Rennet Coagulation Research Articles

Composition and Quality of Low‐Fat Halloumi Cheese Made Using Modified Starch as a Fat Replacer

AbstractThe use of modified maize starch as a fat replacer in low‐fat Halloumi cheese is investigated. Halloumi cheese is made from cow milk (3.5% fat) or from partially skimmed cow milk (1% fat) with 1%, 2%, and 3% modified starch. The addition of modified starch to cow's milk decreased rennet coagulation time and curd syneresis but increased curd tension. The modified starch addition also increased yield and total nitrogen but decreased pH, total solids, fat, ash, and total volatile fatty acids. Total bacterial count and lipolytic bacteria decreased, but proteolytic bacteria and moulds and yeast increased with the added modified starch. The hardness and gumminess values increased, but the elasticity and cohesiveness values of Halloumi cheese decreased. The sensory properties are improved by the addition of modified starch.

Allele frequencies and genotypes of kappa casein (CSN3) and their association with chemical composition and coagulation properties of milk in Brown cattle

Abstract. The aim of the present study was to evaluate allele frequencies and genotypes of kappa casein (CSN3) and their association with milk quality and coagulation properties in Brown cattle. Milk proteins’ polymorphism was found out in 155 tissue samples from cows reared at 4 farms. The analysis of milk composition was done in the lab of the Agriculture Institute – Stara Zagora on Lactoscan ultrasound milk analyzer, whereas coagulation properties of individual milk samples were evaluated on a Computerized Renneting Metter – Polo Trade, Italy. Milk samples were obtained by milk meters. The milk was analysed within 3 hours after sample collection. Naturen Plus 215/0.8L chymosin was used, with milk coagulation activity of 215 IMCU/ml. During the study, the following parameters were studied: milk fat and protein contents (%), rennet coagulation time (RCT, min), curd firmness (а30, mm) and curd firming time (k20, min). Kappa casein (CSN3) is characterised by five genotypes – АА, АВ, ВВ, АН and ВН, the frequency of which varied within various ranges. The milk of cows with genotype AB was characterized by the highest content of fat and protein: 4.85% and 5.00%, respectively. The milk of heterozygous cows from genotype AB demonstrated the longest rennet coagulation time – 18.04 min. The animals carrying the H allele produced milk with the highest curd firmness – 37.00 mm.

Chemical interactions among caseins during rennet coagulation of milk

Rennet milk curds were prepared under 4 different temperature and acidity conditions. The development of different types of inter-protein chemical bonds (disulfide, hydrophobic, electrostatic, hydrogen, and calcium bridges) was monitored for 60 min after curd cutting. Hydrophobic inter-protein interactions originally present in casein micelles in milk were substituted by electrostatic, hydrogen, and calcium bonds throughout the curd curing period. Disulfide bonds were not disturbed by the experimental conditions employed in the study, remaining at a constant level in all studied treatments. Acidification of curds increased the availability of soluble ionic calcium, increasing the relative proportion of calcium bridges at the expense of electrostatic-hydrogen bonds. Although pH defined the nature of the interactions established among proteins in curd, temperature modified the rate at which such bonds were formed.

Effect of β-casein reduction and high heat treatment of micellar casein concentrate on the rennet coagulation properties, composition and yield of Emmental cheese made therefrom

To study the effect of removing β-casein of cheesemilk on cheese manufacture, cheesemilk was formulated from low heat skim milk powder (LH CM), micellar casein concentrate with 1.83% β-casein reduction (MCC CM) and β-casein-reduced micellar casein concentrate with 4.25% β-casein reduction (LB CM) or high heat treatment (HHT; 120 °C, 15 s) LB CM to manufacture Emmental cheeses. MCC- and LB CM had similar rennet coagulation properties and similar compositions and yield in the resultant cheeses. Compared with LB CM, HHT LB CM had an increased level of denatured whey protein and a reduced, yet acceptable, curd firming rate. Higher fat losses, but lower protein losses, from cheesemilk to whey in HHT LB cheeses resulted in a similar yield compared with LB CM cheese. Overall, it was possible to remove β-casein from cheesemilk or apply high heat treatment to whey protein reduced milk without adversely affecting cheese composition and yield.

Effect of Protein Genotypes on Physicochemical Properties and Protein Functionality of Bovine Milk: A Review.

Milk protein comprises caseins (CNs) and whey proteins, each of which has different genetic variants. Several studies have reported the frequencies of these genetic variants and the effects of variants on milk physicochemical properties and functionality. For example, the C variant and the BC haplotype of αS1-casein (αS1-CN), β-casein (β-CN) B and A1 variants, and κ-casein (κ-CN) B variant, are favourable for rennet coagulation, as well as the B variant of β-lactoglobulin (β-lg). κ-CN is reported to be the only protein influencing acid gel formation, with the AA variant contributing to a firmer acid curd. For heat stability, κ-CN B variant improves the heat resistance of milk at natural pH, and the order of heat stability between phenotypes is BB > AB > AA. The A2 variant of β-CN is more efficient in emulsion formation, but the emulsion stability is lower than the A1 and B variants. Foaming properties of milk with β-lg variant B are better than A, but the differences between β-CN A1 and A2 variants are controversial. Genetic variants of milk proteins also influence milk yield, composition, quality and processability; thus, study of such relationships offers guidance for the selection of targeted genetic variants.

Influence of k-casein genotype on heat stability and cheese making properties of milk powder

In this study the effect of k-casein gene polymorphism on the technological characteristics of milk powder obtained by spray (AA1:BB1) and freeze drying (AA2:BB2) was investigated. Standardized and generally accepted methods were used in the field of physical and chemical control of dairy products, as well as methods for assessing the heat stability and cheese making properties of milk. The most heat-resistant were the samples with a predominance of milk obtained from cows with the AA CSN3 genotype, in the pH range from 6.4 to 7.0 (36-91 minutes for AA1:BB1 and 37-101 minutes for AA2:BB2). In systems with a fraction of 25% to 100% of milk from cows with the AA CSN3 genotype obtained by freeze drying, higher (by 3-10%) stabilization qualities of protein were revealed when heated in the pH range from 6.4 to 7.0 compared to spray drying. The analysis of the results regarding the cheese making properties showed that with an increase in the proportion of milk from cows with the BB CSN3 genotype from 0% to 100% in model systems, the rennet coagulation time decreases for all samples, regardless of the drying method. It was also found that when using freeze drying, coagulum of all samples were assigned to the highest class of milk quality in terms of cheese making properties, while during spray drying only the samples consisting of min. 75% or completely of milk obtained from cows with genotype BB CSN3 corresponded to this category.

Relationships of αs1-casein (CSN1S1) and β-casein (CSN2) genotypes and their association with milk quality and coagulation properties in Bulgarian Brown cattle

The aim of the present investigation was to establish the relationships of αs1-casein (CSN1S1) and β-casein (CSN2) genotypes in Bulgarian Brown cattle and to evaluate their association with milk quality and milk coagulation properties. Milk proteins’ polymorphism was found out in 155 tissue samples from cows reared at 4 farms. Innovative protocols and techniques were used for determination of genetic polymorphism of αs1-casein (CSN1S1) and β-casein (CSN2) in Brown cattle. After collection, tissue samples were shipped to the University in Padova, Italy for PCR-RFLP analysis. The analysis of milk composition was done in the lab of the Agriculture Institute – Stara Zagora on Lactoscan ultrasound milk analyzer, whereas coagulation properties of individual milk samples were evaluated on a Computerized Renneting Metter – Polo Trade, Italy. During the study, the following parameters were studied: milk fat and protein contents (%), rennet coagulation time (RCT, min), curd firmness (а30, mm) and curd firming time (k20, min). Heterozygous cows for both studied milk proteins: CSN1S1 and CSN2, had higher milk fat and milk protein percentages, 4.71% fat and 3.45% protein in genotype ВС of CSN1S1 and 5.00% fat and 5.33% protein in genotype АВ of CSN2. The milk of cows from different CSN1S1 and CSN2 genotypes was outlined with moderate curd firmness and good coagulation time. Homozygous cows for both studied milk proteins had higher curd firmness (32.31 mm) for the ВВ genotype of CSN1S1 and 31.29 mm for the АА genotype of CSN2.

Методы оценки свертываемости белков молока в системе прогнозирования технологических свойств

Introduction. An integrated monitoring of raw milk’s contents, quality, and security is a key factor that guarantees the high-quality dairy production. As a result, new research methods of rennet clotting are a topical and urgent area of study. The research objective was to systemize and analyze the basic criteria and assessment methods of rennet-induced protein gels in milk systems. Study objects and methods. The authors reviewed the official Russian criteria and methods of raw milk assessment by its rennet coagulation properties. The research also featured the most widespread instrumental approaches used in best practices from around the world. Results and discussion. In Russian and foreign cheese production, milk is always tested for its physicochemical and microbiological indicators, with a mandatory check of its coagulation characteristics. Russian cheese-makers use different modifications of rennet and rennet-fermenting tests based on subjective sensory evaluation, while international scientific trends in this area aim at developing and improving instrumental methods by using a complex indicator MCP. This indicator characterizes the parameters of rennet coagulation with the help of such devices as Formagraph, Lattodinamografo, Optigraph, etc. Formagraph is a simple instrument for measuring rheological properties of milk clotting. It was popular in the late XX century. The resent years saw the development of other methods of instrumental control, including those based on optical measurements. For instance, Ortigraph is one such instrument that receives unified data on coagulation properties of raw milk by using near-infrared waves. Sensory and instrumental methods have their advantages and disadvantages. However, the most significant criteria for a quick test of cheeseability, yield, and quality are the speed of analysis and the comparability and reproducibility of results. Conclusion. To improve cheeseability testing, Russian cheese-makers need to use the international experience, which offers standardized evaluation criteria in combination with various instrumental approaches. However, the integration of foreign regulations and methods into Russian studies is not the only option. The improvement and development of national instrumental methods of evaluating milk protein coagulation is also crucial.

β-Casein variants differently affect bulk milk mineral content, protein composition, and technological traits

Detailed milk protein composition has strong influence on milk quality. This study quantitatively investigated the effect of β-casein variants A1, A2 and B on composition, and technological traits of bulk milk. A total of 171 commercial herds located in northern and central Italy were visited, and 299 bulk milk samples were collected. Traditional milk quality traits, major minerals, milk coagulation properties were assessed. Detailed milk protein composition and β-casein genetic variants were determined by reversed-phase HPLC. Effects of β-casein variants were estimated by fitting a mixed model with variants concentration as a covariate. Results demonstrated that greater concentration of β-casein B is linked with greater protein, casein, and fat content. Likewise, greater concentration of variants A1 and B of β-casein had a significant positive effect on rennet coagulation time and curd firmness, and was linked to a greater amount of Ca and P content than was the A2 variant.

Genetic parameters of differential somatic cell count, milk composition, and cheese-making traits measured and predicted using spectral data in Holstein cows

Mastitis is one of the most prevalent diseases in dairy cattle and is the cause of considerable economic losses. Alongside somatic cell count (SCC), differential somatic cell count (DSCC) has been recently introduced as a new indicator of intramammary infection. The DSCC is expressed as a count or a proportion (%) of polymorphonuclear neutrophils plus lymphocytes (PMN-LYM) in milk somatic cells. These numbers are complemented to total somatic cell count or to 100 by macrophages (MAC). The aim of this study was to investigate the genetic variation and heritability of DSCC, and its correlation with milk composition, udder health indicators, milk composition, and technological traits in Holstein cattle. Data used in the analysis consisted in single test-day records from 2,488 Holstein cows reared in 36 herds located in northern Italy. Fourier-transform infrared (FTIR) spectroscopy was used to predict missing information for some milk coagulation and cheese-making traits, to increase sample size and improve estimation of the genetic parameters. Bayesian animal models were implemented via Gibbs sampling. Marginal posterior means of the heritability estimates were 0.13 for somatic cell score (SCS); 0.11 for DSCC, MAC proportion, and MAC count; and 0.10 for PMN-LYM count. Posterior means of additive genetic correlations between SCS and milk composition and udder health were low to moderate and unfavorable. All the relevant genetic correlations between the SCC traits considered and the milk traits (composition, coagulation, cheese yield and nutrients recovery) were unfavorable. The SCS showed genetic correlations of -0.30 with the milk protein proportion, -0.56 with the lactose proportion and -0.52 with the casein index. In the case of milk technological traits, SCS showed genetic correlations of 0.38 with curd firming rate (k20), 0.45 with rennet coagulation time estimated using the curd firming over time equation (RCTeq), -0.39 with asymptotic potential curd firmness, -0.26 with maximum curd firmness (CFmax), and of -0.31 with protein recovery in the curd. Differential somatic cell count expressed as proportion was correlated with SCS (0.60) but had only 2 moderate genetic correlations with milk traits: with lactose (-0.32) and CFmax (-0.33). The SCS was highly correlated with the log PMN-LYM count (0.79) and with the log MAC count (0.69). The 2 latter traits were correlated with several milk traits: fat (-0.38 and -0.43 with PMN-LYM and MAC counts, respectively), lactose percentage (-0.40 and -0.46), RCTeq (0.53 and 0.41), tmax (0.38 and 0.48). Log MAC count was correlated with k20 (+0.34), and log PMN-LYM count was correlated with CFmax (-0.26) and weight of water curd as percentage of weight of milk processed (-0.26). The results obtained offer new insights into the relationships between the indicators of udder health and the milk technological traits in Holstein cows.

Effect of ultrasound intensity on the functional characteristics of rennet‐coagulated skim milk

AbstractThe objective of this study was to examine the impact of ultrasound energy density (USED) on the functional properties of rennet‐coagulated skim milk. Skim pasteurized milk was ultrasonicated at 106 W and 375 W at two different times (3 and 9 min) to produce different USED levels (190.4, 570.7, 674.3, and 2016.9 J g−1). The rheological and textural properties of ultrasonicated milk samples were determined during the rennet coagulation as compared to nonsonicated skim milk. The rennet coagulation time was doubled when 674.3 J g−1 was applied to skim milk; however, applying 2016.9 J g−1 did not lead to milk coagulation. Additionally, gel firmness of rennet‐coagulated milk increased significantly from 80 g to 130 g when USED boosted from 190.4 to 674.3 J g−1. The coagulum strength and curd‐firming rate decreased significantly when USED elevated to 2016.9 J g−1. The outcome provides that using suitable USED could be utilized efficiently in the cheese industry to prolong the renneting time of milk.Practical ApplicationsThe ultrasound process can be applied to milk before making different dairy products, such as cheese or other dairy products that need rennet for coagulation to improve the characteristics of those products. Also, ultrasound can be utilized to fractionate dairy components to improve the functionality or yield of products.

The influence of mineral granulated complex on milk productivity and quality indicators of cows’ milk

The purpose of the research was to study the effectiveness of the use of rations for freshly calved cows during the increasing the milk yield period with the use of new mineral granulated complexes produced by Uralchem LLC. The results of research on the replacement of the mineral part of the vitamin and mineral premix in the rations of lactating cows with the mineral granular complex developed according to two recipes have been presented in the article. Research has shown that cows of the 1st and 2nd experimental groups during the experiment period gave more milk than their herdmates from the control group by 70,8 (P ≥ 0,95) and 106,2 kg (P ≥ 0,95). Due to the higher milk yield of animals that consumed the granulated complex, the yield of milk fat was greater than that of the control analogues by 3,21 (P ≥ 0,95) and 5,17 kg (P ≥ 0,95), protein by 2,70 and 4,30 kg (P ≥ 0,95). The milk yield of cows of the 1st and 2nd experimental groups for 305 days of lactation was higher than in the control group, respectively, by 205,3 (P ≥ 0,95) and 296,8 kg (P ≥ 0,95). In the milk of cows that consumed the granulated complex, there was a tendency for a higher content of dry matter (0,09 and 0,16 %), lactose (0,01 and 0,06 %), nonfat milk solids (0,09 and 0,07 %), ash (0,05 and 0,05 %) in comparison with analogues from the control group. A similar trend has been established between groups of cows in terms of milk density, acidity and rennet coagulability. The revenue from the sale of milk produced from cows of the 1st and 2nd experimental groups was more than in the control group for the experimental period (120 days) by 2074,6 and 3344,0 rubles and for the 305 days of lactation by 7055,4 and 9950,6 rubles.

Effect of pH and heat treatment on structure, surface characteristics and emulsifying properties of purified camel β-casein

Oil-in-water emulsions (20%/80%, w/w) were stabilised by two types of β-caseins (1 g/L, w/w) extracted by rennet coagulation from camel and cow’s milk, respectively. Both extracts were treated under different ranges of pH (3.0, 6.0 and 9.0) and temperature (25, 65 and 95 °C for 15 min) before emulsification. The emulsifying properties of the proteins were studied by surface and interfacial measurements. Results show that the emulsifying activity (EAI) of camel β-casein is higher than the bovine protein. Yet, both proteins exhibited heat stability and nonsignificant effect of temperature was reported. Conversely, a significant effect of pH on camel β-casein was recorded: at pH 6.0, the lowest values of EAI were measured and explained by the formation of micellar protein structure. Under such conditions, camel β-casein is therefore a novel emulsifying protein with high potential to stabilise oil-in-water interfaces which provides numerous applications for the food chemistry field.

Rheology of buffalo milk rennet coagulation and gels affected by coagulation temperature, CaCl2, pH and milk heat treatment

The effects of coagulation temperature, CaCl2 concentrations, pH and heat treatment on the rennet coagulation time (RCT), setting time (ST), aggregation rate (AR) and gel firmness (GF) of buffalo milk were studied using dynamic small amplitude oscillatory rheology. The influence of heat treatments on protein profile and casein micelle size was analysed by PAGE electrophoresis and dynamic light scattering. Reducing pH of milk from 6.5 to 6.3 caused the largest decrease in RCT and ST, and the largest increase in AR and GF (P < 0.01) compared with the influence of other examined factors. Decreasing the coagulation temperature from 31 to 27 °C had a minor effect on the rennet coagulation parameters. The amount of CaCl2 added to milk treated with mild heat treatment had a negligible effect on the rennet coagulation parameters. High heat treatment induced an increase in casein micelle diameter and substantially delayed the process of milk coagulation.

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.

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

This study investigated the influence of monthly variation on the composition and properties of raw farm milk collected as part of a full-scale cheese-making trial in a region in northern Sweden. In our companion paper, the contribution of on-farm factors to the variation in milk quality attributes is described. In total, 42 dairy farms were recruited for the study, and farm milk samples were collected monthly over 1 yr and characterized for quality attributes of importance for cheese making. Principal component analysis suggested that milk samples collected during the outdoor period (June-September) were different from milk samples collected during the indoor period. Despite the interaction with the milking system, the results showed that fat and protein concentrations were lower in milk collected during May through August, and lactose concentration was higher in milk collected during April through July than for the other months. Concentrations of free fatty acids were generally low, with the highest value (0.86 mmol/100 g of fat) observed in February and the lowest (0.70 mmol/100 g of fat) observed in June. Plasmin and plasminogen-derived activities varied with sampling month without a clear seasonal pattern. The pH of farm tank milk ranged from 6.60 to 6.82, with the lowest and highest values in September and February, respectively. The highest somatic cell count was observed in August (201 × 103 cells/mL) and the lowest in April (143 × 103 cells/mL). The highest value of gel strength, was recorded in December (88 Pa) and the lowest in July (64 Pa). Rennet coagulation time and gel strength were inversely correlated, with the lowest rennet coagulation time value observed in December. Orthogonal projections to latent structures (OPLS) and discriminant analysis adaptation of OPLS identified casein micelle size and total proteolysis as the milk quality attributes with major responses to sampling month, with smaller casein micelle size and higher total proteolysis associated with the outdoor months. Using discriminant analysis adaptation of OPLS to further investigate causes behind the variation in milk traits revealed that there were factors in addition to feeding on pasture that differed between outdoor and indoor months. Because fresh grass was seldom the primary feed in the region during the outdoor period, grazing was not considered the sole reason for the observed difference between outdoor and indoor periods in raw milk quality attributes.

Predicting cow milk quality traits from routinely available milk spectra using statistical machine learning methods

Numerous statistical machine learning methods suitable for application to highly correlated features, as those that exist for spectral data, could potentially improve prediction performance over the commonly used partial least squares approach. Milk samples from 622 individual cows with known detailed protein composition and technological trait data accompanied by mid-infrared spectra were available to assess the predictive ability of different regression and classification algorithms. The regression-based approaches were partial least squares regression (PLSR), ridge regression (RR), least absolute shrinkage and selection operator (LASSO), elastic net, principal component regression, projection pursuit regression, spike and slab regression, random forests, boosting decision trees, neural networks (NN), and a post-hoc approach of model averaging (MA). Several classification methods (i.e., partial least squares discriminant analysis (PLSDA), random forests, boosting decision trees, and support vector machines (SVM)) were also used after stratifying the traits of interest into categories. In the regression analyses, MA was the best prediction method for 6 of the 14 traits investigated [curd firmness at 60 min, αS1-casein (CN), αS2-CN, κ-CN, α-lactalbumin, and β-lactoglobulin B], whereas NN and RR were the best algorithms for 3 traits each (rennet coagulation time, curd-firming time, and heat stability, and curd firmness at 30 min, β-CN, and β-lactoglobulin A, respectively), PLSR was best for pH, and LASSO was best for CN micelle size. When traits were divided into 2 classes, SVM had the greatest accuracy for the majority of the traits investigated. Although the well-established PLSR-based method performed competitively, the application of statistical machine learning methods for regression analyses reduced the root mean square error compared with PLSR from between 0.18% (κ-CN) to 3.67% (heat stability). The use of modern statistical machine learning methods for trait prediction from mid-infrared spectroscopy may improve the prediction accuracy for some traits.

Physicochemical, Microbiological and Technological Properties of Red Deer (Cervus elaphus) Milk during Lactation.

Simple SummaryMilk from red deer is richer in fat and proteins than that of cow or other ruminants. The semi-captive breeding of this species has traditionally focused on meat, velvet or hunting purposes, but recent studies suggested that the high level of nutrients, the promising content of bioactive peptides and the better digestibility than that of milk from other species could open innovative alternatives for the dairy industry. As for other non-commercial mammalian species that are gaining technological interest for the elaboration of dairy products, it is necessary to understand the aptitude and performance of milk from red deer to be used for the production of cheese, fermented milks or other products. Our study aims to assess some chemical, physical, microbiological and technological properties of red deer milk during a lactation period of 18 weeks. The results show that milk from this species is similar to that of other ruminant species whose milk is commercialized. In addition, our results indicate the best period to industrialize the milk during lactation. To the best of our knowledge, this is the first study to explore the benefits of using red deer milk with a technological approach.This study describes chemical, physical, microbiological and technological characteristics of red deer milk and the effect of lactation on these parameters in order to know their potential aptitude to elaborate dairy products. During 18 weeks, milk from five hinds was monitored for composition, bacteriology, somatic cell count (SCC), physical properties and rennet coagulation. Mean values (g/100 g) for fat, protein, lactose and dry matter were 10.4, 7.1, 4.3 and 24.2, respectively, and for urea, 265 mg/100 mL. Except for lactose, a significant increase in these components was observed (p < 0.01) as lactation progressed. The average values for bacteriology and SCC were 5.3 log cfu/mL and 4.7 log cells/mL, respectively. Regarding physical properties, conductivity (mean: 2.8 ms/cm), viscosity (3.1 Cp), coordinates L* (89.9) and a* (−3.1) and milk fat globule diameter (D4,3: 6.1 µm) increased along with lactation while density (1.038 g/mL) decreased (p < 0.01). The pH (6.7), acidity (22.9° Dornic), coordinate b* (8.4) and ethanol stability (66.6% v/v) were stable during the study period. The stage of lactation also has a significant impact on milk coagulation properties and mean curd yield was 3.29 g/10 mL. These results suggest that red deer milk could be a potential innovative source of milk for the dairy industry.

Sezonowe różnice w parametrach jakościowych mleka z tradycyjnego małego gospodarstwa rodzinnego

This research aimed to determine the hygienic quality, physicochemical properties and technological suitability of milk obtained in an extensive, small family farm in western Poland in the spring-summer (grazing) and autumn-winter (indoor) seasons. The farm was operated in the traditional manner where animals spend 7/24 on the pasture in the spring-summer season. The study was performed on forty-eight samples of bulk tank milk collected once a week over one year from 17 cows of the old local Polish black and white lowland breed. Milk was tested for somatic cell count, total bacterial count, basic composition, density, vitamin C content, rennet coagulation time, pH and colour in the CIE L*a*b* system. In the autumn-winter season, a higher somatic cell count, higher protein, fat and lactose levels, longer coagulation time and lower colour parameter a* values were found compared with the spring-summer period. However, no differences as regards the colour parameters L* and b* and vitamin C content were observed between the seasons. Highly significant negative correlations between the colour of the milk and the total bacterial count and somatic cell count were found (P ≤ 0.01). High somatic cells count in studied milk highlights that mastitis and milking hygiene are still a challenging task in small family farms.

Associations between differential somatic cell count and milk yield, quality, and technological characteristics in Holstein cows

The aim of this study was to investigate the associations between differential somatic cell count (DSCC) and milk quality and udder health traits, and for the first time, between DSCC and milk coagulation properties and cheesemaking traits in a population of 1,264 Holstein cows reared in northern Italy. Differential somatic cell count represents the combined proportions of polymorphonuclear neutrophils plus lymphocytes (PMN-LYM) in the total somatic cell count (SCC), with macrophages (MAC) making up the remaining proportion. The milk traits investigated in this study were milk yield (MY), 8 traits related to milk composition and quality (fat, protein, casein, casein index, lactose, urea, pH, and milk conductivity), 9 milk coagulation traits [3 milk coagulation properties (MCP) and 6 curd firming (CF) traits], 7 cheesemaking traits, 3 cheese yield (CY) traits, and 4 milk nutrient recovery in the curd (REC) traits. A linear mixed model was fitted to explore the associations between SCS combined with DSCC and the aforementioned milk traits. An additional model was run, which included DSCC expressed as the PMN-LYM and MAC counts, obtained by multiplying the percentage of PMN-LYM and MAC by SCC in the milk for each cow in the data set. The unfavorable association between SCS and milk quality and technological traits was confirmed. Increased DSCC was instead associated with a linear increase in MY, casein index, and lactose proportion and a linear decrease in milk fat and milk conductivity. Accordingly, DSCC was favorably associated with all MCP and CF traits (with the exception of the time needed to achieve maximum, CF), particularly with rennet coagulation time, and it always displayed linear relationships. Differential somatic cell count was also positively associated with the recovery of milk nutrients in the curd (protein, fat, and energy), which increased linearly with increasing DSCC. The PMN-LYM count was rarely associated with milk traits, even though the pattern observed confirmed the results obtained when both SCS and DSCC were included in the model. The MAC count, however, showed the opposite pattern: MY, casein index, and lactose percentage decreased and milk conductivity increased with an increasing MAC count. No significant association was found between PMN-LYM count and MCP, CF, CY, and REC traits, whereas MAC count was unfavorably associated with MCP, CF traits, some CY traits, and all REC traits. Our results showed that the combined information derived from SCS and DSCC might be useful to monitor milk quality and cheesemaking-related traits.