During early lactation dairy cows often experience health disorders, which are usually associated with decreased production and reproduction variables. Following parturition, cows use more energy for maintenance and milk production than they consume and enter into a state of negative energy balance. Negative energy balance in early lactation is thought to contribute to decreased milk production, reduced reproductive performance, and increased health disorders. Flunixin meglumine (FM) is an anti-pyretic (fever reducing) and anti-inflammatory drug that is commonly used in the dairy industry. This study evaluated the effect of FM on pyrexia, production and bioenergetic variables in postparturient dairy cows.

Master of Science / Department of Animal Sciences and Industry / Barry Bradford / During the transition period, 3 wk before to 3 wk after calving, dairy cows experience a variety of sudden hormonal and metabolic shifts that could result in metabolic disorders or diseases, which can be detrimental to the productive life and longevity of the cow. Cows undergo a negative energy balance, where they cannot consume enough feed to meet their energy requirements. To make up this deficit, cows mobilize adipose tissue in the form of non-esterified fatty acids (NEFA) which are transported to the liver and are either used for fuel or stored as triglycerides. High levels of circulating NEFA can lead to endoplasmic reticulum (ER) stress, which is linked to inflammation. This low-grade inflammation can compromise cell function. To mitigate this inflammation, sodium salicylate, a non-steroidal anti-inflammatory drug (NSAID), was given to mature (3+ parity) cows for 7 d after parturition via their drinking water. Blood was collected daily and a glucose turnover assay was performed. Liver, muscle, and adipose tissue was collected on d 7. Overall, it appeared that SS increased insulin sensitivity and depressed gluconeogenesis post-transcriptionally. Multiple in vitro studies were performed on immortalized bovine mammary epithelium (MAC-T) cells to determine the action of SS when ER stress was induced with palmitate (PALM). Treatment with SS did not mitigate, and in some cases exacerbated, the ER stress response. The addition of bovine serum albumin (BSA), a common component of cell culture media, may alter reactive oxygen species (ROS) measurements due to its antioxidant property. Overall, SS seems to alter metabolic processes and the cellular response to stress.

Precision dairy monitoring technologies can be used to monitor changes in physiology and behavior associated with transition period postpartum diseases and heat stress. Research Objective One was to evaluate how traditional visual examination, body condition, and locomotion with and without blood, milk, and urine variables and precision dairy monitoring technologies determine variable association with hyperketonemia, metritis, mastitis, hypocalcemia and retained placenta,. This was accomplished by monitoring cows 2 weeks before calving to 3 weeks after calving for any postpartum diseases using daily visual examination and automatically detected variables including activity, milk yield, milk components, lying behavior, feeding behavior, rumination time, and reticulorumen temperature. Deviations in reticulorumen temperature, milk production, eating time, lying time, and activity were detected by precision dairy monitoring technologies among cows with postpartum diseases. Research Objective Two was to determine the association between automatically detected variables and heat stress. This objective was accomplished by monitoring cows under natural ventilation, fans, and fans plus sprinklers for variations under each condition. Changes in physiology and behavior as detected by precision dairy monitoring technologies was associated with postpartum diseases and heat stress. Using precision dairy monitoring technologies and visual examinations may aid producers in identifying postpartum disease and heat stress.

No description available.

Doctor of Philosophy / Department of Animal Sciences and Industry / Barry J. Bradford / The mechanisms behind the metabolic changes observed when transition cows are administered monensin, as well as the effects of supplementing mid-lactation cows with two commercial amino acid products were investigated. Traditionally, the effects of monensin are attributed to increased gluconeogenic precursor supply, but recent research indicated that the effects of monensin extend beyond gluconeogenic flux. Thus, the primary objectives of Experiment 1 were to determine if monensin modulates transition cow feeding behavior, ruminal pH, and/or expression of key metabolic genes. Overall, monensin decreased time between meals prepartum (126 vs. 143 ± 5.0 min; P < 0.03) with a trend appearing postpartum (81.4 vs. 88.8 ± 2.9 min; P < 0.08), which could be related to the smaller ruminal pH standard deviation during the first day cows received the lactation ration (0.31 vs. 0.26 ± 0.015; P < 0.02). Monensin also increased liver mRNA abundance of carnitine palmitoyltransferase 1a (0.15 vs. 0.10 ± 0.002 arbitrary units; P < 0.04), which corresponded to a slower rate of liver triglyceride (TG) accumulation from 7 days before calving through 7 days post calving (412 vs. 128 ± 83 mg TG/g protein over this time period; P = 0.03). No significant effects of monensin supplementation were observed on other metabolic parameters or milk production. Overall, these results confirm that the effects of monensin on transition cows extend beyond altered propionate flux. In Experiment 2, mid-lactation cows consuming a control diet containing 26% wet corn gluten feed (dry matter basis) were compared to cows consuming the same diet supplemented with lysine embedded within Ca salts of fatty acids and the isopropyl ester of 2-hydroxy-4-(methylthio) butanoic acid, a methionine precursor. This trial was conducted because the NRC (2001) model indicated a lysine deficiency prior to supplementation; however amino acid supplementation had no effects. This trial was then extended to decrease dietary CP from 17.9% to 17.1%, and further increase lysine and methionine supply in the treatment diet. No production or intake effects were observed during this period, but MUN was decreased in the treated group (10.8 vs. 12.5 ± 0.2 mg/dL; P < 0.001).

Precision dairy monitoring is used to supplement or replace human observation of dairy cattle. This study examined the value dairy producers placed on disease alerts generated from a precision dairy monitoring technology. A secondary objective was calculating the accuracy of technology-generated disease alerts compared against observed disease events. A final objective was determining the economic viability of investing in a precision dairy monitoring technology for detecting estrus and diseases. A year-long observational study was conducted on four Kentucky dairy farms. All lactating dairy cows were equipped with a neck and leg tri-axial accelerometer. Technologies measured eating time, lying time, standing time, walking time, and activity (steps) in 15-min sections throughout the day. A decrease of ≥ 30% or more from a cow’s 10-d moving behavioral mean created an alert. Alerts were assessed by dairy producers for usefulness and by the author for accuracy. Finally, raw information was analyzed with three machine-learning techniques: random forest, least discriminate analyses, and principal component neural networks. Through generalized linear mixed modeling analyses, dairy producers were found to utilize the alert list when ≤ 20 alerts occurred, when alerts occurred in cows’ ≤ 60 d in lactation, and when alerts occurred during the week. The longer the system was in place, the less likely producers were to utilize alerts. This is likely because the alerts were not for a specific disease, but rather informed the dairy producer an issue might have occurred. The longer dairy producers were exposed to a technology, producers more easily decided which alerts were worth their attention. Sensitivity, specificity, accuracy, and balanced accuracy were calculated for disease alerts that occurred and disease events that were reported. Sensitivity ranged from 12 to 48%, specificity from 91 to 96%, accuracy from 90 to 96%, and balanced accuracy from 50 to 59%. The high number of false positives correspond with the lack of usefulness producers reported. Machine learning techniques improved sensitivity (66 to 86%) and balanced accuracy (48 to 85%). Specificity (24 to 89%) and accuracy (70 to 86%) decreased with the machine learning techniques, but overall detection performance was improved. Precision dairy monitoring technologies have potential to detect behavior changes linked to disease events. A partial budget was created based on the reproduction, production, and early lactation removal rate of an average cow in a herd. The cow results were expanded to a 1,000 cow herd for sensitivity analyses. Four analyses were run including increased milk production from early disease detection, increased estrus detection rate, decreased early lactation removal from early disease detection, and all changes in combination. Economic profitability was determined through net present value with a value ≥ $0 indicating a profitable investment. Each sensitivity analysis was conducted 10,000, with different numbers for key inputs randomly selected from a previously defined distribution. If either milk production or estrus detection were improved, net present value was ≥ 0 in 76 and 85% of the iterations. However, reduced early lactation removal never resulted in a value ≥ 0. Investing in precision dairy technology resulting in improved estrus detection rate and early disease detection was a positive economic decision in most iterations.