Cow Health Research Articles

Short-Term Effects of Heat Stress on Cow Behavior, Registered by Innovative Technologies and Blood Gas Parameters.

Heat stress (HS) is one of the key factors affecting an animal's immune system and productivity, as a result of a physiological reaction combined with environmental factors. This study examined the short-term effects of heat stress on cow behavior, as recorded by innovative technologies, and its impact on blood gas parameters, using 56 of the 1070 cows clinically evaluated during the second and subsequent lactations within the first 30 days postpartum. Throughout the experiment (from 4 June 2024 until 1 July 2024), cow behavior parameters (rumination time min/d. (RT), body temperature (°C), reticulorumen pH, water consumption (L/day), cow activity (h/day)) were monitored using specialized SmaXtec boluses and employing a blood gas analyzer (Siemens Healthineers, 1200 Courtneypark Dr E Mississauga, L5T 1P2, Canada). During the study period, the temperature-humidity index (THI), based on ambient temperature and humidity, was recorded and used to calculate THI and to categorize the data into four THI classes as follows: 1-THI 60-63 (4 June 2024-12 June 2024); 2-THI 65-69 (13 June 2024-18 June 2024); 3-THI 73-75 (19 June 2024-25 June 2024); and 4-THI 73-78 (26 June 2024-1 July 2024). The results showed that heat stress significantly reduced rumination time by up to 70% in cows within the highest THI class (73 to 78) and increased body temperature by 2%. It also caused a 12.6% decrease in partial carbon dioxide pressure (pCO2) and a 32% increase in partial oxygen pressure (pO2), also decreasing plasma sodium by 1.36% and potassium by 6%, while increasing chloride by 3%. The findings underscore the critical need for continuous monitoring, early detection, and proactive management to mitigate the adverse impacts of heat stress on dairy cow health and productivity. Recommendations include the use of advanced monitoring technologies and specific blood gas parameter tracking to detect the early signs of heat stress and implement more timely interventions.

Phenotypic and Genetic Analyses of Mastitis, Endometritis, and Ketosis on Milk Production and Reproduction Traits in Chinese Holstein Cattle.

Mastitis (MAS), endometritis (MET), and ketosis (KET) are prevalent diseases in dairy cows that result in substantial economic losses for the dairy farming industry. This study gathered 26,014 records of the health and sickness of dairy cows and 99,102 data of reproduction from 13 Holstein dairy farms in Central China; the milk protein and milk fat content from 56,640 milk samples, as well as the pedigree data of 37,836 dairy cows were obtained. The logistic regression method was used to analyze the variations in the prevalence rates of MAS, MET, and KET among various parities; the mixed linear model was used to examine the effects of the three diseases on milk production, milk quality, and reproductive traits. DMU software (version 5.2) utilized the DMUAI module in conjunction with the single-trait and two-trait animal model, as well as best linear unbiased prediction (BLUP), to estimate the genetic parameters for the three diseases, milk production, milk quality, and reproductive traits in dairy cows. The primary findings of the investigation comprised the following: (1) The prevalence rates of MAS, MET, and KET in dairy farms were 20.04%, 10.68%, and 7.33%, respectively. (2) MAS and MET had a substantial impact (p < 0.01) on milk production, resulting in significant decreases of 112 kg and 372 kg in 305-d Milk Yield (305-d MY), 4 kg and 12 kg in 305-d Protein Yield (305-d PY), and 6 kg and 16 kg in 305-d Fat Yield (305-d FY). As a result of their excessive 305-d MY, some cows were diagnosed with KET due to glucose metabolism disorder. The 305-d MY of cows with KET was significantly higher than that of healthy cows (205 kg, p < 0.01). (3) All three diseases resulted in an increase in the Interval from Calving to First Service (CTFS, 0.60-1.50 d), Interval from First Service to Conception (FSTC, 0.20-16.20 d), Calving Interval (CI, 4.00-7.00 d), and Number of Services (NUMS, 0.07-0.35). (4) The heritabilities of cows with MAS, MET, and KET were found to be low, with values of 0.09, 0.01, and 0.02, respectively. The genetic correlation between these traits ranged from 0.14 to 0.44. This study offers valuable insights on the prevention and control of the three diseases, as well as feeding management and genetic breeding.

Bioactive Compounds and Probiotics Mitigate Mastitis by Targeting NF-κB Signaling Pathway.

Mastitis is a significant inflammatory condition of the mammary gland in dairy cows. It is caused by bacterial infections and leads to substantial economic losses worldwide. The disease can be either clinical or sub-clinical and presents challenges such as reduced milk yield, increased treatment costs, and the need to cull affected cows. The pathogenic mechanisms of mastitis involve the activation of Toll-like receptors (TLRs), specifically TLR2 and TLR4. These receptors play crucial roles in recognizing pathogen-associated molecular patterns (PAMPs) and initiating immune responses through the NF-κB signaling pathway. Recent in vitro studies have emphasized the importance of the TLR2/TLR4/NF-κB signaling pathway in the development of mastitis, suggesting its potential as a therapeutic target. This review summarizes recent research on the role of the TLR2/TLR4/NF-κB signaling pathway in mastitis. It focuses on how the activation of TLRs leads to the production of proinflammatory cytokines, which, in turn, exacerbate the inflammatory response by activating the NF-κB signaling pathway in mammary gland tissues. Additionally, the review discusses various bioactive compounds and probiotics that have been identified as potential therapeutic agents for preventing and treating mastitis by targeting TLR2/TLR4/NF-κB signaling pathway. Overall, this review highlights the significance of targeting the TLR2/TLR4/NF-κB signaling pathway to develop effective therapeutic strategies against mastitis, which can enhance dairy cow health and reduce economic losses in the dairy industry.

The Effect of an Exercise Paddock on Dairy Cow Behavior, Health, and Nutrient Digestion during the Transition from Pregnancy to Lactation.

Providing an exercise paddock may improve the behavior and health of cows in their dry period. We compared a control group of cows in a shed with no exercise paddock and an experimental group in the same shed but with access to an exercise paddock. Both groups had ad libitum total mixed ration (TMR) indoors combined with access to a paddock (Group EX). The other group was just offered TMR indoors (Group IN). Total lying time was longer for cows without the exercise paddock (859 min/d) than for those with the paddock (733 min/d) (p = 0.012). Lying bouts were shorter, there were more allogrooming bouts, and drinking time was longer if an exercise paddock was provided. Cows with the paddock spent on average 76 min/d in paddock activity. Non-esterified fatty acids in the blood were increased by providing the exercise paddock. No significant differences in postpartum milk yield and calf weight of dry cows with or without access to exercise paddock were observed. However, crude protein and neutral detergent fiber digestibility were increased by providing the exercise paddock. The results suggest that providing an exercise paddock for cows in their dry period increased activity, including allogrooming, reduced lying, and improved digestibility of some major nutrients in the feed.

A new dataset for video-based cow behavior recognition

A new video based multi behavior dataset for cows, CBVD-5, is introduced in this paper. The dataset includes five cow behaviors: standing, lying down, foraging,rumination and drinking. The dataset comprises 107 cows from the entire barn, maintaining an 80% stocking density. Monitoring occurred over 96 h for these 20-month-old cows, considering varying light conditions and nighttime data to ensure standardization and inclusivity.The dataset consists of ranch monitoring footage collected by seven cameras, including 687 video segment samples and 206,100 image samples, covering five daily behaviors of cows. The data collection process entailed the deployment of cameras, hard drives, software, and servers for storage. Data annotation was conducted using the VIA web tool, leveraging the video expertise of pertinent professionals. The annotation coordinates and category labels of each individual cow in the image, as well as the generated configuration file, are also saved in the dataset. With this dataset,we propose a slowfast cow multi behavior recognition model based on video sequences as the baseline evaluation model. The experimental results show that the model can effectively learn corresponding category labels from the behavior type data of the dataset, with an error rate of 21.28% on the test set. In addition to cow behavior recognition, the dataset can also be used for cow target detection, and so on.The CBVD-5 dataset significantly influences dairy cow behavior recognition, advancing research, enriching data resources, standardizing datasets, enhancing dairy cow health and welfare monitoring, and fostering agricultural intelligence development. Additionally, it serves educational and training needs, supporting research and practical applications in related fields. The dataset will be made freely available to researchers world-wide.

Prevalence and risk factors of reproductive health problems in dairy cows in Southern Ethiopia

Reproductive disorders are the leading cause of economic loss in the cattle industry, as they reduce the reproductive efficiency and lifetime productivity of cows. In Ethiopian dairy, without proper preventive measures, these disorders can have a severe impact on productivity. Therefore, it is crucial to identify the extent of these issues and the factors contributing to them in order to improve the health and productivity of dairy cows. This study aimed to assess the prevalence, type, and potential risk factors for reproductive health problems in dairy farms in Hawassa city and Wolaita Sodo town. We observed 391 pregnant and postpartum cows for reproductive disorders and used a logistic regression model to identify risk factors. The study found that 165 cows (41.6%; 95% CI: 36.8-46.5%) had at least one reproductive issue. The most common disorders included retained fetal membrane (11.6%), dystocia (10.5%), metritis (7.2%), abortion (5.6%), stillbirth (2.6%), uterine/vaginal prolapse (2.3%), endometritis (2.1%), and pyometra (0.5%). The risk of dystocia significantly increased with male calf deliveries (OR=2.9; p=0.004) and larger farm sizes (OR=2.1; p=0.039). Cows experiencing dystocia were 5.3 times more likely to have retained fetal membrane (p&lt;0.001). Heifers were significantly more likely to develop metritis (OR=5.1; p=0.001), as were cows with retained fetal membrane (OR=11.6; p&lt;0.001). The incidence of abortion was significantly elevated in cows from semi-intensive farms (OR= 5.3; p&lt;0.001). The study concludes that these reproductive health issues can significantly impact future uterine health, resulting in prolonged uterine involution. It is crucial to raise awareness among dairy farmers about effective herd health management practices to minimize losses.

A Review on Mastitis in Dairy Cows Research: Current Status and Future Perspectives

One of the most serious diseases affecting dairy cattle, causing significant losses both in breeding and economy, is mastitis, an inflammation of the mammary gland. Due to the economic importance of this issue, many research teams are striving to develop an easy-to-apply and, most importantly, effective method to prevent mastitis. The use of traditional methods for mastitis detecting and treating, as well as improvement in hygienic conditions, have not yielded the expected results in combating this disease combating. Currently, the main task is to find the tools that would allow for the rapid detection of mastitis and the improvement of udder health in cows while maintaining high milk production, which is essential for the profitability of dairy cattle farming. Accurate and rapid diagnostic tools, with the simultaneous capability of identifying pathogens, may help to reduce losses. Sufficient sensitivity and specificity for tests are required to minimize the number of false-positive and false-negative cases. Efforts are also being made to determine the optimal threshold value for detecting the disease at its earliest possible stage. The estimation of somatic cell count (SCC) as a phenotypic indicator of mastitis is widely used. A more precise parameter for accurately describing udder health is the differential somatic cell count (DSCC). The well-known California Mastitis Test (CMT) is an inexpensive, easy, and rapid method for mastitis detection useful on farms. The latest diagnostic methods for mastitis utilize tests based on the activity of N-acetyl-β-d-glucosaminidase (NAGase) or lactate dehydrogenase (LDH) as well as the determination of acute phase proteins (APPs) in blood serum and milk (such as haptoglobin, serum amyloid A, fibrinogen, and ceruloplasmin). Research also focuses on the genomic improvement of mastitis resistance in successive generations, and for this purpose, many quantitative trait loci (QTLs) and single nucleotide polymorphisms (SNPs) have been identified. In recent years, immunotherapy has become an increasingly common area of research, including vaccinations, T/B cell immunotherapy, RNA immunotherapy, epigenetic immunotherapy, stem cell therapy, and native secretory factors. An important aspect of the control of mastitis is the implementation of strategies that focus primarily on preventing the disease through appropriate breeding and farm management practices. In the forthcoming years, a significant challenge will be the development of universal diagnostic and therapeutic strategies that can be effectively implemented as alternatives to antibiotic therapy. Future research should prioritize the advancement of preventive and therapeutic techniques, such as immunotherapies, bacteriocins, herbal therapy, and nanoparticle technology.

A randomized controlled trial to study the effect of supplemental premilking stimulation on milking performance, teat tissue condition, udder health, and well-being in dairy cows

The objectives of this study were to evaluate the effect of supplemental premilking stimulation, provided after manual stimulation, by means of high-frequency pulsation without reduction of the vacuum in the pulsation chamber on milking performance, teat tissue condition, udder health, and well-being in dairy cows. In a randomized controlled trial, Holstein cows (n = 491) from 1 commercial dairy farm with a thrice-per-day milking schedule were assigned to treatment and control groups over a 64-d period. Treatments consisted of a maximum of 20 s of pulsation stimulation at a pulsation rate of 100 (SPS100) or 300 (SPS300) cycles per minute and a pulsation ratio of 25:75, which were applied after completion of manual premilking stimulation upon milking unit attachment. Cows in the control group (CON) received only traditional premilking stimulation by manual forestripping for 6 s, and wiping. Milking characteristics were measured with on-farm milk flow meters. Milking machine-induced short-term (swelling at teat base, firmness at teat end, and teat discoloration) and long-term (teat-end callosity) changes to the teat tissue were assessed manually and visually. Composite milk samples were analyzed for somatic cell counts. Cow hind-leg activity was assessed with 3-dimensional accelerometers. Fecal 11,17-dioxoandrostanes (11,17-DOAs; a group of cortisol metabolites) were determined on wk 4 and 8 to assess the well-being of the cows. Generalized linear mixed models were used to study the effect of treatments on the outcome variables milk yield/milking and milking unit-on time. We observed no meaningful differences among groups for milk yield or milking unit-on time. Least squares means and their 95% confidence intervals (95% CI) for cows in the SPS100, SPS300, and CON groups were 13.9 (13.3-14.5), 14.0 (13.4-14.6), and 13.9 (13.3-14.6) kg for milk yield and 218 (212-224), 218 (211-224), and 218 (212-224) s for milking unit-on time, respectively. Compared with cows in the CON group, the odds (95% CI) of short-term changes were 1.30 (0.95-1.78) for the SPS100 group and 1.50 (1.10-2.05) for the SPS300 group. The odds of long-term changes were 0.94 (0.67-1.34) for cows in the SPS100 group and 0.71 (0.49-1.04) for cows in the SPS300 group. We observed no differences in SCC. In reference to the CON group, the hazard ratio (95% CI) in SPS100 and SPS300, respectively, were 0.35 (0.13-0.98) and 1.22 (0.57-2.64) for clinical mastitis, and 0.34 (0.12-0.95) and 1.28 (0.60-2.73) for culling. The least squares means (95% CI) of hind-leg activity during milking were 8.3 (6.5-10.5), 10.6 (8.1-13.7), and 9.1 (7.2-11.6) movements per milking for the SPS100, SPS300, and CON groups, respectively. The least squares means (95% CI) of fecal 11,17-DOAs concentration (ng/g) at the first and second test days, respectively, were 31.1 (28.1-34.2) and 22.3 (19.2-25.4) for the SPS100 group, 26.4 (23.4-29.4) and 25.2 (22.0-28.4) for the SPS300 group, and 24.8 (21.8-27.9) and 25.0 (21.7-28.3) for the CON group. We conclude that applying supplemental stimulation after manual stimulation through the high-frequency pulsation system tested here did not impart additional benefits to the milk harvesting process, teat tissue condition, somatic cell count, or the well-being of the animals.

Assessing Transition Cow Management in Dairy Cows for Improved Health, Milk Production, Pregnancy and Culling Outcomes

Understanding of the social environment has the potential to benefit dairy cow welfare and production. Our aim was to evaluate the associations of stocking density, calving density, days spent in a pre-partum group before calving (days spent in close-up, DCU) and the number of days from a pen filling event (addition of new cows to the pre-partum pen) on early-lactation health, production, pregnancy and culling outcomes in dairy cows. Data were gathered from 2780 cows in 2 herds. Herd management and reproductive records were analyzed for cows receiving treatment in the first 30 d of lactation (days in milk, DIM) for clinical mastitis, reproductive tract disease, ketosis, milk fever and displaced abomasum. Principal component analysis was used to account for the relationship between gestation length (GL) and DCU and their association with early lactation disease, milk production, pregnancy and culling outcomes. The effect of stocking density, the number of days from a pen filling event to calving and the calving density experienced by a cow in her week of calving was also evaluated. Causal inference was used to correct for confounding bias due to farm identity. The odds of disease in the first 30 DIM increased with stocking density before calving. A quadratic association was found between the first principal component (PC1), representing the combined effect of GL and DCU, and the odds of disease in multiparous cows only. Early lactation milk production and 305 d milk production in multiparous cows increased with PC1 score. Quadratic relationships were found between stocking density at d 8 to 2 before calving with both early lactation and 305 d milk production in multiparous cows but no associations were found in primiparous cows. Calving density showed a quadratic association with 305 d milk production in primiparous cows. The number of days from the last pen filling event to calving was not associated with changes in milk production. Disease occurrence was negatively associated with both early lactation and 305 d milk yield in multiparous cows but only with early lactation milk production in primiparous cows. The occurrence of disease was associated with a delayed time to pregnancy only in primiparous cows while both disease and being in lactation group ≥ 3 were negatively associated with time to pregnancy in multiparous cows. Week 4 milk (W4MK) was positively associated with reduced time to pregnancy in multiparous cows. For primiparous cows, increasing age at calving was associated with increased culling risk, while being in lactation group ≥ 3 was associated with increased culling risk in multiparous cows. Culling risk decreased with increasing W4MK in all cows. These results suggest that gestation length, time spent in close-up and stocking density are important factors influencing disease incidence in early lactation and subsequent lactation performance but had differing effects on primiparous versus multiparous cows. A better understanding of how pre-partum management factors influence postpartum health and milk production can help farms to plan facilities and organize the day-to-day management of cows and will assist in improving cow welfare and productivity.

AI-enhanced real-time cattle identification system through tracking across various environments

Video-based monitoring is essential nowadays in cattle farm management systems for automated evaluation of cow health, encompassing body condition scores, lameness detection, calving events, and other factors. In order to efficiently monitor the well-being of each individual animal, it is vital to automatically identify them in real time. Although there are various techniques available for cattle identification, a significant number of them depend on radio frequency or visible ear tags, which are prone to being lost or damaged. This can result in financial difficulties for farmers. Therefore, this paper presents a novel method for tracking and identifying the cattle with an RGB image-based camera. As a first step, to detect the cattle in the video, we employ the YOLOv8 (You Only Look Once) model. The sample data contains the raw video that was recorded with the cameras that were installed at above from the designated lane used by cattle after the milk production process and above from the rotating milking parlor. As a second step, the detected cattle are continuously tracked and assigned unique local IDs. The tracked images of each individual cattle are then stored in individual folders according to their respective IDs, facilitating the identification process. The images of each folder will be the features which are extracted using a feature extractor called VGG (Visual Geometry Group). After feature extraction task, as a final step, the SVM (Support Vector Machine) identifier for cattle identification will be used to get the identified ID of the cattle. The final ID of a cattle is determined based on the maximum identified output ID from the tracked images of that particular animal. The outcomes of this paper will act as proof of the concept for the use of combining VGG features with SVM is an effective and promising approach for an automatic cattle identification system

Genome-Wide Association Study as an Efficacious Approach to Discover Candidate Genes Associated with Body Linear Type Traits in Dairy Cattle.

Body shape traits are very important and play a crucial role in the economic development of dairy farming. By improving the accuracy of selection for body size traits, we can enhance economic returns across the dairy industry and on farms, contributing to the future profitability of the dairy sector. Registered body conformation traits are reliable and cost-effective tools for use in national cattle breeding selection programs. These traits are significantly related to the production, longevity, mobility, health, fertility, and environmental adaptation of dairy cows. Therefore, they can be considered indirect indicators of economically important traits in dairy cows. Utilizing efficacious genetic methods, such as genome-wide association studies (GWASs), allows for a deeper understanding of the genetic architecture of complex traits through the identification and application of genetic markers. In the current review, we summarize information on candidate genes and genomic regions associated with body conformation traits in dairy cattle worldwide. The manuscript also reviews the importance of body conformation, the relationship between body conformation traits and other traits, heritability, influencing factors, and the genetics of body conformation traits. The information on candidate genes related to body conformation traits provided in this review may be helpful in selecting potential genetic markers for the genetic improvement of body conformation traits in dairy cattle.

Learning end-to-end respiratory rate prediction of dairy cows from RGB videos

Respiratory rate (RR) is an important indicator of the health and welfare status of dairy cows. In recent years, progress has been made in monitoring the RR of dairy cows using video data and learning methods. However, existing approaches often involve multiple processing modules, such as region of interest (ROI) detection and tracking, which can introduce errors that propagate through successive steps. The objective of this study was to develop an end-to-end computer vision method to predict RR of dairy cows continuously and automatically. The method leverages the capabilities of a state-of-the-art Transformer model, VideoMAE, which divides video frames into patches as input tokens, enabling the automated selection and featurization of relevant regions, such as a cow's abdomen, for predicting RR. The original encoder of VideoMAE was retained, and a classification head was added on top of it. Further, the weights of the first 11 layers of the pre-trained model were kept, while the weights of the final layer and classifier were fine-tuned using video data collected in a tie-stall barn from 6 dairy cows. Respiratory rates measured using a respiratory belt for individual cows were serving as the ground truth (GT). The evaluation of the developed model was conducted using multiple metrics, including mean absolute error (MAE) of 2.58 breaths per minute (bpm), root mean squared error (RMSE) of 3.52 bpm, root mean squared prediction error (RMSPE; as a proportion of observed mean) of 15.03%, and Pearson correlation (r) of 0.86. Compared with a conventional method involving multiple processing modules, the end-to-end approach performed better in terms of MAE, RMSE and RMSPE. These results suggest the potential to implement the developed computer vision method for an end-to-end solution, for monitoring RR of dairy cows automatically in a tie-stall setting. Future research on integrating this method with other behavioral detection and animal identification algorithms for animal monitoring in a free-stall dairy barn can be beneficial for a broader application.

Innovative bedding materials for compost bedded pack barns: enhancing dairy cow welfare and sustainable dairy farming

AbstractCompost bedded pack (CBP) barns are an innovative housing system that improves the comfort and welfare of dairy cows, compared to cubicle style housing or free stalls with artificial surfaces, such as rubber or concrete. This type of bedding system also has the potential to improve lameness scores, overall health, welfare, and productivity of dairy cows. In CBP barns, carbon materials or organic materials are composted in the barn while being used as bedding for livestock. The animals pass manure on these surfaces providing the nitrogen, microorganisms, and moisture necessary for the composting process. Historically, dry sawdust originating from mills, furniture and pallets have been used as a substrate for compost. However, due to these materials becoming increasingly expensive and hard to source, other materials have been trailed as potential substitutes. Furthermore, there is an increasing interest in making dairy production more environmentally friendly by reducing carbon footprint. This review summarises and highlights appropriate alternative materials that, subject to their management, can be successfully used in the CBP barn system. This will act as an aid for farmers and decision makers when choosing materials to be incorporated in CBP barns. Using alternative materials to sawdust, wood chips and wood shavings, which are the current industry standard, will contribute to a more circular economy and sustainable dairy production, while simultaneously contributing to sustainable development goals, and improved animal health and welfare.

Effect of a lime-based bedding conditioner on physical-chemical characteristics and microbiological counts of recycled manure solids.

Bedding materials are aimed at providing a safe and comfortable resting environment for cows. Control of pathogen proliferation in these substrates is crucial to prevent intramammary infections in dairy cows, as these can significantly impact milk quality, cow health, and farm productivity. This is particularly relevant in the case of organic bedding substrates, including manure-derived materials. This study aimed to evaluate the in vitro effect of a lime-based conditioner (LBC), composed of CaCO3MgCO3 and Mg(OH)2, at increasing concentrations on the physical-chemical characteristics and bacterial counts of untreated anaerobically digested manure solids (ADMS) and separated raw manure solids (SRMS). Unused ADMS and SRMS were evaluated at four LBC weight-based concentrations: 0 (as untreated control), 10, 15, and 20% of LBC inclusion. The bedding materials were assessed immediately after LBC addition (0 h) and after 24, 72, and 168 h of storage at 28°C. The dry matter content (DM), and pH were measured for all the time points. Standard microbiological methods were used to assess total bacterial counts (TBC), other Gram-negative bacteria, coliforms, Escherichia coli, and streptococci and streptococci-like organism (SSLO). It was observed a linear increase in both DM and pH with increasing concentrations of LBC. Specifically, for each percentage unit increase of LBC, the DM of ADMS and SRMS increased by 0.73 and 0.71%, respectively. Similarly, for each percentage unit of LBC, the pH of ADMS and SRMS increased by 0.15 and 0.19, respectively. Conversely, a linear decrease in TBC, Gram-negative bacteria, coliforms, E. coli, and SSLO was observed with increasing concentrations of the LBC. Manure-derived materials without the inclusion of the LBC had bacterial counts that tended to remain high or increase over time. Otherwise, bedding materials with LBC application had reduced bacterial counts. Based on the results of the present study, it was observed that the higher the concentration of LBC, the more significant the reduction of bacterial counts. Specifically, bacterial recovery was lower when higher concentrations of LBC were applied. Our findings underscore the potential of LBC in effectively controlling environmental bacteria and improving the physical-chemical characteristics of manure-derived bedding materials to improve cow health and welfare.

Deep learning aided computer vision system for automated linear type trait evaluation in dairy cows

The assessment of traits is important in determining production potential, reproductive performance, and overall health of dairy cows. The assessment of these traits typically involves visual inspection and manual measurement, which can be time-consuming, subject to bias, and potentially distressing for the animals. To address these challenges, convolutional neural networks (CNNs)-aided non-invasive computer vision system was developed in the present study. This system consists of a depth camera to acquire the RGB images and depth information of cows. The DeepLabV3+ model, having the ResNet50 model as a backbone, was utilized to segment the body parts of cows from RGB images. Image processing-based algorithms were developed to extract key pixel locations for each trait from these segmented images. The system estimated trait dimensions utilizing 3D data of respective key points. The mean-IoU (intersection-over-union) values for the developed segmentation models were 93.46%, 91.25%, and 99.27% for side-view, back-view traits, and stature, respectively. Additionally, the vision system was able to estimate the trait dimensions with mean absolute percentage error (MAPE) below 6.0%. For a few traits, MAPE, however, exceeded 10.0%, indicating higher error. Inaccurate segmentation, imprecise key point extraction, visual overlaps of specific body parts, and variations in cow postures contribute to such errors. The developed system attained a Ratio of Performance to Deviation (RPD) above 1.2 for all traits, indicating its ability to estimate the dimensions of traits efficaciously. Thus, the present study demonstrated the potential of a CNN-based computer vision-based system for automating the trait measurement process in cows.

Association of Dry Period Length with Automatic Milking System, Mastitis, and Reproductive Indicators in Cows.

The objective of this study was to evaluate the association between dry period (DP) length and various indicators of productivity, reproduction, and udder health in cows managed with an automatic milking system. We analyzed records from 3861 cows, categorizing them into three groups based on their DP duration: (1) <40 days, (2) 40-70 days, and (3) DP > 70 days. Cows with a DP of 40-70 days had an average energy-corrected milk production that was 8.2 kg greater than that of cows with a short DP and 5.0 kg greater than that of cows with a long DP (p < 0.001). Milk from the 40-70-day DP group exhibited the highest lactose concentration (4.64 ± 0.01%). Additionally, cows with the longest DP had the smallest proportion of animals with a milk fat-to-protein ratio of 1.2 to 1.4. Cows with a DP of 40-70 days also showed the lowest milk electrical conductivity across all udder quarters, whereas cows with the shortest DP had the highest conductivity. The highest conception rates were observed in the group with the shortest DP. These results suggest that a DP of 40-70 days is optimal for maximizing milk production and improving both udder health and reproductive performance under AMS. Proper management of DP duration can be an effective strategy for sustainable dairy herd management.

Effects of biochanin A on lactational performance, nitrogen metabolism, and blood metabolites in dairy cows

Optimizing nitrogen utilization efficiency and mitigating nitrogen losses in cows plays a pivotal role in fostering economic sustainability within contemporary agricultural systems. Biochanin A (BCA), a natural component in red clover, has the potential to improve nitrogen metabolism in dairy cows. The primary objective of this study was to probe the impact of biochanin A supplementation on lactational performance, nitrogen metabolism, and blood metabolites in dairy cows. A complete randomized block design experiment was conducted over 28 d, involving 36 multiparous Holstein cows (comparable milk yield = 37.1 ± 2.90 kg, BW = 642 ± 70.0 kg, days in milk = 92 ± 8.0 d, and parity = 2.4 ± 0.50), which were allocated to three treatment groups: the Control group (with 0 g/d BCA), the Low group (with 10 g/d per cow BCA), and the High group (with 40 g/d per cow BCA). Biochanin A supplementation improved the lactational performance of cows by increasing milk yield by 6.3% (P = 0.007) and feed efficiency by 12.7% (P = 0.009). Total intestinal apparent digestibility was unaffected by BCA supplementation (P > 0.05), but microbial nitrogen was increased by 30.0% (P = 0.002) for promoting nitrogen utilization efficiency by 20.7% (P = 0.004). Milk competent yields (protein, lactose, and non-fat milk solid) were increased with increasing BCA supplementation (P < 0.05). Urea nitrogen levels in plasma and milk were both decreased by BCA supplementation (P < 0.05). Blood routine parameters and plasma biochemical parameters both received no effect by BCA supplementation (P > 0.05). BCA did not affect body health of dairy cows. Additionally, none of the plasma endocrine hormones were affected (P > 0.05). A total of 95 significantly different metabolites were screened from the plasma metabolites of cows in the BCA-added and non-added groups. After performing an enrichment analysis of the metabolic pathways associated with the different metabolites, six specific pathways were identified: bile acid biosynthesis, aspartate metabolism, pyrimidine metabolism, arginine and proline metabolism, the urea cycle, and ammonia recycling. The inclusion of BCA is suggested to enhance milk yield and modulate nitrogen metabolism by influencing relevant metabolites within the metabolic pathways.

The Effectiveness of Using Bulls With Increased Immune Response in Terms of Milk Yield, Milk Contents, and Somatic Cell Count in Polish Holstein-Friesian Cows

Abstract The dairy cattle industry has witnessed significant advancements in production traits, including milk yield, reproduction, and health, through decades of breeding efforts. Despite these improvements, cow health and milk hygiene remain essential. High immune response (HIR) technology identifies cattle with optimized immune responses, enabling the selection of bulls with high immune responses for breeding. Studies indicate that HIR-based breeding improves animal health without compromising production traits. This study aimed to assess the effectiveness of bulls with a high immune response in improving milk yield, milk contents, and somatic cell count in the milk of Polish Holstein-Friesian cows. A total of 11,509 cows of the Polish Holstein-Friesian breed were used. Among those, 1,773 animals were the offspring of HIR bulls, including 926 first-generation offspring (called I50 group) and 847 second-generation offspring (I25 group). There were 9,736 animals unrelated to HIR bulls (I0 group). Selected production and functional traits were analyzed. The results show that cows with higher kinship to HIR bulls showed increased milk yield. However, their milk exhibited lower fat, protein, and casein content. A favorable impact of HIR bulls was demonstrated by the decrease in somatic cell count in their offspring’s milk compared to the milk of cows from the I0 group. This research contributes valuable insights into the potential benefits of using HIR bulls in dairy cattle breeding programs, emphasizing the importance of balancing production traits with health considerations.

Effects of abomasal infusion of branched-chain amino acids or branched-chain keto-acids on liver function, inflammation, and oxidative stress in multiparous fresh cows

Reduced liver function, increased oxidative stress, and inflammation in early lactation negatively impact lactation performance and health of fresh cows. Previous findings from our group demonstrated that branched-chain amino acids (BCAA) infusion improved lactation performance and branched-chain ketoacids (BCKA) infusion decreased liver triglyceride (TG) in fresh cows. The objectives of this study were to determine the effect of BCAA and BCKA on blood and liver biomarkers of liver function, oxidative stress, and inflammation as well as expression of genes regulating inflammation and antioxidant metabolism in the liver. Thirty multiparous Holstein cows were used in a randomized block design receiving continuous abomasal infusion for 21 d after parturition. Treatments (10 cows each) were control (CON), cows abomasally infused with 0.9% saline; BCA, cows abomasally infused with BCAA (67 g valine, 50 g leucine, and 34 g isoleucine); and BCK, cows abomasally infused with BCKA (77 g ketovaline, 57 g ketoleucine, and 39 g ketoisoleucine). All cows were randomly assigned to treatments after parturition and received the same diet throughout the experimental period. Blood was collected at 3, 7, 14, and 21 d postpartum for liver function, oxidative stress, and inflammation biomarker profiling. Liver was also harvested on 7, 14, and 21 d postpartum for quantification of glutathione, protein carbonylation, and expression of genes. ANOVA was conducted for all data using PROC GLIMMIX in SAS. No treatment differences were observed for liver function biomarkers (bilirubin, gamma-glutamyl transferase, and aspartate aminotransferase). Cows receiving BCAA had lower blood NO2- and NO3- concentrations compared with CON. A tendency for lower advanced oxidized protein products was also observed in BCA cows compared with CON. Additionally, on d 7, BCA cows had lower protein carbonylation in the liver compared with CON. In contrast, BCK cows had higher plasma thiol and albumin, as well as liver reduced and total glutathione compared with CON cows. Compared with CON, BCK cows had higher expression glutathione reductase in the liver. Overall, these results suggest favorable alterations in oxidative stress and inflammation status in fresh cows receiving BCAA or BCKA infusion during the first 3 weeks of lactation, which likely contributed to previously-observed changes in lactation performance and liver TG concentrations. Future work is required to evaluate the interrelated metabolism of BCAA and BCKA to better understand their effects on oxidative and immune metabolism.

Customized voluntary waiting period before first insemination in primiparous dairy cows. Effect on milk production, fertility and health

Customized voluntary waiting period (VWP) before first insemination was tested in 18 commercial dairy herds in Sweden, to assess milk production, fertility and health in primiparous cows expected to be suited for extended VWP. Cow selection for extended VWP was based on 3 criteria in early lactation: 1) the 10% of cows with highest genomic persistency index, 2) cows with a difficult calving or disease during the first month of lactation, and 3) cows with higher yield during d 4-33 after calving than the herd average for primiparous cows. Cows meeting at least one of these criteria were randomly assigned to either the ExtExt treatment (extended VWP of at least 175 d, n = 174; calving interval (CInt) = 16.3 mo) or the ExtConv treatment (conventional VWP of maximum 100 d n = 173; CInt = 12.4 mo). Cows not meeting any of the criteria were assigned to the ConvConv treatment (conventional VWP, n = 183; CInt = 12.0 mo). There were no differences in milk yield per day in the CInt between treatments, although 305-d and whole-lactation (WL) milk yields were higher for ExtExt cows (10,371 and 13,803 kg) than ExtConv cows (9,812 and 10,257 kg). Milk yield at the last test milking before dry-off was lower in ExtExt compared with ExtConv cows (24.9 vs 28.3), however the results showed no difference in dry period length between the treatments. Regarding reproductive performance, the ExtExt cows had higher first service conception rate (FSCR; 60% vs. 45%) and lower number of inseminations per conception (NINS; 1.67 vs. 2.19), compared with the ExtConv cows. As expected, ConvConv cows had the lowest milk yield in 305-d, in WL, and per day in the CInt, however, FSCR and NINS did not differ between ConvConv cows and cows in the other 2 VWP treatments. Disease incidence was higher for cows in the ExtConv compared with the ConvConv treatment, but there was no difference between ExtExt and the 2 other VWP treatments. Further, no difference in proportion of cows with good udder health or culling rate was detected between any of the treatments, though due to low prevalence the study lacked power to draw major conclusions on these results. Thus prolonging VWP for suitable primiparous cows can produce benefits such as improved fertility in the form of higher FSCR and lower NINS, as well as lower dry-off yield, without compromising milk yield or prolonging dry period length.