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Nuclear magnetic resonance spectroscopy was applied to investigate the association between milk metabolome and udder quarter health status in dairy cows. Mammary gland health status was defined by combining information provided by traditional somatic cell count (SCC) and differential SCC (DSCC), which expresses the percentage of neutrophils and lymphocytes over total SCC. Quarter milk samples were collected in triplicate (d 1 to 3) from 10 Simmental cows, 5 defined as cases and 5 defined as controls according to SCC levels at d 0. A total of 120 samples were collected and analyzed for bacteriology, milk composition, SCC, DSCC, and milk metabolome. Bacteriological analysis revealed the presence of mostly coagulase-negative staphylococci in quarter milk samples of cows defined as cases. Nuclear magnetic resonance spectra of all quarter samples were first analyzed using the unsupervised multivariate approach principal component analysis, which revealed a specific metabolomic fingerprint of each cow. Then, the supervised cross-validated orthogonal projections to latent structures discriminant analysis unquestionably showed that each cow could be very well identified according to its milk metabolomic fingerprint (accuracy = 95.8%). The comparison of 12 different models, built on bucketed 1-dimensional NOESY spectra (noesygppr1d, Bruker BioSpin) using different SCC and DSCC thresholds, corroborated the assumption of improved udder health status classification ability by joining information provided by both SCC and DSCC. Univariate analysis performed on the 34 quantitated metabolites revealed lower levels of riboflavin, galactose, galactose-1-phosphate, dimethylsulfone, carnitine, hippurate, orotate, lecithin, succinate, glucose, and lactose, and greater levels of lactate, phenylalanine, choline, acetate, O-acetylcarnitine, 2-oxoglutarate, and valine, in milk samples with high somatic cells. In the 5 cases, results of the udder quarter with the highest SCC compared with its symmetrical relative were in line with quarter-level findings. Our study suggests that increased SCC is associated with changes in milk metabolite fingerprint and highlights the potential use of different metabolites as novel indicators of udder health status and milk quality.

Background The quality of colostrum administered to calves is based on its concentration in immunoglobulins G (IgG, g/L). Immunoglobulins A (IgA) and M (IgM) are also present but at a lower level. The gold standard reference analysis for these traits, radial immunodiffusion, is time-consuming and expensive. In order to define breeding strategies that are aimed at improving colostrum quality in dairy cattle, a large amount of data is needed, and the use of indicator traits would be beneficial. In the study presented here, we explored the heritabilities of reference (radial immunodiffusion) and near infrared-predicted IgG, IgA, and IgM concentrations and estimated their genetic correlations. First, the colostrum of 765 Holstein cows from nine herds was sampled to perform a reference analysis and the near-infrared spectra (400–2500 nm) were stored. We used a calibration set (28% of the initial samples) that was representative of the herds and cow parity orders to develop prediction equations for IgG, IgA, and IgM concentrations. Finally, these traits were predicted in the validation set (72% of the initial samples) to estimate genetic parameters for the predictions. Genetic correlations between reference and predicted values of each trait were estimated through bivariate linear animal models. Results The three near-infrared-predicted immunoglobulin fractions were genetically correlated with their reference value. In particular, the reference and predicted IgG concentrations were strongly correlated at both the genetic (0.854 ± 0.314) and phenotypic level (0.767 ± 0.019). Weaker associations were observed for IgA and IgM concentrations, which were predicted with lower accuracy compared to IgG. Simulation analyses suggested that improving colostrum quality by selective breeding in Holstein cattle based on near-infrared predicted colostrum immunoglobulins concentrations is feasible. In addition, less than 10 mL of colostrum are needed for spectra acquisition and thus implementation of such analyses is possible in the near future. Conclusions The concentrations of colostrum immunoglobulins can be predicted from near-infrared spectra and the genetic correlation between the reference and the predicted traits is positive and favourable, in spite of the large standard errors of the estimates. Near-infrared spectroscopy can be exploited in selective breeding of dairy cattle to improve colostral immunoglobulins concentration.

The present study aimed to investigate non-genetic sources of variation of milk production and quality traits of dual-purpose Original Brown (OB) cows farmed in Italian alpine region by using milk test-day records (n = 4034). Except for milk yield and somatic cell count, all phenotypes were predicted from milk mid-infrared spectra and included traditional composition traits, coagulation properties, casein fractions, minerals and fatty acids. Data were analysed using a mixed linear model which included calving season, parity, stage of lactation and first-order interactions as fixed effects, and cow and herd-test-date as random effects. Milk yield averaged 18.07 kg/d and means of fat, protein and casein content (%) were 4.03, 3.40 and 2.68, respectively. Primiparous OB cows produced milk with a greater content of unsaturated fatty acids compared with multiparous. Except for Na, minerals content was generally greater in primiparous than multiparous cows. The comparison with the literature demonstrated that OB cows produce milk with fatty acid profile similar to that of Alpine Grey and with more favourable coagulation properties and mineral composition than Pinzgauer cows. Considering that OB milk exhibited good coagulation properties, a prerequisite for cheesemaking, strategies to valorise this endangered breed should mainly focus on the manufacturing of OB mountain cheeses. In general, results for several milk-related performance coupled with the well-known strong adaptability of the breed to extensive mountain farming systems are the starting point towards the valorisation and potential expansion of this local dual-purpose genetic resource, with the ultimate goal of contributing to its conservation.Highlights Primiparous cows showed greater mineral content compared to multiparous cows. The good milk coagulation properties and high α-CN and κ-CN of Original Brown cows milk are a prerequisite for cheesemaking efficiency. A greater content of unsaturated fatty acids was observed in primiparous than multiparous OB cows.

Changes in milk production traits over time might be informative of the health status of cows and may contain useful information for selective breeding purposes. In particular, early indicators are useful for traits such as longevity, which become available late in the cow's life. Lactose percentage (LP) tends to decrease in the presence of udder infection and with parity. Therefore, it can be hypothesized that cows exhibiting limited changes in LP across lactations have experienced fewer udder infections in their productive life and have a higher chance to stay longer in the herd than cows with more pronounced reduction of LP across lactations. In this study, 9 descriptors of change in LP during a cow's lifetime were defined and evaluated as potential indicators for selective breeding. For the purpose of this study, test-day records of the first 44 days in milk (DIM) of each lactation were discarded, and cows were required to have at least 5 test-days/cow per lactation (≥45 DIM) over the first 3 lactations. In this study, descriptors of LP were available for 69,586 Italian Holstein cows. Changes in LP in each lactation were quantified by regressing LP on DIM; thus, β1, β2, and β3 represented the changes in LP within lactations 1, 2, and 3, respectively. Changes in LP across multiple lactations were also quantified by regressing LP on DIM (with exclusion of the first 44 DIM of each lactation); briefly, β12 was the change of LP over lactation 1 and 2, β23 was the change of LP over lactation 2 and 3, and β123 was the change of LP over lactation 1, 2, and 3. Alternatively, changes in the LP lactation means (Δ) were quantified between lactations 1 and 2 (Δ12), 2 and 3 (Δ23), and 1 and 3 (Δ13). For comparison, β and Δ were also derived for milk yield (kg/d), somatic cell score, and log-transformed total somatic cells excreted daily in milk (units). Variance components and estimated breeding values (EBV) for all β's and Δ's were estimated. In addition, EBV for bulls with at least 25 daughters were used to assess Calo's genetic correlations between descriptors of change in LP with official published EBV for functional traits. Heritabilities for β and Δ of LP ranged from 0.06 (Δ23) to 0.20 (Δ13), and differed significantly from 0. Furthermore, LP EBV for β and Δ were correlated with official EBV for functional longevity index, udder health index, udder score (mammary gland morphology) index, and milk persistency; Calo's genetic correlations of LP β123 with functional longevity and udder health index were 0.52 and 0.33, respectively. Cows with a stronger reduction of LP across lactations (i.e., stronger and negative β, and greater and positive Δ) were characterized by lower milk persistency, impaired longevity, and worse udder health and morphology than cows with smaller reduction in LP across lactations. Results highlighted that changes in milk LP have the potential to be exploited as indicators for functional traits in Italian Holstein cattle. Further research on the biological relationship between changes in LP and mastitis is recommended.

Milk urea nitrogen (MUN), a trait routinely measured in the national milk recording system, is a useful indicator of nitrogen utilization efficiency of dairy cows, and selection for MUN and MUN-derived traits could be a valid strategy to produce better animals with regard to efficiency of nitrogen utilization. Therefore, the aim of the present study was to explore the genetic aspects of MUN and new potential indicators of nitrogen efficiency, namely ratios of protein to MUN, casein to MUN, and whey protein to MUN, in the Italian Brown Swiss population. A total of 153,175 test-day records of 10,827 cows in 500 herds were used for genetic analysis. Variance components and heritability of the investigated traits were estimated using single-trait repeatability animal models, whereas genetic and phenotypic correlations between the traits were estimated through bivariate repeatability animal models, including fixed effects of herd-test-date, stage of lactation, parity, calving year, and calving season, and the random effects of additive genetic animal, cow permanent environment, and the residual. Heritability estimates for MUN (0.20 ± 0.01) and the 3 new indicators of nitrogen utilization efficiency (0.15 ± 0.01 for protein-to-MUN and casein-to-MUN ratios, and 0.12 ± 0.01 for ratio of whey protein to MUN) suggested that additive genetic variation exists for these traits, and thus there is potential to select for greater organic nitrogen and lower inorganic nitrogen in milk. Genetic association between MUN and the 3 ratios was high (-0.87 ± 0.01) but not unity, suggesting that ratios could provide some further information beyond that provided by MUN with regard to efficiency of nitrogen utilization. Genetic trend of the investigated traits by year of birth of Brown Swiss sires showed how the selection applied in the last 30 yr has led to an increase of both quantity and quality of milk, and a decrease of somatic cell score and MUN. The inclusion of MUN in breeding programs could speed up the process of increasing organic nitrogen such as protein, which is useful for cheese-making, and reducing inorganic nitrogen (MUN) in milk.

The change in feeding regime of dairy herds using summer grazing in mountainous areas has several implications on cows’ productivity and milk composition. The present study quantified the effect of summer grazing on the milk fatty acids (FA) profile of Simmental and crossbred cows in an alpine holding. A total of 616 milk samples of 71 cows were collected 3 days before the onset of the grazing season until 91 days of grazing. Individual and groups of FA were quantified through mid-infrared spectroscopy. Data were analysed using a linear mixed model including the fixed effects of breed, stage of lactation, parity, sampling period, and the random effects of cows nested within breed and the residual. The stage of lactation and the sampling period were the most significant factors associated with milk FA. The variance explained by the random cow effect ranged from 15.10% (C18:1) to 25.31% (medium-chain FA). The concentration of C14:0, C16:0, and short- and medium-chain FA decreased across the summer season. Long-chain FA and polyunsaturated FA concentrations were greater in milk obtained at pasture compared with milk obtained indoors. Given these outcomes, the present study demonstrated the positive effect of grazing on milk FA composition from a nutraceutical point of view.

Simple Summary Dairy herds in alpine areas usually adopt summer grazing, mainly to reduce feeding costs. This practice is related to the maintenance of local traditions and to the manufacturing of niche dairy products. However, it is important to assess the impact of this practice on cattle health. This case study investigated how milk-related health traits vary across extensive grazing during the summer period, using data collected in a dairy herd whose cows were repeatedly controlled for individual milk samples. Although the transition from barn farming to pasture led to a reduction in milk production, proper grazing management can make dairy cows more resilient in terms of udder health and metabolic efficiency. Findings of the present research report suggested that pasture can be adopted to maintain dairy herd sustainability without impairing animal health. Abstract Extensive summer grazing is a dairy herd management practice frequently adopted in mountainous areas. Nowadays, this activity is threatened by its high labour demand, but it is fundamental for environmental, touristic and economic implications, as well as for the preservation of social and cultural traditions. Scarce information on the effects of such low-input farming systems on cattle health is available. Therefore, the present case study aimed at investigating how grazing may affect the health status of dairy cows by using milk traits routinely available from the national milk recording scheme. The research involved a dairy herd of 52 Simmental and 19 Holstein × Simmental crossbred cows. The herd had access to the pasture according to a rotational grazing scheme from late spring up to the end of summer. A total of 616 test day records collected immediately before and during the grazing season were used. Individual milk yield was registered during the milking procedure. Milk samples were analysed for composition (fat, protein, casein and lactose contents) and health-related milk indicators (electrical conductivity, urea and β-hydroxybutyrate) using mid-infrared spectroscopy. Somatic cell count (SCC) and differential SCC were also determined. Data were analysed with a linear mixed model, which included the fixed effects of the period of sampling, cow breed, stage of lactation and parity, and the random effects of cow nested within breed and the residual. The transition from barn farming to pasture had a negative effect on milk yield, together with a small deterioration of fat and protein percentages. Health-related milk indicators showed a minor deterioration of the fat to protein ratio, differential SCC and electrical conductivity, particularly towards the end of the grazing season, whereas the somatic cell score and β-hydroxybutyrate were relatively constant. Overall, the study showed that, when properly managed, pasture grazing does not have detrimental effects on dairy cows in terms of udder health and efficiency. Therefore, the proper management of cows on pasture can be a valuable solution to preserve the economic, social and environmental sustainability of small dairy farms in the alpine regions, without impairing cows’ health.

Food antioxidants enhance products shelf life and stability during technological treatments through the maintenance of their physical and chemical properties. Moreover, they are endowed with several positive effects on human health, including cell membranes preservation, enzyme functionality, and DNA integrity. Milk has been described in relation to a wide array of fat soluble and water-soluble antioxidant compounds, in particular vitamin A, C, and E, lactoferrin and peptides derived from casein and whey proteins. The total antioxidant activity (TAA) of milk is a novel and scarcely explored trait, defined as the sum of antioxidant contributions of the aforementioned compounds. On this background, the aims of the present study were to investigate the variability of milk TAA on a large scale exploiting predictions obtained through mid-infrared (MIR) spectroscopy and to estimate genetic parameters of this trait in Holstein cows. Individual milk samples were collected between January 2011 and December 2018 during the routine milk recording procedure. Samples were analysed for gross composition through MIR spectroscopy and MIR spectra were stored. Milk TAA was then predicted (pTAA) from the stored milk MIR spectra (111,653 test-day records of 9519 cows in 344 herds) using the previously developed prediction model, considering the prediction accuracy, pTAA might be considered a proxy of the TAA determined through the reference method. Overall, pTAA averaged 7.16 mmoL/L of Trolox equivalents, showed a nadir around 40 days after calving and increased thereafter, following a linear trend up to the end of lactation. The lowest pTAA was observed in milk sampled from June to September. Milk pTAA was heritable (0.401 &plusmn, 0.015) and genetically associated to fat yield (0.366 &plusmn, 0.049), crude protein (CP) yield (0.238 &plusmn, 0.052), fat percentage (0.616 &plusmn, 0.022) and CP percentage (0.754 &plusmn, 0.015). The official selection index of Italian Holstein put the 49% of the emphasis on fat and protein yield and percentage, therefore, it derives that an indirect favourable selection for milk pTAA should be already in progress in Italian Holstein population.

This study aimed to estimate genetic parameters for 19 linear type traits related to frame, udder, and feet and legs, and for final score of 10,305 first-parity Jersey cows evaluated between 2004 and 2016. Since scoring of locomotion in Jersey breed started in 2009, a subset of 6853 animals was extracted from the original data and used to investigate sources of variation and heritability of locomotion score, and its associations with the other traits. Univariate animal models were used to estimate variance components of type traits and bivariate analyses were implemented to obtain genetic correlations between traits. Fixed effects were herd-year-classifier, season of evaluation, stage of lactation at scoring and age at calving, and the random effects were additive genetic animal and the residual. Herd-year-classifier was the major source of variation affecting the traits. Heritabilities were low with the only exception of a moderate heritability (0.32 ± 0.02) for stature. The lowest heritabilities were estimated for feet and legs traits with values between 0.04 ± 0.02 (rear leg set side view, rear leg set rear view and locomotion) and 0.07 ± 0.02 (foot angle). The final score had heritability of 0.20 ± 0.02. Genetic correlations were generally stronger than their phenotypic counterparts. Overall, frame traits were weakly correlated with feet and legs, and udder traits, except for rump width, which showed moderate correlations with almost all traits, and angularity which showed the greatest correlations with rear udder height (0.61 ± 0.10) and rear udder width (0.62 ± 0.11). Genetic correlations between locomotion and frame traits ranged from 0.08 ± 0.22 (angularity) to 0.32 ± 0.16 (stature). The strongest correlations were estimated between locomotion and other feet and legs traits, but also with front teat placement (0.97 ± 0.19) and with rear teat placement (0.88 ± 0.17). Results of the present study will be used to enhance genetic evaluation of linear type traits in Jersey cattle breed.

Adequate milk consumption significantly contributes to meeting the human iodine recommended daily intake, which ranges from 70 µg/d for infants to 200 µg/d for lactating women. The fulfilment of iodine recommended daily intake is fundamental to prevent serious clinical diseases such as cretinism in infants and goiter in adults. In the present study iodine content was measured in raw and processed commercial cow milk, as well as in raw buffalo, goat, sheep, and donkey milk. Iodine extraction was based on 0.6% (vol/vol) ammonia, whereas iodine detection and quantification were carried out through an inductively coupled plasma mass spectrometer analyzer. Among processed commercial cow milk, partially skimmed pasteurized milk had the greatest iodine content (359.42 µg/kg) and raw milk the lowest (166.92 µg/kg). With regard to the other dairy species, the greatest iodine content was found in raw goat milk (575.42 µg/kg), followed by raw buffalo (229.82 µg/kg), sheep (192.64 µg/kg), and donkey milk (7.06 µg/kg). Repeatability of milk iodine content, calculated as relative standard deviation of 5 measurements within a day or operator, ranged from 0.96 to 1.84% and 0.72 to 1.16%, respectively. The overall reproducibility of milk iodine content, calculated as relative standard deviation of 45 measurements across 3 d of analyses and 3 operators, was 4.01%. These results underline the precision of the proposed analytical method for the determination of iodine content in milk.

The aim of this study was to estimate genetic associations between alternative somatic cell count (SCC) traits and milk yield, composition and udder type traits in Italian Jersey cows. Alternative SCC traits were test-day (TD) somatic cell score (SCS) averaged over early lactation (SCS_150), standard deviation of SCS of the entire lactation (SCS_SD), a binary trait indicating absence or presence of at least one TD SCC >400,000 cells/ml in the lactation (Infection) and the ratio of the number of TD SCC >400,000 cells/ml to total number of TD in the lactation (Severity). Heritabilities of SCC traits, including lactation-mean SCS (SCS_LM), ranged from 0.038 to 0.136. Genetic correlations between SCC traits were moderate to strong, with very few exceptions. Unfavourable genetic associations between milk yield and SCS_SD and Infection indicated that high-producing cows were more susceptible to variation in SCC than low-producing animals. Cows with deep udders, loose attachments, weak ligaments and long teats were more susceptible to an increase of SCC in milk. Overall, results suggest that alternative SCC traits can be exploited to improve cow's resistance to mastitis in Italian Jersey breed.

The genetic correlations (ra) of milk lactose percentage (LP), lactose yield (LY), and ratios of LP to other milk solids with udder, metabolic, and fertility disorders have not been assessed in dairy cattle so far. To evaluate the potential role of milk lactose as indicator of cow health, 142,285 lactation records of 84,289 Austrian Fleckvieh cows were analyzed with univariate and bivariate animal models. Milk traits were on a 150-d basis and health traits were coded as binary (0/1). Other than LP and LY, 3 new phenotypes were defined and included in the present study, namely the lactose-to-fat, lactose-to-protein, and lactose-to-solids ratios. The most heritable trait was LP (0.566 ± 0.008) and heritability of LY was much lower (0.145 ± 0.005). Heritability estimates close to 0.50 were assessed for the ratios. The frequency of health disorders was higher in multiparous cows yielding milk with low LP (≤4.553%) compared with cows yielding milk with high LP (≥5.045%). Heritabilities of health traits were in the expected ranges, with the highest estimate for ovarian cysts (CYS; 0.037 ± 0.004) and the lowest for retained placenta (0.005 ± 0.001). Mastitis (MAS) genetically correlated with LY (0.518 ± 0.057); considering that the amount of synthesized lactose is the key regulator of milk volume, this result confirmed that high-producing cows are more genetically susceptible to MAS than low-producing animals. Similar to MAS, ketosis (KET) was also positively genetically associated with LY (0.420 ± 0.077) and a weak and unfavorable ra between KET and lactose-to-protein ratio was estimated (0.159 ± 0.077). The ra of LY with milk fever (MFV) and CYS were approximately 0.20. The ra of LP with MAS, KET, and MFV were negative (-0.142 on average), supporting the idea that LP is a potential health indicator. Genetic correlations between health traits ranged from zero (retained placenta with MAS and CYS) to 0.463 ± 0.090 (MAS and MFV). Results of the present study suggest that LP has potentiality to be used as indicator trait to improve udder health in Austrian Fleckvieh population.

The aim of the present study was to assess genetic variation and heritability of a novel indicator of udder health, milk differential somatic cell count (DSCC), which represents the percentage of neutrophils plus lymphocytes in the total somatic cell count (SCC). Furthermore, we estimated genetic and phenotypic correlations of DSCC with other milk traits routinely measured in Italian Holstein cows. Besides DSCC, test-day data included milk yield, composition traits (i.e., fat, protein, casein, and lactose percentages), pH, milk urea nitrogen, and SCC. After editing, the final data set included 10,709 test-day records of 5,142 cows in 299 herds. Mean of DSCC was 62.07%, which means that macrophages were approximately 38% of total SCC. Comparing our results with the literature offered compelling evidence of the importance of acquiring information about the proportion of the different cell types in milk to better define the udder health status. In addition, our analysis revealed, for the first time, that DSCC is a heritable trait, and heritability (0.08 ± 0.02) was higher than that of traditional somatic cell score (0.04 ± 0.02). Nevertheless, heritability of DSCC is still low compared with milk yield and quality traits. Single-trait analysis within parity showed that DSCC was less heritable in primiparous than in multiparous cows, whereas bivariate analysis confirmed that DSCC and somatic cell score were 2 different traits, as their genetic and phenotypic correlations differed from unity. From a genetic point of view, the DSCC was positively weakly associated with milk yield, lactose percentage, and milk urea nitrogen, and negatively associated with pH. Our findings contributed to the understanding of the genetic background of DSCC and are a precursor to the potential use of DSCC in breeding programs to enhance cow resistance to mastitis. However, further research is needed to determine the weight this novel trait should receive in a selection program aimed to reduce udder health problems.

The phenotypic variation of milk total antioxidant activity (TAA) and the ability of mid-infrared spectroscopy to predict this novel trait was investigated. Total antioxidant activity was measured through the reference spectrophotometric method on 1249 individual milk samples of Holstein Friesian cows. Sources of variation of milk TAA were investigated using a mixed model, which included the fixed effects of days in milk, parity and calving season, and the random effects of herd-test-date and error. Mid-infrared spectroscopy prediction models were developed using partial least squares regression approach. The average level of milk TAA was 6.93 mmoL L−1 of Trolox equivalents; this exhibited a coefficient of variation of 15% and showed weak phenotypic correlations with milk quality traits. Values of TAA were lower in early lactation than in late lactation. Mid-infrared spectroscopy prediction models reached a coefficient of determination in external validation of 0.41, suggesting that they are not adequate for analytical purposes.

Milk mineral concentration is important from both the perspective of processing milk into dairy products and its nutritive value for human consumption. Precise estimates of genetic parameters for milk mineral concentration are lacking because of the considerable resources required to collect vast phenotypes quantities. The milk concentration of calcium (Ca), potassium (K), magnesium (Mg), sodium (Na) and phosphorus (P) in the present study was quantified from mid-IR spectroscopy on 12 223 testday records from 1717 Holstein-Friesian cows. (Co)variance components were estimated using random regressions to model both the additive genetic and within-lactation permanent environmental variances of each trait. The coefficient of genetic variation averaged across days-in-milk (DIM) was 6.93%, 3.46%, 6.55%, 5.20% and 6.68% for Ca, K, Mg, Na and P concentration, respectively; heritability estimates varied across lactation from 0.31 ± 0.05 (5 DIM) to 0.67 ± 0.04 (181 DIM) for Ca, from 0.18 ± 0.03 (60 DIM) to 0.24 ± 0.05 (305 DIM) for K, from 0.08 ± 0.03 (15 DIM) to 0.37 ± 0.03 (223 DIM) for Mg, from 0.16 ± 0.03 (30 DIM) to 0.37 ± 0.04 (305 DIM) for Na and from 0.21 ± 0.04 (12 DIM) to 0.57 ± 0.04 (211 DIM) for P. Genetic correlations within the same trait across different DIM were almost unity between adjacent DIM but weakened as the time interval between pairwise compared DIM lengthened; genetic correlations were weaker than 0.80 only when comparing both peripheries of the lactation. The analysis of the geometry of the additive genetic covariance matrix revealed that almost 90% of the additive genetic variation was accounted by the intercept term of the covariance functions for each trait. Milk protein concentration and mineral concentration were, in general, positively genetically correlated with each other across DIM, whereas milk fat concentration was positively genetically correlated throughout the entire lactation with Ca, K and Mg; the genetic correlation with fat concentration changed from negative to positive with Na and P at 243 DIM and 50 DIM, respectively. Genetic correlations between somatic cell score and Na ranged from 0.38 ± 0.21 (5 DIM) to 0.79 ± 0.18 (305 DIM). Exploitable genetic variation existed for all milk minerals, although many national breeding objectives are probably contributing to an indirect positive response to selection in milk mineral concentration.

The present study aimed to assess the phenotypic variation of milk yield (MY) and quality traits in Italian Jersey (IJ) breed. Sources of variation were investigated through a linear mixed model, including the fixed effects of days in milk (DIM), parity, calving season, milking frequency, recording type, the interaction between DIM and parity, and the random effects of herd-test-day (HTD), cow and the residual. Results highlighted the high contents of milk fat (5.18%), protein (4.08%) and casein (3.16%) of IJ cows. Somatic cell score, averaging 3.35 units, should be lowered through specific managerial actions. Phenotypic variances of MY and milk quality traits were mainly due to cow effect, whereas phenotypic variance of milk urea nitrogen (MUN) content was mainly due to HTD effect, meaning that managerial conditions, especially feeding, are very important to explain the variation of MUN. In conclusion, the present study allowed to characterise milk of IJ cows at population level and to identify environmental factors associated with variation of MY and quality traits, which will be useful to adjust phenotypic records in genetic evaluation of Jersey breed.Highlights Factors affecting milk quality traits of Italian Jersey cows have been investigated. Phenotypic variance of milk composition and SCS was mainly due to cow effect, and that of MUN was mainly driven by herd-test-day effect. Significant environmental factors identified in the present study will be used to adjust phenotypic records in genetic analysis.

Milk somatic cell count (SCC), an indicator of udder health and milk hygiene, has not been implemented either in milk payment systems or in the current selection index of Italian buffalo so far. As a matter of fact, there is room to improve udder health through genetic and management strategies in this species. Repeated milk SCC test-day (TD) records on the same animal are useful to derive novel phenotypes on lactation basis by using somatic cell score (SCS) and thus to disclose buffaloes with udder issues to be monitored. In this study, sources of variation of SCC-derived traits in buffalo milk were investigated and their effect on milk yield and composition traits was estimated. Mean SCS (SCS150), standard deviation of SCS (SCS_SD150) and severity (SEV150, ratio between the number of TD SCC >200,000 cells/mL and total number of TD available in the first 150 DIM) in the first 150 days in milk were calculated using TD data of 45,312 lactations from 35,623 buffaloes. Sources of variation of such traits were investigated through a linear model. Both SCS150 and SEV150 increased with parity, whereas SCS_SD150 decreased (p < .001). Subsequently, the three traits were separately included in the model as explanatory variables to estimate their effect on milk yield and composition traits. Results showed that milk yield and lactose content were lower in animals with high and variable SCS in the first 150 days of lactation (p < .001). This study opens the debate on the development of an udder health index for the Italian buffalo.HIGHLIGHTSSo far, somatic cell count has not been considered in payment systems of buffalo milk in Italy.There is need to improve mastitis resistance and udder health in dairy buffaloes.Traits derived from test-day records can be used for management and breeding purposes in buffaloes. So far, somatic cell count has not been considered in payment systems of buffalo milk in Italy. There is need to improve mastitis resistance and udder health in dairy buffaloes. Traits derived from test-day records can be used for management and breeding purposes in buffaloes.

The aim of this study was to investigate the variation of gross composition, somatic cell count, urea content, and fatty acids (FA) composition of bulk milk from single-breed and multi-breed farms in alpine area, keeping either Brown Swiss (BS), Holstein Friesian (HF), Simmental (SI), or their combinations. Gross milk composition, urea content, and FA composition were predicted using mid-infrared spectroscopy. Observations were grouped in 7 combinations consisting of 3 singlebreed and 4 multi-breed types of herd. A mixed linear model was used for data analysis, accounting for the fixed effects of herd composition (7 combinations), month of sampling, year of sampling, and the interactions between herd composition and month of sampling, and between herd composition and year of sampling. Farm was included as random effect. Results highlighted that about two thirds of South Tyrolean farms were single-breed and herds with more than 20 lactating cows changed herd structure over time, switching from multi- to single-breed. Single-breed BS farms produced milk with greater fat, protein, casein, lactose, and FA content than single-breed HF and SI farms. Further, multi-breed herds including BS cows produced milk with greater fat, protein, casein, and polyunsaturated FA content than multi-breed HF+SI herds. Overall, single-breed SI farms produced milk with lower somatic cell count than other herd combinations. Despite the number of BS cows in South Tyrol has decreased in favor of SI in the last years, this breed is still the most interesting for alpine dairy farming to achieve optimal milk quality in both single- and multi-breed scenarios. The tendency to move to SI is mainly related to good milk performance of SI cows coupled with their robustness, high carcass value, high market value of calves, and adaptability to mountain farming system.

Milk and dairy products are considered important sources of iodine in several countries. Despite this, there is a paucity of studies that have investigated sources of variation of milk iodine, especially on a large scale. So far, it is not clear if milk iodine content could be increased through breeding in dairy cattle. Recently, a mid-infrared spectroscopy prediction model has been developed for an indirect quantification of iodine content in cow milk, as it is a faster and less expensive method that allows the prediction at population level. The model has coefficient of determination and ratio of performance to deviation in external validation of 0.57 and 1.44, respectively, and it was used in the present study to predict the iodine content from historical milk spectral data to investigate phenotypic and genetic aspects in the Italian Holstein cattle. Based on the accuracy of the model, the prediction was interpreted as proxy for the real milk iodine concentration (IODP). The data set comprised 33,776 test-day records with IODP from 4,072 cows. Data of IODP were transformed through natural logarithm to achieve a normal distribution. The effect of parity, lactation stage, and month of sampling were investigated, and genetic parameters were estimated using a test-day repeatability animal model. Milk IODP decreased with parities and was the lowest in early lactation. Heritability of IODP was low (0.025) and it was positively genetically correlated with milk yield and negatively with fat content. Results suggested that it would be challenging to directly improve this trait through breeding strategies in dairy cattle, because IODP is mainly affected by temporary environmental factors and thus, cannot be easily improved through genetics. Although preliminary, findings of this study suggest that it would be more convenient to develop feeding and management strategies to drive milk iodine level than to put efforts and resources into breeding strategies. Further studies should validate IODP as an indicator trait of milk iodine content by improving reference data and estimating genetic correlation between predicted and measured values.

Methane (CH4) emissions represent a worldwide problem due to their direct involvement in atmospheric warming and climate change. Ruminants are among the major players in the global scenario of CH4 emissions, and CH4 emissions are a problem for feed efficiency since enteric CH4 is eructed to the detriment of milk and meat production. The collection of CH4 phenotypes at the population level is still hampered by costly and time-demanding techniques. In the present study, a laser methane detector was used to assess repeatability and reproducibility of CH4 phenotypes, including mean and aggregate of CH4 records, slope of the linear equation modelling the aggregate function, and mean and number of CH4 peak records. Five repeated measurements were performed in a commercial farm on three Simmental heifers, and the same protocol was repeated over a period of three days. Methane emission phenotypes expressed as parts per million per linear meter (ppm &times, m) were not normally distributed and, thus, they were log-transformed to reach normality. Repeatability and reproducibility were calculated as the relative standard deviation of five measurements within the same day and 15 measurements across three days, respectively. All phenotypes showed higher repeatability and reproducibility for log-transformed data compared with data expressed as ppm &times, m. The linear equation modelling the aggregate function highlighted a very high coefficient of determination (&ge, 0.99), which suggests that daily CH4 emissions might be derived using this approach. The number of CH4 peaks resulted as particularly diverse across animals and therefore it is a potential candidate to discriminate between high and low emitting animals. Results of this study suggest that laser methane detector is a promising tool to measure bovine CH4 emissions in field conditions.

Serum metabolic profile is a common method to monitor health and nutritional status of dairy cows, but blood sampling and analysis are invasive, time-consuming, and expensive. Milk mid-infrared spectra have recently been used to develop prediction models for blood metabolites. The current study aimed to investigate factors affecting blood &beta, hydroxybutyrate (BHB), non-esterified fatty acids (NEFA), and urea nitrogen (BUN) predicted from a large milk mid-infrared spectra database. Data consisted of the first test-day record of early-lactation cows in multi-breed herds. Holstein-Friesian cows had the greatest concentration of blood BHB and NEFA, followed by Simmental and Brown Swiss. The greatest and the lowest concentrations of BUN were detected for Brown Swiss and Holstein-Friesian, respectively. The greatest BHB concentration was observed in the first two weeks of lactation for Brown Swiss and Holstein-Friesian. Across the first month of lactation, NEFA decreased and BUN increased for all considered breeds. The greatest concentrations of blood BHB and NEFA were recorded in spring and early summer, whereas BUN peaked in December. Environmental effects identified in the present study can be included as adjusting factors in within-breed estimation of genetic parameters for major blood metabolites.

High milk somatic cell count (SCC) influences milk production and quality; however, very little is known about the effect of low SCC on milk quality, especially in terms of mineral content and coagulation properties. Thus, the present study aimed to investigate the effects of somatic cell score (SCS), calculated as log2(SCC/100) + 3, on milk yield, composition (fat, crude protein, casein, lactose, milk urea nitrogen, protein fractions, and mineral contents), and coagulation properties of Brown Swiss, Holstein Friesian, and Simmental cows from multibreed herds. Milk composition and coagulation traits were predicted using mid-infrared spectroscopy. The data set comprised 95,591 observations of 6,940 cows in 313 multibreed herds, collected from January 2011 to December 2017. Observations were divided into 8 classes based on SCS. Statistical analysis was performed using a linear mixed model, which included breed, parity, stage of lactation, SCS class, and their interactions as fixed effects, and herd test day, cow, and residual as random effects. The probability that cows experienced SCS > 4.00 at 30 ± 5, 60 ± 5, or 90 ± 5 d after the observation test day was calculated for each SCS class, and odds ratios to the reference class (-1.00 4.00). Moreover, cows with SCS lower than -1.00 on a test day were about 7 times more likely to present high SCS within the following 90 ± 5 d than cows with SCS between -1.00 and 0.00. Breeds responded similarly to the increase of SCS, but the overall loss of fat and crude protein yields, and several minerals among Holstein Friesian were lower with increasing SCS. The best milk yield and quality were observed between SCS 0.00 and 1.00, but milk quality of Holstein Friesians started to decrease at lower SCS compared with milk quality of Brown Swiss and Simmental cows. Results suggest a breed-dependent optimum of SCS, and highlighted that very low SCS can be an indicator of udder health problems and, thus, may be used for early detection of mastitis.

At the beginning of lactation, high-producing cows commonly experience an unbalanced energy status that is often responsible for the onset of metabolic disorders and impaired health and performance. Blood β-hydroxybutyrate (BHB) and nonesterified fatty acids (NEFA) are indicators of excessive fat mobilization and circulating ketone bodies. Recently, prediction models based on mid-infrared (MIR) spectroscopy have been developed to assess blood BHB and NEFA from routinely collected individual milk samples. This study aimed to estimate genetic parameters of blood BHB and NEFA predicted from milk MIR spectra and to assess their phenotypic and genetic correlations with milk production and composition traits in early-lactation Holstein cows. The data set comprised the first test-day record within lactation and spectra of individual milk samples (n = 22,718) of 13,106 Holstein cows collected from 5 to 35 d in milk (DIM). Blood BHB and NEFA were predicted from milk MIR spectra using previously developed prediction models. Genetic parameters of blood metabolites and milk traits were estimated for the whole observational period (5-35 DIM) and within 6 classes of DIM. Blood BHB and NEFA showed similar genetic variation across DIM, with the highest heritability in the first 10 d after calving (0.31 ± 0.06 and 0.19 ± 0.05 for BHB and NEFA, respectively). The genetic correlation between BHB and NEFA was moderate (0.51 ± 0.05). Genetic correlations of BHB with milk yield, SCS, protein percentage, lactose percentage, and urea nitrogen content were similar to, or at least in the same direction as, the correlations of NEFA with the same traits, whereas opposite correlations were observed with fat percentage and fat-to-protein ratio. Results of the current study suggest that blood BHB and NEFA predicted from milk MIR spectra have genetic variation that is potentially exploitable for breeding purposes. Therefore, they could be used as indicator traits of hyperketonemia in a selection index aimed to reduce the susceptibility of dairy cows to metabolic disorders in early lactation.

The aim of this study was to describe the fecal bacteria and archaea composition of Holstein-Friesian and Simmental heifers and lactating cows, using 16S rRNA gene sequencing. Bacteria and archaea communities were characterized and compared between heifers and cows of the same breed. Two breeds from different farms were considered, just to speculate about the conservation of the microbiome differences between cows and heifers that undergo different management conditions. The two breeds were from two different herds. Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria were the most abundant phyla in all experimental groups. Alpha- and beta-diversity metrics showed significant differences between heifers and cows within the same breed, supported by principal coordinate analysis. The analysis of Holstein-Friesian fecal microbiome composition revealed 3 different bacteria families, 2 genera, and 2 species that differed between heifers and cows; on the other hand, Simmental heifers and cows differed only for one bacteria family, one archaeal genus, and one bacteria species. Results of the present study suggest that fecal communities of heifers and cows are different, and that fecal microbiome is maintained across experimental groups.

The aim of the present study was to investigate sources of variation of milk composition and technological characteristics routinely collected in field conditions in the Italian dairy industry. A total of 40,896 bulk milk records from 620 herds and 10 regions across Italy were analyzed. Composition traits were fat, protein, and casein percentages, urea content, and somatic cell score; and technological characteristics were rennet coagulation time, curd firming time, curd firmness 30 min after rennet addition to milk, and titratable acidity. Data of herd bulk milks were analyzed using a model that included fixed effects of region, herd nested within region, and season of milk analysis. An average good milk quality was reported in the dairy industry (especially concerning fat, protein, and casein percentages), and moderate to high correlations between composition and technological traits were observed. All factors included in the statistical model were significant in explaining the variation of the studied traits except for region effect in the analysis of casein and somatic cell score. Northeast and central-southern Italian regions showed the best performance for composition and technological features, respectively. Traits varied greatly across regions, which could reflect differences in herd management and strategies. Overall, less suitable milk for dairy processing was observed in summer. Results of the present study suggested that a constant monitoring of technological traits in the dairy industry is necessary to improve production quality at herd level and it may be a way to segregate milk according to its processing characteristics.

The aim of this study was to investigate the sources of variation of milk fatty acids (FA) routinely predicted by mid-infrared spectroscopy in Holstein-Friesian (HF), Brown Swiss (BS), Simmental (SI) and Alpine Grey (AG) cattle breeds. A linear mixed model was used to analyse the data which included 153,801 individual milk samples from 14,301 cows. Fixed effects included in the model were breed, month of sampling, year of sampling, stage of lactation, parity and first order interactions between them, and random effects were herd nested within breed, cow nested within breed and the residual error. Milk of AG cows exhibited the lowest content of saturated FA and the greatest content of unsaturated FA, whereas milk of BS had an opposite pattern. Holstein-Friesian and SI were intermediate between AG and BS breeds for all the FA except for total C18:1, which was the greatest in HF. Saturated FA, C14:0 and C16:0 increased from calving until 120 days in milk, whereas unsaturated FA and C18:1 decreased. First parity cows produced milk with lower concentration of de novo FA than multiparous animals. The greatest content of unsaturated FA and C18:1 was observed in summer, whereas saturated FA, C14:0, C16:0 and C18:0 decreased in summer and increased in winter. The differences in milk FA profile among breeds are useful for genetic selection and for feeding strategies.

Dairy cows commonly experience an unbalanced energy status in early lactation, and this condition can lead to the onset of several metabolic disorders. Blood metabolic profile testing is a valid tool to monitor and detect the most common early lactation disorders, but blood sampling and analysis are time-consuming and expensive, and the procedure is invasive and stressful for the cows. Mid-infrared (MIR) spectroscopy is routinely used to analyze milk composition, being a cost-effective and nondestructive method. The present study aimed to assess the feasibility of using routine milk MIR spectra for the prediction of main blood metabolites in dairy cows, and to investigate associations between measured blood metabolites and milk traits. Twenty herds of Holstein Friesian, Brown Swiss, or Simmental cows located in Northeast Italy were visited 1 to 4 times between December 2017 and June 2018, and blood and milk samples were collected from all lactating cows within 35 d in milk. Concentrations of main blood metabolites and milk MIR spectra were recorded from 295 blood and milk samples and used to develop prediction models for blood metabolic traits through backward interval partial least squares analysis. Blood β-hydroxybutyrate (BHB), urea, and nonesterified fatty acids were the most predictable traits, with coefficients of determination of 0.63, 0.58, and 0.52, respectively. On the contrary, predictive performance for blood glucose, triglycerides, cholesterol, glutamic oxaloacetic transaminase, and glutamic pyruvic transaminase were not accurate. Associations of blood BHB and urea with their respective contents in milk were moderate to strong, whereas all other correlations were weak. Predicted blood BHB showed an improved performance in detecting cows with hyperketonemia (blood BHB ≥ 1.2 mmol/L), compared with commercial calibration equation for milk BHB. Results highlighted the opportunity of using milk MIR spectra to predict blood metabolites and thus to collect routine information on the metabolic status of early-lactation cows at a population level.

This study aimed to investigate factors affecting protein fractions, namely &alpha, casein (&alpha, CN), &beta, casein (&beta, CN), &kappa, casein (&kappa, lactoglobulin (&beta, LG) and &alpha, lactalbumin (&alpha, LA) predicted from milk infrared spectra in milk of dairy and dual-purpose cattle breeds. The dataset comprised 735,328 observations from 49,049 cows in 1782 herds. Results highlighted significant differences of protein fractions in milk of the studied breeds. Significant variations of protein fractions were found also through parities and lactation, with the latter thoroughly influencing protein fractions percentage. Interesting correlations (r) were estimated between &beta, CN, &kappa, CN and &beta, LG, expressed as percentage of crude protein, and milk urea nitrogen (r = 0.31, &minus, 0.20 and &minus, 0.26, respectively) and between &alpha, LA and fat percentage (r = 0.41). The present study paves the way for future studies on the associations between protein fractions and milk technological properties, and for the estimation of genetic parameters of predicted protein composition.

The aim of the present study was to assess the relationships of lactose percentage (LP), lactose yield (LY), and freezing point (FRP) with minerals and coagulation properties predicted from mid-infrared spectra in bovine milk. To achieve this purpose, we analyzed 54,263 test-day records of 4,297 Holstein cows to compute (co)variance components with a linear repeatability animal model. Parity, stage of lactation, season of calving, and herd-test-date were included as fixed effects in the model, and additive genetic animal, within- and across-lactation permanent environment, and residual were included as random effects. Lactose percentage was more heritable (0.405 ± 0.027) than LY (0.121 ± 0.021) and FRP (0.132 ± 0.014). Heritabilities (± standard error) of predicted milk minerals varied from 0.375 ± 0.027 for Na to 0.531 ± 0.028 for P, and those of milk coagulation properties ranged from 0.348 ± 0.052 for rennet coagulation time to 0.430 ± 0.026 for curd firming time. Lactose percentage showed favorable (negative) genetic correlations with milk somatic cell score (SCS) and FRP, and it was almost uncorrelated with casein-related minerals (Ca and P) and coagulation properties. Moreover, LP was strongly correlated with Na (-0.783 ± 0.022), a mineral known to increase in the presence of intramammary infection (IMI) and high somatic cell count. Indeed, Na is the main osmotic replacer of lactose in mastitic milk when the blood-milk barrier is altered during IMI. Being strongly associated with milk yield, LY did not favorably correlate with coagulation properties, likely because of the negative correlation of this trait with protein and casein percentages. Milk FRP presented moderate and null genetic associations with Na and SCS, respectively. Results of the present study suggest that the moderate heritability of LP and its genetic correlations with IMI-related traits (Na and SCS) could be exploited for genetic selection against mastitis. Moreover, selection for LP would not impair milk coagulation characteristics or Ca and P content, which are important for cheesemaking.

The objective of the present study was to estimate the effect of breed on milk fatty acid (FA) composition of dairy (Brown Swiss, Holstein-Friesian, and Jersey) and dual-purpose cows (Simmental and Alpine Grey) in multi-breed herds. Information on individual milk samples was collected during routine cow milk testing between 2011 and 2014, and consisted of 285 606 observations from 17 445 cows in 617 herds. Fixed effects included in the mixed model were breed, parity, stage of lactation and the interaction between parity and stage of lactation, and random effects were cow, herd-test-date and residual. Contrast estimates for the studied traits were used to compare specific sets of breeds. Holstein-Friesian produced more milk than the other cattle breeds, with the greatest trans FA and C18:1 and the lowest C18:0 content. Comparison between the specialised dairy vs the dual-purpose breeds highlighted significant differences for all traits except for polyunsaturated FA and trans FA content. Specialised dairy breeds had greater milk saturated FA, short-chain FA, medium-chain FA, C14:0 and C16:0 content, and dual-purpose breeds produced milk with greater content of monounsaturated FA, long-chain FA, C18:0 and C18:1. Results demonstrated that, although specialised dairy produced more milk than dual-purpose breeds, milk FA profile of the latter was more favourable from a human nutrition point of view.

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

Lactose percentage (LP) in milk is currently determined in most herd-testing schemes, and globally, it is usually routinely recorded in the framework of the official milk recording procedures. However, few studies have investigated the phenotypic and genetic variability of this component. Data used in the present paper consisted of 59 811 test-day records from 4355 Holstein cows in 266 herds. Heritabilities of LP and lactose yield (LY) were estimated through single-trait repeatability animal models, whereas genetic and phenotypic correlations of LP and LY with milk composition and production traits, somatic cell score and milk freezing point were estimated using bivariate models. Fixed effects included in the analyses were herd-test-date, season of calving, parity, stage of lactation and the interaction between parity and stage of lactation. Random effects were animal additive genetic, within and across lactation permanent environment and the residual. Lactation curves of LP and LY increased from parturition to the peak of lactation and decreased thereafter, mirroring the typical curve of milk yield. Lactose percentage was greater in first- than later-parity cows. Heritabilities of LP and LY were 0.43 ± 0.03 and 0.14 ± 0.02, respectively, and LP and protein percentage were the most repeatable traits. Genetic correlations (ra) of LP with somatic cell score, LY and milk freezing point were −0.22 ± 0.08, 0.28 ± 0.08 and −0.46 ± 0.05, respectively. Genetic relationships of LY with milk yield (ra = 0.97 ± 0.00), fat percentage (ra = −0.71 ± 0.06), protein percentage (ra = −0.57 ± 0.06) and protein yield (ra = 0.64 ± 0.06) were moderate to strong. Results suggest that milk LP could be considered in breeding strategies to accelerate the gain of correlated low heritable traits. Further research is needed to evaluate the feasibility of including LP in the selection index of Italian Holstein population to address country-specific needs and market demands.

This study estimated the effect of Holstein‐Friesian, Brown Swiss, Jersey, Simmental and Alpine Grey cattle breeds on milk mineral contents (Ca, Mg, P, K, and Na) in multibreed herds using data predicted with mid‐infrared spectroscopy. The dataset included 139,821 observations from 16,566 cows and 977 herds. Fixed effects considered in the mixed model were breed, parity, stage of lactation and first‐order interactions, and random effects were cow, herd‐test‐date, and the residual. Multiple comparisons of least squares means were performed for the main effect of breed, parity, and stage of lactation using Bonferroni adjustment. Holstein‐Friesian yielded milk with the lowest fat, protein, and casein concentration, and Ca, Mg, and P contents, whereas Jersey cows produced milk with the greatest fat, protein, and casein concentration, and Ca and Mg contents. Results of this study suggest that mixing milk from different breeds could enhance milk composition and technological ability, and therefore contribute to improve dairy industry efficiency.

The aim of the present study was to characterize alternative somatic cell count (SCC) traits that could be exploited in genetic selection for mastitis resistance. Data were from 66,407 first-parity Holsteins in 404 herds. Novel SCC traits included average somatic cell score (SCS, log-transformation of SCC) in early lactation (SCS_150), standard deviation of SCS of the entire lactation (SCS_SD), the presence of at least one test-day (TD) SCC >400,000 cells/mL in the lactation, and the ratio of number of TD SCC >400,000 cells/mL to total number of TD in the lactation. Novel traits and lactation-mean SCS (SCS_LM) were analyzed using linear mixed or logistic regression models, including month of calving, year of calving, number of TD, and milk yield as fixed effects, and herd and residual as random terms. A multitrait linear animal model was applied to a random subset of 152 herds (n = 22,695 cows) to assess heritability of and genetic correlations between SCC traits. Alternative SCC traits were affected by the environmental factors included in the model; in particular, results suggested a seasonal effect and a tendency toward an improvement of the udder health status in the last years. Association was also found between novel SCC traits and milk production. Alternative SCC traits exhibited coefficients of additive genetic variation that were similar to or larger than that of traditional SCS_LM. Heritability of novel SCC traits was smaller than heritability of SCS_LM (0.126 ± 0.014), ranging from 0.044 ± 0.008 (SCS_SD) to 0.087 ± 0.010 (SCS_150). Genetic correlations between SCC traits ranged from 0.217 ± 0.096 (SCS_150 and SCS_SD) to 0.969 ± 0.010 (SCS_LM and SCS_150). Alternative SCC traits exhibited additive genetic variation that is potentially exploitable in breeding programs of Italian Holstein population to improve resistance to mastitis.

Population-level phenotyping is, for some traits, hardly achievable due to limitation of reference analyses. Mid-infrared spectroscopy (MIRS) is a quick and cost-effective laboratory technique allowing the prediction of innovative milk quality features on a large scale. The present study aimed at investigating factors associated with milk Ca, K, Mg, Na and P contents predicted by MIRS models on a large multi-breed spectral data set of 123,240 test-day records. Two dairy (Holstein–Friesian and Brown Swiss) and two dual-purpose (Simmental and Alpine Grey) cattle breeds were considered. Sources of variation of predicted milk mineral contents were studied using linear mixed models, including the fixed effects of breed, month of sampling, stage of lactation, parity and interactions between the main effects. Random factors were herd nested within breed, cow nested within breed and the residual. Calcium content was greater in milk of dual-purpose than dairy cattle breeds. Simmental cows produced milk with the greatest content of Ca and Na, and milk of Holstein-Friesian had the lowest P content. Variation of content of Ca, Mg, Na and P throughout lactations exhibited an opposite trend to that of milk yield, with the lowest values around the peak of lactation. On the other hand, K content mirrored the trend of milk yield. Multiparous cows had lower content of milk minerals, with the exception of Na, compared with first parity animals. Environmental factors identified in the present study can be considered for within-breed genetic evaluation to adjust records of milk mineral contents for these effects.

The aim of the present study was to determine the allele frequencies of the diacylglycerol acyltransferase (DGAT1) K232A mutation in Italian Holstein bulls and to estimate the effect of the mutation on milk yield, composition, somatic cell score, and coagulation traits (rennet coagulation time and curd firmness). For this purpose, 349 Italian Holstein bulls were genotyped for the DGAT1 mutation on chromosome 14. Association analysis was performed by regressing the number of copies for the K allele on the deregressed estimated breeding value of the individual. Breeding values were calculated using field data routinely collected in Northeast Italy. The frequencies of the AA, KA, and KK genotypes were 59.6, 32.1, and 8.3%, respectively, and the minor allele frequency (K variant) was 24.7%. The K allele was significantly associated with greater fat yield and fat, protein, and casein percentages and with reduced protein:fat ratio. The association between the DGAT1 mutation and somatic cell score was not significant, whereas a favorable association between presence of the K allele and milk coagulation properties was found. Results from the present study confirmed the effect of the diallelic DGAT1 polymorphism K232A on milk production traits and, for the first time, provided evidence that this mutation also affects milk coagulation properties in the Italian Holstein breed.

The objective of the present study was to investigate how the crossbreeding of Holstein (HO) cows with bulls from Nordic and Alpine European breeds affect milk quality traits, traditional milk coagulation properties (MCP), and curd firmness modeling obtained from individual milk samples. A total of 506 individual milk samples were collected from evening milking at 3 commercial farms located in Northern Italy. Over the past decade, the 3 farms have followed crossbreeding programs in part of their herds, whereas the remainder of the animals consisted of purebred HO. The basic scheme was a 3-breed rotation based on the use of Swedish Red (SR) semen on HO cows (SR × HO), the use of Montbéliarde (MO) semen on first-cross cows [MO × (SR × HO)], and the use of HO semen in the third cross. In all herds, a smaller proportion of purebred HO were mated to M and Brown Swiss (BS) bulls, and these first crosses were mated to SR and MO bulls, respectively. Milk samples were analyzed for milk composition and MCP, and parameters for curd firmness were modeled. Compared with purebred HO, crossbred cows produced less milk with lower lactose content, higher fat and protein content, and a tendency for higher casein content. Crossbred cows generally produced milk with a more favorable curd-firming rate (k₂₀) and curd firmness 30 min after rennet addition, among traditional MCP, and better trends of curd firmness measures as shown by model parameters: estimated rennet coagulation time, asymptotical potential value of curd firmness, and curd-firming instant rate constant. Among crossbred cows, SR × HO presented longer rennet coagulation time compared with MO × HO and BS × HO cows, and MO × HO showed shorter k₂₀ compared with BS × HO cows. Among second-generation cows, those sired by SR bulls showed a lower incidence of noncoagulated samples, higher curd firmness 30 min after rennet addition and asymptotical potential value of curd firmness, and faster curd-firming instant rate constant compared with animals sired by MO bulls. Our results revealed that different sire breeds were characterized by specific technological aptitudes, but that these were not strictly related to other milk quality traits. Furthermore, the favorable characteristics (in terms of the quality and technological properties of milk) could be maintained in the third generation of 3-way crosses without negative effects on milk yield, even though the HO heritage had been reduced from 50 to 25%. Our findings, therefore, suggest that different types of sires can be chosen (depending on the intended use of the milk) to ensure the optimization of farm crossbreeding programs.

The aim of this study was to predict gross feed efficiency of Italian Holstein Friesian bulls selected for production, functional and type traits. A total of 12,238 bulls, from the April 2015 genetic evaluation, were used. Predicted daily gross feed efficiency (pFE) was obtained as ratio between milk yield (MY) and predicted dry matter intake (pDMI). Phenotypic trend for MY, predicted body weight (pBW) and pFE were calculated by the bull birth year. The results suggest that pFE can be successfully selected to increase profitability of dairy cattle using the current milk recording system. Direct measurements on DMI should be considered to confirm results of pFE obtained in the present study.

The aim of this work was to estimate the annual genetic response for milk yield (MY), milk components, somatic cell score (SCS), milk acidity and milk coagulation properties (MCP: rennet coagulation time, RCT; curd firmness 30 min after rennet addition, a 30 ) in Italian Holstein–Friesian (IHF) population under different selection indices and breeding objectives. Current selection index (PFT SI ) of IHF breed includes fat (FY) and protein (PY) yields, fat (F%) and protein (P%) percentages, and SCS. Annual genetic response (GR y ) for the aforementioned traits and correlated response for MCP, MY and milk acidity were estimated using selection index theory. Genetic parameters for all traits were assumed from different sources and validated for positive definite matrix. Alternative selection indices were simulated by adding MCP as direct (MCPd) or predicted (MCPp) traits to current selection index. Direct measures were assumed to be recorded in laboratory by computerized renneting meter, whereas predicted measures by mid-infrared spectroscopy (MIRS). Current breeding objective (PFT BO ) includes FY, PY, F%, P% and SCS with relative emphasis of 13.6, 61.0, 3.4, 5.1 and −16.9%, respectively. Six alternative breeding objectives were formulated according to the relative weight given to MCP: 5% (MCP 5% ), 12.5% (MCP 12.5% ), 25% (MCP 25% ), 50% (MCP 50% ), 75% (MCP 75% ) and 100% (MCP 100% ). Current selection index does not affect significantly MCP traits, whereas MCPp to improve MCP 12.5% resulted in a gain of about 0.10 genetic standard deviations per year for both RCT and a 30 , without losses in GR y for MY, FY and PY. The inclusion of MCP traits in the selection index of IHF is expected to increase casein to protein ratio and to decrease SCS.

The objectives of this study were to estimate genetic parameters for fertility of Brown Swiss cattle, considering reproductive measures in different parities as different traits, and to estimate relationships between production traits of first lactation and fertility of heifers and first-parity and second-parity cows. Reproductive indicators were interval from parturition to first service, interval from first service to conception, interval from parturition to conception, number of inseminations to conception, conception rate at first service, and nonreturn rate at 56 d after first service. Production traits were peak milk yield (pMY), lactation milk yield, and lactation length (LL). Data included 37,546 records on heifers, and 24,098 and 15,653 records on first- and second-parity cows, respectively. Cows were reared in 2,035 herds, calved from 1999 to 2007, and were progeny of 527 AI bulls. Gibbs sampling was implemented to obtain (co)variance components using both univariate and bivariate threshold and censored linear sire models. Estimates of heritability for reproductive traits in heifers (0.016 to 0.026) were lower than those in first-parity (0.017 to 0.142) and second-parity (0.026 to 0.115) cows. Genetic correlations for fertility in first- and second-parity cows were very high (>0.920), whereas those between heifers and lactating cows were moderate (0.348 to 0.709). The latter result indicates that fertility in heifers is a different trait than fertility in lactating cows, and hence it cannot be used as robust indicator of cow fertility. Heifer fertility was not related to production traits in first lactation (genetic correlations between -0.215 and 0.251). Peak milk yield exerted a moderate and unfavorable effect on the interval from parturition to first service (genetic correlations of 0.414 and 0.353 after first and second calving, respectively), and a low and unfavorable effect on other fertility traits (genetic correlations between -0.281 and 0.295). Infertility after first calving caused a strong elongation of the lactation, and LL was negatively correlated with fertility of cows after second calving, so that LL can itself be regarded as a measure of fertility. Lactation milk yield depends on both pMY and LL, and, as such, is a cause and consequence of (in)fertility.

The aim of this study was to estimate direct and maternal genetic parameters for age at sale (AS, d), BW (kg), price (PR, €/kg), and market value (MV, €/calf) of Brown Swiss male calves (Bos taurus) from first- (n = 6,719) and second- (n = 4,405) parity dams marketed at livestock auctions from 2003 to 2007, and destined for veal production. Market value was calculated as the product of PR and BW. Restricted maximum likelihood procedures incorporating multiple trait animal models were used to infer genetic parameters for AS, BW, and PR, whereas estimates for MV were from single trait models. Bivariate analyses treating performance of calves from first- and second-parity cows as different traits were also performed. Direct heritabilities for AS, BW, and cattle prices ranged from 0.046 to 0.090, 0.078 to 0.130, and 0.064 to 0.152, respectively, and the corresponding maternal heritabilities varied from 0.020 to 0.030, 0.036 to 0.079, and 0.020 to 0.045, respectively. Direct genetic correlations between the traits were generally moderate to high and negative, whereas direct-maternal relationships were moderate to low. Genetic correlation between the same trait recorded on calves from first- and second-parity dams was less than unity, but generally high and positive, suggesting that AS, BW, PR, and MV can be treated as the same traits across parities. As calf price is routinely collected at auctions and shows genetic variation, it can be genetically improved.

The aims of this study were 1) to investigate the potential application of near-infrared spectroscopy (NIRS) to predict intramuscular fat (IMF) and fatty acid (FA) composition of individual meat samples, 2) to estimate heritability of IMF and FA NIRS-based predictions, and 3) to assess the statistical relevance of the genetic background of such predictions by using the Bayes factor (BF) procedure. Young Piemontese bulls (n = 1,298) were raised and fattened on 124 farms, and slaughtered at the same commercial abattoir. Intramuscular fat content and FA composition were analyzed on a random subset of 148 samples of minced and homogenized longissimus thoracis muscle. Near-infrared spectroscopy spectra were collected on all samples (n = 1,298) in reflectance mode between 1,100 and 2,498 nm (every 2 nm) using fresh minced meat samples. Calibration models developed from the random subset of 148 samples were used to predict IMF and FA contents of the remaining 1,150 samples. Intramuscular fat content and FA predictions were analyzed under a Bayesian univariate animal linear models, and the statistical relevance of heritability estimates was assessed through BF; the model with polygenic additive effects was favored when BF > 1. In general, satisfactory results (R(2) > 0.60) were obtained for 6 out of the 8 major FA (C14:0, C:16:0, C16:1, C18:0, C18:1n-9 cis/trans, and C18:1n-11 trans), 6 out of the 19 minor FA (C10:0, C12:0, C17:0, C17:1, C18:2 cis-9,trans-11, and C20:2), and the total SFA, MUFA, and PUFA. Bayes factors between models with and without a genetic component provided values greater than 1 for IMF, C14:0, C16:0, C18:1n-9 cis/trans, C17:0, C17:1, C20:2, SFA, MUFA, and PUFA. The greatest BF was reached by C20:2 (BF >10), suggesting strong evidence of genetic determinism, whereas IMF, C18:1n-9 cis/trans, C17:0, C17:1, MUFA, and PUFA showed substantial evidence favoring the numerator model (3.16 < BF < 10). Point estimates of heritabilities for FA predicted by NIRS were low to moderate (0.07 to 0.21). Results support that NIRS is a useful technique to satisfactorily predict some FA of meat. The existence of an important genetic determinism affecting FA profile has been confirmed, suggesting that FA composition of meat can be genetically modified.

The aims of this study were 1) to investigate the potential application of near-infrared spectroscopy (NIRS) to predict beef quality (BQ) traits, 2) to assess genetic variations of BQ measures and their predictions obtained by NIRS, and 3) to infer the genetic relationship between measures of BQ and their predictions. Young Piedmontese bulls (n = 1,230) were raised and fattened on 124 farms and slaughtered at the same commercial abattoir. The BQ traits evaluated were shear force (SF, kg), cooking loss (CL, %), drip loss (DL, %), lightness (L*), redness (a*), yellowness (b*), saturation index (SI), and hue angle. Near-infrared spectra were collected using a Foss NIRSystems 5000 instrument over a spectral range of 1,100 to 2,498 nm every 2 nm, in reflectance mode. After editing, prediction models were developed on a calibration subset (n = 268) using partial least squares regressions, followed by application of these models to the validation subset (n = 940). Estimations of (co)variance for measures of BQ and NIRS-based predictions were obtained through a set of bivariate Bayesian analyses on the validation subset. Near-infrared predictions were satisfactory for measurements of L* (R(2) = 0.64), a* (R(2) = 0.68), hue angle (R(2) = 0.81), and saturation index (R(2) = 0.59), but not for b*, DL, CL, and SF. The loss of additive genetic variance of predicted vs. measured L*, a*, DL, CL, and SF was generally high and was similar to the loss of residual variance, being a function of the calibration parameter R(2). As a consequence, estimated heritabilities of measures and predictions of BQ were similar for traits with high calibration R(2) values. Genetic correlations between BQ measures and predictions were high for all color traits and DL, and were greater than the corresponding phenotypic correlations, whereas both the phenotypic and genetic correlations for SF and CL were nil. Results suggest that NIRS-based predictions for color features and DL may be used as indicator traits to improve meat quality of the Piedmontese breed.

The aim of this study was to investigate the relationship between age (Age; 24.2 ± 8.7 days) and BW (61.0 ± 8.2 kg) of Brown Swiss male calves (n = 6826) sold at auction between 2003 and 2007. Animals were progeny of 330 sires mated to 6826 heifers. Preliminary least-squares analysis showed that herd of origin and date of auction significantly influenced Age and BW, along with age of dam at calving and age of calf for BW. Single-trait animal models highlighted that both Age and BW were heritable (0.075 ± 0.016 and 0.153 ± 0.026, respectively); therefore, under these conditions, Age cannot be regarded as a managerial factor. When included as an explanatory variable, age of calf increased the heritability of BW by 5 or 9% depending on whether the effect was introduced as discrete factor or linear covariate, respectively. Bivariate analyses with or without the inclusion of age of calf in the model for BW provided estimates of heritability similar to those from single-trait analyses (0.079 ± 0.014 for Age, and 0.136 ± 0.021 to 0.192 ± 0.031 for BW). The re-ranking of sires for BW of their calves at auction was very limited comparing bivariate models, while it was more pronounced comparing the results from single-trait models, and from single-trait and bivariate models; this is due to the strong and negative genetic correlation (−0.926 ± 0.081) between Age and BW, which reflects the tendency of farmers to sell first the fast growing and then the slow growing calves. Hence, the inclusion of age of calf as an explanatory variable in single-trait models for BW leads to biases in the estimation of breeding values. On the contrary, combining Age and BW in bivariate analyses leads to unbiased results, suggesting that both traits can be used as good predictors of growth potential in calves.

The aim of the study was to infer (co)variance components for daily milk yield, fat and protein contents, and somatic cell score (SCS) in Burlina cattle (a local breed in northeast Italy). Data consisted of 13,576 monthly test-day records of 666 cows (parities 1 to 8) collected in 10 herds between 1999 and 2009. Repeatability animal models were implemented using Bayesian methods. Flat priors were assumed for systematic effects of herd test date, days in milk, and parity, as well as for permanent environmental, genetic, and residual effects. On average, Burlina cows produced 17.0 kg of milk per day, with 3.66 and 3.33 percent of fat and protein, respectively, and 358,000 cells per mL of milk. Marginal posterior medians (highest posterior density of 95percnt;) of heritability were 0.18 (0.09-0.28), 0.28 (0.21-0.36), 0.35 (0.25-0.49), and 0.05 (0.01-0.11) for milk yield, fat content, protein content, and SCS, respectively. Marginal posterior medians of genetic correlations between the traits were low and a 95 percent Bayesian confidence region included zero, with the exception of the genetic correlation between fat and protein contents. Despite the low number of animals in the population, results suggest that genetic variance for production and quality traits exists in Burlina cattle.

The aim of the study was to assess crossbreeding effects for 305-day milk, fat, and protein yield and calving interval (CI) in Irish dairy cows (parities 1 to 5) calving in the spring from 2002 to 2006. Data included 188,927 records for production traits and 157,117 records for CI. The proportion of genes from North American Holstein Friesian (HO), Friesian (FR), Jersey (JE) and Montbeliarde (MO) breeds, and coefficients of expected heterosis for HOxFR, HOxJE and HOxMO crosses were calculated from the breed composition of cows' parents. The model used to assess crossbreeding effects accounted for contemporary group, age at calving within parity, linear regression on gene proportions for FR, JE and MO, and linear regression on coefficients of expected heterosis for HOxFR, HOxJE and HOxMO, as fixed effects, and additive genetic, permanent environmental and residual as random. Breed effects for production traits were in favour of HO, while for CI were in favour of breeds other than HO. The highest heterosis estimates for production were for HOxJE, with first-generation crosses yielding 477 kg more milk, 25.3 kg more fat, and 17.4 kg more protein than the average of the parental breeds. The highest estimate for CI was for HOxMO, with first-generation crosses showing 10.2 days less CI than the average of the parental breeds. Results from this study indicate breed differences and specific heterosis effects for milk yield traits and fertility exist in Irish dairy population.

Article history: Received 16 October 2009 Received in revised form 22 February 2010 Accepted 22 February 2010 The effect of the environmental level of production (ENV) on the expression of heterosis for 305-day milk, fat, protein, and fat plus protein (FP) yields, lactation average somatic cell score (LSCS), and age at first calving (AFC) was investigated in first lactation Black and White dairy cows in the Netherlands, and officially enrolled in the Dutch herd-book. Holstein Friesian (HF), Dutch Friesian (DF), and first generation (F1) crosses obtained from the mating of HF sires and DF dams (HD) were involved in the study, and data from animals with a calving date between 1990 and 2000 were used. A total of 22,930 cows with production and AFC information distributed in 3549 herds and 11,055 cows with LSCS information distributed in 2071 herds, were available. Adjusted lactation yield of milk for each herd was obtained using a model that accounted for fixed effects of herd, year and month of calving, genotype, and AFC. The overall mean of all adjusted data was computed, and 3 ENV were defined on the basis of the overall mean ±0.5 standard deviations. Once ENV was defined, traits were analysed with a model that included fixed effects of ENV, herd nested within ENV, AFC (only production traits and LSCS), year and month of calving, genotype, and the interaction between ENV and genotype. Least squares means for the interaction effect were used to estimate heterosis and to evaluate its magnitude across ENV. Holstein Friesian achieved higher productions than DF. First generation crosses showed productions close to HF, especially in the low ENV. Estimates of heterosis for yield traits ranged from 2.4% (milk) in the high to 5.3% (fat) in the low ENV, and reduced with increasing ENV. Estimates for LSCS and AFC were low, with the exception of LSCS in the high ENV. Results suggest that the highest non-additive genetic effects for yield traits and LSCS were expressed in the most stressful ENV, i.e., the low one for production and the high one for LSCS. © 2010 Elsevier B.V. All rights reserved.

The aim of this study was to investigate the effect of different breeds and breed crosses on age (AC, d), BW (kg), price (PR, $/kg), and market value (MV, $/calf) of purebred and crossbred calves sold for veal and beef production. The Kovieh wholesale cattle organization (Bolzano, Italy) grouped calves from sev- eral dairy herds located in the Trentino-Sudtirol region in Italy and sold them by public auctions. Data on AC, BW, PR, and MV from 96,458 calves were recorded from January 2003 to December 2007 and consisted of 4 pure breeds (2 dairy, Brown Swiss (BS) and Holstein- Friesian (HF); and 2 dual-purpose, Simmental (SI) and Alpine Grey (AG)), and 8 crossbreds by crosses of Limousin (LI) and Belgian Blue (BB) with the 4 dam breeds. Least squares means for AC, BW, PR, and MV were calculated for breeds and breed crosses with a model that included fixed effects of herd of birth, age (except for AC), sex, and breed of the calf, year and season of auction, and interactions between the main effects. The coefficients of determination of the mod- els were 0.41, 0.51, 0.84, and 0.82 for AC, BW, PR, and MV, respectively. Sex, age, and breed were the most relevant sources of variation for BW (P < 0.001), whereas breed and sex were the most important sources of variation for AC, PR, and MV (P < 0.001). Also, PR and MV were significantly influenced (P < 0.01) by all the effects included in the model, except for sea- son × age interaction in the case of MV. Market value of male was greater (P < 0.001) than that of female calves, with the exception of BS (−$28.76/calf) and HF (−$20.70/calf) purebred males. Dual-purpose pure- bred calves presented greater (P < 0.001) PR and MV than dairy purebreds (MV of $426.97/calf and $307.96/ calf for SI and AG, and $256.24/calf and $275.65/calf for BS and HF, respectively). Calves from SI and AG dams had greater (P < 0.001) BW, PR, and MV than calves from BS and HF dams. Calves from SI cows had greater (P < 0.001) BW, PR, and MV than calves from AG cows. Crossbreeding with beef bulls increased (P < 0.001) BW, PR, and MV of calves from dairy and dual- purpose dams. Crossbreeding with BB bulls increased PR (+$2.58 ± 0.04/kg; P < 0.001) and MV (+$190.84 ± 3.62/calf; P < 0.001) of calves much more than LI. The use of beef bull semen on dairy herds resulted in an economic revenue from selling crossbred calves.

The economic values (EV) of production traits, rennet coagulation time (RCT, min), and curd firmness (a 30 , mm) were derived for Italian Holstein-Friesian dairy cattle, based on the Grana Padano cheese industry. Three different sets of EV for RCT and a 30 were estimated, assuming +2.5% (scenario 1), +5% (scenario 2), and +10% (scenario 3) increment in cheese yield due to the effect of milk coagulation properties (MCP). A model was developed to simulate the transformation of milk into Grana Padano cheese. The EV of RCT and a 30 were −€2.213, −€4.426, and −€8.852/min, and €0.877, €1.755, and €3.509/mm for scenarios 1, 2, and 3, respectively. Relative emphasis of traits in the breeding objectives of the Italian Holstein-Friesian dairy cattle population should account for the effect of MCP on cheese yield. Economic values for milk components and MCP were affected by changes of dairy products, whereas variations of feed prices did not influence EV of RCT and a 30 .

The aim of this study was to investigate the effect of pregnancy stage on milk yield, composition traits, and milk coagulation properties in Italian Holstein cattle. The data set included 25,729 records from 3,995 first-parity cows calving between August 2010 and August 2013 in 167 herds. The traits analyzed were milk yield (kg/d), fat (%), protein (%), casein (%), and lactose (%) contents, pH, somatic cell score, rennet coagulation time (min), and curd firmness (mm). To better understand the effect of gestation on the aforementioned traits, each record was assigned to one of the following classes of pregnancy stage: (1) nonpregnant, (2) pregnant from 1 to 120d, (3) pregnant from 121 to 210d, and (4) pregnant from 211 to 310d. Gestation stage significantly influenced all studied traits with the exception of somatic cell score. Milk production decreased and milk quality improved from the fourth month of pregnancy onward. For all traits, nonpregnant cows performed very similarly to cows in the first period of gestation. Rennet coagulation time and curd firmness were influenced by pregnancy stage, especially in the last weeks of gestation when milk had better coagulation characteristics; this information should be accounted for to adjust test-day records in genetic evaluation of milk coagulation properties.