Search Results (421)

This study assesses the quality of fat in conventional and specialist infant formulas (IFs) available in Poland. The IFs studied were characterized in terms of fatty acid profiles and lipid quality indices. The study material consisted of eight types of conventional and specialist IFs. The determination of fatty acids was carried out using gas chromatography (GC). Lipid quality indices were estimated based on established formulas. Goat milk-based formulas showed significantly higher levels of caproic acid (C6:0) and capric acid (C10:0) than cow milk-based formulas of the same category (initial or follow-on) (p < 0.05). In addition, these IFs stood out in terms of conjugated linoleic acid (CLA) content (0.30%) compared to cow and specialist formulas (about 0.20%). It was shown that the average ratio of n6/n3 fatty acids was significantly lower in conventional IFs (6.07:1) compared to specialist IFs (8.10:1). The goat’s milk-based IFs had the most favorable values for individual lipid quality indices (index of desirable fatty acids (DFAs) = 62.46; index of hypercholesterolemic fatty acids (OFAs) = 25.94; index of atherogenicity (AI) = 0.71; index of thrombogenicity (TI) = 0.88; hypocholesterolemic/hypercholesterolemic ratio (H/H) = 2.05), while the specialist S-PH formula was characterized by the lowest DFA value (49.17) and the highest AI and TI indices (1.48 and 1.68). Multivariate analysis clearly classified the division of formulas into two groups—conventional and specialist—based on lipid quality indices. The results obtained provide new information on the variation in the lipid profile of IFs depending on the intended use of the formula and may serve as a basis for further research in this area. Full article

Following hygiene standards in milk production is essential for making high-quality sour cream, especially when using traditional methods that rely on raw milk. The aim of this study was to determine the physicochemical, microbiological, and sensory quality of artisanal sour cream samples collected from major marketplaces in the wider Zagreb area. On average, the samples contained 27.99% milk fat, 3.30% protein, 34.29% dry matter, 6.51% fat-free dry matter and 3.00% lactose, with considerable variability observed across all components. Microbiological analysis revealed the presence of Staphylococcus aureus in 35.30% of the samples, Enterobacteriaceae in 76.47%, Escherichia coli in 94.11%, Bacillus spp. in 23.53%, and yeasts in 100% of the samples. Listeria monocytogenes and Salmonella spp. were not detected. The sensory analysis of the textural properties showed significant variability in firmness, adhesiveness, viscosity, creaminess, and fizziness. Samples with higher milk fat and dry matter content were rated better for creaminess, viscosity and mouth firmness. Flavour assessments, particularly for cream and diacetyl notes, also varied widely among samples. These findings highlight the complexity of sour cream’s sensory attributes and the significant influence of ingredient composition and processing techniques on appearance, aroma, texture, taste, and flavour. Principal component analysis (PCA) with Varimax rotation simplified the data structure and identified key dimensions of quality variation. Principal component analysis (PCA) revealed that the first principal component (PC1) effectively discriminated the cream samples based on sensory attractiveness and indicators of spoilage and highlighted the association between off-flavour and microbial contamination with inferior characteristics. The second principal component (PC2) captured the differences in physicochemical characteristics and showed a gradient from richer, creamier samples with higher fat content to those with lower acidity and higher freshness. Full article

The amount of protein and fat in raw milk determines its quality, value in the marketplace, and related payment to suppliers. Technicians use expensive specialized laboratory equipment to measure milk quality in specialized laboratories. The continuous quality monitoring of the milk supply in the supplier’s tanks enables the production of higher quality products, better milk supply chain optimization, and reduced milk waste. This paper presents an inexpensive AI-powered IoT sensor that continuously measures the protein and fat in the raw milk in the tanks of dairy farms, pickup trucks, and intermediate storage depots across any milk supply chain. The proposed sensor consists of an in-tank IoT device and related software components that run on any IoT platform. The in-tank IoT device quality incorporates a low-cost spectrometer and a microcontroller that can send milk supply measurements to any IoT platform via NB-IoT. The in-tank IoT device of the milk quality sensor is housed in a food-safe polypropylene container that allows its deployment in any milk tank. The IoT software component of the milk quality sensors uses a specialized machine learning (ML) algorithm to translate the spectrometry measurements into milk fat and protein measurements. The paper presents the design of an in-tank IoT sensor and the corresponding IoT software translation of the spectrometry measurements to protein and fat measurements. Moreover, it includes an experimental milk quality sensor evaluation that shows that sensor accuracy is ±0.14% for fat and ±0.07% for protein. Full article

This study investigated the effect of different farming systems and lactation stages on the physicochemical characteristics, somatic cell count (SCC), and total bacterial count (TBC) of milk from Skopelos goats. This study was conducted over two consecutive lactation periods on two commercial farms in Greece, an extensive system on Skopelos Island and an intensive system in the Attica region, involving 237 goats of shared genetic background, thereby minimizing genetic variability and strengthening the validity of the comparisons between the production systems. Higher milk yields were observed in the extensive system (0.98 vs. 0.85 kg/day), while milk from this system also had a higher protein (3.57% vs. 3.47%; p < 0.001) and casein content (2.72% vs. 2.57%; p < 0.001), which are traits favorable for cheese production. Fat content peaked during mid-lactation (4.83%; p < 0.05) and remained unaffected by the farming system. Lactose declined from early (4.74%) to late lactation (4.42%; p < 0.001). Both SCC and TBC were significantly elevated in the extensive system (p < 0.001), possibly due to hand milking, environmental exposure, and less-controlled hygiene conditions. These findings highlight a trade-off between the nutritional advantages of extensive systems and challenges related to milk hygiene. A balanced approach, optimizing both quality and sustainability, is recommended. Full article

The present study aimed to evaluate the impact of two dietary regimens, characterized by different forage-to-concentrate ratios, on feed intake, milk yield and composition, as well as economic and environmental sustainability in lactating buffalo cows. Group H was fed a high-forage diet, while Group L was fed a diet with a lower forage-to-concentrate ratio. Despite a lower energy value (Unit for Feed Lactation: UFL 0.89 vs. 0.91), the diet of group H met the animals’ nutritional requirements, with similar dry matter intake (DMI) and body condition scores observed in both groups. While there was no significant difference in milk yield, protein, and lactose, group H exhibited significantly higher milk fat content and an enhanced fatty acid profile, characterized by increased oleic acid, conjugated linoleic acids (CLAs), and omega-3 polyunsaturated fatty acids. These fatty acids have been linked to potential health benefits in humans, including anti-inflammatory, cardioprotective, and anticarcinogenic effects. From an economic perspective, the H group’s diet was found to be more cost-effective, resulting in EUR 0.46 savings per head per day and a higher yield of mozzarella cheese. From an environmental perspective, the high-forage diet reduced reliance on imported concentrates and irrigation-dependent crops, aligning with sustainable development goals. In conclusion, increasing the forage content in buffalo diets has been demonstrated to support animal performance, improve milk quality, reduce environmental impact, and enhance economic returns for producers. Full article

Physico-chemical analyses, fatty acid profiles, microbiological analyses and sensory characteristics (assessed by trained judges and by consumers) were carried out on four types of goat cheese produced in artisanal cheese factories using raw milk from different autochthonous Spanish goat breeds (Malagueña, Florida, Murciano-Granadina and Cabra del Guadarrama). The cheeses studied were different in fat, protein, salt, pH, moisture, acidity and color due to the different production technologies and the properties of the milk of each breed. Saturated fatty acids (SFAs) were the predominant fatty acids in all the goat milk cheeses studied. Cabra del Guadarrama Cheese (CGC) and Malagueña Cheese (MC) showed an n-6/n-3 ratio < 4, and MC was found to have the lowest atherogenic and thrombogenic indices. CGC had a lower fat content than the rest of the cheeses studied. The fatty acid profile of CGC was more similar to MC than to Florida Cheese (FC) and Murciano-Granadina Cheese (MGC). MGC had a higher atherogenic and thrombogenic index, a higher PUFA n-6/n-3 ratio than the rest of the cheeses studied and a higher fat content. Therefore, CGC, MC and FC had a healthier lipid profile than MGC. The texture properties of CGC and FC were more similar to each other than to those of MC and MGC (harder cheeses). Sensory analyses performed with trained judges were in accordance with instrumental texture parameters. Consumer acceptability was similar for all the cheeses under blind conditions and only under informed conditions did consumers score FC significantly higher than MGC. In a rank test FC was chosen as the better cheese for a greater number of consumers both in blind and in informed conditions. The provision of information improved the overall liking of Cabra del Guadarrama Cheese and worsened that of Murciano-Granadina Cheese. The high quality of the cheeses confirms the need to raise consumer awareness of autochthonous goat breeds to increase the consumption of these products in order to contribute to the preservation of these breeds. Full article

Donkey milk has received increasing attention in recent years due to its unique nutritional composition and potential biological activities. This comprehensive review analyzed the main nutritional components of donkey milk, including proteins, lipids, carbohydrates, vitamins, and minerals, while also examining its significant biological activities such as antioxidant, antimicrobial, immunomodulatory, and anti-inflammatory properties. The protein profile of donkey milk is notable for its high proportion of whey proteins (55–65%), resembling human milk more closely than cow milk. Its relatively low-fat content (approximately 1.29%) with higher proportions of unsaturated fatty acids provides nutritional advantages for specific dietary needs. The carbohydrate content, primarily lactose, contributes to energy provision and calcium absorption. Donkey milk is also distinguished by its rich vitamin profile, particularly vitamin C (about 4.75 times higher than cow milk), and essential minerals including calcium, phosphorus, and zinc. The biological activities of donkey milk extend to various applications in infant nutrition, particularly for children with cow milk protein allergies, potential medical treatments for infections and inflammatory conditions, and cosmetic formulations. Despite these promising attributes, the donkey milk industry faces challenges including low milk yield, lack of standardized production methods, and quality control measures. The sustainable development of the donkey milk industry requires comprehensive approaches to resource protection, technological innovation, brand building, and supportive policies to realize its full potential in contributing to human health and economic development. Full article

Milk fat plays an important role in the flavor and texture of cheese. However, it contains high amounts of saturated fat and cholesterol, which have recently been reported to be unsuitable for maintaining good health. The aim of this study was to evaluate the effects of milk fat’s replacement with sacha inchi (Plukenetia volubilis) oil in fresh cheese processing on the coagulation properties, nutritional value, and sensory properties, aiming to obtain a hybrid fresh cheese rich in polyunsaturated fatty acids (PUFAs). Milk fat (3.8% in standardized milk) was partly replaced with Vietnamese sacha inchi oil at 20, 40, 60, and 80%. The coagulation time, curd formation, and cheese yield showed no significant differences among the treatments (p > 0.05), suggesting that sacha inchi oil did not adversely affect curd formation. The cholesterol levels decreased substantially, from 8.27 ± 0.53 mg/g in control samples to 2.63 ± 0.63 mg/g at 80% fat replacement. An increase in essential fatty acids in the fresh cheese was also found with an increase in the use of sacha inchi oil to replace milk fat, with the oleic acid concentration (OA, C18:1, cis ω-9) rising from 7.88 ± 0.36% to 23.44 ± 0.13% and the linoleic acid concentration (LA, C18:2, cis ω-6) from 6.44 ± 0.68% to 41.75 ± 2.50% at the highest substitution level. From a nutritional perspective, the replacement of milk fat with sacha inchi oil did not affect the macronutritional values (fat, protein), but it reduced the cholesterol levels and enhanced the overall nutritional value of the fresh cheese with increasing essential fatty acids. The milk fat alternative of sacha inchi oil for cheese processing contributed to a richer and creamier sensory experience of the final products, but no significant differences in the overall liking were found regarding the acceptance of customers. Thus, replacement with sacha inchi oil in PUFA cheese processing is a promising method to improve the nutritional value and sensory quality of fresh cheese. Full article

Utilizing agro-industrial by-products to feed livestock is crucial for environmental protection and, simultaneously, lowering production and feeding costs. In light of these aims, in this study, two trials were conducted to evaluate the impact of jojoba meal (JJM) on Awassi ewes’ milk properties, nutrient intake, digestibility, and the pre-weaning growth of their nursing lambs. In the first trial, 22 Awassi ewes were divided equally between two experimental diets at random (11 ewes per diet): 0% JJM (CON) and 15% JJM (JJM15) of dietary dry matter (DM). In the second trial, 10 ewes were randomly selected (5 ewes/diet) to assess nutritional digestibility and N balance. The results of trial 1 showed that neutral detergent fiber (NDF), acid detergent fiber (ADF), and ether extract (EE) intake values were greater (p ≤ 0.02) in the JJM15 group compared to the CON group. The total gain and average daily gain (ADG) of the lambs in the JJM15 group were significantly higher compared to those of the CON group (p < 0.05). The average milk yield of nursing ewes was similar between the two dietary groups (p ˃ 0.05). The percentage and yield of solids-not-fat (SNF) in the JJM15 group were significantly higher compared to the CON group. The other milk components, including protein, lactose, fat, and total solids yields, were similar between the dietary groups (p ˃ 0.05). The milk production cost was significantly lower for the JJM15 diet than the CON diet (p = 0.004). Triglyceride levels were lower (p = 0.001) in the JJM15 diet group than in the CON diet group. In trial 2, nutrient digestibility and N balance were not affected (p ≥ 0.073) by the consumption of JJM15. In conclusion, JJM at 15% of dietary DM resulted in no negative effects on the health, performance, or milk quality of Awassi ewes. Most significantly, by lowering the cost of production, our results appear to indicate that this dietary supplement improves economic efficiency. Full article

Objectives: This study analyzed correlations of colostrum fatty acids (FAs), newborns’ and mothers’ thyroid hormones (THs), and birth weight, all crucially important in neonatal health. Methods: LC-MS/MS was used to measure 22 FAs in the colostrum of 78 healthy mothers who delivered term babies. FT3, FT4, and TSH levels were determined in the mothers’ serum, and newborns’ TSH was measured in heel-pricked specimens. Correlations were defined in the whole cohort and the subsets, which were separated according to ranges of birth weight, thyroid hormones, and mothers’ body mass index. Phyton Software was used for statistics. Results: The colostrum’s total FA content was highly variable and correlated positively with the percentage values of arachidic, gondoic, and nervonic acids. Five FAs all positively correlated with birth weight for the entire cohort—including ω9 gondoic, erucic, and nervonic acids as well as saturated behenic and lignoceric acids—all produced with the same elongases. These correlations were relevant to gondoic, nervonic, behenic, and lignoceric acids when mothers with low FT4 levels were evaluated separately and to erucic acid in the subset comprising mothers with high TSH values. Conclusions: The priming of breast epithelia to adjust the colostrum quality starts prenatally, whose regulatory mechanisms partially overlap with fetal fat accretion. Thus, colostrum content may undergo modifications to compensate for the harm of subtle TH deficiencies on neonates’ thermoregulation and development. Considering the previous findings showing that milk ω9 FAs are highest in colostrum, and even higher when mothers deliver preterm, our current results indicate their possible protective functions. Full article

Milk lipids are fundamental to the nutritional quality, functional properties, and processing behavior of dairy products. In this study, we employed an untargeted lipidomics approach based on ultra-high-performance liquid chromatography coupled with ultra-high-performance liquid chromatography–high-resolution mass spectrometry (UHPLC-HRMS) to systematically characterize the lipid profiles of ten milk types from eight animal species, including camel, mare, donkey, goat, buffalo, yak, Jersey, and Holstein. A total of 640 lipid species were identified, spanning triglycerides (TGs), phospholipids (PLs), sphingolipids (SPs), ceramides (Cer), wax esters (WEs), and other subclasses. A statistical analysis revealed significant differences in lipid types and abundances among the milk samples. Camel milk exhibited the highest lipid diversity, with notable enrichment in phospholipids and sphingolipids, conferring superior emulsifying properties and stability. Mare milk was rich in polyunsaturated fatty acids (PUFAs), such as linoleic acid and alpha-linolenic acid, making it ideal for developing health-focused dairy products. Despite having the lowest total lipid content, donkey milk was enriched in cholesterol esters and PUFA, suitable for low-fat functional dairy products. Goat milk featured a balanced lipid composition with higher levels of medium-chain fatty acids (MCFAs), promoting digestibility. Buffalo milk was characterized by high TG and wax ester (WE) levels, offering high energy density and suitability for rich dairy products. Yak milk contained higher levels of ceramides (Cer) and saturated fatty acids, reflecting adaptations to high-altitude environments. Jersey milk and Holstein milk displayed similar lipid profiles, with stable compositions suitable for versatile dairy product development. Principal component analysis (PCA), hierarchical clustering, and volcano plot analyses further confirmed species-specific lipidomic signatures and revealed several potential lipid biomarkers, such as LPC (O-16:0) in Hongyuan yak milk, suggesting applications in geographical indication (GI) traceability. This study offers a comprehensive lipidomic landscape across diverse milk sources, providing molecular insights to guide the development of tailored, functional, and regionally branded dairy products. Full article

Donkey milk is well known for its beneficial properties for human health, making it a valuable ingredient in the production of value-added cheese. Rolled cheese, a type of pasta filata cheese, is traditionally produced in the northern part of Serbia. In this study, we produced rolled cheese by adding a certain amount of donkey’s milk from the Balkan and Banat breeds to cow’s milk. The rolled cheese samples were analyzed for their microbiological quality, chemical composition, content of essential and trace elements, as well as sensory characteristics. Adding 10% and 20% donkey’s milk had no effect on the microbiological quality or hedonic scale of rolled cheeses compared with rolled cheese made from raw cow’s milk. However, the addition of donkey’s milk partially affected the chemical composition and mineral profile of the cheeses. The fat, fat in dry matter, calcium contents, and the ratio of calcium and phosphorus significantly (p < 0.05) decreased with the addition of donkey’s milk, while the ash, salt, sodium, and potassium contents significantly (p < 0.05) increased. The assessors successfully distinguished the rolled cheeses containing donkey’s milk from those made with cow’s milk, encouraging the future production of value-added cheese. Full article

Metritis is one of the most common postpartum diseases in dairy cows, associated with impaired reproductive performance and substantial economic losses. In this study, we investigated the potential of machine learning (ML) techniques applied to physiological, behavioural, and milk quality parameters for the early detection of metritis in dairy cows during the postpartum period. A total of 2707 daily observations were collected from 94 cows in early lactation, of which 11 cows (275 records) were diagnosed with metritis. The dataset included daily measurements of body weight, rumination time, milk yield, milk composition (fat, protein, lactose), somatic cell count (SCC), and feed intake. Five classification models—partial least squares discriminant analysis (PLS-DA), random forest (RF), support vector machine (SVM), neural network (NN), and an Ensemble model—were developed using standardised features and stratified 80/20 training/test splits. To address class imbalance, model loss functions were adjusted using class weights. Models were evaluated based on accuracy, sensitivity, specificity, positive and negative predictive values (PPV, NPV), area under the receiver operating characteristic (ROC) area under the curve (AUC), and Matthews correlation coefficient (MCC). The NN model demonstrated the highest overall performance (accuracy = 96.1%, AUC = 96.3%, MCC = 0.79), indicating strong capability in distinguishing both healthy and diseased animals. The SVM achieved the highest sensitivity (90.9%), while RF and Ensemble models showed high specificity (>98%) and PPV. This study provides novel evidence that ML methods can effectively detect metritis using routinely collected, non-invasive on-farm data. Our findings support the integration of neural and Ensemble learning models into automated health monitoring systems to enable earlier disease detection and improved animal welfare. Although external validation was not performed, internal cross-validation demonstrated consistent performance across models, suggesting suitability for application in multi-farm settings. To the best of our knowledge, this is among the first studies to apply ML for early metritis detection based exclusively only automated herd data. Full article

This study aimed to evaluate whether the addition of a phytobiotic additive formulated based on cinnamon and oregano essential oils (50% free and 50% microencapsulated) combined with turmeric extract and tannins to the diet of cows has beneficial effects on health, productivity, and milk quality. In a completely randomized design, eighteen Jersey cows were used in a compost barn system over 45 days. The cows were divided into two homogeneous groups: one control (without additive; n = 9) and another treatment (with a phytobiotic at a dose of 2 g/cow/day; n = 9). The diet was formulated based on corn silage, hay and concentrate for daily 30 L/cow production. Blood and milk samples were collected at 15-day intervals. There was a treatment × day interaction: cows that consumed the phytobiotic additive produced a more significant amount of milk at days 14, 17, 18, 30, 39 and 45 (p ≤ 0.05). When we corrected milk production for fat percentage, we observed higher milk production in the cows that consumed phytobiotics compared to the control during the experimental period (p = 0.01). The feed intake of cows fed phytobiotics was lower (p = 0.01). Thus, feed efficiency was better in cows that consumed phytogenics. There was a higher percentage of fat in the milk of cows that consumed phytobiotics and a higher amount of polyunsaturated fatty acids compared to the control (p = 0.02). There was an increase in total protein and globulin levels (p = 0.01), which may be associated with the interaction of the antimicrobial, antioxidant, and immunomodulatory properties of the phytobiotic additive. An increase in immunoglobulins (p = 0.01) and a reduction in acute-phase proteins (p ≤ 0.05) were observed in the blood of cows in the phytobiotic group. Lower levels of TNF-α, IL-1β and IL-6 and higher levels of IL-10 in the serum of cows that consumed the phytoactive (p = 0.01) reaffirm the anti-inflammatory effect of the additive. Lower levels of lipid peroxidation (TBARS) and reactive oxygen species (ROS) were observed in the serum of cows in the phytobiotic group. Greater catalase and superoxide dismutase activity was observed in cows that consumed the phytogenic (p < 0.01). Therefore, it can be concluded that the additive in question has antioxidant, immunological, and anti-inflammatory actions and has the potential to improve productive performance when corrected for milk fat. Full article

Yogurt is a highly consumed dairy product valued for its nutritional and probiotic properties. Its production involves the use of lactic acid bacteria, which drive biochemical transformations during fermentation. Optimizing fermentation time without compromising yogurt quality is essential for improving processing efficiency. Pulsed electric fields (PEFs) constitute a promising technology that stimulates microbial activity. In this study, a yogurt starter inoculum suspended in milk (IM) with different fat content (0.5–2.8%) was treated with low-intensity PEFs (1 kV/cm, 800–1600 µs) to enhance fermentation kinetics. pH, soluble solids, lactose, lactic acid, and riboflavin concentrations were monitored during 6 h, comparing PEF-treated IM (PEF-IM) and untreated IM (C-IM). PEF-treatments applied to IM reduced the fermentation time of inoculated milk by 4.3–20.4 min compared to C-IM. The lowest fermentation time (5.1 ± 0.16 h) was observed in milk added with PEF-IM (2.8% fat) treated at 1 kV/cm for 1600 µs. Milk inoculated with PEF-IM exhibited enhanced lactose consumption (1.6–3.1%) and higher lactic acid production (7.2%) than milk with C-IM. Riboflavin concentration (0.9–7%) decreased between 2 and 4 h, but it stabilized at the end of fermentation. Obtained results suggest that PEFs promote reversible electroporation in microbial cells, facilitating nutrient uptake and acidification, making it a promising assisted-fermentation approach to improve yogurt production. Full article