Effect of composition on coagulation,curd firming,and syneresis of goat milk

The present study investigated the effect of different levels of fat, protein, and casein on (1) traditional milk coagulation properties, and (2) curd firming over time parameters of 1,272 goat milk samples. Relationships between fat, protein, and casein and some indicators of udder health status (lactose, pH, somatic cells, bacterial count, and NaCl) were also investigated. Traditional milk coagulation properties and modeled curd-firming parameters were analyzed using a mixed model that considered the effect of days in milk, parity, farm, breed, the pendulum of the instrument, and different levels of fat, protein, and casein. Fat, protein, and casein were also tested with the same model but one at a time. Information provided by this model demonstrated the effect of one component alone, without contemporarily considering that of the others. The results allowed us to clarify the effect of the major milk nutrients on coagulation, curd firming, and syneresis ability of goat milk. In particular, milk rich in fat was associated with better coagulation properties, whereas milk rich in protein was associated with delayed coagulation. The high correlation of fat with protein and casein contents suggests that the effect of fat on the cheese-making process is also attributable to the effects of protein and casein. When only protein or only casein was included in the statistical model, the pattern of coagulation, curd firming, and syneresis was almost indistinguishable. The contemporary inclusion of protein and casein in the statistical model did not generate computing problems and allowed us to better characterize the role of protein and casein. Consequently, given their strong association, we also tested the effect of casein-to-protein ratio (i.e., casein number). Higher values of casein number led to a general improvement in the coagulation ability of milk, suggesting that casein-to-protein ratio, not just protein or casein, should be considered when milk is destined for cheese making. These results are especially useful for dairy farmers who want to increase their profits by improving the technological quality of the milk produced.     

Composition,coagulation properties,and predicted cheesemaking traits of bulk goat milk from different farming systems,breeds, and stages of production

At the global level, the quantity of goat milk produced and its gross production value have increased considerably over the last 2 decades. Although many scientific papers on this topic have been published, few studies have been carried out on bulk goat milk samples. The aim of the present study was to investigate in the field the effects of farming system, breed type, individual flock, and stage of production on the composition, coagulation properties (MCP), curd firming over time parameters (CF_t), predicted cheese yield (CY%), and nutrient recovery traits (REC) of 432 bulk milk samples from 161 commercial goat farms in Sardinia, Italy. We found that the variance due to individual flock was of the same order as the residual variance for almost all composition and cheesemaking traits. With regard to the fixed effects, the effect of farming system on bulk milk variability was not highly significant for the majority of traits (it was lower than individual flock), whereas the effects of breed type and stage of production were much higher. More specifically, the intensive farms produced milk with the best concentrations of almost all constituents, whereas extensive farms exhibited faster rennet coagulation times, a slower rate of curd firming, lower potential curd firmness, and lower percentages of fat and energy recoveries in the fresh curd. Farms rearing the local breed, Sarda, alone or together with the Maltese breed, produced milk with the best concentrations of fat and protein, superior curd firmness, and better predicted percentage of fresh curd (CY_CURD) and recovery traits. The results show the potential of both types of breed, either for their quantitative (specialized breeds) or their qualitative (local breeds) attributes. As expected, the concentrations of fat, protein fractions, and lactose were influenced by the stage of production, with samples collected in the early stage of production (in February and March) having a greater quantity of the main constituents. Somatic cells reached the highest levels in the late stage of production, which corresponds to the goats' advanced stage of lactation (June–July), although no differences were present in the logarithmic bacterial counts between the early and late stages. Regarding cheesemaking potential, bulk milk samples of the late stage were characterized by delayed rennet coagulation and curd firming times, the lowest values of curd firmness, and a general reduction in CY%, and REC traits. In conclusion, we highlight several issues regarding the effects of the most important sources of variation on bulk goat milk, and point to some critical factors relevant for improving dairy goat farming and milk production.     

Cheese yield,cheesemaking efficiency,and daily production of 6 breeds of goats

Little is known about the complex process of cheesemaking at the individual level of dairy goats because of the difficulties of producing a high number of model cheeses. The objectives of this work were (1) to study the cheesemaking ability of goat milk; (2) to investigate the variability of cheesemaking-related traits among different farms; (3) to assess the effects of stage of lactation and parity; and (4) to compare 6 breeds of goat (Saanen and Camosciata delle Alpi for the Alpine type; Murciano-Granadina, Maltese, Sarda and Sarda Primitiva for the Mediterranean type) for their cheesemaking ability. For each goat (n = 560) we studied (1) 8 milk quality traits (fat, protein, total solids, casein, lactose, pH, somatic cell score, and bacterial count); (2) 4 milk nutrient recovery traits (fat, protein, total solids, and energy) in curd; (3) 3 actual cheese yield traits (fresh cheese, cheese solids, and cheese water); (4) 2 theoretical cheese yield values (fresh cheese and cheese solids) and the related cheesemaking efficiencies; and (5) daily milk yield and 3 daily cheese yield traits (fresh cheese, cheese solids, and water retained in the curd). With respect to individual animal factors, farm was not particularly important for recovery traits or actual and theoretical cheese yield and estimates of efficiency, whereas it highly influenced daily productions. Parity of goats influenced daily cheese production, whereas DIM slightly affected recovery as well as percent and daily cheese yield traits. Breed was the most important source of variation for almost all cheesemaking traits. Compared with those of Alpine type, the 4 Mediterranean breeds had, on average, lower daily milk and cheese productions, greater actual and theoretical cheese yield, and higher recovery of nutrients in the curd. Among Alpine type, Camosciata delle Alpi was characterized by greater nutrients recovery than Saanen. Within the 4 Mediterranean types, the 3 Italians produced much less milk per day, with much more fat and protein and greater recovery traits than the Murciano-Granadina, resulting in greater actual cheese yield. Within the Italian breeds, milk from Sarda and Sarda Primitiva was characterized by lower daily yields, higher protein and fat content, and greater recoveries of nutrients than Maltese goats. These results confirmed the potential of goat milk for cheese production and could be useful to give new possibilities and direction in breeding programs.     

Effects of protein and fat levels in milk on Cheddar cheese yield

Over a 14-month period, bulk tank milk was collected twice a week and was adjusted with cream and skim milk powder to provide six levels each of fat and protein varying from 3·0 to 4·0%. Milk samples were analyzed for total solids, fat, protein, casein, lactose and somatic cell count and were used for laboratory-scale cheesemaking. Data obtained from the milk input and the cheese output were used to determine actual, moisture adjusted, theoretical yield, and efficiency of yield. Least squares analyses of data indicated that higher cheese yields were obtained from higher fat and protein contents in milk. Higher yield efficiency was associated with higher ratios of protein to fat and casein to fat. Regression analysis indicated that a percentage increase in fat content in milk resulted in an increase of 1·23–1·37% in moisture adjusted yield in the different protein levels. For a similar increase of protein in milk, there were 1·80–2·04% increase in moisture adjusted yields in different fat levels.     

Valuation of milk composition and genotype in cheddar cheese production using an optimization model of cheese and whey production

A mass balance optimization model was developed to determine the value of the κ-casein genotype and milk composition in Cheddar cheese and whey production. Inputs were milk, nonfat dry milk, cream, condensed skim milk, and starter and salt. The products produced were Cheddar cheese, fat-reduced whey, cream, whey cream, casein fines, demineralized whey, 34% dried whey protein, 80% dried whey protein, lactose powder, and cow feed. The costs and prices used were based on market data from March 2004 and affected the results. Inputs were separated into components consisting of whey protein, ash, casein, fat, water, and lactose and were then distributed to products through specific constraints and retention equations. A unique 2-step optimization procedure was developed to ensure that the final composition of fat-reduced whey was correct. The model was evaluated for milk compositions ranging from 1.62 to 3.59% casein, 0.41 to 1.14% whey protein, 1.89 to 5.97% fat, and 4.06 to 5.64% lactose. The κ casein genotype was represented by different retentions of milk components in Cheddar cheese and ranged from 0.715 to 0.7411 kg of casein in cheese/kg of casein in milk and from 0.7795 to 0.9210 kg of fat in cheese/kg of fat in milk. Milk composition had a greater effect on Cheddar cheese production and profit than did genotype. Cheese production was significantly different and ranged from 9,846 kg with a high-casein milk composition to 6,834 kg with a high-fat milk composition per 100,000 kg of milk. Profit (per 100,000 kg of milk) was significantly different, ranging from $70,586 for a high-fat milk composition to $16,490 for a low-fat milk composition. However, cheese production was not significantly different, and profit was significant only for the lowest profit ($40,602) with the κ-casein genotype. Results from this model analysis showed that the optimization model is useful for determining costs and prices for cheese plant inputs and products, and that it can be used to evaluate the economic value of milk components to optimize cheese plant profits.     

Factors affecting variation of different measures of cheese yield and milk nutrient recovery from an individual model cheese-manufacturing process

Cheese yield (CY) is the most important technological trait of milk, because cheese-making uses a very high proportion of the milk produced worldwide. Few studies have been carried out at the level of individual milk-producing animals due to a scarcity of appropriate procedures for model-cheese production, the complexity of cheese-making, and the frequent use of the fat and protein (or casein) contents of milk as a proxy for cheese yield. Here, we report a high-throughput cheese manufacturing process that mimics all phases of cheese-making, uses 1.5-L samples of milk from individual animals, and allows the simultaneous processing of 15 samples per run. Milk samples were heated (35°C for 40 min), inoculated with starter culture (90 min), mixed with rennet (51.2 international milk-clotting units/L of milk), and recorded for gelation time. Curds were cut twice (10 and 15 min after gelation), separated from the whey, drained (for 30 min), pressed (3 times, 20 min each, with the wheel turned each time), salted in brine (for 60 min), weighed, and sampled. Whey was collected, weighed, and sampled. Milk, curd, and whey samples were analyzed for pH, total solids, fat content, and protein content, and energy content was estimated. Three measures of percentage cheese yield (%CY) were calculated: %CY_CURD, %CY_SOLIDS, and %CY_WATER, representing the ratios between the weight of fresh curd, the total solids of the curd, and the water content of the curd, respectively, and the weight of the milk processed. In addition, 3 measures of daily cheese yield (dCY, kg/d) were defined, considering the daily milk yield. Three measures of nutrient recovery (REC) were computed: REC_FAT, REC_PROTEIN, and REC_SOLIDS, which represented the ratio between the weights of the fat, protein, and total solids in the curd, respectively, and the corresponding components in the milk. Energy recovery, REC_ENERGY, represented the energy content of the cheese compared with that in the milk. This procedure was used to process individual milk samples obtained from 1,167 Brown Swiss cows reared in 85 herds of the province of Trento (Italy). The assessed traits exhibited almost normal distributions, with the exception of REC_FAT. The average values (± SD) were as follows: %CY_CURD = 14.97 ± 1.86, %CY_SOLIDS = 7.18 ± 0.92, %CY_WATER = 7.77 ± 1.27, dCY_CURD = 3.63 ± 1.17, dCY_SOLIDS = 1.74 ± 0.57, dCY_WATER = 1.88 ± 0.63, REC_FAT = 89.79 ± 3.55, REC_PROTEIN = 78.08 ± 2.43, REC_SOLIDS = 51.88 ± 3.52, and REC_ENERGY = 67.19 ± 3.29. All traits were highly influenced by herd-test-date and days in milk of the cow, moderately influenced by parity, and weakly influenced by the utilized vat. Both %CY_CURD and dCY_CURD depended not only on the fat and protein (casein) contents of the milk, but also on their proportions retained in the curd; the water trapped in curd presented an higher variability than that of %CY_SOLIDS. All REC traits were variable and affected by days in milk and parity of the cows. The described model cheese-making procedure and the results obtained provided new insight into the phenotypic variation of cheese yield and recovery traits at the individual level.     

Genetic parameters of different measures of cheese yield and milk nutrient recovery from an individual model cheese-manufacturing process

Cheese yield (CY) is an important technological trait in the dairy industry, and the objective of this study was to estimate the genetic parameters of cheese yield in a dairy cattle population using an individual model-cheese production procedure. A total of 1,167 Brown Swiss cows belonging to 85 herds were sampled once (a maximum of 15 cows were sampled per herd on a single test day, 1 or 2 herds per week). From each cow, 1,500 mL of milk was processed according to the following steps: milk sampling and heating, culture addition, rennet addition, gelation-time recording, curd cutting, whey draining and sampling, wheel formation, pressing, salting in brine, weighing, and cheese sampling. The compositions of individual milk, whey, and curd samples were determined. Three measures of percentage cheese yield (%CY) were calculated: %CY_CURD, %CY_SOLIDS, and %CY_WATER, which represented the ratios between the weight of fresh curd, the total solids of the curd, and the water content of the curd, respectively, and the weight of the milk processed. In addition, 3 measures of daily cheese yield (dCY, kg/d) were defined, considering the daily milk yield. Three measures of nutrient recovery (REC) were computed: REC_FAT, REC_PROTEIN, and REC_SOLIDS, which represented the ratio between the weights of the fat, protein, and total solids in the curd, respectively, and the corresponding nutrient in the milk. Energy recovery, REC_ENERGY, represented the energy content of the cheese versus that in the milk. For statistical analysis, a Bayesian animal model was implemented via Gibbs sampling. The effects of parity (1 to ≥4), days in milk (6 classes), and laboratory vat (15 vats) were assigned flat priors; those of herd-test-date, animal, and residual were given Gaussian prior distributions. Intra-herd heritability estimates of %CY_CURD, _%CY_SOLIDS, and %CY_WATER ranged from 0.224 to 0.267; these were larger than the estimates obtained for milk yield (0.182) and milk fat content (0.122), and similar to that for protein content (0.275). Daily cheese yields showed heritability estimates similar to those of daily milk yield. The trait %CY_WATER showed a highly positive genetic correlation with %CY_SOLIDS (0.87), whereas their phenotypic correlation was moderate (0.37), and the fat and protein contents of milk showed high genetic correlations with %CY traits. The heritability estimates of REC_PROTEIN and REC_FAT were larger (0.490 and 0.208, respectively) than those obtained for the protein and fat contents of milk, and the genetic relationships between REC_PROTEIN and REC_FAT with milk protein and fat content were low or moderate; REC_PROTEIN and REC_FAT were moderately correlated with the %CY traits and highly correlated with REC_SOLIDS and REC_ENERGY. Both REC_SOLIDS and REC_ENERGY were heritable (0.274 and 0.232), and showed high correlations with each other (0.96) and with the %CY traits (0.83 to 0.97). Together, these findings demonstrate the existence of economically important, genetically determined variability in cheese yield that does not depend solely upon the fat and protein contents of milk, but also relies on the ability of the coagulum to retain the highest possible proportions of the available protein, fat, and water. Exploitation of this interesting genetic variation does not seem to be feasible through direct measurement of the phenotype in cows at the population level. Instead, further research is warranted to examine possible means for indirect prediction, such as through assessing the mid-infrared spectra of milk samples.     

Predictive formulas for different measures of cheese yield using milk composition from individual goat samples

The objective of this study was to develop formulas based on milk composition of individual goat samples for predicting cheese yield (%CY) traits (fresh curd, milk solids, and water retained in the curd). The specific aims were to assess and quantify (1) the contribution of major milk components (fat, protein, and casein) and udder health indicators (lactose, somatic cell count, pH, and bacterial count) on %CY traits (fresh curd, milk solids, and water retained in the curd); (2) the cheese-making method; and (3) goat breed effects on prediction accuracy of the %CY formulas. The %CY traits were analyzed in duplicate from 600 goats, using an individual laboratory cheese-making procedure (9-MilCA method; 9 mL of milk per observation) for a total of 1,200 observations. Goats were reared in 36 herds and belonged to 6 breeds (Saanen, Murciano-Granadina, Camosciata delle Alpi, Maltese, Sarda, and Sarda Primitiva). Fresh %CY (%CY_CURD), total solids (%CY_SOLIDS), and water retained (%CY_WATER) in the curd were used as response variables. Single and multiple linear regression models were tested via different combinations of standard milk components (fat, protein, casein) and indirect udder health indicators (UHI; lactose, somatic cell count, pH, and bacterial count). The 2 %CY observations within animal were averaged, and a cross-validation (CrV) scheme was adopted, in which 80% of observations were randomly assigned to the calibration (CAL) set and 20% to the validation (VAL) set. The procedure was repeated 10 times to account for sampling variability. Further, the model presenting the best prediction accuracy in CrV (i.e., comprehensive formula) was used in a secondary analysis to assess the accuracy of the %CY predictive formulas as part of the laboratory cheese-making procedure (within-animal validation, WAV), in which the first %CY observation within animal was assigned to CAL, and the second to the VAL set. Finally, a stratified CrV (SCrV) was adopted to assess the %CY traits prediction accuracy across goat breeds, again using the best model, in which 5 breeds were included in CAL and the remaining one in the VAL set. Fitting statistics of the formulas were assessed by coefficient of determination of validation (R²_VAL) and the root mean square error of validation (RMSE_VAL). In CrV, the formula with the best prediction accuracy for all %CY traits included fat, casein, and UHI (R²_VAL = 0.65, 0.96, and 0.23 for %CY_CURD, %CY_SOLIDS, and %CY_WATER, respectively). The WAV procedure showed R²_VAL higher than those obtained in CrV, evidencing a low effect of the 9-MilCA method and, indirectly, its high repeatability. In the SCrV, large differences for %CY_CURD and %CY_WATER among breeds evidenced that the breed is a fundamental factor to consider in %CY predictive formulas. These results may be useful to monitor milk composition and quantify the influence of milk traits in the composite selection indices of specific breeds, and for the direct genetic improvement of cheese production.     

Effects of the detailed protein composition of milk on curd yield and composition measured by model micro-cheese curd making of individual milk samples

The effect of the contents of casein (CN) and whey protein fractions on curd yield (CY) and composition was estimated using 964 individual milk samples. Contents of α_S1-CN, α_S2-CN, β-CN, γ-CN, glycosylated κ-CN (Gκ-CN), unglycosylated κ-CN, β-LG, and α-LA of individual milk samples were measured using reversed-phase HPLC. Curd yield and curd composition were measured by model micro-cheese curd making using 25 mL of milk. Dry matter CY (DMCY) was positively associated with all casein fractions but especially with α_S1-CN and β-CN. Curd moisture decreased at increasing β-CN content and increased at increasing γ-CN and Gκ-CN content. Due to their associations with moisture, Gκ-CN and β-CN were the fractions with the greatest effect on raw CY, which decreased by 0.66% per 1-standard deviation (SD) increase in the content of β-CN and increased by 0.62% per 1-SD increase in the content of Gκ-CN. The effects due to variation in percentages of the casein fractions in total casein were less marked than those exerted by contents. A 1-SD increase in β-CN percentage in casein (+3.8% in casein) exerted a slightly negative effect on DMCY (β = ?0.05%). Conversely, increasing amounts of α_S1-CN percentage were associated with a small increase in DMCY. Hence, results suggest that, at constant casein and whey protein contents in milk, the DMCY depends to a limited extent on the variation in the α_S1-CN:β-CN ratio. κ-Casein percentage did not affect DMCY, indicating that the positive relationship detected between the content of κ-CN and DMCY can be attributed to the increase in total casein resulting from the increased amount of κ-CN and not to variation in κ-CN relative content. However, milk with increased Gκ-CN percentage in κ-CN also shows increased raw CY and produces curds with increased moisture content. Curd yield increased at increasing content and relative proportion of β-LG in whey protein, but this is attributable to an improved capacity of the curd to retain water. Results obtained in this study support the hypothesis that, besides variation in total casein and whey protein contents, variation in protein composition might affect the cheese-making ability of milk, but this requires further studies.     

Use of milk protein concentrate to standardize milk composition in Italian citric Mozzarella cheese making

To better exploit manufacturing facilities and standardize cheese quality, milk composition could be standardized by fortifying its protein content with a milk protein concentrate (MPC) addition so avoiding partially skimming the milk. With this aim Mozzarella cheese was obtained adding citric acid into milk standardized at 4% protein and a fat to protein ratio of 1.0. Protein fortification was obtained adding MPC produced by ultrafiltration. Milk, whey, curd, cheese and stretching water were weighed and analysed for total solid, fat and protein content, to measure component recovery and yield. Yield increase (from 13.8% to 16.7%) was due to the higher recovery of the milk total solids and proteins in MPC cheese (48.2 and 78.3%, respectively) and to the slightly higher cheese moisture, obtained with a little modification of the cheese technology when adding MPC. Milk fat in cheese was lower than that reported in literature. Hot water stretching of the curd resulted in very low losses (1%) of protein and considerable losses (14%) of fat for both control and MPC cheeses. The likely reasons of this low recovery are discussed and it can be supposed that a further cheese yield increase is possible by changing the curd stretching procedures.     

The mineral profile affects the coagulation pattern and cheese-making efficiency of bovine milk

Natural variations in milk minerals, their relationships, and their associations with the coagulation process and cheese-making traits present an opportunity for the differentiation of milk destined for high-quality natural products, such as traditional specialties or Protected Designation of Origin (PDO) cheeses. The aim of this study was to quantify the effects of the native contents of Ca, P, Na, K, and Mg on 18 traits describing traditional milk coagulation properties (MCP), curd firming over time (CF_t) equation parameters, cheese yield (CY) measures, and nutrient recoveries in the curd (REC) using models that either included or omitted the simultaneous effects of milk fat and casein contents. The results showed that, by including milk fat and casein and the minerals in the statistical model, we were able to determine the specific effects of each mineral on coagulation and cheese-making efficiency. In general, about two-thirds of the apparent effects of the minerals on MCP and the CF_t equation parameters are actually mediated by their association with milk composition, especially casein content, whereas only one-third of the effects are direct and independent of milk composition. In the case of cheese-making traits, the effects of the minerals were mediated only negligibly by their association with milk composition. High Ca content had a positive effect on the coagulation pattern and cheese-making traits, favoring water retention in the curd in particular. Phosphorus positively affected the cheese-making traits in that it was associated with an increase in CY in terms of curd solids, and in all the nutrient recovery traits. However, a very high P content in milk was associated with lower fat recovery in the curd. The variation in the Na content in milk only mildly affected coagulation, whereas with regard to cheese-making, protein recovery was negatively associated with high concentrations of this mineral. Potassium seemed not to be actively involved in coagulation and the cheese-making process. Magnesium content tended to slow coagulation and reduce CY measures. Further studies on the relationships of minerals with casein and protein fractions could deepen our knowledge of the role of all minerals in coagulation and the cheese-making process.     

Effect of natural cheese characteristics on process cheese properties

Natural cheese is the major ingredient utilized to manufacture process cheese. The objective of the present study was to evaluate the effect of natural cheese characteristics on the chemical and functional properties of process cheese. Three replicates of 8 natural (Cheddar) cheeses with 2 levels of calcium and phosphorus, residual lactose, and salt-to-moisture ratio (S/M) were manufactured. After 2 mo of ripening, each of the 8 natural cheeses was converted to 8 process cheese foods that were balanced for their composition, including moisture, fat, salt, and total protein. In addition to the standard compositional analysis (moisture, fat, salt, and total protein), the chemical properties (pH, total Ca, total P, and intact casein) and the functional properties [texture profile analysis (TPA), modified Schreiber melt test, dynamic stress rheometry, and rapid visco analysis] of the process cheese foods were determined. Natural cheese Ca and P, as well as S/M, significantly increased total Ca and P, pH, and intact casein in the process cheese food. Natural cheese Ca and P and S/M also significantly affected the final functional properties of the process cheese food. With the increase in natural cheese Ca and P and S/M, there was a significant increase in the TPA-hardness and the viscous properties of process cheese food, whereas the meltability of the process cheese food significantly decreased. Consequently, natural cheese characteristics such as Ca and P and S/M have a significant influence on the chemical and the final functional properties of process cheese.     

Effect of frozen storage on the proteolytic and rheological properties of soft caprine milk cheese

Freezing and long-term frozen storage had minimal impact on the rheology and proteolysis of soft cheese made from caprine milk. Plain soft cheeses were obtained from a grade A goat dairy in Georgia and received 4 storage treatments: fresh refrigerated control (C), aged at 4°C for 28 d; frozen control (FC), stored at −20°C for 2 d before being thawed and aged in the same way as C cheese; and 3-mo frozen (3MF), or 6-mo frozen (6MF), stored at −20°C for 3 or 6 mo before being thawed and aged. Soft cheeses had fragile textures that showed minimal change after freezing or over 28 d of aging at 4°C. The only exceptions were the FC cheeses, which, after frozen storage and aging for 1 d at 4°C, were significantly softer than the other cheeses, and less chewy than the other frozen cheeses. Moreover, after 28 d of aging at 4°C, the FC cheeses tended to have the lowest viscoelastic values. Slight variation was noted in protein distribution among the storage treatment, although no significant proteolysis occurred during refrigerated aging. The creation and removal of ice crystals in the cheese matrix and the limited proteolysis of the caseins showed only slight impact on cheese texture, suggesting that frozen storage of soft cheeses may be possible for year-round supply with minimal loss of textural quality.     

原料乳中蛋白质与脂肪比例对 Mozzarella干酪品质的影响

采用3×3拉丁方试验设计,3个奶酪槽中原料乳的蛋白质与脂肪质量比分别为1∶1,1.2∶1,1.3∶1(通过添加脱脂干奶粉调整蛋白质含量)。研究蛋白质与脂肪比例对Mozzarella干酪的品质的影响。结果表明,随着原料乳中蛋白质脂肪比例的增加,干酪的含水量、油脂析出性显著降低(P<0.05),干酪的弹性显著升高(P<0.05),蛋白质与脂肪比例对Mozzarella干酪的蛋白质水解没有显著的影响。     

Impact of seasonal changes in ovine milk on composition and yield of a hard-pressed cheese

A hard-pressed, brined cheese was produced from frozen ovine milk collected in February, May, and August. Solids in the milk decreased as the season progressed. This was a result of high solids in early-lactation milk and low solids in August milk because of hot weather and poorer quality pastures. Casein as a percentage of true protein and the casein to fat ratio were higher in May and August milk. Fat in the cheese from February milk was higher and total protein was lower than in May and August. Milk, whey, and press whey composition were influenced by season and followed the trends of milk composition. Fat recovery in the cheeses ranged from 83.2 to 84.2%. Protein recovery in the cheeses was not affected by season. Cheese yield from February milk was higher than from May and August milk and was a result of higher casein and fat in the milk.     

Impact of milk preacidification with CO2 on cheddar cheese composition and yield

Preacidification of milk for cheese making may have a beneficial impact on increasing proteolysis during cheese aging. Unlike other acids, CO(2) can easily be removed from whey. The objectives of this work were to determine the effect of milk preacidification on Cheddar cheese composition, the recovery of individual milk components, and yield. Carbon dioxide was injected inline after the cooling section of the pasteurizer. Cheeses with and without added CO(2) were made simultaneously from the same batch of milk. This procedure was replicated 3 times. Carbon dioxide in the cheese milk was about 1600 ppm, which resulted in a milk pH of about 5.9 at 31 degrees C. The starter culture and coagulant addition rates were the same for both the CO(2) treatment and the control. The whey pH at draining of the CO(2) treatment was lower than the control. Total make time was shorter for the CO(2) treatment compared with the control. Cheese manufactured from milk acidified with CO(2) retained less of the total calcium and fat than the control cheese. The higher fat loss was primarily in the whey at draining. Preacidification with CO(2) did not alter the crude protein recovery in the cheese. The CO(2) treatment resulted in a higher added salt recovery in the cheese and produced a cheese that contained too much salt. Considering the higher added salt retention, the salt application rate could be lowered to achieve a typical cheese salt content. Cheese yield efficiency of the CO(2) treated milk was 4.4% lower than the control due to fat loss. Future work will focus on modifying the make procedure to achieve a normal fat loss into the whey when CO(2) is added to milk.     

Effect of milk protein standardization using different methods on the composition and yields of Cheddar cheese

Two sets of Cheddar cheese were made in which the milk protein level (%, wt/wt) was increased from 3.3 (Control A, CA) to 3.6 (set A) or from 3.3 (control B, CB) to 4.0 (set B) by the addition of phosphocasein (PC), milk protein concentrate (MPC), or freshly prepared ultrafiltered milk retentate (UFR). The cheeses were denoted CA, PCA, MPCA, and UFRA from set A, and CB, PCB, MPCB, and UFRB, from set B, respectively. The level of cheese moisture decreased significantly on increasing milk protein level from 3.3 to 3.6 or 4.0% (wt/wt), but was not affected significantly by the method of protein standardization. The percentage milk fat recovered to cheese increased significantly on increasing the level of milk protein from 3.3 to 3.6% (wt/wt) with PC, and from 3.3 to 4.0% (wt/wt) with PC, MPC, and UFR. Increasing milk protein level from 3.3 to 4.0% (wt/wt) with PC significantly increased the percentage of milk protein recovered to cheese. Actual cheese yield increased significantly with milk protein level. The yield of cheese per 100 kg of milk normalized to reference levels of fat (3.4%, wt/wt) and casein (2.53%, wt/wt) indicated no significant effects of protein content or standardization treatment on yield. However, the moisture-adjusted yield per 100 kg of milk with reference levels of fat and casein increased significantly on increasing the protein content from 3.3 to 3.6% (wt/wt) with MPC and from 3.3 to 4.0% (wt/wt) with PC, MPC, and UFR.     

Effects of protein and fat levels in milk on cheese and whey compositions

Bulk tank milk was standardised to six levels of fat (3·0, 3·2, 3·4, 3·6, 3·8, 4·0%) and similarly to six levels of protein, thus giving a total of 36 combinations in composition. Milk was analyzed for total solids, fat, protein, casein, lactose and somatic cell count and was used to make laboratory-scale cheese. Cheese samples from each batch were assayed for total solids, fat, protein and salt. Losses of milk components in the whey were also determined. Least squares analysis of data indicated that higher protein level in milk was associated with higher protein and lower fat contents in cheese. This was accompanied by lower total solids (higher moisture) in cheese. Inversely, higher fat level in milk gave higher fat and lower protein and moisture contents in cheese. Higher fat level in milk resulted in lower retention of fat in cheese and more fat losses in the whey. Higher protein level in milk gave higher fat retention in cheese and less fat losses in the whey. Regression analysis showed that cheese fat increased by 4·22%, while cheese protein decreased by 2·61% for every percentage increase in milk fat. Cheese protein increased by 2·35%, while cheese fat decreased by 6·14% per percentage increase in milk protein. Milk with protein to fat ratio close to 0·9 would produce a minimum of 50% fat in the dry matter of cheese.     

Farm and factory production of goat cheese whey results in distinct chemical composition

To analyze differences in fat and protein content in cheese whey (CW) manufactured in cheese-making factories and farms, goat CW samples were obtained from 60 cheese-making farms and 20 cheese factories. Gross composition of samples was analyzed by using an MIRIS device (MIRIS Inc., Uppsala, Sweden), whey protein composition was subjected to electrophoretic analysis, and fatty acid composition was analyzed via gas chromatography. Goat CW from farms contained higher dry matter content (70.6 vs. 50.8 g/L, farms vs. cheese factories, respectively) and a higher fat percentage (10.5 vs. 1.2% over dry matter, farms vs. cheese factories, respectively) than CW from cheese factories. Analysis of individual proteins showed that CW from farms contained higher concentrations of lactoferrin (0.4 vs. 0.2 mg/mL of CW, farms vs. cheese factories, respectively) and caprine serum albumin (0.6 vs. 0.4 mg/mL of whey, farms vs. cheese factories, respectively) than CW from cheese factories. No differences were observed in the fatty acid profile. The main fatty acids present in goat CW were C16:0, C18:1, C14:0, and C18:0. Thus, the origin of CW affects gross composition and the protein profile, but not the fatty acid profile.