Winter hair coat shedding ability in southern U.S. cattle production has previously been associated with differences in adjusted birth and weaning weights of calves from dams that shed by June or later (Gray et al., 2011; Cauble et al., 2019). This study was developed to research possible avenues of why these relationships exist with winter hair coat shedding ability. The primary objectives of the following experiments were to: 1) evaluate how mineral status relates to winter hair coat shedding ability, 2) evaluate how winter hair coat shedding ability relates to apparent digestibility of forage, 3) evaluate winter hair coat shedding ability’s association with uterine artery hemodynamics during gestation, 4) evaluate how winter hair coat shedding ability is associated with growth performance and development of calves from birth until weaning, and 5) evaluate how winter hair coat shedding ability relates to loin muscle (LM) relative gene expression of dams’ calves from birth until weaning. Results indicated that plasma Cu and Zn levels were greatest for dams during the grazing month of March that reach MFS by April compared to all other groups; dams that reached MFS by July had greatest forage digestibility for DM, Ash, NDF, ADF, and CP for the grazing month of May compared to all other shedding groups; winter hair coat shedding ability had a relation with ipsilateral uterine artery pulsatility at d 150 of gestation while also influencing the growth and development of the uterine artery diameter from d 150 through 210 of gestation; dams that shed by July produced calves that had shorter hip height when measured at 120 d of age and at weaning when compared to calves of dams that reached MFS in April, May, and June; and calves of dams’ that shed by July had increased expression of IGF2 compared to calves of dams’ that shed by April, May, and June, with differing results for IGF1 having the greatest expression for calves produced from dams that shed by April compared to May and June. These results may begin to explain the existing differences in adjusted birth and weaning weight of those calves.

The umami sensation contributes to beef flavor and acceptability. Inosine 5’- monophosphate (IMP) was the most abundant nucleotide in meat known to impart umami taste which thus far had been overlooked in meat flavor studies. The objectives of this study were to determine the umami taste threshold of inosine 5'-monophosphate (IMP), the effects of spiking IMP on the sensory descriptive attributes of various USDA graded beef strip steaks, and to differentiate beef by IMP content using electrochemistry. USDA Prime, Choice, and Select steaks were spiked with 0.3 and 0.6 mM IMP and analyzed chemically and organoleptically. Liquid chromatography-mass spectrometry and descriptive sensory analysis showed no changes in IMP content and the perceived sensory attributes of steaks. The electrochemical approach successfully differentiated IMP concentrations in aqueous solutions when present at 0.5 mM or above and was able to recognize the presence of nucleotides in the meat extract.

Cattle health and production records (CHPR) are data collected by cattle producers and veterinarians in the form of measurements, observations, counts of events over time, and physiologic attributes that describe individual and group-level health and production. These data are useful to both veterinarians and cattle producers for making evidence-based decisions on cow-calf operations. Currently, there are no uniform, industry-wide methods of capturing and recording CHPR in the U.S. cow-calf industry. Although many cow-calf producers in the U.S. are thought to collect some form of CHPR, it is believed that relatively few are doing so in an electronic manner that facilitates optimal use and analysis of those records. Technology offers many opportunities to collect, record, and analyze CHPR for decision-making on cow-calf operations, with smartphones having great potential as a point-of-care CHPR collection device. Little is known regarding 1) barriers faced by producers to collecting and using CHPR, 2) interest of U.S. cow-calf producers in using technology such as smartphones for collecting and recording CHPR, and 3) the role of veterinarians in the collection and use of CHPR on U.S. cow-calf operations. The first study included in this dissertation was a survey of the cattle health and production record-keeping methods of cow-calf producers in Mississippi. The second study in this dissertation was a survey of cow-calf producers across the U.S. regarding their methods and opinions of cattle health and production record-keeping, their access to technology for record-keeping purposes, current types of data being collected on cow-calf operations, and the role of veterinarians in record-keeping on those cow-calf operations. The third study in this dissertation was a demonstration of common epidemiologic and biostatistical skills needed by veterinary practitioners to analyze CHPR and provide quality, evidence-based management recommendations to their cow-calf clients.

Ruminant animals comprise the greatest proportion of herbivores around the world, provide essential ecosystem services and human consumable protein by consuming grass and human inedible dietary fiber. Herbivory pressure alters plant communities and species diversity, effectively making grazing animals ecosystem engineers in dynamic ecosystems. Development of advanced computer processing power coupled with biometric and ecosystem sensors may be employed in the internet of things framework to create an integrated information system designed to inform understanding of grazing system function and animal energy balance. Towards this end, I utilized Bos indicus / Bos taurus crossbred steers (n = 20) across two study sites each in consecutive calendar years and fitted them with GPS and accelerometer collar systems. Steers were grazed in improved grass pastures containing Tall Fescue (Festuca arundinacea) and Bermudagrass (Cyanodon dactylon). Forage samples were collected in a 20-m grid pattern at 35-day intervals to test nutritional composition, and NDVI maps were created using remotely sensed data collected using a UAV mounted camera system. In the first chapter, I utilize the movement ecology framework to investigate metabolic theory and animal behavior on energy budgets, then explore available technology to utilize in an integrative information system. In Chapter 2, I tested preprocessing and behavior collection methods used to train a machine learning randomforest classification model to predict animal behavior using triaxial accelerometers. Landscape functional scale and optimal sampling density is the primary focus of Chapter 3, where I explored the complex relationship between sampling regime, interpolation strategy, and landscape complexity, demonstrating that sampling density is a product of desired accuracy and landscape complexity. Finally, I focused on animal growth in Chapter 4, demonstrating the functionality of a walk-over-weigh system, and identified robust regression as the most accurate smoothing method to identify and remove spurious animal weights.