Can video cameras replace visual estrus detection in dairy cows?

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.

Business analysis of IRT, Visual observation, and Ovsynch as breeding strategies in Alberta dairies

The dairy industry is searching for new technologies to address low (<50%) estrus detection. However, the lack of information on the potential economic benefits regarding new technology implementation has led some dairy producers to continue using conventional estrus detection methods (e.g. visual observation of standing to be mounted). The objective of this study was to compare the costs of infrared thermography (IRT), visual observation (VO) and ovulation synchronization (Ovsynch: OVS) as breeding strategies at different accuracy levels (Sensitivity [Se], Specificity [Sp]) and pregnancy rates (PR). The costs associated with Breeding, Feeding, Operation Costs, Return to Equity and Culling Risk per estrus detection rate (ER; 30-100%, conception rate for OVS; 30-100%), PR [PR per Parity group; 1-2 (50%), 3-4 (43%), and >4 (41%)], and ER accuracy determined the potential financial benefit of each breeding method for a representative farm. Breeding Cost results (Canadian dollars per cow; CAD/cow) showed a higher cost of OVS (138.99) as compared to VO (115.78) and IRT (127.69). Pregnancy Costs were affected by Breeding Cost; however, ER had a significant effect on PR expense for each method, IRT (ER; 30%: 210.38; 100%: 132.19), VO (ER; 30%: 205.93; 100%: 129.39), and OVS (ER; 30%: 247.21; 100%: 155.33). The minimum Se level with a positive Financial Effect for IRT and VO was 60% with a Sp of 100%, and for the OVS was Se 65% and Sp 100%. However, when the Se was 100% a positive Financial Effect was observed with a minimum Sp of 85% for IRT and 75% for VO. Culling Risk was reduced if ER increases differently depending on the parity group. Implementing of IRT as an estrus detection method yields a competitive breeding cost compared to VO and OVS. Further, breeding methods must accomplish at least ∼60% accuracy to have a positive net return.

Potential effects of hormonal synchronized breeding on genetic evaluations of fertility traits in dairy cattle: A simulation study

About 30% of producers use hormone protocols to synchronize ovulation and perform timed artificial insemination (AI) in Canada. Days from calving to first service (CTFS) and first service to conception (FSTC) become masked phenotypes leading to biased genetic evaluations of cows for these fertility traits. The objectives of this study were to (1) demonstrate and quantify the potential amount of bias in genetic evaluations, and (2) find a procedure that could remove the bias. Simulation was used for both objectives. The proposed solution was to identify cows that have been treated by hormone protocols, make their CTFS and FSTC missing, and perform a multiple trait analysis including traits that have high genetic correlations with CTFS and FSTC, and which are not affected by the hormone protocols themselves. A total of 12 scenarios (S1-S12) were tested, changing the percentage of herds and cows that were randomly selected to be under timed AI. Cows that were given hormone protocols had CTFS of 86 d and FSTC of 0, which were used in genetic evaluation. Four criteria were used to indirectly measure the presence of bias: (1) the correlation between true (TBV) and estimated (EBV) breeding values (accuracy); (2) the differences in the mean EBV of top 25, 50, and 75 sires; (3) changes in correlation between TBV and EBV rankings; and (4) the changes in mean EBV over the simulated generations. All criteria changed unfavorably and proportionally to the increased use of timed AI. The accuracy within each class of animals (cows, dams, or sires) decreased proportionally with increased use of timed AI, varying from 0.32 (S12) to 0.52 (S1) for bull EBV for CTFS. The average EBV of the top sires (best 25, 50, 75, or 100 sires) approached population average EBV values when increasing the number of treated animals. The sire rank correlation between EBV and TBV within simulated scenarios was smaller for scenarios with more synchronized animals, going from 0.38 (S12) to 0.67 (S1). The long-term use of hormonal synchronized cows clearly decreased the mean EBV over generations in the population for CTFS and FSTC. The inclusion of genetically correlated traits in a multiple trait model was effective in removing the bias due to the presence of hormonal synchronized cows. However, given the constraints within the simulation, it is important that further investigation with real data is conducted to determine the true effect of including timed AI records within genetic evaluations of fertility traits in dairy cattle.

A 100-Year Review: Practical female reproductive management

Basic knowledge of mechanisms controlling reproductive processes in mammals was limited in the early 20th century. Discoveries of physiologic processes and mechanisms made early in the last century laid the foundation to develop technologies and programs used today to manage and control reproduction in dairy cattle. Beyond advances made in understanding of gonadotropic support and control of ovarian and uterine functions in basic reproductive biology, advancements made in artificial insemination (AI) and genetics facilitated rapid genetic progress of economically important traits in dairy cattle. Technologies associated with management have each contributed to the evolution of reproductive management, including (1) hormones to induce estrus and ovulation to facilitate AI programs; (2) pregnancy diagnosis via ultrasonography or by measuring conceptus-derived pregnancy-associated glycoproteins; (3) estrus-detection aids first devised for monitoring only physical activity but that now also quantitate feeding, resting, and rumination times, and ear temperature; (4) sex-sorted semen; (5) computers and computerized record software packages; (6) handheld devices for tracking cow location and retrieving cow records; and (7) genomics for increasing genetic progress of reproductive and other economically important traits. Because of genetic progress in milk yield and component traits, the dairy population in the United States has been stable since the mid 1990s, with approximately 9 to 9.5 million cows. Therefore, many of these technologies and changes in management have been developed in the face of increasing herd size (4-fold since 1990), and changes from pastoral or dry-lot dairies to increased housing of cows in confinement buildings with freestalls and feed-line lockups. Management of groups of "like" cows has become equally important as management of the one. Management teams, including owner-managers, herdsmen, AI representatives, milkers, and numerous consultants dealing with health, feeding, and facilities, became essential to develop working protocols, monitor training and day-to-day chores, and evaluate current trends and revenues. Good management teams inspect and follow through with what is routinely expected of workers. As herd size will undoubtedly increase in the future, practical reproductive management must evolve to adapt to the new technologies that may find more herds being milked robotically and applying technologies not yet conceived or introduced.

Quantification of Urine Elimination Behaviors in Cats with a Video Recording System

Background

Urinary disorders in cats often require subjective caregiver quantification of clinical signs to establish a diagnosis and monitor therapeutic outcomes.

Objective

To investigate use of a video recording system (VRS) to better assess and quantify urination behaviors in cats.

Animals

Eleven healthy cats and 8 cats with disorders potentially associated with abnormal urination patterns.

Methods

Prospective study design. Litter box urination behaviors were quantified with a VRS for 14 days and compared to daily caregiver observations. Video recordings were analyzed by a behavior analysis software program.

Results

The mean number of urinations per day detected by VRS (2.5 ± 0.7) was significantly higher compared with caregiver observations (0.6 ± 0.6; P < .0001). Five cats were never observed in the litter box by their caregivers. The mean number of urinations per day detected by VRS was significantly higher for abnormal cats (2.9 ± 0.7) compared with healthy cats (2.1 ± 0.7; P = .02); there were no apparent differences in frequency between these groups reported by caregivers (0.7 ± 1.0 and 0.5 ± 1.0, respectively). There were no differences in mean urination time between healthy and abnormal cats as determined by VRS or caregivers. Mean cover‐up time determined by VRS was significantly longer in healthy cats (22.7 ± 12.9 seconds/urination) compared with abnormal cats (8.7 ± 12.9 seconds/urination; P = .03); differences in cover‐up time were not detected by caregivers.

Conclusions and Clinical Importance

Caregivers commonly underestimate urination frequency in cats when compared to video‐based observations. Video recording appears to facilitate objective assessment of urination behaviors and could be of value in future clinical studies of urinary disorders in cats.