Publications by authors named "Claudio Cipolat-Gotet"

26 Publications

  • Page 1 of 1

Predictive formulas for different measures of cheese yield using milk composition from individual goat samples.

J Dairy Sci 2022 May 12. Epub 2022 May 12.

Department of Veterinary Science, University of Parma, 43126 Parma, Italy.

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), total solids (%CY), and water retained (%CY) 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 (R) and the root mean square error of validation (RMSE). In CrV, the formula with the best prediction accuracy for all %CY traits included fat, casein, and UHI (R = 0.65, 0.96, and 0.23 for %CY, %CY, and %CY, respectively). The WAV procedure showed R 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 and %CY 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2022-21848DOI Listing
May 2022

Genomic inbreeding coefficients using imputed genotypes: Assessing different estimators in Holstein-Friesian dairy cows.

J Dairy Sci 2022 May 6. Epub 2022 May 6.

Department of Veterinary Science, University of Parma, 43126 Parma, Italy.

The objective of this study was to estimate inbreeding coefficients in Holstein dairy cattle using imputed SNPs data. A data set of 95,540 Italian Holstein dairy cows from the routine genomic evaluations of the Italian National Association of Holstein, Brown, and Jersey Breeders were analyzed, with 84,445 imputed SNP. Ten widely used genomic inbreeding estimators were tested, including 4 PLINK v1.9 estimators (F, F, F, F), 3 genomic relationship matrix (GRM)-based methods [VanRaden's first method with observed allele frequencies (F) or with fixed frequencies at 0.5 (F), VanRaden's third method, allelic frequency free and pedigree regressed (F)], runs of homozygosity (ROH)-based estimators in a complete (F) and simplified version (F), and proportion of homozygous SNP (F). Pairwise comparisons among them were made, including the comparison with traditional pedigree-based inbreeding coefficients (F). Our results showed variability among the genomic inbreeding estimators. Coefficients of F and F were >1, meaning that more variability has been lost than the variability that existed in the base population. Regarding the remaining ones, F, F, F, and F provided coefficients within the [0,1] space and are considered comparable to F. Not comparable to F, yet with an interpretable value, can be considered the coefficients of F, F, and F. Estimators based on ROH had the highest correlation with pedigree-based coefficients (0.59-0.66), among all estimators tested. In this study, Spearman correlations were shown to possibly provide a clearer estimation of the strength of the relationship between estimators. We hypothesize that imputation might cause extreme genomic inbreeding values that deserves further investigation.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2021-21125DOI Listing
May 2022

Genetic Diversity in the Italian Holstein Dairy Cattle Based on Pedigree and SNP Data Prior and After Genomic Selection.

Front Vet Sci 2021 13;8:773985. Epub 2022 Jan 13.

Dipartimento di Scienze Medico-Veterinarie, University of Parma, Parma, Italy.

Genetic diversity has become an urgent matter not only in small local breeds but also in more specialized ones. While the use of genomic data in livestock breeding programs increased genetic gain, there is increasing evidence that this benefit may be counterbalanced by the potential loss of genetic variability. Thus, in this study, we aimed to investigate the genetic diversity in the Italian Holstein dairy cattle using pedigree and genomic data from cows born between 2002 and 2020. We estimated variation in inbreeding, effective population size, and generation interval and compared those aspects prior to and after the introduction of genomic selection in the breed. The dataset contained 84,443 single-nucleotide polymorphisms (SNPs), and 74,485 cows were analyzed. Pedigree depth based on complete generation equivalent was equal to 10.67. A run of homozygosity (ROH) analysis was adopted to estimate SNP-based inbreeding (F). The average pedigree inbreeding was 0.07, while the average F was more than double, being equal to 0.17. The pattern of the effective population size based on pedigree and SNP data was similar although different in scale, with a constant decrease within the last five generations. The overall inbreeding rate (ΔF) per year was equal to +0.27% and +0.44% for F and F throughout the studied period, which corresponded to about +1.35% and +2.2% per generation, respectively. A significant increase in the ΔF was found since the introduction of genomic selection in the breed. This study in the Italian Holstein dairy cattle showed the importance of controlling the loss of genetic diversity to ensure the long-term sustainability of this breed, as well as to guarantee future market demands.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fvets.2021.773985DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8792952PMC
January 2022

Genome-wide scan reveals genetic divergence in Italian Holstein cows bred within PDO cheese production chains.

Sci Rep 2021 06 15;11(1):12601. Epub 2021 Jun 15.

Dipartimento di Scienze Medico-Veterinarie, University of Parma, Via del Taglio 10, 43126, Parma, Italy.

Dairy cattle breeds have been exposed to intense artificial selection for milk production traits over the last fifty years. In Italy, where over 80% of milk is processed into cheese, selection has also focused on cheese-making traits. Due to a deep-rooted tradition in cheese-making, currently fifty Italian cheeses are marked with the Protected Designation of Origin (PDO) label as they proved traditional land of origin and procedures for milk transformation. This study aimed to explore from a genetic point of view if the presence of such diverse productive contexts in Italy have shaped in a different manner the genome of animals originally belonging to a same breed. We analyzed high density genotype data from 1000 Italian Holstein cows born between 2014 and 2018. Those animals were either farmed in one of four Italian PDO consortia or used for drinkable milk production only. Runs of Homozygosity, Bayesian Information Criterion and Discriminant Analysis of Principal Components were used to evaluate potential signs of genetic divergence within the breed. We showed that the analyzed Italian Holstein cows have genomic inbreeding level above 5% in all subgroups, reflecting the presence of ongoing artificial selection in the breed. Our study provided a comprehensive representation of the genetic structure of the Italian Holstein breed, highlighting the presence of potential genetic subgroups due to divergent dairy farming systems. This study can be used to further investigate genetic variants underlying adaptation traits in these subgroups, which in turn might be used to design more specialized breeding programs.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41598-021-92168-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8206360PMC
June 2021

The mineral profile affects the coagulation pattern and cheese-making efficiency of bovine milk.

J Dairy Sci 2021 Aug 28;104(8):8439-8453. Epub 2021 May 28.

Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, 35020 Legnaro (PD), Italy.

Natural variations in milk minerals, their relationships, and their associations with the coagulation process and cheese-making traits present an opportunity for the differentiation of milk destined for high-quality natural products, such as traditional specialties or Protected Designation of Origin (PDO) cheeses. The aim of this study was to quantify the effects of the native contents of Ca, P, Na, K, and Mg on 18 traits describing traditional milk coagulation properties (MCP), curd firming over time (CF) equation parameters, cheese yield (CY) measures, and nutrient recoveries in the curd (REC) using models that either included or omitted the simultaneous effects of milk fat and casein contents. The results showed that, by including milk fat and casein and the minerals in the statistical model, we were able to determine the specific effects of each mineral on coagulation and cheese-making efficiency. In general, about two-thirds of the apparent effects of the minerals on MCP and the CF equation parameters are actually mediated by their association with milk composition, especially casein content, whereas only one-third of the effects are direct and independent of milk composition. In the case of cheese-making traits, the effects of the minerals were mediated only negligibly by their association with milk composition. High Ca content had a positive effect on the coagulation pattern and cheese-making traits, favoring water retention in the curd in particular. Phosphorus positively affected the cheese-making traits in that it was associated with an increase in CY in terms of curd solids, and in all the nutrient recovery traits. However, a very high P content in milk was associated with lower fat recovery in the curd. The variation in the Na content in milk only mildly affected coagulation, whereas with regard to cheese-making, protein recovery was negatively associated with high concentrations of this mineral. Potassium seemed not to be actively involved in coagulation and the cheese-making process. Magnesium content tended to slow coagulation and reduce CY measures. Further studies on the relationships of minerals with casein and protein fractions could deepen our knowledge of the role of all minerals in coagulation and the cheese-making process.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2021-20233DOI Listing
August 2021

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

J Dairy Sci 2021 Apr 19;104(4):3956-3969. Epub 2021 Feb 19.

Department of Veterinary Science, University of Parma, 43126 Parma, Italy.

The prediction of traditional goat milk coagulation properties (MCP) and curd firmness over time (CF) 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 parameters. In total, 611 individual goat milk samples were used. Analysis of variance of measured MCP and CF 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. 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), the root mean square error of validation (RMSE), 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 values obtained with the CRV procedure were moderate to high for the majority of coagulation traits, with RMSE 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2020-19491DOI Listing
April 2021

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

J Dairy Sci 2021 Apr 13;104(4):3927-3935. Epub 2021 Feb 13.

Department of Veterinary Medicine, University of Sassari, 07100 Sassari, Italy.

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), 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). To assess model performance, coefficient of determination (R) and the root mean squared error of validation were recorded. The R varied between 0.14 and 0.45 (instant curd-firming rate constant and RCT, 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, the maximum R increased at about 15% across traits, with the highest observed for time to curd firmness of 20 mm (20%) and the lowest for RCT (6%). Further investigation evidenced important variability among farms, with R 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2020-19587DOI Listing
April 2021

Genetic Parameters of Different FTIR-Enabled Phenotyping Tools Derived from Milk Fatty Acid Profile for Reducing Enteric Methane Emissions in Dairy Cattle.

Animals (Basel) 2020 Sep 15;10(9). Epub 2020 Sep 15.

Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 1, 35020 Legnaro, Italy.

This study aimed to infer the genetic parameters of five enteric methane emissions (EME) predicted from milk infrared spectra (13 models). The reference values were estimated from milk fatty acid profiles (chromatography), individual model-cheese, and daily milk yield of 1158 Brown Swiss cows (85 farms). Genetic parameters were estimated, under a Bayesian framework, for EME reference traits and their infrared predictions. Heritability of predicted EME traits were similar to EME reference values for methane yield (CH/DM: 0.232-0.317) and methane intensity per kg of corrected milk (CH/CM: 0.177-0.279), smaller per kg cheese solids (CH/SO: 0.093-0.165), but greater per kg fresh cheese (CH/CU: 0.203-0.267) and for methane production (dCH: 0.195-0.232). We found good additive genetic correlations between infrared-predicted methane intensities and the reference values (0.73 to 0.93), less favorable values for CH/DM (0.45-0.60), and very variable for dCH according to the prediction method (0.22 to 0.98). Easy-to-measure milk infrared-predicted EME traits, particularly CH/CM, CH/CU and dCH, could be considered in breeding programs aimed at the improvement of milk ecological footprint.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/ani10091654DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7552146PMC
September 2020

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

J Dairy Sci 2020 Sep 16;103(9):7951-7956. Epub 2020 Jul 16.

Department of Agronomy, Food, Natural Resources, Animals and the Environment, University of Padova, Viale dell'Università 16, Legnaro (PD), Italy 35020. Electronic address:

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2019-17847DOI Listing
September 2020

Modeling weight loss of cheese during ripening and the influence of dairy system, parity, stage of lactation, and composition of processed milk.

J Dairy Sci 2020 Aug 29;103(8):6843-6857. Epub 2020 May 29.

Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE), University of Padova, 35020 Legnaro (PD), Italy.

The yield, flavor, and texture of ripened cheese result from numerous interrelated microbiological, biochemical, and physical reactions that take place during ripening. The aims of the present study were to propose a 2-compartment first-order kinetic model of cheese weight loss over the ripening period; to test the variation in new informative phenotypes describing this process; and to assess the effects on these traits of dairy farming system, individual farms within dairy system, animal factors, and milk composition. A total of 1,211 model cheeses were produced in the laboratory using individual 1.5-L milk samples from Brown Swiss cows reared on 83 farms located in Trento Province. During ripening (60 d; temperature 15°C, relative humidity 85%), the weight of all model cheeses was measured, and cheese yield (cheese weight/processed milk weight, %CY) was calculated at 7 intervals from cheese-making (0, 1, 7, 14, 28, 42, and 60 d). Using these measures, a 2-compartment first-order kinetic model (3-parameter equation) was developed for modeling %CY during the ripening period, as follows: [Formula: see text] , where %CY is the %CY at ripening time t; %CY and %CY are the modeled %CY traits at time 0 d (%CY = initial %CY) and at the end of a ripening period sufficient to reach a constant wheel weight (%CY = final %CY after 60 d ripening in the case of small model cheeses); k is the instant rate constant for cheese weight loss (%/d). Cheese weight and protein and fat losses were calculated as the % difference between the model cheeses at 0 and after 60 d of ripening. The variation in cheese pH was calculated as the % difference between pH at 0 and after 60 d. Dairy system, individual herd within dairy system, and the cow's parity and lactation stage (tested with a linear mixed model) strongly affected almost all the traits collected during model cheese ripening. Milk fat, protein, lactose, pH, and somatic cell score also greatly affected almost all the traits, although k was affected only by milk protein. After including milk composition in the linear mixed model, the importance of all the herd and animal sources of variation was greatly reduced for all traits. The proposed model and novel traits could be tested, first, with the aim of establishing new monitoring procedures enabling the dairy industry to improve milk quality-based payment systems at the herd level and, second, with a view to exploring possible genetic improvements to dairy cow populations.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2019-17829DOI Listing
August 2020

Characterization of milk composition, coagulation properties, and cheese-making ability of goats reared in extensive farms.

J Dairy Sci 2020 Jul 14;103(7):5830-5843. Epub 2020 May 14.

Department of Veterinary Medicine, University of Sassari, 07100 Sassari, Italy.

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), 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, 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2019-17805DOI Listing
July 2020

Differential Somatic Cell Count as a Novel Indicator of Milk Quality in Dairy Cows.

Animals (Basel) 2020 Apr 26;10(5). Epub 2020 Apr 26.

Department of Biomedical, Surgical and Dental Sciences, University of Milano, Via Celoria 10, 20133 Milano, Italy.

Recent available instruments allow to record the number of differential somatic cell count (DSCC), representing the combined proportion of polymorphonuclear leukocytes and lymphocytes, on a large number of milk samples. Milk DSCC provides indirect information on the udder health status of dairy cows. However, literature is limited regarding the effect of DSCC on milk composition at the individual cow level, as well as its relation to the somatic cell score (SCS). Hence, the aims of this study were to (i) investigate the effect of different levels of DSCC on milk composition (fat, protein, casein, casein index, and lactose) and (ii) explore the combined effect of DSCC and SCS on these traits. Statistical models included the fixed effects of days in milk, parity, SCS, DSCC and the interaction between SCS × DSCC, and the random effects of herd, animal within parity, and repeated measurements within cow. Results evidenced a decrease of milk fat and an increase in milk fatty acids at increasing DSCC levels, while protein, casein and their proportion showed their lowest values at the highest DSCC. A positive association was found between DSCC and lactose. The interaction between SCS and DSCC was important for lactose and casein index, as they varied differently upon high and low SCS and according to DSCC levels.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/ani10050753DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7277798PMC
April 2020

Chemometric authentication of farming systems of origin of food (milk and ripened cheese) using infrared spectra, fatty acid profiles, flavor fingerprints, and sensory descriptions.

Food Chem 2020 Feb 6;305:125480. Epub 2019 Sep 6.

Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Padova, Italy.

Milk samples from 1264 cows in 85 farms were authenticated for different farming-systems using a 10-fold cross-validated linear-discriminant-analysis using Fourier-transform infrared spectra (FTIRS) and gas-chromatographic fatty-acid (FA) profiles. FTIRS gave correct classification greater than FAs (97.4% vs. 81.1%) during calibration, but slightly worse in validation (73.5% vs 77.3%) and their combination improved the results. All milk samples were processed into ripened model-cheeses, and analyzed by near-infrared-spectrometry (NIRS), by proton-transfer-reaction time-of-flight mass-spectrometry for their volatile organic compound (VOCs) fingerprint and by panel sensory profiling (SENS). Farming-system authentication on cheese samples was less efficient than on milk, but still possible. The instrumental methods yielded similar validation results, better than SENS, and their combination improved the correct classification rate. The efficiency of the different technics was affected by specific farming systems. In conclusion, dairy products could be discriminated for farming-systems with acceptable accuracy, but the methods tested differ in sampling procedure, rapidity and costs.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.foodchem.2019.125480DOI Listing
February 2020

Accuracy and biases in predicting the chemical and physical traits of many types of cheeses using different visible and near-infrared spectroscopic techniques and spectrum intervals.

J Dairy Sci 2019 Nov 30;102(11):9622-9638. Epub 2019 Aug 30.

Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy.

Near-infrared spectroscopy (NIRS) has been widely used to determine various composition traits of many dairy products in the industry. In the last few years, near-infrared (NIR) instruments have become more and more accessible, and now, portable devices can be easily used in the field, allowing the direct measurement of important quality traits. However, the comparison of the predictive performances of different NIR instruments is not simple, and the literature is lacking. These instruments may use different wavelength intervals and calibration procedures, making it difficult to establish whether differences are due to the spectral interval, the chemometric approach, or the instrument's technology. Hence, the aims of this study were (1) to evaluate the prediction accuracy of chemical contents (5 traits), pH, texture (2 traits), and color (5 traits) of 37 categories of cheese; (2) to compare 3 instruments [2 benchtop, working in reflectance (R) and transmittance (T) mode (NIRS-R and NIRS-T, respectively) and 1 portable device (VisNIRS-R)], using their entire spectral ranges (1100-2498, 850-1048, and 350-1830 nm, respectively, for NIRS-R, NIRS-T and VisNIRS-R); (3) to examine different wavelength intervals of the spectrum within instrument, comparing also the common intervals among the 3 instruments; and (4) to determine the presence of bias in predicted traits for specific cheese categories. A Bayesian approach was used to develop 8 calibration models for each of 13 traits. This study confirmed that NIR spectroscopy can be used to predict the chemical composition of a large number of different cheeses, whereas pH and texture traits were poorly predicted. Color showed variable predictability, according to the trait considered, the instrument used, and, within instrument, according to the wavelength intervals. The predictive performance of the VisNIRS-R portable device was generally better than the 2 laboratory NIRS instruments, whether with the entire spectrum or selected intervals. The VisNIRS-R was found suitable for analyzing chemical composition in real time, without the need for sample uptake and processing. Our results also indicated that instrument technology is much more important than the NIR spectral range for accurate prediction equations, but the visible range is useful when predicting color traits, other than lightness. Specifically for certain categories (i.e., caprine, moldy, and fresh cheeses), dedicated calibrations seem to be needed to obtain unbiased and more accurate results.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2019-16770DOI Listing
November 2019

Effect of Season and Factory on Cheese-Making Efficiency in Parmigiano Reggiano Manufacture.

Foods 2019 Aug 3;8(8). Epub 2019 Aug 3.

Department of Veterinary Science, University of Parma, Via del Taglio 10, I-43126 Parma, Italy.

The assessment of the efficiency of the cheese-making process (ECMP) is crucial for the profitability of cheese-factories. A simple way to estimate the ECMP is the measure of the estimated cheese-making losses (ECL), expressed by the ratio between the concentration of each constituent in the residual whey and in the processed milk. The aim of this research was to evaluate the influence of the season and cheese factory on the efficiency of the cheese-making process in Parmigiano Reggiano cheese manufacture. The study followed the production of 288 Parmigiano Reggiano cheese on 12 batches in three commercial cheese factories. For each batch, samples of the processed milk and whey were collected. Protein, casein, and fat ECL resulted in an average of 27.01%, 0.72%, and 16.93%, respectively. Both milk crude protein and casein contents were negatively correlated with protein ECL, r = -0.141 ( ≤ 0.05), and r = -0.223 ( ≤ 0.001), respectively. The same parameters resulted in a negative correlation with casein ECL ( ≤ 0.001) (r = -0.227 and -0.212, respectively). Moreover, fat ECL was correlated with worse milk coagulation properties and negatively correlated with casein content (r = -0.120; ≤ 0.05). In conclusion, ECLs depend on both milk characteristics and season.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/foods8080315DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6722500PMC
August 2019

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

J Dairy Sci 2019 Oct 24;102(10):8648-8657. Epub 2019 Jul 24.

Department of Veterinary Medicine, University of Sassari, 07100 Sassari, Italy.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2019-16369DOI Listing
October 2019

Milk protein fractions strongly affect the patterns of coagulation, curd firming, and syneresis.

J Dairy Sci 2019 Apr 14;102(4):2903-2917. Epub 2019 Feb 14.

Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova (Padua), 35020 Legnaro (PD), Italy.

The aim of this study was to assess the role of milk protein fractions in the coagulation, curd firming, and syneresis of bovine milk. Analyses were performed on 1,271 individual milk samples from Brown Swiss cows reared in 85 herds classified into 4 types of farming systems, from the very traditional (tied cows, feed manually distributed, summer highland pasture) to the most modern (loose cows, use of total mixed rations with or without silage). Fractions α-casein (CN), α-CN, β-CN, κ-CN, β-lactoglobulin (LG), and α-lactalbumin (LA) and genotypes at CSN2, CSN3, and BLG were obtained by reversed-phase HPLC. The following milk coagulation properties were measured with a lactodynamograph, with the testing time extended to 60 min: rennet coagulation time (RCT, min), curd firming time (min), and curd firmness at 30 and 45 min (mm). All the curd firmness measures recorded over time (total of 240 observations/sample) were used in a 4-parameter nonlinear model to obtain parameters of coagulation, curd firming, and syneresis: RCT estimated from the equation (min), asymptotic potential curd firmness (mm), the curd firming and syneresis instant rate constants (%/min), and the maximum curd firmness value (CF, mm) and the time taken to reach it (min). All the aforementioned traits were analyzed with 2 linear mixed models, which tested the effects of the protein fractions expressed in different ways: in the first, quantitative model, each protein fraction was expressed as content in milk; in the second, qualitative model, each protein fraction was expressed as a percentage of total casein content. Besides proteins, additional nuisance parameters were herd (included as a random effect), daily milk production (only for the quantitative model), casein content (only for the qualitative model), dairy system, parity, days in milk, the pendulum of the lactodynamograph, and the CSN2, CSN3, and BLG genotypes. Both α-CN and β-CN showed a clear and favorable effect on CF, where the former effect was almost double the latter. Milk coagulation ability was favorably affected by κ-CN, which reduced both the RCT and RCT estimated from the equation, increased the curd firming and syneresis instant rate constants, and allowed a higher CF to be reached. In contrast, α-CN delayed gelation time and β-LG worsened curd firming, both resulting in a low CF. The results of this study suggest that modification of the relative contents of specific protein fractions can have an enormous effect on the technological behavior of bovine milk.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2018-15524DOI Listing
April 2019

Cheese yield, cheesemaking efficiency, and daily production of 6 breeds of goats.

J Dairy Sci 2018 Sep 4;101(9):7817-7832. Epub 2018 Jul 4.

Department of Veterinary Medicine, University of Sassari, via Vienna 2, 07100 Sassari, Italy.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2018-14450DOI Listing
September 2018

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

J Dairy Sci 2018 Oct 16;101(10):8788-8804. Epub 2018 Aug 16.

Department of Veterinary Science, University of Parma, Via del Taglio 10, I-43126 Parma, Italy.

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

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2018-14503DOI Listing
October 2018

Direct and indirect predictions of enteric methane daily production, yield, and intensity per unit of milk and cheese, from fatty acids and milk Fourier-transform infrared spectra.

J Dairy Sci 2018 Aug 24;101(8):7219-7235. Epub 2018 May 24.

Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova (Padua), viale dell'Università 16-35020 Legnaro (PD), Italy. Electronic address:

Mitigating the dairy chain's contribution to climate change requires cheap, rapid methods of predicting enteric CH emissions (EME) of dairy cows in the field. Such methods may also be useful for genetically improving cows to reduce EME. Our objective was to evaluate different procedures for predicting EME traits from infrared spectra of milk samples taken at routine milk recording of cows. As a reference method, we used EME traits estimated from published equations developed from a meta-analysis of data from respiration chambers through analysis of various fatty acids in milk fat by gas chromatography (FA). We analyzed individual milk samples of 1,150 Brown Swiss cows from 85 farms operating different dairy systems (from very traditional to modern), and obtained the cheese yields of individual model cheeses from these samples. We also obtained Fourier-transform infrared absorbance spectra on 1,060 wavelengths (5,000 to 930 waves/cm) from the same samples. Five reference enteric CH traits were calculated: CH yield (CH/DMI, g/kg) per unit of dry matter intake (DMI), and CH intensity (CH/CM, g/kg) per unit of corrected milk (CM) from the FA profiles; CH intensity per unit of fresh cheese (CH/CY, g/kg) and cheese solids (CH/CY, g/kg) from individual cheese yields (CY); and daily CH production (dCH, g/d). Direct infrared (IR) calibrations were obtained by BayesB modeling; the determination coefficients of cross-validation varied from 0.36 for dCH to 0.57 for CH/CM, and were similar to the coefficient of determination values of the equations based on FA used as the reference method (0.47 for CH/DMI and 0.54 for CH/CM). The models allowed us to select the most informative wavelengths for each EME trait and to infer the milk chemical features underlying the predictions. Aside from the 5 direct infrared prediction calibrations, we tested another 8 indirect prediction models. Using IR-predicted informative fatty acids (FA) instead of FA, we were able to obtain indirect predictions with about the same precision (correlation with reference values) as direct IR predictions of CH/DMI (0.78 vs. 0.76, respectively) and CH/CM (0.82 vs. 0.83). The indirect EME predictions based on IR-predicted CY were less precise than the direct IR predictions of both CH/CY (0.67 vs. 0.81) and CH/CY (0.62 vs. 0.78). Four indirect dCH predictions were obtained by multiplying the measured or IR-predicted daily CM production by the direct or indirect CH/CM. Combining recorded daily CM and predicted CH/CM greatly increased precision over direct dCH predictions (0.96-0.96 vs. 0.68). The estimates obtained from the majority of direct and indirect IR-based prediction models exhibited herd and individual cow variability and effects of the main sources of variation (dairy system, parity, days in milk) similar to the reference data. Some rapid, cheap, direct and indirect IR prediction models appear to be useful for monitoring EME in the field and possibly for genetic/genomic selection, but future studies directly measuring CH with different breeds and dairy systems are needed to validate our findings.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2017-14289DOI Listing
August 2018

Modeling of coagulation, curd firming, and syneresis of goat milk from 6 breeds.

J Dairy Sci 2018 Aug 3;101(8):7027-7039. Epub 2018 May 3.

Department of Veterinary Medicine, University of Sassari, via Vienna 2, 07100 Sassari, Italy.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2018-14397DOI Listing
August 2018

Technical note: Improving modeling of coagulation, curd firming, and syneresis of sheep milk.

J Dairy Sci 2018 Jul 19;101(7):5832-5837. Epub 2018 Apr 19.

Department of Veterinary Medicine, University of Sassari, Via Vienna 2, 07100 Sassari, Italy.

The importance of milk coagulation properties for milk processing, cheese yield, and quality is widely recognized. The use of traditional coagulation traits presents several limitations for testing bovine milk and even more for sheep milk, due to its rapid coagulation and curd firming, and early syneresis of coagulum. The aim of this technical note is to test and improve model fitting for assessing coagulation, curd firming, and syneresis of sheep milk. Using milk samples from 87 Sarda ewes, we performed in duplicate lactodynamographic testing. On each of the 174 analyzed milk aliquots, using 180 observations from each aliquot (one every 15 s for 45 min after rennet addition), we compared 4 different curd firming models as a function of time (CF, mm) using a nonlinear procedure. The most accurate and informative results were observed using a modified 4-parameter model, structured as follows: [Formula: see text] where t is time, RCT (min) is the gelation time, CF (mm) is the potential asymptotical CF at an infinite time, k (%/min) is the curd firming rate constant, and k (%/min) is the curd syneresis rate constant. To avoid nonconvergence and computational problems due to interrelations among the equation parameters, CF was preliminarily defined as a function of maximum observed curd firmness (CF, mm) recorded during the analysis. For this model, all the modeling equations of individual sheep milk aliquots were converging, with a negligible standard error of the estimates (coefficient of determination >0.99 for all individual sample equations). Repeatability of the modeled parameters was acceptable, also in the presence of curd syneresis during the lactodynamographic analysis.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2017-14256DOI Listing
July 2018

Phenotypic and genetic relationships between indicators of the mammary gland health status and milk composition, coagulation, and curd firming in dairy sheep.

J Dairy Sci 2018 Apr 7;101(4):3164-3175. Epub 2018 Feb 7.

Department of Veterinary Medicine, University of Sassari, via Vienna 2, 07100 Sassari, Italy.

The present study investigated the effect of somatic cell count, lactose, and pH on sheep milk composition, coagulation properties (MCP), and curd firming (CF) parameters. Individual milk samples were collected from 1,114 Sarda ewes reared in 23 farms. Milk composition, somatic cell count, single point MCP (rennet coagulation time, RCT; curd firming time, k; and curd firmness, a, a, and a), and CF model parameters were achieved. Phenotypic traits were statistically analyzed using a mixed model to estimate the effects of the different levels of milk somatic cell score (SCS), lactose, and pH, respectively. Additive genetic, herd, and residual correlations among these 3 traits, and with milk composition, MCP and CF parameters, were inferred using a Bayesian approach. From a phenotypic point of view, higher SCS levels caused a delayed gelification of milk. Lactose concentration and pH were significant for many milk quality traits, with a very intense effect on both coagulation times and curd firming. These traits (RCT, RCT estimated using the curd firming over time equation, and k) showed an unfavorable increase of about 20% from the highest to the lowest level of lactose. Milk samples with pH values lower than 6.56 versus higher than 6.78 were characterized by an increase of RCT (from 6.00 to 14.3 min) and k (from 1.65 to 2.65 min) and a decrease of all the 3 curd firmness traits. From a genetic point of view, the marginal posterior distribution of heritability estimates evidenced a large and exploitable variability for all 3 phenotypes. The mean intra-farm heritability estimates were 0.173 for SCS, 0.418 for lactose content, and 0.206 for pH. Lactose (favorably), and SCS and pH (unfavorably), at phenotypic and genetic levels, were correlated mainly with RCT and RCT estimated using the curd firming over time equation and scarcely with the other curd firming traits. The SCS, lactose, and pH were significantly correlated with each other's. In conclusion, results reported in the present study suggest that SCS, pH, and lactose affect, contemporarily and independently, milk quality and MCP. These phenotypes, easily available during milk recording schemes measured by infrared spectra prediction, could be used as potential indicators traits for improving cheese-making ability of ovine milk.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2017-13975DOI Listing
April 2018

Garlic (Allium sativum L.) fed to dairy cows does not modify the cheese-making properties of milk but affects the color, texture, and flavor of ripened cheese.

J Dairy Sci 2018 Mar 10;101(3):2005-2015. Epub 2018 Jan 10.

Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padua, Viale dell'Università 16, 35020 Legnaro (PD), Italy. Electronic address:

Garlic and garlic components have recently been proposed as ruminal activity modulators to reduce the enteric methane emissions of ruminants, but little is known of their influence on milk coagulation properties, nutrient recovery, cheese yield, and sensorial and rheological characteristics of milk and cheese. The present study assessed the effects of garlic and diallyl sulfide supplements on dry matter intake (DMI), productive performance, milk coagulation properties, cheese yield, milk and cheese sensory profiles, and rheological characteristics. Four dairy cows were fed a total mixed ration either alone (control) or supplemented with 100 or 400 g/d of garlic cloves or 2 g/d of diallyl sulfide in 4 consecutive experimental periods in a 4 × 4 Latin square design. The diallyl sulfide dose was established to provide approximately the same amount of allyl thiosulfinate compounds as 100 g of fresh garlic cloves. The total mixed ration was composed of 0.29 corn silage, 0.23 corn-barley mixture, 0.17 sunflower-soybean mixture, 0.12 alfalfa hay, 0.12 grass hay, 0.04 sugar beet pulp, and 0.02 other additives, and contained 0.253 starch, 0.130 crude protein, and 0.375 neutral detergent fiber, on a dry matter basis. Each experimental period consisted of 7 d of transition and 14 d of treatment. On d 18 and 21 of each period, milk samples (10 L) were collected from each cow for chemical analysis and cheese-making. The organoleptic properties of the milk and 63-d-ripened cheeses were assessed by a panel of 7 trained sensory evaluators. The experimental treatments had no effects on DMI, milk yield, feed efficiency (milk yield/DMI), milk coagulation properties, nutrient recovery, or cheese yield. Garlic-like aroma, taste, and flavor of milk and cheese were significantly influenced by the treatments, particularly the highest dose of garlic cloves, and we found close exponential relationships between milk and cheese for garlic-like aroma (R = 0.87) and garlic-like flavor (R = 0.79). Diallyl sulfide and 400 g/d of garlic cloves resulted in lower pH, shear force, and shear work of ripened cheeses compared with the other treatments. Garlic cloves and diallyl sulfide had opposite effects on cheese color indices. We conclude that adding 400 g/d of garlic to the feed of lactating dairy cows highly influences the sensory and rheological characteristics of cheese.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3168/jds.2017-13884DOI Listing
March 2018

Inferring individual cow effects, dairy system effects and feeding effects on latent variables underlying milk protein composition and cheese-making traits in dairy cattle.

J Dairy Res 2018 Feb 10;85(1):87-97. Epub 2017 Nov 10.

Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE),University of Padova,Viale dell'Università 16, 35020 Legnaro,Italy.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1017/S0022029917000632DOI Listing
February 2018

Variation of milk coagulation properties, cheese yield, and nutrients recovery in curd of cows of different breeds before, during and after transhumance to highland summer pastures.

J Dairy Res 2017 Feb 3;84(1):39-48. Epub 2016 Oct 3.

Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE),University of Padova,Viale dell' Università 16, 35020 Legnaro, PD,Italy.

This paper aimed at evaluating the effect of summer transhumance to mountain pastures of dairy cows of different breeds on cheese-making ability of milk. Data were from 649 dairy cows of specialized (Holstein Friesian and Brown Swiss) dual purpose (Simmental) and local (mostly Rendena and Alpine Grey) breeds. The Fourier-Transform Infra-Red Spectra (FTIRS) of their milk samples were collected before and after transhumance in 109 permanent dairy farms, and during transhumance in 14 summer farms (with multi-breeds herds) of the Trento Province, north-eastern Italy. A variety of 18 traits describing milk coagulation, curd firming, cheese yield and nutrients recovery in curd/loss in whey were predicted on the basis of FTIRS collected at the individual cow level. Moving the cows to summer farms improved curd firming traits but reduced cheese yields because of an increase of water and fat lost in the whey. During summer grazing, most of cheese-making traits improved, often non-linearly. The milk from summer farms supplementing cows with more concentrates showed better curd firming and cheese yield, because of lower fat lost in the whey. The breed of cows affected almost all the traits with a worst cheese-making ability for milk samples of Holsteins through all the trial, and interacted with concentrate supplementation because increasing compound feed tended to improve cheese-making traits for all breed, with the exception of local breeds for coagulation time and of Brown Swiss for curd firming time. In general, summer transhumance caused a favourable effect on cheese-making aptitude of milk, even though with some difference according to parity, initial days in milk, breed and concentrate supplementation of cows.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1017/S0022029916000583DOI Listing
February 2017
-->