Reproductive Management Research Articles

Unravelling the impact of epigenetic mechanisms on offspring growth, production, reproduction and disease susceptibility.

Epigenetic mechanisms, such as DNA methylation, histone modifications and non-coding RNA molecules, play a critical role in gene expression and regulation in livestock species, influencing development, reproduction and disease resistance. DNA methylation patterns silence gene expression by blocking transcription factor binding, while histone modifications alter chromatin structure and affect DNA accessibility. Livestock-specific histone modifications contribute to gene expression and genome stability. Non-coding RNAs, including miRNAs, piRNAs, siRNAs, snoRNAs, lncRNAs and circRNAs, regulate gene expression post-transcriptionally. Transgenerational epigenetic inheritance occurs in livestock, with environmental factors impacting epigenetic modifications and phenotypic traits across generations. Epigenetic regulation revealed significant effect on gene expression profiling that can be exploited for various targeted traits like muscle hypertrophy, puberty onset, growth, metabolism, disease resistance and milk production in livestock and poultry breeds. Epigenetic regulation of imprinted genes affects cattle growth and metabolism while epigenetic modifications play a role in disease resistance and mastitis in dairy cattle, as well as milk protein gene regulation during lactation. Nutri-epigenomics research also reveals the influence of maternal nutrition on offspring's epigenetic regulation of metabolic homeostasis in cattle, sheep, goat and poultry. Integrating cyto-genomics approaches enhances understanding of epigenetic mechanisms in livestock breeding, providing insights into chromosomal structure, rearrangements and their impact on gene regulation and phenotypic traits. This review presents potential research areas to enhance production potential and deepen our understanding of epigenetic changes in livestock, offering opportunities for genetic improvement, reproductive management, disease control and milk production in diverse livestock species.

PSVII-28 Unraveling the mechanisms governing boar semen quality during chilled storage

Abstract Artificial insemination (AI) appears as a core of reproductive management in the hog industry. AI involves the use of chilled semen doses meeting routine thresholds for motility (≥ 70%) and morphology (≥ 80%) at collection. However, semen doses meeting these standards exhibit a gradual decline in sperm quality, with likely divergent profiles during preservation that impact fertility outcomes. Hence, this study aims to unravel the sperm quality dynamics of boar semen doses during 7-d chilled storage at 17ºC. Semen doses (n = 25) from proven-fertile Duroc boars were provided by a commercial hog farm (Prestage Farm, MS) and transported to the laboratory within 30 min of collection. Each semen sample was aliquoted and analyzed on the day of collection (d 0) and after 7 d of storage (d 7) at 17°C. Sperm total motility (TM), progressive motility (PM), and normal morphology (NM) were assessed using a computer-assisted sperm analyzer (CASA; CEROS II, IMV Biotechnologies). Apoptosis (Annexin V/7-AAD), viability (Propidium iodide – PI), and intracellular reactive oxygen species (ROS; DCFH-DA) were evaluated using flow cytometry. Total antioxidant activity (TAOC) and lipid peroxidation (malondialdehyde; MDA) were assessed using commercial kits (Cayman Chemical). Data analysis was conducted using parametric statistics (SPSS), with P < 0.05 considered significant. Results were presented as mean ± SEM. Data analysis confirmed the significant decrease of CASA parameters, particularly TM from d 0 to d 7 (78.87 ± 1.37 vs. 73.19 ± 1.98%), with extreme variance on d 7 allowing to discriminate high motility (HM, n = 6) vs low motility (LM, n = 6) semen doses. HM doses evidenced significantly greater (P < 0.05) TM (83.73 ± 1.17%), PM (36.07 ± 1.11%), and NM (89.45 ± 2.30%) compared with LM doses (TM: 59.40 ± 3.35%, PM: 16.57 ± 3.25%, NM: 79.93 ± 2.61%) on d 7. Unlike HM samples, which were comparable between d 0 and d 7, LM doses displayed significantly greater proportions of apoptotic and viable cells, and increased intracellular ROS levels on d 0. Likewise, LM samples revealed significantly greater (P < 0.05) proportions of apoptotic cells (3.69 ± 1.66%), dead cells (38.41 ± 3.71%), and cells with intracellular ROS (36.21 ± 3.62%) than HM samples (apoptotic cells: 0.03 ± 0.02%, dead cells: 4.73 ± 4.65%, ROS: 5.34 ± 4.91%) on d 0; however, only the proportions of dead cells displayed significant increase in LM on d 7. MDA concentrations were comparable between HM and LM samples on d 0. However, on d 7, LM samples exhibited significantly greater MDA concentrations than HM samples. In contrast, TAOC was significantly greater in HM samples (2.53 ± 0.14 mM) compared with LM samples (2.17 ± 0.07 mM) on d 0. In conclusion, semen samples with similar gross characteristics at collection exhibited differential responses during storage. Their initial redox potential and apoptosis-like changes may contribute to their varying ability to withstand prolonged storage. Work supported by USDA-ARS grant# 6066-31000-015-00D.

452 Data-driven strategic sustainability initiatives of beef and dairy genetics consortiums: A comprehensive landscape analysis for USA, Brazil, and Europe

Abstract The past two decades have witnessed beef and dairy genetic consortiums implementing data-driven germplasm propagation programs in global cattle systems. These programs optimize for multi-dimensional economic, environmental, and animal welfare related sustainability goals and are driven by consumer demands and shifts in supply chains. To summarize these programs and gain insights into the sustainability journey of industry, we did a comprehensive landscape analysis of the strategic initiatives of key global genetics companies, their germplasm offerings, and data platforms offered in three major cattle producing geographies, namely the USA, Brazil, and Europe. Within these locales, they followed selection index-based genomic and reproductive management strategies for both beef, dairy, and beef-on-dairy production, tailored to relevant market and climatic conditions (Figure 1). While individual traits in selection indices ranged between 40 to 90 traits, all traits could be broadly grouped into three: namely production, longevity, health and reproduction. In the USA, companies like ABS Global, Select Sires, Genex Cooperative, STGenetics, Zoetis, Vytelle offer genomic selection programs encompassing germplasm products, and genetic and production data tracking platforms across the beef, dairy, and beef-on-dairy value chains. These companies have implemented reproductive management programs such as in-vitro fertilized embryo transfer, sexed semen, along with genomic selection with a focus on future replacements based on multi-trait sustainability indices. These initiatives are customized for each of the cow-calf, backgrounding, and feedlot sector of beef production. In dairy, these companies have diversified data-driven production programs customizable to conventional and organic production systems. In Europe, companies like CRV, Viking Genetics, and Alta Genetics prioritize traits related to resource efficiency, animal welfare and environmental impact. Semen companies also offer data management tools tailored to European market requirements, alongside services for on-farm semen production and storage to reduce transportation-related emissions. In Brazil, companies such as ABS Pecplan, CRV Brazil, and Semex Brazil, developed herd management solutions focusing on traits like heat tolerance, tropical environmental adaptability, and disease resistance. The landscape analysis revealed a dynamic industry, evolving to meet sustainability goals and market demands. These enterprises collaborate with stakeholders across the value chain, including producers, policymakers, and industry associations, to scale data-driven production systems that balance profitability and environmental footprint of cattle production. As such, they have positioned themselves to capitalize on the growing interest in sustainable livestock production practices worldwide by aligning scientific and technical strategies with evolving regulatory requirements and consumer demands. The global cattle industry is positioned to venture forward by leveraging niche carbon markets and new marketing channels propelled by emerging principles of environmental, social, and corporate governance. Strategic germplasm and data-tracking platform initiatives by these groups thus become an integral part of the livestock sustainability solution palette and will contribute its share to a climate-neutral Earth by 2050.

347 Quantifying phenotypic and genetic variation for cow fertility phenotypes in American Simmentals using total herd reporting data

Abstract Inefficiencies in reproduction are the largest drivers of loss in United States beef production. Nearly all reproductive traits are at least modestly heritable, making genetic selection and improvement possible over the long term. Cow-centric reproductive traits present unique challenges, as they are not expressed in male animals and will not be observed until later in the productive life of a female, if at all. This makes cow-centric fertility traits ideal candidates for selection with Expected Progeny Differences (EPDs). We used a commercially generated dataset from the American Simmental Association (ASA) to explore the phenotypic and genetic variation in these traits. The dataset comprised Total Herd Enrollment (THE) records, which required unbiased reporting of enrollment, calving, and disposal for 303,158 females (132,403 cows and 170,755 heifers). Using the THE data, we calculated three continuous and two discrete traits that are indicators of heifer and cow fertility and rebreeding ability. These traits were: 1) calving date (calving date of the cow relative to the start of the calving season), 2) calving interval (days between calves), 3) first calving interval (calving interval observation between the first and second calving record for a female), 4) heifer pregnancy (did the animal calve as 2-yr-old?), and 5) discrete early calving (did animal calve in the first 30 d of the calving season?). We observed a significant difference in calving date in mature cows that calved in the first 30 d of the calving season of their contemporary group as heifers compared with those that calved later (Table 1). Early calving heifers averaged a nearly 10 d sooner calving date throughout their productive lives compared with those that calved after 30 d as heifers (29.9 d vs. 40.2 d, P-value < 0.01). We used a combined pedigree and genomic approach, implemented in GIBBSF90+, to estimate genetic, environmental, and permanent environmental variance components. We estimated heritabilities of 0.24 (± 0.037215) for heifer pregnancy, 0.06 (± 0.009265) for calving date, 0.07 (± 0.015451) for discrete early calving, 0.04 (± 0.003954) for calving interval, and 0.04 (± 0.009604) for first calving interval. We observed positive phenotypic and genetic correlations between these traits, ranging from 0.01 to 0.96 (Table 2). This work provides an extensive population survey of phenotypic trends in reproductive performance and management in a large seedstock population. The heritable nature of the inspected traits motivates further work in understanding their genetic architectures and how they are affected by heterosis in crossbreeding programs.

185 Effect of synchronized fixed-time AI and non-pregnant heifer delayed feedlot entry on reproductive performance and system economics

Abstract Heifer reproduction management research is being conducted at the NDSU–Dickinson Research Extension Center. Using crossbred heifers, the objective was to evaluate reproductive performance and economic efficiencies comparing a drylot synchronized fixed-time AI protocol with clean-up bulls to two grazing systems using a fixed-time AI protocol without clean-up bulls. Synchronization protocol:14-d CIDR-PG-GnRH (TAI 66 h ± 2 h). Fixed-time AI treatments: 1) Drylot Control (DLOT) with clean-up bulls, 2) Integrated diverse crop-heifer annual forage grazing (IAF, no clean-up bulls), and 3) Native range grazing (NR, no clean-up bulls). Following pregnancy ultrasound on d 85, non-pregnant heifers continued to bale-graze until late November, when they were transferred to the University of Wyoming SAREC feedlot, finished, harvested at Cargill Meat Solutions packing plant, Ft. Morgan, CO, and grid marketed. Data were analyzed using the MIXED procedure of SAS. Year 1 and 2 grazing days were 121, and 149, respectively. Synchronized TAI pregnancy rates yr 1 and 2 for DLOT, IAF, and NR were 59.4, 43.8, and 62.5%; 68.8, 46.9, and 34.4%, respectively. Total DLOT control pregnancy rates yr 1 and 2 were 90.6 and 100%. Grazing heifer feedlot performance Yr 1 did not differ for starting body weight (BW; 452 vs 436 kg, P = 0.29), ending BW (610 vs 600 kg, P = 0.74), gain (157 vs 164 kg, P = 0.69), average daily gain (ADG; 1.42 vs 1.48 kg, P = 0.70), dry matter (DM) feed intake (15.0 vs 14.7 kg, P = 0.73), F:G (4.81 vs 4.56 kg, P = 0.42), daily feed cost ($7.45 vs $9.47, P = 0.73), feed cost/kg BW gain ($3.11 vs $2.95, P = 0.51), and feed and yardage cost ($3.41 vs $3.24, P = 0.55). Year 2 grazing heifer feedlot performance for the IAF and NR were starting BW (501 vs 456 kg, P = 0.007), ending BW (670 vs 604 kg, P = 0.004), feedlot finishing gain (143 vs 123 kg, P = 0.05), ADG (1.08 vs 0.93 kg/day, P = 0.06), daily DM feed intake (20.1 vs 20.1 kg/d, P = 0.98), feed to gain ratio (7.13 vs 8.22 kg/d, P = 0.11), daily feed cost ($9.61 vs $9.54/d, P = 0.94), feed cost/kg BW gain ($4.05 vs $4.67/kg, P = 0.11), and feed and yardage cost/kg gain ($4.45 vs $5.13/kg, P = 0.092). IAF and NR Yr 1 HCW (P = 0.83), dressing % (P = 0.69), marbling score (P = 0.78) did not differ. Year 2, except for hot carcass weight (HCW; 379 vs 341 kg, P = 0.004), dressing pct (P = 0.99), fat depth (P = 0.29), marbling score (P = 0.94) did not differ. Systems 2-yr mean net return for DLOT, IAF, and NR were $592, $296, $379, respectively. Systems net return profitability was very good for all management comparisons, but reduced for IAF and NR due to IAF farming, finishing, and transportation costs, and NR finishing and transportation costs.

420 Automated identification and behavioral estrus detection in freestall-housed dairy cows using computer vision and machine learning: A two-layered algorithm approach

Abstract A critical aspect of dairy management involves maintaining accurate records of individual animals and promptly detecting estrus behavior, which is vital for successful breeding and reproductive outcomes. Recent advancements in precision livestock management, utilizing computer vision and machine learning technologies, have paved the way for automated and precise solutions in these areas. The objective of this study is to investigate the application of computer vision and machine learning for animal identification and behavioral estrus detection in dairy cows housed in freestall settings, employing a two-layered algorithmic approach. The research was conducted at the Joe Bearden Dairy Research Center, where a total of 10 lactating Holstein-Friesian cows were assessed across a 7-d trial period. For synchronization efforts, cows were provided a single injection of Prostaglandin F2α at trial initiation with expected estrus behaviors to be exhibited within the following 56 h. Continuous video was captured in 4k resolution using a five-camera closed caption media recording system strategically placed in the pen corners and over the feed bunk alleyway to capture multiple perspectives. Video data extrapolated into frames and manual annotation was utilized to generate the machine learning algorithm’s training data. Frames were randomly selected from a scattering of 56 h of video across all five camera viewpoints and down sampled to 384 x 640 p for both layers. A two-layer approach was employed utilizing an algorithm for each aspect of the study with the first model detecting the behavior, and the second model using the detected region of interest to identify specific cows. The first layer was trained on 682 frames and validated against 123 manually annotated frames. The second layer was trained on 102 frames and validated against 16 frames manually annotated for individual animals. Results demonstrated that the model used for mounting behavior identification has high precision (0.819) and recall (0.89), achieving a 0.926 mAP at an IoU of 0.5. This model achieved an F1 score of 0.86 at a confidence threshold of 0.268. The results demonstrated that the model used for individual animal identification across different classes achieved high precision (0.861) and recall (0.842), with a mAP of 0.897 at an IoU of 0.5. The F1 score for all classes was 0.89 at a confidence threshold of 0.788. In conclusion, these promising findings underscore the potential of computer vision and machine learning technologies to revolutionize dairy cow management practices. This innovative approach not only has potential to enhance operational efficiency, but also contributes significantly to improved reproductive management, thereby advancing precision and productivity in dairy operations.

7 Role of the preovulatory follicle in oocyte metabolic and developmental competence for pregnancy

Abstract A majority of bovine pregnancy loss occurs in the first 7 d of gestation. The oocyte is a key driver of embryo viability during this time, and its competence for embryo development and pregnancy establishment is greatly influenced by the surrounding microenvironment during oocyte maturation. Assisted reproductive technologies allow for more efficient propagation of superior genetics and improved reproductive management of the cattle herd; however, many assisted reproductive technologies alter the normal microenvironment of the maturing oocyte and negatively impact oocyte competence for early embryo development. For example, oocytes induced to ovulate from preovulatory follicles of lesser physiological maturity (decreased estradiol production and smaller diameter) have reduced blastocyst development, poorer embryo quality, and a hastened rate of embryo development compared with those ovulated from follicles of greater maturity. Our overarching hypothesis is that the intrafollicular milieu of physiologically mature preovulatory follicles provides the necessary microenvironment to metabolically program maturing oocytes for successful embryo development. Studies by our team have demonstrated that the follicular fluid metabolite milieu during in vivo oocyte maturation differs between preovulatory follicles of greater and lesser maturity and that such differences have direct effects on the maturing oocyte. Numerous follicular fluid metabolites involved in glucose and amino acid metabolism were more abundant in preovulatory follicles of greater versus lesser physiological maturity. Additionally, abundance of transcripts encoding glycolytic enzymes was higher in cumulus cells from follicles of greater maturity, and both ATP and levels of key transcripts in the mitochondrial respiratory chain were higher in oocytes collected from preovulatory follicles of greater versus lesser maturity. We supplemented in vitro maturing oocytes with follicular fluid from preovulatory follicles of greater or lesser maturity to determine causality of differing follicular fluid milieu on cumulus-oocyte metabolism and oocyte competence for early embryo development. Follicle maturity status had robust effects on cumulus-oocyte complex consumption or production of key metabolites in glucose, purine, and amino acid metabolism pathways during oocyte maturation. We also observed hastened development rate in embryos arising from in vitro matured oocytes supplemented with lesser maturity follicular fluid, mirroring past in vivo findings by others. Furthermore, RNA-sequencing of resulting blastocysts of identical stage and quality suggested more efficient metabolism and Wnt/β-catenin signaling in blastocysts derived from oocytes matured in preovulatory follicular fluid from greater maturity follicles. In contrast, transcriptome profiles of blastocysts from oocytes matured in preovulatory follicular fluid from lesser maturity follicles indicated oxidative stress and dysregulated cell division. These recent findings by our lab indicate that impacts of follicle maturity and the resulting follicular fluid microenvironment on the maturing oocyte withstand throughout early embryo development and hold promising roles to improve reproductive efficiency in cattle.

389 Impact of a Controlled Internal Drug Release device on circulating and local concentrations of progesterone

Abstract Controlled Internal Drug Release (CIDR) devices have become an important component of reproductive management programs in many beef herds. When a CIDR is inserted into a cow, circulating concentrations of progesterone mimic a functional corpus luteum. Some data, however, suggest that concentration of progesterone following insertion of a CIDR might have negative consequences on fertility in Bos indicus animals. Therefore, the objective of this study was to determine the impact of a CIDR device on circulating and uterine tissue concentrations of progesterone. A blood sample and a uterine biopsy were collected from non-suckled postpartum cycling Brahman cows (n = 10; Cycling) during the midluteal stage. A blood sample and a uterine biopsy were also collected from non-suckled postpartum cycling Brahman cows (n = 9; CIDR) after a CIDR had been in place for 5 d. To collect uterine biopsies from CIDR cows, the uterine biopsy tool was placed inside a plastic covering, both were passed into the cervix of the cow before the tool was extended through the covering and into the uterus. After the biopsy was collected, the tool was carefully removed to prevent sample contamination. Blood samples were centrifuged, and serum was collected to determine concentrations of progesterone. Uterine biopsies were snap frozen until extraction. Biopsies were weighted, thawed, and homogenized in assay buffer. Samples were then extracted with methyl tert-butyl ether and resuspended in assay buffer. Serum concentrations are reported as ng/mL and uterine concentrations are reported as ng/g. Statistical analysis was performed using the GLM procedure in SAS with treatment (CIDR vs Cycling), tissue type (uterine vs serum) and their interaction included in the model. There was a significant effect of treatment (P = 0.0062), tissue (P = 0.0063) and a treatment by tissue interaction (P = 0.0068). Animals with a CIDR had greater concentrations of progesterone than Cycling animals (274.77 vs 4.37 ng, respectively). Uterine samples had greater concentrations of progesterone than serum samples (274.40 vs 4.74 ng, respectively). These increased concentrations of progesterone were mainly from CIDR uterine samples (543.24 ng/g) which had greater (P < 0.001) concentrations of progesterone compared with all other samples, which did not differ from each other (P > 0.98; CIDR Serum 6.29 ng/mL, Cycling Serum 3.2 ng/mL, and Cycling Uterus 5.54 ng/g). In summary, CIDRs increased circulating concentrations of progesterone sufficient to keep animals from exhibiting estrus, and were not different from cows in the midluteal stage of their cycle. Local concentrations in uterine tissue; however, were significantly greater when a CIDR was in place compared with uterine tissue collected during the midluteal phase. The implications of these significantly greater concentrations of progesterone in uterine tissue warrant further investigation.

Infrared thermometry for detecting estrus and pregnancy in Holstein cows

Efficient reproductive management is paramount in enhancing the productivity and welfare of dairy cows. This study investigates the effects of pregnancy status, seasonal variations, and diurnal shifts on the body temperature of different body parts in dairy cows. Using a structured approach, cows were categorized based on pregnancy status (pregnant vs. control) or estrous status (estrous vs. control), season (winter, spring, summer), and time of day (morning, noon, evening). The analysis revealed that pregnancy and estrous statuses significantly affect the body temperature, with pregnant and estrous cows displaying higher temperatures (39.0 ± 0.03 and 38.0 ± 0.06 °C, respectively) than controls (37.1 ± 0.06 °C; p < 0.01). Seasonal impacts were also notable, with the highest temperatures observed in summer (38.3 ± 0.07 °C) followed by spring (38.1 ± 0.09 °C) and winter (37.7 ± 0.06 °C; p < 0.01), indicating a strong environmental influence on physiological responses. Furthermore, diurnal analysis indicated temperature fluctuations throughout the day, peaking at noon (38.1 ± 0.09 °C; p < 0.05) compared to morning and evening. High positive correlations were observed between the measured temperatures in different areas and rectal and vaginal temperatures, suggesting the skin surface is ideal for assessing thermal changes. These findings underscore the critical interplay between an animal's physiological state and external environmental factors in managing dairy cow health and reproduction. The study highlights the potential of non-invasive temperature monitoring as a tool for optimizing reproductive management and underscores the necessity of accounting for environmental and physiological variations in dairy management practices.

Association between Serum Glycated Hemoglobin Levels and Female Infertility: A Cross-Sectional Survey and Genetic Approach.

Female infertility affects a significant portion of the population, and recent studies suggest a potential link between glycemic control and reproductive health. This study investigates the association between serum glycated hemoglobin (HbA1c) levels and female infertility, utilizing data from the NHANES 2017-2020 and Mendelian randomization (MR) analysis. A cross-sectional study was conducted with 1578 women aged 20-45 who attempted pregnancy for at least one year. Serum HbA1c levels were analyzed in relation to infertility status, with multivariable logistic regression models adjusting for covariates such as age, body mass index, race/ethnicity, education, marital status, hypertension, and hyperlipidemia. Higher HbA1c levels were significantly associated with increased infertility risk. Each 1% increase in HbA1c was linked to higher odds of infertility (adjusted OR: 1.40, 95% CI: 1.15-1.69, p = 0.003). HbA1c levels ≥ 6.5% showed the strongest association. MR analysis employed single-nucleotide polymorphisms as instrumental variables to assess the causal relationship between HbA1c and infertility, confirming a causal relationship between higher genetically predicted HbA1c levels and infertility (OR: 1.82, 95% CI: 1.33-2.49, p = 0.00018). Sensitivity analyses supported the robustness of these findings. Elevated HbA1c levels are associated with an increased risk of female infertility, suggesting the importance of glycemic control in reproductive health management.

Problems of reproductive risk management in occupational medicine and issues of causation

In the Russian Federation, 2024 has been declared the year of the family, which, in the context of the growth of domestic industrial production, determines the importance of preserving the reproductive health of women working in harmful and unfavorable working conditions, preventing the adverse effects of factors in the working environment and the labor process on women’s health indicators. The review examines publications presented in the RSCI, PubMed, Scopus, and Google Scholar databases, which cover mainly the last 10 years (2013–2023)

Adjusting the timing of inseminations to the time lag on luteolysis alerts results in higher conception in dairy cattle

Dairy cow fertility is a complex trait that depends on the cow's physiological status, the farm's environmental and management conditions, and their interactions. Already the slightest improvement in fertility can positively impact a farm's profitability and sustainability. In research, milk progesterone (P4) has often been used as an accurate and feasible way to identify a dairy cow's reproduction status. Moreover, in Europe and Canada, it has been used to improve fertility management on commercial farms as it allows to accurately identify reproduction issues, pregnancy and the optimal insemination window. An on-farm P4 device (OPD) automatically samples, measures and monitors the milk P4 concentration of individual cows. To this end, the P4 data is smoothed to be robust for measurement errors and outliers, and fixed thresholds are used to estimate the time of luteolysis preceding ovulation, thereby generating a luteolysis alert (LA). By smoothing the P4 data, the OPD introduces a time lag on the LA. Variation in this time lag is not considered in the estimation of the optimal insemination window that is advised to the farmer. Ignoring this variation might decrease the accuracy of the optimal insemination window and, therefore, decreases the likelihood of conception. We hypothesize that considering the length of the time lag and adapting the advice accordingly improves the conception rate. This observational retrospective study uses an extensive data set from 17 commercial dairy farms that are equipped with an OPD. We estimated the time lag on the alerts and evaluated their relationship with the interval from LA to insemination for successful (n = 3721) and unsuccessful inseminations (n = 3896) separately. Results showed that the probability of conception increases when a longer LA time lag is compensated with a shorter interval from LA to insemination and vice versa. In addition, for successful inseminations, we found a clear negative relation between the time lag and the interval from LA to insemination and the interval was significantly shorter when the time lag of the LA was longer. This negative relation between time lag and interval from LA to insemination was less pronounced for unsuccessful inseminations. Additionally, we evaluated the conception rates for inseminations that are performed too early, in time or too late with respect to the optimal insemination window advised by the OPD, in function of their associated time lags. We found that, for inseminations that were preceded by a short time lag (<8 h), the conception rate was 17.5 percentage points higher when cows were inseminated later than advised. Likewise, when inseminations were preceded by a long time lag (≥24 h), we found that the conception rate was 13 percentage points higher when cows were inseminated earlier than advised. Our results suggest that farmers using an OPD could potentially increase their conception success by compensating the variable time lag on the LA by adapting the interval from alert to insemination accordingly. This could be used to develop reproductive management strategies to improve reproductive performance on those farms, which can positively impact their sustainability.

Bottom-up approach to deciphering the targets of the ubiquitin-proteasome system in porcine sperm capacitation

Capacitation is an essential post-testicular maturation event endowing spermatozoa with fertilizing capacity within the female reproductive tract, significant for fertility, reproductive health, and contraception. By using a human-relevant large animal model, the domestic boar, this study focuses on furthering our understanding of the involvement of the ubiquitin-proteasome system (UPS) in sperm capacitation. The UPS is a universal, evolutionarily conserved, cellular proteome-wide degradation and recycling machinery, that has been shown to play a significant role in reproduction during the past two decades. Herein, we have used a bottom-up proteomic approach to (i) monitor the capacitation-related changes in the sperm protein levels, and (ii) identify the targets of UPS regulation during sperm capacitation. Spermatozoa were capacitated under proteasomal activity-permissive and inhibiting conditions and extracted sperm proteins were subjected to high-resolution mass spectrometry. We report that 401 individual proteins differed at least two-fold in abundance (P < 0.05) after in vitro capacitation (IVC) and 13 proteins were found significantly different (P < 0.05) between capacitated spermatozoa with proteasomal inhibition compared to the vehicle control. These proteins were associated with biological processes including sperm capacitation, sperm motility, metabolism, binding to zona pellucida, and proteasome-mediated catabolism. Changes in RAB2A, CFAP161, and TTR during IVC were phenotyped by immunocytochemistry, image-based flow cytometry, and Western blotting. We conclude that (i) the sperm proteome is subjected to extensive remodeling during sperm capacitation, and (ii) the UPS has a narrow range of distinct protein substrates during capacitation. This knowledge highlights the importance of the UPS in sperm capacitation and offers opportunities to identify novel pharmacological targets to modulate sperm fertilizing ability for the benefit of human reproductive health, assisted reproductive therapy, and contraception, as well as reproductive management in food animal agriculture.

Reproductive Disorders in Donkeys: Current Evidence and Update.

Reproductive disorders in donkeys present a significant challenge to their health and welfare, impacting their roles in agriculture, conservation, and companionship. With the development of large-scale donkey farming in recent years, reproductive disorders have become a limiting factor for the expansion of the donkey population. In general, donkeys suffer from a similar array of diseases like horses, but little is known about the specificities of donkey reproductive disorders. This review synthesizes current knowledge on the pathogenesis, distribution, presentation, diagnosis, treatment, and prognosis of a diverse array of reproductive disorders affecting donkeys. There are similar infectious and non-infectious causes for infertility and pregnancy loss in jennies compared with mares, but a difference in disease susceptibility does exist, which may be attributed to genetic influence, pathogen specificity, the environment, and reproductive management practices. Diagnostic and treatment plans need to be tailored towards the particularities of donkey reproductive disorders to increase donkey populations and to enhance the standard of care for this species. Enhancing reproductive health in donkeys not only ensures their sustainable use but also promotes their welfare and longevity in diverse human-animal interactions.

Evaluation of Hormonal and Biochemical Profile of Ladakhi Cow during Estrous Cycle: The Future Perspective of Reproductive Management of Ladakhi Cow

The Ladakhi cow is an indigenous breed from Ladakh, India, and has a unique genetic makeup to adapt to high-altitude hypobaric stress. Furthermore, little study is available on examining the Ladakhi cow’s blood biochemicals and reproductive hormonal status during various stages of the estrus cycle. Hence, the current study was conducted on eight reproductively mature Ladakhi cows at the experimental dairy cattle unit in Leh-Ladakh, India, to determine the changes in serum biochemical and hormonal levels during the estrus cycle. The estrus behaviour was initially observed before the blood sampling on days 0 (the day the cow exhibited heat symptoms), 2nd, 8th, 17th, and 21st days. The serum was isolated for biochemical and hormonal profiling as per standard procedures using commercially available kits. The results revealed that serum biochemicals, viz. Ca, Fe, ALT, AST, ALP, TG, TP, Albumin, Glucose, UA, Creatinine, and Urea levels were within the normal range of cows at high altitudes. However, reproductive hormones, e.g. GnRH, FSH, LH, progesterone, estrogen, PGF2α, IGF-1, and Insulin varied from the reference level at different stages of the estrus cycle. This study’s findings have provided new insights into the serum biochemical and hormonal profiling of Ladakhi cows during the estrus cycle and this information may help to develop a reference range and baseline value for the serum biochemicals and hormonal levels of Ladakhi cows for other breeding programs and health monitoring.

Enhancing early identification of high-fertile cattle females using infrared blood serum spectra and machine learning

Artificial insemination (AI) success in bovine reproduction is vital for the cattle industry’s economic sustainability and for advancing the understanding of reproductive physiology. Identify high-fertile animals’ fertility is a complex task due to multifactorial traits, including hormonal, age-related, and body condition factors. Early high-fertility identification is crucial for timely interventions and enhancing AI success. In this study, we present the potential use of Fourier-transform infrared (FTIR) spectroscopy on blood serum for early identification of high-fertile Nellore female cows for AI protocols. Blood serum FTIR spectra were obtained from Nellore female cows before AI. FTIR spectra underwent data analysis and the results demonstrated successful discrimination between animals that exhibit pregnant and non-pregnant diagnoses 30 days after AI. FTIR spectra revealed consistent vibrational modes, emphasizing Amide I and II bands. Principal Component Analysis (PCA) effectively segregated groups based on molecular information. Linear SVM with C = 10 and 4 PCs achieved 100% accuracy in the group classification. This innovative approach using FTIR spectroscopy and ML algorithms offers a promising means of high-fertile cow identification, potentially improving AI outcomes in Nellore cattle. The study presents valuable insights into advancements in reproductive management practices for this economically significant breed.

Intracytoplasmic sperm injection zone: insights and applications from a university-based assisted reproduction laboratory

Intracytoplasmic sperm injection (ICSI) has become one of the most important tools used for in vitro production of embryos (IVP) in equine reproduction management programs around the world. This procedure is often performed in the US for several breeds and is used primarily to optimize foal production for broodmares and performance mares but also for stallions with limited semen availability or poor semen quality. As such, there are a limited number of US laboratories capable of using this method, which requires advanced training of personnel and specialized equipment. Many veterinarians and breeding farms currently aspirate ovarian follicles in cycling mares and ship oocytes to ICSI-capable laboratories, where embryos can be produced and typically vitrified for ultralow temperature storage and transport for transfer to recipient mares and establishment of surrogate pregnancies. The Veterinary Assisted Reproduction Laboratory in the School of Veterinary Medicine at the University of California, Davis, maintains a 3-dimensional approach to equine assisted reproductive technology. We offer commercial solutions to breeders, educational advice and training to other laboratories, veterinarians, and visiting scholars. Moreover, as a research laboratory, our objective is to analyze and apply observations from IVP to elucidation of complex developmental problems such as embryonic and fetal loss. In 2018, we reported the birth of the first foal produced at UC Davis using ICSI, and we have since developed a commercial ICSI program for practitioners and horse breeders in the US. Today, our laboratory receives thousands of immature oocytes for ICSI sessions every year, with an average of 2 embryos per mare-session. Our research is focused on molecular, cellular and genetic aspects of gamete biology, perifertilization events, and early equine development using an array of tools including advanced microscopy, sequencing, and time-lapse imaging of developing embryos. In this review, we have highlighted our laboratory’s current methods for commercial equine IVP and research and clinical studies conducted to optimize IVP in horses.

An IMU-based machine learning approach for daily behavior pattern recognition in dairy cows

Technological advancements have revolutionized livestock farming, notably in health monitoring. Traditional methods, which have been criticized for subjectivity and treatment delays, can be replaced with efficient health monitoring systems, thereby reducing costs and workload. Implementing cow behavior recognition allows for effective dairy cow health monitoring. In this research, we propose an integrated system using inertial measurement unit (IMU) devices and machine learning techniques for dairy cow behavior recognition. Six main dairy cow behaviors were studied: lying, standing, walking, drinking, feeding, and ruminating. All behavior types were manually labeled into the IMU data by reviewing the recorded footage. The labeled IMU data underwent four processing steps: selecting different window sizes, feature extraction, feature selection, and normalization. These processed data were then used to build the behavior recognition model. Various model structures, including SVM, Random Forest, and XGBoost, were tested. The top-performing model, XGBoost, with its proposed 58 features achieved an F1-score of 0.87, with specific scores of 0.93 for lying, 0.85 for walking, 0.94 for ruminating, 0.89 for feeding, 0.86 for standing, 0.93 for drinking, and 0.59 for other activities. During our online testing, we observed similar patterns for each healthy cow. The cumulative time spent on each behavior also matched the statistics from previous surveys. Additionally, our backend optimization approach resulted in a final overall percentage error of 1.55 % per day during online testing. In conclusion, our study presents an IMU-based system capable of accurately recognizing dairy cow behavior. Feature design and appropriate models are proposed herein. A functional optimization method was introduced indicating that our system has the potential with applications for estrus detection and other reproductive management practices in the dairy industry.

Physiological Function of Gut Microbiota and Metabolome on Successful Pregnancy and Lactation in the Captive Yangtze finless porpoise (Neophocaena asiaeorientalis asiaeorientalis).

The gestation period in captive Yangtze finless porpoise (YFP) is a well-coordinated and dynamic process that involves both systemic and local alterations. The gut microbiota and its connection to fecal metabolites are crucial in supporting fetal development and ensuring maternal health during reproductive stages. This study evaluates changes in the gut microbiota and their correlation with fecal metabolites in captive YFPs during different reproductive stages. The results reveal that microbial community structure changed significantly during reproductive stages, while gut microbial diversity remained stable. The genus unclassified Peptostrptococcaceae, Corynebacterium, and norank KD4-96 were significantly greater in non-pregnancy (NP), Terrisporobacter was significantly greater in lactating (LL), and Clostridium was significantly higher in early-pregnancy (EP) compared to the other groups. The host fecal metabolome exhibited significant alterations during the reproductive stages. Indoxyl sulfate, octadecatrienoic acid, and methionyl-methionine were significantly higher in the NP; galactosylglycerol, chondroitin 6-sulfate, and lumichrome were significantly higher in the EP and mid-pregnancy (MP); and valylleucine and butyryl-l-carnitine were significantly higher in the LL. The altered metabolites were mostly concentrated in pathways associated with arachidonic acid metabolism (significantly altered in NP), leucine, valine, and isoleucine biosynthesis (significantly altered in EP and MP), and glycerophospholipid metabolism (significantly altered in LL compared to others stages). Additionally, we found a strong link between variations in the host metabolism and alterations in the fecal bacteria of captive YFP. In conclusion, this study provides detailed insights into host metabolic and fecal bacterial changes in captive YFP during reproduction stages, providing important knowledge for improving the reproductive management in the captive YFP.

Comparative analysis of breeding patterns and reproductive efficiency of mares in subtropical conditions of Pakistan.

The present study aimed to evaluate and compare the overall and breed-specific seasonal breeding patterns, fertility rates, cyclicity, and follicular dynamics of Arab, Thoroughbred, and Percheron mares under the subtropical conditions of Pakistan. A retrospective analysis of climatic data and breeding records of eleven breeding studs spanning four years (2020-2023) was made to find out the overall seasonality in the breeding pattern of mares. Fifty mares of each breed (n=150 in total) were scanned by ultrasonography for a calendar year to find the cyclicity pattern and follicular dynamics (follicular growth rate, size of ovulatory follicle, and days from estrus till ovulation). The statistical analysis of breeding records demonstrated a clear pattern of seasonal breeding (p<0.05). The highest monthly foalings were noted in March (247±45.37), and overall breeding activities peaked in Spring season (p<0.05). Breed-specific results of Arab, Thoroughbred, and Percheron mares revealed that Arab mares maintained stable breeding activity throughout the year, with the highest activity in spring and peak conception rate in winter (56.25%±32.78; p>0.05). Thoroughbred mares experienced significant seasonal declines from spring to winter with a peak conception rate in winter (63.89%±27.37, p>0.05). Percherons showed the most pronounced seasonal effects, especially with a high fall conception rate (73.04%±19.61) and a sharp decrease in winter breeding metrics (p<0.05). Furthermore, Thoroughbred and Percheron mares displayed the most pronounced seasonal effects on the percentage of cyclic mares 77.3% and 56% in winters (p<0.05). Moreover, the follicular dynamics of the three breeds also exhibited significant differences (p<0.05). The current study concludes that seasonal and breed-specific variability exists among the reproductive parameters of Arab, Thoroughbred, and Percheron mares in subtropics, necessitating breed-specific reproductive management measures to maximize mare breeding efficiency.