Guinea Pig Preimplantation Embryos: Generation, Collection, and Immunofluorescence

Studying various animal models is important for comparative biology and to better understand evolutionary development. Furthermore, when aiming to translate findings to human development, it is crucial to select an appropriate animal model that closely resembles the specific aspect of development under study. The guinea pig is highlighted as a useful platform for reproductive studies due to similarities in in utero development and general physiology with the human. This chapter outlines the methods required for guinea pig mating and collection of embryos for in vitro culture and molecular characterization. Specifically, this chapter provides detailed guidance on monitoring the estrus cycle to determine the mating time, performing a vaginal flush and smear to confirm successful mating, performing euthanasia of the guinea pig, and flushing in vivo embryos. Once collected, the embryos can be utilized for numerous downstream applications. Here we will cover embryo culturing and processing embryos for immunofluorescence.

Comparison of three reproductive management strategies for lactating dairy cows using combination of estrus detection or ovulation synchronization and Fixed-Timed Artificial Insemination

The objective of this study was to compare the reproductive performance of lactating dairy cows submitted to first AI after combination of estrus detection and fixed timed AI (FTAI) and FTAI only. Cows were randomly assigned to receive AI at detected estrus between 50 and 70 d in milk (DIM), if not detected in estrus, were enrolled in either Ovsynch (ED-Ov, n = 485) or PRIDsynch (ED-PR, n = 505) protocols; or received FTAI at 80 DIM after Double-Ovsynch protocol (DO, n = 501). Cows were body condition scored (BCS) at calving and at 43 DIM; and evaluated for postpartum disorders within 7 d postpartum; clinical mastitis, lameness and bovine respiratory disease were recorded until first AI. Ovarian cyclicity was monitored at 43 and 50 DIM, and at 70 and 77 DIM. Pregnancy diagnoses (PD) were performed at 32 and 63 d after AI. Overall prevalence of postpartum anovulation was 7.8%. Pregnancy per AI (P/AI) did not differ between reproductive strategies at 32 d PD (ED-Ov = 43.2%; ED-PR = 41.7%; DO= 45.3%). Primiparous cows had greater P/AI than multiparous cows (53.7% vs 36.8%). Cows on farm 1 had lower P/AI compared with their counterparts on farm 2 (42.1% vs 45.4%). Cows with BCS > 2.5 at 43 DIM had greater P/AI compared with cows with BCS ≤ 2.5 (44.5% vs 34.7%). Similar P/AI for cow's receiving AI at detected estrus and FTAI, low prevalence of disease anovulation may have contributed to the similar performance of ED-Ov, ED-PR and DO.

Climate change and socio-economic assessment of PLF in dairy farms: Three case studies

Precision Livestock Farming (PLF) techniques include sensors and tools to install on livestock farms and/or animals to monitor them and support the decision making process of farmers, finally early detecting alerting conditions and improving the livestock efficiency. Direct consequences of this monitoring include enhanced animal welfare, health and productivity, improved farmer lifestyle, knowledge, and traceability of livestock products. The indirect consequences, instead, include improved Carbon Footprint and socio-economic indicators of livestock products. In this context, the aim of this paper is to develop an indicator applicable to dairy cattle farming that takes into account concurrently these indirect consequences. The indicator was developed combining the three sustainability pillars (with specific criteria): environmental (carbon footprint), social (5 freedoms of animal welfare and antimicrobial use) and economic (cost of technology and manpower use). The indicator was then tested on 3 dairy cattle farms located in Italy, where a baseline traditional scenario (BS) was compared with an alternative scenario (AS) where PLF techniques and improved management solutions were adopted. The results highlighted that the carbon footprint reduced in all AS by 6-9 %, and the socio-economic indicators entailed improvements in animals and workers welfare with some differences based on the tested technique. Investing in PLF techniques determines positive effects on all/almost all the criteria adopted for the sustainability indicator, with case-specific aspects to consider. Being a user-friendly tool that supports the testing of different scenarios, this indicator could be used by stakeholders (policy makers and farmers in particular) to identify the best direction towards investments and incentive policies.

Peri-estrus activity and mounting behavior and its application to estrus detection in Hanwoo (Korea Native Cattle)

This study was conducted to investigate the change in activity and mounting behavior in Hanwoo (Korean Native Cattle) during the peri-estrus period and its application to estrus detection. A total of 20 Hanwoo cows were fitted with a neck-collar accelerometer device, which measured the location and acceleration of cow movements and recorded the number of instances of mounting behavior by the altitude data. The data were analyzed in three periods (24-, 6-, and 2-h periods). Blood samples were collected for 5 days after the prostaglandin F2α (PGF2α) injection, and the concentrations of estradiol, progesterone, follicle-stimulating hormone, and luteinizing hormone were determined by enzyme-linked immunosorbent assays. Activity and mounting behavior recorded over 2-h periods significantly increased as estrus approached and were more efficient at detecting estrus than over 24- and 6-h periods (p < 0.05). Endocrine patterns did not differ with the variation of individual cows during the peri-estrus period (p > 0.05). Activity was selected as the best predictor through stepwise discriminant analysis. However, activity alone is not enough to detect estrus. We suggest that a combination of activity and mounting behavior may improve estrus detection efficiency in Hanwoo. Further research is necessary to validate the findings on a larger sample size.

Increased accuracy of estrus prediction using ruminoreticular biocapsule sensors in Hanwoo (Bos taurus coreanae) cows

Visual estrus observation can only be confirmed at a rate of 50%-60%, which is lower than that obtained using a biosensor. Thus, the use of biosensors provides more opportunities for artificial insemination because it is easier to confirm estrus than by visual observation. This study determines the accuracy of estrus prediction using a ruminoreticular biosensor by analyzing ruminoreticular temperature during the estrus cycle and measuring changes in body activity. One hundred and twenty-five Hanwoo cows (64 with a ruminal biosensor in the test group and 61 without biosensors in the control group) were studied. Ruminoreticular temperatures and body activities were measured every 10 min. The first service of artificial insemination used gonadotropin-releasing hormone (GnRH)-based fixed-time artificial insemination protocol in the control and test groups. The test group received artificial insemination based on the estrus prediction made by the biosensor, and the control group received artificial insemination according to visual estrus observation. Before artificial insemination, the ruminoreticular temperature was maintained at an average of 38.95 ± 0.05°C for 13 h (-21 to -9 h), 0.73°C higher than the average temperature observed at -48 h (38.22 ± 0.06°C). The body activity, measured using an indwelling 3-axis accelerometer, averaged 1502.57 ± 27.35 for approximately 21 h from -4 to -24 h before artificial insemination, showing 203 indexes higher body activity than -48 hours (1299 ± 9.72). Therefore, using an information and communication techonology (ICT)-based biosensor is highly effective because it can reduce the reproductive cost of a farm by accurately detecting estrus and increasing the rate of estrus confirmation in cattle.

The evaluation of an artificial intelligence system for estrus detection in sows

BACKGROUND

Good estrus detection in sows is essential to predict the best moment of insemination. Nowadays, a technological innovation is available that detects the estrus of the sow via connected sensors and cameras. The collected data are subsequently analyzed by an artificial intelligence (AI) system. This study investigated whether such an AI system could support the farmer in optimizing the moment of insemination and reproductive performance. M&M: Three Belgian sow farms (A, B and C) where the AI system was installed, participated in the study. The reproductive cycles (n = 6717) of 1.5 years before and 1.5 years after implementation of the system were included. Parameters included: (1) farrowing rate (FR), (2) percentage of repeat-breeders (RB), (3) farrowing rate after first insemination (FRFI) and (4) number of total born piglets per litter (NTBP). Also, data collected by the system were analyzed to describe the weaning-to-estrus interval (WEI), estrus duration (ED) and the number of inseminations used per estrus. This dataset included 2261 cycles, collected on farms B and C.

RESULTS

In farm A, all parameters significantly improved namely FR + 4.3%, RB - 3.75%, FRFI + 6.2% and NTBP + 1.06 piglets. In farm B, the NTBP significantly decreased with 0.48 piglets, but in this farm the insemination dose was too low (0.8 × 10⁹ spermatozoa per dose). In farm C, only the NTBP significantly increased with 0.45 piglets after the implementation of the system. The WEI as determined by the system varied between 78 and 90 h, being 10-20 h shorter in comparison with the WEI as determined by the farmer. The ED, determined by the system ranged from 48 to 60 h, and was less variable as compared to the ED as assessed by the farmer. The mean number of inseminations per estrus remained similar over time in farm B whereas it decreased over time from approximately 1.6-1.2 in farm C.

CONCLUSION

The AI system can help farmers to improve the reproductive performance, assess estrus characteristics and reduce the number of inseminations per estrus. Results may vary between farms as many other variables such as farm management, genetics and insemination dose also influence reproductive performance.

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.

Performance and optimization of an ear tag automated activity monitor for estrus prediction in dairy heifers

The objectives of this study were to evaluate the performance of the SCR eSense ear tag automated activity monitor (AAM) to detect estrus behavior in Holstein heifers and to determine the optimal time from estrus alert to artificial insemination (AI) using sex-sorted or conventional semen. In total, 281 heifers were fitted with the AAM once eligible for breeding (>13.5 m of age). For the first AI, estrus was synchronized using 500 μg of cloprostenol (PGF), given 14 d apart, and heifers were given estrus detection patches (Estrotect™) after the second PGF. Heifers were inseminated at randomly attributed times after high activity alert from the AAM system or if the estrus patch had ≥ 50% colour change. Most heifers received sex-sorted semen for the first AI and conventional semen for subsequent inseminations. Pregnancy diagnosis was performed at 30 d post AI and heifers had four opportunities to become pregnant. In a subset of heifers (n = 149), ovaries were scanned every 12 h from the time of AI until ovulation (OV). The system recorded a heat index (measure of estrus strength), maximum activity change, maximum rumination change and duration of high activity. The sensitivity was 91.0%, with a false positive and false negative rate of 8.0%, and the positive predictive value to detect true estrus events was 83.5%. Pregnancy per AI to first AI was 67.6% and 97.9% of heifers become pregnant after four inseminations. Most false positive estrus events had a heat index < 45 and a rumination change < -20, while false negative events had a rumination change ≥ -20. Odds of pregnancy was not associated with any estrus characteristics measured by the system. However, pre-ovulatory follicle diameter had a weak correlation (r < 0.25) with all estrus characteristics. The average (range) interval of onset of high activity, peak activity and end of high activity to OV was 28 h (16-46 h), 22 h (10-40 h) and 16 h (0-36 h), respectively. For conventional semen, each hour increase in interval from activity onset or peak activity to AI reduced the predicted probability of pregnancy by 3.8 and 4.2%, respectively. For sex-sorted semen, the relationship between activity onset or peak activity to AI and predicted probability of pregnancy was quadratic, but not significant. Overall, the SCR eSense ear tag AAM performed well and strategies to identify false positive and false negative estrus events, along with optimization of timing of AI, should further improve performance in Holstein heifers.

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 (r_s = 0.827; P < 0.001) and CL volume and progesterone concentration (r_s = 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.

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.

Reproductive cycle stage assessment using vaginal cytology evaluation in African lions (Panthera leo)

Vaginal cytology evaluation is an economic, non-invasive technique for indirect monitoring of fluctuations in estrogen concentrations, and thus progression of the estrous cycle. This technique is widely used in domestic dogs for determining timing of artificial insemination. There, however, are only a few reports on the vaginal cytology of non-domestic felids, including lions. This study was conducted, therefore, to describe the vaginal epithelial changes throughout the reproductive cycle of African lions, and to investigate the efficacy of vaginal cytology assessments for predicting reproductive stages. During a 12-month period, reproductive behavioral data and vaginal swabs were collected daily from five lionesses. In total, 541 vaginal smears were evaluated for the proportion of mucosal epithelial cells, neutrophils, bacterial cells, and amount of mucous, cellular debris. One single swab with a large proportion of superficial cells, absence of neutrophils, large number of bacteria, without cellular debris was sufficient for detecting lionesses in estrus. Likewise, one cytology sample with a large proportion of parabasal and intermediate cells, few neutrophils, few bacteria, and large amount of mucous, cellular debris enabled detection of females in advanced diestrus or gestation. To distinguish lionesses in early diestrus from those in an inter-estrous period, at least two consecutive swabs were necessary for satisfactory classification. Overall, evaluation of vaginal cytology samples was an effective technique for differentiation among different stages of the reproductive cycle, confirmation of estrus, and pregnancy diagnosis in lionesses. This technique, therefore, has the potential for application in classifying different stages of the reproductive cycle in other feline species.

Comparison of the effects of two shortened timed-AI protocols on pregnancy per AI in beef cattle

The objective was to compare pregnancy per AI (P/AI) between two shortened timed-AI (TAI) protocols in beef cattle. This study also determined whether administration of eCG in heifers and timing of AI in cows would affect P/AI. Cattle were submitted at random to either a modified 5-d Co-synch protocol (Day 0 = progesterone releasing device (CIDR); Day 5 = CIDR removal and 500 μg of cloprostenol (PGF); Day 8 = 100 μg GnRH concurrent with AI) or J-synch protocol (Day 0 = CIDR insertion and 2 mg of estradiol benzoate i.m.; Day 6 = CIDR removal and 500 μg PGF; Day 9 = 100 μg GnRH concurrent with AI). In Experiment 1, 1135 heifers (13-15 mo of age) received an estrus detection patch (Estrotect™) on Day 5 and 579 were selected at random to receive 300 IU of equine chorionic gonadotropin (eCG) at the time of CIDR removal. Patches were scored from 0 to 3 based on color change between initial application and AI; 0 = unchanged, 1 = ≤ 50% change, 2 = > 50% change, 3 = missing. Estrus was defined to have occurred when the patch was scored 2 or 3. In Experiment 2, 399 cyclic, non-lactating beef cows from 1 location were submitted to either the modified 5-d Co-synch or J-synch protocol and within each protocol cows were TAI at either 66 ± 1 (n = 199) or 72 ± 1 h (n = 200) following CIDR removal. Transrectal ultrasonography was used in both experiments to determine presence of a corpus luteum (CL) on Day 0, and to diagnose pregnancy 35 d after TAI. In Experiment 1, eCG increased estrus rate only in heifers without a CL on day 0 that were submitted to the modified 5-d Co-synch protocol (41.9 vs. 69.6%). Heifers submitted to the J-synch protocol had greater (P = 0.03) P/AI compared with those in the modified 5-d Co-synch (48.7 vs. 41.1%) and heifers that expressed estrus before AI had increased (P < 0.0001) P/AI compared to those that did not (53.6 vs. 36.5%). Administration of eCG and presence of a CL tended to affect P/AI (P = 0.13). In Experiment 2, cows submitted to the J-synch protocol tended (P = 0.07) to have greater P/AI compared to those in the modified 5-d Co-synch (74.1 vs. 66.5%). There was no association between P/AI and timing of AI. In summary, the J-synch protocol resulted in greater P/AI than the modified 5-day Co-synch protocol in heifers and cows. Administration of eCG increased estrus rate in heifers without a CL at the start of the protocol and tended to improve P/AI in all heifers. Timing of AI (66 vs. 72 h) had no effect on P/AI in cows subjected to either TAI protocol.

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.

Comprehensive Breeding Techniques for the Giant Panda

The dramatic growth of the captive giant panda (Ailuropoda melanoleuca) population exemplifies how the application of scientific findings to animal care and reproductive management can improve conservation breeding outcomes. Detailed behavioral studies of giant panda estrus, pregnancy and cub rearing have demonstrated the importance of husbandry management that supports natural reproductive behavior to enhance breeding success. Natural breeding has been valuably augmented by the development of assisted reproductive techniques founded through detailed studies of the reproductive physiology of the giant panda and outlining fundamental information about reproductive seasonality, male fertility and characterization of the estrous cycle. The resultant holistic understanding of giant panda reproduction has improved reproductive success in the captive population to such an extent that it is now self-sustaining and provides surplus animals for reintroduction. Despite these significant advances, there are knowledge gaps and remaining challenges to be addressed. Pregnancy detection remains the single biggest challenge when determining if natural mating or assisted breeding have been successful. Because pregnancy can only be determined in the few weeks prior to parturition, there are gaps in understanding and detecting delayed implantation and early embryonic loss. Additionally, dynamic management practices and standard of care for reproductive assistance needs to be developed. Only large breeding centers in China have the ability to promote normal reproductive behaviors and allow mate choice for the giant panda. These challenges need to be addressed in the near future in order to maintain a self-sustaining, genetically diverse and behaviorally competent captive population. This chapter documents the development of successful giant panda managed breeding programs by focusing on three key areas, (1) the development of science-driven reproductive techniques to improve fecundity in a species where the mating system was poorly understood, (2) how targeted research and adaptive management of social settings surrounding estrus and breeding improved reproductive success, and (3) insights and solutions to challenges faced across the program's history with future directions for research.

Presynchronization strategy using prostaglandin F2α, gonadotropin-releasing hormone, and detection of estrus to improve fertility in a resynchronization program for dairy cows

Objectives of experiment 1 were to evaluate pregnancy outcomes and reinsemination patterns of cows whose estrous cycles or ovulation were presynchronized with prostaglandin (PGF_2α) or PGF_2α and gonadotropin-releasing hormone (GnRH) after non-pregnancy diagnosis in programs focusing on inseminating cows based on tail paint removal. Objectives of experiment 2 were to evaluate pregnancy outcomes and reinsemination patterns of cows with or without a corpus luteum (CL) present at non-pregnancy diagnosis in a program utilizing PGF_2α and GnRH to presynchronize estrous cycles before resynchronization. Lactating Holstein cows from three herds were enrolled in the experiments at non-pregnancy diagnosis (d 0). Estrus was determined daily based on tail paint removal. In experiment 1, cows were assigned randomly to two treatments: (1) PGF_2α on d 0 (n = 967; P7); and 2) PGF_2α on d 0 and GnRH on d 7 (n = 962; P7G7). Cows not reinseminated based on tail paint removal were submitted to the timed-AI Cosynch-72 protocol 7 d after presynchronization treatments. Pregnancy per AI (P/AI) was greater (P = 0.01) for P7G7 cows than P7 cows. Cows inseminated based on tail paint removal had increased (P < 0.01) P/AI than cows submitted to the timed AI protocol. In addition, an interaction was detected (P = 0.03) between method of insemination and presynchronization treatment such that cows submitted to timed AI in the P7G7 treatment had greater P/AI than P7 cows. Nonetheless, P7 cows were inseminated at a faster rate (P < 0.01) than P7G7 cows. In experiment 2, presence of a CL was determined by transrectal ultrasonography at initiation of the P7G7 protocol (n = 1479). In a random subset of cows (n = 210), blood samples were collected immediately after ultrasound examination to determine progesterone concentration in order to evaluate accuracy of detection of a CL by ultrasonography. Accuracy of detection of a CL was 80%. Hazard to insemination and P/AI did not differ among cows regardless of CL status. In conclusion, herds relying mostly on detected estrus to reinseminate cows may achieve greater pregnancy outcomes if presynchronizing with PGF_2α and GnRH instead of only PGF_2α, albeit at a slower insemination rate. In addition, pregnancy outcomes and reinsemination patterns were similar for cows bearing or not bearing a CL when utilizing the P7G7 protocol, indicating a limited benefit of evaluating ovarian luteal structures by ultrasonography.

The use of infrared thermography to detect the stages of estrus cycle and ovulation time in anatolian shepherd dogs

BACKGROUND

The aim of the study is to evaluate the effectiveness of thermographic monitoring, using the temperature changes of perianal and perivulvar areas for the determination of estrus in Anatolian Shepherd bitches. Fifteen bitches were used in the study. Blood and vaginal smear samples were collected and thermographic monitoring of perianal and perivulvar areas were carried out starting from proestrus to early diestrus. Also, external signs of estrus were investigated. Smear samples were evaluated by light microscopy after Diff-Quik staining method and superficial and keratinized superficial cells were determined as percentage (S + KS%). Progesterone and luteinizing hormone measurements were done by radioimmunoassay. The difference in temperature between perianal and perivulvar areas was evaluated through thermographic images by FLIR ResearchIR Software.

RESULTS

According to the results obtained from the study, differences between progesterone and S + KS% were statistically significant (P < 0,05). Although temperature showed increase and decrease with progesterone and S + KS%, the differences were not important statistically (P > 0,05). Serum luteinizing hormone levels did not sign any difference (P > 0,05).

CONCLUSIONS

As a result, thermographic monitoring alone is not enough for estrus detection in Anatolian Shepherd bitches. However, it can be used to assist the actual estrus detection technique in terms of providing some foreknowledge by evaluating the differences in temperature.

Exploration of Luteinizing hormone in murrah buffalo (Bubalus bubalis) urine: Extended surge window opens door for estrus prediction

Estrus detection in buffaloes has been a major concern for decades, and lack of reliable methods affects their effective reproductive management. Luteinizing hormone (LH) detection in urine is in practice for several mammals for timed insemination, whereas very few reports are available on buffalo urinary LH. The focus of this study is to detect the presence of LH in buffalo urine, quantitate variation in urinary LH during different estrous cycle phases and examine the duration of mid-cycle LH window. Nearly hundred buffaloes were examined, longitudinal urine samples (n=42) were collected from seventeen animals and classified into respective phases based on several estrus detection parameters. The urinary LH was detected using bovine LH ELISA kit validated for serum/plasma/tissue homogenate. Detection of buffalo LH in the neat urine convincingly proved the competence of the bovine LH kit. Variation in the LH range was observed between different phases of estrous cycle and significant fold variation (P<0.05) was noticed during estrus phase (1.01±0.23) with average baseline value of 46.73±3.36mIU/mL. Interestingly, an extended window (A1-A3) of mid-cycle LH surge was observed due to its lingering excretion in urine. The results, altogether, revealed that LH can be detected in buffalo urine with noticeable fold variation during estrus phase and the extended LH window intensifies the chance of ovulation prediction for timed insemination.

The effect of Presynch-Ovsynch protocol with or without estrus detection on reproductive performance by parity, and the long-term effect of these different management strategies on milk production, reproduction, health and survivability of dairy cows

During the Presynch-Ovsynch protocol, at least half of the cows enrolled display signs of estrus, which can present as an opportunity for cows to be inseminated before the completion of the protocol. The primary objective of this study is to compare two management strategies for first service using the Presynch-Ovsynch protocol: insemination at completion of the Presynch-Ovsynch program (TAIonly) or insemination after estrus detection during the Presynch-Ovsynch protocol, with the remainder of cows being inseminated at timed artificial insemination (ED + TAI). Cows inseminated at completion of the protocol have a longer voluntary waiting period, which could potentially extend their lactation length, allowing them to recover BCS at the end of their lactation and ultimately impacting their subsequent lactation. Therefore, this study has a secondary objective to evaluate the long term impact of these two strategies on reproductive outcomes, culling, milk production and health during the subsequent lactation. A total randomized field trial study design was used, and a total of 3489 cows were randomly enrolled to one of the treatment groups: ED + TAI or TAIonly. Cows enrolled in the TAIonly started the Presynch protocol receiving two injections of PGF2α at 55 ± 3 and 69 ± 3 DIM. They were subsequently submitted to the Ovsynch protocol: GnRH at 81 ± 3 DIM, PGF2α at 88 ± 3 DIM, and GnRH at 90 ± 3 DIM, and then inseminated at fixed time at 91 ± 3 DIM. Cows enrolled in the ED + TAI were submitted to the same synchronization protocol, but they were eligible to be inseminated at any time after the beginning of the synchronization protocol, if detected in estrous. During the experimental lactation, the effect of treatment on first service conception rate (FSCR) was conditional to parity: no difference among primiparous cows, but for multiparous cows, the FSCR was 41.2% and 35.3% for TAIonly and ED + TAI, respectively. Although TAIonly strategy increased the lactation length for primiparous and multiparous, no differences were observed on lactation and reproductive performances. The rate at which cows conceived, and the calving to conception interval during the subsequent lactation was not affected by management strategy. Additionally, no differences were observed in milk production during the experimental and subsequent lactations. The effect of management strategy on survivability was conditional to parity: no differences were observed for multiparous cows, while primiparous ED + TAI cows tended to be less likely to be culled than TAIonly counterparts. Additionally, no differences in health outcomes during the subsequent lactation were observed.

A correlation of fecal volatiles and steroid hormone profiles with behavioral expression during estrous cycle of goat, Capra hircus

Chemical signals (both volatile and non-volatile) form the major communication channels in animals. These signals are transferred mainly through excretory sources to facilitate inter-individual communication. In particular, the reproductive cycle of female mammals, including goats, exhibits significant changes in the constituents of their excretory products, and female mammals also express different behavioral patterns. We propose that feces is one of the important sources of chemo-signals in goats. However, the behavioral patterns and analysis of excretory sources based on chemical communication have not yet been studied in the Indian goat, Capra hircus. To validate our hypothesis, we analyzed the behavioral patterns and the volatiles and steroid hormone profiles in the feces samples of female goats during the estrous cycle. Here, we synchronized the estrous cycle in six female goats and obtained feces samples. The samples were extracted with dichloromethane and analyzed using gas chromatography-mass spectrometry. A portion of the sample was used for hormone assay to confirm the phases in the estrous cycle. Induction of she-goats into estrus was detected from the vaginal swelling, mucus discharge, restlessness, reduced milk secretion, bellowing, bleating, frequent urination, standing heat, allowing the male to mount, mounting on other females and teasing of males. The repeated male behaviors viz., flehmen, mounting, penile protrusion, body rubbing, dominance over other males and finally coitus with estrus female by male goats were observed. Analysis of volatiles revealed a total of twenty-four compounds combining all the phases in the estrous cycle. Among those, some of the volatile compounds and two antioxidants (ascorbic acid and vitamin E) were estrus-specific. Based on the fecal steroid analysis, higher level of estradiol during estrus and higher level of progesterone during post-estrus were observed. The behavioral patterns of female and male goats combined with qualitative differences in the volatile compounds and the two antioxidants rendered the estrus identifiable. Furthermore, the fecal steroid analysis also supported the detection of hormonal status during the estrous cycle. To the best of our knowledge, this is the first report correlating the behavior with volatiles and hormones in the feces samples from female Indian goats. It is concluded that the volatile pattern and hormone profile in feces, supported by specific behavioral patterns, should be considered a better modality of non-invasive estrus detection in goats.

Infrared technology for estrus detection and as a predictor of time of ovulation in dairy cows in a pasture-based system

The development and application of an algorithm to assess the ability of an infrared thermography (IRT) device to predict cows in estrus and about to ovulate was investigated. Twenty cows were synchronized using a controlled internal drug release and PGF2α. Vulval and muzzle temperatures were measured every 12 hours from controlled internal drug release insertion to 32 hours after PGF2α treatment and then every 4 hours until ovulation occurred or until 128 hours after PGF2α treatment (whichever occurred first). Thermal images obtained with a FLIR T620 series infrared camera were analyzed using ThermaCAM Researcher Professional 2.9 software. Cows were also monitored for behavioral signs of estrus and color changes of an Estrotect applied to the tail head of each cow 36 hours after PGF2α treatment. Algorithms were developed by adjusting body surface temperature of individual animals for ambient temperature and humidity during each observation period, and were expressed as a deviation from the baseline temperature. Of the 20 cows enrolled in this study, 12 (60%) ovulated. An IRT estrus alert was defined using different thresholds (D = 1 °C, 1.25 °C, and 1.5 °C). Sensitivity and specificity to predict estrus depended upon the chosen threshold level. At a threshold D = 1 °C, the highest sensitivity (92%; n = 11) and the lowest specificity (29%) and positive predictive value (64%) were observed. Conversely, D = 1.5 °C resulted in sensitivity of 75%, specificity of 57%, and positive predictive value of 69%. The mean ± standard deviation intervals between onset and the end of IRT estrus alert to ovulation were 30.7 ± 8.2 and 13.3 ± 7.7 hours, respectively. Ovulation occurred 24 to 47 hours after the onset of the IRT estrus alert for eight out of the 11 ovulated cows (73%). Although the sensitivity of the IRT alert was greater than visual observation (67%) and Estrotect activation (67%), the specificity and positive predictive value were lower than these two aids (i.e., the IRT overpredicted the incidence of ovulation). Results presented indicate that IRT shows some potential as an estrus detection aid; however, further studies investigating the potential to improve the specificity and capturing data throughout entire 21-day reproductive cycles would be worthwhile.