Yield of Cheddar cheese manufactured from milk concentrate by ultrafiltration

There are basically two methods by which the manufacture of cheese from milk concentrated by ultrafiltration can increase yields. Firstly, the procedure can increase the weight of certain water-soluble, solids-non-fat components (mainly whey proteins) in the cheese. This extra solids-non-fat may allow extra water to be incorporated into the product without a decline in quality. Secondly, if suitable equipment can be designed, manufacture of cheese from concentrated milk can lead to a reduction in the losses of insoluble casein, fat and fines. The present study suggests that with a fivefold concentration of milk by ultrafiltration, and with the same losses of insoluble casein, fat and fines as with conventional cheesemaking, the yield of Cheddar is increased by around 4.5%. About half this increase is due to water-soluble, solids-non-fat components; the remainder is due to water. With the elimination of all losses of insoluble casein and fines the gain in product is predicted to be around 6% while increases in the fat retention to 95% would bring the yield advantage to about 8%. However, it is suggested that the elimination of casein fines losses may be difficult to achieve in commercial-scale, ultrafiltration cheesemaking equipment and that reductions in fat percentages in the whey are of little financial advantage to companies that recover whey fat .     

Effect of goat milk composition on cheesemaking traits and daily cheese production

Cheese yield is strongly influenced by the composition of milk, especially fat and protein contents, and by the efficiency of the recovery of each milk component in the curd. The real effect of milk composition on cheesemaking ability of goat milk is still unknown. The aims of this study were to quantify the effects of milk composition; namely, fat, protein, and casein contents, on milk nutrient recovery in the curd, cheese yield, and average daily yield. Individual milk samples were collected from 560 goats of 6 different breeds. Each sample was analyzed in duplicate using the 9-laboratory milk cheesemaking assessment, a laboratory method that mimicked cheesemaking procedures, with milk heating, rennet addition, coagulation, curd cutting, and draining. Data were submitted to statistical analysis; results showed that the increase of milk fat content was associated with a large improvement of cheese yield because of the higher recovery of all milk nutrients in the curd, and thus a higher individual daily cheese yield. The increase of milk protein content affected the recovery of fat, total solids, and energy in the curd. Casein number, calculated as casein-to-protein ratio, did not affect protein recovery but strongly influenced the recovery of fat, showing a curvilinear pattern and the most favorable data for the intermediate values of casein number. In conclusion, increased fat and protein contents in the milk had an effect on cheese yield not only for the greater quantity of nutrients available but also for the improved efficiency of the recovery in the curd of all nutrients. These results are useful to improve knowledge on cheesemaking processes in the caprine dairy industry.     

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 sheep alpha s1-casein CC, CD and DD genotypes on milk composition and cheesemaking properties.

The effects of sheep alpha s1-casein CC, CD and DD genotypes on milk composition and cheese yield were studied. Processed bulk milk was collected from three groups of 15 ewes, carrying alpha s1-casein CC, CD and DD genotypes. CC milk was higher in casein content than CD or DD milk (+3.5 and +8.6% respectively), and had a higher protein: fat ratio and a smaller casein micelle diameter. In addition, DD milk had a significantly lower alpha s1-casein content. The main differences were in curd formation: CC milk had better renneting properties. Cheesemaking trials, carried out in a pilot plant, showed that CC milk had better cheesemaking characteristics than DD milk, while CD milk was intermediate. Both 1 d old and fully ripened cheeses had different fat: dry matter ratios and alpha s1-I-casein electrophoretic mobilities: these were lower for DD cheese. As a consequence, these genotypes could be considered as markers of milk and/or cheese quality.     

A comparison of the composition, coagulation characteristics and cheesemaking capacity of milk from Friesian and Jersey dairy cows

Twenty-nine multiparous cows of each of the Jersey and Friesian breeds, all kappa-casein AB phenotype, were grazed together and managed identically. On three occasions during 10 d in spring (early lactation), milk was collected from all cows at four consecutive milkings and bulked according to breed. On a separate occasion, milk samples were also collected from each cow at consecutive a.m. and p.m. milkings to form one daily sample per cow. The bulked milks (800-1000 l per breed on each occasion) were standardized to a protein:fat (P:F) ratio of 0.80, and 350 l from each breed was made into Cheddar cheese. The solids content of the remaining Friesian milk was then increased by ultrafiltration to a solids concentration equal to that of the Jersey milk. This solids-standardized Friesian milk and a replicate batch of P:F standardized Jersey milk were made into two further batches of Cheddar cheese in 350-l vats. Compared with Friesian milk, Jersey milk had higher concentrations of most milk components measured, including protein, casein and fat. There were few difference in milk protein composition between breeds, but there were differences in fat composition. Friesian milk fat had more conjugated linoleic acid (CLA) than Jersey milk fat. Jersey milk coagulated faster and formed firmer curd than Friesian milk. Concentrations of some milk components were correlated with coagulation parameters, but relationships did not allow prediction of cheesemaking potential. Jersey milk yielded 10% more cheese per kg than Friesian milk using P:F standardized milk, but for milks with the same solids concentration there were no differences in cheese yield. No differences in cheese composition between breeds were detected. Differences in cheesemaking properties of milk from Jerseys and Friesians were entirely related to the concentrations of solids in the original milk.     

浓缩酪蛋白胶束成分的影响因素及其在奶酪生产中的应用

目前,采用膜过滤技术可从脱脂奶中分离酪蛋白,随后通过浓缩、杀菌、干燥等工艺获得浓缩酪蛋白胶束。对浓缩酪蛋白胶束成分的影响因素及其在奶酪生产中的应用进行综述,发现膜过滤期间的pH值、温度和洗滤条件均会影响浓缩酪蛋白胶束的成分,使其具有不同浓度的酪蛋白、乳清蛋白、乳糖以及钙。而且可以利用浓缩酪蛋白胶束标准化原奶,从而制备成分和品质一致的奶酪;也可以利用不同成分的浓缩酪蛋白胶束获得不同的原奶组合物,从而制备所需品质和功能的奶酪。总之,在奶酪生产过程中添加浓缩酪蛋白胶束能够影响奶酪的成分、质地以及风味等,但通过调整膜过滤和奶酪生产的工艺参数可以解决这些问题。未来还需获得一种经济有效的方式来保存浓缩酪蛋白胶束,赋予其更长的保质期,良好的凝乳酶凝乳特性,从而保证奶酪的品质和产量。     

Composition, coagulation properties and Parmigiano-Reggiano cheese yield of Italian Brown and Italian Friesian herd milks

The authors report the results of a study aimed at the comparison of the basic chemical composition, the main protein fractions distribution, rennet coagulation properties and Parmigiano-Reggiano cheese yield of vat milk from Italian Brown and Italian Friesian herds. Parmigiano-Reggiano cheese factories which manufacture milk separately from Italian Brown herds and Italian Friesian herds were used in the study. Thirteen cheesemaking trials were performed at 10 different commercial cheese factories. The study was carried out from March to October 2003. For each cheesemaking trial in each factory, approximately 1100 kg milk from Italian Brown cows and from Italian Friesian cows were processed in parallel. The animals involved in the study came from farms with comparable management practices, size, location, number of lactation and days in milking. Each vat contained milk obtained by combining milk collected during the evening milking (partially skimmed milk by natural creaming) and the following morning milking (full-cream milk), from at least 2 dairy herds. Milk from Italian Brown cows is characterised by a higher casein content (27.1 v. 23.7 g/kg; P < or = 0.0001) than Italian Friesian cows' milk. Curd firming time (k20) of Italian Brown cows' milk was markedly lower than that of Italian Friesian cows' milk (6.6 v. 10.0 min; P < or = 0.001). This implies a higher rate of aggregation of para-casein micelles for Italian Brown cows' milk. The coagulum of Italian Brown cows' milk had better rheological properties and lower losses of fat in the cheese whey. Parmigiano-Reggiano cheese yield at 24 h was also higher for Italian Brown cows' milk, + 0.99 kg cheese for every 100 kg vat milk.     

Production of cheese from donkey milk as influenced by addition of transglutaminase

Donkey milk is characterized by low contents of total solids, fat, and caseins, especially κ-casein, which results in formation of a very weak gel upon renneting. The objective of this study was to evaluate the effect of fortification of donkey milk with microbial transglutaminase (MTGase) for cheesemaking in relation to different enzyme addition protocols (patterns, PAT). Four independent trials were performed using MTGase (5.0 U/g of milk protein) according to the following experimental patterns: control (no MTGase addition); MTGase addition (40°C) 15 min before starter inoculation (PAT1); addition of MTGase to milk simultaneously with starter culture (40°C) (PAT2); and MTGase addition simultaneously with rennet (42°C) in acidified milk (pH 6.3) (PAT3). Evolution of pH during acidification, cheesemaking parameters, and proximal composition and color of cheese at 24 h were recorded. The protein fractions of cheese and whey were investigated by urea-PAGE and sodium dodecyl sulfate-PAGE. Addition of MTGase had no significant effect on moisture, protein, fat, or cheese yield. The addition of MTGase with rennet (PAT3) improved curd firmness compared with the control. Among the different patterns of MTGase addition, PAT3 reduced gel formation time, time between rennet addition and cheese molding, and weight loss of cheese at 24 h. The PAT3 treatment also resulted in the lowest lightness and highest yellowness color values of the cheese. Sodium dodecyl sulfate-PAGE of cheeses revealed that MTGase modified the protein pattern in the high-molecular-weight zone (range 37–75 kDa) compared with the control. Of the MTGase protocols, PAT3 showed better casein retention in cheese, as confirmed by the lanes of α- and β-caseins in the electropherogram of the whey, which was subtler for this protocol. In conclusion, MTGase may be used in cheese production from donkey milk to improve curd firmness; MTGase should be added simultaneously with the rennet.     

Improving rennet coagulation and cheesemaking properties of reverse osmosis skim milk concentrates by pH adjustment

The use of reverse osmosis (RO) for cheese milk concentration has advantages including obtaining reusable low pollutant permeates and reducing milk transportation costs. However, high levels of lactose and salts in RO concentrates impair their cheesemaking abilities. The objective of this work was to optimise the use of RO concentrates (5–11% protein content) for cheesemaking by pH adjustment. Rennet coagulation kinetics, salt partitioning and cheesemaking properties were studied in comparison with ultrafiltration concentrates. Results showed that concentration by RO induced an increase regarding the coagulation time and the gel maximal firming rate that reached a plateau at 9% protein content. Increases in calcium mineralisation of casein micelles as well as in yield, moisture and lactose content in model cheese were observed. Lowering renneting pH was found to improve the cheesemaking properties of RO concentrates by promoting partial demineralisation of casein micelles, accelerating coagulation kinetics and increasing curd drainage.     

Invited review: Microfiltration-derived casein and whey proteins from milk

Milk, a rich source of nutrients, can be fractionated into a wide range of components for use in foods and beverages. With advancements in filtration technologies, micellar caseins and milk-derived whey proteins are now produced from skim milk using microfiltration. Microfiltered ingredients offer unique functional and nutritional benefits that can be exploited in new product development. Microfiltration offers promise in cheesemaking, where microfiltered milk can be used for protein standardization to improve the yield and consistency of cheese and help with operation throughputs. Micellar casein concentrates and milk whey proteins could offer unique functional and flavor properties in various food applications. Consumer desires for safe, nutritious, and clean-label foods could be potential growth opportunities for these new ingredients. The application of micellar casein concentrates in protein standardization could offer a window of opportunity to US cheese makers by improving yields and throughputs in manufacturing plants.     

An empirical method for prediction of cheese yield

Theoretical cheese yield can be estimated from the milk fat and casein or protein content of milk using classical formulae, such as the VanSlyke formula. These equations are reliable predictors of theoretical or actual yield based on accurately measured milk fat and casein content. Many cheese makers desire to base payment for milk to dairy farmers on the yield of cheese. In small factories, however, accurate measurement of fat and casein content of milk by either chemical methods or infrared milk analysis is too time consuming and expensive. Therefore, an empirical test to predict cheese yield was developed which uses simple equipment (i.e., clinical centrifuge, analytical balance, and forced air oven) to carry out a miniature cheese making, followed by a gravimetric measurement of dry weight yield. A linear regression of calculated theoretical versus dry weight yields for milks of known fat and casein content was calculated. A regression equation of y = 1.275x + 1.528, where y is theoretical yield and x is measured dry solids yield (r2 = 0.981), for Cheddar cheese was developed using milks with a range of theoretical yield from 7 to 11.8%. The standard deviation of the difference (SDD) between theoretical cheese yield and dry solids yield was 0.194 and the coefficient of variation (SDD/mean x 100) was 1.95% upon cross validation. For cheeses without a well-established theoretical cheese yield equation, the measured dry weight yields could be directly correlated to the observed yields in the factory; this would more accurately reflect the expected yield performance. Payments for milk based on these measurements would more accurately reflect quality and composition of the milk and the actual average recovery of fat and casein achieved under practical cheese making conditions.     

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.     

Effect of calcium on the minerals retention and cheesemaking parameters of milk

The objective of this study was to evaluate the effect of calcium on minerals retention and cheesemaking parameters of milk during manufacture of a model soft cheese. Several batches of both reconstituted skim milk containing 9, 12 and 15% (w/v) and whole milk with 12, 15 and 18% (w/v) of total solids were used to prepare a soft 'stretchable' cheese of the mozzarella type. A small amount of added calcium (0.14 mM) influenced the level of minerals and some of the measured cheesemaking parameters (clotting time, weight of whey, protein and fat recovery), but the efficiency of the cheesemaking process was lower than would be expected in commercial terms .     

Influence of the casein/fat ratio in milk on the moisture in the non-fat substance in Cheddar cheese

For maximum profitability, the moisture in the non-fat substance (MNFS) in Cheddar cheese must be controlled. Commercial data are used to show that, with fixed manufacturing conditions, the MNFS in cheese may be increased by decreasing the casein/fat ratio in milk and vice versa. It is suggested that this method of varying MNFS may be useful in factories that have difficulty in regulating MNFS by other methods. The relationships between the casein/fat ratio in milk, manufacturing conditions and the fat in the dry matter, MNFS, fat and moisture percentages in cheese are explained.     

Invited review: A commentary on predictive cheese yield formulas

Predictive cheese yield formulas have evolved from one based only on casein and fat in 1895. Refinements have included moisture and salt in cheese and whey solids as separate factors, paracasein instead of casein, and exclusion of whey solids from moisture associated with cheese protein. The General, Barbano, and Van Slyke formulas were tested critically using yield and composition of milk, whey, and cheese from 22 vats of Cheddar cheese. The General formula is based on the sum of cheese components: fat, protein, moisture, salt, whey solids free of fat and protein, as well as milk salts associated with paracasein. The testing yielded unexpected revelations. It was startling that the sum of components in cheese was <100%; the mean was 99.51% (N × 6.31). The mean predicted yield was only 99.17% as a percentage of actual yields (PY%AY); PY%AY is a useful term for comparisons of yields among vats. The PY%AY correlated positively with the sum of components (SofC) in cheese. The apparent low estimation of SofC led to the idea of adjusting upwards, for each vat, the 5 measured components in the formula by the observed SofC, as a fraction. The mean of the adjusted predicted yields as percentages of actual yields was 99.99%. The adjusted forms of the General, Barbano, and Van Slyke formulas gave predicted yields equal to the actual yields. It was apparent that unadjusted yield formulas did not accurately predict yield; however, unadjusted PY%AY can be useful as a control tool for analyses of cheese and milk. It was unexpected that total milk protein in the adjusted General formula gave the same predicted yields as casein and paracasein, indicating that casein or paracasein may not always be necessary for successful yield prediction. The use of constants for recovery of fat and protein in the adjusted General formula gave adjusted predicted yields equal to actual yields, indicating that analyses of cheese for protein and fat may not always be necessary for yield prediction. Composition of cheese was estimated using a predictive formula; actual yield was needed for estimation of composition. Adjusted formulas are recommended for estimating target yields and cheese yield efficiency. Constants for solute exclusion, protein-associated milk salts, and whey solids could be used and reduced the complexity of the General formula. Normalization of fat recovery increased variability of predicted yields.     

Statistical data validation methods for large cheese plant database

Production data of the cheesemaking process are used to monitor milk fat and protein recoveries in cheese, cheese yield, and composition and eventually to predict these parameters. Due to the large impact of these factors on cheese quality and plant profitability, it is very important to use reliable data for analysis, modeling, and control of the process. This paper tested six methods for detecting erroneous data in industrial cheesemaking databases. The data analyzed came from 4 yr of stirred-curd Cheddar cheese production in an industrial cheesemaking facility, comprising over 10,000 vats. Single vat outliers were detected using a simple statistical criterion of mean +/- 3.6 SD on single variable distributions, Fourier series modeling of seasonal variables (fat, protein, lactose, and total solids in milk, and protein in whey), and the multivariate Mahalanobis outlier analysis. Detection of outlier productions (corresponding to several vats) was done by applying the mean +/- 3.6 SD criterion to variables obtained through calculating the fat mass balance, fat retention coefficient, and yield efficiency. Data treatment enabled the detection of outlier data, but also pinpointed variables with a low reliability (manually registered times). Single variable and multivariable methods proved complementary, and the use of both types of methods is recommended when validating an existing database.     

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.     

Seasonal trends in the efficiency of recovery of milk fat and casein in cheese manufacture

A study was undertaken to define the seasonal changes in the efficiency of recovery of milk fat and protein in curd during Cheddar cheese manufacture, and to examine the milk compositional factors that may contribute to these effects. Distinct seasonal trends in the efficiency of conversion of milk fat and protein to cheese were noted. Variations in the retention of milk fat in curd could be associated with seasonal changes in the casein to fat ratio of the milk.     

Transfer of protein from milk to cheese

This report concerns measurement of paracasein in milk and transfer of protein from milk to cheese. In the main experiment, two vats of Cheddar cheese were made from each of 11 lots of milk from one large herd over a period of 7 mo. Exclusion of solutes from moisture in paracasein micelles in milk and cheese was central to estimation of paracasein and to the transfer of protein from milk to cheese and whey. Solute-exclusion by paracasein and its changes during cheesemaking could be visualized by considering paracasein micelles to be a very fine sponge. The sponge excludes solutes, especially the large solutes like whey proteins. The sponge shrinks during cheesemaking and expels solute-free liquid, thereby slightly diluting the whey surrounding the micelles inside the curd. Paracasein N in milk was calculated as the difference between total milk N and rennet whey N, the latter adjusted to its level in milk. Adjustment used appropriate solute-exclusion factors (h) of the protein fractions of whey and 1.08 for paracasein and associated salts. They were combined to give a factor Fpc, which adjusted the level of rennet whey N to its level in milk: 1.001 x (1 - 1.01 x FM/100 - Fpc x pc/100), where FM = fat in milk, pc = estimated paracasein, and 1.001 = dilution of milk by chymosin and CaCl2. The mean Fpc was 3.03. Differences in values were small among different procedures for calculating paracasein, but they are considered to be important because they represent biases, which, in turn, are important in analyses commercially. We conclude that solute exclusion by moisture in paracasein must have decreased during cheesemaking because the ratio of moisture to paracasein in the final cheese was 1.5, much less than the h of 2.6 for serum proteins by paracasein. Release of solute-excluding moisture from paracasein during cooking was likely the reason for lower total N in cheese whey than in the rennet whey in the paracasein analysis. Paracasein, estimated to be in cheese, curd fines, salted whey, and whey during cheddaring, was 98.21, 0.20, 0.25 and 0.19%, respectively, of the paracasein in milk for a total of 98.85% (SD of 22 vats = 0.46); the location of the missing paracasein is not known. On the other hand, recovery of milk N in cheese and wheys was 99.92% (SD = 0.37%). Nitrogen in paracasein and its hydrolysis products in cheese was estimated to be 98.51% of total cheese N. Proteose-peptone from milk appeared not to be included with the paracasein in appreciable amounts. Some was apparently included with denatured serum proteins during Rowland fractionation of whey, perhaps as a coprecipitate. Measured paracasein would include fat globule membrane proteins in milk containing fat, and denatured whey proteins in heated milks. It was concluded that the method of measurement and the associated calculations are integral parts of the definition and quantification of paracasein in milk.     

The effects of microfluidization on the physical,microbial, chemical,and coagulation properties of milk

This work examines the use of mild heat treatments in conjunction with 2-pass microfluidization to generate cheese milk for potential use in soft cheeses, such as Queso Fresco. Raw, thermized, and high temperature, short time pasteurized milk samples, standardized to the 3% (wt/wt) fat content used in cheesemaking, were processed at 4 inlet temperature and pressure conditions: 42°C/75 MPa, 42°C/125 MPa, 54°C/125 MPa, and 54°C/170 MPa. Processing-induced changes in the physical, chemical, and microbial properties resulting from the intense pressure, shear, and cavitation that milk experiences as it is microfluidized were compared with nonmicrofluidized controls. A pressure-dependent increase in exit temperature was observed for all microfluidized samples, with inactivation of alkaline phosphatase in raw and thermized samples at 125 and 170 MPa. Microfluidization of all samples under the 4 inlet temperature and processing pressure conditions resulted in a stable emulsion of fat droplets ranging from 0.390 to 0.501 μm, compared with 7.921 (control) and 4.127 (homogenized control) μm. Confocal imaging showed coalescence of scattered fat agglomerates 1 to 3 μm in size during the first 24 h. We found no changes in fat, lactose, ash content or pH, indicating the major components of milk remained unaffected by microfluidization. However, the apparent protein content was reduced from 3.1 to 2.2%, likely a result of near infrared spectroscopy improperly identifying the micellar fragments embedded into the fat droplets. Microbiology results indicated a decrease in mesophilic aerobic and psychrophilic milk microflora with increasing temperature and pressure, suggesting that microfluidization may eliminate bacteria. The viscosities of milk samples were similar but tended to be higher after treatment at 54°C and 125 or 170 MPa. These samples exhibited the longest coagulation times and the weakest gel firmness, indicating that formation of the casein matrix, a critical step in the production of cheese, was affected. Low temperature and pressure (42°C/75 MPa) exhibited similar coagulation properties to controls. The results suggest that microfluidization at lower pressures may be used to manufacture high-moisture cheese with altered texture whereas higher pressures may result in novel dairy ingredients.