Goat cheese yield and recovery of fat, protein, and total solids in curd are affected by milk coagulation properties

Utilization of two plant polysaccharides to improve fresh goat milk cheese: Texture, rheological properties, and microstructure characterization

This study aimed to evaluate the effects of added jujube polysaccharide (JP) and Lycium barbarum polysaccharide (LBP) on the texture, rheological properties, and microstructure of goat milk cheese. Seven groups of fresh goat milk cheese were produced with 4 levels (0, 0.2, 0.6, and 1%, wt/wt) of JP and LBP. The goat milk cheese containing 1% JP showed the highest water-holding capacity, hardness, and the strongest rheological properties by creating a denser and more stable casein network structure. In addition, the yield of goat milk cheese was substantially improved as a result of JP incorporation. Cheeses containing LBP expressed lower fat content, higher moisture, and softer texture compared with the control cheese. Fourier-transform infrared spectroscopy and low-field nuclear magnetic resonance analysis demonstrated that the addition of JP improved the stability of the secondary protein structure in cheese and significantly enhanced the binding capacity of the casein matrix to water molecules due to strengthened intermolecular interactions. The current research demonstrated the potential feasibility of modifying the texture of goat milk cheese by JP or LBP, available for developing tunable goat milk cheese to satisfy consumer preferences and production needs.

Phenotypic Analysis of Fourier-Transform Infrared Milk Spectra in Dairy Goats

The infrared spectrum of bovine milk is used to predict many interesting traits, whereas there have been few studies on goat milk in this regard. The objective of this study was to characterize the major sources of variation in the absorbance of the infrared spectrum in caprine milk samples. A total of 657 goats belonging to 6 breeds and reared on 20 farms under traditional and modern dairy systems were milk-sampled once. Fourier-transform infrared (FTIR) spectra were taken (2 replicates per sample, 1314 spectra), and each spectrum contained absorbance values at 1060 different wavenumbers (5000 to 930 × cm^-1), which were treated as a response variable and analyzed one at a time (i.e., 1060 runs). A mixed model, including the random effects of sample/goat, breed, flock, parity, stage of lactation, and the residual, was used. The pattern and variability of the FTIR spectrum of caprine milk was similar to those of bovine milk. The major sources of variation in the entire spectrum were as follows: sample/goat (33% of the total variance); flock (21%); breed (15%); lactation stage (11%); parity (9%); and the residual unexplained variation (10%). The entire spectrum was segmented into five relatively homogeneous regions. Two of them exhibited very large variations, especially the residual variation. These regions are known to be affected by the absorbance of water, although they also exhibited wide variations in the other sources of variation. The average repeatability of these two regions were 45% and 75%, whereas for the other three regions it was about 99%. The FTIR spectrum of caprine milk could probably be used to predict several traits and to authenticate the origin of goat milk.

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

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

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.

Composition and aptitude for cheese-making of milk from cows, buffaloes, goats, sheep, dromedary camels, and donkeys

Bovines account for about 83% of the milk and dairy products consumed by humans worldwide, the rest represented by bubaline, caprine, ovine, camelid, and equine species, which are particularly important in areas of extensive pastoralism. Although milk is increasingly used for cheese production, the cheese-making efficiency of milk from the different species is not well known. This study compares the cheese-making ability of milk sampled from lactating females of the 6 dairy species in terms of milk composition, coagulation properties (using lactodynamography), curd-firming modeling, nutrients recovered in the curd, and cheese yield (through laboratory model-cheese production). Equine (donkey) milk had the lowest fat and protein content and did not coagulate after rennet addition. Buffalo and ewe milk yielded more fresh cheese (25.5 and 22.9%, respectively) than cow, goat, and dromedary milk (15.4, 11.9, and 13.8%, respectively). This was due to the greater fat and protein contents of the former species with respect to the latter, but also to the greater recovery of fat in the curd of bubaline (88.2%) than in the curd of camelid milk (55.0%) and consequent differences in the recoveries of milk total solids and energy in the curd; protein recovery, however, was much more similar across species (from 74.7% in dromedaries to 83.7% in bovine milk). Compared with bovine milk, the milk from the other Artiodactyla species coagulated more rapidly, reached curd firmness more quickly (especially ovine milk), had a more pronounced syneresis (especially caprine milk), had a greater potential asymptotical curd firmness (except dromedary and goat milk), and reached earlier maximum curd firmness (especially caprine and ovine milk). The maximum measured curd firmness was greater for bubaline and ovine milk, intermediate for bovine and caprine milk, and lower for camelid milk. The milk of all ruminant species can be used to make cheese, but, to improve efficiency, cheese-making procedures need to be optimized to take into account the large differences in their coagulation, curd-firming, and syneresis properties.

Advances in research on calf rennet substitutes and their effects on cheese quality

Milk coagulation is an important step in cheese production, and milk-clotting enzymes (MCEs) play a major role in this process. Calf rennet is the most widely used MCE in the cheese industry. The use of calf rennet substitutes is becoming necessary due to the limited availability of calf rennet and the increase in cheese consumption. The objective of this review is to summarize the latest findings on calf rennet substitutes (animal MCEs, plant-derived MCEs, recombinant MCEs and microbial MCEs) and their application in cheese production. Special emphasis has been placed on aspects of the effects of these substitutes on hydrolysis, functional peptides, cheese variety and cheese yield. The advantages and disadvantages of different calf rennet substitutes are discussed, in which microbial MCEs have the advantages of less expensive production, greater biochemical diversity, easier genetic modification, etc. In particular, some of these MCEs have suitable characteristics for cheese production and are considered to be the most potential calf rennet substitutes. Moreover, challenges and future perspectives are presented to provide inspiration for the development of excellent calf rennet substitutes.

Derivation of multivariate indices of milk composition, coagulation properties, and curd yield in Manchega dairy sheep

This study approaches the interrelation patterns between composition of milk and whey, curd yield, chromaticity, syneresis, and technological quality of Manchega sheep milk using multivariate factor analysis. In addition, the effect of the main husbandry components (flock, prolificacy, season of the year, stage of lactation, and parity) on the common latent factors that define the pattern of variation of Manchega milk was assessed. For this purpose, 1,200 individual Manchega ewe milk samples from 4 different flocks registered under the Protected Designation of Origin Queso Manchego were analyzed (50 ewes/flock). Samples were collected in 2 different seasons of the year (spring and autumn) and at 3 time points per season: early, mid-, and late lactation. The obtained results suggested that curd yield mainly depends on milk composition, and the retention of water in the curd is related to coagulation traits. Thus, composition and moisture content could be useful indicators to assess the efficiency and quality of milk intended for cheesemaking, regardless of the analysis of coagulation properties. Finally, in terms of husbandry, a direct effect of flock and stage of lactation was observed on all analyzed factors, with a lower influence of season and parity.

Breed of goat affects the prediction accuracy of milk coagulation properties using Fourier-transform infrared spectroscopy

The prediction of traditional goat milk coagulation properties (MCP) and curd firmness over time (CF_t) parameters via Fourier-transform infrared (FTIR) spectroscopy can be of significant economic interest to the dairy industry and can contribute to the breeding objectives for the genetic improvement of dairy goat breeds. Therefore, the aims of this study were to (1) explore the variability of milk FTIR spectra from 4 goat breeds (Camosciata delle Alpi, Murciano-Granadina, Maltese, and Sarda), and to assess the possible discriminant power of milk FTIR spectra among breeds, (2) assess the viability to predict coagulation traits by using milk FTIR spectra, and (3) quantify the effect of the breed on the prediction accuracy of MCP and CF_t parameters. In total, 611 individual goat milk samples were used. Analysis of variance of measured MCP and CF_t parameters was carried out using a mixed model including the farm and pendulum as random factors, and breed, parity, and days in milk as fixed factors. Milk spectra for each goat were collected over the spectral range from wavenumber 5,011 to 925 × cm^-1. Discriminant analysis of principal components was used to assess the ability of FTIR spectra to identify breed of origin. A Bayesian model was used to calibrate equations for each coagulation trait. The accuracy of the model and the prediction equation was assessed by cross-validation (CRV; 80% training and 20% testing set) and stratified CRV (SCV; 3 breeds in the training set, one breed in the testing set) procedures. Prediction accuracy was assessed by using coefficient of determination of validation (R²_VAL), the root mean square error of validation (RMSE_VAL), and the ratio performance deviation. Moreover, measured and FTIR predicted traits were compared in the SCV procedure by assessing their least squares means for the breed effect, Pearson correlations, and variance heteroscedasticity. Results showed the feasibility of using FTIR spectra and multivariate analyses to correctly assign milk samples to their breeds of origin. The R²_VAL values obtained with the CRV procedure were moderate to high for the majority of coagulation traits, with RMSE_VAL and ratio performance deviation values increasing as the coagulation process progresses from rennet addition. Prediction accuracy obtained with the SCV were strongly influenced by the breed, presenting general low values restricting a practical application. In addition, the low Pearson correlation coefficients of Sarda breed for all the traits analyzed, and the heteroscedastic variances of Camosciata delle Alpi, Murciano-Granadina, and Maltese breeds, further indicated that it is fundamental to consider the differences existing among breeds for the prediction of milk coagulation traits.

Goat farm variability affects milk Fourier-transform infrared spectra used for predicting coagulation properties

Driven by the large amount of goat milk destined for cheese production, and to pioneer the goat cheese industry, the objective of this study was to assess the effect of farm in predicting goat milk-coagulation and curd-firmness traits via Fourier-transform infrared spectroscopy. Spectra from 452 Sarda goats belonging to 14 farms in central and southeast Sardinia (Italy) were collected. A Bayesian linear regression model was used, estimating all spectral wavelengths' effects simultaneously. Three traditional milk-coagulation properties [rennet coagulation time (min), time to curd firmness of 20 mm (min), and curd firmness 30 min after rennet addition (mm)] and 3 curd-firmness measures modeled over time [rennet coagulation time estimated according to curd firmness change over time (RCT_eq), instant curd-firming rate constant, and asymptotical curd firmness] were considered. A stratified cross validation (SCV) was assigned, evaluating each farm separately (validation set; VAL) and keeping the remaining farms to train (calibration set) the statistical model. Moreover, a SCV, where 20% of the goats randomly taken (10 replicates per farm) from the VAL farm entered the calibration set, was also considered (SCV₈₀). To assess model performance, coefficient of determination (R²_VAL) and the root mean squared error of validation were recorded. The R²_VAL varied between 0.14 and 0.45 (instant curd-firming rate constant and RCT_eq, respectively), albeit the standard deviation was approximating half of the mean for all the traits. Although average results of the 2 SCV procedures were similar, in SCV₈₀, the maximum R²_VAL increased at about 15% across traits, with the highest observed for time to curd firmness of 20 mm (20%) and the lowest for RCT_eq (6%). Further investigation evidenced important variability among farms, with R²_VAL for some of them being close to 0. Our work outlined the importance of considering the effect of farm when developing Fourier-transform infrared spectroscopy prediction equations for coagulation and curd-firmness traits in goats.

Short communication: Dietary protein restriction and conjugated linoleic acid supplementation in dairy cows affect milk composition, the cheese-making process, and cheese quality

We used 20 mid-lactating Holstein cows, housed in 4 pens according to a Latin square design, to evaluate the effects of dietary protein restriction (crude protein: 12.3 vs. 15.0% dry matter) and conjugated linoleic acid supplementation (CLA: 6.34 g/d of C18:2cis-9,trans-11 and 6.14 g/d of C18:2trans-10,cis-12) on milk composition, coagulation, curd firming and syneresis modeling, and cheese yield and quality (96 small cheeses). Dietary crude protein restriction, suggested as a way to reduce N excretion in farming, caused a reduction in milk protein content (-4%,), milk casein (-3.8%), lactose (-1%), cheese soluble protein (-16.8%), and the cheese maturation index (-15%), and a correlated increase in cheese fat content (+7.5%) and the fat to protein ratio (+18%). A modest reduction (-0.9%) in milk fat recovery in the curd did not affect cheese yield. The addition of CLA to the cows' diet, suggested as a way to improve N use efficiency and the nutritional value of dairy products, caused substantial alterations to the milk composition, cheese-making process, and cheese quality. The CLA reduced the fat (-12.3%), protein (-2%), casein (-2.2%), lactose (-1.0), and total solids (-4%) contents of milk, tended to delay coagulation, and weakened curd firming. The CLA reduced the fresh cheese yield (-7.5%) and cheese solids (-8.2%) because of the lower nutrient content of the milk, but also because of a lower recovery of milk protein in the curd (-0.9%) and lower total solids (-4.5%). It also reduced the fat content in the ripened cheese (-11.8%), as well as the fat to protein ratio (-19.4%) as a result of having increased the protein content (+9.3%). Last, it increased the lightness of the paste of the ripened cheeses (+3.3%), and especially the shear force (+16.3%). Dietary crude protein restriction, and CLA addition in particular, substantially altered the milk composition, cheese-making process, and cheese quality, and therefore needs to be carefully evaluated. Further studies are required to shed light on the causes of these modifications.