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The aims of this study were to (1) characterize sheep milk for nonenzymatic antioxidant activity via 2 different assays, namely the ferric reducing antioxidant power (FRAP) and the 2,2-diphenyl-1-picryl-hydrazyl-hydrate (DPPH), and (2) investigate the effect of milk composition and animal-related parameters on these 2 assays by using the generalized additive mixed model (GAMM) approach. A total of 740 ewes belonging to the Massese and Comisana breeds were sampled once during the morning milking across 11 sampling sessions. All milk samples were analyzed for fat, protein, CN, and lactose, SCS, and minerals (Ca, Mg, Na, and Cl). The FRAP and DPPH assays were tested to measure the nonenzymatic antioxidant activity of milk, expressed as micromolar equivalents (μM Eq) of ascorbic acid/mL of milk and percent of inhibition, respectively. The GAMM model included the effect of parity and breed as parametric terms, and the effect of DIM, milk yield, and the interactions protein × fat, CN × SCS, Ca × Mg, and Na × Cl as smooth terms. The sampling day was included in the model as a random effect. Results revealed that the nonenzymatic antioxidant capacity of sheep milk, expressed as FRAP, was affected by DIM, potentially because of changes in milk composition over time. Conversely, parity and breed of ewes affected DPPH, suggesting that age- and breed-specific factors are related to specific components in milk acting as hydrogen donors. Milk fat and high CN percentages were found to significantly affect FRAP, and protein content was crucial for high DPPH levels. Additionally, Ca and Mg emerged as important nonenzymatic antioxidants for both FRAP and DPPH, highlighting their important role in antioxidant activity of sheep milk. In contrast, combinations of Na and Cl were particularly influential for FRAP, revealing the complex relationship between these minerals and nonenzymatic antioxidant activity of milk. These findings offer valuable insights into the factors affecting the antioxidative properties of sheep milk, highlighting the need for further exploration of other nonenzymatic antioxidants and their contribution to the total antioxidant activity., (© 2024, The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Parmigiano Reggiano protected designation of origin (PDO) cheese inherently exhibits variability due to the characteristics of the production system, contributing to heterogeneity in the composition and properties of milk used in the cheese-making process. This variability leads to variations in cheese yield and nutrient recoveries. The direct measurement of these traits is not feasible in routine practice. Therefore, among indirect analytical techniques, infrared spectroscopy could help to predict these traits from the milk spectra collected directly in the dairy plant. This work aimed to assess the impact of cow breed, farm, dairy factory, and production parameters on cheese-making traits prediction. The impact of this variability has been measured by prediction bias, using a stratified cross-validation. The results confirmed high variability across dairy industries and showed that breed had the highest influence. The use of milk spectra combined with chemometrics was feasible to characterize Parmigiano Reggiano PDO production., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The prediction of the cheese yield (%CY) traits for curd, solids, and retained water and the amount of fat, protein, solids, and energy recovered from the milk into the curd (%REC) by Bayesian models, using Fourier-transform infrared spectroscopy (FTIR), can be of significant economic interest to the dairy industry and can contribute to the improvement of the cheese process efficiency. The yields give a quantitative measure of the ratio between weights of the input and output of the process, whereas the nutrient recovery allows to assess the quantitative transfer of a component from milk to cheese (expressed in % of the initial weight). The aims of this study were: (1) to investigate the feasibility of using bulk milk spectra to predict %CY and %REC traits, and (2) to quantify the effect of the dairy industry and the contribution of single-spectrum wavelengths on the prediction accuracy of these traits using vat milk samples destined to the production of Grana Padano Protected Designation of Origin cheese. Information from 72 cheesemaking days (in total, 216 vats) from 3 dairy industries were collected. For each vat, the milk was weighed and analyzed for composition (total solids [TS], lactose, protein, and fat). After 48 h from cheesemaking, each cheese was weighed, and the resulting whey was sampled for composition as well (TS, lactose, protein, and fat). Two spectra from each milk sample were collected in the range between 5,011 and 925 cm -1 and averaged before the data analysis. The calibration models were developed via a Bayesian approach by using the BGLR (Bayesian Generalized Linear Regression) package of R software. The performance of the models was assessed by the coefficient of determination (R 2 VAL ) and the root mean squared error (RMSE VAL ) of validation. Random cross-validation (CVL) was applied [80% calibration and 20% validation set] with 10 replicates. Then, a stratified cross-validation (SCV) was performed to assess the effect of the dairy industry on prediction accuracy. The study was repeated using a selection of informative wavelengths to assess the necessity of using whole spectra to optimize prediction accuracy. Results showed the feasibility of using FTIR spectra and Bayesian models to predict cheesemaking traits. The R 2 VAL values obtained with the CVL procedure were promising in particular for the %CY and %REC for protein, ranging from 0.44 to 0.66 with very low RMSE VAL (from 0.16 to 0.53). Prediction accuracy obtained with the SCV was strongly influenced by the dairy factory industry. The general low values gained with the SCV do not permit a practical application of this approach, but they highlight the importance of building calibration models with a dataset covering the largest possible sample variability. This study also demonstrated that the use of the full FTIR spectra may be redundant for the prediction of the cheesemaking traits and that a specific selection of the most informative wavelengths led to improved prediction accuracy. This could lead to the development of dedicated spectrometers using selected wavelengths with built-in calibrations for the online prediction of these innovative traits., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Costs of production have deeply increased each year in the last decades, breeders are continuously looking for more cost effective and more efficient ways to produce milk. Despite the major signs of progress in productivity, it is fundamental to optimize rather than maximize the performances of the dairy cows. Mastitis is still a highly prevalent disease in the dairy sector which causes several economic losses and environmental effect. Its accurate and early diagnosis is crucial to improve profitability of dairy cows and contribute to a more sustainable dairy industry. Among mastitis reduction strategies, there is the urgent need to implement breeding objectives to select cows displaying mastitis resistance by investigating the genetic mechanisms at the base of the inflammatory response. Therefore, in this study we aimed to further understand the genetic background of the differential somatic cell count (DSCC), which provides thorough insights on the actual inflammatory status of the mammary glands. The objectives of this study were to estimate on a cohort of 20,215 Italian Simmental cows over a 3-yr period: (1) the heritability and repeatability values of somatic cell score (SCS) and DSCC, (2) the genetic and phenotypic correlations between these 2 traits and milk production and milk composition traits, (3) the heritability and repeatability values of SCS and DSCC within class of udder health status. Heritability was low both for SCS (0.06) and DSCC (0.08), whereas the repeatability values for these traits were 0.43 and 0.36, suggesting that the magnitude of cow permanent environmental effect for these traits is remarkable. The genetic and phenotypic correlation of SCS with DSCC was 0.612 and 0.605, respectively. Because both significantly differed from the unit, we must consider those traits as different ones. This latter aspect corroborates the need to consider the DSCC as a further indicator of inflammatory status which might be implemented in the Simmental breed genetic evaluation. It is worthy to mention that heritability estimates for SCS and DSCC were the highest in healthy cows compared with the other udder health classes. This implies that when the udder health status changes, it is most likely due to environmental factors rather than aspects related to the animal's genetics. In contrast, the highest additive genetic variance and heritability found for SCS and DSCC in the healthy group might reveal the potential to further implement breeding strategies to select for healthier animals., (© 2023, The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

The objectives of this study were to explore the use of Fourier-transform infrared (FTIR) spectroscopy on individual sheep milk samples for predicting cheese-making traits, and to test the effect of the farm variability on their prediction accuracy. For each of 121 ewes from 4 farms, a laboratory model cheese was produced, and 3 actual cheese yield traits (fresh cheese, cheese solids, and cheese water) and 4 milk nutrient recovery traits (fat, protein, total solids, and energy) in the curd were measured. Calibration equations were developed using a Bayesian approach with 2 different scenarios: (1) a random cross-validation (80% calibration; 20% validation set), and (2) a leave-one-out validation (3 farms used as calibration, and the remaining one as validation set) to assess the accuracy of prediction of samples from external farms, not included in calibration set. The best performance was obtained for predicting the yield and recovery of total solids, justifying for the practical application of the method at sheep population and dairy industry levels. Performances for the remaining traits were lower, but still useful for the monitoring of the milk processing in the case of fresh curd and recovery of energy. Insufficient accuracies were found for the recovery of protein and fat, highlighting the complex nature of the relationships among the milk nutrients and their recovery in the curd. The leave-one-out validation procedure, as expected, showed lower prediction accuracies, as a result of the characteristics of the farming systems, which were different between calibration and validation sets. In this regard, the inclusion of information related to the farm could help to improve the prediction accuracy of these traits. Overall, a large contribution to the prediction of the cheese-making traits came from the areas known as "water" and "fingerprint" regions. These findings suggest that, according to the traits studied, the inclusion of water regions for the development of the prediction equation models is fundamental to maintain a high prediction accuracy. However, further studies are necessary to better understand the role of specific absorbance peaks and their contribution to the prediction of cheese-making traits, to offer reliable tools applicable along the dairy ovine chain., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

The aim of this study was to quantify some environmental (individual herds, herd productivity, milking system, and season) and animal factors [individual animals, breed, days in milk (DIM) and parity] on the variability of the log-10 transformation of somatic cell count (LSCC) and differential somatic cell count (DSCC) on individual bovine milk. A total of 159,360 test-day records related to milk production and composition were extracted from 12,849 Holstein-Friesian and 9,275 Simmental cows distributed across 223 herds. Herds were classified into high and low productivity, defined according to the average daily milk net energy output (DMEO) yielded by the cows. Data included daily milk yield (DYM; kg/d), milk fat, protein, lactose, SCC, and DSCC, and information on herds (i.e., productivity, milking system). The daily production of total and differential somatic cells in milk was calculated and then log-10 transformed, obtaining DLSCC and DLDSCC, respectively. Data were analyzed using a mixed model including the effects of individual herd, animal, repeated measurements intra animal as random, and herd productivity, milking system, season, breed, DIM, parity, DIM × parity, breed × season, DIM × milking system and parity × milking system as fixed factors. Herds with a high DMEO were characterized by a lower content of LSCC and DSCC, and higher DLSCC and DLDSCC, compared to the low DMEO herds. The association between milking system and somatic cell traits suggested that the use of the automatic milking systems would not allow for a rapid intervention on the cow, as evidenced by the higher content of all somatic cell traits compared to the other milking systems. Season was an important source of variation, as evidenced by high LSCC and DSCC content in milk during summer. Breed of cow had a large influence, with Holstein-Friesian having greater LSCC, DSCC, DLSCC, and DLDSCC compared to Simmental. With regard to DIM, the variability of LSCC was mostly related to that of DSCC, showing an increase from calving to the end of lactation, and suggesting the higher occurrence of chronic mastitis in cows toward the end of lactation. All the somatic cell traits increased across number of parities, possibly because older cows may have increased susceptibility to intramammary infections., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Society of Animal Science.)

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 (R 2 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 R 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 R 2 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.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., (Copyright © 2021 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

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 (SCV 80 ). To assess model performance, coefficient of determination (R 2 VAL ) and the root mean squared error of validation were recorded. The R 2 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 SCV 80 , the maximum R 2 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 R 2 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., (Copyright © 2021 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Different fractions of milk nitrogenous compounds (not only caseins) have different effects on the nutritional value of milk, its coagulation and curd firming properties, and its cheese-making efficiency. To assess different sources of variation, especially the cows' breed and genetic variants of the main protein fractions, milk samples were collected from 1,504 cows belonging to 3 dairy breeds (Holstein-Friesian, Brown Swiss, and Jersey) and 3 dual-purpose breeds (Simmental, Rendena, and Alpine Grey) reared in 41 multibreed herds. Beyond crude protein, casein (CN), and urea, 7 protein fractions were analyzed using HPLC, and 5 other N fraction traits were calculated. All 15 traits were measured qualitatively (% of milk N) and quantitatively (g/L of milk). The HPLC technique allowed us to discriminate between the main genetic variants of β-CN, κ-CN, and β-lactoglobulin and thus to genotype the cows for the CSN2, CSN3, and BLG genes, respectively. Data were analyzed using 2 mixed models, both including the effects of herd-date, breed, parity, and lactation stage, and only one also including the effects of the genotypes of the milk proteins. Breed of cow explained 2 to 36% of phenotypic variability for all the N fractions, with the exception of the urea and total casein contents of milk and the urea and β-CN proportions of total milk N. Lactation stage had a considerable influence on the amount (g/L) of almost all the protein fractions in milk, but neither the nonprotein N fractions nor the percentage of milk N protein profile were affected. The inclusion of the CSN2, CSN3, and BLG genotypes in the model explained a large part of the total variability in all the milk protein and nonprotein fractions except urea. It also reduced the variance explained by breed and residual factors. An exception was shown by the proportion of α S1 -CN variance explained by breed that moved from 13 to 28%. Similarly, for amount (g/L) of β-CN, the effect of breed became significant (12%), whereas it was almost null before inclusion of genotypes. In terms of percentage of milk N, the genotypes of CSN3 notably affected all the casein fractions, whereas the BLG genotypes had a much greater influence on most noncasein traits. The genotypes of the CSN2 gene exerted an appreciable effect on α S2 -CN and not β-CN, as expected. Comparing the 2 models, we were also able to discriminate the effect of the breed on a milk N fraction, both quantitatively and qualitatively, in 2 quotas: the first due to the milk protein polymorphisms (major genes) and the second due to other genetic factors (polygene), after correcting for the effect of herd-date of sampling, parity, and lactation stage. The knowledge about the detailed milk protein profile of different cattle breeds provided by this study could be of great benefit for the dairy industry, providing new tools for the enhancement of milk payment systems and breeding program designs., (Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The aims of this study were to explore the variability of milk composition, coagulation properties, and cheese-making traits of the Sarda goat breed, and to investigate the effects of animal and farm factors, and the geographic area (Central-East vs. South-West) of an insular region of Italy, Sardinia. A total of 570 Sarda goats reared in 21 farms were milk-sampled during morning milking. Individual milk samples were analyzed for composition, traditional milk coagulation properties (MCP), modeled curd-firming over time parameters (CF t ), and cheese-making traits (cheese yield, %CY; recovery of nutrients, %REC; daily cheese yield, dCY). Farms were classified into 2 categories based on milk energy level (MEL; high or low), defined according to the average net energy of milk daily produced by the lactating goats. Milk yield and composition were analyzed using a mixed model including the fixed effects of MEL, geographic area, days in milk, and parity, and the random effect of farm within MEL and geographic area. Data about MCP, CF t , and the cheese-making process were analyzed using the same model, with the inclusion of the effects of animal and pendulum of the lactodynamograph instrument, allowing the measure of repeatability of these traits. Results showed that animal had greater influence on coagulation and cheese-making traits compared with farm effect. Days in milk influenced milk composition, whose changes partly reflected the modifications of %CY traits. Moreover, large differences were observed between primiparous and multiparous goats: primiparous goats produced less milk of better quality (higher fat, lower somatic cell and bacterial counts) and less cheese, but with higher recovery of fat and protein in the curd, compared with multiparous goats. The repeatability was very high, for both coagulation (84.0 to 98.8%) and cheese-making traits (89.7 to 99.9%). The effect of MEL was significant for daily productions of milk and cheese, coagulation time, and recovery of protein in the curd, which were better in high-MEL farms. As regards geographic area, milk composition and percentage cheese yield were superior in the Central-East area, whereas daily milk and cheese production and MCP were better in the South-West. This result was explainable by the phenomenon of crossbreeding Sarda goats with Maltese bucks, which occurred with greater intensity in the South-West than in the Central-East area of the island. The results provided by this study could be of great interest for the goat dairy sector. Indeed, the methods described in the present study could be applicable for other farming methods, goat breeds, and geographic areas. The collection of a wide range of phenotypes at individual animal level is fundamental for the characterization of local populations and can be used to guarantee breed conservation and the persistence of traditional farming systems, and to increase farmers' profit., (Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The aims of the present research were to quantify the effects of each coagulation trait, traditional milk coagulation properties [MCP: rennet coagulation time (RCT), curd-firming time (k 20 ), and curd firmness at 30 min (a 30 )], and modeled curd-firming over time (CF t ) parameters [estimated rennet coagulation time (RCT eq ), curd-firming instant rate constant (k CF ), and potential curd firmness (CF P )] directly on the following: (1) recovery of 3 milk components in the curd (%REC), (2) 3 measures of cheese yield (%CY), and (3) 3 daily cheese yield traits (dCY) from goat milk. Cheese-making traits were analyzed using 2 mixed different models, the first to test MCP and the second to test CF t parameters. Pearson correlations were also calculated. Significant and favorable relationships (negative for time intervals and positive for CF measures) were found between the traditional MCP and the CF t parameters and %REC and %CY traits. The effects of milk fat and protein contents were particularly important on all cheese-making traits, with the only exception being the effect of fat content on water retention in cheese (%CY WATER ). We found an optimum value of milk k 20 , associated with the highest recovery of components and cheese yield in solids (%CY SOLIDS ). In addition, a lower level of curd water retention and an increased fresh curd yield (%CY CURD ) were associated with greater recovery of fat. The collection of all available information during the process of milk coagulation and curd-firming allowed us to discover the effect of RCT eq on %REC traits and %CY SOLIDS , which had not previously been revealed for traditional RCT. Moreover, higher k CF values were associated with increased %CY CURD and %CY SOLIDS . Given that CF t parameters showed a high level of independence from one another, these can also be easily used and characterized in future applications at the industry level. Information provided by traditional and modeled coagulation properties could efficiently support the goat dairy industry and lay the foundations for a quality payment scheme for goat milk., (Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The aim of this study was to quantify the major sources of variation in the levels of 15 minerals in individual milk samples collected from cows raised in multibreed dairy herds. The herds (n = 27) were classified into 2 categories, according to milk productivity. Milk productivity was based on the net energy of lactating cows' average daily milk yield. Milk samples were collected from 240 cows of 6 different breeds: 3 specialized dairy (Holstein-Friesian, Brown Swiss, and Jersey) and 3 dual-purpose (Simmental, Rendena, and Alpine Grey). The samples were analyzed for macro-elements (Na, Mg, P, S, K, and Ca), essential micro-elements (Mn, Fe, Cu, Zn, and Se), and environmental micro-elements (B, Si, Sr, and Sn), using inductively coupled plasma-optical emission spectrometry. Data were analyzed using a linear mixed model that included fixed effects of days in milk (DIM), parity, breed, and herd productivity, and a random effect of herd-date within productivity level. Results showed that the effect of herd-date varied across minerals. It was especially large for environmental minerals (ranging from 47 to 91% of total variance) and ranged from 11 to 61% for macrominerals and essential microminerals. Milk samples collected from farms with a high level of herd productivity had a richer mineral profile than samples from low-productivity herds. Parity only influenced macrominerals, with the exception of S and Ca, while DIM influenced almost all minerals, with a few exceptions among the environmental elements. Differences in mineral profile were small between specialized and dual-purpose breeds, but they were large within the group of the specialized cows. These breed differences were reduced after adjusting for milk quality and yield, particularly in the case of milk Mg, S, Ca, Mn, and Zn levels. Milk samples from the Jersey and Brown Swiss cows had higher mineral levels (Sn excluded) than milk from the Holstein-Friesian cows; the other breeds of Alpine origin produced milk of intermediate quality. Our findings suggest that breed has a stronger effect on macrominerals and some of the essential microminerals than herd productivity, parity, and DIM. The modification of the mineral profile in milk seems possible for many minerals, but it likely depends on genetics (e.g., breed, selection) and on environmental and management factors in variable proportions according to the mineral considered., (Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

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., (Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

We investigated whether variation of the sheep Growth Hormone Receptor (GHR), Growth Hormone Releasing Hormone Receptor (GHRHR) and Insulin-Like Growth Factor 1 (IGF1) genes were associated with milk coagulation properties (MCP) in sheep. The GHR, GHRHR and IGF1 genes are part of the GH system, which is known to modulate metabolism, growth and reproduction as well as mammogenesis and galactopoiesis in dairy species. A total of 380 dairy Sarda sheep were genotyped for 36 SNPs mapping to these three genes. Traditional MCP were measured as rennet coagulation time (RCT), curd-firming time (k20) and curd firmness at 30 m (a30). Modeling of curd firming over time (CFt) was based on a 60 m lactodynamographic test, generating a total of 240 records of curd firmness (mm) for each milk sample. The model parameters obtained included: the rennet coagulation time as a result of modeling all data available (RCTeq, min); the asymptotic potential value of curd firmness (CFP, mm) at an infinite time; the CF instant rate constant (kCF, %/min); the syneresis instant rate constant (kSR, %/min); the maximum value of CF (CFmax, mm) and the time at achievement of CFmax (tmax, min). Statistical analysis revealed that variation of the GHR gene was significantly associated with RCT, kSR and CFP (P < 0.05). No other significant associations were detected. These findings may be useful for the dairy industry, as well as for selection programs.

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., (Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The present study investigated the effect of different levels of fat, protein, and casein on (1) traditional milk coagulation properties, and (2) curd firming over time parameters of 1,272 goat milk samples. Relationships between fat, protein, and casein and some indicators of udder health status (lactose, pH, somatic cells, bacterial count, and NaCl) were also investigated. Traditional milk coagulation properties and modeled curd-firming parameters were analyzed using a mixed model that considered the effect of days in milk, parity, farm, breed, the pendulum of the instrument, and different levels of fat, protein, and casein. Fat, protein, and casein were also tested with the same model but one at a time. Information provided by this model demonstrated the effect of one component alone, without contemporarily considering that of the others. The results allowed us to clarify the effect of the major milk nutrients on coagulation, curd firming, and syneresis ability of goat milk. In particular, milk rich in fat was associated with better coagulation properties, whereas milk rich in protein was associated with delayed coagulation. The high correlation of fat with protein and casein contents suggests that the effect of fat on the cheese-making process is also attributable to the effects of protein and casein. When only protein or only casein was included in the statistical model, the pattern of coagulation, curd firming, and syneresis was almost indistinguishable. The contemporary inclusion of protein and casein in the statistical model did not generate computing problems and allowed us to better characterize the role of protein and casein. Consequently, given their strong association, we also tested the effect of casein-to-protein ratio (i.e., casein number). Higher values of casein number led to a general improvement in the coagulation ability of milk, suggesting that casein-to-protein ratio, not just protein or casein, should be considered when milk is destined for cheese making. These results are especially useful for dairy farmers who want to increase their profits by improving the technological quality of the milk produced., (Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Goat milk and cheese production is continuously increasing and milk composition and coagulation properties (MCP) are useful tools to predict cheesemaking aptitude. The present study was planned to investigate the extension of lactodynamographic analysis up to 60 min in goat milk, to measure the farm and individual factors, and to investigate differences among 6 goat breeds. Daily milk yield (dMY) was recorded and milk samples collected from 1,272 goats reared in 35 farms. Goats were of 6 different breeds: Saanen and Camosciata delle Alpi for the Alpine type, and Murciano-Granadina, Maltese, Sarda, and Sarda Primitiva for the Mediterranean type. Milk composition (fat, protein, lactose, pH; somatic cell score; logarithmic bacterial count) and MCP [rennet coagulation time (RCT, min), curd-firming time (k 20 , min), curd firmness at 30, 45, and 60 min after rennet addition (a 30 , a 45 , and a 60 , mm)] were recorded, and daily fat and protein yield (dFPY g/d) was calculated as the sum of fat and protein concentration multiplied by the dMY. Data were analyzed using different statistical models to measure the effects of farm, parity , stage of lactation and breed; lastly, the direct and the indirect effect of breed were quantified by comparing the variance of breed from models with or without the inclusion of linear regression of fat, protein, lactose, pH, bacterial, somatic cell counts, and dMY. Orthogonal contrasts were performed to compare least squares means. Almost all traits exhibited high variability, with coefficients of variation between 32 (for RCT) and 63% (for a 30 ). The proportion of variance regarding dMY, dFPY, and milk composition due to the farm was moderate, whereas for MCP it was low, except for a 60 , at 69%. Parity affected both yield and quality traits of milk, with least squares means of dMY and dFPY showing an increase and RCT and curd firmness traits a decrease from the first to the last parity class. All milk quality traits, excluding fat, were affected by the stage of lactation; RCT and k 20 decreased rapidly and a 30 was higher from the first to the last part of lactation. Alpine breeds showed the highest dMY and dFPY but Mediterranean the best percentage of protein, fat, and lactose and a shorter k 20 and a greater a 30 . Among the Mediterranean goats, Murciano-Granadina goats had the highest milk yield, fat, and protein contents, whereas Maltese, Sarda, and Sarda Primitiva were characterized by much more favorable technological properties in terms of k 20 , a 30 , and a 45 . In conclusion, as both the farm and individual factors highly influenced milk composition and MCP traits, improvements of these traits should be based both on modifying management and individual goat factors. As expected, several differences were attributable to the breed effect, with the best milk production for the Alpines and milk quality and coagulation for the Mediterranean goats., (Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Traditional milk coagulation properties are used to predict the suitability of milk for cheese-making. In bovine and ovine species, the introduction of the concept of curd firming over time, continuously recorded by a lactodynamograph during prolonged tests, provides additional information about milk coagulation, curd-firming, and syneresis processes. The aims of present study were (1) to test the adaptability of a 4-parameter curd-firming model in the assessment of goat milk (also comparing published data of other species); (2) to describe variability of coagulation, curd firming, and syneresis processes among individual goat milk samples; (3) to quantify the effects of farm and animal factors (breed, parity, and stage of lactation); and (4) to compare 6 goat breeds for their model parameters. Milk samples from 1,272 goats reared in 35 farms were collected. Goats were of 6 breeds: Saanen and Camosciata delle Alpi for the Alpine type; and Murciano-Granadina, Maltese, Sarda, and Sarda Primitiva for the Mediterranean type. During a lactodynamographic analysis (60 min), 240 measures of curd firmness (mm) were recorded for each milk sample. The modeling of curd firming allowed us to achieve the rennet coagulation time estimated on the basis of all the data points (min); the curd firming and the curd syneresis instant rate constants; the asymptotical potential value of curd firming; the actual maximum curd firmness; and the time at which the curd firming maximum level is attained. Modeling parameter data were analyzed using a linear mixed model. Comparison with other dairy species showed several differences: goat milk coagulated later than sheep but earlier than bovine, and curd firming and curd syneresis instant rate constants were greater in small ruminants. Modeling parameters of goat milk were mostly affected by the farm effect (37% of the total variance, on average) compared with the results found for bovine and ovine samples, and this was probably attributable to the marked differences among goat farming systems. Small differences were demonstrated between Alpine and Mediterranean breeds, but the time of maximum curd firmness was lower in Murciano-Granadina compared with Maltese, Sarda, and Sarda Primitiva. Sarda and Sarda Primitiva were very similar and exhibited the most favorable coagulation properties of milk. For almost all the model parameters, the direct effect of breed was increased after correction for milk yield and composition. In conclusion, this approach allowed us to fully depict the effects of the different factors on coagulation of goat milk, and clarified the different renneting pattern among goat breeds, and with other species. Results could be used for the valorization of goat dairy products, also when these are linked to particular local breeds, and to stimulate further studies about relationships between coagulation and cheese-making traits., (Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Little is known about cheese-making efficiency at the individual cow level, so our objective was to study the effects of herd productivity, individual herd within productivity class and breed of cow within herd by producing, then analyzing, 508 model cheeses from the milk of 508 cows of six different breeds reared in 41 multi-breed herds classified into two productivity classes (high v. low). For each cow we obtained six milk composition traits; four milk nutrient (fat, protein, solids and energy) recovery traits (REC) in curd; three actual % cheese yield traits (%CY); two theoretical %CYs (fresh cheese and cheese solids) calculated from milk composition; two overall cheese-making efficiencies (% ratio of actual to theoretical %CYs); daily milk yield (dMY); and three actual daily cheese yield traits (dCY). The aforementioned phenotypes were analyzed using a mixed model which included the fixed effects of herd productivity, parity, days in milk (DIM) and breed; the random effects were the water bath, vat, herd and residual. Cows reared in high-productivity herds yielded more milk with higher nutrient contents and more cheese per day, had greater theoretical %CY, and lower cheese-making efficiency than low-productivity herds, but there were no differences between them in terms of REC traits. Individual herd within productivity class was an intermediate source of total variation in REC, %CY and efficiency traits (10.0% to 17.2%), and a major source of variation in milk yield and dCY traits (43.1% to 46.3%). Parity of cows was an important source of variation for productivity traits, whereas DIM affected almost all traits. Breed within herd greatly affected all traits. Holsteins produced more milk, but Brown Swiss cows produced milk with higher actual and theoretical %CYs and cheese-making efficiency, so that the two large-framed breeds had the same dCY. Compared with the two large-framed breeds, the small Jersey cows produced much less milk, but with greater actual and theoretical %CYs, similar efficiencies and a slightly lower dCY. Compared with the average of the specialized dairy breeds, the three dual-purpose breeds (Simmental and the local Rendena and Alpine Grey) had, on average, similar dMY, lower actual and theoretical %CY, similar fat and protein REC, and slightly greater cheese-making efficiency.

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 (k 20 , min), and CF at 30, 45, and 60 min from rennet addition (a 30 , a 45 , and a 60 , 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., (Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Buffalo milk is the world's second most widely produced milk, and increasing attention is being paid to its composition, particularly the fatty acid profile. The objectives of the present study were (1) to characterize the fatty acid composition of Mediterranean buffalo milk, and (2) to investigate potential sources of variation in the buffalo milk fatty acid profile. We determined the profile of 69 fatty acid traits in 272 individual samples of Mediterranean buffalo milk using gas chromatography. In total, 51 individual fatty acids were identified: 24 saturated fatty acids, 13 monounsaturated fatty acids, and 14 polyunsaturated fatty acids. The major individual fatty acids in buffalo milk were in the order 16:0, 18:1 cis-9, 14:0, and 18:0. Saturated fatty acids were the predominant fraction in buffalo milk fat (70.49%); monounsaturated and polyunsaturated fatty acids were at 25.95 and 3.54%, respectively. Adopting a classification based on carbon-chain length, we found that medium-chain fatty acids (11-16 carbons) represented the greater part (53.7%) of the fatty acid fraction of buffalo milk, whereas long-chain fatty acids (17-24 carbons) and short-chain fatty acids (4-10 carbons) accounted for 32.73 and 9.72%, respectively. The n-3 and n-6 fatty acids were 0.46 and 1.77%, respectively. The main conjugated linoleic acid, rumenic acid, represented 0.45% of total milk fatty acids. Herd/test date and stage of lactation were confirmed as important sources of variation in the fatty acid profile of buffalo milk. The percentages of short-chain and medium-chain fatty acids in buffalo milk increased in early lactation (+0.6 and +3.5%, respectively), whereas long-chain fatty acids decreased (-4.2%). The only exception to this pattern was butyric acid, which linearly decreased from the beginning of lactation, confirmation that its synthesis is independent of malonyl-CoA. These results seem to suggest that in early lactation the mobilization of energy reserves may have less influence on the fatty acid profile of buffalo milk than that of cow milk, probably due to a shorter and less severe period of negative energy balance. Parity affected the profiles of a few traits and had the most significant effects on branched-chain fatty acids. This work provided a detailed overview of the fatty acid profile in buffalo milk including also those fatty acids present in small concentrations, which may have beneficial effects for human health. Our results contributed also to increase the knowledge about the effects of some of the major factors affecting buffalo production traits and fatty acid concentrations in milk, and consequently its technological and nutritional properties., (Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Milk coagulation properties (MCP) have been widely investigated in the past using milk collected from different cattle breeds and herds. However, to our knowledge, no previous studies have assessed MCP in individual milk samples from several multi-breed herds characterized by either high or low milk productivity, thereby allowing the effects of herd and cow breed to be evaluated independently. Multi-breed herds (n=41) were classified into 2 categories based on milk productivity (high vs. low), defined according to the average milk net energy yielded daily by lactating cows. Milk samples were taken from 1,508 cows of 6 different breeds: 3 specialized dairy (Holstein-Friesian, Brown Swiss, Jersey) and 3 dual-purpose (Simmental, Rendena, Alpine Grey) breeds, and analyzed in duplicate (3,016 tests) using 2 lactodynamographs to obtain 240 curd firming (CF) measurements over 60min (1 every 15 s) for each duplicate. The 5 traditional single-point MCP (RCT, k 20 , a 30 , a 45 , and a 60 ) were yielded directly by the instrument from the available CF measures. All 240 CF measures of each replicate were also used to estimate 4 individual equation parameters: RCT estimated according to curd firm change over time modeling (RCT eq ), asymptotic potential curd firmness (CF P ), curd firming instant rate constant (k CF ), and syneresis instant rate constant (k SR ) and 2 derived traits: maximum curd firmness achieved within 45min (CF max ) and time at achievement of CF max (t max ) by curvilinear regression using a nonlinear procedure. Results showed that the effect of herd-date on traditional and modeled MCP was modest, ranging from 6.1% of total variance for k 20 to 10.7% for RCT, whereas individual animal variance was the highest, ranging from 32.0% for t max to 82.5% for RCT eq . The repeatability of MCP was high (>80%) for all traits except those associated with the last part of the lactodynamographic curve (i.e., a 60 , k SR , k CF , and t max : 57 to 71%). Reproducibility, taking into account the effect of instrument, was equal to or slightly lower than repeatability. Milk samples collected in farms characterized by high productivity exhibited delayed coagulation (RCT eq : 18.6 vs. 16.3min) but greater potential curd firmness (CF P : 76.8 vs. 71.9mm) compared with milk samples collected from low-productivity herds. Parity and days in milk influenced almost all MCP. Large differences in all MCP traits were observed among breeds, both between specialized and dual-purpose breeds and within these 2 groups of breeds, even after adjusting for milk quality and yield. Milk quality and MCP of samples from Jersey cows, and coagulation time of samples from Rendena cows were better than in milk from Holstein-Friesian cows, and intermediate results were found with the other breeds of Alpine origin. The results of this study, taking into account the intrinsic limitation of this technique, show that the effects of breed on traditional and modeled MCP are much greater than the effects of herd productivity class, parity, and DIM. Moreover, the variance in individual animals is much greater than the variance in individual herds within herd productivity class. It seems that improvement in MCP depends more on genetics (e.g., breed, selection) than on environmental and management factors., (Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Summer transhumance of dairy cows to high Alpine pastures is still practiced in many mountainous areas. It is important for many permanent dairy farms because the use of highland pastures increases milk production and high-priced typical local dairy products often boost farm income. As traditional cheese- and ricotta-making procedures in Alpine pastures are central to this dairy system, the objective of this study was to characterize the quality and efficiency of products and their relationships with the quality and availability of grass during the grazing season. The milk from 148 cows from 12 permanent farms reared on a temporary farm located in Alpine pastures was processed every 2wk during the summer (7 cheesemakings from late June to early September). During each processing, 11 dairy products (4 types of milk, 2 by-products, 3 fresh products, and 2 ripened cheeses) were sampled and analyzed. In addition, 8 samples of fresh forage from the pasture used by the cows were collected and analyzed. At the beginning of the pasture season the cows were at 233±90d in milk, 2.4±1.7 parities, and produced 23.6±5.7kg/d of milk. The milk yield decreased with the move from permanent to temporary farms and during the entire summer transhumance, but partly recovered after the cows returned to the permanent farms. Similar trends were observed for the daily yields of fat, protein, casein, lactose, and energy, as we found no large variations in the quality of the milk, with the exception of the first period of Alpine pasture. The somatic cell counts of milk increased during transhumance, but this resulted from a concentration of cells in a lower quantity of milk rather than an increase in the total number of cells ejected daily from the udder. We noted a quadratic trend in availability of forage (fresh and dry matter weight per hectare), with a maximum in late July. The quality of forage also varied during the summer with a worsening of chemical composition. The evening milk (before and after natural creaming), the whole morning milk, and the mixed vat milk had different chemical compositions, traditional coagulation properties, and curd-firming modeling parameters. These variations over the pasture season were similar to the residual variations with respect to chemical composition, and much lower with respect to coagulation and curd-firming traits. Much larger variations were noted in cream, cheese, and ricotta yields, as well as in nutrient recoveries in curd during the pasture season. The protein content of forage was correlated with some of the coagulation and curd-firming traits, the ether extract of forage was positively correlated with milk fat content and cheese yields, and fiber fractions of forage were unfavorably correlated with some of the chemical and technological traits. Traditional cheese- and ricotta-making procedures showed average cream, cheese, and ricotta yields of 6.3, 14.2, and 4.9%, respectively, and an overall recovery of almost 100% of milk fat, 88% of milk protein, and 60% of total milk solids., (Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The aims of this study were (1) to assess variability in the major mineral components of buffalo milk, (2) to estimate the effect of certain environmental sources of variation on the major minerals during lactation, and (3) to investigate the possibility of using Fourier-transform infrared (FTIR) spectroscopy as an indirect, noninvasive tool for routine prediction of the mineral content of buffalo milk. A total of 173 buffaloes reared in 5 herds were sampled once during the morning milking. Milk samples were analyzed for Ca, P, K, and Mg contents within 3h of sample collection using inductively coupled plasma optical emission spectrometry. A Milkoscan FT2 (Foss, Hillerød, Denmark) was used to acquire milk spectra over the spectral range from 5,000 to 900 wavenumber/cm. Prediction models were built using a partial least square approach, and cross-validation was used to assess the prediction accuracy of FTIR. Prediction models were validated using a 4-fold random cross-validation, thus dividing the calibration-test set in 4 folds, using one of them to check the results (prediction models) and the remaining 3 to develop the calibration models. Buffalo milk minerals averaged 162, 117, 86, and 14.4mg/dL of milk for Ca, P, K, and Mg, respectively. Herd and days in milk were the most important sources of variation in the traits investigated. Parity slightly affected only Ca content. Coefficients of determination of cross-validation between the FTIR-predicted and the measured values were 0.71, 0.70, and 0.72 for Ca, Mg, and P, respectively, whereas prediction accuracy was lower for K (0.55). Our findings reveal FTIR to be an unsuitable tool when milk mineral content needs to be predicted with high accuracy. Predictions may play a role as indicator traits in selective breeding (if the additive genetic correlation between FTIR predictions and measures of milk minerals is high enough) or in monitoring the milk of buffalo populations for dairy industry purposes., (Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The aim of this study was to propose and test a new laboratory cheesemaking procedure [9-mL milk cheesemaking assessment (9-MilCA)], which records 15 traits related to milk coagulation, curd firming, syneresis, cheese yield, and curd nutrients recovery or whey loss. This procedure involves instruments found in many laboratories (i.e., heaters and lacto-dynamographs), with an easy modification of the sample rack for the insertion of 10-mL glass tubes. Four trials were carried out to test the 9-MilCA procedure. The first trial compared 8 coagulation and curd firming traits obtained using regular or modified sample racks to process milk samples from 60 cows belonging to 5 breeds and 3 farms (480 tests). The obtained patterns exhibited significant but irrelevant between-procedure differences, with better repeatability seen for 9-MilCA. The second trial tested the reproducibility and repeatability of the 7 cheesemaking traits obtained using the 9-MilCA procedure on individual samples from 60 cows tested in duplicate in 2 instruments (232 tests). The method yielded very repeatable outcomes for all 7 tested cheese yield and nutrient recovery traits (repeatability >98%), with the exception of the fresh cheese yield (84%), which was affected by the lower repeatability (67%) of the water retained in the curd. In the third trial (96 tests), we found that using centrifugation in place of curd cooking and draining (as adopted in several published studies) reduced the efficiency of whey separation, overestimated all traits, and worsened the repeatability. The fourth trial compared 9-MilCA with a more complex model cheese-manufacturing process that mimics industry practices, using 1,500-mL milk samples (72 cows, 216 tests). The average results obtained from 9-MilCA were similar to those obtained from the model cheeses, with between-method correlations ranging from 78 to 99%, except for the water retained in the curd (r=54%). Our results indicate that new 9-MilCA method is a powerful research tool that allows the rapid, inexpensive, and partly automated analysis processing 40 samples per day with 2 replicates each, using 1 lacto-dynamograph, 2 heaters, and 3 modified sample racks, and yields a complete picture of the cheesemaking process (e.g., milk gelation, curd firming, syneresis, and whey expulsion) as well as the cheese yield and the efficiency of energy or nutrients retention in the cheese or loss in the whey., (Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Milk coagulation properties are used to evaluate the cheesemaking aptitude of milk samples. No international standard procedure exists, although laboratories often mimic the production of a full-fat fresh cheese for milk coagulation properties. Questions have arisen about the predictability of such a procedure for different types of cheese production. The aim of this study was to establish a procedure mimicking the production conditions of a long-ripened hard cheese, taking Protected Designation of Origin Grana Padano as a case study. With respect to the traditional conditions (standard procedure; SP), the Grana Padano procedure (GP) modifications were the use of standardized milk, coagulation lower temperature, previous milk acidification, lysozyme addition, and rennet type. Each modification was tested in turn versus the SP and also all together in the GP. Another 3 tests were carried out: SP on naturally creamed milk, SP with double the quantity of rennet, and a simplified GP on a full-fat milk sample. The 10 procedures were tested on 2 subsamples with 2 replicates each and were repeated using individual milk samples from 15 dual-purpose Simmental cows in 4 sessions for a total of 600 tests. Two Formagraph instruments (Foss Electric A/S, Hillerød, Denmark) measuring curd firmness every 15 s were used, prolonging test duration to 60min to obtain 5 traditional single-point milk coagulation properties and 3 parameters of the curd firming model using all 240 points recorded for each replicate. The 8 traits of each replicate were analyzed according to a mixed model with fixed effects of 4 sessions, 10 treatments, 2 instruments, and 16microvats, and random effects of 15 animals and 300 subsamples. Compared with the SP, the coagulation and curd firming was slowed by low temperature and was accelerated by acidification and by adding a double amount of rennet; natural creaming, fat standardization, and rennet with 5% pepsin affected only some traits, whereas lysozyme addition affected none. Combination of all modifications tended to compensate for each of their effects, resulting in similar average patterns between GP and SP. Modifications to repeatability were found for all traits with the exception of 2. The ability of the SP to predict GP, tested through correlations between procedures, was not very high. Whereas SP is used for both research and in the dairy industry, better results for Grana Padano cheesemaking can only be achieved by adopting specific, more complex, and labor-intensive procedures at the research level or, possibly, by specific calibrations through Fourier-transform infrared spectroscopy at the industry level., (Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)