Health Of Dairy Cattle Research Articles

Automating hock wound detection in dairy cattle

Hock scoring in dairy cattle is a crucial welfare assessment tool used to evaluate the condition of a cow's hocks, particularly for signs of injury, swelling, or lesions. These scores provide insight into the overall well-being of the animals and are essential for ensuring proper management and housing conditions. Accurate hock scoring is vital because it can indicate issues such as poor bedding quality or inadequate space, which directly affect the health and productivity of the herd. Traditionally, hock scoring is performed manually by trained observers. However, consistency in scoring can be a challenge. Two studies were conducted to quantify inconsistency in hock scoring. In one study, manual scoring repeatability was measured. In the second study, manual and video scoring repeatability was measured. Repeatability was quantified with a weighted Cowen's kappa metric. Manual scoring was found to be inconsistent but more consistent than video scoring. This variability highlights the need for a more reliable, objective method of scoring. To address this, we explored the automation of hock score detection using artificial intelligence. Specifically, we employed a simple U-net semantic segmentation algorithm to detect wounds on the hocks without classifying them into specific categories. Automating the detection process can reduce observer bias, improve consistency, and allow for continuous monitoring of large herds. This approach holds promise for enhancing animal welfare by providing a more efficient and accurate method of assessing hock health in dairy cattle.

Effect of Age at First Calving on the Reproduction Parameters, Metabolic Profile, and Fatty Acid Composition of Polish Holstein Friesian (PHF) and Crossbreds PHF × Swedish Red (SRB) Cattle

Background: The high dairy production of Polish Holstein Friesian (PHF) cows determines high energy requirements in the early stages of lactation. Unfortunately, it is very often difficult to meet this demand through feedstuffs; therefore, homeostasis may be disturbed and metabolic diseases may occur, causing a majority of cows’ health problems. Breeders are, therefore, looking for alternatives to the PHF breed using crossbreeding. Methods: This experiment involved 30 PHF cows and 30 PHF × Swedish Red (SRB) crossbred hybrid cows, divided into two age groups, <2 years and >2 years, at first calving. Milk and blood samples were collected at 35 ± 5 days postpartum for analysis. Data on reproductive performance were also analyzed. Results: This study revealed lower milk production for the crossbreds hybrid (27.44 kg compared to 32.08 kg), with a higher basic composition content than PHF cows (fat: 3.97% compared to 3.83%, protein: 3.53% compared to 3.27%). The heifers of the crossbreds hybrid reached sexual maturity earlier but did not affect the lower age at first calving. Dividing the cows into age categories provided a more detailed perspective of the impact of genotypic differences on reproductive and metabolic profiles in PHF and PHF × SRB cattle. The findings highlight the importance of considering age-specific effects when assessing the performance and health of dairy cattle with diverse genotypes. Conclusions: The choice between PHF and PHF × SRB should depend on the specific goals and priorities of the cattle farming operation. Factors such as overall milk yield requirements, market demands, reproductive management strategies, and health considerations should be carefully evaluated to determine the most suitable breed for a given farming context.

Gene Enrichment and Pathway Analysis for Ketosis Resistance in Dairy Cattle: A GWAS-Based Approach

Ketosis in dairy cattle is a common metabolic disorder that arises during the transition period from late gestation to early lactation. It is primarily caused by an imbalance between energy intake and expenditure, leading to an excessive accumulation of ketone bodies. This condition can significantly affect cattle health and productivity. Recent advances in genomic research, especially genome-wide association studies (GWAS), offer an opportunity to explore the genetic factors that contribute to ketosis resistance. The aim of this study is to comprehensively review and analyze existing GWAS data using gene enrichment analysis to identify potential functional candidate gene pathways associated with ketosis resistance in dairy cattle. In this study, data obtained from seven different studies were examined and 640 non-repetitive genes were obtained after filtering. Using Enrichr, an online tool for gene annotation, pathway analysis was performed with human homologs of the identified genes. Our findings highlight the acylglycerol homeostasis pathway, the regulation of triglyceride metabolism, and the role of chylomicrons in maintaining metabolic balance during ketosis. Additionally, immune response pathways were found to be linked to the genes associated with ketosis, offering insights into the intricate interplay between metabolic and immune pathways in ketosis. This study emphasizes the importance of understanding genetic factors in developing breeding strategies aimed at enhancing metabolic health and productivity in dairy cattle. Future research should focus on validating these candidate genes and exploring their mechanistic roles to facilitate targeted interventions and improve resistance to ketosis in dairy herds.

The Contribution of Dairy Bedding and Silage to the Dissemination of Genes Coding for Antimicrobial Resistance: A Narrative Review.

Antimicrobial resistance (AMR) is a concern in the dairy industry. Recent studies have indicated that bedding serves as a reservoir for antimicrobial-resistant bacteria and antimicrobial-resistance genes (ARGs), while silage has been proposed as another possible source. The impact of AMR in dairy farming can be significant, resulting in decreased productivity and economic losses for farmers. Several studies have highlighted the safety implications of AMR bacteria and genes in bedding and silage, emphasizing the need for further research on how housing, bedding, and silage management affect AMR in farm environments. Exposure to sub-lethal concentrations of antibiotics, such as those from contaminated bedding and silage, can prompt bacteria to develop resistance mechanisms. Thus, even if antimicrobial usage is diminished, ARGs may be maintained in the dairy farm environment. By implementing proactive measures to tackle AMR in dairy farming, we can take steps to preserve the health and productivity of dairy cattle while also protecting public health. This involves addressing the prudent use of antibiotics during production and promoting animal welfare, hygiene, and management practices in bedding and farm environments to minimize the risk of AMR development and spread. This narrative review compiles the growing research, positioning the contribution of bedding and silage to the prevalence and dissemination of AMR, which can elicit insights for researchers and policymakers.

Commercial perspectives: Genome editing as a breeding tool for health and well-being in dairy cattle

Genome editing is the latest breeding tool capable of accelerating the rate of genetic improvement for health and well-being traits in food animals. It enables the introduction of beneficial alleles within a single generation, including those of low frequency or absent in the population, while effectively bypassing linkage drag. For the dairy industry, genome editing can be used to make rapid genetic improvements that are precise, efficient, and transgene-free for functional traits that are not practically addressed without disrupting conventional breeding goals for overall economic merit based on genomic selection. Herein, various case studies for dairy cattle breeding are presented that demonstrate applications of genome editing for enhancing heat stress tolerance, reduced disease susceptibility, and/or other qualitative traits absent in some breeds. One case highlights the success of simultaneous editing of multiple loci through recent advancements in embryonic stem cell biology. Multiplexed editing is crucial for addressing the polygenic nature inherent to many economically important traits in livestock. However, maximizing the benefits of genome editing depends on the continued discovery of targets for editing that are commercially important. Commercialization also depends on rapidly evolving regulatory statutes for risk assessment, where some countries already permit the commercialization of cattle with non-GMO genome alterations through existing regulations. New breeding technologies like genome editing are now poised to have significant impact in equipping elite performance cattle to be more resilient to infectious disease and climate change without the loss of production gains obtained from decades of selection.

Biofermentation of aquatic plants: Potential novel feed ingredients for dairy cattle production

The study assessed the impacts of aquatic plant silages on feeding efficiency and dairy cattle health as an alternative to conventional corn silage under high altitude conditions. Mid-lactation Holstein cows were assigned to treatment groups according to a randomized complete block design of parity, previous 105-d milk yield, and body weight. Cows (n = 8 per group) were fed with aquatic plant silage inoculated with Bacillus subtilis (BS), Yeast (YS), or conventional corn silage without inoculants (control) in addition to [standard grain feed] for 75 consecutive days. BS and YS had higher protein contents than control silage (111.20 ± 7.68, 112.10 ± 6.83 vs 76.94 ± 3.48 g/kg DM), while feeding efficiency was comparable between treatments (1.07, 0.99, and 0.90, respectively). In addition, the addition of aquatic plant silage in ruminant diets enhanced immunity and antioxidant capacity when compared with control group. Metagenomic analysis showed similar composition in rumen microbiota between YS and control groups, with higher enrichment for energy and nitrogen utilization pathways in YS-treated cows. This study highlights the use of aquatic plant silage as an alternative feed for dairy cattle with higher protein than corn silage. Our results suggest YS or BS could potentially boost immune and antioxidant functions, improving adaptation to high-altitudes and reducing demand for high input corn production on the Qinghai-Tibetan Plateau.

Enhancing hoof health and locomotion in crossbred dairy cows: impact of recycled manure solids bedding on lameness incidence and gait kinematics.

Recycled manure solids has emerged as a promising alternative for animal bedding, owing to its economic feasibility, ready availability on farms, and soft, non-abrasive nature. This research aimed to assess the impact of recycled manure solids (RMS) bedding, combined with a conditioner containing 7.5% lime and 6% sodium hydrosulphate, on dairy cow welfare and gait kinematics over three months. Hock and knee injury scores, lameness incidence, and gait kinematic parameters were evaluated for animals housed on cement flooring (Control), RMS bedding (Treatment I), and conditioner-added RMS bedding (Treatment II) on days 0, 45, and 90 of the experiment with six crossbred cows in each group. The results revealed a significant reduction (p < 0.05) in lameness scores (5-point scale) for animals in both the RMS and conditioner-added RMS groups, with scores of 1.09 ± 0.05 and 1.04 ± 0.03, respectively, compared to those on cement floors. Moreover, a noteworthy decrease (p < 0.05) in knee and hock injury scores (4-point scale) was observed in the RMS groups, indicating a potentially positive impact on joint health. Gait kinematic analysis demonstrated that animals in the RMS (1.03 ± 0.04m/s) and conditioner-added RMS (1.02 ± 0.06m/s) groups exhibited higher walking speeds and increased step angles (158.59 ± 4.82° and 149.58 ± 3.85°) compared to their cement-floor counterparts. No significant changes (p > 0.05) were observed in stride length, step asymmetry, step length, and step width. The study concluded that the conditioner incorporated recycled manure solids resulting in a substantial decrease in lameness incidence and a reduction in hock and knee injuries among dairy cows. Additionally, the improved gait kinematics observed in non-lame animals suggest that this bedding combination positively influences overall animal well-being. These findings underscore the potential of sustainable bedding practices to enhance both physical health and locomotor behaviour in dairy cattle.

Association of genomic prediction for twin pregnancies with the incidence of double ovulation in primiparous dairy cows.

Twin pregnancies compromise the health and well-being of dairy cattle. A recent genomic prediction model for twin pregnancies has been developed based on twin calving or abortion. However, the incidence of double ovulation is significantly higher than that of twin births. This study aimed to evaluate whether genomic prediction values for twin pregnancies are associated with the incidence of double ovulation in primiparous dairy cows. Factors influencing the double ovulation rate were analysed using binary logistic regression on 676 cows: 475 (70.3%) inseminated at spontaneous estrus and 201 following one of two different estrus synchronization protocols for fixed-time artificial insemination (FTAI). The odds ratio for double ovulations was 0.92 (p = .002) per unit increase in prediction value and 2 (p = .01) for cows subjected to an FTAI protocol. Our findings suggest that genomic prediction values for twin pregnancies can effectively identify the risk of double ovulation at the herd level.

Converting estimated breeding values from the observed to probability scale for health traits

Dairy cattle health traits are paramount from a welfare and economic viewpoint; therefore, modern breeding programs prioritize the genetic improvement of these traits. Estimated breeding values for health traits are published as the probability of animals staying healthy. They are obtained using threshold models, which assume that the observed binary phenotype (i.e., healthy or sick) is dictated by an underlying normally distributed liability exceeding or not a threshold. This methodology requires significant computing time and faces convergence challenges as it implies a nonlinear system of equations. Linear models have more straightforward computations and provide a robust approximation to threshold models; thus, they could be used to overcome the mentioned challenges. However, linear models yield estimated breeding values on the observed scale, requiring an approximation to the liability scale analogous to that from threshold models to later obtain the estimated breeding values on the probability scale. In addition, the robustness of the approximation of linear to threshold models depends on the amount of information and the incidence of the trait, with extreme incidence (i.e., ≤ 5%) deviating from optimal approximation. Our objective was to test a transformation from the observed to the liability and then to the probability scale in the genetic evaluation of health traits with moderate and very low (extreme) incidence. Data comprised displaced abomasum (5.1M), ketosis (3.6M), lameness (5M), and mastitis (6.3M) records from a Holstein population with a pedigree of 6M animals, of which 1.7M were genotyped. Univariate threshold and linear models were performed to predict breeding values. The agreement between estimated breeding values on the probability scale derived from threshold and linear models was assessed using Spearman rank correlations and comparison of estimated breeding values distributions. Correlations were at least 0.95, and estimated breeding value distributions almost entirely overlapped for all the traits but displaced abomasum, the trait with the lowest incidence (2%). Computing time was ∼3x longer for threshold than for linear models. In this Holstein population, the approximation was suboptimal for a trait with extreme incidence (2%). However, when the incidence was ≥6%, the approximation was robust, and its use is recommended along with linear models for analyzing categorical traits in large populations to ease the computational burden.

Peripartal changes of metabolic and hormonal parameters in Romanian spotted cows and their relation with retained fetal membranes

This clinical study investigates various metabolic and physiological parameters in dairy cows during puerperium. Retained fetal membranes (RFM) is a significant postpartum complication that can affect the overall health, fertility and productivity of dairy cattle. The research focuses on changes in total proteins, albumin, glucose, triglycerides, total cholesterol, aspartate aminotransferase (AST) and alanine aminotransferase (ALT), cortisol, insulin, and insulin-like growth factor 1 (IGF-1) levels among cows experiencing normal post-partum period (NP) and those with RFM. A significant increase in protein levels was noted during the post-partum period in the RFM group, indicating physiological impacts of RFM at this stage. Albumin levels showed significant differences, highlighting a significant biological effect of RFM in the post-partum period. Glucose levels varied significantly in the weeks leading to parturition, suggesting altered metabolic states in cows that suffered RFM. Triglyceride and cholesterol levels were significantly higher during the antepartum period in the group that experienced reproductive failure, indicating substantial alterations in lipid metabolism which could herald the apparition of RFM. AST and ALT levels provided insights into cellular stress and liver function, with significant increases noted around parturition which could be attributed to the substantial physiological strain of parturition itself. Cortisol levels were higher in RFM cows 2 weeks before parturition, which could indicate an increasing stress response or a physiological preparation for the upcoming labor, and may be more pronounced in cows predisposed to RFM. Insulin levels decreased significantly before and at parturition in RFM cows, indicating a strong energy deficit. IGF-1 levels decreased significantly in RFM cows after parturition. Significant changes in metabolic parameters, such as glucose, triglycerides, and cholesterol levels, delineate the pronounced metabolic challenges faced by cows with RFM. The study elucidates that while some variations are noted as parturition approaches, the most substantial impacts attributable to RFM on metabolic and physiological parameters occur after parturition. These changes may have implications for the health, recovery, and productivity of cows postpartum, suggesting the need for targeted management strategies to mitigate the effects of RFM.

Global losses due to dairy cattle diseases: A comorbidity-adjusted economic analysis

An economic simulation was carried out over 183 milk-producing countries to estimate the global economic impacts of 12 dairy cattle diseases and health conditions: mastitis (subclinical and clinical), lameness, paratuberculosis (Johne's disease), displaced abomasum, dystocia, metritis, milk fever, ovarian cysts, retained placenta, and ketosis (subclinical and clinical). Estimates of disease impacts on milk yield, fertility, and culling were collected from the literature, standardized, meta-analyzed using a variety of methods ranging from simple averaging to random-effects models, and adjusted for comorbidities to prevent overestimation. These comorbidity-adjusted disease impacts were then combined with a set of country-level estimates for lactational incidence or prevalence or both, herd characteristics, and price estimates within a series of Monte Carlo simulations that estimated and valued the economic losses due to these diseases. It was estimated that total annual global losses are US$65 billion (B). Subclinical ketosis, clinical mastitis, and subclinical mastitis were the costliest diseases modeled, resulting in mean annual global losses of approximately US$18B, US$13B, and US$9B, respectively. Estimated global annual losses due to clinical ketosis, displaced abomasum, dystocia, lameness, metritis, milk fever, ovarian cysts, paratuberculosis, and retained placenta were estimated to be US$0.2B, US$0.6B, US$0.6B, US$6B, US$5B, US$0.6B, US$4B, US$4B, and US$3B, respectively. Without adjustment for comorbidities, when statistical associations between diseases were disregarded, mean aggregate global losses would have been overestimated by 45%. Although annual losses were greatest in India (US$12B), the United States (US$8B), and China (US$5B), depending on the measure of losses used (losses as a percentage of gross domestic product, losses per capita, losses as a percentage of gross milk revenue), the relative economic burden of these dairy cattle diseases across countries varied markedly.

Health and Thermal Comfort of Dairy Cattle in Compost-Bedded Pack Barns and Other Types of Housing: A Comparative Systematic Review

This systematic review was conducted to describe and discuss the main research findings available in the literature concerning the health and thermal comfort of dairy cattle housed in Compost-Bedded Pack Barn (CBP) systems, in comparison to Free Stall (FS), Tie-Stall (TS), and/or Loose Housing (LH) systems. Searches for peer-reviewed experimental articles in English were performed in the Scopus and Web of Science databases. Forty-three non-duplicated scientific articles were obtained and subjected to a four-stage evaluation process, according to the PRISMA methodology and predefined eligibility criteria. This process resulted in the selection of 13 articles for inclusion. Regarding animal health, the results provide evidence that the incidence of problems such as lameness, limb injuries, and reproductive disorders is lower in CBP systems. However, if bedding management is not effective in ensuring the provision of dry and comfortable surfaces, an increase in somatic cell count (SCC) and prevalence of mastitis incidence (PMI) may occur. For thermal comfort, it was found that the CBP system exhibited higher temperatures during summer and lower temperatures during winter when compared to FS with cross-ventilation in association with evaporative cooling. However, no differences were observed in terms of thermal comfort in spring and autumn. As this is a recent research area, caution should be exercised when extrapolating the results, considering the specificities of each cited study.

Genomic prediction of blood biomarkers of metabolic disorders in Holstein cattle using parametric and nonparametric models

BackgroundMetabolic disturbances adversely impact productive and reproductive performance of dairy cattle due to changes in endocrine status and immune function, which increase the risk of disease. This may occur in the post-partum phase, but also throughout lactation, with sub-clinical symptoms. Recently, increased attention has been directed towards improved health and resilience in dairy cattle, and genomic selection (GS) could be a helpful tool for selecting animals that are more resilient to metabolic disturbances throughout lactation. Hence, we evaluated the genomic prediction of serum biomarkers levels for metabolic distress in 1353 Holsteins genotyped with the 100K single nucleotide polymorphism (SNP) chip assay. The GS was evaluated using parametric models best linear unbiased prediction (GBLUP), Bayesian B (BayesB), elastic net (ENET), and nonparametric models, gradient boosting machine (GBM) and stacking ensemble (Stack), which combines ENET and GBM approaches.ResultsThe results show that the Stack approach outperformed other methods with a relative difference (RD), calculated as an increment in prediction accuracy, of approximately 18.0% compared to GBLUP, 12.6% compared to BayesB, 8.7% compared to ENET, and 4.4% compared to GBM. The highest RD in prediction accuracy between other models with respect to GBLUP was observed for haptoglobin (hapto) from 17.7% for BayesB to 41.2% for Stack; for Zn from 9.8% (BayesB) to 29.3% (Stack); for ceruloplasmin (CuCp) from 9.3% (BayesB) to 27.9% (Stack); for ferric reducing antioxidant power (FRAP) from 8.0% (BayesB) to 40.0% (Stack); and for total protein (PROTt) from 5.7% (BayesB) to 22.9% (Stack). Using a subset of top SNPs (1.5k) selected from the GBM approach improved the accuracy for GBLUP from 1.8 to 76.5%. However, for the other models reductions in prediction accuracy of 4.8% for ENET (average of 10 traits), 5.9% for GBM (average of 21 traits), and 6.6% for Stack (average of 16 traits) were observed.ConclusionsOur results indicate that the Stack approach was more accurate in predicting metabolic disturbances than GBLUP, BayesB, ENET, and GBM and seemed to be competitive for predicting complex phenotypes with various degrees of mode of inheritance, i.e. additive and non-additive effects. Selecting markers based on GBM improved accuracy of GBLUP.

The bacterial microbiota of the gastrointestinal tract of dairy cattle: structure, functions, importance (review)

The review presents the generalized material of experimental studies and review works (114 sources, including 110 foreign) on studying the composition of bacterial microbiota of the gastrointestinal tract in cattle depending on age, clinical condition of animals and level of productivity, shows the influence of the functional activity of microbiota on the formation and development of the organism. The microbiota affects the health and productive qualities of dairy cattle. The bacterial community of the gastrointestinal tract plays a crucial role in the digestive system. This complex system with feedback, where on the one hand, the microbiota is influenced by the genotype of the host, feed base, living conditions, breeding methods, and drugs used, and on the other hand, the microbiota primarily affects plastic and energy metabolism, but also indirectly affects respiratory, urinary, central nervous, and immune systems of the body. Bacterial diversity is laid down during the fetal period, undergoes significant changes during calf growth, and remains stable throughout life, adapting to changing conditions. Modern studies of gastrointestinal diseases are increasingly focusing on the composition of the microbial community, pointing to the dangers of antibiotic use and the need for a transition to probiotic and prebiotic therapy. Productive qualities of cows, such as milk yield and fat and protein content, also depend on the composition of the microbiota.

The Experimental and In Silico-Based Evaluation of NRF2 Modulators, Sulforaphane and Brusatol, on the Transcriptome of Immortalized Bovine Mammary Alveolar Cells.

Changes during the production cycle of dairy cattle can leave these animals susceptible to oxidative stress and reduced antioxidant health. In particular, the periparturient period, when dairy cows must rapidly adapt to the sudden metabolic demands of lactation, is a period when the production of damaging free radicals can overwhelm the natural antioxidant systems, potentially leading to tissue damage and reduced milk production. Central to the protection against free radical damage and antioxidant defense is the transcription factor NRF2, which activates an array of genes associated with antioxidant functions and cell survival. The objective of this study was to evaluate the effect that two natural NRF2 modulators, the NRF2 agonist sulforaphane (SFN) and the antagonist brusatol (BRU), have on the transcriptome of immortalized bovine mammary alveolar cells (MACT) using both the RT-qPCR of putative NRF2 target genes, as well as RNA sequencing approaches. The treatment of cells with SFN resulted in the activation of many putative NRF2 target genes and the upregulation of genes associated with pathways involved in cell survival, metabolism, and antioxidant function while suppressing the expression of genes related to cellular senescence and DNA repair. In contrast, the treatment of cells with BRU resulted in the upregulation of genes associated with inflammation, cellular stress, and apoptosis while suppressing the transcription of genes involved in various metabolic processes. The analysis also revealed several novel putative NRF2 target genes in bovine. In conclusion, these data indicate that the treatment of cells with SFN and BRU may be effective at modulating the NRF2 transcriptional network, but additional effects associated with cellular stress and metabolism may complicate the effectiveness of these compounds to improve antioxidant health in dairy cattle via nutrigenomic approaches.

Harnessing Vaginal Probiotics for Enhanced Management of Uterine Disease and Reproductive Performance in Dairy Cows: A Conceptual Review.

Uterine disease in cattle impairs reproductive performance and profitability and increases antibiotic use and antimicrobial resistance. Thus, probiotics offer a promising alternative therapy. This review presents conceptual findings on the efficacy of probiotics in managing uterine diseases and fertility in cows. Probiotics containing Lactobacillus spp. and Bifidobacterium spp. individually or as composite formulations are known to improve fertility. Strategic intravaginal administration of these formulations would likely enhance uterine immunity, particularly during the postpartum period. While current findings on the benefits to uterine health are encouraging, there is still significant knowledge missing, including a lack of empirical information from large-scale field trials. This review underscores the need for evidence-based guidelines for probiotics, such as genomic selection of formulations, targeted delivery, or potential synergy with other interventions. Future research should address these gaps to maximize the potential of probiotics in managing uterine diseases and enhancing the reproductive health of dairy cattle.

Prevalence of Lameness in Dairy Cows and Associated Risk Factors at Hawassa Town Dairy Farms, Ethiopia.

Lameness is one of the greatest constraints on the productivity, health, and welfare of dairy cattle. A cross-sectional study was carried out from March 2021 to September 2021 in Hawassa town with the aim of assessing the prevalence and identifying the associated risk factors of lameness in dairy farms. The study was conducted on 440 animals belonging to 19 randomly selected intensive dairy farms. Data regarding lameness and its possible risk factors were collected both at animal and farm level using a questionnaire. The results showed that the overall prevalence of lameness was 10.2% (n = 45/440). The association of lameness prevalence with various risk factors including milking status, exercise, age, parity, milk yield, and lactation stage was statistically tested using logistic regression model. There was a significant variation in the prevalence of lameness (P < 0.05) between cattle with different milking status, age, parity, milk yield, and stage of lactation by the univariable analysis result. According to the multivariable analysis, only milk yield and lactation stage were statistically associated with the occurrence of lameness. Milking animals (8%) had higher prevalence of lameness than nonmilking (2.2%). The occurrence of lameness increased with milk yield. The highest prevalence of lameness was recorded in the early stage of lactation. Lameness was more frequent in hind limbs (6.6%) than in forelimbs (3.6%). The main causes of lameness observed in this study were both claw overgrowth 10 (2.3%), unequal claw size 10 (2.3%), solar ulcer 8 (1.8%), interdigital necrobacillosis 2 (0.5%), interdigital hyperplasia 2 (0.5%), and digital dermatitis 1 (0.2%). There was no means of early lameness diagnosis in 94.7% of farms. Lameness was found to be an important disease in dairy cows at Hawassa town. Prevention and early diagnosis leading to prompt treatment of lameness in cows should be part of dairy farm management practice.

The Most Important Metabolic Diseases in Dairy Cattle during the Transition Period.

This review paper provides an in-depth analysis of three critical metabolic diseases affecting dairy cattle such as subacute ruminal acidosis (SARA), ketosis, and hypocalcemia. SARA represents a disorder of ruminal fermentation that is characterized by extended periods of depressed ruminal pH below 5.5-5.6. In the long term, dairy herds experiencing SARA usually exhibit secondary signs of the disease, such as episodes of laminitis, weight loss and poor body condition despite adequate energy intake, and unexplained abscesses usually 3-6 months after an episode of SARA. Depressed milk-fat content is commonly used as a diagnostic tool for SARA. A normal milk-fat test in Holstein dairy cows is >4%, so a milk-fat test of <3% can indicate SARA. However, bulk tank testing of milk fat is inappropriate to diagnose SARA at the herd level, so when >4 cows out of 12 and <60 days in milk are suspected to have SARA it can be considered that the herd has a problem. The rapid or abrupt introduction of fresh cows to high-concentrate diets is the most common cause of SARA. Changes in ruminal bacterial populations when exposed to higher concentrate rations require at least about 3 weeks, and it is recommended that concentrate levels increase by no more than 400 g/day during this period to avoid SARA. Ketosis, a prevalent metabolic disorder in dairy cattle, is scrutinized with a focus on its etiological factors and the physiological changes leading to elevated ketone bodies. In total mix ration-fed herds, an increased risk of mastitis and reduced fertility are usually the first clinical signs of ketosis. All dairy cows in early lactation are at risk of ketosis, with most cases occurring in the first 2-4 weeks of lactation. Cows with a body condition score ≥3.75 on a 5-point scale at calving are at a greater risk of ketosis than those with lower body condition scores. The determination of serum or whole blood acetone, acetoacetate, beta-hydroxybutyrate (BHB) concentration, non-esterified fatty acids (NEFA), and liver biopsies is considered the best way to detect and monitor subclinical ketosis, while urine or milk cowside tests can also be used in on-farm monitoring programs. Concentrations >1.0 mmol/L or 1.4 mmol/L blood or serum BHB are considered diagnostic of subclinical ketosis. The standard threshold used for blood is 1.2 mmol/L, which corresponds to thresholds of 100 mcmol/L for milk and 15 mg/dL for urine. Oral administration of propylene glycol (250-400 g, every 24 h for 3-5 days) is the standard and most efficacious treatment, as well as additional therapy with bolus glucose treatment. Hypocalcemia is a disease of adult dairy cows in which acute hypocalcemia causes acute to peracute, afebrile, flaccid paralysis that occurs most commonly at or soon after parturition. Dairy cows are at considerable risk for hypocalcemia at the onset of lactation, when daily calcium excretion suddenly increases from about 10 g to 30 g per day. Cows with hypocalcemia have a more profound decrease in blood calcium concentration-typically below 5.5 mg/dL. The prevention of parturient paresis has been historically approached by feeding cows low-calcium diets during the dry period. Negative calcium balance triggers calcium mobilization before calving and better equips the cow to respond to the massive calcium needs at the onset of lactation. Calcium intake must be limited to <20 g per day for calcium restriction to be effective. The most practical and proven method for monitoring hypocalcemia is by feeding cows an acidogenic diet for ~3 weeks before calving. Throughout the review, emphasis is placed on the importance of early diagnosis and proactive management strategies to mitigate the impact of these metabolic diseases on dairy cattle health and productivity. The comprehensive nature of this paper aims to serve as a valuable resource for veterinarians, researchers, and dairy farmers seeking a deeper understanding of these prevalent metabolic disorders in dairy cattle.

Multifractal characterization and recognition of animal behavior based on deep wavelet transform

The study conduct an in-depth exploration of the multifractal characteristics of dairy cows behavioral data, aiming to reveal their complexity and representation in behavioral patterns. By means of Multifractal Detrended Fluctuation Analysis (MFDFA) in conjunction with deep wavelet transform, we extract multifractal indices that precisely depict the differences and dynamic changes of cows behavior. Further, we delves into the potential correlations between these multifractal features and the physiological states of dairy cattle, particularly focusing on their potential applications in predicting different physiological conditions. And an assessment model is developed based on these fractal indices and utilize advanced machine learning techniques to evaluate their effectiveness and accuracy in predicting the physiological states of dairy cattle. This study not only unveils the multifractal properties of cattle behavior but also demonstrates how these features can be utilized to predict significant physiological states, providing new scientific bases and methods for dairy cattle health management.

Uterine Disease in Dairy Cows: A Comprehensive Review Highlighting New Research Areas.

Uterine disease is an intensely studied part of dairy cattle health management as it heavily affects many commercial dairy farms and has serious economic consequences. Forms of the disease, pathophysiology, pathogens involved and the effects of uterine disease on the health and performance of cows have already been well described by various authors. Lately, researchers' attention has shifted towards the healthy microbiome of the uterus and the vagina to put emphasis on prevention rather than treatment. This aligns with the growing demand to reduce the use of antibiotics or-whenever possible-replace them with alternative treatment options in farm animal medicine. This review provides a comprehensive summary of the last 20 years of uterine disease research and highlights promising new areas for future studies.