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.     

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.     

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.     

Comparison between genetic parameters of cheese yield and nutrient recovery or whey loss traits measured from individual model cheese-making methods or predicted from unprocessed bovine milk samples using Fourier-transform infrared spectroscopy

Cheese yield is an important technological trait in the dairy industry. The aim of this study was to infer the genetic parameters of some cheese yield-related traits predicted using Fourier-transform infrared (FTIR) spectral analysis and compare the results with those obtained using an individual model cheese-producing procedure. A total of 1,264 model cheeses were produced using 1,500-mL milk samples collected from individual Brown Swiss cows, and individual measurements were taken for 10 traits: 3 cheese yield traits (fresh curd, curd total solids, and curd water as a percent of the weight of the processed milk), 4 milk nutrient recovery traits (fat, protein, total solids, and energy of the curd as a percent of the same nutrient in the processed milk), and 3 daily cheese production traits per cow (fresh curd, total solids, and water weight of the curd). Each unprocessed milk sample was analyzed using a MilkoScan FT6000 (Foss, Hillerød, Denmark) over the spectral range, from 5,000 to 900 wavenumber × cm⁻¹. The FTIR spectrum-based prediction models for the previously mentioned traits were developed using modified partial least-square regression. Cross-validation of the whole data set yielded coefficients of determination between the predicted and measured values in cross-validation of 0.65 to 0.95 for all traits, except for the recovery of fat (0.41). A 3-fold external validation was also used, in which the available data were partitioned into 2 subsets: a training set (one-third of the herds) and a testing set (two-thirds). The training set was used to develop calibration equations, whereas the testing subsets were used for external validation of the calibration equations and to estimate the heritabilities and genetic correlations of the measured and FTIR-predicted phenotypes. The coefficients of determination between the predicted and measured values in cross-validation results obtained from the training sets were very similar to those obtained from the whole data set, but the coefficient of determination of validation values for the external validation sets were much lower for all traits (0.30 to 0.73), and particularly for fat recovery (0.05 to 0.18), for the training sets compared with the full data set. For each testing subset, the (co)variance components for the measured and FTIR-predicted phenotypes were estimated using bivariate Bayesian analyses and linear models. The intraherd heritabilities for the predicted traits obtained from our internal cross-validation using the whole data set ranged from 0.085 for daily yield of curd solids to 0.576 for protein recovery, and were similar to those obtained from the measured traits (0.079 to 0.586, respectively). The heritabilities estimated from the testing data set used for external validation were more variable but similar (on average) to the corresponding values obtained from the whole data set. Moreover, the genetic correlations between the predicted and measured traits were high in general (0.791 to 0.996), and they were always higher than the corresponding phenotypic correlations (0.383 to 0.995), especially for the external validation subset. In conclusion, we herein report that application of the cross-validation technique to the whole data set tended to overestimate the predictive ability of FTIR spectra, give more precise phenotypic predictions than the calibrations obtained using smaller data sets, and yield genetic correlations similar to those obtained from the measured traits. Collectively, our findings indicate that FTIR predictions have the potential to be used as indicator traits for the rapid and inexpensive selection of dairy populations for improvement of cheese yield, milk nutrient recovery in curd, and daily cheese production per cow.     

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.     

Effects of indirect indicators of udder health on nutrient recovery and cheese yield traits in goat milk

In dairy goats, very little is known about the effect of the 2 most important indirect indicators of udder health [somatic cell count (SCC) and total bacterial count (TBC)] on milk composition and cheese yield, and no information is available regarding the effects of lactose levels, pH, and NaCl content on the recovery of nutrients in the curd, cheese yield traits, and daily cheese yields. Because large differences exist among dairy species, conclusions from the most studied species (i.e., bovine) cannot be drawn for all types of dairy-producing animals. The aims of this study were to quantify, using milk samples from 560 dairy goats, the contemporary effects of a pool of udder health indirect indicators (lactose level, pH, SCC, TBC, and NaCl content) on the recovery of nutrients in the curd (%REC), cheese yield (%CY), and daily cheese yields (dCY). Cheese-making traits were analyzed using a mixed model, with parity, days in milk (DIM), lactose level, pH, SCC, TBC, and NaCl content as fixed effects, and farm, breed, glass tube, and animal as random effects. Results indicated that high levels of milk lactose were associated with reduced total solids recovery in the curd and lower cheese yields, because of the lower milk fat and protein contents in samples rich in lactose. Higher pH correlated with higher recovery of nutrients in the curd and higher cheese yield traits. These results may be explained by the positive correlation between pH and milk fat, protein, and casein in goat milk. High SCC were associated with higher recovery of solids and energy in the curd but lower recovery of protein. The higher cheese yield obtained from milk with high SCC was due to both increased recovery of lactose in the curd and water retention. Bacterial count proved to be the least important factor affecting cheese-making traits, but it decreased daily cheese yields, suggesting that, even if below the legal limits, TBC should be considered in order to monitor flock management and avoid economic losses. The effect of NaCl content on milk composition was linked with lower recovery of all nutrients in the curd during cheese-making. In addition, high milk NaCl content led to reductions in fresh cheese yield and cheese solids. The indirect indicators of the present study significantly affected the cheese-making process. Such information should be considered, to adjust the milk-to-cheese economic value and the milk payment system.     

Evaluation of oscillatory and shear strain behaviour for thermo-rheological plasticisation of non-ripened cheese curd: Effect of water,protein, and fat

Non-ripened cheese curd with different dry matter (34.5–47.0 g 100 g⁻¹), protein (13.4–30.4 g 100 g⁻¹), and fat (0.5–25.9 g 100 g⁻¹) contents were produced from pre-acidified milk (citric acid, pH 5.8) with different fat-to-protein ratios (0, 0.18, 0.33, 0.79, 1.60) and different curd cooking times (15 min, 30 min, 85 min). From small angle oscillatory temperature sweep and large strain capillary rheology shear experiments it was deduced that the protein content increases and fat decreases maximal loss tangent and storage modulus. This is discussed in relation to suggested changes in casein micelle voluminosity with temperature. A critical shear stress above which the flow behaviour changes from regular to melt fracture behaviour was observed. This is explained by shear jamming and the frequency dependency of the sol–gel transition.     

Phenotypic and genetic characterization of the occurrence of noncoagulating milk in dairy sheep

Milk coagulation ability is of central importance for the sheep dairy industry because almost all sheep milk is destined for cheese processing. The occurrence of milk with impaired coagulation properties is an obstacle to cheese processing and, in turn, to the profitability of the dairy companies. In this work, we investigated the causes of noncoagulation of sheep milk; specifically, we studied the effect of milk physicochemical properties on milk coagulation status [coagulating and noncoagulating (NC) milk samples, which do or do not coagulate within 30 min, respectively], and whether mid-infrared spectroscopy (MIR) could be used to assess variability in coagulation status. We also investigated the genetic background of milk coagulation ability. Individual milk samples were collected from 996 Sarda ewes farmed in 47 flocks located in Sardinia (Italy). Considered traits were daily milk yield, milk composition traits, and milk coagulation properties (rennet coagulation time, curd firming time, and curd firmness), and MIR spectra were acquired. About 9% of samples did not coagulate within 30 min. A logistic regression approach was used to test the effect of milk-related traits on milk coagulation status. A principal component (PC) analysis was carried out on the milk MIR spectra, and PC scores were then used as covariates in a logistic regression model to assess their relationship with milk coagulation status. Results of the present work demonstrated that the probability of having NC samples increases as milk contents of proteins and chlorides and somatic cell score increase. The analysis of PC extracted from milk spectra that influenced coagulation status highlighted key regions associated with lactose and protein concentrations, and others not associated with routinely collected milk composition traits. These results suggest that the occurrence of NC is mostly related to damage of the epithelium secretory mammary cells, which occurs with the advancement of a lactation or due to unhealthy mammary gland status. Genetic analysis of milk coagulation status and of the extracted PC confirmed the genetic background of the milk coagulability of sheep milk.     

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.     

Short communication: Fourier-transform mid-infrared spectroscopy to predict coagulation and acidity traits of sheep bulk milk

Sheep milk is mainly transformed into cheese; thus, the dairy industry seeks more rapid and cost-effective methods of analysis to determine milk coagulation and acidity traits. This study aimed to assess the feasibility of Fourier-transform mid-infrared spectroscopy to determine milk coagulation and acidity traits of sheep bulk milk and to classify milk samples according to their renneting capacity. A total of 465 bulk milk samples collected in 140 single-breed flocks of Comisana (84 samples, 24 flocks) and Sarda (381 samples, 116 flocks) breeds located in Central Italy were analyzed for coagulation properties (rennet coagulation time, curd firming time, and curd firmness) and acidity traits (pH and titratable acidity) using standard laboratory procedures. Fourier-transform mid-infrared spectroscopy prediction models for these traits were built using partial least squares regression analysis and were externally validated by randomly dividing the full data set into a calibration set (75%) and a validation set (25%). The discriminant capacity of the rennet coagulation time prediction model was determined using partial least squares discriminant analysis. Prediction models were more accurate for acidity traits than for milk coagulation properties, and the ratio of prediction to deviation ranged from 1.01 (curd firmness) to 2.14 (pH). Moreover, the discriminant analysis led to an overall accuracy of 74 and 66% for the calibration and validation sets, respectively, with greater sensitivity for samples that coagulated between 10 and 20 min and greater specificity to detect early-coagulating (<10 min) and late-coagulating (20–30 min) samples. Results suggest that Fourier-transform mid-infrared spectroscopy has the potential to help the dairy sheep industry identify milk with better coagulation ability for cheese production and thus improve milk transformation efficiency. However, further research is needed before this information can be exploited at the industry level.     

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.     

Somatic cell counts,chemical composition and coagulation properties of goat and sheep bulk tank milk

This study focused on the need for bulk milk tank somatic cell count (BMTSCC) thresholds and cut-off levels indicating a decrease in milk quality that consequently influences product quantity and quality. First, 226 ewes and 231 goat bulk tank milk samples were collected from different Israeli herds and coagulation properties were determined. Second, soft cheese was produced. No correlation of coagulation properties was found with BMTSCC for sheep milk up to 3264 × 10³ and goat milk up to 6452 × 10³ cells mL⁻¹. Coagulation properties of goat milk with cell count higher than the latter resulted in a significant decrease in curd firmness. For breeds and management system in Israel, 2500 × 10³ cells mL⁻¹ is suggested as the cut-off level for sheep and 3500 × 10³ cell mL⁻¹ for goats. The cell count cut-off level and milk price according to BMTSCC should be tested and then determined for every breed and management and final dairy product.     

The effect of calcium chloride addition on the microstructure and composition of Cheddar cheese

The addition of calcium is widely accepted as a tool in cheese-making but the effect on the microstructure of cheese during and following manufacture is not known. In this study, cheeses made with milk containing 200–600 mg L⁻¹ of additional CaCl₂ had significantly lower fat loss into the whey collected after cooking; however, the final fat composition or yield of cheese did not change. The microstructure of the gel with 300 or 600 mg L⁻¹ CaCl₂ addition was less porous and the cooked curd consisted of a denser protein network that may retain more fat during the early stages of manufacture. In contrast, the cheddared curd and cheese contained more micro-pores than cheeses with lower or no calcium addition. Such micro-pores could possibly be the channels by which fat escaped during pressing. This study shows that calcium addition altered the microstructure and pattern of fat loss during Cheddar manufacture.     

Effect of high-pressure treatment of ewe raw milk curd at 200 and 300 MPa on characteristics of Hispánico cheese

Hispánico cheese is a semihard variety made from a mixture of cow and ewe milks. Production of ewe milk declines in summer and autumn. To surmount the seasonal shortage of ewe milk and prevent the inactivation of milk enzymes by pasteurization, curd made in spring from ewe raw milk was pressurized at 200 and 300 MPa and stored frozen for 4 mo. Thawed ewe milk curds were added to fresh curd made from pasteurized cow milk for the manufacture of experimental Hispánico cheeses. Control cheese was made from a mixture of pasteurized cow and ewe milk in the same proportions as those used for experimental cheeses. Experimental cheeses exhibited lower dry matter content, higher aminopeptidase activity and total free amino acid concentration, and higher levels of acetic and propionic acids, aldehydes, alcohols, and esters compared with control cheese. In contrast, the concentration of total free fatty acids and ketones and the levels of textural parameters were significantly higher in control cheese. The use of ewe raw milk curd pressurized at 200 and 300 MPa, stored frozen and thawed for Hispánico cheese manufacture, was generally beneficial for cheese characteristics and increased cheese yield because of the lower dry matter content of experimental cheeses.     

Comparison of Bayesian and partial least squares regression methods for mid-infrared prediction of cheese-making properties in Montbéliarde cows

Assessing the cheese-making properties (CMP) of milks with a rapid and cost-effective method is of particular interest for the Protected Designation of Origin cheese sector. The aims of this study were to evaluate the potential of mid-infrared (MIR) spectra to estimate coagulation and acidification properties, as well as curd yield (CY) traits of Montbéliarde cow milk. Samples from 250 cows were collected in 216 commercial herds in Franche-Comté with the objectives to maximize the genetic diversity as well as the variation in milk composition. All coagulation and CY traits showed high variability (10 to 43%). Reference analyses performed for soft (SC) and pressed cooked (PCC) cheese technology were matched with MIR spectra. Prediction models were built on 446 informative wavelengths not tainted by the water absorbance, using different approaches such as partial least squares (PLS), uninformative variable elimination PLS, random forest PLS, Bayes A, Bayes B, Bayes C, and Bayes RR. We assessed equation performances for a set of 20 CMP traits (coagulation: 5 for SC and 4 for PCC; acidification: 5 for SC and 3 for PCC; laboratory CY: 3) by comparing prediction accuracies based on cross-validation. Overall, variable selection before PLS did not significantly improve the performances of the PLS regression, the prediction differences between Bayesian methods were negligible, and PLS models always outperformed Bayesian models. This was likely a result of the prior use of informative wavelengths of the MIR spectra. The best accuracies were obtained for curd yields expressed in dry matter (CY_DM) or fresh (CY_FRESH) and for coagulation traits (curd firmness for PCC and SC) using the PLS regression. Prediction models of other CMP traits were moderately to poorly accurate. Whatever the prediction methodology, the best results were always obtained for CY traits, probably because these traits are closely related to milk composition. The CY_DM predictions showed coefficient of determination (R²) values up to 0.92 and 0.87, and RS_y,x values of 3 and 4% for PLS and Bayes regressions, respectively. Finally, we divided the data set into calibration (2/3) and validation (1/3) sets and developed prediction models in external validation using PLS regression only. In conclusion, we confirmed, in the validation set, an excellent prediction for CY_DM [R² = 0.91, ratio of performance to deviation (RPD) = 3.39] and a very good prediction for CY_FRESH (R² = 0.84, RPD = 2.49), adequate for analytical purposes. We also obtained good results for both PCC and SC curd firmness traits (R² ≥ 0.70, RPD ≥1.8), which enable quantitative prediction.     

Composition, yield, and functionality of reduced-fat Oaxaca cheese: effects of using skim milk or a dry milk protein concentrate

The effect of adding either skim milk or a commercial dry milk protein concentrate (MPC) to whole milk on the composition, yield, and functional properties of Mexican Oaxaca cheese were investigated. Five batches of Oaxaca cheeses were produced. One batch (the control) was produced from whole milk containing 3.5% fat and 9% nonfat solids (SNF). Two batches were produced from milk standardized with skim milk to 2.7 and 1.8% fat, maintaining the SNF content at 9%. In the other 2 batches, an MPC (40% protein content) was used to standardize the milk to a SNF content of 10 and 11%, maintaining the milk fat content at 3.5%. The use of either skim milk or MPC caused a significant decrease in the fat percentage in cheese. The use of skim milk or MPC showed a nonsignificant tendency to lower total solids and fat recoveries in cheese. Actual, dry matter, and moisture-adjusted cheese yields significantly decreased with skim milk addition, but increased with MPC addition. However, normalized yields adjusted to milk fat and protein reference levels did not show significant differences between treatments. Considering skim milk-added and control cheeses, actual yield increased with cheese milk fat content at a rate of 1.34 kg/kg of fat (R = 0.88). In addition, cheese milk fat and SNF:fat ratio proved to be strong individual predictors of cheese moisture-adjusted yield (r² ≈ 0.90). Taking into account the results obtained from control and MPC-added cheeses, a 2.0-kg cheese yield increase rate per kg of milk MPC protein was observed (R = 0.89), with TS and SNF being the strongest predictors for moisture adjusted yield (r² ≈ 0.77). Reduced-fat Oaxaca cheese functionality differed from that of controls. In unmelted reduced-fat cheeses, hardness and springiness increased. In melted reduced-fat cheeses, meltability and free oil increased, but stretchability decreased. These changes were related to differences in cheese composition, mainly fat in dry matter and calcium in SNF.     

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.     

Microbiological,chemical, textural and sensory characteristics of Hispánico cheese manufactured using frozen ovine milk curds scalded at different temperatures

Hispánico cheese is a semi-hard variety, manufactured in Spain from a mixture of pasteurized bovine and ovine milk. To study one strategy for overcoming a seasonal shortage of ovine milk in summer and autumn, curds made from ovine milk, scalded at 32, 35 or 38 °C, were pressed for 30 min and frozen at ?24 °C for 4 months. After thawing, they were added to fresh bovine milk curd for the manufacture of experimental Hispánico cheeses. Control cheese was made from a mixture of pasteurized bovine and ovine milk in the same (80:20) proportion. No significant effect of the addition of frozen ovine milk curd or scalding temperature was found for lactic acid bacteria counts, dry matter content, hydrophilic and hydrophobic peptides, 45 out of 65 volatile compounds, texture, and sensory characteristics throughout a 60-day ripening period. Differences between cheeses, of low magnitude and little practical significance, were found for pH value, aminopeptidase activity, proteolysis, free amino acids, free fatty acids, and the remaining 20 volatile compounds. Thus, the addition of frozen ovine milk curd to fresh bovine milk curd does not alter the main physicochemical and sensory characteristics of Hispánico cheese.     

Fate of Listeria monocytogenes in Gouda microcheese: No growth,and substantial inactivation after extended ripening times

This challenge study demonstrates that Listeria monocytogenes does not grow in Gouda cheese: during the first 8 weeks of ripening no growth was observed and between 8 and 52 weeks viable numbers declined significantly in a well-established Gouda microcheese system. Cheese milk was artificially contaminated just prior to addition of the starter culture. Three individual L. monocytogenes strains were used, including strains originating from cheese, a cheese plant environment and a reference strain. During curd formation, viable numbers of L. monocytogenes increased by 0.5 log cfu g⁻¹, resulting from entrapment in the curd. No growth was observed during the first 8 weeks of ripening. A significant decline in the viable numbers of L. monocytogenes was observed in Gouda cheese that was ripened for longer than 8 weeks. Two factors that could possibly control the fate of L. monocytogenes in Gouda cheese were lactic acid and water activity.     

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.