Composition and properties of bovine milk: A study from dairy farms in northern Sweden; Part II. Effect of monthly variation

Milking system and diet forage type effect on milk quality of Italian Holstein-Friesian

Moving from conventional (CMS) to automatic (AMS) milking systems could affect milk quality. Moreover, the type and preservation methods of the forages used in the TMR, such as alfalfa hay (HTMR) or corn silage (STMR) have been demonstrated to modify milk composition. Thus, this study investigated the effect of implementing AMS and different diet forage types on the quality of Italian Holstein-Friesian bulk milk. Milk samples (n = 168) were collected monthly from 21 commercial farms in northern Italy during a period of 8 mo. Farms were categorized into 4 groups according to their milking system (CMS vs. AMS) and diet forage type (HTMR vs. STMR). Milk quality data were analyzed through the mixed procedure for repeated measurement of SAS with the milking system, diet forage type, and sampling day as fixed effects. Milking through the AMS led to lower milk fat, freezing point, and β-LG A; longer coagulation time; and higher K content, pH, and β-LG B than CMS. Cows fed STMR produced milk with greater fat, protein, casein, Mg content, titratable acidity, and β-LG A, but with reduced curd firming time, freezing point, and β-LG B than those fed HTMR. In conclusion, milk quality is not only altered by the diet's forage type and characteristics but also by the milking system.

The microbiota of ensiled forages and of bulk tank milk on dairy cattle farms in northern Sweden - a case study

Factors contributing to variations in the quality and microbiota of ensiled forages and in bulk tank microbiota in milk from cows fed different forages were investigated. Nutritional quality, fermentation parameters and hygiene quality of forage samples and corresponding bulk tank milk samples collected in 3 periods from 18 commercial farms located in northern Sweden were compared. Principal coordinates analysis revealed that the microbiota in forage and bulk milk, analyzed using 16S rRNA gene-based amplicon sequencing, were significantly different. The genera Lactobacillus, Weissella and Leuconostoc dominated in forage samples, whereas Pseudomonas, Staphylococcus and Streptococcus dominated in bulk milk samples. Forage quality and forage-associated microbiota were affected by ensiling method and by use of silage additive. Forages stored in bunker and tower silos (confounded with use of additive) were associated with higher levels of acetic and lactic acid and Lactobacillus. Forage ensiled as bales (confounded with no use of additive) was associated with higher dry matter content, water-soluble carbohydrate content, pH, yeast count and the genera Weissella, Leuconostoc and Enterococcus. For bulk tank milk samples, milking system was identified as the major factor affecting the microbiota and type of forage preservation had little impact. Analysis of common amplicon sequence variants (ASVs) suggested that forage was not the major source of Lactobacillus found in bulk tank milk.

Bovine milk microbiota: Key players, origins, and potential contributions to early-life gut development

BACKGROUND

Bovine milk is a significant substitute for human breast milk and holds great importance in infant nutrition and health. Apart from essential nutrients, bovine milk also contains bioactive compounds, including a microbiota derived from milk itself rather than external sources of contamination.

AIM OF REVIEW

Recognizing the profound impact of bovine milk microorganisms on future generations, our review focuses on exploring their composition, origins, functions, and applications.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Some of the primary microorganisms found in bovine milk are also present in human milk. These microorganisms are likely transferred to the mammary gland through two pathways: the entero-mammary pathway and the rumen-mammary pathway. We also elucidated potential mechanisms by which milk microbiota contribute to infant intestinal development. The mechanisms include the enhancing of the intestinal microecological niche, promoting the maturation of immune system, strengthening the intestinal epithelial barrier function, and interacting with milk components (e.g., oligosaccharides) via cross-feeding effect. However, given the limited understanding of bovine milk microbiota, further studies are necessary to validate hypotheses regarding their origins and to explore their functions and potential applications in early intestinal development.

Near-infrared hyperspectral image analysis for monitoring the cheese-ripening process

Ripening is the most crucial process step in cheese manufacturing and constitutes multiple biochemical alterations that describe the final cheese quality and its perceived sensory attributes. The assessment of the cheese-ripening process is challenging and requires the effective analysis of a multitude of biochemical changes occurring during the process. This study monitored the biochemical and sensory attribute changes of paraffin wax-covered long-ripening hard cheeses (n = 79) during ripening by collecting samples at different stages of ripening. Near-infrared hyperspectral (NIR-HS) imaging, together with free amino acid, chemical composition, and sensory attributes, was studied to monitor the biochemical changes during the ripening process. Orthogonal projection-based multivariate calibration methods were used to characterize ripening-related and orthogonal components as well as the distribution map of chemical components. The results approve the NIR-HS imaging as a rapid tool for monitoring cheese maturity during ripening. Moreover, the pixelwise evaluation of images shows the homogeneity of cheese maturation at different stages of ripening. Among the chemical compositions, fat content and moisture are the most important variables correlating to NIR-HS images during the ripening process.

Variation in Dairy Milk Composition and Properties Has Little Impact on Cheese Ripening: Insights from a Traditional Swedish Long-Ripening Cheese

The monthly variation in raw dairy silo milk was investigated and related to the ripening time of the resulting cheese during an industrial cheese-making trial. Milk composition varied with month, fat and protein content being lowest in August (4.19 and 3.44 g/100 g, respectively). Casein micelle size was largest (192–200 nm) in December–February and smallest (80 nm) in August. In addition, SCC, total bacteria count, proteolytic activities, gel strength, and milk fatty acid composition were significantly varied with month. Overall sensory and texture scores of resulting cheese were mainly influenced by plasmin and plasminogen activity, indicating the importance of native proteolytic systems. Recently, concepts based on the differentiated use of milk in dairy products have been suggested. For the investigated cheese type, there might be little to gain from such an approach. The variation in the investigated quality characteristics of the dairy milk used for cheese making had little effect on cheese ripening in our study. In contrast to our hypothesis, we conclude that as long as the quality of the milk meets certain minimum criteria, there are only weak associations between cheese milk characteristics and the time required for the development of aroma and texture in the cheese. To find answers behind the observed variation in cheese ripening time, studies on the effects of process parameters are needed.

Composition and properties of bovine milk: A study from dairy farms in northern Sweden; Part I. Effect of dairy farming system

This study was part of a larger project that aimed to understand the causes for increasing variation in cheese ripening in a cheese-producing region in northern Sweden. The influence of different on-farm factors on raw milk composition and properties was investigated and is described in this paper, whereas the monthly variation in the milk quality traits during 1 yr is described in our companion paper. The dairy farming systems on a total of 42 dairy farms were characterized through a questionnaire and farm visits. Milk from farm tanks was sampled monthly over 1 yr and analyzed for quality attributes important for cheese making. On applying principal component analyses to evaluate the variation in on-farm factors, different types of farms were distinguished. Farms with loose housing and automatic milking system (AMS) or milking parlor had a higher number of lactating cows, and predominantly Swedish Holstein (SH) breed. Farms associated with tiestalls had a lower number of lactating cows and breeds other than SH. Applying principal component analyses to study the variation in composition and properties of tank milk samples from farms revealed a tendency for the formation of 2 clusters: milk from farms with AMS or a milking parlor, and milk from farms with tiestall milking. The interaction between the milking system, housing system, and breed probably contributed to this grouping. Other factors that were used in the characterization of the farming systems only showed a minor influence on raw milk quality. Despite the interaction, milk from tiestall farms with various cow breeds had higher concentrations (g/100 g of milk) of fat (4.74) and protein (3.63), and lower lactose concentrations (4.67) than milk from farms with predominantly SH cows and AMS (4.32, 3.47, and 4.74 g/100 g of milk, respectively) or a milking parlor (4.47, 3.54, and 4.79 g/100 g of milk, respectively). Higher somatic cell count (195 × 10³/mL) and lower free fatty acid concentration (0.75 mmol/100 g of fat) were observed in milk from farms with AMS than in milk from tiestall systems (150 × 10³/mL and 0.83 mmol/100 g of fat, respectively). Type of farm influenced milk gel strength, with milk from farms with predominantly SH cows showing the lowest gel strength (65.0 Pa), but not a longer rennet coagulation time. Effects of dairy farming system (e.g., dominant breed, milking system, housing, and herd size) on milk quality attributes indicate a need for further studies to evaluate the in-depth effects of farm-related factors on milk quality attributes.