Bacterial networks and enzyme genes in bacterial floccules from hydrolysis and aeration reactors in a dairy wastewater treatment system.

The dairy industry generates substantial wastewater, which is commonly treated using integrated anaerobic hydrolysis and aerated biofilm reactors. However, the bacterial composition and functional differences within the generated floccules remain unclear. In this study, we employed 16S rRNA and metagenomic sequencing to compare bacterial communities and enzyme gene profiles between suspended floccules from the hydrolysis ponds and the aeration ponds. Results revealed that the bacterial phyla Firmicutes, Proteobacteria, and Bacteroidetes dominated the wastewater treatment system and the relative abundance of these bacterial phyla varied in each pond. Additionally, the aeration ponds exhibited higher bacterial operational taxonomic units and enzyme gene abundance. Network analysis demonstrated a more complex bacterial network structure in the hydrolysis ponds compared to the aeration ponds. Furthermore, enzyme gene abundance revealed higher metabolic enzyme genes in the hydrolysis ponds, while signal transduction enzyme genes were more abundant in the aeration ponds. Notably, the top 10 bacterial genera, primarily Hydromonas in the hydrolysis ponds and Ferruginibacter in the aeration ponds, exhibited distinct contributions to signal transduction enzyme genes. Hydromonas dominated the metabolic enzyme genes in both ponds. These findings provide crucial insights for optimizing dairy wastewater treatment technologies.

Effects of dietary zinc on the gut microbiome and resistome of the gestating cow and neonatal calf.

Zinc is an essential trace element required in the diet of all species. While the effects of zinc have been studied in growing calves, little is known about the effect of zinc on the microbiota of the gestating cow or her neonatal calf. Understanding factors that shape the gut health of neonatal animals and evaluating the effect of dietary supplements in adult gestating animals is important in promoting animal health and informing feeding practices. The aims of this study were to determine the effect of dietary zinc on the microbiota and resistome of the gestating cow and calf. Gestating cows received standard (40 ppm) or high (205 ppm) dietary zinc levels from dry off to calving. Fecal samples were collected from cows upon enrollment and at calving and from neonatal calves. Fecal samples underwent 16S rRNA sequencing and a subset also underwent shotgun metagenomic sequencing. The effect of zinc supplementation on the diversity and composition of the cow and calf microbiome and resistome was assessed. Alpha and beta diversity and composition of the microbiota were significantly altered over time but not by treatment in the cows, with alpha diversity decreasing and 14 genera found at significantly higher relative abundances at calving compared to enrollment. Levels of 27 antimicrobial resistance genes significantly increased over time. Only a small number of taxa were differentially expressed at calving in treatment and control groups, including Faecalibacterium, Bacteroides, Turicibacter, and Bifidobacterium pseudolongum. No effect of the dam's treatment group was observed on the diversity or composition of the neonatal calf microbiota. The calf resistome, which was relatively rich and diverse compared to the cow, was also unaffected by the dam's treatment group. The impact of high levels of dietary zinc thus appeared to be minimal, with no observed changes in alpha or beta diversity, and few changes in the relative abundance of a small number of taxa and antimicrobial resistance genes.

Modelling solar photovoltaic systems on dairy farms for cost savings and GHG emission reduction.

Rising on-farm electricity demand, coupled with surges in electricity prices, has increased costs associated with milk production. Additionally, the use of grid electricity with a high carbon footprint depreciates the environmental performance of dairy farming. We assessed the potential of photovoltaic (PV) systems installed on dairy parlours under different policy incentives to reduce electricity costs and the carbon footprint of dairy farms in Ireland. The HOMER Pro software was employed to model electricity consumption, generation and economic performance of four 15-year PV project scenarios for 11 Irish farms. Scenarios considering the targeted agricultural modernisation scheme II (TAMS) and the microgeneration support scheme are assessed. The results show that PV systems are a feasible option to power dairy farms when current energy prices and inflation rates are applied. Small systems eligible for TAMS grants presented an average discounted payback period of 5 years, making them a better option for farmers than larger projects, which had an average payback period of 8.5 years. The deployment of PV systems reduced the GHG intensity of electricity consumed at the farms by up to 29 %.

Antimicrobial resistance and prevalence of Listeria species from raw milk and dairy products in Burdur, Turkey.

OBJECTIVES: Worldwide, but especially in emerging nations, concerns about food safety pose a serious obstacle to societal and economic progress. This research aimed to examine the prevalence of Listeria spp. in raw milk and dairy products in Burdur, as well as the presence of genes associated with biofilm formation and antibiotic resistance in the isolates. METHODS: A total of 185 samples, including raw milk, curd, cream, butter, yogurt and cheese, were randomly collected in Burdur. The enrichment and isolation methods specified by the United States Department of Agriculture was used to identify Listeria species in milk and dairy product samples. Culture-positive strains were identified as Listeria genus and as species by PCR. Antibiotic susceptibility of the isolates was evaluated against 14 antibiotics using the disc diffusion technique (EUCAST). RESULTS: Of them, 2.2% (4/185) were positive for Listeria spp. Listeria species were isolated from cheese and yogurt samples. Two of them were Listeria innocua 1.1% (2/185), one was Listeria ivanovii 0.5% (1/185) and the other was Listeria welshimeri 0.5% (1/185). As a result of multiplex PCR of the biofilm genotypic marker luxS and flaA genes, the flaA gene was detected in three of four isolates, the luxS gene was detected in one isolate, and these two genes were not found in one isolate. Although all isolates were resistant to gentamicin and rifampicin, they also showed multidrug resistance. CONCLUSION: This study revealed that the diversity of prevalence of Listeria spp. in Burdur requires microbial risk assessment in the milk and dairy products value chain and the need to focus on the problem of multiple antibiotic resistance.

Integrated Analysis of Transcriptome Profiles and lncRNA-miRNA-mRNA Competing Endogenous RNA Regulatory Network to Identify Biological Functional Effects of Genes and Pathways Associated with Johne's Disease in Dairy Cattle.

Paratuberculosis or Johne's disease (JD), a chronic granulomatous gastroenteritis caused by Mycobacterium avium subsp. paratuberculosis (MAP), causes huge economic losses and reduces animal welfare in dairy cattle herds worldwide. At present, molecular mechanisms and biological functions involved in immune responses to MAP infection of dairy cattle are not clearly understood. Our purpose was to integrate transcriptomic profiles and competing endogenous RNA (ceRNA) network analyses to identify key messenger RNAs (mRNAs) and regulatory RNAs involved in molecular regulation of peripheral blood mononuclear cells (PBMCs) for MAP infection in dairy cattle. In total, 28 lncRNAs, 42 miRNAs, and 370 mRNAs were identified by integrating gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. In this regard, we identified 21 hub genes (CCL20, CCL5, CD40, CSF2, CXCL8, EIF2AK2, FOS, IL10, IL17A, IL1A, IL1B, IRF1, MX2, NFKB1, NFKBIA, PTGS2, SOCS3, TLR4, TNF, TNFAIP3, and VCAM1) involved in MAP infection. Furthermore, eight candidate subnets with eight lncRNAs, 29 miRNAs, and 237 mRNAs were detected through clustering analyses, whereas GO enrichment analysis of identified RNAs revealed 510, 22, and 11 significantly enriched GO terms related to MAP infection in biological process, molecular function, and cellular component categories, respectively. The main metabolic-signaling pathways related to MAP infection that were enriched included the immune system process, defense response, response to cytokine, leukocyte migration, regulation of T cell activation, defense response to bacterium, NOD-like receptor, B cell receptor, TNF, NF-kappa B, IL-17, and T cell receptor signaling pathways. Contributions of transcriptome profiles from MAP-positive and MAP-negative sample groups plus a ceRNA regulatory network underlying phenotypic differences in the intensity of pathogenicity of JD provided novel insights into molecular mechanisms associated with immune system responses to MAP infection in dairy cattle.

Characterization of highly pathogenic avian influenza virus in retail dairy products in the US.

In March 2024, clade 2.3.4.4b H5N1 highly pathogenic avian influenza virus (HPAIV) was detected in dairy cattle in the US, and it was discovered that the virus could be detected in raw milk. Although affected cow's milk is diverted from human consumption and current pasteurization requirements are expected to reduce or eliminate infectious HPAIV from the milk supply, a study was conducted to characterize whether the virus could be detected by quantitative real-time RT-PCR (qrRT-PCR) in pasteurized retail dairy products and, if detected, to determine whether the virus was viable. From 18 April to 22 April 2024, a total of 297 samples of Grade A pasteurized retail milk products (23 product types) were collected from 17 US states that represented products from 132 processors in 38 states. Viral RNA was detected in 60 samples (20.2%), with qrRT-PCR-based quantity estimates (non-infectious) of up to 5.4log1050% egg infectious doses per mL, with a mean and median of 3.0log10/mL and 2.9log10/mL, respectively. Samples that were positive for type A influenza by qrRT-PCR were confirmed to be clade 2.3.4.4 H5 HPAIV by qrRT-PCR. No infectious virus was detected in any of the qrRT-PCR-positive samples in embryonating chicken eggs. Further studies are needed to monitor the milk supply, but these results provide evidence that the infectious virus did not enter the US pasteurized milk supply before control measures for HPAIV were implemented in dairy cattle.IMPORTANCEHighly pathogenic avian influenza virus (HPAIV) infections in US dairy cattle were first confirmed in March 2024. Because the virus could be detected in raw milk, a study was conducted to determine whether it had entered the retail food supply. Pasteurized dairy products were collected from 17 states in April 2024. Viral RNA was detected in one in five samples, but infectious virus was not detected. This provides a snapshot of HPAIV in milk products early in the event and reinforces that with current safety measures, infectious viruses in milk are unlikely to enter the food supply.

Genomic characterization of highly pathogenic avian influenza A H5N1 virus newly emerged in dairy cattle.

In March 2024, the emergence of highly pathogenic avian influenza (HPAI) A (H5N1) infections in dairy cattle was detected in the United Sates for the first time. We genetically characterize HPAI viruses from dairy cattle showing an abrupt drop in milk production, as well as from two cats, six wild birds, and one skunk. They share nearly identical genome sequences, forming a new genotype B3.13 within the 2.3.4.4b clade. B3.13 viruses underwent two reassortment events since 2023 and exhibit critical mutations in HA, M1, and NS genes but lack critical mutations in PB2 and PB1 genes, which enhance virulence or adaptation to mammals. The PB2 E627 K mutation in a human case associated with cattle underscores the potential for rapid evolution post infection, highlighting the need for continued surveillance to monitor public health threats.

Is the milk we drink safe from elevated concentrations of prioritised heavy metals/metalloids? - A global systematic review and meta-analysis followed by a cursory risk assessment reporting.

Milk has been globally recognised as a comprehensive and vital food source for centuries. However, the presence of heavy metals and metalloids (metal(loid)s) in milk is a global problem. As metal(loid)s are present in the soil due to natural geogenic and various anthropogenic activities, these metal(loid)s are bio-transferred into animal feed, which further results in the presence of metal(loid)s in milk due to bio transfer/accumulation. This systematic review collated information from published literature between 2000 and 2021. It focused on the global issue of metal(loid)s in milk, posing potential health risks. These contaminants enter the food chain through the bio-transfer/accumulation process from soil to animal feed to milk. The key metal(loid)s examined are arsenic (As), mercury (Hg), lead (Pb), and cadmium (Cd). A meta-analysis of 66 selected papers revealed the widespread presence of these contaminants in milk samples globally, with Pb being the most studied (43 %). This research estimated metal(loid)s levels or concentrations as 12.71 (95 % Confidence Interval (CI) = 0.16-25.26), 16.09 (95 % CI = 4.31-27.70), 197.04 (95 % CI = 75.28-318.18), 31.67 (95 % CI = 20.14-43.20) µg/kg (ppb) for As, Hg, Pb, and Cd, respectively using Stata™. The metal(loid) concentrations in milk were within the threshold limits other than Pb and Cd. Some studies in America, Africa, and Asia reported elevated Pb and Cd concentrations, raising health concerns. The simulated Risk Quotients (RQ) and Integrated Risk Quotient (IRQ) values generally remain above one, indicating potential human health risks. Notably, the IRQ value increases with more metal(loid)s consideration. Subgroup analysis indicates low-fat milk contains higher metal(loid)s concentrations. While metal(loid)s concentrations in milk largely comply with safety limits, some regions exhibit concerning concentrations. Therefore, continued surveillance to address potential health risks associated with metal(loid)s in milk is necessary to ensure dairy products' safety.

Alteration of Fecal Microbiota, Fecal Metabolites, and Serum Metabolites in Dairy Cows with Pre-Retained Placenta.

Retained placenta (RP) affects lactation and fertility in dairy cows and causes economic losses to the dairy industry. Therefore, screening for early warning of this disease is important. This study used multi omics techniques to reveal the metabolic differences of dairy cows before RP onset and to find potential warning markers. Fecal samples and serum samples of 90 healthy Holstein cows were collected 7 days pre-calving; 10 healthy and 10 RP cows were enrolled according to normal expulsion of fetal membranes after calving. Fecal samples were subjected to 16S rRNA sequencing and untargeted metabolomics analysis, while plasma was analyzed using targeted metabolomics. Pathogenic bacteria levels increased in the intestines of cows with RP compared to those in healthy cows. Lipid metabolites constituted the largest proportion of differential metabolites between feces and plasma. Six potential warning markers for RP in cows were identified, including two fecal microbiomics markers (Oscillospiraceae UCG-005 and Escherichia-Shigella), one fecal untargeted metabolomics marker (N-acetylmuramic acid), and three plasma targeted metabolomics markers (glycylcholic acid-3 sulfate, 7-ketolithocholic acid, and 12-ketolithocholic acid). These biomarkers can predict RP occurrence in the early perinatal period. These results lay a theoretical foundation for early nutritional intervention and pathogenesis research in dairy cows.

Methicillin-Resistant Staphylococcus aureus (MRSA) in Dairy Products and Bulk-Tank Milk (BTM).

In order to contribute to an assessment of the role of food in the risks of transmission of methicillin-resistant Staphylococcus aureus (MRSA), a review was undertaken of research on this microorganism in milk and dairy products published from January 2001 to February 2024. A total of 186 publications were selected, 125 for dairy products and 61 for bulk-tank milk (BTM). MRSA was detected in 68.8% of the research into dairy products and 73.8% of investigations relating to BTM, although in most studies the prevalence was less than 5%. Of the set of S. aureus strains isolated, approximately 30% corresponded to MRSA. The foods most extensively contaminated with this microorganism were raw milk and some types of soft cheese. Determination of the mecA gene on its own is known not to suffice for the detection of all MRSA strains. The great diversity of techniques used to study MRSA in milk and dairy products made it difficult to draw comparisons between studies. It would thus be advisable to develop a standardized protocol for the study of this microorganism in foods.

Comparative Antimicrobial Resistance and Prevalence of Methicillin Resistance in Coagulase-Positive Staphylococci from Conventional and Organic Dairy Farms in South Korea.

Bovine mastitis (BM) has caused huge economic and financial losses in the dairy industry worldwide, with Staphylococcus aureus as one of its major pathogens. BM treatment still relies on antibiotics and its extensive use often generates methicillin-resistant S. aureus (MRSA) and mupirocin-resistant S. aureus (MuRSA). This study compared the antimicrobial resistance trend in coagulase-positive Stapholococci (CoPS) isolated from BM milk in conventional and organic dairy farms and checked prevalence of MRSA and MuRSA. A total of 163 presumptive Staphylococci were isolated, wherein 11 out of 74 from 4 conventional farms (CF1, CF2, CF3, CF4) and 17 out of 89 from 3 organic farms (OF1, OF2, OF3) exhibited coagulase activity. Multiplex-PCR amplification confirmed at least one coagulase-positive isolate from CF1, CF2, CF3, CF4, and OF1 as S. aureus, denoted by the presence of the nuc gene. Three isolates from CF2 contained the mecA gene, indicating MRSA prevalence, while the MuRSA gene marker, mupA, was not detected in any of the isolates. Antimicrobial testing showed that conventional farm isolates were more resistant to antibiotics, especially ampicillin and tetracycline. This suggests a risk of developing multidrug resistance in dairy farms if antibiotic use is not properly and strictly monitored and regulated.

From Herd Health to Public Health: Digital Tools for Combating Antibiotic Resistance in Dairy Farms.

The emergence of antimicrobial resistance (AMR) is a significant threat to global food security, human health, and the future of livestock production. Higher rates of antimicrobial use in dairy farming and the sheer lack of new antimicrobials available for use focused attention on the question of how the dairy production sector contributed to the development of AMR and paved the path toward taking action to curtail it on the targeted type of farms. This paper aims to provide an introduction to a phenomenon that has gained considerable attention in the recent past due to its ever-increasing impact, the use of antimicrobial drugs, the emergence of antimicrobial resistance (AMR) on dairy farms, and seeks to discuss the possibilities of approaches such as digital health monitoring and precision livestock farming. Using sensors, data, knowledge, automation, etc., digital health monitoring, as well as Precision Livestock Farming (PLF), is expected to enhance health control and minimize disease and antimicrobial usage. The work presents a literature review on the current status and trends of AMR in dairy farms, an understanding of the concept of digital health monitoring and PLF, and the presentation and usefulness of digital health monitoring and PLF in preventing AMR. The study also analyses the strengths and weaknesses of adopting and incorporating digital technologies and artificial intelligence for dairy farming and presents areas for further study and level of use.

Current Trends in Artificial Intelligence and Bovine Mastitis Research: A Bibliometric Review Approach.

Mastitis, an important disease in dairy cows, causes significant losses in herd profitability. Accurate diagnosis is crucial for adequate control. Studies using artificial intelligence (AI) models to classify, identify, predict, and diagnose mastitis show promise in improving mastitis control. This bibliometric review aimed to evaluate AI and bovine mastitis terms in the most relevant Scopus-indexed papers from 2011 to 2021. Sixty-two documents were analyzed, revealing key terms, prominent researchers, relevant publications, main themes, and keyword clusters. "Mastitis" and "machine learning" were the most cited terms, with an increasing trend from 2018 to 2021. Other terms, such as "sensors" and "mastitis detection", also emerged. The United States was the most cited country and presented the largest collaboration network. Publications on mastitis and AI models notably increased from 2016 to 2021, indicating growing interest. However, few studies utilized AI for bovine mastitis detection, primarily employing artificial neural network models. This suggests a clear potential for further research in this area.

Impact of Heat Stress on the Balance between Oxidative Markers and the Antioxidant Defence System in the Plasma of Mid-Lactating Modicana Dairy Cows.

Animal health is affected during heat stress as a result of impaired immune responses, increased production of reactive oxygen species, and/or a deficiency of antioxidants. This leads to an imbalance between oxidants and antioxidants and results in oxidative stress. Heat stress is usually measured in dairy cattle via the temperature-humidity index (THI). In the present study, we aimed at assessing the influence of incremental THI on the balance between oxidative markers and the antioxidant defence system in the plasma of Modicana cows. Twenty-four multiparous, mid-lactating dairy cows were divided into two groups on the basis of different levels of mean THI reached in the period of the previous week up until the day of blood and milk sampling (April THI1:55, May THI2:68, June THI3:71, July THI4:80). The blood samples were collected to measure reactive oxygen metabolites (ROM) and antioxidant defense markers (ferric reducing ability of plasma (FRAP), paraoxonase (PON), advanced oxidation protein products (AOPP), plasma thiol groups (SHp), as well as lipid-soluble antioxidant pro-vitamin (ß-carotene) and vitamins (tocopherol and retinol). Milk characteristics, haematological values, and plasma biochemical metabolites were also evaluated. Results showed a significant increase in ROM (p < 0.05) and a significant decrease in PON (p < 0.05), AOPP (p < 0.05), and ß-carotene (p < 0.001). Incremental THI significantly decreased levels of milk fat content, red and white blood cells, plasma glucose, and non-esterified fatty acids, while significantly increasing monocytes and the concentrations of ß-hydroxybutyrate and creatinine, but not fructosamine. The results of the study show that heat stress significantly affects reactive oxygen species production and antioxidant parameters. Carotenoid supplementation should be considered to alleviate the impact of these effects.

Identification of Predictive Biomarkers of Lameness in Transition Dairy Cows.

The aim of this study was to identify with a high level of confidence metabolites previously identified as predictors of lameness and understand their biological relevance by carrying out pathway analyses. For the dairy cattle sector, lameness is a major challenge with a large impact on animal welfare and farm economics. Understanding metabolic alterations during the transition period associated with lameness before the appearance of clinical signs may allow its early detection and risk prevention. The annotation with high confidence of metabolite predictors of lameness and the understanding of interactions between metabolism and immunity are crucial for a better understanding of this condition. Using liquid chromatography-tandem mass spectrometry (LC-MS/MS) with authentic standards to increase confidence in the putative annotations of metabolites previously determined as predictive for lameness in transition dairy cows, it was possible to identify cresol, valproic acid, and gluconolactone as L1, L2, and L1, respectively which are the highest levels of confidence in identification. The metabolite set enrichment analysis of biological pathways in which predictors of lameness are involved identified six significant pathways (p < 0.05). In comparison, over-representation analysis and topology analysis identified two significant pathways (p < 0.05). Overall, our LC-MS/MS analysis proved to be adequate to confidently identify metabolites in urine samples previously found to be predictive of lameness, and understand their potential biological relevance, despite the challenges of metabolite identification and pathway analysis when performing untargeted metabolomics. This approach shows potential as a reliable method to identify biomarkers that can be used in the future to predict the risk of lameness before calving. Validation with a larger cohort is required to assess the generalization of these findings.

Detection and Phenotypic Antimicrobial Susceptibility of Salmonella enterica Serotypes in Dairy Cattle Farms in the Po Valley, Northern Italy.

The presence of Salmonella spp. in dairy cattle farms poses a major risk to animal health and welfare. This study focused on Salmonella detection in dairy farms located in the Cremona and Mantua provinces (northern Italy) in samples collected and submitted to laboratories in 2021-2022. A total of 2710 samples from different sources, including calf carcasses/organs (n = 128), rectal swabs (n = 1937), feces (n = 390), bulk milk (n = 93), and overshoes/swabs (n = 127) for environmental sampling, were analyzed for the presence of Salmonella spp. and were included in the present study. Our results indicate that Salmonella was most commonly firstly identified from calf carcasses and organs (61.67%) and that the serotypes most frequently detected in dairies were S. Dublin (38.33%), S. Typhimurium (23.33%), and S. Typhimurium monophasic variant (14.17%). The most common pathological findings in calf carcasses were enteritis, hepatosplenomegaly, and pneumonia. The antimicrobial resistance pattern analyzed using the MIC assay of 51 Salmonella isolates revealed the presence of multi-resistant strains, which pose a major risk to public and animal health.

A Review of the Effects of Stress on Dairy Cattle Behaviour.

In this narrative review, the authors summarise the relationship between stress and behaviour and how dairy cattle cope with stressors. Based on the available literature, the most common stressors in intensive dairy cattle farming, such as pain, disease, heat stress, poor comfort caused by technology, and social stress, are surveyed. The authors describe how these stressors modify the behaviour of dairy cattle, influencing their feeding patterns, social interactions, and overall well-being. Additionally, the review explores the effectiveness of various coping mechanisms employed by dairy cattle to mitigate stress, including physiological adaptations and behavioural responses. This review is a valuable resource for understanding and grading stress in dairy cattle through behavioural reactions. Elucidating the intricate interplay between stressors and behaviour offers insights into potential interventions to improve animal welfare and productivity in dairy farming. Furthermore, this review highlights areas for future research, suggesting avenues for more comprehensive behavioural studies to enhance our understanding of stress management strategies in dairy cattle.

Subacute Rumen Acidosis in Greek Dairy Sheep: Prevalence, Impact and Colorimetry Management.

Subacute rumen acidosis (SARA) is a current issue in intensive livestock farming, and it is particularly associated with feeding high-concentrate diets. This study investigated the prevalence and impact of SARA in forty-two Greek dairy sheep flocks by recording rumen pH, milk composition, and milk yield over a period of nine months. Moreover, it explored the use of computerized rumen colorimetry as a management and diagnostic tool for SARA in dairy sheep. In culled ewes, computerized rumen mucosal colorimetry was applied, and rumen wall samples taken for histological examination. SARA cases were identified in 19 farms (45%, n = 42). Farms with SARA cases had lower milk fat levels, while milk yield and milk protein levels did not differ based on the SARA status of the farms. In culled ewes, rumen color was significantly associated with the flock's SARA status, and affected ewes showed increased thickness in non-keratinized and total epithelial layers. It was concluded that computerized rumen mucosal colorimetry in aged, culled ewes shows promise as an indicator, post mortem, of SARA present in dairy sheep flocks whose impact can be minimized by making significant changes in dietary management.

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.

A Look Inside-Histopathological Examinations of Different Tail Tip Lesions in Dairy Cows.

Feedlot cattle are frequently affected by inflammation and necrosis of the tail tips, resulting in impeded animal welfare and economic losses. In a recent study, it was demonstrated that dairy cows are also affected by different lesions of the tail tip, including alopecia, annular constrictions, crusting, scaling and swelling. Despite the frequent occurrence of these lesions, the underlying etiology and pathomechanisms are unclear to date. To gain insight into this malady, we histopathologically examined 16 tail tips of slaughtered dairy cows, representing the entire range of different lesions. While macroscopically alopecic areas were characterized by the formation of granulation tissue in the dermis with an inconspicuous epidermis, we found not only dermal granulation tissue but also purulent-necrotizing inflammation with the breakdown of the basement membrane in encrusted lesions. Interestingly, in some cases, we found areas of coagulation necrosis of the epidermal and dermal layers in the crusts. Tails with macroscopical scaling were affected by ortho- and/or parakeratotic hyperkeratosis, and, in tails with macroscopical swelling, we observed a low-protein edema of the central longitudinal connective tissue of the tail. We conclude that the observed lesions might be caused by ischemia of the skin in the distal parts of the tail.