Environmental impact of Holstein Friesian and 3-breed crossbred dairy cows using a life cycle assessment approach applied to individual animals.

This study aimed to set up a life cycle assessment (LCA) approach at the level of individual animals to assess the effects of a 3-breed crossbreeding program on the environmental impact of cows. The study involved 564 cows, 279 purebred Holstein Friesian (HO) and 285 crossbred cows (CR), that originated from a 3-breed crossbreeding program based on the rotational use of Viking Red, Montebèliarde, and HO sires and kept in 2 dairy herds of northern Italy (224 and 340 cows/herd, respectively). The reference unit of the LCA model was the lifetime of cows, from the birth to culling or death. Data were collected at different levels: individual animal-based data referred to the whole life (birth, calving, dry, cull or death dates, and milk production); individual test-date collection of body measures and BCS, used to predict BW and to estimate energy requirements; common farm-based data concerning herd management (diets composition, and materials used). Data were used to compute DMI, milk and milk components production, gross income (GI), and income over feed costs (IOFC) pertaining to the lifespan of cows. An individual LCA-derived approach was set up to compute global warming potential (GWP), acidification and eutrophication potential (AP and EP, respectively), and land occupation (LO), which have been associated with different functional units (cow in her whole life or per day of life; kilograms of milk fat plus protein, and GI and IOFC [in euros] produced in the herd life). Data were analyzed using a generalized linear model including the fixed effects of genetic group (CR vs. HO), farm, and their interaction (genetic group × farm). Compared with HO, CR cows completed more lactations (+12%), had earlier first calving (-2 wk), yielded more fat plus protein in milk both in the lifespan (+8%) and per day of life (+4%). Concerning the environmental impact, when compared with HO herd mates, CR cows had nominal greater emissions per cow in the whole life, similar emissions per day of life and ∼3% lower GWP, AP, and EP per kilogram of fat plus protein yielded in lifespan. Income over feed costs per unit of emission tended to be ∼4% greater in CR compared with HO cows. Also, the use of land tended to be lower in CR compared with HO in most indicators considered. In conclusion, LCA could be adapted to represent individual animals. Moreover, managing dairy cows according to a 3-breed rotational crossbreeding scheme may be regarded as a strategy that can contribute to mitigate the emissions and to improve the environmental impact of dairy operations.

Review of equations to predict methane emissions in dairy cows from milk fatty acid profiles and their application to commercial dairy farms.

Greenhouse gas emission from the activities of all productive sectors is currently a topic of foremost importance. The major contributors in the livestock sector are ruminants, especially dairy cows. This study aimed to evaluate and compare 21 equations for predicting enteric methane emissions (EME) developed on the basis of milk traits and fatty acid profiles, which were selected from 46 retrieved through a literature review. We compiled a reference database of the detailed fatty acid profiles, determined by GC, of 992 lactating cows from 85 herds under 4 different dairy management systems. The cows were classified according to DIM, parity order, and dairy system. This database was the basis on which we estimated EME using the selected equations. The EME traits estimated were methane yield (20.63 ± 2.26 g/kg DMI, 7 equations), methane intensity (16.05 ± 2.76 g/kg of corrected milk, 4 equations), and daily methane production (385.4 ± 68.2 g/d, 10 equations). Methane production was also indirectly calculated by multiplying the daily corrected milk yield by the methane intensity (416.6 ± 134.7 g/d, 4 equations). We also tested for the effects of DIM, parity, and dairy system (as a correction factor) on the estimates. In general, we observed little consistency among the EME estimates obtained from the different equations, with exception of those obtained from meta-analyses of a range of data from different research centers. We found all the EME predictions to be highly affected by the sources of variation included in the statistical model: DIM significantly affected the results of 19 of the 21 equations, and parity order influenced the results of 13. Different patterns were observed for different equations with only some of them in accordance with expectations based on the cow's physiology. Finally, the best predictions of daily methane production were obtained when a measure of milk yield was included in the equation or when the estimate was indirectly calculated from daily milk yield and methane intensity.

Cull cow carcass traits and risk of culling of Holstein cows and 3-breed rotational crossbred cows from Viking Red, Montbéliarde, and Holstein bulls.

Culled dairy cows represent a considerable source of meat production, but their carcasses may vary greatly in quality because of the wide variation in the age, stage of lactation, breed, body condition, and other characteristics of the cows at slaughter. However, the effect of crossbreeding on the value of culled cows has so far received little investigation. The aim of this observational study was to compare a range of carcass attributes of cull cows from 3-breed rotational crossbreeding using Viking Red, Montbéliarde (MO), and Holstein (HO) bulls with those of HO purebred cows. Data on 1,814 dairy cows were collected. Cows were reared together in one herd and slaughtered in 4 slaughterhouses. The carcass weight, fleshiness, and fatness scores, the total value, and the price (€/kg) of each cow carcass were recorded. The culling of a few cows in the sample (n = 86) was classified by the farm manager as "urgent" following a diagnosis of injury or sickness, and this information was recorded. Carcass traits were analyzed with a mixed model which included the fixed effects of parity, days in milk, genetic group (purebred HO, 787 cows, and crossbred cows, classified according to the breed of sire within crossbreds, with 309, 428, and 290 cows sired by Viking Red, MO, and HO bulls, respectively), and interactions, and the random effects of month × year of the date of slaughter, and slaughterhouse. Logistic regression was used to investigate the association of parity, days in milk and purebred or crossbred origin with unplanned, "urgent" culling compared with regular culling. Average carcass weight across genetic groups was 297 ± 65 kg, average price €2.03 ± 0.53/kg, and average value €631 ± 269. Compared with HO, crossbred carcasses were 7 to 12% heavier depending on the breed of sire, were graded + 0.12 to + 0.28 units higher for fleshiness and + 0.26 to + 0.30 units higher for fatness, and fetched an 8 to 11% higher price. As a consequence, compared with purebred HO, carcasses from crossbreds had 15 to 24% higher value (€84 to €133 more per cow), with crossbred cows sired by MO showing the greatest values. Moreover, compared with the HO cows, the crossbred cows had a 37% lower risk of being urgently removed from the herd, which raises welfare concerns and may reduce the salvage value of cull cows. Because cull cows represent a supplemental source of income for dairy farmers, the greater overall value of crossbred cull cows should be taken into account in evaluating the economic effectiveness of crossbreeding schemes.

Association between days open and milk spectral data in dairy cows.

Data on 19,489 Brown Swiss cows reared in northeastern Italy were used to associate absorbances of individual wavenumbers within the mid-infrared range with days open (DO). Different postcalving days in milk (DIM) intervals were studied to determine the most informative milk sampling periods for predicting DO. Milk samples were analyzed using a MilkoScan (Foss Electric, Hillerød, Denmark) Fourier-transform infrared (FTIR) spectrometer for 1,060 wavenumbers (wn) ranging from 5,011 to 925 cm-1. To determine DO, we considered an insemination to lead to conception when there was no return of heat (i.e., no successive insemination) and the cow had a subsequent calving date whereby gestation length was required to be within ±30 d of 290 d. Only milk records within the first 90 DIM were considered. Associations were inferred by (1) fitting linear regression models between the DO and each individual wavenumber or milk component, and (2) fitting a Bayesian regression model that included the complete FTIR spectral data. The effects of including systematic effects (parity number, year-season, herd) in the model on these associations were also studied. These analyses were performed for the complete data (5-90 DIM) and for data stratified by DIM period (5 to 30, 31 to 60, and 61 to 90 DIM). Overall, regions of wavenumbers of the milk FTIR spectra that were associated with DO included wn 2,973 to 2,830 cm-1 [related to fat-B (C-H stretch)], wn 2,217 to 1,769 cm-1 [related to fat-A (C = O stretch)], wn 1,546 cm-1 (related to protein), wn 1,465 cm-1 (related to urea and fat), wn 1,399 to 1,245 cm-1 (related to acetone), and wn 1,110 cm-1 (related to lactose). Estimated effects depended on the DIM period, with milk samples drawn during DIM intervals 31 to 60 d and 61 to 90 d being most strongly associated with DO. These DIM intervals are also typically most associated with negative energy balance and peak lactation.

Genetic correlations between fertility traits and milk composition and fatty acids in Holstein-Friesian, Brown Swiss, and Simmental cattle using recursive models.

This study aimed to investigate the genetic and putative causal relationships between fertility traits [i.e., days open (DO) and calving rate (CR)] and milk quality, composition, and fatty acid contents (milk composition traits) in Holstein-Friesian, Brown Swiss, and Simmental cattle, using recursive models within a Bayesian framework. Trivariate animal models were run, each including one fertility trait, one milk composition trait, and, in all models, milk yield. The DO and CR data were merged with the test days closest to the insemination date for milk composition traits. After editing, 16,468 to 23,424 records for Holstein-Friesian, 23,424 to 46,660 for Brown Swiss, and 26,105 to 35,574 for Simmental were available for the analyses. Recursive animal models were applied to investigate the possible causal influences of milk composition traits on fertility and the genetic relationships among these traits. The results suggested a potential cause-and-effect relationship between milk composition traits and fertility traits, with the first trait influencing the latter. We also found greater recursive effects of milk composition traits on DO than on CR, the latter with some putative differences among breeds in terms of sensitivity. For instance, the putative causal effects of somatic cell score on CR (on the observed scale, %) varied from -0.96 to -1.39%, depending on the breed. Concerning fatty acids, we found relevant putative effects of C18:0 on CR, with estimates varying from -7.8 to -9.9%. Protein and casein percentages, and short-chain fatty acid showed larger recursive effects on CR, whereas fat, protein, and casein percentages, C16:0, C18:0, and long-chain fatty acid had larger effects on DO. The results obtained suggested that these milk traits could be considered as effective indicators of the effects of animal metabolic and physiological status on fertility.

Associations between differential somatic cell count and milk yield, quality, and technological characteristics in Holstein cows.

The aim of this study was to investigate the associations between differential somatic cell count (DSCC) and milk quality and udder health traits, and for the first time, between DSCC and milk coagulation properties and cheesemaking traits in a population of 1,264 Holstein cows reared in northern Italy. Differential somatic cell count represents the combined proportions of polymorphonuclear neutrophils plus lymphocytes (PMN-LYM) in the total somatic cell count (SCC), with macrophages (MAC) making up the remaining proportion. The milk traits investigated in this study were milk yield (MY), 8 traits related to milk composition and quality (fat, protein, casein, casein index, lactose, urea, pH, and milk conductivity), 9 milk coagulation traits [3 milk coagulation properties (MCP) and 6 curd firming (CF) traits], 7 cheesemaking traits, 3 cheese yield (CY) traits, and 4 milk nutrient recovery in the curd (REC) traits. A linear mixed model was fitted to explore the associations between SCS combined with DSCC and the aforementioned milk traits. An additional model was run, which included DSCC expressed as the PMN-LYM and MAC counts, obtained by multiplying the percentage of PMN-LYM and MAC by SCC in the milk for each cow in the data set. The unfavorable association between SCS and milk quality and technological traits was confirmed. Increased DSCC was instead associated with a linear increase in MY, casein index, and lactose proportion and a linear decrease in milk fat and milk conductivity. Accordingly, DSCC was favorably associated with all MCP and CF traits (with the exception of the time needed to achieve maximum, CF), particularly with rennet coagulation time, and it always displayed linear relationships. Differential somatic cell count was also positively associated with the recovery of milk nutrients in the curd (protein, fat, and energy), which increased linearly with increasing DSCC. The PMN-LYM count was rarely associated with milk traits, even though the pattern observed confirmed the results obtained when both SCS and DSCC were included in the model. The MAC count, however, showed the opposite pattern: MY, casein index, and lactose percentage decreased and milk conductivity increased with an increasing MAC count. No significant association was found between PMN-LYM count and MCP, CF, CY, and REC traits, whereas MAC count was unfavorably associated with MCP, CF traits, some CY traits, and all REC traits. Our results showed that the combined information derived from SCS and DSCC might be useful to monitor milk quality and cheesemaking-related traits.

Milk coagulation traits and cheese yields of purebred Holsteins and 4 generations of 3-breed rotational crossbred cows from Viking Red, Montbéliarde, and Holstein bulls.

Crossbreeding is a strategy to counter the declining fertility, resilience, and longevity of purebred Holstein (Ho) cows. However, little is known of the effects of long-term systematic rotational crossbreeding on milk technological properties and cheese yield (CY). In this study, we compared the individual milk composition, milk coagulation properties (MCP), and CY of 468 purebred Ho and 648 crossbred (CR) cows obtained from two 3-breed rotational crossbreeding systems using Viking Red (VR), Montbéliarde (Mo), and Ho sires over 4 generations. Individual milk samples were collected once from 1,116 primiparous and multiparous cows kept in 2 dairy herds, raised for the production of Grana Padano (high milk yield, total mixed ration based on corn silage) and Parmigiano Reggiano (moderate milk yield, only dry feeds) cheeses. In both herds, a 3-breed rotational mating system was used in which Ho cows were first inseminated with VR, whereas Mo and Ho semen was used in the subsequent generations. In one herd, the sequence Mo-VR-Ho was also used. Individual milk samples were analyzed for milk composition, single-point MCP, and parameters for modeling curd firming over time, whereas CY and milk nutrient recovery in the curd were assessed through a laboratory cheese-making procedure. Compared with Ho, CR cows produced 5.8% less milk, which had comparable fat but greater protein and casein contents and lower lactose contents and somatic cell scores. Milk from CR cows tended to reach a curd firmness of 20 mm more quickly and exhibited greater curd firmness at 45 and 60 min from rennet addition. Holstein and CR cows yielded milk with similar CY and recovery in the curd traits. The milk fat content, somatic cell scores, curd firmness traits, and CY of CR cows relative to the Ho cows differed in the 2 herds, and the favorable effects on the CR cows were more evident in the herd with the greatest milk yield and the worst MCP traits. Crossbred cows of the 4 generations performed similarly, with the exception of the better MCP of the milk from first-generation CR cows. The 2 rotational systems using different sire-breed sequences also performed similarly. In summary, both rotational crossbreeding programs exhibited some advantage over the Ho purebred breeding system in terms of milk composition and MCP but not CY. Future research is needed to investigate the interactions between crossbreeding schemes and dairy systems.

Genetic parameters for fertility traits assessed in herds divergent in milk energy output in Holstein-Friesian, Brown Swiss, and Simmental cattle.

In this study, we aimed to investigate differences in the genetics of fertility traits (heritability of traits and correlations between traits in divergent environments) in dairy cows of different production levels defined on the basis of the herd-average daily milk energy output (herd-dMEO). Data were obtained from Holstein-Friesian (n = 37,359 for fertility traits, 381,334 for dMEO), Brown Swiss (n = 79,638 for fertility traits, 665,697 for dMEO), and Simmental cows (n = 63,048 for fertility traits, 448,445 for dMEO) reared in northeastern Italy. Fertility traits under study were interval from calving to first service, interval from first service to conception, days open, calving interval, calving rate, and nonreturn rate at d 56. We classified herds into low and high productivity based on the herd-average dMEO (inferred using mixed effects models). We estimated genetic parameters using Bayesian bivariate animal models, where expressions of a phenotype in the low and high dMEO herds were taken as being different-albeit correlated-traits. Fertility traits were more favorable in Simmental than in Holstein-Friesian cows, whereas for all traits, Holstein-Friesian had the highest estimates of intraherd heritability [ranging from 0.021 (0.006-0.038) to 0.126 (0.10-0.15)] and Simmental the lowest [ranging from 0.008 (0.001-0.017) to 0.101 (0.08-0.12)]. The genetic correlations between fertility traits and dMEO were moderate and unfavorable, ranging, in absolute values, from 0.527 (0.37-0.68) to 0.619 (0.50-0.73) in Holstein-Friesian; from 0.339 (0.20-0.47) to 0.556 (0.45-0.66) in Brown Swiss; and from 0.340 (0.10-0.60) to 0.475 (0.33-0.61) in Simmental cattle. The only exception was the nonreturn rate at d 56, which had weak genetic correlations with dMEO in all 3 breeds. The herd correlations between fertility and dMEO tended to be modest and favorable and the residual correlations modest and variable. The heritability of fertility traits tended to be greater in the low dMEO than in the high dMEO herds in the case of the Holstein-Friesians, but not in the case of the Brown Swiss or Simmentals. The additive genetic correlations between fertility traits in the low and high dMEO herds were always lower than 1 [0.329 (-0.17 to 0.85) to 0.934 (0.86 to 0.99)] for all traits considered in all breeds. The correlation was particularly low for the threshold characters and the interval from first service to conception in Holstein-Friesian, suggesting that the relative performances of genotypes vary significantly between herds of different dMEO levels. Although there was large variability in the estimates, results might support making separate genetic evaluations of fertility in the different herd production groups. Our results also indicate that Simmental, a dual-purpose breed, has higher fertility and lower environmental sensitivity than Holstein-Friesian, with Brown Swiss being intermediate.

Detailed macro- and micromineral profile of milk: Effects of herd productivity, parity, and stage of lactation of cows of 6 dairy and dual-purpose breeds.

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

Genetic and genomic analyses of latent variables related to the milk fatty acid profile, milk composition, and udder health in dairy cattle.

The aim of this study was to perform genetic, genome-wide association (GWAS), and gene-set enrichment analyses with latent variables related to milk fatty acid profile (i.e., fatty acids factor scores; FAF), milk composition, and udder health in a cohort of 1,158 Italian Brown Swiss cows. The phenotypes under study were 12 FAF previously identified through factor analysis and classified as follows: de novo FA (F1), branched-chain FA-milk yield (F2), biohydrogenation (F3), long-chain fatty acids (F4), desaturation (F5), short-chain fatty acids (F6), milk protein and fat contents (F7), odd fatty acids (F8), conjugated linoleic acids (F9), linoleic acid (F10), udder health (F11) and vaccelenic acid (F12). (Co)variance components were estimated for factor scores using a Bayesian linear animal model via Gibbs sampling. The animals were genotyped with the Illumina BovineSNP50 BeadChip v.2 (Illumina Inc., San Diego, CA). A single marker regression model was fitted for GWAS analysis. The gene-set enrichment analysis was run on the GWAS results using the Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes pathway databases to identify the ontologies and pathways associated with the FAF. Marginal posterior means of the heritabilities of the aforementioned FAF ranged from 0.048 for F12 to 0.310 for F5. Factors F1 and F6 had the highest number of relevant genetic correlations with the other traits. The genomic analysis detected a total of 39 significant SNP located on 17 Bos taurus autosomes. All latent variables produced signals except for F2 and F10. The traits with the highest number of significant associations were F11 (17) and F12 (7). Gene-set enrichment analyses identified significant pathways (false discovery rate 5%) for F3 and F7. In particular, systemic lupus erythematosus was enriched for F3, whereas the MAPK (mitogen-activated protein kinase) signaling pathway was overrepresented for F7. The results support the existence of important and exploitable genetic and genomic variation in these latent explanatory phenotypes. Information acquired might be exploited in selection programs and when designing further studies on the role of the putative candidate genes identified in the regulation of milk composition and udder health.

A landscape of the heritability of Fourier-transform infrared spectral wavelengths of milk samples by parity and lactation stage in Holstein cows.

Fourier-transform near- and mid-infrared (FTIR) milk spectral data are routinely collected in many countries worldwide. Establishing an optimal strategy to use spectral data in genetic evaluations requires knowledge of the heritabilities of individual FTIR wavelength absorbances. Previous FTIR heritability estimates have been based on relatively small sample sizes and have not considered the possibility that heritability may vary across parities and stages of the lactation. We used data from ∼370,000 test-day records of Canadian Holstein cows to produce a landscape of the heritability of FTIR spectra, 1,060 wavelengths in the near- and mid-infrared spectrum (5,011-925 cm-1), by parity and month of the lactation (mo 1 to 3 and mo 1 to 6, respectively). The 2 regions of the spectrum associated with absorption of electromagnetic energy by water molecules were estimated to have very high phenotypic variances, very low heritabilities, and very low proportion of variance explained by herd-year-season (HYS) subclasses. The near- or short-wavelength infrared (SWIR: 5,066-3,672 cm-1) region was also characterized by low heritability estimates, whereas the estimated proportion of the variance explained by HYS was high. The mid-wavelength infrared region (MWIR: 3,000-2,500 cm-1) and the transition between mid and long-wavelength infrared region (MWIR-LWIR: 1,500-925 cm-1) harbor several waves characterized by moderately high (≥0.4) heritabilities. Most of the high-heritability regions contained wavelengths that are reported to be associated with important milk metabolites and components. Interestingly, these 2 same regions tended to show more variability in heritabilities between parity and lactation stage. Second parity showed heritability patterns that were distinctly different from those of the first and third parities, whereas the first 2 mo of the lactation had clearly distinct heritability patterns compared with mo 3 to 6.

From milk to cheese: Evolution of flavor fingerprint of milk, cream, curd, whey, ricotta, scotta, and ripened cheese obtained during summer Alpine pasture.

The role of each step of cheese and ricotta making in development of flavor of cheese and other dairy products is not yet well known. The objectives of this study were to characterize volatile organic compounds (VOC) in cheese and ricotta making with bulk milk from cows grazing in a highland area and to evaluate their evolution in the various dairy products and by-products obtained during the production processes. A group of 148 cows was grazed day and night on pasture from June to September. A total of 7 cheese-making sessions were carried out using the bulk milk collected every 2 wk during summer pasturing according to the artisanal procedure used for Malga cheese production. All milks, products, and by-products were sampled, and the VOC content of milk, cream, whey, ricotta, scotta (residual liquid), fresh cheeses, and cheeses ripened for 6 and 12 mo was determined by solid-phase microextraction gas chromatography-mass spectrometry. Forty-nine compounds were identified belonging to the following chemical families: alcohols (13), aldehydes (9), esters (8), free fatty acids (6), ketones (5), lactones (2), sulfurs (2), terpenes (2), phenol (1), and benzene (1). The results showed that the amounts of VOC in the various dairy products differed significantly. Comparisons between the VOC of 4 types of milk (whole evening, skim evening, whole morning, mixed in the vat) showed that the skimming process had the greatest effect, with about half of all the VOC analyzed affected, followed by time of milking (evening milking vs. morning milking) and mixing (skim evening milk mixed with whole morning milk). In general, among fresh products, cream had higher contents of fatty acids, sulfurs, and terpene volatile compounds than fresh cheese and ricotta, whereas ricotta showed a very high VOC amount compared with fresh cheese, probably due to its high processing temperature. The effects of the progressive nutrient depletion in milk during processing were investigated by comparing the amounts of VOC in vat milk, whey, and scotta. Although milk contained greater amounts of nutrients, whey and especially scotta had higher concentrations of VOC, with the exception of esters, sulfurs, terpenes, and phenolic compounds, as a result of physicochemical and microbial modifications during processing. Finally, the effect of ripening was tested by comparing the VOC of fresh and ripened cheeses (6 and 12 mo), revealing that VOC release increased dramatically during the first semester and further with increasing the ripening period to 1 yr. In particular, some alcohols (butan-2-ol), aldehydes (2-methylpropanal, hexanal, and heptanal), esters (ethyl butanoate and ethyl hexanoate), fatty acids (acetic, butanoic, and hexanoic acids), and ketones (butan-2-one, pentan-2-one, and heptan-2-one) showed a very large increase. In conclusion, according to the artisanal milk processing carried out for Malga cheese production, the quantity of VOC was shown to increase about 3 times during cheese making (from milk in vat to fresh cheese plus whey), almost 4 times during ricotta making (from whey to ricotta plus scotta), and about 16 times during 1 yr of ripening of cheese.

From cow to cheese: Novel phenotypes related to the sensory profile of model cheeses from individual cows.

Milk samples were taken once 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 not 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.

Breed of cow and herd productivity affect milk composition and modeling of coagulation, curd firming, and syneresis.

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, k20, a30, a45, and a60) 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 (RCTeq), asymptotic potential curd firmness (CFP), curd firming instant rate constant (kCF), and syneresis instant rate constant (kSR) and 2 derived traits: maximum curd firmness achieved within 45min (CFmax) and time at achievement of CFmax (tmax) 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 k20 to 10.7% for RCT, whereas individual animal variance was the highest, ranging from 32.0% for tmax to 82.5% for RCTeq. The repeatability of MCP was high (>80%) for all traits except those associated with the last part of the lactodynamographic curve (i.e., a60, kSR, kCF, and tmax: 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 (RCTeq: 18.6 vs. 16.3min) but greater potential curd firmness (CFP: 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.

Factors affecting variations in the detailed fatty acid profile of Mediterranean buffalo milk determined by 2-dimensional gas chromatography.

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.

Pathway-based genome-wide association analysis of milk coagulation properties, curd firmness, cheese yield, and curd nutrient recovery in dairy cattle.

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.

Short communication: Association between udder health status and blood serum proteins in dairy cows.

The aim of this study was to investigate the association between udder health (UH) status and blood serum proteins (i.e., total protein, albumin, globulin, and albumin-to-globulin ratio) in dairy cows. Blood and milk samples were collected from 1,508 cows of 6 different breeds (Holstein Friesian, Brown Swiss, Jersey, Simmental, Rendena, and Alpine Grey) that were housed in 41 multibreed herds. Bacteriological analysis was performed on milk samples with somatic cell count (SCC) >100,000 cells/mL and bacteria identification was confirmed by multiplex-PCR assays. Milk samples were grouped into 7 clusters of UH status: healthy (cows with milk SCC <100,000 cells/mL and not cultured); culture-negative samples with low, medium, or high SCC; and culture-positive samples with contagious, environmental, and opportunistic intramammary infections. Data of blood serum proteins were analyzed using a linear mixed model that included the fixed effects of stage of lactation, parity, breed, herd productivity (high or low production) and UH status, and the random effect of herd-date within herd productivity. Culture-negative samples with high milk SCC, which were most likely undergoing a strong inflammatory response and whose pathogens could not be isolated because they were engulfed by macrophages or because they had already cleared, and milk samples infected by contagious and environmental bacteria were associated with greater globulin concentrations (and lower albumin-to-globulin ratio) in blood. Variation in blood serum proteins seems to be associated with inflammatory status rather than infection, as serum globulin significantly increased in UH status groups with the highest milk SCC and no differences were observed among intramammary infections pathogens. Blood serum proteins can be a mammary gland inflammation indicator, but cannot be used to differentiate among different UH status groups.

Genetic analysis of coagulation properties, curd firming modeling, milk yield, composition, and acidity in Sarda dairy sheep.

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.

Associations between pathogen-specific cases of subclinical mastitis and milk yield, quality, protein composition, and cheese-making traits in dairy cows.

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.

Prediction and repeatability of milk coagulation properties and curd-firming modeling parameters of ovine milk using Fourier-transform infrared spectroscopy and Bayesian models.

The aim of this study was to apply Bayesian models to the Fourier-transform infrared spectroscopy spectra of individual sheep milk samples to derive calibration equations to predict traditional and modeled milk coagulation properties (MCP), and to assess the repeatability of MCP measures and their predictions. Data consisted of 1,002 individual milk samples collected from Sarda ewes reared in 22 farms in the region of Sardinia (Italy) for which MCP and modeled curd-firming parameters were available. Two milk samples were taken from 87 ewes and analyzed with the aim of estimating repeatability, whereas a single sample was taken from the other 915 ewes. Therefore, a total of 1,089 analyses were performed. For each sample, 2 spectra in the infrared region 5,011 to 925 cm-1 were available and averaged before data analysis. BayesB models were used to calibrate equations for each of the traits. Prediction accuracy was estimated for each trait and model using 20 replicates of a training-testing validation procedure. The repeatability of MCP measures and their predictions were also compared. The correlations between measured and predicted traits, in the external validation, were always higher than 0.5 (0.88 for rennet coagulation time). We confirmed that the most important element for finding the prediction accuracy is the repeatability of the gold standard analyses used for building calibration equations. Repeatability measures of the predicted traits were generally high (≥95%), even for those traits with moderate analytical repeatability. Our results show that Bayesian models applied to Fourier-transform infrared spectra are powerful tools for cheap and rapid prediction of important traits in ovine milk and, compared with other methods, could help in the interpretation of results.