Cheese yield and nutrients recovery in the curd predicted by Fourier-transform spectra from individual sheep milk samples.

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.

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

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

Prediction accuracies of cheese-making traits using Fourier-transform infrared spectra in goat milk.

The objectives of this study were to explore the use of Fourier-transform infrared (FITR) spectroscopy on 458 goat milk samples for predicting cheese-making traits, and to test the effect of the farm variability on their prediction accuracy. Calibration equations were developed using a Bayesian approach with three different scenarios: i) a random cross-validation (CV) [80% calibration (CAL); 20% validation (VAL) set], ii) a stratified CV [(SCV), 13 farms used as CAL, and the remaining one as VAL set], and iii) a SCV where 20% of the goats randomly selected from the VAL farm were included in the CAL set (SCV80). The best prediction performance was obtained for cheese yield solids, justifying for its practical application at population level. Overall results were similar to or outperformed those reported for bovine milk. Our results suggest considering specific procedures for calibration development to propose reliable tools applicable along the dairy goat chain.

Variations in Casein Genes Are Associated with Milk Protein and Fat Contents in Sarda Goats (Capra hircus), with an Important Role of CSN1S2 for Milk Yield.

This work aimed to assess the variability of casein genes in a population of 153 bucks and 825 lactating does of the Sarda breed, and to perform association analysis between polymorphic sites and milk yield and composition traits. To genotype the casein genes, we chose an SNP panel including 44 SNPs mapping to the four casein genes CSN1S1, CSN2, CSN1S2, and CSN3. Genotyping (made by KASP™ genotyping assay, based on competitive allele-specific PCR) revealed the high variability of the Sarda goat, and haplotype analysis revealed linkage disequilibrium (LD) between CSN1S1 and CSN2 genes, in addition to two LD blocks within the CSN1S2 and two LD blocks within the CSN3 gene, in bucks and does. Association analysis revealed that variability at all four casein genes was associated with milk protein content, total solids, and milk energy. The three Ca-sensitive casein genes were associated with lipid content, and CSN1S2 showed a unique pattern, with intron variants associated with milk yield, in addition to milk pH, NaCl, and SCS (Somatic Cell Score). This information might prove useful in selection schemes and in future investigations aiming to better understand the biology of lactation, and the direct link between genotype and phenotype.

Haplotype structure of MSTN, IGF1, and BMP2 genes in Tunisian goats (Capra hircus) and their association with morphometric traits.

The aim of the present study was to evaluate variability and haplotype structure of twenty-eight single nucleotide polymorphisms (SNPs) at myostatin (MSTN), insulin-like growth factor 1 (IGF1), and bone morphogenetic protein 2 (BMP2) genes. Association between the polymorphic SNPs and morphometric traits was performed on a population of 263 Tunisian goats. The SNPs analyzed were all polymorphic (except one), and the three genes had different haplotype structures. Significant association of SNPs at MSTN with head length was highlighted in the Tunisian goats. The variability at IGF1 gene was associated with body length, ear length, tail length, and chest depth. For BMP2, significant association was revealed with chest depth. Significant association was also detected between linkage disequilibrium (LD) block 2 at IGF1 with body length. These findings might play a potential role in gene-assisted programs.

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

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

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

The objective of this study was to develop formulas based on milk composition of individual goat samples for predicting cheese yield (%CY) traits (fresh curd, milk solids, and water retained in the curd). The specific aims were to assess and quantify (1) the contribution of major milk components (fat, protein, and casein) and udder health indicators (lactose, somatic cell count, pH, and bacterial count) on %CY traits (fresh curd, milk solids, and water retained in the curd); (2) the cheese-making method; and (3) goat breed effects on prediction accuracy of the %CY formulas. The %CY traits were analyzed in duplicate from 600 goats, using an individual laboratory cheese-making procedure (9-MilCA method; 9 mL of milk per observation) for a total of 1,200 observations. Goats were reared in 36 herds and belonged to 6 breeds (Saanen, Murciano-Granadina, Camosciata delle Alpi, Maltese, Sarda, and Sarda Primitiva). Fresh %CY (%CYCURD), total solids (%CYSOLIDS), and water retained (%CYWATER) 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 (R2VAL) and the root mean square error of validation (RMSEVAL). In CrV, the formula with the best prediction accuracy for all %CY traits included fat, casein, and UHI (R2VAL = 0.65, 0.96, and 0.23 for %CYCURD, %CYSOLIDS, and %CYWATER, respectively). The WAV procedure showed R2VAL 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 %CYCURD and %CYWATER 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.

Mitochondrial DNA diversity of the Sardinian local cattle stock.

The aim of this research was to characterize the genetic diversity of the Sarda (Sa, n = 131), Sardo Bruna (SB, n = 44) and Sardo Modicana (SM, n = 26) cattle breeds, reared in the island of Sardinia (Italy). A portion of the mitochondrial DNA hypervariable region was sequenced, in order to identify a potential signature of African introgression. The FST coefficients among populations ranged between 0.056 for Sa vs SB and 0.167 for SB vs SM. AMOVA analysis indicated there was a significant differentiation of the three breeds, although most of diversity was gathered at the within-breed level. The Median Joining Network of the Sardinian sequences showed a potential founder effect signature. A MJ network including Sardinian cattle plus African, Italian, Iberian and Asian sequences, revealed the presence of haplogroup T3, already detected in Sa cattle, and the presence of Hg T1 and Hg T1'2'3, in Sa and SB. The presence of a private haplotype belonging to haplogroup T1, which is characteristic of African taurine breeds, may be due to the introgression of Sardinian breeds with African cattle, either directly (most probable source: North African cattle) or indirectly (through a Mediterranean intermediary already introgressed with African blood).

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

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

Novel Genes Associated with Dairy Traits in Sarda Sheep.

The aim of the present research was to analyze the variability of 45 SNPs from different genes involved in metabolism and innate immunity to perform an association analysis with the milk yield, composition and milk coagulation traits. A population of 1112 Sarda breed sheep was sampled. Genotyping was generated by a TaqMan Open ArrayTM. Thirty out of the 45 SNPs were polymorphic, and 12 displayed a minor allele frequency higher than 0.05. An association analysis showed that the variability at genes PRKAG3 and CD14 was significantly associated with the daily milk yield. The variability at PRKAG3 was also associated with the protein and casein content, somatic cell score and bacterial score. The variation at the PRKAA2 gene was associated with the milk lactose concentration. The SNPs at CD14 were also associated with the traditional milk coagulation properties, while the SNPs at GHR and GHRHR were associated with kSR, a derived coagulation parameter related to the rate of syneresis. The information provided here is new and increases our knowledge of genotype-phenotype interactions in sheep. Our findings might be useful in appropriate breeding schemes to be set up for the Sarda sheep breed, but these should be confirmed by further studies, possibly performed on independent populations.

Polymorphisms at Myostatin Gene (MSTN) and the Associations with Sport Performances in Anglo-Arabian Racehorses.

One hundred and eighty Anglo-Arabian horses running 1239 races were sampled for the present study. DNA was extracted from the blood and myostatin gene, MSTN, was genotyped. Moreover, prizes won and places were achieved for the 1239 races to perform association analyses between the different genotypes and sport traits. Two SNPs already reported in previous studies regarding the Thoroughbred breed, rs69472472 and rs397152648, were revealed as polymorphic. The linkage disequilibrium analysis investigating the haplotype structure of MSTN did not evidence any association block. Polymorphism at SNP rs397152648, previously known as g.66493737 T>C, significantly influenced sport traits, with heterozygous horses TC showing better results than homozygotes TT. The portion of variance due to the random effect of the individual animal, and the other phenotypic effects of sex, percentage of Arabian blood and race distance, computed together with the genotype at MSTN in the statistical models, exerted a significant influence. Hence, this information is useful to improve knowledge of the genetic profile of Anglo-Arabian horses and a possible selection for better sport performance.

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

Driven by the large amount of goat milk destined for cheese production, and to pioneer the goat cheese industry, the objective of this study was to assess the effect of farm in predicting goat milk-coagulation and curd-firmness traits via Fourier-transform infrared spectroscopy. Spectra from 452 Sarda goats belonging to 14 farms in central and southeast Sardinia (Italy) were collected. A Bayesian linear regression model was used, estimating all spectral wavelengths' effects simultaneously. Three traditional milk-coagulation properties [rennet coagulation time (min), time to curd firmness of 20 mm (min), and curd firmness 30 min after rennet addition (mm)] and 3 curd-firmness measures modeled over time [rennet coagulation time estimated according to curd firmness change over time (RCTeq), instant curd-firming rate constant, and asymptotical curd firmness] were considered. A stratified cross validation (SCV) was assigned, evaluating each farm separately (validation set; VAL) and keeping the remaining farms to train (calibration set) the statistical model. Moreover, a SCV, where 20% of the goats randomly taken (10 replicates per farm) from the VAL farm entered the calibration set, was also considered (SCV80). To assess model performance, coefficient of determination (R2VAL) and the root mean squared error of validation were recorded. The R2VAL varied between 0.14 and 0.45 (instant curd-firming rate constant and RCTeq, respectively), albeit the standard deviation was approximating half of the mean for all the traits. Although average results of the 2 SCV procedures were similar, in SCV80, the maximum R2VAL increased at about 15% across traits, with the highest observed for time to curd firmness of 20 mm (20%) and the lowest for RCTeq (6%). Further investigation evidenced important variability among farms, with R2VAL 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.

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

The prediction of traditional goat milk coagulation properties (MCP) and curd firmness over time (CFt) 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 CFt parameters. In total, 611 individual goat milk samples were used. Analysis of variance of measured MCP and CFt 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 (R2VAL), the root mean square error of validation (RMSEVAL), 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 R2VAL values obtained with the CRV procedure were moderate to high for the majority of coagulation traits, with RMSEVAL 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.

Assessing the Diversity and Population Substructure of Sarda Breed Bucks by Using Mtdna and Y-Chromosome Markers.

A sample of 146 Sarda bucks from eight subregions of Sardinia, Italy (Nuorese, Barbagia, Baronia, Ogliastra, Sarrabus, Guspinese, Iglesiente, Sulcis) were characterized for Y-chromosome and mtDNA markers to assess the levels of population substructure. Five polymorphic loci (SRY, AMELY, ZFY, and DDX3Y) on the Y-chromosome were genotyped. The control region of mtDNA was sequenced as a source of complementary information. Analysis of Y-chromosome data revealed the segregation of 5 haplotypes: Y1A (66.43%), Y2 (28.57%), Y1C (3.57%), Y1B1 (0.71%), and Y1B2 (0.71%). High levels of Y-chromosome diversity were observed in populations from Southwest Sardinia. The FST values based on Y-chromosome and mtDNA data were low, although a paternal genetic differentiation was observed when comparing the Nuorese and Barbagia populations (Central Sardinia) with the Sulcis, Iglesiente, and Sarrabus populations (Southern Sardinia). AMOVA analysis supported the lack of population substructure. These results suggest the occurrence of a historical and extensive gene flow between Sarda goat populations from different locations of Sardinia, despite the fact that this island is covered by several large mountain ranges. Introgression with foreign caprine breeds in order to improve milk production might have also contributed to avoiding the genetic differentiation amongst Sarda populations.

Exploring the Genotype at CSN3 Gene, Milk Composition, Coagulation and Cheese-Yield Traits of the Sardo-Modicana, an Autochthonous Cattle Breed from the Sardinia Region, Italy.

The Sardo-Modicana is a local cattle breed from Sardinia, Italy. No information about its dairy potential is available in the literature. This study investigated the genotype at the CSN3 gene and milk traits of the Sardo-Modicana cattle breed. Fifty-four cows were sampled for DNA extraction and genotyping at the κ-casein gene locus, CSN3. Forty individual milk samples were analyzed for milk composition, milk coagulation properties and cheese yield (CY%). All the Sardo-Modicana cows were BB homozygotes at CSN3. Hence, the results were compared with the other two local Sardinian breeds. Eighty-three Sarda and 21 Sardo-Bruna cows were genotyped, and the A allele was found (at frequencies of 0.416 and 0.405, respectively). As regards milk traits, the mean protein value was 3.74 g/100 mL, and the mean casein value was 2.98 g/100 mL. Total bacterial and somatic cell counts showed excellent levels of hygiene considering the extensive farming and hand milking. In addition, milk produced by Sardo-Modicana cows was characterized by favorable values of coagulation properties and cheese yield. This information may represent a starting point for the conservation and enhancement of this breed.

Test positivity for Maedi-Visna virus and Mycobacterium avium ssp. paratuberculosis in Sarda ewes: Effects on milk composition and coagulation traits and heritability estimates for susceptibility.

Maedi-Visna virus (MVV) and Mycobacterium avium ssp. paratuberculosis (MAP) are two pathogens that cause chronic, production-limiting diseases in dairy sheep. Although they are present worldwide, there are no detailed reports on their actual effects on milk traits in the literature. This study was designed to investigate the effects of test positivity to MVV and MAP on ovine milk yield, composition and coagulation properties, and curd-firming over time (CFt) variables in clinically healthy animals at the field level. The additive genetic variation and heritabilities of MVV and MAP positivity were also estimated. Milk samples were collected from 1,079 Sarda sheep kept on 23 farms, and pedigree information was obtained from the flock book. Milk yield was also recorded on the sampling date. Positivity for MVV and MAP was determined from milk samples using indirect ELISA test kits. Milk composition traits were measured by spectroscopy, milk coagulation properties were measured with a Formagraph (Foss Italia, Padua, Italy), and CFt traits were calculated using the data from the Formagraph diagram. The effects of MVV and MAP positivity on milk traits were determined through a set of mixed linear models, which took into account various sources of variation, such as days in milk, parity, and flock effects, and included the effects (positive or negative) of the 2 pathogens. A Bayesian threshold sire model with sire relationship was used to estimate genetic variation and heritability. The overall animal prevalence of MVV-positive ewes was 43.6%; on only 1 farm of the 23 tested were all sampled ewes negative. An overall animal prevalence of 10.6% was recorded for MAP, with 4 farms at 0%. Positivity for MVV significantly affected the logarithmic score of the bacterial count, curd firmness after 30 min and 45 min, and the curd-firming instant rate constant. We found significant effects of MAP infection on milk composition, pH, and rennet coagulation time. The mean of the posterior distributions of heritability estimates on the liability scale was 0.15 for MAP and 0.07 for MVV. Our results demonstrate that only a few traits are negatively affected by MVV and MAP positivity, and that there is exploitable genetic variation in MVV and MAP susceptibility in dairy sheep.

Association Analysis between SPP1, POFUT1 and PRLR Gene Variation and Milk Yield, Composition and Coagulation Traits in Sarda Sheep.

Many studies focus on the identification of genomic regions that undergo selective processes, where evidence of selection is revealed and positional candidate genes are identified. The aim of the research was to evaluate the association between positional candidate genes, namely secreted phosphoprotein 1 (SPP1, sheep chromosome Ovis aries OAR6, 36.651-36.658 Mb), protein O-fucosyltransferase 1 (POFUT1, OAR13, 61.006-61.027 Mb) and prolactin receptor (PRLR, OAR16, 38.969-39.028 Mb) with milk yield, composition and coagulation traits. Eight single nucleotide polymorphisms (SNPs) mapping to the three genes were genotyped in 380 Sarda dairy sheep. Statistical analysis revealed an association between SNP rs161844011 at SPP1 (chromosome position Oar_v3 OAR6:36651870, gene region exon 7) and somatic cell score, while POFUT1 SNP rs424501869 (OAR13:61007495, intron 1) was associated with curd firmness both 45 and 60 min after rennet addition (p = 0.015 and p = 0.007, respectively). SNP rs400874750 at PRLR gene (OAR16:39004070, intron 2) had a significant association with lactose content (p = 0.020), somatic cell score (p = 0.038), rennet coagulation time (p = 0.018) and curd firming time (p = 0.047). The outcome of this research confirmed predictions based on genomic studies, producing new information regarding the SPP1, POFUT1 and PRLR genes, which may be useful for future breeding schemes.

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

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 (CFt), 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, CFt, 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.

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

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 (k20), and curd firmness at 30 min (a30)], and modeled curd-firming over time (CFt) parameters [estimated rennet coagulation time (RCTeq), curd-firming instant rate constant (kCF), and potential curd firmness (CFP)] 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 CFt 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 CFt 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 (%CYWATER). We found an optimum value of milk k20, associated with the highest recovery of components and cheese yield in solids (%CYSOLIDS). In addition, a lower level of curd water retention and an increased fresh curd yield (%CYCURD) 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 RCTeq on %REC traits and %CYSOLIDS, which had not previously been revealed for traditional RCT. Moreover, higher kCF values were associated with increased %CYCURD and %CYSOLIDS. Given that CFt 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.