeding at the optimal time for conception, biosensor technology can significantly improve reproductive performance [25], contributing to Thai dairy farms' overall economic sustainability. ...
Background and Aim: Movement activity sensors are known for their potential to boost the reproductive performance of dairy cows. This study evaluated the effectiveness of these sensors on three Thai dairy farms (MK, NF, and CC), each using different sensor brands. We focused on reproductive performance at these farms and expanded our evaluation to include farmer satisfaction with sensor technology on five farms (MK, NF, CC, AP, and IP), allowing for a thorough analysis of both operational outcomes and user feedback.
... Therefore, the timing of insemination relative to ovulation is critical for fertility. Successful fertilisation requires the presence of spermatozoa in the uterine tubes at the correct time to fertilize the ovum [20,[22][23][24]64]. Thus, for a correct timing of insemination, the lifespan of bull spermatozoa must be considered, which ranges between 24 and 30 h [65], as well as the time required for sperm transport to the site of fertilization and their capacitation, which averages 6-8 h [1,[64][65][66]. ...
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.
... The boluses can detect behavioural changes associated with oestrus (Knight 2020) and alert the farmer to the appropriate insemination window. Further, milk progesterone (P4) concentration, which is often considered a gold-standard in evaluation of reproduction status, can be measured using biosensors (e.g. the Herd Navigator Lattec I/S, Hillerød, Denmark) (Saint-Dizier and Chastant-Maillard 2012). Video camera software also shows promise for use in oestrus detection. ...
Precision Livestock Farming (PLF) describes the use of technology within livestock systems to monitor animals, their products, and the environment. A main aim of PLF technologies is to provide continuous individual-animal data to farmers, which can then be used to inform management decisions and improve production and resource-use efficiency. For dairy and beef cattle, PLF technologies have historically been used to provide data on oestrus (specifically for dairy systems), production parameters, and animal health. As the sophistication of PLF technologies increases, so too does their capacity to measure more complex outcomes, such as indicators of animal welfare. This chapter provides an overview of the use of PLF technologies within dairy and beef cattle systems and concludes with a discussion on the implications of PLF for cattle welfare. Current and future PLF technologies are described, using the framework of the Five Freedoms to guide the discussion.
... Invasive methods frequently involve internal examinations or procedures that may cause the animal discomfort, such as electronic noses [4], accelerometers [5], pedometers, and pressure sensors [6]. In contrast, non-invasive methods, such as herders' visual observations, rely on external signs and behaviors, such as infrared thermography [7], surveillance cameras [8], and audio [9]. However, these conventional methods are prone to human error and require continuous monitoring, making them laborious and less reliable. ...
... Some aids in visual detection, such as chin ball markers and pressure-sensitive mount detection devices (Kamar Heatmount Detectors; Kamar Products Inc., Zionsville, IN, USA), could be helpful to an extent. The output of this method could be increased by enhancing the number of observations per day, but it requires to incur more labor and cost [38]. ...
... Limiting factors of this method include improper identification of animals and displacement of the device itself, or rubbing with other objects in the vicinity. This option is available to farmers at a high installation cost; this factor limits its use by most of them [38]. There is no doubt in the efficiency of the method, however, the performance of camera-assisted estrus detection can be enhanced by replacing this camera with a thermal camera with an added advantage of its potential capability to assess estrus detection through thermal variation. ...
... The threshold of increased intensity installed to detect estrus is a major factor in determining the efficiency of these instruments. There is reluctance among farmers to adopt these systems due to the initial high cost of installation [38]. ...
The productivity of dairy animals has significantly increased over the past few decades due to intense genetic selection. However, the enhanced yield performance of milk animals caused a proportional increase in stress and compromised reproductive efficiency. Optimal reproductive performance is mandatory for the sustainable production of dairy animals. Reproductive efficiency is marked by proper estrus detection and precise breeding to achieve maximum pregnancies. The existing conventional methods of estrus detection are somewhat labor intensive and less efficient. Similarly, the modern automated methods that rely on detecting physical activity are expensive, and their efficiency is affected by factors such as type of housing (tie stall), flooring, and environment. Infrared thermography has recently emerged as a technique that does not depend on monitoring physical activity. Furthermore, infrared thermography is a non-invasive, user-friendly, and stress-free option that aids in the detection of estrus in dairy animals. Infrared thermography has the potential to be considered a useful non-invasive tool for detecting temperature fluctuations to generate estrus alerts without physical contact in cattle and buffaloes. This manuscript highlights the potential use of infrared thermography to understand reproductive physiology and practical implementation of this technique through discussing its advantages, limitations, and possible precautions.
... management conditions. Management plays an important role in reproduction efficiency. A management practice like oestrus detection can make a difference in reproduction performance of dairy herds. Increasing oestrus detection can improve insemination results, calving interval and the total pregnancy rate,Frik et. al (2022), Helman et. al (2011) andSaint -Dizier et. al ...
This study was initiated to investigate the effect of parity, year of calving and season of calving on days open (DO), calving interval (CI) and number of inseminations per conception (NIPC) in the Holstein Friesian dairy herd of Alwaha Farm, east of Khartoum State, Sudan. Records of 166 cows that calved between the years 2016 to 2018 were examined. After removing records with missing data, the editing procedure resulted in 125 records for analysis. The data were analysed using a three-way ANOVA using a GLM model in the SPSS Statistical Software Package Version 21.00. Tukey test was used to determine the significant difference among means of analysed parameters. The result showed that parity number had no significant effect on days open, calving interval and number of inseminations per conception (P˃0.05). The year of calving had a highly significant effect on three traits, (P˂ 0.001). The season of calving had a highly significant effect (P˂ 0.001) on days open and calving interval and a significant effect (P˂ 0.05) on number of inseminations per conception. The interactions of parity × season of calving, parity × year of calving and parity × year of calving × season of calving had no significant effect (P˃ 0.05) on the studied traits. The interaction of season of calving × year of calving had significantly affected (P˂ 0.05) number of inseminations per conception. It is concluded that the reproduction traits studied were highly responsive to the year and season of calving under the prevailing management and environmental factors in that farm.
... management conditions. Management plays an important role in reproduction efficiency. A management practice like oestrus detection can make a difference in reproduction performance of dairy herds. Increasing oestrus detection can improve insemination results, calving interval and the total pregnancy rate,Frik et. al (2022), Helman et. al (2011) andSaint -Dizier et. al ...
... management conditions. Management plays an important role in reproduction efficiency. A management practice like oestrus detection can make a difference in reproduction performance of dairy herds. Increasing oestrus detection can improve insemination results, calving interval and the total pregnancy rate,Frik et. al (2022), Helman et. al (2011) andSaint -Dizier et. al ...
This study was initiated to investigate the effect of parity, year of calving and season of calving on days open (DO), calving interval (CI) and number of inseminations per conception (NIPC) in the Holstein Friesian dairy herd of Alwaha Farm, east of Khartoum State, Sudan. Records of 166 cows that calved between the years 2016 to 2018 were examined. After removing records with missing data, the editing procedure resulted in 125 records for analysis. The data were analysed using a three-way ANOVA using a GLM model in the SPSS Statistical Software Package Version 21.00. Tukey test was used to determine the significant difference among means of analysed parameters. The result showed that parity number had no significant effect on days open, calving interval and number of inseminations per conception (P˃0.05). The year of calving had a highly significant effect on three traits, (P˂ 0.001). The season of calving had a highly significant effect (P˂ 0.001) on days open and calving interval and a significant effect (P˂ 0.05) on number of inseminations per conception. The interactions of parity × season of calving, parity × year of calving and parity × year of calving × season of calving had no significant effect (P˃ 0.05) on the studied traits. The interaction of season of calving × year of calving had significantly affected (P˂ 0.05) number of inseminations per conception. It is concluded that the reproduction traits studied were highly responsive to the year and season of calving under the prevailing management and environmental factors in that farm.
... In dairy cattle, several tools are already available to automatically obtain the behaviour over time, such as the time spent grazing, ruminating, resting, and detect heat events (oestrus) [5,6] but no proper tools are available to detect disturbances such as stressful events or diseases in cattle. It is also worth mentioning that no disturbance detection tools exist for calves even though they are prone to a lot of different stressful events during the first few months (separation from the mother, weaning, dehorning, transport, etc) and vulnerable to certain diseases (neonatal diarrhoea, bovine respiratory disease, etc.) [7]. ...
While human activity has received much attention in time-series analysis research, animal activity has received much less attention. The monitoring of cattle in Precision Livestock Farming is a promising application area as it is reasonable to expect that cattle will be equipped with low-cost sensors for animal welfare reasons. In this paper, we present work on feature selection to detect disturbance in calves such as diseases or stressful events from accelerometer sensors attached to a neck-collar. While the long-term objective is to generate an alert when a disturbance is detected, the work presented here focuses on identifying the most discriminating accelerometer features to detect activity changes associated with a calf stressful event. For that purpose, we used accelerometer data from 47 calves who were dehorned at 16 days +/-10 days, a routine procedure known to be painful and stressful for calves. We calculated 7 primary features that could change after an occurrence of a disturbance, within a 24 hours period before and after dehorning for each calf, falling under the areas of energy expenditure and the structure of the calf activity. These features were explored under 17 timescales from 1 second to 24 hours to find the best timescale associated with each feature. First filtering with Mutual Information (MI) and Gini index was applied to reduce the candidate set of features for the second features selection with Random Forest Features Importance (RFFI). Performance were evaluated with Random Forest, k-Nearest Neighbor and Gaussian Naive Bayes models on test-sets to assess the relevancy of the selected features. Performance of all classifiers is improved or maintained when features from MI and Gini selection are used but decreased when further feature reduction with RFFI is applied. Therefore, based on MI and Gini selection, the most discriminating features are linked to activity peaks (maximum), amount of dynamic behaviors (standard-deviation) and activity structure (spectral entropy, Hurst exponent) with timescales ranging from 1 second to 24 hours depending on the features, which is consistent with animal welfare literature.
