Estrus Detection and Dairy Cow Identification with Cascade Deep Learning for Augmented Reality-Ready Livestock Farming.

Accurate prediction of the estrus period is crucial for optimizing insemination efficiency and reducing costs in animal husbandry, a vital sector for global food production. Precise estrus period determination is essential to avoid economic losses, such as milk production reductions, delayed calf births, and disqualification from government support. The proposed method integrates estrus period detection with cow identification using augmented reality (AR). It initiates deep learning-based mounting detection, followed by identifying the mounting region of interest (ROI) using YOLOv5. The ROI is then cropped with padding, and cow ID detection is executed using YOLOv5 on the cropped ROI. The system subsequently records the identified cow IDs. The proposed system accurately detects mounting behavior with 99% accuracy, identifies the ROI where mounting occurs with 98% accuracy, and detects the mounting couple with 94% accuracy. The high success of all operations with the proposed system demonstrates its potential contribution to AR and artificial intelligence applications in livestock farming.

Effect of reproductive management programs that prioritized artificial insemination at detected estrus or timed artificial insemination on the economic performance of primiparous Holstein cows of different genetic merit for fertility.

The objective of this randomized controlled experiment was to evaluate the effect of reproductive management programs that prioritized artificial insemination (AI) at detected estrus (AIE) or timed AI (TAI) during the first lactation on the economic performance of dairy cows of different genomically enhanced predicted transmitting ability for fertility. Lactating primiparous Holstein cows from 6 commercial farms were stratified into high, medium, and low fertility groups based on a reproduction index value calculated from multiple genomically enhanced predicted transmitting abilities to predict the number of days to achieve pregnancy. Within herd and fertility group, cows were randomly assigned either to a program that prioritized AIE (P-AIE; n = 1,416) and used TAI for cows not AIE for all AI services or another that prioritized TAI and had an extended voluntary waiting period for first service and prioritized TAI for second and greater AI services (P-TAI; n = 1,338). Cash flow (CF) per cow accumulated for the experimental (first) and second calving interval (CIN) and cash flow per slot per 28 mo after calving in the experimental lactation were calculated. Market and rearing heifer cost values were used for estimating CF. For cows in the high fertility group, a positive effect of delayed pregnancy on milk income during the first lactation was observed (+$248 for P-TAI) but was insufficient to generate significant differences in CF between treatments mainly because of milk income compensation in the second lactation (+$125 for P-AIE) and minor reductions in reproductive cost and gains in calf value for the P-AIE treatment. In this regard, CF for 2 CIN was greater for the P-TAI treatment by $61 and $86 for market and rearing replacement heifer cost, respectively. Similarly, CF per slot was favorable to the P-TAI treatment but only by $13 and $47 for market and rearing replacement heifer cost, respectively. For cows in the low fertility group, CF was numerically in favor of the P-AIE treatment due to a pregnancy and herd exit dynamics that resulted in gains in milk income over feed cost during the first ($29) and second ($113) lactation. Differences in CF for the 2 CIN were $58 and $47 for market or rearing heifer value, respectively, and $77 and $19 for market and rearing heifer values, respectively for the slot analysis. Differences in CF between cows of different genetic merit for fertility were consistent across treatment and estimation method. Of note, cows in the low fertility group had greater CF than cows in the high fertility group in all comparisons, ranging from $198 per cow for 2 CIN to as much as $427 per slot. For the low fertility group, greater milk production contributed directly (milk income over feed cost) and indirectly (reduced culling) to increased CF. We concluded that genetic merit for fertility and CF are associated because cows of inferior genetic potential for fertility had greater CF than cows of superior genetic for fertility despite some increased costs and reduced revenues. Also, the magnitude of the CF differences observed for cows of different genetic merit for fertility managed with the P-AIE or P-TAI program may be valuable to commercial dairy farms but did not allow to conclusively support the choice of a type of reproductive management strategy for cows of different genetic merit for fertility.

Targeted reproductive management for lactating Holstein cows: Reducing the reliance on exogenous reproductive hormones.

Adoption of automated monitoring devices (AMD) affords the opportunity to tailor reproductive management according to the cow's needs. We hypothesized that a targeted reproductive management (TRM) would reduce the use of reproductive hormones while increasing the percentage of cows pregnant 305 d in milk (DIM). Holstein cows from 2 herds (n = 1,930) were fitted with an AMD at 251.0 ± 0.4 d of gestation. Early-postpartum estrus characteristics (EPEC; intense estrus = heat index ≥70; 0 = minimum, 100 = maximum) of multiparous cows were evaluated at 40 (herd 1) or 41 (herd 2) DIM and EPEC of primiparous cows were evaluated at 54 (herd 1) or 55 (herd 2) DIM. Control cows received the first artificial insemination at fixed time (TAI; primiparous, herd 1 = 82 and herd 2 = 83 DIM; multiparous, herd 1 = 68 and herd 2 = 69 DIM) following the Double-Ovsynch (DOV) protocol. Cows enrolled in the TRM treatment were managed as follows: (1) cows with at least one intense estrus were inseminated upon AMD detected estrus for 42 d and, if not inseminated, were enrolled in the DOV protocol; and (2) cows without an intense estrus were enrolled in the DOV protocol at the same time as cows in the control treatment. Control cows were re-inseminated based on visual or patch aided detection of estrus, whereas TRM cows were re-inseminated as described for control cows with the aid of the AMD. Cows received a GnRH injection 27 ± 3 d after insemination and, if diagnosed as nonpregnant, completed the 5-d Cosynch protocol and received TAI 35 ± 3 d after insemination. Among cows in the TRM treatment, 55.8 and 42.9% of primiparous and multiparous cows, respectively, received the first insemination in spontaneous estrus. The interaction between treatment and parity affected pregnancy 67 d after the first AI (primiparous: control = 37.6%, TRM = 27.4%; multiparous: control = 41.0%, TRM = 44.7%). The TRM treatment increased re-insemination in estrus (control = 48.3%, TRM = 70.5%). Pregnancy 67 d after re-inseminations tended to be affected by the interaction between treatment and EPEC (no intense estrus: control = 25.3%, TRM = 32.0%; intense estrus: control = 32.9%, TRM = 32.2%). The interaction between treatment and EPEC affected pregnancy by 305 DIM (no intense estrus: control = 80.8%, TRM = 88.2%; intense estrus: control = 87.1%, TRM = 86.1%). Treatment did not affect the number of reproductive hormone treatments among cows that had not had an intense estrus (control = 10.5 ± 0.3, TRM = 9.1 ± 0.2 treatments/cow), but cows in the TRM treatment that had an intense estrus received fewer reproductive hormone treatments than cows in the control treatment (2.0 ± 0.1 vs. 9.6 ± 0.2 treatments/cow). Selecting multiparous cows for first AI in estrus based on EPEC reduced the use of reproductive hormones without impairing the likelihood of pregnancy to first AI. The use of AMD for re-insemination expedited the establishment of pregnancy among cows that did not display an intense estrus early postpartum.

Identification of oestrus cows based on vocalisation characteristics and machine learning technique using a dual-channel-equipped acoustic tag.

Timely and accurate detection of oestrus in cows is an essential element of the good management of dairy farms. At present, the detection of cows in oestrus by acoustic means is impeded by the problems of filtering, incomplete feature selection, and poor recognition accuracy. To overcome these difficulties, this study proposes a sound detection method for cows in oestrus based on machine learning technology using an optimal feature combination and an optimal time window. Firstly, a dual-channel sound detection tag consisting of a unidirectional microphone and an omnidirectional microphone (OM) was developed. The Least Mean Squares adaptive algorithm based on wavelet thresholds was used to filter the signals from the OM, and the dual-channel endpoint detection algorithm was used to identify the lowing of individual cows. The Friedman analysis was then used to select the sound features with significant differences before and after oestrus in terms of time, frequency, and cepstrum, and these were used to determine the most acceptable feature combination. We then analysed the effects of Back Propagation Neural Network (BPNN), Cartesian Regression Tree, Support Vector Machine, and Random Forest classification on the accuracy, precision, sensitivity, specificity, and F1 score of oestrus discrimination. Different time windows were used, and the discrimination performance of these algorithms was evaluated using the Area under Receiver Operating Characteristic Curve to find the most satisfactory match between the time window and the recognition algorithm. The dual-channel acoustic tag's accuracy, precision, sensitivity, and specificity results were 91.25, 98.83, 91.75, and 83.68%, respectively. BPNN with the 70 ms time window and the feature combination (spectral roll-off + spectral flatness + Mel-Frequency Cepstrum Coefficients) was confirmed as the most suitable oestrus recognition method. The average accuracy, precision, sensitivity, specificity, and F1 score of this method were 97.62, 98.07, 97.17, 97.19, and 97.63%, respectively. Based on these results, the approach was shown to be a feasible means of oestrus detection in dairy cows. Based on its ability to differentiate cows and its consistency, it was demonstrated that sound has the potential to replace accelerometers as an early indicator of oestrus in dairy cows.

Effect of a targeted reproductive management program designed to prioritize insemination at detected estrus and optimize time to insemination on the reproductive performance of lactating dairy cows.

The primary objective of this randomized controlled experiment was to evaluate the insemination dynamic and reproductive performance of cows managed with a targeted reproductive management (TRM) program designed to prioritize artificial insemination (AI) at detected estrus (AIE) and optimize timing of AI by grouping cows based on detection of estrus during the voluntary waiting period (VWP). Our secondary objective was to evaluate reproductive outcomes for cows with or without estrus during the VWP. Lactating Holstein cows fitted with an ear-attached sensor for detection of estrus were randomly assigned to a TRM treatment that prioritized AIE based on detection of estrus during the VWP (TP-AIE; n = 488), a non-TRM treatment that prioritized AIE (P-AIE; n = 489), or an all timed AI (TAI) treatment with extended VWP (ALL-TAI; n = 491). In TP-AIE, cows with or without automated estrus alerts (AEA) recorded during the VWP received AIE if detected in estrus for at least 31 ± 3 or 17 ± 3 d after a 49 d VWP, respectively. Cows not AIE with or without AEA during the VWP received TAI after Ovsynch with progesterone supplementation and 2 PGF2α treatments (P4-Ov) at 90 ± 3 or 74 ± 3 d in milk (DIM), respectively. In P-AIE, cows received AIE if detected in estrus for 24 ± 3 d after a 49 d VWP, and if not AIE received TAI at 83 ± 3 DIM after P4-Ov. In ALL-TAI, cows received TAI at 83 ± 3 DIM after a Double-Ovsynch protocol. Data were analyzed by logistic and Cox's proportional hazard regression. The proportion of cows AIE did not differ for TP-AIE (71.0%) and P-AIE (74.6%). Overall P/AI at 39 d after first service was greater for the ALL-TAI (47.6%) than for the P-AIE (40.2%) and TP-AIE (39.5%) treatments. The hazard of pregnancy up to 150 DIM was greater for cows in TP-AIE (hazard ratio = 1.2; 95% confidence interval: 1.1-1.4) and P-AIE (hazard ratio = 1.2; 95% confidence interval: 1.1-1.4) than for cows in the ALL-TAI treatment which resulted in median time to pregnancy of 89, 89, and 107 d. Conversely, the proportion of cows pregnant at 150 DIM did not differ (ALL-TAI 78.5%, P-AIE 76.3%, TP-AIE 76.0%). Except for a few outcomes for which no difference was observed, cows detected in estrus during the VWP had better performance than cows not detected in estrus. Cows with AEA during the VWP were more likely to receive AIE, had greater P/AI, and greater pregnancy rate up to 150 DIM regardless of first service management. We conclude that a TRM program designed to prioritize AIE by grouping cows based on detection of estrus during the VWP was an effective strategy to submit cows for first service resulting in similar or improved performance than a non-TRM program that prioritized AIE or an all-TAI program with extended VWP. Also, AEA recorded during the VWP might be used as a strategy for identifying subgroups of cows with different reproductive performance.

Evaluating automated infrared thermography and vulva exposure tracking as components of an estrus detection platform in a commercial dairy herd.

The primary objective of this study was to develop an automated infrared thermography platform (Estrus BenchMark) capable of measuring skin temperature and tail movements as a means of identifying cows in estrus. The secondary objective was to evaluate the accuracy of Estrus BenchMark to detect estrus compared to in-line milk progesterone (P4) analysis (Herd Navigator System) in a commercial dairy herd managed under a robotic milking system. Data were collected on forty-six cows from 45 to 120 d after calving. Cows were flagged in estrus when milk P4 fell below 5 ng/mL. The Estrus BenchMark true positive estrus alerts (Sensitivity; Se%) were compared to Herd Navigator System estrus alerts at different time-windows (±12 h, ±24 h, ±48 h, and ±72 h) relative to the Estrus BenchMark estrus alerts for all the estrus alerts (AE) and confidence-quality estrus (CQE; >80% quality) alerts identified by Herd Navigator System. The Estrus BenchMark captured skin temperature and tail movements resulting in vulva exposure (left tail movements, LTail; right tail movements, RTail; and pooled tail movements, PTail) for each milking event. Skin temperature tended to increase when the milk P4 concentration (Least-Squares Means ±â€¯SE) dropped for AE (estrus day [d 0]; P4; 3.51 ±â€¯0.05 ng/mL, Skin temperature; 33.31 ±â€¯2.38 °C) compared with d -7 (P4; 20.22 ±â€¯0.73 ng/mL; Skin temperature: 32.05 ±â€¯3.77 °C). The increase in skin temperature, however, was significant in cows with CQE > 80% at d 0 (32.75 ±â€¯0.29 °C) compared to d -7 (31.80 ±â€¯0.28 °C). The prevalence of tail movements to expose vulva was greater (P = 0.01) in AE at d 0 (LTail: 62.50%; PTail; 68.75%; and RTail: 56.25%) compared with d -7 (LTail: 18.75%; PTail: 9.37%: and RTail: 9.37%), and d +4 (LTail: 9.37%; PTail: 9.37%; and RTail: 12.5%). Moreover, the higher prevalence of tail movements at d 0 was observed in cows with CQE > 80% (LTail; 65%, PTail; 80%, and RTail; 70%) compared to those with CQE < 80%. The highest Estrus BenchMark Youden index (YJ; 0.45), diagnostic odds ratio (DOR; 9.04), and Efficiency (0.77) were achieved for AE in a ±48 h window and at ±72 h window for CQE (YJ; 0.66, DOR; 25.29, and Efficiency 0.76) relative to Herd Navigator System estrus alerts. The highest Estrus BenchMark resulted in 58% estrus detection rates for AE and 80% for cows with CQE compared to the Herd Navigator System.

Motivations and attitudes of Brazilian dairy farmers regarding the use of automated behaviour recording and analysis systems.

In this Research Communication we investigate the motivations of Brazilian dairy farmers to adopt automated behaviour recording and analysis systems (ABRS) and their attitudes towards the alerts that are issued. Thirty-eight farmers participated in the study distributed into two groups, ABRS users (USERS, n = 16) and non-users (NON-USERS, n = 22). In the USERS group 16 farmers accepted being interviewed, answering a semi-structured interview conducted by telephone, and the answers were transcribed and codified. In the NON-USERS group, 22 farmers answered an online questionnaire. Descriptive analysis was applied to coded answers. Most farmers were young individuals under 40 years of age, with undergraduate or graduate degrees and having recently started their productive activities, after a family succession process. Herd size varied with an overall average of approximately 100 cows. Oestrus detection and cow's health monitoring were the main reasons given to invest in this technology, and cost was the most important factor that prevented farmers from purchasing ABRS. All farmers in USERS affirmed that they observed the target cows after receiving a health or an oestrus alert. Farmers believed that they were able to intervene in the evolution of the animals' health status, as the alerts gave a window of three to four days before the onset of clinical signs of diseases, anticipating the start of the treatment.The alerts issued by the monitoring systems helped farmers to reduce the number of cows to be observed and to identify pre-clinically sick and oestrous animals more easily. Difficulties in illness detection and lack of definite protocols impaired the decision making process and early treatment, albeit farmers believed ABRS improved the farm's routine and reproductive rates.

Comparison of pregnancy per AI of heifers inseminated with sex-sorted or conventional semen after oestrus detection or timed artificial insemination.

The objective of the study was to compare the fertility after using sex-sorted or conventional semen either with oestrus detection (EST) or timed artificial insemination (TAI) in Holstein heifers. Holstein heifers were randomly assigned to one of the following treatments in a 2 × 2 factorial design. Heifers in the EST group were inseminated with sex-sorted (n = 114) or conventional semen (n = 100) after spontaneous or induced oestrus. Heifers in the TAI, subjected to the 5-day Cosynch+Progesterone protocol (GnRH+P4 insertion-5d-PGF2α +P4 removal-1d-PGF2α -2d-GnRH+TAI), were inseminated with sex-sorted (n = 113) or conventional semen (n = 88). Statistical analyses were performed using PROC GLIMMIX procedure of SAS 9.4 (SAS Institute Inc., Cary, NC). Overall P/AI was 60.7% for EST and 54.2% for TAI regardless of types of semen and 68.1% for conventional and 48.9% for sex-sorted semen regardless of insemination strategies. Fertility of heifers inseminated with either sex-sorted (53.5%; 44.2%) or conventional (69.0%; 67.0%) semen did not differ between EST and TAI respectively. Besides, the interaction between the semen type and the insemination strategy was not significant for P/AI. The embryonic loss was significantly greater with sex-sorted semen (17.1%) compared to conventional semen (1.6%). There was no sire effect with sex-sorted semen on P/AI (52.6% vs. 46.2%) and embryonic loss (16.4% vs. 18.0%). As expected, sex-sorted semen resulted in more female calves (89.8% vs. 51.6%) than conventional semen. Thus, sex-sorted semen can be used with 5-day Cosynch+Progesterone protocol to eliminate the inadequate oestrus detection and to increase female calves born in dairy heifers.

Effect of types of breeding on embryo survival following first AI in lactating Holstein cows.

The main objective was to investigate the effects of timed-AI protocols versus AI following oestrus detection on circulating progesterone (P4) and embryo survival after first service in Holstein cows. Cycling status was determined by ultrasonography and by plasma P4 concentrations 14 and 26 days after calving, and only cows with a corpus luteum and/or P4 ≥ 1 ng/ml were used. Cows were randomly allocated to one of three types of breeding: DO (n = 80), received GnRH-7d-PGF2α-3d-GnRH and Ovsynch56 was initiated 7 days later; G7G (n = 70), received PGF2α-2d-GnRH and Ovsynch56 (GnRH-7d-PGF2α-56h-GnRH-16h-AI) was initiated 7 days later; or AI based on oestrus detection, EDAI (n = 60). Progesterone was also determined at AI and 8, 16, 18 and 20 days after AI; ISG15 and MX2 mRNA abundance were determined 16 days after AI. Mean plasma P4 at AI was greater in the EDAI group compared with DO and G7G groups, while after AI, P4 was greater in DO and G7G groups compared with EDAI group. However, the percentage of cows with a concentration of P4 < 0.8 ng/ml at AI did not differ among groups. Relative mRNA abundance of ISG15 and MX2 was greater in the DO and G7G groups compared to those in EDAI group. Pregnancy per AI 16, 32 and 60 days after AI was greater (p < .05) in cows in the DO group compared with those in EDAI group (47.5%, 38.8% and 36.3% vs. 30.0%, 21.7% and 15.0%). Pregnancy losses between 16 and 60 days after AI were greater (p < .05) in cows in the EDAI (50.0%) group compared to those subjected to DO (23.7%) or G7G (24.1%). In conclusion, the use of timed-AI synchronization protocols resulted in greater circulating P4 concentrations post-AI and greater embryo survival following first service in lactating Holstein cows.

An attempt at estrus detection in cattle by continuous measurements of ventral tail base surface temperature with supervised machine learning.

We aimed to determine the effectiveness of estrus detection based on continuous measurements of the ventral tail base surface temperature (ST) with supervised machine learning in cattle. ST data were obtained through 51 estrus cycles on 11 female cattle (six Holsteins and five Japanese Blacks) using the tail-attached sensor. Three estrus detection models were constructed with the training data (n = 17) using machine learning techniques (random forest, artificial neural network, and support vector machine) based on 13 features extracted from sensing data (indicative of estrus-associated ST changes). Estrus detection abilities of the three models on test data (n = 34) were not statistically different among models in terms of sensitivity and precision (range 50.0% to 58.8% and 60.6% to 73.1%, respectively). The relatively poor performance of the models might indicate the difficulty of separating estrus-associated ST changes from estrus-independent fluctuations in ST.

Estrous detection with an activity and rumination monitoring system in an organic grazing and a low-input conventional dairy herd.

The objective of this study was to evaluate estrous detection using a physical activity and rumination monitoring system in a seasonal calving organic grazing (GRAZ) and a low-input conventional (ZEROGRAZ) dairy herd. The study was conducted from June 2014 to August 2017. During each breeding season, physical activity and rumination were monitored electronically using an activity and rumination monitoring system (HR-LD tags; SCR Engineers Ltd., Netanya, Israel). Signals resulting from the activity and rumination monitoring system for individual cows were used to determine consistency of the values using this system with the breeding date of cows. Breeding dates were determined using EstrotectTM patches. The study included 1,463 breeding dates from 531 cows. Within the GRAZ herd, during the summer breeding season the monitoring system was less sensitive for estrous detection (33.8 %) than during the winter breeding season (79.8 %).The activity and rumination monitoring system had a sensitivity of 56.7 %, specificity of 99.3 % and positive predictive value of 59.8 % for the GRAZ herd, and sensitivity of 70.1 %, specificity of 99.2 % and positive predictive value of 66.3 % for the ZEROGRAZ herd. For cows that were determined to be pregnant and subsequently calved as a result of the mating, the sensitivity for estrous detection was slightly greater for the GRAZ (60.7 %) and ZEROGRAZ (72.5 %) herds. The activity and rumination monitoring system evaluated in this study has potential for estrous detection in grazing herds during the winter breeding season and in small-input dairy herds during both, winter and summer breeding seasons.

Effects of twice daily compared with split-time estrous detection on pregnancy percentage in recipient beef cows.

Objectives were to compare pregnancy percentages per embryo transfer (P/ET) in recipient beef cows following twice daily compared with split-time estrous detection and to determine associations of dominant follicle diameter, CL volume and progesterone concentrations. All cows (n = 695) were treated to synchronize time of estrus among cows using a CIDR + Select-Synch treatment regimen and randomly assigned to twice-daily or split-time estrous detection (CS-DEET or CS-SEET, respectively). Cows in the CS-DEET group were observed twice daily (eight times) for estrus until 96 h after the time of PGF2α administration, whereas cows in the CS-SEET group were observed twice (64 and 84 h after PGF2α). In 280 recipient cows, blood sampling (for progesterone) and ultrasonographic assessment of dominant follicle diameter were conducted 48 h after the time of PGF2α administration. At 7 d after estrus, the CL was imaged and there was transfer of a frozen-thawed embryo into cows with a CL ≥ 1.5 cm. There were positive correlations between follicle diameter and CL volume (rs = 0.827; P < 0.001) and CL volume and progesterone concentration (rs = 0.680; P < 0.001). Progesterone and CL volume differed between cows in CS-SEET and CS-DEET groups P < 0.05), however, percentage P/ET for cows in the CS-SEET and CS-DEET groups did not differ (P > 0.1). Dominant follicle diameter, CL volume and progesterone concentrations were greater in pregnant compared with nonpregnant cows. In conclusion, percentage P/ET did not differ when there was twice daily and split-time estrous detection highlighting the value of this approach in beef enterprises.

Effect of estrous detection strategy on pregnancy outcomes of lactating Holstein cows receiving artificial insemination and embryo transfer.

Objectives of the current experiment were to evaluate the effects on reproductive performance of adding an automated estrous detection (AED) device to the reproductive management of Holstein cows. In addition, we aimed to determine whether the AED device would equally influence the reproductive performance of cows receiving artificial insemination and those receiving embryo transfer. Cows (n = 1,244) were observed daily for estrous detection by trained farm personnel with the aid of a tail head mounting device. Cows (n = 641) enrolled in the AED treatment were fitted with a neck-mounted automated estrus detection device, and cows enrolled in the control (CTRL, n = 603) treatment were not fitted with the AED device. Cows not detected in estrus by 54 ± 3 DIM received 1 injection of PGF2α, and those not detected in estrus by 68 ± 3 DIM were enrolled in an ovulation synchronization protocol. The hazard of first service tended to be affected by treatment [CTRL: referent, AED: adjusted hazard ratio (AHR) = 1.11, 95% confidence interval (CI) = 0.98, 1.25], and we determined a tendency for the AED treatment to reduce the proportion of cows receiving the first service at fixed time (39.7 ± 5.7 vs. 45.5 ± 5.8%). After the first service, high-producing cows enrolled in the AED treatment were more likely to be pregnant (19.1 ± 2.4 vs. 31.8 ± 3.0%), but no differences between the AED and CTRL treatments were observed among low-producing cows (24.9 ± 2.9 vs. 24.7 ± 2.9%). The hazard of second service was affected by treatment (CTRL: referent, AED: AHR = 1.22, 95% CI = 1.01, 1.47), and the AED treatment reduced the proportion of cows receiving the second service at fixed time compared with the CTRL treatment (15.7 ± 2.2 vs. 21.9 ± 2.5%). After the second service, the AED treatment tended to increase the proportion of cows pregnant (31.0 ± 3.0 vs. 24.9 ± 2.6%) and tended to reduce the proportion of cows that lost pregnancy between the first and second pregnancy exams (9.7 ± 3.3 vs. 16.7 ± 4.6%). The interaction between treatment and type of service did not affect percentage of cows pregnant and pregnancy loss to the first and second services. The hazard of pregnancy was affected by the interaction between treatment and milk yield, in that cows with above the median milk yield in the AED treatment became pregnant at a faster rate than CTRL cows, but no difference between treatments was observed among cows with milk yield below the median. Cows with above the median milk yield had shorter duration of estrus and were less likely to have activity peak at estrus ≥89 (0 = minimum, 100 = maximum). The current experiment suggests that AED devices may improve reproductive performance not only by increasing service rates but also by improving accuracy of estrous detection. According to the current experiment, high-producing cows may benefit most from the addition of AED devices to reproductive management.

Association between hoof lesions and fertility in lactating Jersey cows.

The objectives of this study were to evaluate the association between hoof lesions and fertility in dairy cows. Lactating Jersey cows (n = 1,639) were enrolled at 20 ± 3 d in milk (D20), examined and treated for presence of hoof lesions (HL), and evaluated for body condition score (BCS). Afterward, they were managed according to standard farm procedures, including estrus detection and presynchronization and a 5 d Cosynch-72 protocol for cows that failed to show estrus. Ovaries were scanned at 27 and 41 ± 3 d in milk, and cows with a corpus luteum greater than 20 mm on at least 1 exam were considered cyclic. At 120 ± 3 d in milk (D120), cows were re-examined for HL and BCS. Cows were classified at D20 according to HL status as healthy (n = 1,197) or having HL (n = 429), and according to HL category as healthy (n = 1,197) or having a sole hemorrhage (n = 280), noninfectious HL (sole ulcer, toe ulcer, or white line disease; n = 113), or infectious HL (digital dermatitis and foot rot; n = 36). Cows with HL at D20 had reduced odds of being cyclic (38.3 vs. 51.9%) and a longer interval from calving to first service (58 vs. 51 d) compared with healthy cows. Cows with infectious HL at D20 had reduced odds of pregnancy to first service (16.7 vs. 38.3%) compared with healthy cows. Cows with sole hemorrhage at D20 were more likely to lose pregnancies between d 32 and 64 after the first service postpartum compared with healthy cows (10.5 vs. 5.2%). Cows with sole hemorrhage at D20 had a smaller hazard of pregnancy (67.9 vs. 75.5%) at 150 d in milk and more days open (88 vs. 77d) compared with healthy cows. To assess the relationship between the development of HL and fertility, cows were classified as healthy (no HL at D20 and D120; n = 308), cured (any HL at D20 and no HL at D120; n = 72), new HL (no HL at D20 and any HL at D120; n = 597), and chronic (any HL at D20 and D120; n = 226). Sole hemorrhage accounted for 93% of new HL. The proportions of cows with HL at D20 and D120 were 26.9 and 68.4%, respectively. We found no evidence for a difference in pregnancy hazard at 150 d in milk between cows that remained healthy (n = 308) and cows that developed new HL (n = 597). Hoof lesions at D20, but not new HL, were associated with decreased odds of cyclicity, longer interval from calving to first service postpartum, and reduced pregnancy hazard in Jersey cows. The effect of an HL diagnosis in early lactation and management to reduce chronic HL in dairy cows warrants further investigation.

A novel method to detect bovine sex pheromones using l-tyrosine-capped silver nanoparticles: Special reference to nanosensor based estrus detection.

In the present study, a simple and a selective colorimetric method for pheromone detection to diagnose estrus in cattle was established based on the l-tyrosine functionalized silver nanoparticles (l-TyrAgNPs). The synthesized silver nanoparticles was spotted by color change (colorless to pale yellow) due to surface plasmon resonance (SPR). In order to confirm, Ag nanoparticles was characterized by field emission scanning electron microscopy (FESEM), dynamic light scattering (DLS) and zeta potential, X-ray diffraction (XRD) and UV- Vis spectrophotometer. It was found that the pre-colored Ag colloids could be turned from yellow to reddish-brown by the addition of the sex pheromones such as acetic acid or propionic acid, which may have potential application in the colorimetric sensor. The augmented optical nature of nanoparticles furnishes a suitable base to develop a colorimetric sensor for bovine sex pheromones detection. In addition, the computational analyses are critically required to validate residual interactions of bovine odorant-binding protein (OBP) with pheromones. The method was successfully applied to the detection of acetic acid or propionic acid using a biological molecule l-Tyr AgNPs. These results clearly indicate that the biosynthesis of l-Tyr AgNPs can be used as a promising colorimetric sensor for accurate time of estrus prediction in bovine.

Pregnancy rates to fixed-time AI in Bos indicus-influenced beef cows using PGF2α with (Bee Synch I) or without (Bee Synch II) GnRH at the onset of the 5-day CO-Synch + CIDR protocol.

Objectives were to 1) characterize fixed-time AI (FTAI) pregnancy rates using the 5-Day CO-Synch + CIDR protocol in mature, suckled Bos indicus-influenced beef cows, 2) compare FTAI pregnancy rates in the latter to a modified version (5-Day Bee Synch + CIDR; Bee Synch I) that included treatment with prostaglandin F2α (PGF2α) at CIDR insertion on Day 0, and 3) test the hypothesis that elimination of both GnRH-1 at the onset of synchronization and the double dose of PGF on Day 5 (Bee Synch II) would not reduce FTAI pregnancy rates compared to Bee Synch I. For Experiment 1-trial 1, Brahman x Hereford (F-1) cows (n = 168) at least 40 d postpartum (PP; r = 40-92 d) at the time of CIDR insertion were administered the 5-Day CO-Synch + CIDR protocol with FTAI at 72 h after CIDR removal. Pregnancy rates to FTAI averaged 34.9 ± 1.9%. In Experiment 1-trial 2, fall- and spring-breeding Brahman x Hereford (F-1) beef cows (n = 269) were stratified by days PP and assigned randomly to receive either the 5-Day CO-Synch + CIDR (n = 136) or Bee Synch I (n = 133) protocol, with FTAI at 66 h after CIDR removal. Pregnancy rate to FTAI was greater (P < 0.05) in Bee Synch I (52.6 ± 0.9%) than in the 5-Day CO-Synch + CIDR procedure (40.4 ± 5.7%). For Experiment 2, 422 mature Braford, Brangus, Nelore x Brahman, and Brahman crossbred cows (Bos indicus proportion unknown) at 4 locations were treated with Bee Synch I, with FTAI at 66 h. Overall FTAI pregnancy rate averaged 51.7 ±â€¯2.1%. Finally, from 2013 through spring 2018, we used a switchback design using fall- and spring-breeding herds to compare Bee Synch I (402 observations) to Bee Synch II (393 observations). Overall frequency of detected estrus at 66 h using ESTROTECT™ breeding indicator patches was 57.2 ±â€¯2.4%, conception rates of those detected in estrus was 64.4 ±â€¯3.5%, and FTAI pregnancy rates averaged 52.3 ±â€¯2.4%, none of which differed between treatments. Moreover, pregnancy rates to FTAI in both treatments did not differ in cows synchronized between 40 and 80 d PP but increased after 80 d PP (P < 0.05). Bee Synch II, which eliminates GnRH-1 and the double dose of PGF2α on Day 5, results in FTAI pregnancy rates essentially identical to Bee Synch I but reduces synchronization costs and avoids the need for off-label (double dose PGF2α) drug use.

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

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.

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.

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

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.

Automated detection of estrous behavior in tie-stall housing using a barometer and accelerometer.

Tie-stall housing inhibits movement in cows, thereby restricting the behavioral indicators used by farmers for detecting estrous. In this study, we investigated the changes in patterns of lying and standing times at estrous, and evaluated the potential for automated detection of estrous within tie-stalls using a barometer and accelerometer. On estrous days, total daily standing time was significantly longer than that during non-estrous days (P < 0.05). A practical method was developed for detecting slight altitude changes using a novel device, which consisted of a barometer and accelerometer, and was attached to the neckband. Total daily standing time predicted using this new device was found to be highly correlative with the observed measured data (r = 0.95, P < 0.01), indicating the accuracy of the device in measuring daily standing time in tie-stall housed cows. In addition, the device detected an overall increase in total daily standing time during estrous days.