Search Results (4,116)

Milk color reflects the optical output of a complex colloidal system governed by protein micelles, fat globules, and serum phase interactions. In this study, we evaluated whether CIE Lab* color parameters can explain variation in milk composition and somatic cell count (SCC) using Lasso-based multiple linear regression and Extreme Gradient Boosting (XGBoost). A total of 119 Holstein milk samples were analyzed for fat, protein, lactose, dry matter, electrical conductivity, freezing point, and SCC, and five color indices (L*, a*, b*, Hue, and Chroma) were used as predictors. Model robustness was evaluated using 10-fold cross-validation and an independent 80/20 train–test split. In regression analyses, Lasso explained 32.7% of protein variation (R² = 0.327), 26.3% of dry matter (R² = 0.263), 22.8% of lactose (R² = 0.228), and 19.1% of fat (R² = 0.191). Spectral tone parameters (a*, Hue, and Chroma) were consistently retained as key predictors, whereas L* showed a limited contribution. SCC exhibited weak direct associations with color traits but was significantly related to electrical conductivity (p < 0.05), indicating inflammation-driven ionic changes rather than pigment effects. In classification analysis (SCC ≥ 200,000 cells/mL), the XGBoost model achieved 74% accuracy and an AUC of 0.69 in the independent test set, with Chroma and electrical conductivity identified as the most influential features. These findings suggest that, among the evaluated color variables, Chroma provided the most relevant information for discriminating SCC status, whereas the overall contribution of milk color traits to compositional prediction remained moderate. Therefore, color-derived measurements should be interpreted as instrument-based optical indicators that may complement, but not replace, conventional milk quality assessments. Full article

The expansion of digital technologies in dairy farming (precision dairy farming) has created new opportunities for the systematic use of data, which can lead to more efficient production processes. This study aimed to develop and evaluate models for predicting daily milk yield from dairy cows during summer. This yield was modeled at the individual level, with days in milk and parity group included as baseline covariates in all analyses. Three feature-set scenarios were defined and evaluated, in which the temperature–humidity index (THI) and milk yield history were added to the baseline variables either separately (Scenarios 1 and 2) or jointly (Scenario 3). Performance was evaluated using walk-forward validation, and feature selection was nested within each iteration’s training window. The performance of the linear mixed model (LMM) was then compared with two machine learning models, random forest (RF) and gradient boosting machine (GBM), within the same experimental framework. In Scenario 3, all three models showed similar fits (R² = 0.92 and concordance correlation coefficient = 0.96), although the GBM model yielded a smaller error (root mean square error [RMSE] = 2.07 ± 0.22, mean absolute error [MAE] = 1.39 ± 0.12) than the RF model (RMSE = 2.10 ± 0.23, MAE = 1.45 ± 0.13) and the LMM (RMSE = 2.15 ± 0.22, MAE = 1.41 ± 0.10). Overall, adding the THI and recent milk yield history to the baseline variables improved short-term prediction accuracy in this dataset, with the GBM model showing the smallest error. These results can support farmers and herd managers in predicting short-term milk yield under heat stress conditions and making timely management decisions. Full article

Antimicrobial resistance (AMR) is increasingly becoming a major global public health concern, as antibiotics are losing their effectiveness at an alarming rate due to drug resistance. The ß-lactam group of antibiotics are widely used in dairy farms to treat animal infections, and their presence in the food chain is a significant concern. Addressing this issue requires the development of effective analytical tools for the rapid detection of antibiotics. In this work, a miniaturized Biosensor-on-Pillar platform was developed for detecting ß-lactam antibiotics in milk, which operates in a rapid, cost-effective, and user-friendly format, making it particularly suitable for resource-limited settings. The platform employs an enzyme induction-based approach, wherein Bacillus cereus spores germinate in the presence of β-lactam antibiotics, leading to the production of β-lactamase enzyme, which is then recognized using a chromogenic substrate functionalized on paper associated with the pillar platform. The developed biosensor can detect 12 β-lactam antibiotics with limits of detection (LODs) ranging from 1 to 1000 ppb, achieving sensitivity at or below the maximum residue limits (MRLs) set by regulatory bodies (FSSAI/CODEX) for the majority of the tested antibiotics. The performance of the platform, including the design, fabrication, and working principle, was further evaluated by analyzing six blind milk samples, yielding significant results compared to the commercially available AOAC-approved gold-standard method. Hence, the developed biosensor demonstrates promising potential for the rapid, cost-effective and high-throughput screening of milk samples for β-lactam antibiotics, benefiting the dairy industry and ensuring food safety. Full article

Streptococcus agalactiae, also known as Group B Streptococcus (GBS), is a major pathogen responsible for mastitis in dairy cows. It causes persistent and difficult-to-treat mammary infections, leading to reduced milk production. Baicalein, a flavonoid compound, exhibits anticancer, anti-inflammatory, and antibacterial activities; however, its specific mechanism of action against GBS remains unclear. This study aimed to investigate the mechanism by which baicalein inhibits GBS invasion of bovine mammary epithelial cells (bMECs). The results showed that baicalein at concentrations of 4 μg/mL or higher effectively inhibited 50% of the invasion of bMECs by GBS strain HB31 and exerted a concentration-dependent inhibitory effect on bacterial adhesion. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of baicalein against HB31 were both greater than 1024 μg/mL. Therefore, the antibacterial effect of baicalein alone may not fully account for its mechanism; other pathways likely contribute to the reduced invasiveness of GBS. To elucidate the mechanism by which baicalein inhibits GBS invasiveness, this study investigated both bacterial metabolism and gene expression. Metabolomic analysis revealed that baicalein treatment led to the downregulation of amino acid metabolites, including alanine and aspartic acid, as well as nucleotide metabolites such as adenine and UMP in GBS HB31. Additionally, the NADH/NAD⁺ ratio increased while ATP levels decreased, indicating that the overall metabolic activity of GBS was suppressed. Transcriptomic analysis focused on changes in invasion-associated virulence genes. The results showed that the expression of pbsP, an invasion-associated virulence gene, was significantly reduced, while the expression of hylB and cfb showed downward trends that did not reach statistical significance. In contrast, the expression of cylE and the two-component system vicKR was upregulated. The upregulation of cylE may be related to baicalein-induced oxidative stress in HB31. Furthermore, HB31 suppressed Nrf2-HO-1 mRNA expression, whereas baicalein activated the Nrf2 signaling pathway and reduced HB31-induced IL-6 and NF-κBmRNA expression. These findings provide new insights for the development of anti-virulence therapeutic strategies targeting GBS. Full article

This study investigated how Pb, Cd, and Cu are distributed between curd and whey during milk coagulation in milk from different animal species, and how the level of metal addition and the coagulation method influence metal retention. Raw milk from buffalo, cow, donkey, goat, and sheep was supplemented with Pb, Cd, and Cu under controlled laboratory conditions at two levels corresponding to the regulatory maximum level (ML) and ten times this level (10 × ML). All three metals were added simultaneously to the same milk aliquot, and coagulation was induced either enzymatically or by acidification at pH 4.6. Metal concentrations in curd and whey were determined by atomic absorption spectrophotometry. In all milk types, Pb, Cd, and Cu were retained mainly in the curd fraction. At ML, curd retention generally ranged from about 77% to 97%, whereas at 10 × ML, retention decreased and transfer to whey increased. Donkey milk consistently showed lower metal retention in curd than ruminant milk. Statistical analysis of curd retention showed that metal type, milk species, the level of metal addition, and their interactions significantly influenced metal retention, indicating that the effect of coagulation method depended on the experimental conditions rather than being uniform across all cases. Overall, the results show that milk coagulation favours the association of Pb, Cd, and Cu with the curd fraction, highlighting the importance of the milk protein phase in determining metal distribution during dairy processing. These findings improve our understanding of heavy-metal behaviour during milk processing and help clarify their potential transfer into curd-based dairy products. Full article

Modeling milk yield in dairy cows is essential for improving management decisions, but traditional lactation curve models often fail to capture individual variability. Machine learning approaches offer greater flexibility; however, their performance in small, within-herd datasets and their reliance on explicit cow identification remain unclear, particularly in grazing systems. This study aimed to evaluate whether routinely measured biological traits can substitute for cow identification in machine learning models for predicting daily milk yield within a herd under limited data conditions. The dataset comprised 62 lactations from 48 Holstein–Friesian cows in a grazing system. Two machine learning models were developed: one including cow identification (With ID) and another excluding cow identification but incorporating milk quality traits, body weight, and body condition score (Without ID). Both models were compared with the Wood lactation model fitted to individual cows. The With ID and Without ID models achieved $R^2$ values of 0.97 and 0.93 and RMSE values of 1.2 and 1.6 ${\mathrm{kg} \mathrm{d}}^{-1}$, respectively. Both machine learning models outperformed the Wood model fitted individually to each cow ($R^2$ < 0.90; RMSE > 2.03 ${\mathrm{kg} \mathrm{d}}^{-1}$), which represents an implicitly cow-specific approach. The model including cow identification therefore served as a machine learning analogue to this benchmark. Importantly, the trait-based model closely matched the performance of the cow-specific model. These results demonstrate that machine learning models based on routinely measured traits provide a practical approach for predicting within-herd milk yield from small datasets, while retaining much of the accuracy of cow-specific models. Full article

Milk production in tropical smallholder systems is constrained by limited high-quality roughage during the hot–dry season. Sweet sorghum silage is drought-tolerant and may replace corn stover silage. Twelve Holstein–Friesian crossbred cows were assigned to the same commercial concentrate plus either corn stover silage or sweet sorghum silage as the primary roughage source (n = 6 per diet). Intake, apparent digestibility, milk yield and composition, and feed-use efficiency were evaluated on day 15 and 30 and analyzed using linear mixed-effects models with cow as a random effect. Compared with corn stover silage, sweet sorghum silage increased dry matter intake (p < 0.05) and improved the digestibility of fibre fractions, including crude fibre, NDF and ADF (p ≤ 0.003), while crude protein- and nitrogen-free extract digestibility were not different (p > 0.05). Milk yield, 4% fat-corrected milk, energy-corrected milk, and feed-use efficiency indices were unaffected by silage source (p > 0.05). Milk protein concentration was higher with sweet sorghum silage (treatment effect p < 0.05), whereas milk fat and lactose were unchanged. Sweet sorghum silage can therefore replace corn stover silage in tropical dairy diets, improving intake and fibre utilization without compromising milk output. Full article

Raw milk dairy products, an integral part of Italian food heritage, are the primary products of small-scale farms in mountain regions where pasture is seasonal. While raw milk dairy products offer potential health benefits, their physicochemical properties make them susceptible to foodborne pathogens. Long-term surveillance of these products is essential to safeguard consumer health. Here, we present a fourteen-year microbiological surveillance of raw milk dairy products and intermediate matrices from northeastern Italy’s alpine areas, analyzing coagulase-positive Staphylococci (CPS), β-glucuronidase-positive Escherichia coli, Listeria monocytogenes, and Shiga toxin-producing E. coli (STEC). The most frequently detected pathogens were CPS and β-glucuronidase-positive E. coli, with up to 19.6% and 51.7% of samples exceeding regulatory limits, respectively. Butter, curd, and fresh cream were the most contaminated matrices. Detection rates of staphylococcal enterotoxins, L. monocytogenes, and STEC aligned with European detection averages (6.7%, 2.6%, and 2.1%, respectively). These findings underscore the necessity of Good Hygiene and Management Practices, together with regular microbiological monitoring to mitigate contamination risks, supporting the safety and quality of traditional raw milk dairy products in alpine regions. Full article

Milk production in dairy herds is determined by both intrinsic and extrinsic factors, with reproductive efficiency serving as a primary determinant. Infectious, nutritional, and management-related challenges can reduce this efficiency. Following parturition, cows are more susceptible to clinical disorders due to a temporary loss of integrity in the cervix, vagina, and vulva, which allows environmental bacteria to ascend and alter the vaginal microbiota. These microbial changes may disrupt endocrine responses related to conception and contribute to repeat breeder cow syndrome (RBCS), which is defined as failure to conceive after three or more inseminations. This study investigated associations among cultivable vaginal bacteria, circulating progesterone and glucose concentrations, and reproductive performance in 30 fourth-parity Holstein cows with a body condition score of 3.5. Cows were classified by reproductive history as repeat breeders (RBCS; n = 14) or controls (CTL; n = 16). Vaginal mucosal samples were collected at insemination and cultured on blood agar and MacConkey media under aerobic and microaerobic conditions. Bacterial identification was conducted using Gram staining and standard biochemical assays. Blood samples were collected at insemination, on day 5 post-insemination, and every two days thereafter to measure progesterone and glucose concentrations. Fertility outcomes were analyzed using PROC GLIMMIX, and hormonal data were analyzed using mixed models with repeated measures. The bacterial genera identified included Bacillus, Escherichia coli, Staphylococcus, Klebsiella, Proteus, Streptococcus, and Actinomyces. Progesterone and glucose concentrations did not differ significantly between groups (p > 0.05). However, the fertility rate (p < 0.05; CTL:87.50% vs. RBCS:57.14%) and number of attempts to conceive (p < 0.001; CTL:2.5 vs. RBCS:6.7) differed statistically between treatments. A higher prevalence of S. hyicus was detected in RBCS cows, and E. coli, S. hyicus, and Proteus spp. were more frequently detected in non-pregnant cows. These findings suggest that the identified cultivable vaginal bacteria are associated with reproductive status in dairy cows. Full article

Background: Lumpy skin disease (LSD) is caused by a Capripoxvirus. Live attenuated vaccines, which are commercially available, could be not safe because of the side effects. The aim of this study was the evaluation of the safety, immunogenicity, and effects on the qualitative and quantitative parameters of milk. The feasibility of identifying vaccinated animals using our inactivated vaccine in dairy cows was analysed. The vaccine was tested in guinea pigs as an immunogenicity predictive model. Methods: LSD virus was propagated on Madin–Darby Bovine Kidney (MDBK) cells, then inactivated and supplemented with keyhole limpet hemocyanin (KLH) protein, obtaining a positive marker vaccine. This was inoculated in guinea pigs and in dairy cows, and animal sera were analysed using enzyme-linked immunosorbent assay (ELISA) and a serum neutralisation (SN) test. Quantitative and qualitative analyses were performed on milk. Results: The vaccine was previously tested for efficacy in vaccinated calves, showing a pronounced reduction in clinical symptoms after challenge. The safety and immunogenicity obtained in calves were also confirmed in dairy cows in this study. In fact, high values of the SN test (1:20 to 1:80) and ELISA (90 and 240 S/P%) were obtained after vaccination. Moreover, high immunogenicity of the vaccine was also assessed in guinea pigs. In addition, the results of the milk analyses did not show any differences between vaccinated and control groups. The KLH was able to elicit an immune response detectable using an ELISA (3.0 and 3.5 optical density values). Finally, our vaccine could be used to reduce LSD symptoms and identify vaccinated animals. Full article

This study investigates the antioxidant properties of several synthetic peptides derived from milk proteins previously identified in milk permeate, a by-product of the dairy industry. The aim of the research is to identify which peptides present in milk permeate are responsible for its antioxidant activity. A comprehensive experimental strategy was employed to evaluate their antioxidant potential, including in silico selection, in vitro free radical scavenging assays and cellular models using Caco-2 and HCT116 cell lines. The peptides were screened using a molecular docking approach for their potential interaction with the Kelch-like ECH-associated protein 1/nuclear factor erythroid 2-related factor 2 (Keap1/Nrf2) pathway, and eight out of twenty-eight were selected and synthesized for further analyses. In vitro, six of the selected peptides demonstrated significant direct antioxidant activity in the DPPH scavenging assay, and two in the ABTS scavenging test. In cellular environments, three peptides (LPAPELGPRQA, LPIIQKLEPQI and NGQVWEESLKRL) effectively protect cells from oxidative stress induced by tert-butyl hydroperoxide, reducing reactive oxygen species production and partially mitigating lipid peroxidation. Further investigation showed that two of them (LPAPELGPRQA and LPIIQKLEPQI) effectively induce the Keap1/Nrf2 pathway, as evidenced by a ∼1.5-fold increase in Nrf2 levels and overexpression of downstream proteins. Permeability studies revealed that these peptides can cross the intestinal monolayer (2–3% in 2 h), suggesting potential systemic effects. Overall, these findings highlight the multifunctional antioxidant properties of the investigated peptides and support their potential application as nutraceuticals or therapeutic agents for oxidative stress-related conditions. Full article

Foot-and-mouth disease (FMD) poses a significant threat to the United States dairy industry. This study evaluates the effectiveness of regional zoning, enhanced detection, and biosecurity in controlling FMD spread, focusing on the New England milkshed, using the InterSpread Plus (ISP+) model. We adapted a baseline ISP+ configuration incorporating United States dairy farm data, movement networks, cattle dealers, markets, and slaughterhouses, with milk processing plants as a model addition. Four hypotheses were tested to understand the impact of different biosecurity strategies: (H1) regional zoning limits the interregional spread of FMD post-detection; (H2) earlier detection in New England via increased passive surveillance reduces the overall outbreak impact; (H3) reduced indirect transmission through enhanced biosecurity measures improves FMD outbreak control; (H4) the combination of regional zoning and earlier detection provides synergistic reduction in FMD impact beyond either strategy alone. The four hypotheses were tested using three geographically distinct infection seed sets; 100 iterations of each scenario were simulated over 210 days and compared to the baseline. Key impact metrics included the daily number of infected premises, the outbreak duration, and the total number of infected premises across the outbreak scenarios. Results suggest shorter outbreak durations and reduced total infected premises under the hypothesized scenarios, compared to the baseline scenario. Kruskal–Wallis H tests confirmed significant differences across the baseline, regional zoning, early detection, enhanced biosecurity, and the combination of heightened passive surveillance with regional zoning scenarios in terms of total infected premises. Post hoc Dunn’s tests indicated that enhanced biosecurity outperformed other control strategies tested. These findings demonstrate that layered interventions may substantially curtail both the national amplification and local spread of FMD, and thus protect the consumer milk supply and reduce cascading economic shocks from an outbreak. Full article

This experiment aimed to evaluate physiological and behavioral responses of crossbred Dehong dairy buffaloes to heat stress (HS) in comparison with those in a thermoneutral (TN) environment. Twelve crossbred dairy buffaloes at similar lactation stages were randomly allocated to two groups of six animals each. Six buffaloes were exposed to HS conditions and the other six to TN conditions in an open loose-housing barn without individual stalls. Respiration rates were manually recorded at 08:00 h, 13:00 h, and 18:00 h. Duration and frequency of behaviors (standing, lying, feeding, and drinking) were continuously monitored using digital cameras for 20 consecutive days. Compared with the TN group, HS-exposed buffaloes exhibited markedly higher respiration rates (p < 0.001) and feeding frequencies (p < 0.05), but significantly shorter feeding duration throughout the observation period (p < 0.05). No significant differences were observed in the time spent standing, lying, or drinking between the two groups (p ≥ 0.05). Under HS conditions, buffaloes preferred a vertical lying posture to reduce exposure to intense solar radiation. These results suggest that crossbred Dehong dairy buffaloes can adapt to heat stress by modulating their physiological and behavioral strategies. The observed changes in physiological indices and behavioral patterns provide fundamental data for further elucidating the heat stress adaptation mechanisms in dairy buffaloes. Full article

A robust analysis of water use in major food production systems is crucial for improving their productivity and sustainability in water-scarce arid and semi-arid regions like Punjab (India) facing the depletion of groundwater resources. This study aimed to assess blue water use and blue water productivity in dairy farming systems across different farm sizes in Punjab. Comprehensive monitoring and assessment of water use over a full year (from July 2022 to June 2023) was conducted on 24 dairy farm sheds in Punjab, revealing significant variability in their blue water use (measured in L per adult animal per day) and blue water productivity quantified as kg of fat- and protein-corrected milk (FPCM) produced per m³ of the blue water consumed. The variability was influenced by factors such as livestock species, farm size (medium with 15–25 livestock, large with 25–100 livestock, and commercial with >100 livestock), bathing and servicing routines, and energy use patterns. The average dairy livestock total blue water consumption varied from 112 ± 14 to 131 ± 19 L per adult animal per day, with 20–40% higher livestock drinking water and about six times higher livestock bathing and serving water used during the summer months. Interestingly, a large share (45%) of the average total blue water consumption is contributed by indirect water consumption via the use of energy (electricity and diesel) in dairy farm sheds. Dairy milk blue water productivity was quantified higher, ranging from 154 ± 11 to 225 ± 59 kg FPCM per m³ in buffalo- and crossbred cattle-based dairy farm sheds. However, indigenous cattle showed a lower blue water productivity ranging from 56 to 97 kg FPCM per m³, reflecting their lower milk yields and limited use of intensified management practices. The state-level water scarcity footprint (WSF) of Punjab dairy farm sheds was quantified at 4870 million m³ world-eq, which showed a significant spatial variation among Punjab districts. However, the results of this study offer novel seasonally and spatially disaggregated benchmarks of blue water consumption, blue water productivity, and the water scarcity footprint of Punjab’s dairy farming sheds. This new information is crucial for the development of locally calibrated and validated models for improving the water productivity and sustainability of dairy farming across Punjab and other similar arid and semi-arid regions in Southeast Asian countries. Full article

Rumen microbial fermentation plays a central role in nutrient utilization and milk production in dairy cows. This study evaluated the effects of supplementation with exogenous fibrolytic enzymes, alone or in combination with live yeast on rumen microbiota, fermentation characteristics, nitrogen-related metabolites, and production performance during the transition from outdoor grazing to indoor housing. Thirty Lithuanian Red dairy cows were assigned to control (CTR), enzyme (E), or enzyme plus yeast (YE) treatments across outdoor (OD) and transit (T) periods, while nine cows (three per group) were selected for rumen and microbiota analysis. Rumen bacterial communities were characterized using 16S rRNA gene sequencing, and functional parameters were evaluated using linear mixed-effects models. Supplementation resulted in selective changes in several bacterial genera, including Blautia spp., WPS-2, Ruminococcus spp., Erysipelotrichaceae UCG-009, Sharpea spp., uncultured Bacteroidales, and Prevotellaceae UCG-003, and was associated with alterations in fermentation patterns, particularly propionate concentration, and in nitrogen metabolism, including putrescine dynamics. The transition period significantly influenced microbial diversity and total bacterial abundance across treatments. Cows in the YE group maintained higher milk yield during the transition period. Overall, dietary supplementation modulated specific rumen metabolic responses and contributed to production stability without causing large-scale changes in overall microbial structure. Full article