Variation of milk technological properties in sheep milk: Relationships among composition,coagulation and cheese-making traits

The relationships between milk composition, coagulation properties and cheese-making traits in sheep milk were characterised. Ten traits related to milk coagulation (RCT_eq, k_CF, CF_p), cheese yield (%CY_CURD, %CY_SOLIDS, %CY_WATER), and curd nutrients recovery or whey loss (%REC_FAT, %REC_PROTEIN, %REC_SOLIDS, %REC_ENERGY) were recorded. To obtain a measure of the efficiency in terms of %CY, the ratio between the observed and the theoretical %CY (Ef-%CY_CURD, Ef-%CY_SOLIDS) was calculated. Sheep milk showed good qualities for coagulation and cheese production; milk lactose appeared to be the component most linked to gelation, curd firming time and water retained in the curd. In the case of milk protein, an opposite relationship with gelation time was observed. Milk fat and protein positively affected total solids recovery and yield inducing higher %CY_CURD. Relationships with CF_t parameters were limited; curd firming instant rate seems to be the most informative trait to assess the efficiency of the cheese-making process.     

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.     

Pathway-based genome-wide association analysis of milk coagulation properties,curd firmness,cheese yield,and curd nutrient recovery in dairy cattle

It is becoming common to complement genome-wide association studies (GWAS) with gene-set enrichment analysis to deepen the understanding of the biological pathways affecting quantitative traits. Our objective was to conduct a gene ontology and pathway-based analysis to identify possible biological mechanisms involved in the regulation of bovine milk technological traits: coagulation properties, curd firmness modeling, individual cheese yield (CY), and milk nutrient recovery into the curd (REC) or whey loss traits. Results from 2 previous GWAS studies using 1,011 cows genotyped for 50k single nucleotide polymorphisms were used. Overall, the phenotypes analyzed consisted of 3 traditional milk coagulation property measures [RCT: rennet coagulation time defined as the time (min) from addition of enzyme to the beginning of coagulation; k₂₀: the interval (min) from RCT to the time at which a curd firmness of 20 mm is attained; a₃₀: a measure of the extent of curd firmness (mm) 30 min after coagulant addition], 6 curd firmness modeling traits [RCT_eq: RCT estimated through the CF equation (min); CF_P: potential asymptotic curd firmness (mm); k_CF: curd-firming rate constant (% × min^?1); k_SR: syneresis rate constant (% × min^?1); CF_max: maximum curd firmness (mm); and t_max: time to CF_max (min)], 3 individual CY-related traits expressing the weight of fresh curd (%CY_CURD), curd solids (%CY_SOLIDS), and curd moisture (%CY_WATER) as a percentage of weight of milk processed and 4 milk nutrient and energy recoveries in the curd (REC_FAT, REC_PROTEIN, REC_SOLIDS, and REC_ENERGY calculated as the % ratio between the nutrient in curd and the corresponding nutrient in processed milk), milk pH, and protein percentage. Each trait was analyzed separately. In total, 13,269 annotated genes were used in the analysis. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway databases were queried for enrichment analyses. Overall, 21 Gene Ontology and 17 Kyoto Encyclopedia of Genes and Genomes categories were significantly associated (false discovery rate at 5%) with 7 traits (RCT, RCT_eq, k_CF, %CY_SOLIDS, REC_FAT, REC_SOLIDS, and REC_ENERGY), with some being in common between traits. The significantly enriched categories included calcium signaling pathway, salivary secretion, metabolic pathways, carbohydrate digestion and absorption, the tight junction and the phosphatidylinositol pathways, as well as pathways related to the bovine mammary gland health status, and contained a total of 150 genes spanning all chromosomes but 9, 20, and 27. This study provided new insights into the regulation of bovine milk coagulation and cheese ability that were not captured by the GWAS.     

Genome-wide association study for cheese yield and curd nutrient recovery in dairy cows

Cheese production and consumption are increasing in many countries worldwide. As a result, interest has increased in strategies for genetic selection of individuals for technological traits of milk related to cheese yield (CY) in dairy cattle breeding. However, little is known about the genetic background of a cow's ability to produce cheese. Recently, a relatively large panel (1,264 cows) of different measures of individual cow CY and milk nutrient and energy recoveries in the cheese (REC) became available. Genetic analyses showed considerable variation for CY and for aptitude to retain high proportions of fat, protein, and water in the coagulum. For the dairy industry, these characteristics are of major economic importance. Nevertheless, use of this knowledge in dairy breeding is hampered by high costs, intense labor requirement, and lack of appropriate technology. However, in the era of genomics, new possibilities are available for animal breeding and genetic improvement. For example, identification of genomic regions involved in cow CY might provide potential for marker-assisted selection. The objective of this study was to perform genome-wide association studies on different CY and REC measures. Milk and DNA samples from 1,152 Italian Brown Swiss cows were used. Three CY traits expressing the weight (wt) of fresh curd (%CY_CURD), curd solids (%CY_SOLIDS), and curd moisture (%CY_WATER) as a percentage of weight of milk processed, and 4 REC (REC_FAT, REC_PROTEIN, REC_SOLIDS, and REC_ENERGY, calculated as the % ratio between the nutrient in curd and the corresponding nutrient in processed milk) were analyzed. Animals were genotyped with the Illumina BovineSNP50 Bead Chip v.2. Single marker regressions were fitted using the GenABEL R package (genome-wide association using mixed model and regression–genomic control). In total, 103 significant associations (88 single nucleotide polymorphisms) were identified in 10 chromosomes (2, 6, 9, 11, 12, 14, 18, 19, 27, 28). For REC_FAT and REC_PROTEIN, high significance peaks were identified in Bos taurus autosome (BTA) 6 and BTA11, respectively. Marker ARS-BFGL-NGS-104610 (～104.3 Mbp) was highly associated with REC_PROTEIN and Hapmap52348-rs29024684 (～87.4 Mbp), closely located to the casein genes on BTA6, with REC_FAT. Genomic regions identified may enhance marker-assisted selection in bovine cheese breeding beyond the use of protein (casein) and fat contents, whereas new knowledge will help to unravel the genomic background of a cow's ability for cheese production.     

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.     

Associations between pathogen-specific cases of subclinical mastitis and milk yield,quality, protein composition,and cheese-making traits in dairy cows

The aim of this study was to investigate associations between pathogen-specific cases of subclinical mastitis and milk yield, quality, protein composition, and cheese-making traits. Forty-one multibreed herds were selected for the study, and composite milk samples were collected from 1,508 cows belonging to 3 specialized dairy breeds (Holstein Friesian, Brown Swiss, and Jersey) and 3 dual-purpose breeds of Alpine origin (Simmental, Rendena, and Grey Alpine). Milk composition [i.e., fat, protein, casein, lactose, pH, urea, and somatic cell count (SCC)] was analyzed, and separation of protein fractions was performed by reversed-phase high performance liquid chromatography. Eleven coagulation traits were measured: 5 traditional milk coagulation properties [time from rennet addition to milk gelation (RCT, min), curd-firming rate as the time to a curd firmness (CF) of 20 mm (k₂₀, min), and CF at 30, 45, and 60 min from rennet addition (a₃₀, a₄₅, and a₆₀, mm)], and 6 new curd firming and syneresis traits [potential asymptotical CF at an infinite time (CF_P, mm), curd-firming instant rate constant (k_CF, % × min^?1), curd syneresis instant rate constant (k_SR, % × min^?1), modeled RCT (RCT_eq, min), maximum CF value (CF_max, mm), and time at CF_max (t_max, min)]. We also measured 3 cheese yield traits, expressing the weights of total fresh curd (%CY_CURD), dry matter (%CY_SOLIDS), and water (%CY_WATER) in the curd as percentages of the weight of the processed milk, and 4 nutrient recovery traits (REC_PROTEIN, REC_FAT, REC_SOLIDS, and REC_ENERGY), representing the percentage ratio between each nutrient in the curd and milk. Milk samples with SCC > 100,000 cells/mL were subjected to bacteriological examination. All samples were divided into 7 clusters of udder health (UH) status: healthy (cows with milk SCC < 100,000 cells/mL and uncultured); culture-negative samples with low, medium, or high SCC; and culture-positive samples divided into contagious, environmental, and opportunistic intramammary infection (IMI). Data were analyzed using a linear mixed model. Significant variations in the casein to protein ratio and lactose content were observed in all culture-positive samples and in culture-negative samples with medium to high SCC compared to normal milk. No differences were observed among contagious, environmental, and opportunistic pathogens, suggesting an effect of inflammation rather than infection. The greatest impairment in milk quantity and composition, clotting ability, and cheese production was observed in the 2 UH status groups with the highest milk SCC (i.e., contagious IMI and culture-negative samples with high SCC), revealing a discrepancy between the bacteriological results and inflammatory status, and thus confirming the importance of SCC as an indicator of udder health and milk quality.     

Variations in milk protein fractions affect the efficiency of the cheese-making process

The aim of this study was to assess the influence of the amounts of the α_S1-, α_S2-, β-, and κ-casein (CN) and the α-lactalbumin and β-lactoglobulin protein fractions on the efficiency of the cheese-making process independently of their genetic polymorphisms. The study was carried out on milk samples from 1,271 Brown Swiss cows from 85 herds classified into 4 categories according to management, feeding, and housing characteristics (traditional and modern systems). To assess the efficiency of the cheese-making process, we processed the milk samples according to a laboratory cheese-making procedure (1,500 mL/sample) and obtained the following measures: (1) 3 percentage cheese yields (%CY_curd, %CY_solids, %CY_water), (2) 2 daily cheese yields obtained by multiplying %CY (curd and total solids) by daily milk yields (dCY_curd, dCY_solids), (3) 4 measures of nutrient recovery in the curd (REC_fat, REC_protein, REC_solids, REC_energy), and (4) 2 measures of cheese-making efficiency in terms of the ratio between the observed and theoretical %CY (Ef-%CY_curd, Ef-%CY_solids). All the aforementioned traits were analyzed by fitting 2 linear mixed models with protein fractions as fixed effects expressed as percentage in the milk (model M-%milk) and as percentage of the total casein content (model M-%cas) together with the effects of total casein content (only in model M-%cas), daily milk yield (only in model M-%milk; not for dCY traits), dairy system, herd (random effect), days in milk, parity, and vat. The efficiency of overall cheese yield (Ef-%CY_curd) was mostly positively associated with β-CN content in the milk, whereas Ef-%CY_solids was greater with higher amounts of κ-CN and α_S1-CN (M-%milk) due to the strong influence of both fractions on the recovery rate of milk components in the curd (fat and total solids, protein with α_S1-CN only) when expressed as percentage of milk and of total casein; only β-CN was more important for REC_protein. In contrast, we found β-lactoglobulin to be highly negatively related to all the traits related to the cheese-making process and to the daily cheese yield per cow, whereas α-lactalbumin was positively associated with the latter traits. Additional research on this topic is needed, with particular focus on the genetic and genomic aspects of the role of protein fractions in the cheese-making process and on the associations between genetic polymorphisms in milk protein and milk nutrient recovery in the curd.     

Genetic parameters of milk coagulation properties and their relationships with milk yield and quality traits in Italian Holstein cows

Milk coagulation properties (MCP) are an important aspect in assessing cheese-making ability. Several studies showed that favorable conditions of milk reactivity with rennet, curd formation rate, and curd strength, as well as curd syneresis, have a positive effect on the entire cheese-making process and subsequently on the ripening of cheese. Moreover, MCP were found to be heritable, but little scientific literature is available about their genetic aspects. The aims of this study were to estimate heritability of MCP and genetic correlations among MCP and milk production and quality traits. A total of 1,071 Italian Holstein cows (progeny of 54 sires) reared in 34 herds in Northern Italy were sampled from January to July 2004. Individual milk samples were collected during the morning milking and analyzed for coagulation time (RCT), curd firmness (a₃₀), pH, titratable acidity, fat, protein, and casein contents, and somatic cell count. About 10% of individual milk samples did not coagulate in 31 min, so they were removed from the analyses. Estimates of heritability for RCT and a₃₀ were 0.25 ± 0.04 and 0.15 ± 0.03, respectively. Estimates of genetic correlations between MCP traits and milk production traits were negligible except for a₃₀ with protein and casein contents (0.44 ± 0.10 and 0.53 ± 0.09, respectively). Estimates of genetic correlations between MCP traits and somatic cell score were strong and favorable, as well as those between MCP and pH and titratable acidity. Selecting for high casein content, milk acidity, and low somatic cell count might be an indirect way to improve MCP without reducing milk yield and quality traits.     

The use of Fourier-transform infrared spectroscopy to predict cheese yield and nutrient recovery or whey loss traits from unprocessed bovine milk samples

Cheese yield is an important technological trait in the dairy industry in many countries. The aim of this study was to evaluate the effectiveness of Fourier-transform infrared (FTIR) spectral analysis of fresh unprocessed milk samples for predicting cheese yield and nutrient recovery traits. A total of 1,264 model cheeses were obtained from 1,500-mL milk samples collected from individual Brown Swiss cows. Individual measurements of 7 new cheese yield-related traits were obtained from the laboratory cheese-making procedure, including the fresh cheese yield, total solid cheese yield, and the water retained in curd, all as a percentage of the processed milk, and nutrient recovery (fat, protein, total solids, and energy) in the curd as a percentage of the same nutrient contained in the milk. All individual milk samples were analyzed using a MilkoScan FT6000 over the spectral range from 5,000 to 900 wavenumber × cm⁻¹. Two spectral acquisitions were carried out for each sample and the results were averaged before data analysis. Different chemometric models were fitted and compared with the aim of improving the accuracy of the calibration equations for predicting these traits. The most accurate predictions were obtained for total solid cheese yield and fresh cheese yield, which exhibited coefficients of determination between the predicted and measured values in cross-validation (1-VR) of 0.95 and 0.83, respectively. A less favorable result was obtained for water retained in curd (1-VR = 0.65). Promising results were obtained for recovered protein (1-VR = 0.81), total solids (1-VR = 0.86), and energy (1-VR = 0.76), whereas recovered fat exhibited a low accuracy (1-VR = 0.41). As FTIR spectroscopy is a rapid, cheap, high-throughput technique that is already used to collect standard milk recording data, these FTIR calibrations for cheese yield and nutrient recovery highlight additional potential applications of the technique in the dairy industry, especially for monitoring cheese-making processes and milk payment systems. In addition, the prediction models can be used to provide breeding organizations with information on new phenotypes for cheese yield and milk nutrient recovery, potentially allowing these traits to be enhanced through selection.     

Detection of milk powder and caseinates in Halloumi cheese

Halloumi cheese is traditionally manufactured from fresh milk. Nevertheless, dried dairy ingredients are sometimes illegally added to increase cheese yield. Lysinoalanine and furosine are newly formed molecules generated by heating and drying milk protein components. The levels of these molecular markers in the finished Halloumi have been investigated to verify their suitability to reveal the addition of skim milk powder and calcium caseinate to cheese milk. Because of the severe heating conditions applied in curd cooking, genuine Halloumi cheeses (n = 35), representative of the Cyprus production, were characterized by levels of lysinoalanine (mean value = 8.1 mg/100 g of protein) and furosine (mean value = 123 mg/100 g of protein) unusual for natural cheeses. Despite the variability of the values, a good correlation between the 2 parameters (R = 0.975) has been found in all cheeses, considering both the fresh and mature cheeses as well as those obtained from curd submitted to a prolonged cooking following a traditional practice adopted by a very small number of manufacturers. Experimental cheeses made by adding as low as 5% of skim milk powder, or calcium caseinate, or both, to cheese milk fell outside the prediction limits at ±2 standard deviation of the above-reported correlation regardless of curd cooking conditions or ripening length. This correlation may be adopted as a reliable index of Halloumi cheese genuineness.     

Influence of curd cutting programme and stirring speed on the prediction of syneresis indices in cheese-making using NIR light backscatter

An NIR reflectance sensor, with a large field of view and a fibre-optic connection to a spectrometer for measuring light backscatter at 980 nm, was used to monitor the syneresis process online during cheese-making with the goal of predicting syneresis indices (curd moisture content, yield of whey and fat losses to whey) over a range of curd cutting programmes and stirring speeds. A series of trials were carried out in an 11 L cheese vat using recombined whole milk. A factorial experimental design consisting of three curd stirring speeds and three cutting programmes, was undertaken. Milk was coagulated under constant conditions and the casein gel was cut when the elastic modulus reached 35 Pa. Among the syneresis indices investigated, the most accurate and most parsimonious multivariate model developed was for predicting yield of whey involving three terms, namely light backscatter, milk fat content and cutting intensity (R² = 0.83, SEy = 6.13 g/100 g), while the best simple model also predicted this syneresis index using the light backscatter alone (R² = 0.80, SEy = 6.53 g/100 g). In this model the main predictor was the light backscatter response from the NIR light back scatter sensor. The sensor also predicted curd moisture with a similar accuracy.     

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.     

Adjustment of vat milk treatment to optimize whey protein transfer into semi-hard cheese: A case study

The influence of heat treatment combined with microfiltration on the protein transfer from milk to cheese was investigated. Small-scale laboratory cheese-making experiments (10 L vat) showed that, upon adjusting coagulant and CaCl₂ addition, curd-making was possible as long as β-lactoglobulin denaturation was below 40%. It was also possible to compensate the negative effect of heating on rennet gel formation by protein enrichment through microfiltration. Depending on heat treatment intensity, the protein yield in curd increased to approximately 6%. Using Gouda cheese technology, pilot-scale experiments (500 L vat) showed that, depending on heat treatment intensity (up to 85 °C/60 s) and concentration (up to a concentration factor 2.0), it was possible to reduce the amount of protein which is lost in permeate and whey by 15–30%. Dry matter and crude protein of cheeses were significantly affected by heat treatment and microfiltration of milk, and proteolysis during maturation was delayed.     

Estimation of genetic parameters for cheese-making traits in Spanish Churra sheep

The global production of sheep milk is growing, and the main industrial use of sheep milk is cheese making. The Spanish Churra sheep breed is one of the most important native dairy breeds in Spain. The present study aimed to estimate genetic parameters for a wide range of traits influencing the cheese-making ability of Churra sheep milk. Using a total of 1,049 Churra ewes, we studied the following cheese-making traits: 4 traits related to milk coagulation properties (rennet coagulation time, curd-firming time, and curd firmness at 30 and 60 min after addition of rennet), 2 traits related to cheese yield (individual laboratory cheese yield and individual laboratory dried curd yield), and 3 traits measuring curd firmness over time (maximum curd firmness, time to attain maximum curd firmness, and syneresis). In addition, a list of milk traits, including the native pH of the milk and several milk production and composition traits (milk yield; the fat, protein, and dried extract percentages; and the somatic cell count), were also analyzed for the studied animals. After discarding the noncoagulating samples (only 3.7%), data of 1,010 ewes were analyzed with multiple-trait animal models by using the restricted maximum likelihood method to estimate (co)variance components, heritabilities, and genetic correlations. In general, the heritability estimates were low to moderate, ranging from 0.08 (for the individual laboratory dried curd yield trait) to 0.42 (for the fat percentage trait). High genetic correlations were found within pairs of related traits (i.e., 0.93 between fat and dried extract percentages, ?0.93 between the log of the curd-firming time and curd firmness at 30 min, 0.70 between individual laboratory cheese yield and individual laboratory dried curd yield, and ?0.94 between time to attain maximum curd firmness and syneresis). Considering all the information provided here, we suggest that in addition to the current consideration of the protein percentage trait for improving cheese yield traits, the inclusion of the pH of milk as a measured trait in the Churra dairy breeding program would represent an efficient strategy for improving the cheese-making ability of milk from this breed.     

Yield, composition and rheological characteristics of cheddar cheese made with high pressure processed milk

High Pressure (HP) treatment of milk prior to cheese-making was shown to increase the yield of cheese due to increased protein and moisture retention in cheese. Cheeses were made with raw milk or milk treated with high temperature short-time (HTST) pasteurization, and HP treatments at two levels (483 and 676 MPa) at 10 °C, 483 MPa HP at 30 °C, and 483 MPa HP at 40 °C. Cheese yield, total solids, protein, fat and salt contents were evaluated, and fat and protein recovery indices were calculated. Cheeses from HP treatments of 676 MPa at 10 °C and 483 MPa at 30 °C exhibited wet yields of 11.40% and 11.54%, respectively. Protein recovery was 79.9% for HP treatment of 676 MPa at 10 °C. The use of slightly higher pressurization temperatures increased moisture retention in cheese. Visco-elasticity of cheeses was determined by dynamic oscillatory testing and a creep-recovery test. Rheological parameters such as loss (G″) and storage (G′) moduli were dependent on oscillation frequency. At high (173 rad/s) and low (2.75 rad/s) angular frequencies, cheeses made from milk treated at 483 MPa at 10 °C behaved more solid-like than other treatments. Creep tests indicated that cheeses from milk treated with 483 MPa HP at 10 °C showed the smallest instantaneous compliance (J_o), confirming the more solid-like behavior of cheese from the 483 MPa at 10 °C treatment compared to the behavior of cheeses from other treatments. Cheeses made with pasteurized milk were more deformable, exhibited less solid-like behavior than cheeses made with HP treated milk, as shown by the J_o value. With more research into bacteriological implications, HP treatment of raw milk can augment Cheddar cheese yield with better curd formation properties.     

Effect of β-lactoglobulin A and B whey protein variants on cheese yield potential of a model milk system

Cheese yield mainly depends on the amount and proportion of milk constituents; however, genetic variants of the proteins present in milk may also have an important effect. The objective of this research was to study the effect of the variants A and B of β-lactoglobulin (LG) on cheese yield using a model system consisting of skim milk powder fortified with different levels of a mixture containing α-lactalbumin and β-LG genetic variants (A, B, or A-B) in a 1:2 ratio. Fortified milk samples were subjected to pasteurization at 65°C for 30 min. Miniature cheeses were made by acidifying (pH = 5.9) fortified milk and incubating with rennet for 1 h at 32°C. The clot formed was cut, centrifuged at 2,600 × g for 30 min at 20°C and drained for determining cheese yield. Cheese-yielding capacity was expressed as actual yield (grams of cheese curd per 100 g of milk) and dry weight yield (grams of dried cheese curd per 100 g of milk). Free-zone capillary electrophoresis was used for determining β-LG A or B recovery in the curd during rennet-induced coagulation. The presence of β-LG variant B resulted in a significantly higher actual and dried weight cheese yield than when A or A-B were present at levels ≤0.675% of whey protein (WP) addition. Results of free-zone capillary electrophoresis allowed us to infer that β-LG B associates with the casein micelles during renneting, as shown by an increase in the recovery of this variant in the curd when β-LG B was added up to a maximum at 0.45% (equivalent to 0.675% WP). In general, actual or dried weight cheese yield increased as WP addition was increased from 0.225 to 0.675%. However, when WP addition ranged from 0.675 to 0.90%, a drastic drop in cheese yield was observed. This behavior may be because an increase in the aggregation of casein micelles with a concomitant inclusion of whey protein in the gel occurs at low levels of WP addition, whereas once the association of WP with the casein micelles reach a saturation point at addition levels higher than 0.675%, rearrangements of the gel network result in larger whey expulsion and syneresis. This knowledge is expected to be useful to maximize cheese yield and optimize processing conditions during cheese and cheese analogs manufacturing.     

Potential influence of herd and animal factors on the yield of cheese and recovery of components from Sarda sheep milk,as determined by a laboratory bench-top model cheese-making

Individual milk samples from 169 Sarda sheep were collected to characterise the cheese-making potential through the use of a laboratory bench-top model cheese-manufacturing procedure. As the milk samples were not standardised before processing, the data collected at laboratory level fully reflected the great variability of milk from individual animals. The average cheese yield traits of fresh cheese, cheese dry matter and water retained in cheese (as percentages of the milk processed) were 20.6%, 10.1% and 10.6%. The average milk fat and protein recoveries in the curd were 94.0% and 76.7%, respectively. The values for daily production of curd and curd dry matter per sheep were 0.41 kg d⁻¹ and 0.20 kg d⁻¹, respectively. The cheese yield and cheese-related traits were mainly affected by the nutrient content of the milk and the individual effects of the stage of lactation and daily milk yield, respectively, but also by a large individual variation.     

Short communication: Aflatoxin M1 in dairy products sold in Şanlıurfa,Turkey

The aim of this study was to detect the presence of aflatoxin M₁ (AFM1) in samples of raw milk (n = 38), UHT milk (n = 12), white pickled cheese (n = 50), and yogurt (n = 50) collected from the ?anl?urfa city markets and locally produced dairy products by ELISA. The mean contamination rates were 56.74 ± 40.32, 43.1 ± 23.19, 103.2 ± 29.13, and 55.28 ± 12.68 ng/kg, respectively, for raw milk, UHT milk, white pickled cheese, and yogurt. According to the data, 21 (55%) raw milk, 3 (25%) UHT milk, 10 (20%) white pickled cheese, and 10 (20%) yogurt samples were contaminated with AFM1 over the acceptable levels (≥50 ng/kg), ranging from 0.82 to 130.89 ng/kg. None of the white pickled cheese samples contained AFM1 levels above the Turkish legal limit (250 ng/kg). Consequently, the AFM1 contamination levels determined in this study in white pickled cheese were not considered to pose a serious public health hazard. However, the AFM1 levels in raw and UHT milk and yogurt samples indicate an increased human health risk in Turkey related to high aflatoxin levels. Therefore, milk and dairy products have to be monitored by the Turkish public health authorities continuously to detect AFM1 contamination.     

Milk clotting and proteolytic activity of an enzyme preparation from Bromelia hieronymi fruits

A new enzyme preparation (hieronymain), obtained from unripe fruits of Bromelia hieronymi Mez (Bromeliaceae), was assayed for its ability to clot milk and hydrolyze bovine casein and milk whey proteins. Caseinolytic activity at 30 °C and pH 6.5 (milk clotting conditions) was 3.3 Ucas/mL and milk clotting activity was 40 ± 0.2 IMCU/mL. The κ-casein fraction, involved in the clotting formation, began to be degraded after 10 min of reaction, while the degradation of the other casein fractions proceeded slowly enough as to guarantee the production of a firm curd, with no evidence of extensive hydrolysis, a necessary condition for cheese making. In the case of whey proteins, bovine serum albumin and α-lactalbumin were quickly degraded after 30 min, while β-lactoglobulin was considerably degraded only after 60 min at 50 °C. Miniature cheeses were manufactured both with chymosine and hieronymain and analyzed by a taste panel, who found acceptable both cheeses. Hieronymain might be appropriate for cheese making, as well as for the production of milk protein hydrolysates.     

Value-added utilization of yak milk casein for the production of angiotensin-I-converting enzyme inhibitory peptides

Yak (Bos grunniens) milk casein derived from Qula, a kind of acid curd cheese from northwestern China, was hydrolysed with alcalase. The hydrolysates collected at different hydrolysis times (0 min, 60 min, 120 min, 180 min, 240 min, 300 min, 360 min) were assayed for the inhibitory activity of angiotensin-I-converting enzyme (ACE), and the one obtained at 240 min hydrolysis showed the highest ACE inhibitory activity. The active hydrolysate was further consecutively separated by ultrafiltration with 10 kDa and then with 6 kDa molecular weight cut-off membranes into different parts, and the 6 kDa permeate showed the highest ACE-inhibiting activity. This active fraction was further purified to yield two novel ACE-inhibiting peptides, whose amino acid sequences were Pro–Pro–Glu–Ile–Asn (PPEIN)(κ-CN; f156–160) and Pro–Leu–Pro–Leu–Leu (PLPLL) (β-CN; f136–140), respectively. The molecular weight and IC₅₀ value of the peptides were 550 Da and 566.4 Da, and 0.29 ± 0.01 mg/ml and 0.25 ± 0.01 mg/ml, respectively.