Rial, C., Hussain, I., Hoff, R., Tompkins, S., Erickson, D., Branen, J., and Giordano J. O.*
J. Dairy. Sci., Accepted 04 May 2024

Our objectives were to develop and evaluate an integrated system consisting of a lateral-flow immunoassay (LFIA) and an electronic portable imaging device for determination of pregnancy status of cows based on plasma concentrations of pregnancy-specific protein B (PSPB). Experiment 1 was conducted to test the performance of the LFIA for PSPB (PSPB-LFIA) whereas experiment 2 was conducted to evaluate the performance of the integrated system including both the LFIA and imaging device. The PSPB-LFIA strips were made of nitrocellulose membrane with polystreptavidin, anti-mouse antibody, Europium-anti-PSPB conjugates, and biotin-PSPB. After adding buffer and plasma in a 96-well plate, strips were dipped to initiate flow and were read in a fluorescence microscope to estimate PSPB concentrations based on the test-to-control line signal (T/C ratio). The T/C ratio of standards was linearly associated with PSPB (R2=0.99 in both experiments) concentrations. To test the ability to identify pregnant cows of the PSPB-LFIA only or the integrated system, plasma samples were collected and transrectal ultrasonography (TUS) was conducted 29 to 35 d post AI in lactating Holstein cows (Experiment 1: n = 83; Experiment 2: n = 205). A cow was considered pregnant (Preg) if concentrations of PSPB in plasma obtained by ELISA were ≥ 2 ng/mL or if an embryo was visible by TUS. In Experiment 1, the accuracy of the PSPB-LFIA compared with ELISA was 92.7% (91.2% Se; 96.1% Sp; 98.1% PPV; 83.3% NPV) and compared with TUS was 90.4% (100% Se; 78.9% Sp; 84.9% PPV; 100% NPV). The agreement between LFIA and ELISA (kappa=0.84; 95%CI 0.71–0.96) or LFIA and TUS (kappa=0.80; 95%CI 0.67–0.93) as methods to classify cows as Preg or Non-Preg was high. In Experiment 2, the accuracy of the PSPB-LFIA compared with ELISA was 96.1% (93.8% Se; 100% Sp; 100% PPV; 90.5% NPV) and compared with TUS was 92.2% (99.0% Se; 84.7% Sp; 87.6% PPV; 98.8% NPV). The agreement between LFIA and ELISA (kappa=0.92; 95%CI 0.86–0.97) or LFIA and TUS (kappa=0.84; 95%CI 0.77–0.92) as methods to classify cows as Preg or Non-Preg was high. We conclude that a system integrating a fluorescence-based LFIA and an optical reader was effective for classifying cows as pregnant or not pregnant based on estimations of plasma concentrations of PSPB. This novel system serves as a platform for further development of on-farm pregnancy testing tools based on measurement of biomarkers of pregnancy in bodily fluids of cattle.

Rial C., & J. O. Giordano*
Dairy. Sci., Accepted 11 March 2024
Article in Press | https://doi.org/10.3168/jds.2023-24309

Grouping cows for targeted reproductive management based on levels of multiple factors might help identify subgroups with greater differences in performance than when a single factors is used. Therefore, our objective was to compare differences in reproductive performance for dairy cows grouped based on the combination of data for predictors available during the prepartum period and before the end of the VWP, automated estrus alerts (AEA) during the VWP, and the combination of both factors. In a cohort study, data for AEA and potential predictors of the percentage of cows inseminated in estrus (AIE) and pregnancies per AI (P/AI) for first service, and the percentage of cows pregnant by 150 DIM (P150) were collected from -21 to 49 DIM for lactating Holstein cows (n=886). Individual predictors (health disorders, gDPR, and MY) associated with the three reproductive outcomes in all models were used to group cows based on risk factors (RF; yes, n=535 or no, n=351) for poor reproductive performance. Specifically, cows were included in the RF group if any of the following conditions were met: the cow was in the high MY group, had low gDPR, or had at least one health disorder recorded. Cows were grouped into estrus groups during the VWP based on records of AEA (E-VWP, n=476 or NE-VWP, n=410). Finally, based on the combination of levels of AEA and RF cows were grouped into an estrus and no RF (E-NoRF, n=217), no estrus and RF (NE-RF, n=276), no estrus and no RF (NE-NoRF, n=134), and estrus and RF (E-RF, n=259) groups. Cows received AIE up to 31 d after the end of the VWP, and if not AIE, received timed AI after an Ovsynch plus progesterone protocol. Logistic and Cox proportional hazard regression compared differences in reproductive outcomes for different grouping strategies. The NoRF (AIE:76.9%; P/AIE:53.1%; P150:84.5%) and E-VWP (AIE:86.8%; P/AIE:44.8%; P150:82.3%) groups had more cows AIE, P/AI, and P150 than the RF (AIE:64.5%; P/AIE:34.9%; P150:72.9%) and NE-VWP (AIE:50.0%; P/AIE:38.9%; P150:72.1%) groups, respectively. When both factors were combined, the largest and most consistent differences were between the E-NoRF (AIE:91.3%; P/AIE:58.7%; P150:88.5%) and NE-RF groups (AIE:47.3%; P/AIE:35.8%; P150:69.5%). Compared with the whole population of cows or cows grouped based on a single factor, the E-NoRF and NE-RF groups had the largest and most consistent differences with the whole cow cohort. The E-NoRF and NE-RF group also had statistically significant differences of a large magnitude when compared with the remaining cow cohort after removal of the respective group. We conclude that combining data for AEA during the VWP with other predictors of reproductive performance could be used to identify groups of cows with larger differences in expected reproductive performance than if AEA and the predictors are used alone.

Sitko E. M., A. Laplacette, D. Duhatschek, C. Rial, M. M. Perez, S. Tompkins, A. Kerwin, R. Domingues, M. Wiltbank, J. O. Giordano*
J. Dairy. Sci., Accepted 14 March 2024
Article in Press | https://doi.org/10.3168/jds.2023-24378

Physiological differences for cows of different genomic merit for fertility can be the basis for the development of novel targeted management strategies to enhance dairy herd reproductive performance and management. Thus, the objectives of this prospective cohort study were to characterize associations among genomic merit for fertility with ovarian and endocrine function and the estrous behavior of dairy cows during an entire, non-hormonally manipulated estrous cycle. Lactating Holstein cows entering their first (n = 82) or second (n = 37) lactation had ear-notch tissue samples collected for genotyping using a commercial genomic test. Based on genomic predicted transmitting ability values for daughter pregnancy rate (gDPR) cows were classified into a high (Hi-Fert; gDPR > 0.6 n = 36), medium (Med-Fert; gDPR −1.3 to 0.6 n = 45), and low fertility (Lo-Fert; gDPR < −1.3 n = 38) group. At 33 to 39 DIM, cohorts of cows were enrolled in the Presynch-Ovsynch protocol for synchronization of ovulation and initiation of a new estrous cycle. Thereafter, the ovarian function and endocrine dynamics were monitored daily until the next ovulation by transrectal ultrasonography and concentrations of progesterone (P4), estradiol, and FSH. Estrous behavior was monitored with an ear-attached automated estrus detection system that recorded physical activity and rumination time. Overall, we observed an association between fertility group and the ovarian and hormonal phenotype of dairy cows during the estrous cycle. Cows in the Hi-Fert group had greater circulating concentrations of P4 than cows in the Lo-Fert group from d 4 to 13 after induction of ovulation and from day −3 to −1 before the onset of luteolysis. The frequency of atypical estrous cycles was 3-fold greater for cows in the Lo-Fert than the Hi-Fert group. These results demonstrate that differences in reproductive performance between cows of different genomic merit for fertility classified based on gDPR may be partially associated with circulating concentrations of P4, the incidence of atypical phenotypes during the estrous cycles, and to a lesser extent the follicular wave dynamics. The observed physiological and endocrine phenotypes might help explain part of the differences in reproductive performance between cows of superior and inferior genomic merit for fertility.

Front. Anim. Sci., 17 March 2023
Sec. Precision Livestock Farming
Volume 4 – 2023 | https://doi.org/10.3389/fanim.2023.1093857

Technologies for automating animal management and monitoring tasks can improve efficiency and productivity of livestock production. We developed the e-Synch system for automated control and monitoring the estrous cycle of cattle through intravaginal hormone delivery and sensing. Thus, our objective was to evaluate luteinizing hormone (LH) concentrations after intravaginal instillation of the Gonadotropin-releasing hormone (GnRH) analogue Gonadorelin with the e-Synch system. This system consists of an intravaginal electronically controlled automated hormone delivery and sensing device integrated with an IoT platform. Lactating Holstein cows with their estrous cycle synchronized were used in two experiments (Exp). In Exp 1, at 48 h after induction of luteolysis, cows (n=5-6 per group) were randomized to receive 100 µg of Gonadorelin through intramuscular (i.m.) injection, 100 µg of Gonadorelin in a 2 mL solution delivered with e-Synch, and an empty e-Synch device. In Exp 2, at 48 h after induction of luteolysis cows (n=6-7 per group) were randomized to receive 100 µg of Gonadorelin i.m., or an intravaginal treatment with e-Synch consisting of 100 or 1,000 µg of Gonadorelin in 2 or 10 mL of solution containing 10% citric acid as absorption enhancer. Circulating concentrations of LH were analyzed with linear mixed models with or without repeated measurements. In Exp 1, cows in the i.m. Gonadorelin treatment had a surge of LH whereas cows in the other two treatments did not have a surge of LH for up to 8 h after treatment. In Exp 2, the 1,000 µg dose of Gonadorelin elicited more LH release than the 100 µg dose, regardless of solution quantity. The overall LH response as determined by area under the curve, mean, and maximum LH concentrations was similar between cows receiving 1,000 µg of Gonadorelin delivered with e-Synch and 100 μg of Gonadorelin i.m. Increasing volume of solution for delivering the same dose of Gonadorelin partially increased LH release only for the 100 µg dose. We conclude that the e-Synch system could be used to automatically release Gonadorelin in a dose and volume that induces a surge of LH of similar magnitude than after i.m. injection of 100 μg of Gonadorelin. Also, the dose of Gonadorelin delivered by e-Synch is more critical than the volume of solution used.

Front. Anim. Sci., 16 March 2023
Sec. Precision Livestock Farming
Volume 4 – 2023 | https://doi.org/10.3389/fanim.2023.1093851

The objective of this manuscript was to present the e-Synch system, integrating an intravaginal electronically controlled hormone delivery and sensing device with an IoT platform for remote programming and monitoring. Secondary objectives were to demonstrate system functionality and cow responses to e-Synch. External components of e-Synch include a 3D-printed case with retention wings, a flexible wideband antenna, and silicone membrane for pressure balancing. Internal components include a central control board, battery, wireless charging coil, and two silicone hormone reservoirs connected to individual peristaltic pumps. An accelerometer and a high-accuracy temperature sensor are integrated in the custom printed circuit board (PCB). The IoT platform includes a gateway consisting of Raspberry PI 3 and a CC1352 radiofrequency module that collects sensor data at 915 mHz. Data is transferred to the Google Cloud utilizing the IoT Core service through TCP/IP, and then is pulled by the Pub/Sub service. After routing to a BigQuery table by the Dataflow service, data visualization is provided by Data Studio. Drug delivery protocols are selected using an IOS device app that connects to e-Synch through Bluetooth. Experiments with lactating Holsteins cows were conducted to demonstrate proof-of-concept system functionality and evaluate cow responses. Despite unstable communication and signal discontinuity because of signal strength attenuation by body tissue, devices (n=6) communicated with the IoT platform in 89% (24/27) of use instances. Temperature and accelerometer data were received for at least one 15 min period during an 8 h insertion period from all devices that communicated with the IoT platform. Variation in accelerometer data (± 8.565 m/s²) was consistent with cow activity during experimentation and mean vaginal temperature of 39.1 °C (range 38.6 to 39.5 °C) demonstrated sensor functionality. Hormone release was confirmed in all instances of device use except for one. Cow behavior evaluated through signs of discomfort and pain, and tail raising scores was mostly unaltered by e-Synch. Vaginal integrity and mucus scores also remained unaltered during and after device insertion. In conclusion, the e-Synch device integrated with a controlling app and IoT platform might be used to automate intravaginal hormone delivery and sensing for controlling the estrous cycle of cattle.