Search Results (3,014)

Milk flow dynamics during mechanical milking are strongly influenced by species-specific mammary anatomy, milk partitioning between cisternal and alveolar compartments, and milking management. The present study aimed to compare milkability traits across the main dairy species reared in central Italy using a large dataset collected over 20 years. A total of 7315 animals were included: dairy cows (1103), buffaloes (2870), goats (2399), sheep (754), and donkeys (189). Milk flow curves were recorded using a portable Lactocorder^® device. The following traits were analyzed: milk yield (MY), lag time (LT), milk ejection time (MET), total milking time (TMT), peak flow rate (PFR), average flow rate (AFR), plateau phase (PL), bimodal phase (BM), and bimodality incidence (Bimo). Marked interspecific differences emerged. Dairy cows showed the highest MY and PFR, with bimodality occurring in 23.7% of curves. Buffaloes exhibited lower flow rates, prolonged LT, and extended TMT, reflecting their strong dependence on oxytocin-mediated alveolar milk ejection. Sheep demonstrated short milking times and low bimodality (13.5%), consistent with their large cisternal milk fraction. Goats displayed breed-dependent variability, with specialized dairy breeds showing higher PFR and longer TMT. Donkeys produced low milk volumes but exhibited rapid and efficient milk flow, with the lowest incidence of bimodality (7.4%). Overall, milk flow patterns reflected species-specific udder morphology and physiological mechanisms of milk ejection. Although this field-based study faces inherent limitations in environmental and protocol standardization across farms, the resulting long-term dataset remains highly representative. These findings highlight the importance of tailoring milking machine settings and prestimulation protocols to species and breed characteristics to optimize milking efficiency, labor management, and animal welfare. Full article

Microbial inactivation is essential for extending the shelf life of raw milk. Radio frequency (RF) thermal pasteurization has emerged as a promising technology for small-scale dairy processing. This study aimed to determine optimal RF temperature–time conditions, evaluate their effects on milk quality across milk from different species of cows, and assess economic feasibility. Raw milk from Holstein Friesian, Jersey, and Brown Swiss cows was treated using a dielectric heating system (40.68 MHz) at 72–92 °C for 20–100 s. The results were compared with conventional low-temperature long-time (LTLT) pasteurization of untreated milk. The optimal condition was 92 °C for 50 s, reducing the aerobic plate count from 5.80 to 0.69 log CFU/mL (a 5.11 log reduction), with no detection of Staphylococcus aureus, Bacillus cereus, and Escherichia coli. RF treatment did not significantly affect milk composition (p > 0.05), and color changes remained within acceptable limits. Milk stored at 4 °C maintained quality and safety for up to 28 days. Economic analysis indicated a net present value of USD 134,721.78, a benefit–cost ratio of 3.25, and a payback period of 6.8 months, confirming economic feasibility. These findings demonstrate that RF pasteurization can improve processing efficiency and support sustainable dairy production. Full article

Milk titratable acidity is a key indicator of raw milk freshness and quality, but its variation across different dairy animal species remains incompletely characterized. Based on 16,984 raw milk samples from eight dairy animal species (Holstein cow, goat, buffalo, camel, sheep, yak, donkey, and horse) collected within a retrospective raw milk quality monitoring framework in China from 2016 to 2024, this study provides a large-scale descriptive comparison of milk titratable acidity across species. Distinct titratable acidity profiles were observed among species, with camel and yak milk showing relatively high values, sheep, Holstein, and buffalo milk exhibiting intermediate values, and donkey and horse milk presenting markedly low values. Calendar-season-associated patterns also differed among species. Correlations between titratable acidity and milk components varied by species, with relatively stronger positive associations with protein and solids-not-fat (SNF) in several ruminant milks, suggesting that milk composition may contribute to differences in titratable acidity. However, because this study was based on an unbalanced observational dataset with limited animal-level, farm-level, feeding, management, physiological, and environmental metadata, these observations should be interpreted as descriptive and exploratory patterns rather than causal biological mechanisms. This dataset provides preliminary reference information for future studies on species-associated variation in raw milk titratable acidity and for discussions on species-specific raw milk quality evaluation. Full article

Fluorescence emission-excitation matrices for cow milk samples with different fat contents in the range of 0.05–10% and a constant protein content of 3%, as well as for butter and extracted milk components such as casein and lactose, have been measured using a spectrofluorometer. The influence of the increased fat content on the shape of the fluorescence spectra of milk has been studied. In addition, fluorescence spectra measured for serial dilutions of high-fat milk with water and skim milk, along with aqueous dilutions of skim milk, have shown that the fluorescence diagnostics of fat and protein content in milk can be implemented using excitation at only two wavelengths: 280 and 320 nm. The optimal spectral ranges proposed for detecting the content of milk components via fluorescence measurements can be useful when designing UV LED-based fluorescence analyzers of milk composition. Full article

Subclinical bovine mastitis (SBM) is an inflammatory condition of the udder that remains a major concern for the dairy industry due to its high incidence and the direct and indirect associated costs. Antibiotics are widely used for prophylaxis and therapy in livestock, especially for SBM. However, overuse and misuse have contributed to the emergence of antimicrobial resistance (AMR), enabling resistant bacteria to enter the food chain and potentially spread to humans. This study aimed to detect antibiotic-resistant Staphylococcus and Streptococcus associated with SBM in dairy cows from Pioter, north-central Ecuador. For this, a commercial screening test, morphological and biochemical assays, standard culture techniques, mass spectrometry, and PCR (polymerase chain reaction) were applied. Among 99 isolates, 77 were Staphylococcus and 22 were Streptococcus. Among the identified Staphylococcus isolates, S. aureus was the predominant species (36.4%). Resistance in Staphylococcus exceeded 70% for fosfomycin and was under 30% for the other antibiotics tested. In Streptococcus, S. uberis predominated (54.5%), with resistance primarily to penicillin and tetracycline (>50%). PCR identified mecA, nuc, and lukSF-PV genes in 7.8%, 29.9%, and 6.5% of Staphylococcus isolates, respectively. In Streptococcus, the ermB and blaZ genes were found in 18.2% and 50% of isolates, respectively. These data provide a baseline on SBM-associated AMR in the study area and highlight the need for ongoing surveillance and improved milking practices to mitigate risks to the dairy sector and public health. Full article

Accurate prediction of dry matter intake (DMI) is essential for ration formulation, nutrient supply, and evaluation of production efficiency in lactating dairy cows. Several DMI prediction models are currently used, but most comparative studies have emphasized overall accuracy rather than whether model bias changes across biologically relevant production contexts. The objective of this study was to evaluate the context-dependent bias of widely used DMI prediction models in lactating dairy cows across classes of energy-corrected milk (ECM) and lactation stage. A literature-derived database was assembled from 135 studies consisting of 436 treatments from 6985 Holstein cows, reporting observed DMI and the variables required to implement five prediction models and evaluate their prediction error (PE): NRC2001, the Cornell Net Carbohydrate and Protein System (CNCPS), NASEM2021, Agroscope2021, and GfE2023. PE was calculated as predicted DMI minus observed DMI, such that positive values indicated overprediction and negative values indicated underprediction. Observations were classified according to ECM and days in milk (DIM). Mixed models were fitted separately for the ECM class and the lactation-stage class, with the study fitted as a random effect. PE differed among models, and the pattern of bias depended on both the ECM and the lactation-stage classes. The interaction between the ECM class and the model was significant, indicating that productive level modified model bias. The interaction between lactation-stage class and model was also significant and more pronounced, indicating marked changes in model bias across lactation stages. Across classes, NASEM2021 generally remained closest to zero, whereas GfE2023 and CNCPS showed more negative PE values in most contexts. Agroscope2021 showed a more context-sensitive pattern, and NRC2001 remained comparatively moderate across several classes. These findings indicate that the evaluation of DMI prediction models based only on global mean bias may conceal an important biological structure in PE. Context-specific evaluation, particularly across the lactation stage, may provide a more informative basis for selecting DMI prediction models for research and practical ration formulation. Full article

Leptin (LEP) is an adipocyte-derived cytokine that integrates nutritional status, metabolism, and reproduction in cattle, with particular relevance for modern high-producing dairy cows. In ruminants, LEP and its receptors are widely expressed in metabolic and reproductive tissues, including adipose tissue, liver, hypothalamus, pituitary, ovary, uterus, and placenta, where LEP modulates energy homeostasis, neuroendocrine function, and local tissue responses. Changes in circulating LEP concentrations during the transition period reflect changes in body fat reserve, insulin and GH-IGF-1 dynamics, thyroid hormones, and inflammation and contribute to coordinated metabolic adaptations supporting the onset of lactation. At the reproductive level, LEP influences the hypothalamic–pituitary–gonadal axis, affects the pulsatility of luteinizing hormone (LH) under nutritional stress, and exerts direct effects on ovarian steroidogenesis, folliculogenesis, oocyte competence, embryo development, and uterine immune function. New evidence also links LEP profiles to major peripartum disorders, including subclinical ketosis, insulin resistance, postpartum ovarian inactivity, and uterine inflammatory diseases, and emphasises its potential as part of a panel evaluating the risk of metabolic and reproductive disorders. Furthermore, polymorphisms within the bovine LEP gene and its signalling network have been associated with milk production, feed efficiency, body condition, and fertility traits, suggesting opportunities to incorporate markers into genomic selection schemes aimed at improving robustness and reproductive performance. This review summarises current knowledge on LEP biology in cattle, with an emphasis on dairy cows, and discusses perspectives on translating this information into practical tools for nutritional management, health monitoring, and genetic improvement in bovine production systems. Full article

Selective dry cow therapy (SDCT) has emerged as a key strategy to reduce antimicrobial use in dairy production while maintaining udder health. This study aimed to evaluate the feasibility and impact of implementing SDCT in Romanian dairy farms by comparing low-risk cows treated with internal teat sealant only (ITS) at dry-off with low-risk cows treated with intramammary antibiotics at dry-off. A prospective field study was conducted on two commercial dairy herds, including 87 cows classified based on somatic cell count (SCC) and differential SCC (DSCC), and compared with a historical cohort of 37 cows. Udder health parameters, milk yield during the first 100 days in milk (DIM), antimicrobial use, and economic outcomes were evaluated. No significant differences were observed between groups in terms of postpartum intramammary infections, somatic cell score, DSCC, or clinical mastitis incidence. Milk yield during early lactation was also not affected by treatment. The ITS-only strategy resulted in a substantial reduction in antimicrobial use (−88.8% per cow) without significant differences in total economic costs. Farm-related differences highlighted the influence of management conditions on outcomes. These findings indicate that, in low-risk cows, SDCT using ITS alone is a safe and effective alternative to antibiotic treatment and support the feasibility of implementing SDCT under Romanian dairy production conditions as a sustainable strategy to promote the targeted and prudent use of antimicrobials while reducing unnecessary antibiotic exposure in dairy herds. However, given the limited number of herds and animals included, further studies are needed to confirm these promising findings under a broader range of production conditions. Full article

The risk of subacute ruminal acidosis (SARA) in grazing dairy cows remains uncertain, particularly when concentrates are supplemented. This study evaluated the effects of concentrate supplementation on the evolution of diurnal ruminal pH and its relationship with production, nutrient utilization, digestive indicators, and health status. Eight ruminal-fistulated multiparous Holstein–Friesian cows were assigned to a 2-period crossover design comparing a pasture-only diet (PO) and the same pasture supplemented with 6 kg/d of grain-based concentrate (PC). Each 28 d period included 21 d of adaptation and 7 d of measurements. Cows were fed freshly cut perennial ryegrass. Ruminal pH was recorded at 0, 2, 4, 6, 8, 10, 12, and 18 h relative to feeding. Concentrate supplementation slightly decreased minimum ruminal pH (5.97 vs. 6.15) but remained above the SARA threshold. Total volatile fatty acids (VFAs) increased, and acetate molar percentage decreased with supplementation. Total dry matter intake increased by 3.5 kg/d, increasing milk yield by 3.85 kg/d, and improving milk protein concentration, while milk fat and fatty acid profile, ruminal ammonium, and clinical indicators were unaffected. Ruminal pH was higher and VFA concentrations lower late in the season. Overall, concentrate supplementation was associated with improved productivity without compromising ruminal stability under the conditions of this study; however, responses were influenced by seasonal variation in pasture characteristics. Full article

The aim of this study was to characterize the coordinated dynamics of the mammary microbiome, antibiotic resistance genes (ARGs), and mobile genetic elements (MGEs) across the dry period, calving, and early lactation. The mammary microbiome undergoes substantial ecological changes across these stages, yet the coordinated dynamics of microbial composition, ARGs, and MGEs remain poorly understood. Here, shotgun metagenomic sequencing was performed on mammary secretion samples collected before dry-off (BM), immediately after calving (ACM), and one month postpartum (AM). The mammary microbiome exhibited a clear “exposure–bottleneck–reassembly” trajectory. BM was characterized by high microbial diversity and the enrichment of environmentally associated taxa, whereas ACM displayed a pronounced immunological bottleneck with markedly reduced microbial diversity and network complexity. During AM, microbial communities partially recovered but remained distinct from the BM state, indicating persistent ecological restructuring after calving. ARGs and MGEs showed parallel dynamics, with broad resistome and mobilome diversity in BM, a sharp contraction in ACM, and a selective re-expansion in AM. Network analysis further revealed maximal ecological complexity in BM, increased ARGs/MGEs connectivity in ACM, and partial stabilization in AM. These findings demonstrate that host physiological transitions, together with dry cow therapy (DCT), drive the coordinated remodeling of the mammary microbiome, resistome, and mobilome across the dry period. Full article

The objectives of this study were: (1) to identify factors influencing the performance of dairy cows in an automated milking system (AMS); (2) to construct a synthetic robotic adaptability index (RAI) of cows’ adaptation to the AMS; (3) to evaluate the predictive capabilities of traits describing the milking process and RAI; and (4) to compare the predictive power of different modeling approaches. The data on 796 primiparous Polish Holstein–Friesian cows (40,233 milkings) were obtained from the milking robot management system. Milking efficiency (ME), and the average number (AA) and time (AT) of the teat cup attachments and RAI served as predicted variables. Days in milk, and four AMS milking-related and 18 linear conformation traits were used as predictors. The highest predictive ability for ME was achieved with multilayer perceptron (R² = 0.895), followed by linear regression. For AA, AT, and RAI, the highest R² values were obtained for LASSO regression (0.663, 0.642 and 0.670, respectively). The key factors determining milking performance were functional variables, particularly milk flow rate (MilkFlow) and the number of failed milking attempts (Failure), while conformation traits had limited significance. More complex machine learning models do not always lead to improved prediction quality compared to statistical methods, which emphasizes the need for a critical approach to their application in the analysis of production data. Full article

Vaccinia virus strain Cantagalo (CTGV) causes a pustular disease in dairy cows and milkers in Brazil. Outbreaks in several states have been frequently reported, but the full genome sequence and genomic analysis of isolates from the Northeast region have never been described. Here, we report CTGV outbreaks in two Northeastern states, affecting milkers, lactating cows, and suckling calves. The farms were located in the main dairy belt of Pernambuco, in the Borborema Plateau, and in a rural region of Bahia. Of the 12 samples that tested positive for CTGV, five had their genomes fully sequenced. They cluster with CTGV isolates from Goiás (Midwest region, 2022) and São Paulo (Southeast region, 2023) but diverge from isolates from the Southeast in the early 2000s. Two clinical isolates have accumulated greater genetic variability and segregate separately from the other three isolates from the Northeast, showing evidence of potential recombination events with the FAI-01 isolate from the Midwest region (2022). We also detected Parapoxvirus and CTGV coinfection in some animals. These findings likely suggest different episodes of virus introduction in these states. The spread of CTGV raises concerns about the potential impact on local economic activities and underscores the importance of avoiding raw milk consumption. Full article

Sustainable cow–calf production requires balancing animal performance, economic returns, and environmental impacts under highly variable forage conditions. This study presents a conceptual model, CattleSat, whose decision-support framework integrates satellite-derived forage biomass with mechanistic ruminant nutrition models to simulate the effects of herd size and stocking strategies on animal performance, greenhouse gas emissions, and economic outcomes. A case study simulation using data from a Texas grazing system was conducted to demonstrate the application and behavior of the model under variable herd sizes. Results showed that increasing herd size reduced forage allowance, leading to decreased cow dry matter intake and, consequently, individual animal performance, particularly milk yield and weaning weight, while total calf production exhibited a curvilinear response. Economic outcomes followed similar patterns, with total net return increasing but net return per cow declining as herd size increased. Based on the assumptions and parameterization adopted in this simulation, a critical transition point was identified where system-level profitability and individual efficiency were balanced. Additionally, carbon emission intensity increased at higher stocking rates, indicating reduced environmental efficiency. Overall, forage dynamics were relevant drivers of system variability. These findings highlight the importance of adaptive, data-driven stocking strategies and demonstrate the potential of integrating remote sensing with mechanistic models to improve the sustainability of grazing systems. Future studies and model improvements should be incorporated to expand the applicability of the framework across diverse grazing systems. Full article

Background: The translocation of diet-derived antigens from the maternal intestine to breast milk represents a primary gateway for neonatal immune priming, yet the structural basis for why certain proteins survive this transit while others do not remains poorly understood. This review introduces the “Survivor Peptide” hypothesis, proposing that specific food allergens possess intrinsic “stability architectures” that enable them to resist maternal digestion and navigate the gut–mammary axis to reach the infant in an immunologically active form. Methods: We analyzed the current literature regarding the detection and structural characteristics of food allergens in human milk. Integrating evidence from 26 major sources, we performed an in silico structural analysis of five representative “survivor” proteins: Gal d 1 (egg white), Bos d 5 (cow’s milk), Gal d 6 (egg yolk), Tri a 19 (wheat), and tropomyosin (Der p 10-mite/shellfish). High-resolution 3D models were retrieved from the Protein Data Bank and AlphaFold2, and then visualized in UCSF ChimeraX to map stability anchors, including disulfide bonds and hydrophobic clusters, against solvent-accessible IgE-binding epitopes. Results: We identified and categorized allergens into distinct Molecular Resilience Architectures: the “Covalent Cage” (Gal d 1), defined by dense disulfide stapling, the “Glycoprotein Shield” (Gal d 6), utilizing yolk-matrix structural anchors, the “Topological Shield” (Bos d 5), characterized by a stable β-barrel, and “Coiled-Coil Rigidity” (Der p 10). These frameworks protect large, immunogenic fragments that maintain the spatial arrangement required for IgE cross-linking. Conclusions: Allergen persistence in the gut–mammary axis is dictated by a protein’s intrinsic structural architecture. Identifying these stability fingerprints provides a unified theory for allergen persistence and offers a path for refining component-resolved diagnostics and neonatal oral tolerance strategies. Full article

Understanding behavioral responses of dairy cows to thermal load under different milking-system environments is essential for welfare monitoring in subtropical production systems, yet field-based evidence remains limited. This study compared heat-related behavioral responses between an automated milking system (AMS) and a conventional parlor system under commercial subtropical conditions, with the hypothesis that cows in the AMS would exhibit more stable and less variable behavioral patterns under heat stress. Panting, feeding, and rumination were continuously monitored and analyzed at the barn level in relation to the temperature–humidity index (THI). The AMS barn showed lower panting duration and reduced day-to-day variability, whereas the traditional barn exhibited higher panting levels and greater short-term fluctuations. Panting increased consistently with THI, showing a clear temporal trend (β ≈ 0.65 min/day), and emerged as the most sensitive indicator of thermal load, while feeding and rumination showed weaker responses. During heatwaves, panting increased markedly in both systems, with limited changes in feeding and rumination. Multivariate analyses (PCA) showed more compact clustering in the AMS barn, with higher variance explained along the first principal component (PC1 ≈ 44%), compared to greater dispersion in the traditional barn. These findings demonstrate that cows managed in the AMS exhibited more stable and less variable behavioral patterns under heat stress, whereas cows in the conventional parlor system showed higher panting levels and greater short-term fluctuations. These system-level differences directly address the study objective and support panting as a practical indicator for heat-stress monitoring in subtropical dairy systems. Full article