bluuebunny/crossref_metadata_2025_split huggingface dataset:
232 Influence of melatonin supplementation on uterine and coccygeal artery hemodynamics of pregnant multiparous crossbred beef cows grazing endophyte-infected tall fescue
Authors: Snider Miriam A , Culp Timothy C , Hopkins Carson R , Moss Nathaniel T , Edwards J Lannett , Looney Charles R , Powell Jeremy G , Kegley Elizabeth B , Coffey Ken P , Gadberry M Shane , Lemley Caleb O , Littlejohn Brittni P 
Published: September 2024

Abstract
The objective was to determine the influence of melatonin supplementation on uterine and coccygeal artery hemodynamics of pregnant beef cattle grazing toxic, endophyte-infected (E+) tall fescue during mid-late gestation. Multiparous crossbred cows were artificially inseminated with sex-sorted semen (Y chromosome-bearing sperm) from a single Red Angus sire and maintained on pastures free from E+ fescue prior to the start of the treatment period. Pregnant cows (n = 50) were assigned to one of three treatment groups with two replications per treatment: non-toxic, novel endophyte-infected (NE+) fescue without melatonin supplementation (NE+/NM; n = 16), E+ fescue with melatonin supplementation (E+/M; n = 16), and E+ fescue without melatonin supplementation (E+/NM; n = 18). Treatments were administered over a 70-d period between May and July (d 147 ± 1 to 217 ± 1 of gestation). A commercially available feed was mixed with or without melatonin [100 µg/kg body weight (BW)] and hand-fed daily. Cows were weighed at d 0, 14, 28, 42, 56, and 70 relative to the start of the treatment period. Measures of uterine and coccygeal artery hemodynamics included artery diameter, pulsatility index (PI), resistance index (RI), blood flow (BF), and blood flow as a proportion of BW (BF/BW) and were determined by color Doppler ultrasonography at the conclusion of the 70-d treatment period. Plasma prolactin was determined at the end of the 70-d treatment by radioimmunoassay. After the treatment period, cattle were maintained together as a single group on pastures that were free from E+ fescue. Body weights were analyzed using the MIXED procedure of SAS specific for repeated measures with treatment, time, and the interaction as fixed effects and replicate as random. Prolactin and arterial hemodynamics were analyzed using the MIXED procedure of SAS with treatment as a fixed effect and replicate as random. There was an effect of time and a treatment by time interaction on cow BW (P &lt; 0.01). Prolactin was decreased (P = 0.02) in E+/NM (71.8 ± 14.0 ng/mL) and E+/M (86.9 ± 14.9 ng/mL) relative to NE+/NM (128.9 ± 14.9 ng/mL) cows. Coccygeal artery PI was decreased (P &lt; 0.02) in E+/M (0.86 ± 0.1) relative to NE+/NM (1.06 ± 0.1) cows. Coccygeal artery RI was decreased (P &lt; 0.01) in E+/M (0.53 ± 0.02) relative to NE+/NM (0.62 ± 0.02) cows. There were no other effects of treatment (P &gt; 0.05). Preliminary results suggest limited effects of melatonin on uterine and coccygeal artery hemodynamics in pregnant multiparous crossbred beef cows grazing endophyte-infected tall fescue.
231 Ovarian follicle diameter and corpus luteum volume of beef cows enrolled in fixed-time artificial insemination while receiving chromium propionate supplementation
Authors: Vidlund Trinity , Currin John , Clark Sherrie , Stewart Jamie L , Craun Hannah , Mitchell Camille , Wolpert Bailey , Redifer Tracey , Mercadante Vitor R G 
Published: September 2024

Abstract
We investigated the effects of chromium propionate (CrP) supplementation on reproductive performance of beef cows during the pre-partum and breeding periods. Angus-based commercial suckled beef cows were stratified by predicted calving date, body weight (BW) and randomly assigned to one of two treatments: 1) Control, (n = 30) supplementation of a corn gluten, soy hull pellet feed (50:50) with a mineral pack at 1 kg ּ cows-1 d-1; or 2) CrP, (n = 32) supplementation at 1 kgּ cow-1ּּ d-1 of a corn gluten, soy hull pellet feed (50:50) with a mineral pack containing 1.4 g of CrP (KemTRACE chromium 0.4%, Kemin Industries, Inc., Des Moines, IA). Cows remained on a single pasture equipped with feed bunks capable of monitoring individual supplement intake (SmartFeed, C-lock Inc., Rapid City, SD). Treatments were initiated at 92 d prepartum and ended on d 35 post fixed-time artificial insemination (TAI), for a total of 127 d. Cows were enrolled in the 7-d CO-Synch+CIDR TAI protocol. Ovarian ultrasonography was performed to determine diameter of the largest follicle, and the volume of a corpus luteum (CL) on d -10, -3, 0 (TAI day), and 7. Pregnancy diagnosis was performed by ultrasonography on d 35. Cow BW was recorded on d -92, 0, and 35. Data were analyzed using the GLIMMIX and MIXED procedures of SAS with cow as the experimental and fixed effect of treatment. Age, days postpartum, and initial BW were similar (P &gt; 0.05) between treatments (7.4 and 7.2 ± 0.61 yr, 81.3 and 80.8 ± 4.61 d, 526.2 and 528.6 ± 16.21 kg for Control and CrP, respectively). Supplement intake was similar (P = 0.534) between treatments (1.22 and 1.03 gּ cow-1ּּ d-1, for Control and CrP, respectively). Cow BW was similar (P &gt; 0.05) between treatments on d 0 and 35 (548.5 and 551.4 ± 13.50 kg, 562.8 and 574.6 ± 11.41 kg, for Control and CrP, respectively). Furthermore, estrus expression and TAI pregnancy rate was similar (P &gt; 0.05) between treatments (62.1 and 61.1 ± 1.2% estrus, 55.1 and 81.2 ± 20.1% TAI pregnancy rate, for Control and CrP, respectively). However, CrP cows had a larger follicle (P = 0.028) on d 0 (13.79 and 15.56 ± 0.58 mm, for Control and CrP, respectively). Additionally, on d 7, CrP cows had an increased (P = 0.038) CL volume (15.24 and 17.55 ± 0.68 mm3, for Control and CrP, respectively). Supplementation of CrP to beef cows from the pre-partum until breeding did not change cow BW, but increased follicle diameter at TAI and subsequent CL volume.
391 The impact of trace mineral source on systemic immunological status associated with early embryonic loss in lactating dairy cattle
Authors: Leach Mary A , Tucker Hannah L M , Tucker Heather A , Seymour William , Eckelkamp Elizabeth , Shepherd Elizabeth , Mathew Daniel , McLean Kyle J 
Published: September 2024

Abstract
Milk production has doubled from 1970 to 2009 but has been associated with a decline in fertility. Around 25% of failed pregnancies in dairy cattle are due to embryonic loss. Mineral bioavailability may affect embryonic retention, so we hypothesized that Zn, Cu, and Mn sources will influence systemic immunological status, which affects early embryonic retention. Holstein cows (n = 58) were randomly assigned to one of two daily oral drench trace mineral (Zn, Cu, and Mn) treatments 30 d before breeding (d -30): 1) Inorganic (ITM) or 2) Metal Methionine Hydroxy Analog Chelate (MMHAC). Before treatments began, cows were assigned to a semen type, beef vs. Holstein, equally, across treatments. All cows underwent a double Ovsynch protocol and were artificially inseminated on d 0. Humoral immunological status was assessed in serum samples taken on d 0 and d 7. Immune activity was quantified via a D2Dx systemic immunity score, which assesses samples for the presence of IgG, IgM, cytokines, and complement proteins. Ultrasonography was utilized for pregnancy confirmation on d 35, classifying cows as pregnant (P) or open. Progesterone analysis from d 21 plasma was used to categorize open cows as either non-pregnant (NP) or early embryonic loss (EEL). Statistical analyses in R Studio were completed, in two models based on pregnancy (P vs EEL and NP vs EEL), to determine the effects of mineral treatment, pregnancy status, semen type, and all interactions on humoral immune status. In the P vs EEL model, there were no effects (P &gt; 0.30) of semen type, mineral treatment, pregnancy status, or any interactions on systemic immunity score on the day of breeding (d 0) or d 7. On d 0, cows provided MMHAC had a systemic immunity score of 0.073 ± 0.008 but were not different (P &gt; 0.34) from ITM cows (0.063 ± 0.006). This trend continued on d 7 with systemic immunity scores of MMHAC cows not differing (P &gt; 0.32) from ITM cows (0.055 ± 0.004 and 0.061 ± 0.003; respectively). There was a tendency (P = 0.10) for the three-way interaction of semen type x pregnancy x treatment to influence the immunity score change from d 0 to d 7. Pregnant cows on ITM treatment bred with beef semen had a positive change in immunity score (0.020 ± 0.0085). Whereas ITM cows bred with Holstein semen that underwent EEL had a negative change (-0.015 ± 0.0085); all other means were intermediate. In the NP vs EEL model, there were no effects (P &gt; 0.14) of semen type, treatment, pregnancy status, or any interactions on systemic immunity score on d 0, d 7, or the change between d 0 and d 7. In summary, trace mineral bioavailability tended to affect systemic immunological status in P vs EEL cows but not in NP vs EEL cows, which may allow for the elucidation of immunological status differences during pregnancy establishment.
386 Pregnancy supportive metabolites are enhanced in Brahman cows on day 15 of the estrous cycle
Authors: Smith Damon , Poliakiwski Brette , Vilches Mario , Muntari Musah , Singleton Sarah A , Polanco Odile , Melo Gabriela , Mercadante Vitor R G , Moorey Sarah , Ealy Alan , Biase Fernando , Lamb Cliff C , Pohler Ky G 
Published: September 2024

Abstract
Bos indicus-influenced cattle are more resilient to pregnancy loss while receiving a restricted nutrient diet compared with Bos taurus cattle, but the mechanism behind this resilience is still unknown. To undercover this mechanism, the present study was designed with Angus (Bos taurus), Brangus (Bos indicus-influenced), and Brahman (Bos indicus) cows randomly assigned (d -30) to either a 100% maintenance diet (n = 22), or a 70% maintenance diet (n = 23) for 45 d. All cows were submitted to a 5-d CO-Synch + CIDR synchronization protocol on d -7 with ovulation induction representing d 0. A cervically navigated foley catheter was placed in the uterine horn ipsilateral to the corpus luteum on d 15 of the estrous cycle. Approximately 50 mL of phosphate buffered saline was infused into the uterus then recovered for uterine flush analysis. Recovered uterine fluid was subjected to metabolomic analysis by ultra-high performance liquid chromatography - high resolution mass spectrometry. A significant breed by metabolite interaction occurred (P &lt; 0.001). A treatment by metabolite interaction was also observed (P = 0.015) in which maintenance and restricted cows clustered within their respective treatment when plotted in an orthogonal PCA graph. Of the 101 metabolites analyzed, 7 metabolites (aspartate, glutamate, hydroxyphenylacetate, taurine, uric acid, uridine, and xanthine) differed (P &lt; 0.05) among breeds. Brahman cows had the greatest value of all 7 metabolites (P &lt; 0.05) except hydroxyphenylacetate (P &gt; 0.10). Angus and Brangus metabolomic values were similar for aspartate, taurine, and uridine (P &gt; 0.10) but differed for glutamate, hydroxyphenylacetate, uric acid, and xanthine (P &lt; 0.05). Two metabolites that were greatest in Brahman cows (aspartate and glutamate) contribute significantly to the Kreb Cycle, indicating that Brahman cows have the ability to maintain proper amounts of substrates for energy production compared with Angus cows. Both glutamate and aspartate also aid in the removal of toxic ammonium as they are substrates for a-ketoglutarate and oxaloacetate, respectively, which both consume ammonium in their respective reactions. Furthermore, uric acid (which has a precursor of xanthine) was also greatest in Brahman cows and is a potent antioxidant with strong capabilities of scattering reactive oxygen species. Finally, aspartate also aids in the detoxification of ammonium within the urea cycle. Taken together, these four metabolites (aspartate, glutamate, uric acid, and xanthine) are working together but separately with the overall goal to provide more functional energy, while removing unnecessary toxins which may be two mechanisms in how Bos indicus-influenced cows are better able to sustain optimal reproductive efficiency than Angus cows.
389 Impact of a Controlled Internal Drug Release device on circulating and local concentrations of progesterone
Authors: Perry George A , Carson Chloey P , Quail Lacey K , Blaske Sarah , Ketchum Jaclyn N 
Published: September 2024

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 &lt; 0.001) concentrations of progesterone compared with all other samples, which did not differ from each other (P &gt; 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.
461 Machine learning and AI to improve genetic prediction in beef cattle: Potential uses and misuses
Authors: Spangler Matthew L 
Published: September 2024

Abstract
The current objective is to discuss if and where machine learning (ML) and artificial intelligence (AI) fit in the genetic prediction toolbox. Critical to the discussion is recognizing that, by definition, models currently employed for routine genetic prediction are part of the ML family, albeit linear as opposed to deep, and that ML fits under the more general umbrella of AI. Henderson’s Mixed Model Equations (MME) have served the animal breeding and genetic community well for several decades and have proven useful at predicting the additive genetic merit of animals. Moreover, extensions of the MME have clearly demonstrated the ability to fit non-additive genetic effects such as dominance and epistasis. The literature contains multiple examples of comparisons of genetic prediction between ML and mixed linear models, with a general consensus that ML does not outperform the MME when the trait(s) analyzed are largely additive in nature. With this in mind, the question of where ML fits is appropriate to ask. Given not all data are equally informative due to potential heterogeneity in the data generation process it is reasonable to employ ML to categorize data based on quality. Examples of using deep learning exist as a means of avoiding rules-based approaches to data editing and to categorize and weight data based on quality prior to inclusion in routine genetic evaluations. Additionally, the phenotypes used in genetic evaluations themselves could be predicted by ML. This might be the case in the use of animal tracking to garner data on social behavior, animal health and welfare, or metrics of libido and fertility; parasite loads predicted from camera data; or animal body weight gain or feed intake predicted from partial measurements. In all cases, the size of the raw data and lack of biological interpretation associated with it could necessitate the use of a predicted value. However, the error structure associated with the predicted values and the potential for compounding errors in genetic prediction need to be considered. Given the phenotype of an animal arises due to genetic and environmental effects and the complex interactions among and between these two broad sources of variation, the use of ML could be envisioned to predict phenotypic outcomes to aid in management and marketing decisions. To exploit this possibility, and outperform mixed linear models, the environmental data used would need to be sufficiently granular and high dimensional. There also exists the potential to employ ML to perform feature selection, as in the case of selecting variants from whole genome sequencing where feature subsets may be informed by multiple layers of external information. The use cases for AI also include decision support to help practitioners make use of enumerable genetic predictions given their unique objectives and circumstances.
463 Cyber-Physical Systems with robots and AI for precision dairy farming
Authors: Kaur Upinder 
Published: September 2024

Abstract
The emergence of precision livestock farming (PLF) offers a transformative lens through which to prioritize animal welfare. At the heart of this transformation lies the rumen, a complex microbial ecosystem within dairy cows responsible for converting feed into nutrients and impacting cow health, productivity, and environmental footprint. Despite its pivotal role, our understanding of the inner workings of the rumen remains limited due to a lack of real-time monitoring tools. My research leverages AI and robotics in PLF to address this gap, focusing on developing a closed-loop system for continuous, in-vivo rumen monitoring. This system employs cyber-physical systems (CPS) embedded with modular sensors and adaptive algorithms. These sensor modules, powered by AI-based data tracking, autonomously monitor rumen temperature, humidity, pressure, and methane concentration, enabling early detection of imbalances and prompt interventions to maintain optimal rumen health. A key innovation is the self-powered in-vivo robot capable of traversing the rumen’s stratified layers. Guided by AI-powered localization, this robot unlocks unparalleled access to new data, aiding in identifying specific regions associated with conditions like subacute ruminal acidosis (SARA) and methane production. This non-invasive approach eliminates the need for traditional cannulation, minimizing stress on the animal and opening new avenues for animal scientists. The impact of this research extends beyond individual cow health. By optimizing rumen function, we can improve feed efficiency, reduce methane emissions, and promote overall sustainability in dairy farming. Additionally, real-time data insights pave the way for precision nutrition, tailored interventions, and improved disease prevention, directly enhancing animal welfare. This novel approach to rumen monitoring represents a significant step towards realizing the full potential of PLF. By integrating AI and robotics, we can usher in a future where animal welfare and environmental sustainability go hand-in-hand, ultimately contributing to a more responsible and ethical dairy industry.
451 Establishing producer research sites for the development of beef and bison climate-smart agriculture
Authors: Zuidema Dalen , Cammack Kristi M , Blair Amanda , Menendez Hector M , Brennan Jameson R , Graham Christopher , Short Rachel A 
Published: September 2024

Abstract
Greenhouse gas (GHG) emissions and livestock production are topics that are increasingly intertwined. While livestock production is frequently presented as harmful to the environment, this perception fails to consider the carbon sequestration that takes place in livestock grazing systems and the role that grazing ruminants have in maintaining healthy grassland ecosystems. Grazing lands, which are often unsuited to row crop agriculture, are estimated to account for 25% of the global soil sequestration potential for soil carbon storage. Grazing livestock producers are often overlooked in the GHG reduction conversation, despite over 70% of beef GHG emissions being attributed to the cow-calf sector, which is primarily grazing. Furthermore, there is a relative lack of data surrounding the implementation of climate-smart agriculture practices on grazing operations and a lack of cost-effective methods to measure carbon/GHG sinks and sources on these landscapes. The potential climate benefits are considerable, with nearly 940 million acres of rangelands in the U.S. supporting forage-based livestock production. South Dakota State University recently received funding to support a large-scale climate-smart project focused on grazing beef and bison. For this project, we are utilizing the Cottonwood Field Station that has over 80 yr of historical grazing data, along with six grazing beef and bison ranching operations in the Northern Great Plains. The work on these ranches will focus on measuring and monitoring the impacts of climate-smart NRCS land practices, including cover crops, improved pasture and range seedings, prescribed grazing, and prescribed burning. A significant focus will be extensive, annual soil sampling across these operations to continuously monitor changes in soil organic carbon, bulk density, texture, pH, and soil microbiome community profiles. Each operation will have GreenFeed methane pasture units deployed for 5 yr to monitor changes in beef cattle and bison methane emissions in response to climate-smart practice adoption. We are also assessing biodiversity pre and post climate-smart practice adoption, as biodiversity improvements may be one of the most overlooked and yet most important responses to climate-smart land practice implementation. Over the duration of this project, a large-scale, comprehensive data collection will be achieved and used to refine GHG and carbon sequestration estimates associated with range livestock systems. Data resulting from this project will be used to inform research protocols and prediction models, fill knowledge gaps, and shape science-based discussions and marketing strategies for climate-smart agricultural commodities.