Search Results (695)

The purpose of this study was to examine vegetable consumption and its relationship with lifestyle characteristics among children and adolescents. Data from a health survey administered to a representative sample of 177,091 schoolchildren between the ages of 8 and 17 were employed in this observational, cross-sectional investigation. Physical activity level, screen time, and sleeping patterns were assessed using self-completed questionnaires. Vegetable consumption and dietary habits were analyzed using the Mediterranean Diet Quality Index for Children and Adolescents. Participants consuming vegetables more than once daily were categorized as consumers vs. non-consumers. Physical education teachers measured anthropometric and physical fitness factors. Descriptive statistics and binary logistic regression analysis were conducted, and the odds ratio with the corresponding 95% confidence interval was calculated and adjusted for confounders. Vegetables were consumed once or more times a day by more females than males (25.5% vs. 24.0%, p < 0.001). In both sexes, vegetable consumers slept more, ate healthier, spent less time on screens, and had better anthropometric and aerobic fitness measurements than non-consumers. Healthy eating practices, such as regularly consuming fruits, legumes, nuts, and dairy products, were strongly correlated with vegetable intake. For every one-year increase in age, the odds of being a vegetable consumer decreased by 8% and 10% in boys and girls, respectively. Overweight/obese participants had lower odds of being a vegetable consumer by 20%. Increased screen time, inadequate physical activity, and insufficient sleeping hours decreased the odds of being a vegetable consumer by 22%, 30%, and 25%, respectively (all p-values < 0.001). Overall, a healthier lifestyle profile was associated with higher vegetable intake for both sexes among children and adolescents. Full article

Heat stress in dairy cows, caused by high temperature and humidity during summer, has led to significant declines in milk production and severe economic losses for farms. Exosomes—extracellular vesicles carrying bioactive molecules—are critical for intercellular communication and immunity but remain understudied in heat-stressed Holstein cows. In this study, we extracted exosomes from three heat-stressed (HS) cows and three non-heat-stressed (Ctr) cows and employed proteomics to analyze plasma exosomes. We identified a total of 28 upregulated and 18 downregulated proteins in the HS group compared to the control group. Notably, we observed a significant upregulation of key protein groups, including cytoskeletal regulators, signaling mediators, and coagulation factors, alongside the downregulation of HP-25_1. These differentially expressed proteins demonstrate strong potential as heat stress biomarkers. GO and KEGG analyses linked the differentially expressed proteins to actin cytoskeleton regulation and endoplasmic reticulum pathways. Additionally, protein–protein interaction (PPI) analysis revealed the PI3K-Akt signaling pathway as a central node in the cellular response to heat stress. These findings establish plasma exosomes as valuable biospecimens, provide valuable insights into the molecular mechanisms of heat stress response, and may contribute to the development of precision breeding strategies for enhanced thermal resilience in dairy herds. Full article

This study aimed to develop a functional powder using whey and milk matrices, leveraging the protective capacity of chia–alginate hydrogels and the advantages of electrohydrodynamic spraying (EHDA), a non-thermal technique suitable for encapsulating probiotic cells under stress conditions commonly encountered in food processing. A hydrogel matrix composed of chia seed mucilage and sodium alginate was used to form a biopolymeric network that protected probiotic cells during processing. The encapsulation efficiency reached 99.0 ± 0.01%, and bacterial viability remained above 9.9 log₁₀ CFU/mL after lyophilization, demonstrating the excellent protective capacity of the hydrogel matrix. Microstructural analysis using confocal laser scanning microscopy (CLSM) revealed well-retained cell morphology and homogeneous distribution within the hydrogel matrix while, in contrast, scanning electron microscopy (SEM) showed spherical, porous microcapsules with distinct surface characteristics influenced by the encapsulation method. Encapsulates were incorporated into beverages flavored with red fruits and pear and subsequently freeze-dried. The resulting powders were analyzed for moisture, protein, lipids, carbohydrates, fiber, and color determinations. The results were statistically analyzed using ANOVA and response surface methodology, highlighting the impact of ingredient ratios on nutritional composition. Raman spectroscopy identified molecular features associated with casein, lactose, pectins, anthocyanins, and other functional compounds, confirming the contribution of both matrix and encapsulants maintaining the structural characteristics of the product. The presence of antioxidant bands supported the functional potential of the powder formulations. Chia–alginate hydrogels effectively encapsulated L. reuteri, maintaining cell viability and enabling their incorporation into freeze-dried beverage powders. This approach offers a promising strategy for the development of next-generation functional food gels with enhanced probiotic stability, nutritional properties, and potential application in health-promoting dairy systems. Full article

Background: Environmental enrichment is a promising strategy to improve the welfare of dairy goats and sheep. However, studies in this field remain scattered, and its effects on productivity are unclear. Objectives: To evaluate the effects of environmental enrichment on behavioral, physiological, and productive parameters in dairy goats and sheep. Data sources: Scopus and Web of Science were searched for studies published from 2010 to 2025. Study eligibility criteria: Experimental or observational peer-reviewed studies comparing enriched vs. non-enriched housing in dairy goats or sheep, reporting on welfare or productivity outcomes. Methods: This review followed PRISMA 2020 guidelines and the PICO framework. Two independent reviewers screened and extracted data. Risk of bias was assessed with the SYRCLE tool. Results: Thirteen studies were included, mostly with goats. Physical, sensory, and social enrichments showed benefits for behavior (e.g., activity, fewer stereotypies) and stress physiology. However, results varied by social rank, enrichment type, and physiological stage. Only three studies assessed productive parameters (weight gain in kids/lambs); none evaluated milk yield or quality. Limitations: Most studies had small samples and short durations. No meta-analysis was conducted due to heterogeneity. Conclusions: Environmental enrichment can benefit the welfare of dairy goats and sheep. However, evidence on productivity is scarce. Long-term studies are needed to evaluate its cost-effectiveness and potential impacts on milk yield and reproductive performance. Full article

Global policy narratives on livestock development increasingly emphasize environmental concerns, often overlooking the social dimensions of the sector. In the case of dairy, the world’s most valuable agricultural commodity, its role in social and economic development remains poorly quantified. Our study contributes to a more balanced vision of the UN SDGs thanks to the inclusion of a socio-economic dimension. Here we present a novel empirical approach to assess the socio-economic impacts of dairy development using a new global dataset and non-parametric modelling techniques (local polynomial regressions), with yield as a proxy for sectoral performance. We find that as dairy systems intensify, the number of farm households engaged in production declines, yet household incomes rise. On-farm labour productivity also increases, accompanied by a reduction in employment but higher wages. In dairy processing, employment initially grows, peaks, and then contracts, again with rising wages. The most substantial impact is observed among consumers: an increased milk supply leads to lower prices and improved affordability, expanding the access to dairy products. Additionally, dairy development is associated with greater agricultural value added, an expanding tax base, and the increased formalization of the economy. These findings suggest that dairy development, beyond its environmental footprint, plays a significant and largely positive role in social transformation, yet is having to adapt sustainably while tackling labour force relocation, and that dairy development’s social impacts mimic the general agricultural sector. These results might be of interest for the assessment of policies regarding dairy development. Full article

Background/Objectives: Understanding the impact of dietary habits in terms of obesity, health outcomes, and functional decline is critical in Europe’s growing elderly population. This study analyzed trends in Mediterranean diet (MD) adherence, obesity prevalence, and grip strength among middle-aged and elderly Europeans using data from the Survey of Health, Ageing and Retirement in Europe (SHARE). Methods: Data from four SHARE waves (2015–2022) across 28 countries were analyzed. Dietary patterns were assessed through food frequency questionnaires classifying participants as MD-adherent or non-adherent where adherent implies daily consumption of fruits and vegetables and occasional (3–6 times/week) intake of eggs, beans, legumes, meat, fish, or poultry (an unvalidated definition of the MD pattern). Handgrip strength, a biomarker of functional capacity, was categorized into low, medium, and high groups. Body mass index (BMI), self-perceived health (SPHUS), chronic disease prevalence, and CASP-12 scores (control, autonomy, self-realization, and pleasure evaluated on the 12-item version) were also evaluated. Statistical analyses included descriptive methods, logistic regressions, and multiple imputations to address missing data. Results: A significant majority (74–77%) consumed fruits and vegetables daily, which is consistent with MD principles; however, the high daily intake of dairy products (>50%) indicates limited adherence to the MD, which advocates for moderate consumption of dairy products. Logistic regression indicated that individuals with two or more chronic diseases were more likely to follow the MD (odds ratio [OR] = 1.21, confidence interval [CI] = 1.11–1.32), as were those individuals who rated their SPHUS as very good/excellent ([OR] = 1.42, [CI] = 1.20–1.69). Medium and high maximal handgrip were also strongly and consistently associated with higher odds of MD adherence (Medium: [OR] = 1.44, [CI] = 1.18–1.74; High: [OR] = 1.27, [CI] = 1.10–1.48). Conclusions: The findings suggest that middle-aged and older adults are more likely to adhere to the MD dietary pattern if they have more than two chronic diseases, are physically active, and have a medium or high handgrip. Although an unvalidated definition of the MD dietary pattern was used, the results highlight the importance of implementing targeted dietary strategies for middle-aged and elderly adults. Full article

The demand for plant-based fermented beverages is being driven by dietary restrictions, health concerns, and environmental concerns. However, the use of plant substrates, such as oats, presents challenges in terms of fermentation and texture formation. The effects of enzymatic hydrolysis, homogenization and the addition of 1% pectin on oat-based beverages fermented with Lactobacillus delbrueckii subsp. bulgaricus were evaluated in this study. The samples were evaluated for a number of characteristics, including physicochemical, rheological, antioxidant and sensory properties. After 6 h fermentation, pectin-containing samples showed a statistically significant decrease in pH (to 3.91) and an increase in titratable acidity (to 92 °T). Homogenization and the addition of pectin were found to significantly increase viscosity (by 1.5–2 times) and water-holding capacity (by 2 times) while reducing syneresis by 96%. The antioxidant activity of L. bulgaricus-fermented samples increased significantly: the radical scavenging activity (RSA) and OH-radical inhibition increased by 40–60%, depending on the treatment. Extractable polysaccharides (PSs) inhibited lipase and glucosidase by 90% and 85%, respectively; significantly higher inhibition was observed in the fermented and pectin-containing groups. Sensory evaluation showed that the homogenized, pectin-enriched samples (Homog+) scored highest for consistency (4.5 ± 0.2), texture (4.9 ± 0.2), and overall acceptability (4.8 ± 0.2); these scores were all statistically higher than those for the untreated samples. These results suggest that combining enzymatic hydrolysis, homogenization and fermentation with L. bulgaricus significantly improves the structural, functional and sensory properties of oat-based beverages, providing a promising approach to producing high-quality, functional non-dairy products. Full article

The authenticity of Protected Designation of Origin (PDO) Feta cheese is critical for consumer confidence and market integrity, particularly in light of widespread concerns over economically motivated adulteration. This study evaluated the potential of Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) spectroscopy combined with chemometric modeling to differentiate authentic Feta from non-Feta white brined cheeses. A total of 90 cheese samples, consisting of verified Feta and cow milk cheeses, were analyzed in both freeze-dried and fresh forms. Spectral data from raw, first derivative, and second derivative spectra were analyzed using principal component analysis–linear discriminant analysis (PCA-LDA) and Partial Least Squares Discriminant Analysis (PLS-DA) to distinguish authentic Feta from non-Feta cheese samples. Derivative processing significantly improved classification accuracy. All classification models performed relatively well, but the PLS-DA model applied to second derivative spectra of freeze-dried samples achieved the best results, with 95.8% accuracy, 100% sensitivity, and 90.9% specificity. The most consistently highlighted discriminatory regions across models included ~2920 cm⁻¹ (C–H stretching in lipids), ~1650 cm⁻¹ (Amide I band, corresponding to C=O stretching in proteins), and the 1300–900 cm⁻¹ range, which is associated with carbohydrate-related bands. These findings support ATR-FTIR spectroscopy as a rapid, non-destructive tool for routine Feta authentication. The approach offers promise for enhancing traceability and quality assurance in high-value dairy products. Full article

This study investigated ten potential toxic metals (PTMs) in six milk and dairy product types and evaluated food safety (TDI, RDA), human exposure (EDI), non-carcinogenic risk (THQ, HI), and contamination levels (CF, PLI). Based on total PTM load, products ranked as: children’s milk > yogurt > protein milk > milk > ayran > kefir. Aluminum (Al) showed the highest average concentration in all products except ayran, where manganese (Mn) was dominant. Cadmium (Cd), mercury (Hg), and lead (Pb) were consistently at the lowest levels. Except for chromium (Cr) exposure from children’s milk, all average and maximum EDI values stayed below TDI and RDA thresholds. Children’s milk had the highest non-carcinogenic risk, while yogurt, kefir, milk, and ayran may also pose potential risks when maximum HI values are considered. Although CF values varied across products, PLI results showed all products had high levels of PTM contamination. Given the widespread consumption of dairy across all age groups, especially by sensitive populations like children, monitoring and controlling PTM levels is crucial alongside ensuring nutritional quality. Full article

This study analyzes the use of a lightweight image-based deep learning model to classify dairy cows into low-, medium-, and high-milk-yield categories by automatically detecting the udder region of the cow. The implemented model was based on the YOLOv11 architecture, which enables efficient object detection and classification with real-time performance. The model is trained on a public dataset of cow images labeled with 305-day milk yield records. Thresholds were established to define the three yield classes, and a balanced subset of labeled images was selected for training, validation, and testing purposes. To assess the robustness and consistency of the proposed approach, the model was trained 30 times following the same experimental protocol. The system achieves precision, recall, and mean Average Precision (mAP@50) of 0.408 ± 0.044, 0.739 ± 0.095, and 0.492 ± 0.031, respectively, across all classes. The highest precision (0.445 ± 0.055), recall (0.766 ± 0.107), and mAP@50 (0.558 ± 0.036) were observed in the low-yield class. Qualitative analysis revealed that misclassifications mainly occurred near class boundaries, emphasizing the importance of consistent image acquisition conditions. The resulting model was deployed in a mobile application designed to support field-level assessment by non-specialist users. These findings demonstrate the practical feasibility of applying vision-based models to support decision-making in dairy production systems, particularly in settings where traditional data collection methods are unavailable or impractical. Full article

Previous studies of direct-fed microbial (DFM) supplements showed variable effects on the microbiota and physiology of dairy cows. The main aims of this study were to investigate the milk microbiota of cows supplemented with a lactobacilli-based DFM compared to untreated cows; describe the changes; and quantify the association between the taxa and cow productivity. The study followed seventy-five Holstein–Friesian dairy cows supplemented with a DFM over 16 months compared to seventy-five non-supplemented cows. Twenty-five cows from each group were sampled for microbiota analysis. The top taxa significantly associated with the variables were as follows: Age (Mammaliicoccus_319276, Turicibacter), milk production (Turicibacter, Bifidobacterium_388775), DIM (Stenotrophomonas_A_615274, Pedobacter_887417), milk fat percentage (Pseudomonas_E_647464, Lactobacillus), calendar month (Jeotgalicoccus_A_310962, Planococcus), milk protein percentage (Tistrella, Pseudomonas_E_650325), experimental group (Enterococcus_B, Aeromonas), SCC (Paenochrobactrum, Pseudochrobactrum), and trimester of pregnancy (Dyadobacter_906144, VFJN01 (Acidimicrobiales)). These were identified using multivariable analysis. Twenty-six genera were associated with the differences between experimental groups, including Pseudomonas, Lactococcus and Staphylococcus. Microbial taxa that changed in relative abundance over time included Atopostipes, Brevibacterium and Succinivibrio. Many of these genera were also part of the core microbiota. Supplementation with the DFM significantly altered the milk microbiota composition in the dairy cows, highlighting the impact of long-term DFM supplementation on microbial communities. Full article

The singular biodiversity of the Brazilian Caatinga inspires innovative solutions in food science. In this study, we evaluated the prebiotic potential of honeys produced by Apis mellifera in the Pajeú hinterland, Pernambuco, Brazil (Caatinga Biome), with different floral origins: Mastic (Aroeira), Mesquite (Algaroba), and mixed flowers. These were used to formulate synbiotic and alcoholic beverages fermented by Saccharomyces boulardii CNCM I-745. Static and dynamic simulations of the human gastrointestinal tract (GIT) were used, as well as physicochemical, rheological, and microbiological analyses. The results revealed that honey positively influences the viability and resilience of probiotic yeast, especially honey with a predominance of Algaroba, which promoted the highest survival rate (>89%) even after 28 days of refrigeration and in dynamic in vitro simulation of the GIT (more realistic to human physio-anatomical conditions). The phenolic composition of the honeys showed a correlation with this tolerance. The use of complementary methodologies, such as flow cytometry, validated the findings and highlighted the functional value of these natural matrices, revealing an even greater longevity potential compared to conventional microbiological methodology. The data reinforces the potential of the Caatinga as a source of bioactive and sustainable compounds, proposing honey as a promising non-dairy synbiotic vehicle. This work contributes to the appreciation of the biome and the development of functional food products with a positive social, economic, and ecological impact. Full article

Dairy mastitis is a common dairy farming disease. It severely affects the health of dairy cows and the quality and yield of dairy products. This paper reviews the main current mastitis treatments and associated bacterial resistance. It emphasizes the importance of integrated resistance and treatment management. The therapeutic efficacy and resistance associated with commonly used antibiotics such as penicillin, cephalosporins, macrolides and fluoroquinolones are analyzed. The principles, application effects and benefits of non-antibiotic therapies are also discussed, including those of immunotherapy, herbal therapy, probiotic therapy and phage therapy. The paper presents the latest gene editing and nanotechnology advances in the contexts of big data and artificial intelligence. It suggests future research directions such as developing new antibiotics, optimizing treatment and enhancing immunity. In conclusion, effective treatment and management can control dairy cow mastitis. It can guarantee cow health, improve dairy product quality and promote sustainable dairy industry development. Full article

To study behavioral and productive factors to detect changes that may indicate and predict clinical mastitis cure, Holstein dairy cows (n = 60), in an automatic milking system (AMS) and equipped with behavioral monitoring collar, were monitored from the diagnosis of clinical mastitis (D0) until clinical cure. The parameters collected through sensors were feeding activity, milk electrical conductivity (EC), milk yield, Mastitis Detection Index (MDi), milk flow, and number of gate passages. Clinical mastitis cases (n = 22) were monitored and divided into cured cases (n = 14) and non-cured cases within 30 days (n = 8), paired with a control case group (n = 28). Cows were assessed three times per week, and cure was determined when both clinical assessment and California Mastitis Test (CMT) results were negative in three consecutive evaluations. Mixed generalized linear regression was used to assess the relationship between parameters and clinical mastitis results. Mixed generalized logistic regression was used to create a predictive model. The average clinical cure time for cows with clinical mastitis was 11 days. Feeding activity, gate passages, milk yield, milk flow, EC, and the MDi were associated with cure. The predictive model based on data from D0 showed an Area Under the Curve of 0.89 (95% CI = 0.75–1). Sensitivity and specificity were 1 (95% CI = 1–1) and 0.63 (95% CI = 0.37–0.91), respectively. The predictive model demonstrated to have good internal sensitivity and specificity, showing promising potential for predicting clinical mastitis cure within 14 days based on data on the day of clinical mastitis diagnosis. Full article

Heat stress has been identified as one of the main challenges for dairy production systems, particularly in the context of global warming. This one-year study aimed to evaluate the impact of heat stress on milk yield and composition in a dairy farm located in the Elvas region of Portugal. A pack of electronic sensors was installed in the lactating animal facilities, allowing continuous recording of environmental data (temperature, humidity, ammonia and carbon dioxide). Based on these data, the Temperature-Humidity Index (THI) was automatically calculated on a daily basis, with the values subsequently aggregated into 7-day moving averages and integrated with milk production records, somatic cell count, and milk fat and protein content. The results indicate a significant influence of THI on both milk yield and composition, particularly on protein and fat content. The relationships between the variables were found to be non-linear, which contrasts with some results described in the literature. These discrepancies may be related to genetic differences between animals, variations in diets, production levels, management conditions, or the statistical models used in previous studies. Dry matter intake proved to be an important predictive variable. These findings reinforce the importance of ensuring animal welfare through continuous environmental monitoring and the implementation of effective heat stress mitigation strategies in the dairy sector. Full article