Search Results (137)

Camel milk (CM), which is produced by both Camelus dromedarius and Camelus bactrianus, is gaining increasing popularity as a value-added functional dairy product, but the science of managing its shelf life has progressed more slowly than its commercial expansion. Unlike bovine milk, CM lacks β-lactoglobulin (β-LG), has a unique casein (CN) micelle structure with a high β-CN-to-αs1-CN ratio, and low κ-CN protein content, and contains an unusually rich bioactive protein fraction including lactoferrin (LF), immunoglobulin G (IgG), lysozyme (LZ), and peptidoglycan recognition protein (PGRP). These compositional characteristics imbue CM with both significant inherent antimicrobial benefits and place it at risk of processing weaknesses that do not have direct analogs in bovine dairy science. The review discusses three key areas of CM shelf life science that have not been sufficiently addressed in the published literature. The first relates to physicochemical mechanisms of deterioration, including lipid oxidation of polyunsaturated fatty acids (PUFA), destabilization of CN micelles in the structural absence of β-LG, and Maillard browning during thermal treatment and storage of powder. The second addresses the fate of bioactive proteins, with the majority being lactoferrin (LF), immunoglobulin G (Igs), and heavy chain-only antibodies (HCAbs), under both thermal and non-thermal processing conditions. The third looks at new non-thermal preservation methods, such as high-pressure processing (HPP), pulsed electric field (PEF), ultrasonication, ultraviolet irradiation, cold plasma, and electromagnetic (EM) field treatment, and functional packaging innovations, which contribute to longer shelf life. Of the non-thermal options examined, HPP at 200–400 MPa today provides the most mechanistically proven evidence for camel-specific microbial deactivation with satisfactory quality preservation. The latest primary CM research also indicates that processing with EMs in the 850 mT range can potentially be as effective as conventional pasteurization in microbial control and may be more effective than pasteurization in retaining desirable bioactive markers, although this result needs to be independently replicated before more responsible conclusions can be drawn. The review ends with four priority research gaps: standardized kinetic shelf life modeling frameworks, systematic characterization of bioactive protein stability under commercial processing conditions, life cycle assessment of preservation chains across the camel dairy supply continuum, and the urgent validation of camel-specific pasteurization adequacy indicators to replace bovine alkaline phosphatase, which remains active in CM after conventional high-temperature short-time (HTST) pasteurization. Full article

Mastitis remains the most economically damaging disease in the global dairy industry, and conventional genetic selection based on somatic cell score (SCS) has produced only limited gains in resistance. Epigenetic mechanisms—mitotically heritable yet environmentally responsive and largely reversible modifications that regulate gene expression without altering the DNA sequence—are now emerging as a complementary layer of biological information that can sharpen the prediction of disease susceptibility. This review summarizes current evidence on three classes of epigenetic markers associated with bovine mastitis resistance: DNA methylation, non-coding RNAs (with emphasis on microRNAs, long non-coding RNAs, circular RNAs, and small nucleolar RNAs), and histone modifications, alongside the increasingly important epitranscriptomic layer of N6-methyladenosine (m6A) RNA modification. Particular attention is given to differentially methylated regions and discriminant methylation haplotype blocks in immune-related genes, circulating and milk-derived non-coding RNA biomarkers, m6A-mediated regulation of inflammatory transcripts, and histone-mark dynamics in mammary epithelial cells challenged with Staphylococcus aureus and Escherichia coli. We conclude with current limitations and perspectives on translating these markers into selection tools and therapeutic targets. Across all marker classes, current evidence remains constrained by small cohort sizes, breed-specific study designs, a scarcity of longitudinal and multi-generational data, and limited functional validation, so most candidate markers are still at the discovery stage and require cautious interpretation before deployment. Full article

Bovine mastitis, a prevalent and economically detrimental inflammatory disease in dairy cattle, leads to substantial economic losses due to reduced milk yield, impaired milk quality, and increased veterinary costs. Infrared thermography (IRT) provides an efficient, non-invasive approach for early mastitis detection by leveraging computer vision to analyze temperature differences between ocular and udder regions. However, in practical farm environments, arbitrary head movements, particularly horizontal rotation, alter sensor-to-object distance, introducing systematic biases in thermal measurements and degrading diagnostic reliability. To address this limitation, a two-stage detection framework is proposed under a lateral infrared imaging configuration, in which the camera is positioned perpendicular to the walking direction of cows. First, a posture classification module based on pose estimation is employed to identify cows with consistent lateral orientation and minimal head rotation, thereby maintaining stable sensor-to-object distance between the ocular and udder regions. Second, instance segmentation is applied to posture-constrained thermal images to achieve accurate regional temperature extraction and quantitative analysis. In addition, an improved YOLO26 model integrated with a Deformable Attention Transformer (DAT-YOLO26) is developed to enhance feature representation capability and detection performance under variable imaging conditions. On an independent 40-cow blind diagnostic cohort (20 healthy, 20 mastitis-positive), the proposed method achieved an accuracy of 87.5%, an F1-score of 87.18%, a sensitivity of 85%, and a specificity of 90%. These results, while constrained by the size of the test cohort, suggest that enforcing posture consistency improves IRT-based diagnostic performance under the present acquisition conditions. We emphasize, however, that these findings are based on a single-farm, single-season pilot cohort of 40 cows; multi-farm and multi-season validation are required before broader deployment claims can be made. Full article

Bovine mastitis caused by Streptococcus uberis (S. uberis) remains a major challenge of dairy production system worldwide. This study aimed to develop a colorimetric loop-mediated isothermal amplification (LAMP) assay and a conventional PCR assay targeting the 16S rRNA gene for detection of S. uberis in bovine milk. Both assays were evaluated with a simplified HotSHOT (HS) DNA preparation method that can be completed in under 10 min and was compared with a commercial DNA extraction kit before LAMP and PCR testing. LAMP reactions using HS-extracted DNA required an extended incubation time of 30 min, compared with the standard 60 min, to account for the crude DNA preparation. Using tenfold serial dilutions of purified DNA in nuclease-free water, the limit of detection was 1.84 × 10⁻⁴ ng/µL for LAMP and 1.84 × 10⁻⁵ ng/µL for PCR. In pasteurised milk spiked with S. uberis DNA and extracted by HS, the limit of detection was 10 ng/mL for LAMP and 1 ng/mL for PCR. Using the commercial kit, both methods achieved 1 ng/mL. Among 17 culture-confirmed clinical milk samples extracted by HS, LAMP detected S. uberis in 14 samples (82.35%; 95% CI: 0.56 to 0.96), while PCR detected 15 samples (88.24%; 95% CI: 0.64 to 0.99), with no significant difference between methods (McNemar’s test, p > 0.05). Both LAMP and PCR showed 100% analytical specificity against 10 non-target bacterial species under the conditions tested. These findings support HS combined with colorimetric LAMP as a practical diagnostic workflow that warrants further validation under field conditions. Full article

Bovine milk represents a highly complex colloidal system whose physicochemical stability depends on the organization of milk fat globules, casein micelles, membrane-associated phospholipids, and somatic cellular components. Mechanical separation procedures such as centrifugation induce redistribution of dispersed colloidal fractions and structural perturbations within the milk matrix, potentially enabling fraudulent reduction of somatic cell count while preserving bulk compositional parameters. In the present study, we investigated whether advanced deep learning architectures could identify centrifugation-associated structural alterations in bovine milk using microscopy image representations. A total of 16,472 microscopy images obtained from centrifuged and non-centrifuged milk samples were analyzed using Swin Transformer V2 and ConvNeXt-Base architectures. Both models successfully detected centrifugation-associated structural perturbations and substantially outperformed the previously analyzed InceptionC baseline. ConvNeXt-Base achieved 87.30% classification accuracy together with 86.85% balanced accuracy and 86.59% harmonic average of recalls following totalogit aggregation. Importantly, Swin Transformer V2 demonstrated strong monotonic relationships between logit metrics and centrifugation ratio (r = 0.640–0.651, p < 0.01), indicating sensitivity to progressive image-level changes associated with increasing centrifugation ratio. Collectively, the obtained findings demonstrate that microscopy-derived deep learning representations capture structural information associated with centrifugation-induced changes in bovine milk, supporting the applicability of AI-assisted microscopy for detecting processing-related alterations in complex dairy systems. Full article

Mastitis remains the most economically damaging disease of dairy production, and recent molecular work has converged on the NLRP3 inflammasome as a key integrative node of its pathogenesis. This narrative review integrates evidence published largely between 2015 and 2026 to show how diverse triggers—Staphylococcus aureus and Escherichia coli, lipopolysaccharide (LPS) and lipoteichoic acid (LTA), non-esterified fatty acids (NEFA), heat stress, environmental xenobiotics including nanoplastics, and microbiota-derived signals—may funnel into a common NLRP3–ASC–caspase-1–GSDMD axis that drives pyroptosis, blood–milk barrier disruption, and clinical disease. The review examines the potential obligatory role of reactive oxygen species (ROS), mitochondrial dysfunction, and selenoprotein-mediated redox control in licensing inflammasome assembly. It further evaluates the emerging gut–mammary and rumen–mammary axes that operate upstream of local epithelial activation. We survey a structurally diverse therapeutic landscape encompassing dietary selenium, probiotics, microbial metabolites, plant-derived nanovesicles, polyphenols, ginsenosides, and small-molecule NLRP3 antagonists, identifying recurring mechanistic motifs that suggest combinatorial regimens may yield additive benefit. Importantly, much of the evidence derives from in vitro and murine models, and we highlight the translational gaps that must be bridged before clinical application in dairy cattle. Finally, we map outstanding research gaps and propose priorities for translational work aimed at sustainable, antibiotic-sparing management of bovine mastitis. Full article

Streptococcus agalactiae is a major contagious pathogen of bovine mastitis and causes substantial economic losses in the dairy industry. In this study, a dual-readout RPA-PfAgo detection platform targeting the conserved cfb gene of S. agalactiae was established and optimized. Seven pairs of RPA primers were designed and screened to construct the Basic-RPA assay, and six guide DNAs (gDNAs) together with a specific probe were evaluated for PfAgo-assisted detection. Field validation was performed using 153 bovine milk samples collected from five dairy-farming regions in China, and assay performance was compared with bacteriological culture and a standardized quantitative PCR (qPCR) assay. The Basic-RPA assay achieved optimal amplification at 37 °C for 30 min, with a detection limit of 1 × 10⁻³ ng/µL and no cross-reactivity with non-target bacteria. The optimized RPA-PfAgo-RTF assay detected as few as 10 copies/µL, whereas the RPA-PfAgo-LFD assay detected 100 copies/µL, and both formats showed high analytical specificity. In field milk samples, bacteriological culture detected 21 positive samples, whereas standardized real-time PCR (qPCR), RPA-PfAgo-RTF, and RPA-PfAgo-LFD each detected 33 positive samples. When compared with bacteriological culture as a conventional comparator, all three molecular assays showed 100.00% positive agreement, 90.91% negative agreement, and a Kappa value of 0.733. In addition, RPA-PfAgo-RTF and RPA-PfAgo-LFD were completely concordant with the standardized qPCR assay across all 153 samples. These results indicate that the dual-readout RPA-PfAgo platform is a rapid and reliable molecular tool for detection of S. agalactiae in bovine milk. Full article

The INFOGEST protocol is a standardised in vitro digestion model widely utilised to evaluate the digestibility and bioaccessibility of nutrients in diverse food matrices. This review focuses on its application since 2020 (after the publication of the INFOGEST 2.0 model) to milk and dairy products, which often serve as a suitable food matrix in digestion studies. By analysing 50 studies selected using a semi-automated method, this review highlights its strong performance in reproducing general digestive trends, including peptide fingerprint profiling, consistent high-protein digestibility, and matrix-dependent lipid and mineral bioaccessibility. The model is particularly effective in evaluating structural modifications of dairy products and their impact on digestive behaviour. However, its application remains skewed toward bovine systems, limiting broader relevance to other dairy matrices. Methodological variability, including protocol modifications and emerging semi-dynamic adaptations, poses challenges to reproducibility. Furthermore, reliance on simplified downstream models constrains the physiological interpretation of bioactivity and nutrient absorption. Future progress requires harmonised dynamic extensions, expanded use of advanced biological systems, and inclusion of diverse dairy matrices. Collectively, these advances will support a shift from descriptive bioaccessibility toward more predictive assessments of nutrient bioavailability. This six-year, non-topic-dependent bibliometric analysis contextualises the expanding adoption of INFOGEST 2.0 as reflected in its versatility and evolving scope, positioning it as a cornerstone tool for advancing our understanding of dairy nutrition, digestion-derived bioactivity, and ultimately, the relationship between dairy consumption and human health. Full article

Antimicrobial resistance in bovine mastitis pathogens poses interconnected threats to dairy productivity and public health; however, longitudinal evidence on the association between veterinary oversight and lower resistance to critically important antimicrobials in tropical smallholder systems remains limited. This study analyzed 1347 quarter milk samples from 47 dairy farms in Saraburi Province, Thailand, submitted consecutively over five years (2020–2025), to evaluate whether participation in a veterinary-led herd health (HH) program was independently associated with reduced vancomycin resistance and multidrug resistance (MDR). Bacterial identification was conducted using standard methods, and susceptibility was determined using the Kirby–Bauer disk diffusion method. Among 1069 culture-positive samples, Streptococcus spp. (25.3%) and coagulase-negative staphylococci (16.8%) predominated. Vancomycin resistance declined from 15.9% to 5.4% between early (2020–2022) and recent (2023–2025) periods. Of the 686 isolates tested against ≥3 antibiotic classes, 61 (8.9%) were MDR; vancomycin resistance co-occurred in 34.4% of these samples. Repeated logistic regression identified non-HH farm status (OR = 4.035; p = 0.027) and early-year groups (OR = 4.611; p = 0.002) as independent risk factors for vancomycin resistance. As HH participation and year group showed a significant interaction, their joint effect for MDR was modeled: compared with non-HH farms in the early period (reference), all other combinations—including HH farms in 2023, HH farms in 2020, and non-HH farms in 2023—were associated with significantly lower odds of MDR. These findings provide the first evidence from Thailand that structured veterinary herd health programs are independently associated with lower critically important antimicrobial resistance, supporting their integration into a One-Health stewardship policy. Full article

Bovine milk adulteration with coconut milk poses a significant threat to food safety, as both liquids are visually similar yet nutritionally distinct. This study presents an integrated analytical framework combining excitation–emission matrix (EEM) fluorescence spectroscopy with chemometric and deep learning techniques to detect and quantify coconut milk adulteration in bovine milk across nine concentration levels (0–100% v/v). Parallel factor analysis (PARAFAC) resolved two dominant fluorescent components, tryptophan (λ ex/em: 290/350 nm) and riboflavin (λ ex/em: 450/525 nm), whose scores decreased monotonically with increasing adulteration, confirming their role as key chemical biomarkers. For quantitative prediction, PLSR and 1D-CNN models were developed using emission spectra at three excitation wavelengths, with best performances achieved at 450 nm (PLSR: R²P = 0.97, RMSEP = 5.00%; 1D-CNN: R²P = 0.94, RMSEP = 6.75%). A lightweight 2D-CNN utilizing full EEM contour maps as image inputs outperformed all quantitative models, achieving R²P = 0.99, RMSEP = 2.36%, and RPD = 12.97, demonstrating the advantage of preserving the full two-dimensional fluorescence topology over discrete wavelength selection. These results confirm that EEM combined with 2D-CNN provides a highly accurate and non-destructive tool for dairy authentication. Full article

Bovine milk is a primary dietary source of nutrients and bioactive compounds. However, its safety is increasingly under threat due to contamination from mining and intensive agriculture. In the Peruvian Andes, where small-scale dairy farming coexists with historical environmental liabilities, identifying the transfer of metals into the food chain is essential for public health. This study quantifies the concentrations of lead (Pb) and cadmium (Cd) in raw milk from small-scale producers in rural districts in the province of Huancayo. Non-carcinogenic risks for populations aged 2–85 years were assessed under three consumption scenarios. Forty-five samples were analyzed using microwave plasma atomic emission spectrometry (MP-AES). The mean concentrations of Pb and Cd were 11.30 ± 18.94 µg/kg and 7.85 ± 18.11 µg/kg, respectively, which are below the maximum permissible limits (MPL). However, spatial analysis identified critical hotspots near smelters, where Pb levels reached 103 µg/kg, which is a significant exceedance of the MPL of 20 µg/kg. Toxicological modelling showed that the Hazard Index (HI) remained below the unity threshold (HI < 1) for all scenarios, ruling out immediate systemic risks. Nevertheless, the highest HI (0.78) was observed in two-year-old children in the high-consumption scenario, highlighting a localized neurodevelopmental concern. These findings emphasize the importance of georeferenced environmental monitoring and differentiated public health policies to mitigate the chronic low-level exposure to metals in vulnerable, high-altitude populations. Full article

Our previous work demonstrated that bovine milk-derived extracellular vesicles (mEVs) could alleviate the inflammatory response of mice colitis, along with hundreds of differentially expressed (DE) mRNAs. This study further analyzed the profiles of non-coding RNAs (ncRNAs) and explored the correlation with DE mRNAs by constructing ceRNA networks. Six-week-old male C57BL/6 mice were fed either a control diet or a diet added with mEVs for 30 days. Then the mice were given dextran sulphate sodium in drinking water for 7 days to induce colitis. A total of 40 miRNAs, 541 lncRNAs and 643 circRNAs exhibited changes in mEVs pretreatment group. Among these DE miRNAs, mEVs pretreatment significantly increased the expressions of miR-122, miR-147, miR-210, miR-1224, miR-148a, and miR-212, which might participate in the inflammatory response of the colitis models. The expression of Tug1 increased after mEVs pretreatment, while Snhg5 and H19 decreased, which might be involved in intestinal barrier restoration. Functional analysis of the DE ncRNAs suggested mEVs might exert protective effects not only through modulation of inflammatory responses but also by enhancing intestinal stem cell function and epithelial regeneration, which were mainly regulated by Wnt and Hippo signaling pathways according to the ceRNA networks. Full article

Despite the growing number of publications using the value network approach to analyze agro-industrial competitiveness, knowledge gaps persist in other food production sectors. The objective of this study is to analyze, through bibliometric techniques, the scientific articles that have studied the competitiveness of food products using the value network framework. The study will determine the spatial and temporal distribution of the identified food products and detect opportunities for generating new research. Articles from major publishing databases (Elsevier, Scopus, Frontiers, MDPI, and Springer) were considered. The keywords used were “red de valor” and “value network”, combined with “sustainable agricultural production” and “food security”. This information formed the basis of a spatial–temporal analysis and bibliometric indicators using descriptive statistics, as well as keyword and author networks generated with VOSviewer software. A total of 147 scientific articles were documented. The highest growth in publications occurred from 2017 to 2024 and was concentrated in Latin America, Europe, and Asia. Studies in these regions analyzed basic food products such as maize, mango, rice, and coffee in Latin America; wine and bovine milk in Europe; and rice and sugar in Asia. Research in aquaculture, apiculture, and non-timber forest sectors was limited, positioning these areas as opportunities for generating new knowledge, particularly through the analysis of local resources to enhance their market positioning while incorporating sustainability aspects. Full article

Background/Objectives: Milk somatic cells reflect the cellular composition and functional state of the lactating mammary gland and represent a valuable, non-invasive source for transcriptomic studies. Single-cell RNA sequencing (scRNA-seq) enables cell-type-resolved analysis of bovine milk; however, sequencing depth strongly influences the detection of lowly expressed genes and the resolution of transcriptional cell states. The aim of this study was to further characterise the single-cell transcriptome of bovine milk somatic cells, with particular emphasis on high-resolution gene expression profiling and cellular heterogeneity. Methods: Milk somatic cells were isolated from two healthy Holstein Friesian cows in mid-lactation and profiled using a droplet-based scRNA-seq platform. Newly generated high-depth datasets were integrated with two previously published bovine milk scRNA-seq datasets using an identical bioinformatics pipeline. Data integration, clustering and cell-type annotation were performed using the Seurat framework, and transcription factor expression was evaluated across datasets with different sequencing depths. Results: Single-cell transcriptomic analysis revealed a diverse cellular landscape in bovine milk, comprising epithelial, progenitor, and immune cell populations. Unsupervised clustering identified 21 transcriptionally distinct clusters, including multiple CD8⁺ T-cell subpopulations, monocytes, neutrophils, mast cells, and B cells, as well as luminal epithelial and luminal progenitor cells. While overall cell-type composition was comparable across datasets, deeply sequenced samples exhibited higher transcriptomic complexity and enabled refined resolution of immune and epithelial subpopulations. Deeper sequencing facilitated the detection of low-abundance transcription factors that were not observed in lower-depth datasets. Among these, NANOG was detected exclusively in deeply sequenced samples, suggesting the presence of rare transcriptional states associated with cellular plasticity. Conclusions: This study expands the single-cell transcriptomic landscape of bovine milk somatic cells and demonstrates the importance of sequencing depth for resolving functional cellular heterogeneity. The results highlight milk as a powerful, non-invasive source for investigating mammary gland biology and cellular plasticity during lactation. Full article

Immunocompromised pediatric populations (children with inborn errors of immunity, HIV infection, and cancer, as well as those undergoing hematopoietic stem-cell transplantation) have severe nutritional challenges, with malnutrition depending on the underlying condition. Camel milk (CM) represents a culturally accessible, high-quality nutritional parameter and functional food naturally enriched with particular immunological components such as heavy-chain antibodies that represent 75% of total immunoglobulins (IGs) and lactoferrin (LF) at a concentration 3–5 times higher than bovine milk (BM). However, there is a critical processing paradox: the thermal treatments required for the microbiological safety of immunosuppressed children who show a 20-fold greater susceptibility to foodborne pathogens degrade the therapeutic bioactive proteins. This comprehensive review provides a systematic evaluation of processing-induced modifications of CM IGs and LF, which involve thermal and non-thermal technologies, and their effects on the molecular structure and biological function. Emerging alternatives such as high-pressure processing (HPP), pulsed electric fields, and strategic fermentation show promising bioactivity retention without compromising safety. Critical knowledge gaps remain in the structure–function relationships of processed CM proteins, necessitating evidence-based optimization strategies to balance microbiological safety with clinically relevant immunomodulatory functions for vulnerable pediatric populations. Full article