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Little is known about the influence of dietary crude protein (CP) restriction and rumen-protected conjugated linoleic acid (rpCLA) supply on digestibility and metabolism of nutrients in dairy cows. This study investigated the effect of low dietary CP level combined with rpCLA supply on FA secretion into milk and excretion via feces in dairy cows. Twenty Friesian cows were involved in a 4 × 4 Latin square design over 3-week periods. Cows were fed 4 different rations based on 2 dietary CP levels (150 and 123 g/kg dry matter of CP), each one with or without the addition of a 80 g/d supplement of rpCLA. Feed, feces and milk samples were analyzed for their fatty acid content (FA) and data were used to calculate apparent FA transfer as the ratios between the daily FA secretion in milk, or excretion in feces, and intake. Dietary CP restriction had little influence on apparent FA transfer from the feed to the feces and the milk, but slightly increased the apparent transfer to the milk of 14:0iso (P = 0.031) and 15:0iso (P = 0.006), and tended to increase transfer of other branched FAs of microbial origin, i.e. 15:0anteiso (P = 0.06), 16:0iso (P = 0.06) and 17:0iso (P = 0.07). The rpCLA supply lowered the secretion/intake ratio of total FAs in the milk (P = 0.02), particularly those with the shortest chains and with even numbers of carbons, but had no effect on apparent transfer of branched and odd FAs of microbial origin. The rpCLA supply greatly reduced (P

As double-muscled Belgian Blue (BB) and Piemontese (PIEM) breeds are heavily selected for different objectives (the former mainly for muscularity, the latter for ease of calving), the aim of this study was to compare sexual dimorphism in 56 crossbred young bulls and heifers obtained from dairy cows mated to bulls of the two beef breeds. Young PIEM- and BB-sired bulls had similar fattening performances and beef traits, although the BB crossbreds were slightly more muscular. Otherwise, the BB-sired heifers exceeded the PIEM-sired heifers in growth rate (1.12 vs. 0.98kg/d), feed efficiency (0.129 vs. 0.121kg/kg DM), increases in muscle scores (1.45 vs. 0.98 SEUROP scores) and carcass yield (0.612 vs. 0.605), but not in fatness, retail cut proportions and meat quality traits. Sexual dimorphism is, therefore, less distinct in BB than in PIEM crossbreds. In conclusion, BB sires are to be preferred for "product quality", and PIEM sires for "process quality", on account of welfare and ethical issues.

International audience; Milk samples were taken one , from a total of 1,224 Brown Swiss cows from 83 herds, and 1,500 mL of raw full-fat milk from each cow was processed according to a laboratory-scale model-cheese-making procedure. A sensory panel was assembled and the members trained to evaluate the sensory profile of individual model cheeses. The protocol scorecard was composed of 7 main sensory descriptors related to smell intensity, flavor intensity, taste (salt and sour), and texture (elasticity, firmness, and moisture), and 40 sensory attributes describing smell and flavor profiles. Sensory data were analyzed using a mixed model that included random effects of herd, animal, and panelist, as well as fixed effects of dairy system, days in milk, parity, and order of cheese presentation, and covariates for cheese weight and fat:protein ratio. The sensory profile was not much affected by the dairy farming systems included in the trial, but it was affected by farm within dairy system: cheeses from traditional dairy farms had a greater wood/humus attribute of both smell and flavor than those from modern farm. Of the modern farms, cheeses from those using total mixed rations including silages had a more intense smell of sour milk and a firmer, less moist texture than those using total mixed rations without silages. Moreover, for all the sensory traits, we found less variance related to herd and animals than that related to the panelists and the residuals. Stage of lactation was found to be the most important, whereas parity was riot relevant. In particular, cheese smell intensity (and some related attributes) exhibited a quadratic trend with lower values in mid-lactation, whereas flavor and salt descriptors were more intense in the last period of lactation.

The genomic landscape in human B-cell lymphoma has revealed several somatic mutations and potentially relevant germline alterations affecting therapy and prognosis. Also, mutations originally described as somatic aberrations have been shown to confer cancer predisposition when occurring in the germline. The relevance of mutations in canine B-cell lymphoma is scarcely known and gene expression profiling has shown similar molecular signatures among different B-cell histotypes, suggesting other biological mechanisms underlining differences. Here, we present a highly accurate approach to identify single nucleotide variants (SNVs) in RNA-seq data obtained from 62 completely staged canine B-cell lymphomas and 11 normal B-cells used as controls. A customized variant discovery pipeline was applied and SNVs were found in tumors and differentiated for histotype. A number of known and not previously identified SNVs were significantly associated to MAPK signaling pathway, negative regulation of apoptotic process and cell death, B-cell activation, NF-kB and JAK-STAT signaling. Interestingly, no significant genetic fingerprints were found separating diffuse large B-cell lymphoma from indolent lymphomas suggesting that differences of genetic landscape are not the pivotal causative factor of indolent behavior. We also detected several variants in expressed regions of canine B-cell lymphoma and identified SNVs having a direct impact on genes. Using this brand-new approach the consequence of a gene variant is directly associated to expression. Further investigations are in progress to deeply elucidate the mechanisms by which altered genes pathways may drive lymphomagenesis and a higher number of cases is also demanded to confirm this evidence.

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

The fatty acid (FA) profile has a considerable impact on the nutritional and technological quality of milk and dairy products. The molecular mechanism underlying the regulation of fat metabolism in bovine mammary gland have been not completely elucidated. We conducted genome-wide association studies (GWAS) across 65 milk FAs and fat percentage in 1,152 Brown Swiss cows. In total, we identified 175 significant single nucleotide polymorphism (SNPs) spanning all chromosomes. Pathway analyses revealed that 12:0 was associated with the greatest number of overrepresented categories/pathways (e.g. mitogen-activated protein kinase (MAPK) activity and protein phosphorylation), suggesting that it might play an important biological role in controlling milk fat composition. An Associated Weight Matrix approach based on SNP co-associations predicted a network of 791 genes related to the milk FA profile, which were involved in several connected molecular pathways (e.g., MAPK, lipid metabolism and hormone signalling) and undetectable through standard GWAS. Analysis of transcription factors and their putative target genes within the network identified BACH2, E2F3 and KDM5A as key regulators of milk FA metabolism. These findings contribute to increasing knowledge of FA metabolism and mammary gland functionality in dairy cows and may be useful in developing targeted breeding practices to improve milk quality.

The aims of this study were to infer variance components and heritability for the direct component on embryo establishment and survival related traits and to compare different statistical models in terms of goodness-of-fit and predictive ability. Embryo establishment and survival (EES) was defined as the outcome of an AI event, its direct effect was represented as the effect of the service sire from which semen was taken. Indicators of EES were calving per service (CS) and non-return at 56 d after service (NR56). Insemination records from the Italian Brown Swiss population reared in the Alps were used. Data included 124,206 inseminations performed by 86 technicians on 28,873 cows in 1400 herds. Services were recorded from 1999 to 2008. Linear-sire, linear-animal, threshold-sire, and threshold-animal models were used to estimate (co)variance components for CS and NR56. Four levels of complexity within each model were tested, so that 16 different models were compared for each of the two fertility traits. Comparison was assessed on the basis of the goodness-of-fit and predictive ability. Paternal half-sibs groups were created as average outcome of the inseminations from a given service sire. Goodness-of-fit was evaluated by regressing the service sire estimated breeding value from each model to paternal half-sibs average CS or NR56. Predictive ability was assessed through sums of chi-squared and percentage of wrong predictions. Predictors were the respective service sire’s estimated breeding values constructed on a reduced (independent) training dataset, including years from 1999 to 2005, and predictands were the paternal half-sibs means for every bull in the remaining years (2006–2008). Prediction of EES was considered differently according to whether service sires had observations in the training dataset (prediction of proven bulls) or they had not (prediction of young bulls). Estimates of heritability ranged from 0.011 to 0.119 for CS, and from 0.005 to 0.054 for NR56. In general, threshold models explained a larger proportion of additive genetic variance than linear models, and animal models yielded higher heritabilities than sire models. Calving per service was much more predictable than NR56, but no significant differences were found among models. Although heritabilities were low, the prediction of future EES of a paternal half-sib group is feasible.

In this study, 2-dimensional gas chromatography (GC × GC) was used to obtain a detailed fatty acid (FA) profile of sheep milk and to evaluate the effects of a rumen-protected conjugated linoleic acid (rpCLA) supply, breed, days in milk (DIM), sampling period, and number of lambs suckling on the FA profile. Twenty-four ewes, from 3 autochthonous breeds of the Veneto Alps (Brogna, Foza, and Lamon), were housed in 6 pens (2 pens/breed), according to DIM (38 ± 23 d) and body weight (61 ± 13 kg). The ewes and their offspring of 3 pens (1 pen/breed) were fed ad libitum a total mixed ration (control), and the other animals received the same diet supplemented with 12 g/d per ewe, plus 4 g/d for each lamb older than 30 d, of an rpCLA mixture. The study lasted 63 d. Two composite milk samples for each ewe were prepared during the first and second months of the trial. The pooled milk samples were analyzed in duplicate for FA profile by 2-dimensional gas chromatography, which allowed us to obtain a detailed FA profile of sheep milk, with 170 different FA detected, including many that were present in small concentrations. The milk relative proportions of individual FA, groups of FA, or FA indices were analyzed by PROC MIXED of SAS (SAS Institute Inc., Cary, NC), considering diet, breed, DIM, and sampling period as sources of variation. The random effect of animal was used to test diet, breed, and DIM, whereas the effects of period were tested on the residual. Breed had a small influence on milk FA profile, mainly on branched- and odd-chain FA. Within breed, animal repeatability for the relative proportions of milk FA was notable for almost all monounsaturated FA and for saturated FA with 14 to 19 carbon atoms, except C16:0, and less so for polyunsaturated FA. The inclusion of rpCLA (CLA cis-9,trans-11 and CLA trans-10,cis-12) increased the presence of the same CLA isomers in the milk as well as that of CLA trans-9,trans-11, and decreased the proportions of de novo-synthesized short-chain FA. From a cluster analysis based on the matrix of correlation coefficients among all FA relative proportions, 3 main FA groups were observed: the first included mainly odd- or branched-chain saturated FA, C18:0, C16:0 and CLA trans-10,cis-12; the second included monounsaturated FA or polyunsaturated FA with 16 to 20 carbons, CLA cis-9,trans-11, and CLA trans-9,trans-11; and the third included short- to medium-chain saturated FA, polyunsaturated FA with 2 to 5 double bonds, and 3 CLA isomers not affected by rpCLA addition (CLA trans-11,cis-13, CLA cis-9,cis-11, and CLA cis-10,cis-12).

We examined the latent structure of 26 cheese related phenotypes in dairy cattle. Traits related to milk yield and quality (8 traits), milk protein fractions (8 traits), coagulation and curd firmness indicators (CF, 5 traits) and cheese-making phenotypes (cheese yields (%CY) and nutrient recoveries in the curd (REC), 5 traits) were analysed through multivariate factor analysis (MFA) using a varimax rotation. All phenotypes were measured in 1264 Brown Swiss cows. Ten mutual orthogonal, latent variables (factors; Fs) were obtained explaining 74% of the original variability. These Fs captured basic concepts of the cheese-making process. More precisely, the first 4 Fs, sorted by variance explained, were able to capture the underlying structure of the CY percentage (F1: %CY), the CF process with time (F2: CFt), the milk and solids yield (F3: Yield) and the presence of nitrogen (N) in the cheese (F4: Cheese N). Moreover, 4 Fs (F5: as1-β-CN, F7: κ-β-CN, F8: as2-CN and F9: as1-CN-Ph) were related to the basic milk caseins and 1 factor was associated with the α-LA whey protein (F10: α-LA). A factor describing udder health status (F6: Udder health), mainly loaded on lactose, other nitrogen compounds in the milk and SCS, was also obtained. Further, we inferred the effects of some potential sources of variation (e.g. stage of lactation and parity) including feeding and management systems. Stage of lactation had a significant effect for 7 of the 10 Fs, followed by parity of the cow (3 Fs), dairy system and feeding (3 Fs). Our work demonstrates the usefulness of MFA in reducing a large number of variables to a few latent factors with biological meaning and representing groups of traits that describe a complex process like cheese-making. Such an approach would be a valuable tool for studying the influence of different production environments and individual animal factors on protein composition and cheese-making related traits.

Blood serum proteins are significant indicators of animal health. Nevertheless, several factors should be considered to appropriately interpret their concentrations in blood. Therefore, the objectives of this study were (1) to assess the effect of herd productivity, breed, age and stage of lactation on serum proteins and (2) to investigate association between serum proteins and somatic cell count (SCC) in dairy cattle. Milk and blood samples were collected from 1508 cows of six different breeds (Holstein Friesian, Brown Swiss, Jersey, Simmental, Rendena and Alpine Grey) that were housed in 41 multi-breed herds. Milk samples were analyzed for composition and SCC, while blood samples were analyzed for serum proteins (i.e. total protein, albumin, globulin and albumin-to-globulin ratio (A : G)). Herds were classified as low or high production, according to the cow’s average daily milk energy yield adjusted for breed, days in milk (DIM) and parity. Data were analyzed using a linear mixed model that included the fixed effects of DIM, parity, SCS, breed, herd productivity and the random effect of the Herd-test date within productivity level. Cows in high producing herds (characterized also by greater use of concentrates in the diet) had greater serum albumin concentrations. Breed differences were reported for all traits, highlighting a possible genetic mechanism. The specialized breed Jersey and the two dual-purpose local breeds (Alpine Grey and Rendena) had the lowest globulin concentration and greatest A : G. Changes in serum proteins were observed through lactation. Total protein reached the highest concentration during the 4th month of lactation. Blood albumin increased with DIM following a quadratic pattern, while globulin decreased linearly. As a consequence, A : G increased linearly during lactation. Older cows had greater total protein and globulin concentrations, while albumin concentration seemed to be not particularly affected by age. A linear relationship between serum proteins and SCS was observed. High milk SCS was associated with greater total protein and globulin concentrations in blood. The rise in globulin concentration, together with a decrease in albumin concentrations, resulted in a decline in A : G as SCS of milk increased. In conclusion, such non-genetic factors must be considered to appropriately interpret serum proteins as potential animal welfare indicator and their evaluation represents an important first-step for future analysis based on the integration of metabolomics, genetic and genomic information for improving the robustness of dairy cows.

It is becoming common to complement genome-wide association studies (GWAS) with gene-set enrichment analysis to deepen the understanding of the biological pathways affecting quantitative traits. Our objective was to conduct a gene ontology and pathway-based analysis to identify possible biological mechanisms involved in the regulation of bovine milk technological traits: coagulation properties, curd firmness modeling, individual cheese yield (CY), and milk nutrient recovery into the curd (REC) or whey loss traits. Results from 2 previous GWAS studies using 1,011 cows genotyped for 50k single nucleotide polymorphisms were used. Overall, the phenotypes analyzed consisted of 3 traditional milk coagulation property measures [RCT: rennet coagulation time defined as the time (min) from addition of enzyme to the beginning of coagulation; k20: the interval (min) from RCT to the time at which a curd firmness of 20 mm is attained; a30: a measure of the extent of curd firmness (mm) 30 min after coagulant addition], 6 curd firmness modeling traits [RCTeq: RCT estimated through the CF equation (min); CFP: potential asymptotic curd firmness (mm); kCF: curd-firming rate constant (% × min−1); kSR: syneresis rate constant (% × min−1); CFmax: maximum curd firmness (mm); and tmax: time to CFmax (min)], 3 individual CY-related traits expressing the weight of fresh curd (%CYCURD), curd solids (%CYSOLIDS), and curd moisture (%CYWATER) as a percentage of weight of milk processed and 4 milk nutrient and energy recoveries in the curd (RECFAT, RECPROTEIN, RECSOLIDS, and RECENERGY calculated as the % ratio between the nutrient in curd and the corresponding nutrient in processed milk), milk pH, and protein percentage. Each trait was analyzed separately. In total, 13,269 annotated genes were used in the analysis. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway databases were queried for enrichment analyses. Overall, 21 Gene Ontology and 17 Kyoto Encyclopedia of Genes and Genomes categories were significantly associated (false discovery rate at 5%) with 7 traits (RCT, RCTeq, kCF, %CYSOLIDS, RECFAT, RECSOLIDS, and RECENERGY), with some being in common between traits. The significantly enriched categories included calcium signaling pathway, salivary secretion, metabolic pathways, carbohydrate digestion and absorption, the tight junction and the phosphatidylinositol pathways, as well as pathways related to the bovine mammary gland health status, and contained a total of 150 genes spanning all chromosomes but 9, 20, and 27. This study provided new insights into the regulation of bovine milk coagulation and cheese ability that were not captured by the GWAS.

Milk yield has a strong effect on fertility, but it may vary across different herds and individual cows. Therefore, the aim of this study was to assess the effects of breed and its interaction with level of milk production at the herd level (Herd-L) and at a cow-within-herd level (Cow-L) on fertility traits in dairy cattle. Data were gathered from Holstein (n = 17,688), Brown Swiss (n = 32,697), Simmental (n = 27,791), and Alpine Grey (n = 13,689) cows in northeastern Italy. The analysis was based on records from the first 3 lactations in the years 2011 to 2014. A mixed model was fitted to establish milk production levels of the various herds (Herd-L) and individual cows (Cow-L) using milk as a response variable. The interval fertility traits were interval from calving to first service, interval from first service to conception, and number of days open. The success traits were nonreturn rate at 56 d after first service, pregnancy rate at first service, and the number of inseminations. The interval from calving to first service, interval from first service to conception, and number of days open were analyzed using a Cox's proportional hazards model. The nonreturn rate at 56 d after first service, pregnancy rate at first service, and the number of inseminations were analyzed using logistic regression. There was a strong interaction between breed and productivity class at both Herd-L and Cow-L on all traits. The effects of herd and cow productivity differed from each other and differed among breeds. The dual-purpose Simmental and Alpine Grey breeds had better fertility than the specialized Holstein and Brown Swiss dairy cows; this difference is only partly attributable to different milk yields. Greater herd productivity can result in higher fertility in cows, whereas higher milk yield of individual cows within a herd results in lower fertility. These effects at both Herd-L and Cow-L are curvilinear and are stronger in dual-purpose breeds, which was more evident from low to intermediate milk yield levels than from central to high productivity classes. Disentangling the effects of milk productivity on fertility at Herd-L and Cow-L and taking the nonlinearity of response into account could lead to better modeling of populations within breed. It could also help with management—for example, in precision dairy farming of dairy and dual-purpose cattle. Moreover, assessing the fertility of various breeds and their different responses to herd and individual productivity levels could be useful in devising more profitable crossbreeding programs in different dairy systems.

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

The aim of this study was to perform genome-wide associations (GWAS) and gene-set enrichment analyses with protein composition and cheesemaking-related latent variables (factors; F) in a cohort of 1,011 Italian Brown Swiss cows. Factor analysis was applied to identify latent structures of 26 phenotypes related to bovine milk quantity and quality, protein fractions [αS1-, αS2-, β-, and κ-casein (CN), β-lactoglobulin, and α-lactalbumin (α-LA)], coagulation and curd firming at time t (CFt) measures, and cheese properties [cheese yield (%CY) and nutrients recovery in the curd] of individual cows. Ten orthogonal F were extracted, explaining 74% of the original variability. Factor 1%CY underlined the %CY characteristics, F2CFt was related to the CFt process parameters, F3Yield was considered as descriptor of milk and solids yield, whereas F4Cheese N underscored the presence of nitrogenous compounds (N) into the cheese. Four more F were related to the milk caseins (F5αS1-β-CN, F7β-κ-CN, F8αS2-CN, and F9αS1-CN-Ph) and 1 F was linked to the whey protein (F10α-LA); 1 F underlined the udder health status (F6Udder health). All cows were genotyped with the Illumina BovineSNP50 Bead Chip v.2 (Illumina Inc., San Diego, CA). Single marker regression GWAS were fitted. Gene-set enrichment analysis was run on GWAS results, using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway databases, to reveal ontologies or pathways associated with the F. All F but F3Yield showed significance in GWAS. Signals in 10 Bos taurus autosomes (BTA) were detected. High peaks on BTA6 (∼87 Mbp) were found for F6β-κ-CN, F5αS1-β-CN, and at the tail of BTA11 (∼104 Mbp) for F4Cheese N. Gene-set enrichment analyses showed significant results (false discovery rate at 5%) for F8αS2-CN, F1%CY, F4Cheese N, and F10α-LA. For F8αS2-CN, 33 Gene Ontology terms and 3 Kyoto Encyclopedia of Genes and Genomes categories were enriched, including terms related to ion transport and homeostasis, neuron function or part, and GnRH signaling pathway. Our results support the feasibility of factor analysis as a dimension reduction technique in genomic studies and evidenced a potential key role of αS2-CN in milk quality and composition.

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

We studied the genetics of cheese-related latent variables (factors; Fs) for application in dairy cattle breeding. In total, 26 traits, recorded in 1264 Brown Swiss cows, were analyzed through multivariate factor analysis (MFA). Traits analyzed were descriptors of milk quality and yield (including protein fractions) and measures of coagulation, curd firmness (CF), cheese yields (%CY) and nutrient recoveries in the curd (REC). A total of 10 Fs (mutual orthogonal with a varimax rotation) were obtained. To assess the practical use of the Fs into breeding, we inferred their genetic parameters using single and bivariate animal models under a Bayesian framework. Heritability estimates (intra-herd) varied between 0.11 and 0.72 (F3: Yield and F7: κ-β-CN, respectively). The Fs underlined basic characteristics of the cheese-making process, milk components and udder health, while retaining 74% of the original variability. The first two Fs were indicators of the CY percentage (F1: %CY) and the CF process (F2: CF t ), and presented similar heritability estimates: 0.268 and 0.295, respectively. The third factor was associated with the yield of milk and solids (F3: Yield) characterized by a low heritability (0.108) and the fourth with the cheese nitrogen (N) (F4: Cheese N) that conversely appeared to be characterized by a high heritability (0.618). Three Fs were associated with the proportion of the basic milk caseins on total milk protein (F5: as1-β-CN, F7: κ-β-CN, F8: as2-CN), also highly heritable (0.565, 0.723 and 0.397, respectively) and 1 factor with the phosphorylated form of the as1-CN (F9: as1-CN-Ph; 0.318). Moreover, 1 factor was linked to the whey protein α-LA (F10: α-LA; 0.147). An indicator factor of a cow's udder health (F6: Udder health) was also obtained and showed a moderate heritability (0.204). Although the Fs were phenotypically uncorrelated, considerable additive genetic correlations existed among them, with highest values observed between F10: α-LA and F6: Udder health (-0.67) as well as between F9: as1-CN-Ph and F3: Yield (-0.60). Our results show the usefulness of MFA in dairy cattle breeding. The ability to replace a large number of variables with a few latent indicators of the same biological meaning marks MFA as a valuable tool for developing breeding strategies to improve cow's cheese-related traits.

Cheese production and consumption are increasing in many countries worldwide. As a result, interest has increased in strategies for genetic selection of individuals for technological traits of milk related to cheese yield (CY) in dairy cattle breeding. However, little is known about the genetic background of a cow's ability to produce cheese. Recently, a relatively large panel (1,264 cows) of different measures of individual cow CY and milk nutrient and energy recoveries in the cheese (REC) became available. Genetic analyses showed considerable variation for CY and for aptitude to retain high proportions of fat, protein, and water in the coagulum. For the dairy industry, these characteristics are of major economic importance. Nevertheless, use of this knowledge in dairy breeding is hampered by high costs, intense labor requirement, and lack of appropriate technology. However, in the era of genomics, new possibilities are available for animal breeding and genetic improvement. For example, identification of genomic regions involved in cow CY might provide potential for marker-assisted selection. The objective of this study was to perform genome-wide association studies on different CY and REC measures. Milk and DNA samples from 1,152 Italian Brown Swiss cows were used. Three CY traits expressing the weight (wt) of fresh curd (%CYCURD), curd solids (%CYSOLIDS), and curd moisture (%CYWATER) as a percentage of weight of milk processed, and 4 REC (RECFAT, RECPROTEIN, RECSOLIDS, and RECENERGY, calculated as the % ratio between the nutrient in curd and the corresponding nutrient in processed milk) were analyzed. Animals were genotyped with the Illumina BovineSNP50 Bead Chip v.2. Single marker regressions were fitted using the GenABEL R package (genome-wide association using mixed model and regression-genomic control). In total, 103 significant associations (88 single nucleotide polymorphisms) were identified in 10 chromosomes (2, 6, 9, 11, 12, 14, 18, 19, 27, 28). For RECFAT and RECPROTEIN, high significance peaks were identified in Bos taurus autosome (BTA) 6 and BTA11, respectively. Marker ARS-BFGL-NGS-104610 (∼104.3 Mbp) was highly associated with RECPROTEIN and Hapmap52348-rs29024684 (∼87.4 Mbp), closely located to the casein genes on BTA6, with RECFAT. Genomic regions identified may enhance marker-assisted selection in bovine cheese breeding beyond the use of protein (casein) and fat contents, whereas new knowledge will help to unravel the genomic background of a cow's ability for cheese production.

SummaryGenome-wide association (GWA) studies play a key role in current genetics research, unravelling genomic regions linked to phenotypic traits of interest in multiple species. Nevertheless, the extent of linkage disequilibrium (LD) may provide confounding results when significant genetic markers span along several contiguous cM. In this study, we have adapted the composite interval mapping approach to the GWA framework (composite GWA), in order to evaluate the impact of including competing (possibly linked) genetic markers when testing for the additive allelic effect inherent to a given genetic marker. We tested model performance on simulated data sets under different scenarios (i.e., qualitative trait loci effects, LD between genetic markers and width of the genomic region involved in the analysis). Our results showed that the genomic region had a small impact on the number of competing single nucleotide polymorphisms (SNPs) as well as on the precision of the composite GWA analysis. A similar conclusion was derived from the preferable range of LD between the tested SNP and competing SNPs, although moderate-to-high LD seemed to attenuate the loss of statistical power. The composite GWA improved specificity and reduced the number of significant genetic markers. The composite GWA model contributes a novel point of view for GWA analyses where testing circumscribed to the genomic region flanking each SNP (delimited by the nearest competing SNPs) and conditioning on linked markers increases the precision to locate causal mutations, but possibly at the expense of power.

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

The aim of this study was to investigate associations between pathogen-specific cases of subclinical mastitis and milk yield, quality, protein composition, and cheese-making traits. Forty-one multibreed herds were selected for the study, and composite milk samples were collected from 1,508 cows belonging to 3 specialized dairy breeds (Holstein Friesian, Brown Swiss, and Jersey) and 3 dual-purpose breeds of Alpine origin (Simmental, Rendena, and Grey Alpine). Milk composition [i.e., fat, protein, casein, lactose, pH, urea, and somatic cell count (SCC)] was analyzed, and separation of protein fractions was performed by reversed-phase high performance liquid chromatography. Eleven coagulation traits were measured: 5 traditional milk coagulation properties [time from rennet addition to milk gelation (RCT, min), curd-firming rate as the time to a curd firmness (CF) of 20 mm (k20, min), and CF at 30, 45, and 60 min from rennet addition (a30, a45, and a60, mm)], and 6 new curd firming and syneresis traits [potential asymptotical CF at an infinite time (CFP, mm), curd-firming instant rate constant (kCF, % × min-1), curd syneresis instant rate constant (kSR, % × min-1), modeled RCT (RCTeq, min), maximum CF value (CFmax, mm), and time at CFmax (tmax, min)]. We also measured 3 cheese yield traits, expressing the weights of total fresh curd (%CYCURD), dry matter (%CYSOLIDS), and water (%CYWATER) in the curd as percentages of the weight of the processed milk, and 4 nutrient recovery traits (RECPROTEIN, RECFAT, RECSOLIDS, and RECENERGY), representing the percentage ratio between each nutrient in the curd and milk. Milk samples with SCC > 100,000 cells/mL were subjected to bacteriological examination. All samples were divided into 7 clusters of udder health (UH) status: healthy (cows with milk SCC < 100,000 cells/mL and uncultured); culture-negative samples with low, medium, or high SCC; and culture-positive samples divided into contagious, environmental, and opportunistic intramammary infection (IMI). Data were analyzed using a linear mixed model. Significant variations in the casein to protein ratio and lactose content were observed in all culture-positive samples and in culture-negative samples with medium to high SCC compared to normal milk. No differences were observed among contagious, environmental, and opportunistic pathogens, suggesting an effect of inflammation rather than infection. The greatest impairment in milk quantity and composition, clotting ability, and cheese production was observed in the 2 UH status groups with the highest milk SCC (i.e., contagious IMI and culture-negative samples with high SCC), revealing a discrepancy between the bacteriological results and inflammatory status, and thus confirming the importance of SCC as an indicator of udder health and milk quality.

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 investigate the association between 10 candidate genes and carcass weight and conformation, carcass daily gain, and meat quality (pH, color, cooking loss, drip loss and shear force) in 990 double-muscled Piemontese young bulls. Animals were genotyped at each of the following genes: growth hormone, growth hormone receptor, pro-opiomelanocortin, pro-opiomelanocortin class 1 homeobox 1, melanocortin-4 receptor, corticotrophin-releasing hormone, diacylglycerol O-acyltransferase-1, thyroglobulin, carboxypeptidase E and gamma-3 regulatory subunit of the AMP-activated protein kinase. All the investigated SNPs had additive effects which were relevant for at least one of the traits. Relevant associations between the investigated SNPs and carcass weight, carcass daily gain and carcass conformation were detected, whereas associations of SNPs with meat quality were moderate. Results confirmed some of previously reported associations, but diverged for others. Validation in other cattle breeds is required to use these SNPs in gene-assisted selection programs for enhancement of carcass traits and meat quality.

The aim of this study was to investigate 96 single-nucleotide polymorphisms (SNPs) from 54 candidate genes, and test the associations of the polymorphic SNPs with milk yield, composition, milk urea nitrogen (MUN) content and somatic cell score (SCS) in individual milk samples from Italian Brown Swiss cows. Milk and blood samples were collected from 1271 cows sampled once from 85 herds. Milk production, quality traits (i.e. protein, casein, fat and lactose percentages), MUN and SCS were measured for each milk sample. Genotyping was performed using a custom Illumina VeraCode GoldenGate approach. A Bayesian linear animal model that considered the effects of herd, days in milk, parity, SNP genotype and additive polygenic effect was used for the association analysis. Our results showed that 14 of the 51 polymorphic SNPs had relevant additive effects on at least one of the aforementioned traits. Polymorphisms in the glucocorticoid receptor DNA-binding factor 1 (GRLF1), prolactin receptor (PRLR) and chemokine ligand 2 (CCL2) were associated with milk yield; an SNP in the stearoyl-CoA desaturase (SCD-1) was related to fat content; SNPs in the caspase recruitment domain 15 protein (CARD15) and lipin 1 (LPIN1) affected the protein and casein contents; SNPs in growth hormone 1 (GH1), lactotransferrin (LTF) and SCD-1 were relevant for casein number; variants in beta casein (CSN2), GH1, GRLF1 and LTF affected lactose content; SNPs in beta-2 adrenergic receptor (ADRB2), serpin peptidase inhibitor (PI) and SCD-1 were associated with MUN; and SNPs in acetyl-CoA carboxylase alpha (ACACA) and signal transducer and activator of transcription 5A (STAT5A) were relevant in explaining the variation of SCS. Although further research is needed to validate these SNPs in other populations and breeds, the association between these markers and milk yield, composition, MUN and SCS could be exploited in gene-assisted selection programs for genetic improvement purposes.

The aim of the present study was to identify transcriptional modifications and regulatory networks accounting for physiological and metabolic responses to specific nutrients in the liver of young Belgian Blue × Holstein bulls using RNA-sequencing. A larger trial has been carried out in which animals were fed with different diets: 1] a conventional diet; 2] a low-protein/low-mineral diet (low-impact diet) and 3] a diet enriched in n-3 fatty acids (FAs), conjugated linoleic acid (CLA) and vitamin E (nutraceutical diet). The initial hypothesis was that the administration of low-impact and nutraceutical diets might influence the transcriptional profiles in bovine liver and the resultant nutrient fluxes, which are essential for optimal liver function and nutrient interconversion. Results showed that the nutraceutical diet significantly reduced subcutaneous fat covering in vivo and liver pH. Dietary treatments did not affect overall liver fat content, but significantly modified the liver profile of 33 FA traits (out of the total 89 identified by gas-chromatography). In bulls fed nutraceutical diet, the percentage of n-3 and CLA FAs increased around 2.5-fold compared with the other diets, whereas the ratio of n6/n3 decreased 2.5-fold. Liver transcriptomic analyses revealed a total of 198 differentially expressed genes (DEGs) when comparing low-impact, nutraceutical and conventional diets, with the nutraceutical diet showing the greatest effects on liver transcriptome. Functional analyses using ClueGo and Ingenuity Pathway Analysis evidenced that DEGs in bovine liver were variously involved in energy reserve metabolic process, glutathione metabolism, and carbohydrate and lipid metabolism. Modifications in feeding strategies affected key transcription factors regulating the expression of several genes involved in fatty acid metabolism, e.g. insulin-induced gene 1, insulin receptor substrate 2, and RAR-related orphan receptor C. This study provides noteworthy insights into the molecular changes occurring as a result of nutrient variation in diets (aimed at reducing the environmental impact and improving human health) and broadens our understanding of the relationship between nutrients variation and phenotypic effects.

Fourier-transform infrared (FTIR) spectra are used to predict the fat, protein, casein, and lactose contents of milk. These estimates are currently used to predict the individual estimated breeding values of animals. The objective of the present study was to estimate the genetic variation and heritabilities of the milk transmittance spectrum at each individual FTIR wave. Milk was sampled once per cow from a total of 1,064 Italian Brown Swiss cows from 30 herds, sired by 50 artificial insemination sires. The FTIR spectra of all samples were collected within 3 h of sampling from 25 mL of milk. The obtained spectral range comprised wavenumbers 5,000 to 930×cm(-1), corresponding to wavelengths 2.00 to 10.76 μm and frequencies from 149.9 to 27.9 THz, for a total of 1,056 waves. These were acquired using a MilkoScan FT120 FTIR interferometer (Foss Electric A/S, Hillerød, Denmark). Each spectral data point was treated as a single trait and analyzed using an animal model REML method. The results indicated that the transmittance of the bovine milk FTIR spectrum was heritable for most individual waves in the wavenumber interval from 5,000 to 930×cm(-1). Moreover, the transmittance of contiguous FTIR waves was much more highly correlated in terms of the average value and phenotypic variation, compared with genetic variation. In the present study, we characterized 5 regions of the FTIR spectrum that were relevant to the analysis of milk; 2 regions, one in the transition area between the short-wavelength infrared (SWIR) and mid-wavelength infrared (MWIR) divisions of the electromagnetic spectrum (SWIR-MWIR region) and another very short region in the MWIR division (MWIR-2 region), were characterized by very high phenotypic variability in the transmittance of individual milk samples within each wave. This was caused by the absorption peaks of water, which can mask the effects of other important milk components. These regions also showed high genetic variability in transmittance, and the heritability estimates of individual waves were generally very low (with some exceptions). The 3 other identified regions contained many transmittance peaks that represented important chemical bonds; these showed much lower phenotypic and genetic variability in terms of individual waves, but relatively higher and less variable heritability estimates. Among them, the SWIR region (near-infrared) showed a peculiar cyclic pattern of the heritability coefficients of transmittance, the MWIR-1 region was particularly important for the estimation of fat, and the MWIR-LWIR region (also known also as the "fingerprint region") had 3 areas of relatively high heritability. In summary, we found that the transmittance data from the FTIR spectra of milk have genetic variability that may prove useful for the direct genetic improvement of dairy species, rather than only through indirect phenotypic predictions of individual milk quality and technological traits.

The aim of this study was to propose the survival analysis technique as a statistical approach for the analysis of rennet coagulation time (RCT) able to make use of coagulating and noncoagulating (NC) milk information in order to estimate potential sources of variations that affects RCT. A total of 1,025 Italian Holstein-Friesian cows (HF; progeny of 54 sires) and 1,234 Brown Swiss cows (BS; progeny of 58 sires) reared in 34 and 38 herds, respectively, were milk-sampled once. Rennet coagulation time was analyzed with a semiparametric proportional hazard model (i.e., a Cox model), with the NC samples considered as censored records. Furthermore, a different censoring scenario, with a new end point at 18 min, was considered after the rearrangement of the time space originally used for the observation of RCT. The percentage of NC samples was almost 10% for HF and 3.5% for BS cows in in the 31 min set, whereas it increased to 44 and 24.9%, respectively, in the 18 min set. Estimated hazard ratios indicated that the most important factors affecting the coagulation process were herd, days in milk, casein number, and milk acidity (expressed in terms of titratable acidity) for both HF and BS, whereas the SCS was relevant only for BS. The survival model seems to be particularly suitable for this analysis, as it can properly account for censored and uncensored records and appropriately use all available information. Moreover, this methodology allows us to rearrange the time space used for the observation of RCT and to define alternative traits (i.e., RCT with an end point at 18 min). Our restriction of the time space and the increased percentage of censored records did not highlight any substantial differences in terms of the risk of coagulating with respect to the traditional 31 min testing time. Although further research is needed to investigate the effect of these sources of variation on cheese yield, our results indicate that casein number, acidity, and SCS may be used as indicator traits for enhancing the technological properties of bovine milk.

Aim of this study was to compare three methods for determining fatty acid (FA) profiles in ruminant feces by GC. The first method ( J ) was based on a mild acid–base treatment directly performed on the dry fecal samples, completing in one step hydrolysis, extraction and methylation of FA. The second method ( J EE ) was based on acid hydrolysis followed by an accelerated solvent extraction (ASE) of ether extract (EE) and by a mild acid–base catalyzed methylation of FA. The third method ( C EE ) was based on an acid hydrolysis followed by ASE of EE and by an acid catalyzed methylation of FA ( C EE ). The experimental design involved the fecal samples of 9 bulls fed a total mixed ration supplemented with 0, 8 or 80 g/d of rumen protected CLA (rpCLA; 3 bulls/dose). Feces collected from these bulls were analyzed, by GC, in triplicates by each method expressing FA contents as mg/g DM. The repeatability of FA and CLA measurements of each method was determined. For the content of CLA isomers, the methods presented heteroscedastic residual variances and, thus, were compared by linear regression. Within method, fecal contents of CLA were regressed against the rpCLA dose. The F -test was employed to test the significance of any slope that deviated from unity and any intercept that was different from zero. There were no differences among methods for the total amount of FA extracted, which averaged 24.55 mg/g DM. The J method was the most repeatable method for most single FA, and for the sums of SFA, MUFA and PUFA. The two EE-methods evidenced for C18:2 c 9, t 11 CLA and C18:2 t 10, c 12 CLA linear relationships with slopes and intercepts close to 1 and 0, respectively, whereas the relationships of J EE and C EE with J had slopes lower than unity. With increasing rpCLA dosage the EE-based methods provided lower increase of fecal contents of C18:2 c 9, t 11 CLA and of C18:2 t 10, c 12 CLA isomers and a higher C18:2 t 9, t 11 CLA content than J , probably as a result of a modification of cis-trans isomerism caused by acid hydrolysis and ASE. The J method should be preferred as it provides more repeatable measures of the fecal FA profiles and because it causes a lower shift in CLA isomer composition with respect to procedures based on acid hydrolysis and ASE.

The aim of the present work was to evaluate the prolonging of the lactodynamographs observation period from 30 to 90 min, and to model curd firmness as a function of time (CFt, mm) using a four-parameter asymptotic function. The model tested was: CF t = CF P × ( 1 − e − k CF × ( t - RCT ) ) × e − k SR × ( t - RCT ) , where RCT (min−1) is the rennet coagulation time, CFP (mm) is the potential asymptotical CF at an infinite time, kCF (min−1) the curd-firming rate constant, and kSR (min−1) the curd syneresis rate constant. The CFt model was applied to data from milk of 105 Brown Swiss cows. The model appears promising as the four novel parameters are less interdependent than are the traditional measures and it gives also an insight on the syneresis. The repeatability of parameters of the CFt equation, estimated using information obtained from 50 samples (two bulk milks × 5 consecutive days × 5 replicates each) gave better results than traditional parameters.

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 investigate the consequences of reducing the dietary crude protein content, with or without a supply of protected conjugated linoleic acid (CLA), on the milk fatty acid (FA) yield and recovery in 90d ripened cheese. Twenty mid-lactation Friesian dairy cows were reared for 4 periods of 3wk each in groups of 5, following a 4×4 Latin square design. Cows were fed 4 different rations, consisting of a combination of the 2 dietary crude protein levels [150 (CP15) or 123 (CP12) g of crude protein/kg of dry matter], with or without a conjugated linoleic acid supply (80g/d, providing 5.57 and 5.40g/d of C18:2 cis-9,trans-11 and C18:2 trans-10,cis-12, respectively). Milk yield was recorded. Twice in each period, milk samples were analyzed for protein, fat, and lactose content, and 10 L milk samples (pooled by group) were processed to produce 96 cheeses, which were ripened for 90d. Milk and cheese fat were analyzed for their FA profiles. Milk and cheese FA were expressed as daily yields and relative proportions, and nutrient recoveries were computed. Dietary crude protein reduction had small or no effects on the yield and relative presence of FA in milk and cheese, except for a small increase in mid-chain branched saturated fatty acids. The CLA supply strongly reduced the yield of various categories of FA, and had major effects on short-chain FA of de novo synthesis, leading to changes in the relative proportions of the various FA in milk and cheese. The addition of CLA tended to reduce uniformly the recovery of all milk constituents and of short-, medium-, and long-chain FA groups, but we observed large differences among individual FA with apparent recoveries ranging between 640 and 1,710g/kg. The highest recoveries were found for polyunsaturated long-chain FA, the lowest for saturated or monounsaturated short- or medium-chain FA. A notable rearrangement of these FA components, particularly the minor ones, took place during ripening.

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

Sheep milk is an important source of food, especially in Mediterranean countries, and is used in large part for cheese production. Milk technological traits are important for the sheep dairy industry, but research is lacking into the genetic variation of such traits. Therefore the aim of this study was to estimate the heritability of traditional milk coagulation properties and curd firmness modeled on time t (CFt) parameters, and their genetic relationships with test-day milk yield, composition (fat, protein, and casein content), and acidity in Sarda dairy sheep. Milk samples from 1,121 Sarda ewes from 23 flocks were analyzed for 5 traditional coagulation properties by lactodynamographic tests conducted for up to 60min: rennet coagulation time (min), curd-firming time (k20, min), and 3measures of curd firmness (a30, a45, and a60, mm). The 240 curd firmness observations (1 every 15 s) from each milk sample were recorded, and 4 parameters for each individual sample equation were estimated: rennet coagulation time estimated from the equation (RCTeq), the asymptotic potential curd firmness (CFP), the curd firming instant rate constant (kCF), and the syneresis instant rate constant (kSR). Two other derived traits were also calculated (CFmax, the maximum curd firmness value; and tmax, the attainment time). Multivariate analyses using Bayesian methodology were performed to estimate the genetic relationships of milk coagulation properties and CFt with the other traits; statistical inference was based on the marginal posterior distributions of the parameters of concern. The marginal posterior distribution of heritability estimates of milk yield (0.16±0.07) and composition (0.21±0.11 to 0.28±0.10) of Sarda ewes was similar to those often obtained for bovine species. The heritability of rennet coagulation time as a single point trait was also similar to that frequently obtained for cow milk (0.19±0.09), whereas the same trait calculated as an individual equation parameter exhibited larger genetic variation and a higher heritability estimate (0.32±0.11). The other curd firming and syneresis traits, whether as traditional single point observations or as individual equation parameters and derived traits, were characterized by heritability estimates lower than for coagulation time and for the corresponding bovine milk traits (0.06 to 0.14). Phenotypic and additive genetic correlations among the 11 technological traits contribute to describing the interdependencies and meanings of different traits. The additive genetic relationships of these technological traits with the single test-day milk yield and composition were variable and showed milk yield to have unfavorable effects on all measures of curd firmness (a30, a45, a60, CFP, and CFmax) and tmax, but favorable effects on both instant rate constants (kCF and kSR). Milk fat content had a positive effect on curd firmness traits, especially on those obtained from CFt equations, whereas the negative effects on both coagulation time traits were attributed to the milk protein and casein contents. Finally, in view of the estimated heritabilities and additive genetic correlations, enhancement of technological traits of sheep milk through selective breeding could be feasible in this population.

Regulatory variation at the ovine casein genes could have important effects on the composition and coagulation properties of milk. Herewith, we have partially resequenced the promoters and the 3′-UTR of the four casein genes in 25 Sarda sheep. Alignment of these sequences allowed us to identify a total of 29 SNPs. This level of polymorphism (one SNP every 250 bp) is remarkably high if compared with SNP densities estimated in human genic regions (approximately one SNP per bp). The 29 SNPs identified in our resequencing experiment, plus three previously reported SNPs mapping to the lactalbumin, alpha (LALBA) and β-lactoglobulin (BLG, also known as progestagen-associated endometrial protein, PAEP) genes, were genotyped with a multiplex TaqMan Open Array Real-Time PCR assay in 760 Sarda sheep with records for milk composition and coagulation properties. Association analysis revealed the existence of significant associations of CSN1S2 and CSN3 genotypes with milk protein and casein contents. Moreover, genotypes at CSN1S1 were significantly associated with rennet coagulation time, curd firming time and curd firmness, whereas CSN2 was associated with curd firming time. These results suggest that SNPs mapping to the promoters and 3′-UTRs of ovine casein genes may exert regulatory effects on gene expression and that they could be used for improving sheep milk quality and technological traits at the population level through marker assisted selection., This research was supported by a grant from the Fondazione di Sardegna (Sardinia Foundation).

In order to investigate the effects of dietary crude protein (CP) and lysine (Lys) content on some technological properties of green hams destined for Protected Designation of Origin (PDO) dry-cured ham, green hams visual appraisal scores, thickness, iodine number and fatty acid composition of subcutaneous fat, and ham weight losses during seasoning (SL) were assessed. The green hams were obtained from 233 pigs fed four diets containing 140 to 110 g/kg CP and 6.5 to 5.3 g/kg total Lys from 90 to 165 kg body weight. A reduction in dietary CP and Lys of up to 20% compared with conventional feeds led to a 15% increase in the thickness of the subcutaneous fat, a 5% decrease in linoleic and polyunsaturated fatty acids in subcutaneous fat and a 7% decrease in SL. A 20% reduction of CP and Lys in diets for finishing pigs has positive effects on the technological properties of green hams destined for PDO dry-cured ham production.

We investigated the potential of using multivariate factor analysis to extract metabolic information from data on the quantity and quality of milk produced under different management systems. We collected data from individual milk samples taken from 1,158 Brown Swiss cows farmed in 85 traditional or modern herds in Trento Province (Italy). Factor analysis was carried out on 47 individual fatty acids, milk yield, and 5 compositional milk traits (fat, protein, casein, and lactose contents, somatic cell score). According to a previous study on multivariate factor analysis, a variable was considered to be associated with a specific factor if the absolute value of its correlation with the factor was ≥0.60. The extracted factors were representative of the following 12 groups of fatty acids or functions: de novo fatty acids, branched fatty acid-milk yield, biohydrogenation, long-chain fatty acids, desaturation, short-chain fatty acids, milk protein and fat contents, odd fatty acids, conjugated linoleic acids, linoleic acid, udder health, and vaccelenic acid. Only 5 fatty acids showed small correlations with these groups. Factor analysis suggested the existence of differences in the metabolic pathways for de novo short- and medium-chain fatty acids and Δ9-desaturase products. An ANOVA of factor scores highlighted significant effects of the dairy farming system (traditional or modern), season, herd/date, parity, and days in milk. Factor behavior across levels of fixed factors was consistent with current knowledge. For example, compared with cows farmed in modern herds, those in traditional herds had higher scores for branched fatty acids, which were inversely associated with milk yield; primiparous cows had lower scores than older cows for de novo fatty acids, probably due to a larger contribution of lipids mobilized from body depots on milk fat yield. The statistical approach allowed us to reduce a large number of variables to a few latent factors with biological meaning and able to represent groups of fatty acids with a common origin and function. Multivariate factor analysis would therefore be a valuable tool for studying the influence of different production environments and individual animal factors on milk fatty acid composition, and for developing nutritional strategies able to manipulate the milk fatty acid profile according to consumer demand.

The aim of this study was to elucidate the relationships between various cheesemaking-related traits, namely the well-known traditional milk coagulation properties (MCP), the new curd firming and syneresis traits, the cheese yield, and the curd nutrient recoveries or whey losses (all measured at the individual level). Data were obtained from 1,167 Brown Swiss cows reared in 85 herds. A 2-L milk sample was collected once from each animal and assessed for 10 phenotypes related to changes in curd firmness (CF) over time, plus 7 cheesemaking traits. The CF-related traits included 4 traditional single-point lactodynamographic properties [rennet coagulation time (RCT, min); time to a CF of 20mm, min; and the CF 30 and 45 min after rennet addition (a30 and a45, respectively)], 4 parameters used to model the 360 CF data recorded over time for each milk sample [the potential asymptotic CF at infinite time (CFP, mm); the CF instant rate constant, % × min(-1); the syneresis instant rate constant, % × min(-1); and the RCT obtained from modeling individual samples], and 2 traits calculated from individual equations [the maximum CF(CFmax, mm); and the time at CFmax, min]. The cheesemaking traits included 3 cheese yield traits (weights of the fresh curd, curd solids and curd moisture as percent of the weights of the processed milk) and 4 milk nutrient recoveries in the curd (calculated as the percent ratios between a given nutrient in the curd versus that in the processed milk). Bayesian methodology-based multivariate analyses were used to estimate the phenotypic, additive genetic, herd/date, and residual relationships between the aforementioned traits, whereas statistical inferences were based on the marginal posterior distributions of the parameters of concern. The a45, CFP, and CFmax traits were genetically associated with all of the percent cheese yield traits (the additive genetic correlations varied from 0.752 to 0.855 for a45; 0.496 to 0.583 for CFP; and 0.750 to 0.801 for CFmax) and the nutrient recovery traits (additive genetic correlations varied from 0.296 to 0.901 for a45; 0.428 to 0.697 for CFP; and 0.412 to 0.941 for CFmax). Moreover, the nutrient recoveries for fat, solids, and energy exhibited large additive genetic correlations with the other coagulation and curd firming traits. In particular, recovery of protein and fat were found to be powerful instruments for understanding the relationships between milk technological properties and cheese quantity or quality. We observed only weak genetic relationships with the milk quality and MCP traits, suggesting that the highly heritable trait of protein recovery should perhaps be included as a genetic index when seeking to improve cheesemaking efficiency at the population level. In contrast, we found that fat recovery exhibited moderate genetic variation and could be improved through the CF over time traits, especially using those recorded during the late phase of the curd firming process. Moreover, our results demonstrated that the traditional MCP have limited relevance for predicting individual cheese yield. Therefore, their use for this purpose in the dairy industry and breeding programs seems questionable.

Background Volatile organic compounds determine important quality traits in cheese. The aim of this work was to infer genetic parameters of the profile of volatile compounds in cheese as revealed by direct-injection mass spectrometry of the headspace gas from model cheeses that were produced from milk samples from individual cows. Methods A total of 1075 model cheeses were produced using raw whole-milk samples that were collected from individual Brown Swiss cows. Single spectrometry peaks and a combination of these peaks obtained by principal component analysis (PCA) were analysed. Using a Bayesian approach, we estimated genetic parameters for 240 individual spectrometry peaks and for the first ten principal components (PC) extracted from them. Results Our results show that there is some genetic variability in the volatile compound fingerprint of these model cheeses. Most peaks were characterized by a substantial heritability and for about one quarter of the peaks, heritability (up to 21.6%) was higher than that of the best PC. Intra-herd heritability of the PC ranged from 3.6 to 10.2% and was similar to heritabilities estimated for milk fat, specific fatty acids, somatic cell count and some coagulation parameters in the same population. We also calculated phenotypic correlations between PC (around zero as expected), the corresponding genetic correlations (from −0.79 to 0.86) and correlations between herds and sampling-processing dates (from −0.88 to 0.66), which confirmed that there is a relationship between cheese flavour and the dairy system in which cows are reared. Conclusions This work reveals the existence of a link between the cow’s genetic background and the profile of volatile compounds in cheese. Analysis of the relationships between the volatile organic compound (VOC) content and the sensory characteristics of cheese as perceived by the consumer, and of the genetic basis of these relationships could generate new knowledge that would open up the possibility of controlling and improving the sensory properties of cheese through genetic selection of cows. More detailed investigations are necessary to connect VOC with the sensory properties of cheese and gain a better understanding of the significance of these new phenotypes. Electronic supplementary material The online version of this article (doi:10.1186/s12711-016-0263-4) contains supplementary material, which is available to authorized users.

Association analyses between candidate genes and bovine milk fatty acids can improve our understanding of genetic variation in milk fatty acid profiles and reveal potential opportunities to tailor milk fat composition through selection strategies. In this work, we investigated the association of 51 single nucleotide polymorphisms (SNP) selected from 37 candidate genes using a functional and positional approach, with 47 fatty acids, 9 fatty acid groups, and 5 Δ(9)-desaturation indices in milk samples from Brown Swiss cows. Individual milk samples were collected from 1,158 Italian Brown Swiss cows, and gas chromatography was used to obtain detailed milk fatty acid compositions. A GoldenGate assay system (Illumina, San Diego, CA) was used to perform genotype 96 selected SNP located in 54 genes across 22 chromosomes. In total, 51 polymorphic SNP in 37 candidate genes were retained for the association analysis. A Bayesian linear animal model was used to estimate the contribution of each SNP. A total of 129 tests indicated relevant additive effects between a given SNP and a single fatty acid trait; 38 SNP belonging to 30 genes were relevant for a total of 57 fatty acid traits. Most of the studied fatty acid traits (~81%) were relevantly associated with multiple SNP. Relevantly associated SNP were mainly found in genes related to fat metabolism, linked to or contained in previously identified quantitative trait loci for fat yield or content, or associated with genes previously identified in association analyses with milk fatty acid profiles in other cow breeds. The most representative candidate genes were LEP, PRL, STAT5A, CCL3, ACACA, GHR, ADRB2, LPIN1, STAT1, FABP4, and CSN2. In particular, relevant associations with SNP located on bovine chromosome 19 (BTA19) were found. Two candidate genes on BTA19 (CCL3 and ACACA) were relevantly associated with de novo short- and medium-chain fatty acids, likely explaining the high heritability values found for these fatty acids (with the exception of C6:0). Two additional genes on BTA19 (CCL2 and GH1) showed associations with saturated and branched-chain fatty acids. Our findings provide basic information on genes and SNP affecting the milk fatty acid composition of dairy cows. These results may support the possibility of using genetic selection to modify milk fatty acid profiles to promote beneficial health-related effects.

The aim of this study was to characterize the profile of 47 fatty acids, including conjugated linoleic acid (CLA), 13 fatty acid groups, and 5 Δ 9 -desaturation indices in milk samples from Brown Swiss cows. The genetic variation was assessed and the statistical relevance of the genetic background for each trait was evaluated using the Bayes factor test. The additive genetic, herd-date, and residual relationships were also estimated among all single fatty acids and groups of fatty acids. Individual milk samples were collected from 1,158 Italian Brown Swiss cows and a detailed analysis of fat percentages and milk fatty acid compositions was performed by gas chromatography. Bayesian animal models were used for (co)variance components estimation. Exploitable genetic variation was observed for most of the de novo synthesized fatty acids and saturated fatty acids, except for C4:0 and C6:0, whereas long-chain fatty acids and unsaturated fatty acids (including CLA) were mainly influenced by herd-date effects. Herd-date effect explained large portions of the total phenotypic variance for C18:2 cis- 9, cis- 12 (0.668), C18:3 cis- 9, cis- 12, cis- 15 (0.631), and the biohydrogenation and elongation products of these fatty acids. The desaturation ratios showed higher heritability estimates than the individual fatty acids, except for CLA desaturation index (0.098). Among the medium-chain fatty acids, C12:0 had greater heritability than C14:0 (0.243 vs. 0.097, respectively). Both C14:0 and C16:0 showed negative additive genetic correlations with the main monounsaturated and polyunsaturated fatty acids of milk fat, suggesting that their synthesis in the mammary gland may be influenced by the presence of unsaturated fatty acids. No correlation was observed between C4:0 and the other short-chain fatty acids (except for C6:0), confirming the independence of C4:0 from de novo mammary fatty acid synthesis. Among the genetic correlations dealing with potentially beneficial fatty acids, C18:0 was positively correlated with vaccenic and rumenic acids and negatively with linoleic acid. Finally, fatty acids C6:0 through C14:0 showed relevant correlations due to unknown environmental effects, suggesting the potential existence of genetic variances in micro-environmental sensitivity. This study allowed us to acquire new knowledge about the genetic and the environmental relationships among fatty acids. Likewise, the existence of genetic variation for most of de novo synthetized fatty acids and saturated fatty acids was also observed. Overall, these results provide useful information to combine feeding with genetic selection strategies for obtaining a desirable milk fatty acids profile, depending on the origin of fatty acids in milk.

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.

Effects of diets differing in crude protein (CP) concentrations, top-dressed or not with 80 g/d of rumen-protected conjugated linoleic acid (rpCLA), on N efficiency of double muscled (DBM) Piemontese bulls were studied using four experimental diets being: high CP, HP; high CP plus rpCLA, HP rpCLA ; low CP, LP; low CP plus rpCLA, LP rpCLA . The HP diets (145 g/kg DM of CP) were similar those used commercially and the LP diets (108 g/kg DM of CP) were used to evaluate effects of lower dietary CP levels on intake, digestibility and body retention of nutrients, as well as N excretion. Forty-eight young bulls (237 ± 24.4 kg body weight (BW)), housed in 12 pens were fed one of the four experimental diets. Bulls were slaughtered at 668 ± 56.2 kg BW, after 332 days on their diet. Dry matter intake was measured daily on a pen basis and bulls were individually weighed monthly. Blood, rumen fluid and faecal samples were collected from each bull at 63, 179 and 283 days. Empty body composition at the start and the end of the feeding period was estimated using equations developed on DBM bulls and from the composition of the 5th rib collected at slaughter. Nitrogen balance was computed using a mass balance approach. Lowering of the diet CP level reduced both blood urea N (P

Summary Five single-nucleotide polymorphisms (SNPs) located in the calpain 1, (mu/I) large subunit (CAPN1), calpastatin (CAST), and cathepsin D (CTSD) genes were analyzed in a large sample of Piemontese cattle. The aim of this study was to evaluate allele and genotype frequencies of these SNPs and to investigate associations of CAPN1, CAST, and CTSD gene variants with meat quality traits. Minor allele frequencies ranged from 30 to 48%. The presence of the A allele at CAPN530 increased yellowness and drip loss. The CAST282 G allele was associated with an increased drip loss compared to the C allele, and the CAST2959 A allele decreased redness compared to the G allele.

The aim of this study was to investigate sources of variation of milk coagulation properties (MCP) of buffalo cows. Individual milk samples were collected from 200 animals in 5 herds located in northern Italy from January to March 2010. Rennet coagulation time (RCT, min) and curd firmness after 30min from rennet addition (a 30 , mm) were measured using the Formagraph instrument (Foss Electric, Hillerod, Denmark). In addition to MCP, information on milk yield, fat, protein, and casein contents, pH, and somatic cell count (SCC) was available. Sources of variation of RCT and a 30 were investigated using a linear model that included fixed effects of herd, days in milk (DIM), parity, fat content, casein content (only for a 30 ), and pH. The coefficient of determination was 51% for RCT and 48% for a 30 . The most important sources of variation of MCP were the herd and pH effects, followed by DIM and fat content for RCT, and casein content for a 30 . The relevance of acidity in explaining the variation of both RCT and a 30 , and of casein content in explaining that of a 30 , confirmed previous studies on dairy cows. Although future research is needed to investigate the effect of these sources of variation on cheese yield, findings from the present study suggest that casein content and acidity may be used as indicator traits to improve technological properties of buffalo milk.

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.

Associations of allelic variants of the β-lactoglobulin ( LGB ), stearoyl-coenzyme A desaturase 1 ( SCD ), and sterol regulatory element binding protein ( SREBP-1 ) genes with milk production, composition (fat, protein, and casein content), acidity (pH and titratable acidity), and coagulation properties (rennet coagulation time and curd firmness) were investigated in Brown Swiss cows. In total, 294 animals (progeny of 15 sires) reared in 16 herds were milk-sampled once. The additive effects of LGB (rs109625649:C>T), SCD (ss469414220:C>T), and SREBP-1 (AB355704: g.101_185ins) polymorphisms on the aforementioned traits were analyzed through Bayesian linear models. The LGB genotype affected rennet coagulation time, with TT (or BB) alleles showing longer rennet coagulation time compared with CC (or AA) cows. The SCD gene allelic variants were found to be associated with protein and casein contents and curd firmness: CC animals had the lowest values for the aforementioned traits. An association was found between SREBP-1 alleles and fat content, with the highest values for cows carrying the 84-bp insertion (or L) allele. Results suggest a possible use of these loci in gene-assisted selection programs for the improvement of milk quality traits and coagulation properties in Brown Swiss cattle.

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.

Aims of this study were to propose statistical models for the analysis of rennet coagulation time (RCT) suitable for making use of coagulating and noncoagulating (NC) milk information, to estimate heritabilities and to obtain rank correlations for sire merit. A total of 1,025 Holstein cows (progeny of 54 sires) reared in 34 herds were milk-sampled once. Data were analyzed using 4 alternative models: a standard linear (SLM), a right-censored linear Gaussian (CLM), a survival (SUM), and a threshold (THM) model. Model SLM analyzed coagulated milk records only, whereas analysis with CLM or SUM considered information of NC samples as censored records. Model THM analyzed occurrence of milk coagulation as a dichotomous trait. An artificial censoring scenario with an endpoint at 18 min (SET18) was considered after the rearrangement of the timeframe originally used for the observation of RCT (SET31). Heritabilities ranged from 0.12 to 0.25. Correlations of sire rankings ranged from 0.23 to 0.92. Differences in sire rankings between SLM and CLM or SUM increased when the proportion of NC records increased. Correlations between sire rankings obtained for SET31 and SET18 were high for CLM and SUM, indicating that rankings provided by these models tended to be stable even when a large fraction of samples with observed RCT was re-classified as NC milk. Results indicate that CLM and SUM are more suitable than SLM and THM for the analysis of coagulation ability when data contain NC milk information.

The aims of this study were to estimate genetic parameters of image analysis traits of cross-sectioned dry-cured hams and carcass weight (CW) and to investigate effects of some nongenetic sources of variation on these traits. Computer image analysis (CIA) had been carried out for digital images of the cross-section of 1,319 San Daniele dry-cured hams. The cross-sectional area (SA, cm(2)); the average thickness of subcutaneous fat (FT, cm); and the proportions of lean (LA, %), fat-eye (FEA, %), and subcutaneous fat area (SCF, %) to SA, and of biceps femoris (BFA, %) and semitendinosus muscle area (STA, %) to LA were recorded. Bivariate analyses were carried out for pairs of traits for estimation of genetic parameters using Bayesian methodology and linear models. Linear models included the nongenetic effects of slaughter groups and sex and the additive genetic effects of pigs and their ancestors (1,888 animals). Variation of FEA was nearly 4-fold that of SA and LA. Variation of CIA traits due to sex effect was not large, whereas slaughter group effects were relevant sources of variation for all traits. For all traits, with the exception of FEA, the posterior probability for the true heritability being greater than 0.1, was greater than 0.95. Point estimates of heritabilities for FT and SCF were 0.42 and 0.51, respectively. Heritability estimates for FEA, LA, BFA, and STA were 0.13, 0.44, 0.44, and 0.36, respectively. The genetic correlations between CW and CIA traits were positive and large for SA (0.86), positive and moderate for FT, FEA, and STA (0.47, 0.40, and 0.45, respectively) and negative with LA (-0.28). Although FEA, FT, and SCF were all measures of the extent of fat deposition in the ham, the genetic correlations between FT or SCF and FEA were very low. A very large estimate (0.74) was obtained for the genetic relationship between SA and FEA, suggesting that reduction of ham roundness through selective breeding would be beneficial for decreasing FEA. On the basis of the estimated parameters, genetic selection is expected to be effective in changing size of fatty and lean areas of the cross-section of dry-cured hams. Causes related to the abnormal development of the fat-eye depot remain unknown, but this study provided evidence that influences of polygenic effects on phenotypic variation of FEA are limited.