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.

Effect of intramammary infection and inflammation on milk protein profile assessed at the quarter level in Holstein cows.

In this study we wanted to investigate the associations between naturally occurring subclinical intramammary infection (IMI) caused by different etiological agents (i.e., Staphylococcus aureus, Streptococcus agalactiae, Streptococcus uberis, and Prototheca spp.), in combination with somatic cell count (SCC), on the detailed milk protein profile measured at the individual mammary gland quarter. An initial bacteriological screening (time 0; T0) conducted on individual composite milk from 450 Holstein cows reared in 3 herds, was performed to identify cows with subclinical IMI. We identified 78 infected animals which were followed up at the quarter level at 2 different sampling times: T1 and T2, 2 and 6 wk after T0, respectively. A total of 529 quarter samples belonging to the previously selected animals were collected at the 2 sampling points and analyzed with a reversed phase HPLC (RP-HPLC) validated method. Specifically, we identified and quantified 4 caseins (CN), namely αS1-CN, αS2-CN, κ-CN, and ß-CN, and 3 whey protein fractions, namely ß-lactoglobulin, α-lactalbumin, and lactoferrin (LF), which were later expressed both quantitatively (g/L) and qualitatively (as a percentage of the total milk nitrogen content, % N). Data were analyzed with a hierarchical linear mixed model with the following fixed effects: days in milk (DIM), parity, herd, SCC, bacteriological status (BACT), and the SCC × BACT interaction. The random effect of individual cow, nested within herd, DIM and parity was used as the error term for the latter effects. Both IMI (i.e., BACT) and SCC significantly reduced the proportion of ß-CN and αS1-CN, ascribed to the increased activity of both milk endogenous and microbial proteases. Less evident alterations were found for whey proteins, except for LF, which being a glycoprotein with direct and undirect antimicrobial activity, increased both with IMI and SCC, suggesting its involvement in the modulation of both the innate and adaptive immune response. Finally, increasing SCC in the positive samples was associated with a more marked reduction of total caseins at T1, and αS1-CN at T2, suggesting a synergic effect of infection and inflammation, more evident at high SCC. In conclusion, our work helps clarify the behavior of protein fractions at quarter level in animals having subclinical IMI. The inflammation status driven by the increase in SCC, rather the infection, was associated with the most significant changes, suggesting that the activity of endogenous proteolytic enzymes related to the onset of inflammation might have a pivotal role in directing the alteration of the milk protein profile.

Associations between subclinical intramammary infection and milk fatty acid profile at the quarter level in Holstein cattle.

Mastitis, especially the subclinical form, is the most common economic and health problem in dairy cows. Little is known about changes in milk fatty acid (FA) composition according to infection/inflammation status of the mammary gland. The aim of this study was to investigate the associations between naturally occurring subclinical intramammary infection (IMI) from different pathogens, i.e. Streptococcus agalactiae, Staphylococcus aureus, Streptococcus uberis and Prototheca spp., and the detailed milk FA profile assessed at quarter level in Holstein cows. After an initial bacteriological screening (T0) on 450 Holstein cows reared in three dairy herds, we identified 78 cows positive at the bacteriological examination. These animals were followed up at the quarter level two weeks (T1) and six weeks (T2) after T0. In total, 600 single-quarter samples were obtained at T1 and T2. Individual FAs were determined using the gas chromatography analytical method. Investigated traits were 70 individual FAs, 12 FA groups, and six desaturation indices. The associations between subclinical IMI combined with somatic cell count (SCC) and milk FA profile were investigated using a hierarchical linear mixed model (i.e., observational unit was quarter within cow) with the following fixed effects: days in milk (DIM), parity, herd, SCC, bacteriological status (BACT, positive and negative), and the SCC × BACT interaction. The random effect of individual cow nested within herd, DIM and parity was used as the error term for the latter effects. The most significant associations were detected at T2. Notably, IMI reduced the proportions of individual short-chain FA, especially 4:0 and 6:0 (-14%), but increased the proportion of the most abundant medium-chain FA (MCFA), 16:0 (+4%). A reduction in the desaturation indices was observed mostly for 14:1 index (-9%), in line with the reduction in 14:1 (-10%). Somatic cell count significantly affected 14 individual FAs. In particular, samples with high SCC (≥200 000) had significantly lower proportions of 8:0, 10:0, 11:0, 12:0, and 13:0 compared with samples with low SCC (<200 000). Increasing SCC in animals positive at the bacteriological examination were associated with a reduction in total MCFA at T2 (while in negative animals, they remained constant across SCC classes), possible evidence that elongation of the FA chain from 11 to 16 carbons is affected by a combination of infection and SCC. This study showed that subclinical IMI and SCC are mainly associated with reductions in the synthesis of FA and the desaturation process in the mammary gland.

Predicting milk protein fractions using infrared spectroscopy and a gradient boosting machine for breeding purposes in Holstein cattle.

In recent years, increasing attention has been focused on the genetic evaluation of protein fractions in cow milk with the aim of improving milk quality and technological characteristics. In this context, advances in high-throughput phenotyping by Fourier transform infrared (FTIR) spectroscopy offer the opportunity for large-scale, efficient measurement of novel traits that can be exploited in breeding programs as indicator traits. We took milk samples from 2,558 Holstein cows belonging to 38 herds in northern Italy, operating under different production systems. Fourier transform infrared spectra were collected on the same day as milk sampling and stored for subsequent analysis. Two sets of data (i.e., phenotypes and FTIR spectra) collected in 2 different years (2013 and 2019-2020) were compiled. The following traits were assessed using HPLC: true protein, major casein fractions [αS1-casein (CN), αS2-CN, ß-CN, κ-CN, and glycosylated-κ-CN], and major whey proteins (ß-lactoglobulin and α-lactalbumin), all of which were measured both in grams per liter (g/L) and proportion of total nitrogen (% N). The FTIR predictions were calculated using the gradient boosting machine technique and tested by 3 different cross-validation (CRV) methods. We used the following CRV scenarios: (1) random 10-fold, which randomly split the whole into 10-folds of equal size (9-folds for training and 1-fold for validation); (2) herd/date-out CRV, which assigned 80% of herd/date as the training set with independence of 20% of herd/date assigned as the validation set; (3) forward/backward CRV, which split the data set in training and validation set according with the year of milk sampling (FTIR and gold standard data assessed in 2013 or 2019-2020) using the "old" and "new" databases for training and validation, and vice-versa with independence among them; (4) the CRV for genetic parameters (CRV-gen), where animals without pedigree as assigned as a fixed training population and animals with pedigree information was split in 5-folds, in which 1-fold was assigned to the fixed training population, and 4-folds were assigned to the validation set (independent from the training set). The results (i.e., measures and predictions) of CRV-gen were used to infer the genetic parameters for gold standard laboratory measurements (i.e., proteins assessed with HPLC) and FTIR-based predictions considering the CRV-gen scenario from a bi-trait animal model using single-step genomic BLUP. We found that the prediction accuracies of the gradient boosting machine equations differed according to the way in which the proteins were expressed, achieving higher accuracy when expressed in g/L than when expressed as % N in all CRV scenarios. Concerning the reproducibility of the equations over the different years, the results showed no relevant differences in predictive ability between using "old" data as the training set and "new" data as the validation set and vice-versa. Comparing the additive genetic variance estimates for milk protein fractions between the FTIR predicted and HPLC measures, we found reductions of -19.7% for milk protein fractions expressed in g/L, and -21.19% expressed as % N. Although we found reductions in the heritability estimates, they were small, with values ranging from -1.9 to -7.25% for g/L, and -1.6 to -7.9% for % N. The posterior distributions of the additive genetic correlations (ra) between the FTIR predictions and the laboratory measurements were generally high (>0.8), even when the milk protein fractions were expressed as % N. Our results show the potential of using FTIR predictions in breeding programs as indicator traits for the selection of animals to enhance milk protein fraction contents. We expect acceptable responses to selection due to the high genetic correlations between HPLC measurements and FTIR predictions.

Impact of somatic cell count combined with differential somatic cell count on milk protein fractions in Holstein cattle.

Udder health in dairy herds is a very important issue given its implications for animal welfare and the production of high-quality milk. Somatic cell count (SCC) is the most widely used means of assessing udder health status. However, differential somatic cell count (DSCC) has recently been proposed as a new and more effective means of evaluating intramammary infection dynamics. Differential SCC represents the combined percentage of polymorphonuclear neutrophils and lymphocytes (PMN-LYM) in the total SCC, with macrophages (MAC) accounting for the remaining proportion. The aim of this study was to evaluate the association between SCC and DSCC and the detailed milk protein profile in a population of 1,482 Holstein cows. A validated reversed-phase HPLC method was used to quantify 4 caseins (CN), namely αS1-CN, αS2-CN, κ-CN, and ß-CN, and 3 whey protein fractions, namely ß-lactoglobulin, α-lactalbumin, and lactoferrin, which were expressed both quantitatively (g/L) and qualitatively (as a percentage of the total milk nitrogen content, %N). A linear mixed model was fitted to explore the associations between somatic cell score (SCS) combined with DSCC and the protein fractions expressed quantitatively and qualitatively. We ran an additional model that included DSCC expressed as PMN-LYM and MAC counts, obtained by multiplying the percentages of PMN-LYM and MAC by SCC for each cow in the data set. When the protein fractions were expressed as grams per liter, SCS was significantly negatively associated with almost all the casein fractions and positively associated with the whey protein α-lactalbumin, while DSCC was significantly associated with αS1-CN, ß-CN, and α-lactalbumin, but in the opposite direction to SCS. We observed the same pattern with the qualitative data (i.e., %N), confirming opposite effects of SCS and DSCC on milk protein fractions. The PMN-LYM count was only slightly associated with the traits of concern, although the pattern observed was the same as when both SCS and DSCC were included in the model. The MAC count, however, generally had a greater impact on many casein fractions, in particular decreasing both ß-CN content (g/L) and proportion (%N), and exhibited the opposite pattern to the PMN-LYM count. Our results show that information obtained from both SCS and DSCC may be useful in assessing milk quality and protein fractions. They also demonstrate the potential of MAC count as a novel udder health trait.

Genetic parameters of differential somatic cell count, milk composition, and cheese-making traits measured and predicted using spectral data in Holstein cows.

Mastitis is one of the most prevalent diseases in dairy cattle and is the cause of considerable economic losses. Alongside somatic cell count (SCC), differential somatic cell count (DSCC) has been recently introduced as a new indicator of intramammary infection. The DSCC is expressed as a count or a proportion (%) of polymorphonuclear neutrophils plus lymphocytes (PMN-LYM) in milk somatic cells. These numbers are complemented to total somatic cell count or to 100 by macrophages (MAC). The aim of this study was to investigate the genetic variation and heritability of DSCC, and its correlation with milk composition, udder health indicators, milk composition, and technological traits in Holstein cattle. Data used in the analysis consisted in single test-day records from 2,488 Holstein cows reared in 36 herds located in northern Italy. Fourier-transform infrared (FTIR) spectroscopy was used to predict missing information for some milk coagulation and cheese-making traits, to increase sample size and improve estimation of the genetic parameters. Bayesian animal models were implemented via Gibbs sampling. Marginal posterior means of the heritability estimates were 0.13 for somatic cell score (SCS); 0.11 for DSCC, MAC proportion, and MAC count; and 0.10 for PMN-LYM count. Posterior means of additive genetic correlations between SCS and milk composition and udder health were low to moderate and unfavorable. All the relevant genetic correlations between the SCC traits considered and the milk traits (composition, coagulation, cheese yield and nutrients recovery) were unfavorable. The SCS showed genetic correlations of -0.30 with the milk protein proportion, -0.56 with the lactose proportion and -0.52 with the casein index. In the case of milk technological traits, SCS showed genetic correlations of 0.38 with curd firming rate (k20), 0.45 with rennet coagulation time estimated using the curd firming over time equation (RCTeq), -0.39 with asymptotic potential curd firmness, -0.26 with maximum curd firmness (CFmax), and of -0.31 with protein recovery in the curd. Differential somatic cell count expressed as proportion was correlated with SCS (0.60) but had only 2 moderate genetic correlations with milk traits: with lactose (-0.32) and CFmax (-0.33). The SCS was highly correlated with the log PMN-LYM count (0.79) and with the log MAC count (0.69). The 2 latter traits were correlated with several milk traits: fat (-0.38 and -0.43 with PMN-LYM and MAC counts, respectively), lactose percentage (-0.40 and -0.46), RCTeq (0.53 and 0.41), tmax (0.38 and 0.48). Log MAC count was correlated with k20 (+0.34), and log PMN-LYM count was correlated with CFmax (-0.26) and weight of water curd as percentage of weight of milk processed (-0.26). The results obtained offer new insights into the relationships between the indicators of udder health and the milk technological traits in Holstein cows.

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.

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.

The influence of dietary nitrogen reduction and conjugated linoleic acid supply to dairy cows on fatty acids in milk and their transfer to ripened cheese.

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 use of 2-dimensional gas chromatography to investigate the effect of rumen-protected conjugated linoleic acid, breed, and lactation stage on the fatty acid profile of sheep milk.

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).

Effect of dairy farming system, herd, season, parity, and days in milk on modeling of the coagulation, curd firming, and syneresis of bovine milk.

The objectives of this study were to characterize the variation in curd firmness model parameters obtained from coagulating bovine milk samples, and to investigate the effects of the dairy system, season, individual farm, and factors related to individual cows (days in milk and parity). Individual milk samples (n = 1,264) were collected during the evening milking of 85 farms representing different environments and farming systems in the northeastern Italian Alps. The dairy herds were classified into 4 farming system categories: traditional system with tied animals (29 herds), modern dairy systems with traditional feeding based on hay and compound feed (30 herds), modern dairy system with total mixed ration (TMR) that included silage as a large proportion of the diet (9 herds), and modern dairy system with silage-free TMR (17 herds). Milk samples were analyzed for milk composition and coagulation properties, and parameters were modeled using curd firmness measures (CFt) collected every 15 s from a lacto-dynamographic analysis of 90 min. When compared with traditional milk coagulation properties (MCP), the curd firming measures showed greater variability and yielded a more accurate description of the milk coagulation process: the model converged for 93.1% of the milk samples, allowing estimation of 4 CFt parameters and 2 derived traits [maximum CF (CF(max)) and time from rennet addition to CF(max) (t(max))] for each sample. The milk samples whose CFt equations did not converge showed longer rennet coagulation times obtained from the model (RCT(eq)) and higher somatic cell score, and came from less-productive cows. Among the sources of variation tested for the CFt parameters, dairy herd system yielded the greatest differences for the contrast between the traditional farm and the 3 modern farms, with the latter showing earlier coagulation and greater instant syneresis rate constant (k(SR)). The use of TMR yielded a greater tmax because of a higher instant curd-firming rate constant (k(CF)). Season of sampling was found to be very important, yielding higher values during winter for all traits except k(CF) and k(SR). All CFt traits were affected by individual cow factors. For parity, milk produced by first-lactation cows showed higher k(CF) and k(SR), but delays in achieving CF(max). With respect to stage of lactation, RCT(eq) and potential asymptotic CF increased during the middle of lactation and stabilized thereafter, whereas the 2 instant rate constants presented the opposite pattern, with the lowest (k(CF)) and highest (k(SR)) values occurring in mid lactation. The new challenge offered by prolonging the test interval and individual modeling of milk technological properties allowed us to study the effects of parameters related to the environment and to individual cows. This novel strategy may be useful for investigating the genetic variability of these new coagulation traits.

Technical note: In vitro total gas and methane production measurements from closed or vented rumen batch culture systems.

This study compared measured gas production (GP) and computed CH4 production values provided by closed or vented bottles connected to gas collection bags. Two forages and 3 concentrates were incubated. Two incubations were conducted, where the 5 feeds were tested in 3 replicates in closed or vented bottles, plus 4 blanks, for a total of 64 bottles. Half of the bottles were not vented, and the others were vented at a fixed pressure (6.8 kPa) and gas was collected into one gas collection bag connected to each bottle. Each bottle (317 mL) was filled with 0.4000 ± 0.0010 g of feed sample and 60 mL of buffered rumen fluid (headspace volume = 257 mL) and incubated at 39.0°C for 24 h. At 24 h, gas samples were collected from the headspace of closed bottles or from headspace and bags of vented bottles and analyzed for CH4 concentration. Volumes of GP at 24 h were corrected for the gas dissolved in the fermentation fluid, according to Henry's law of gas solubility. Methane concentration (mL/100mL of GP) was measured and CH4 production (mL/g of incubated DM) was computed using corrected or uncorrected GP values. Data were analyzed for the effect of venting technique (T), feed (F), interaction between venting technique and feed (T × F), and incubation run as a random factor. Closed bottles provided lower uncorrected GP (-18%) compared with vented bottles, especially for concentrates. Correction for dissolved gas reduced but did not remove differences between techniques, and closed bottles (+25 mL of gas/g of incubated DM) had a greater magnitude of variation than did vented bottles (+1 mL of gas/g of incubated DM). Feeds differed in uncorrected and corrected GP, but the ranking was the same for the 2 techniques. The T × F interaction influenced uncorrected GP values, but this effect disappeared after correction. Closed bottles provided uncorrected CH4 concentrations 23% greater than that of vented bottles. Correction reduced but did not remove this difference. Methane concentration was influenced by feed but not by the T × F interaction. Corrected CH4 production was influenced by feed, but not by venting technique or the T × F interaction. Closed bottles provide good measurements of CH4 production but not of GP. Venting of bottles at low pressure permits a reliable evaluation of total GP and CH4 production.

Effect of high or low protein ration combined or not with rumen protected conjugated linoleic acid (CLA) on meat CLA content and quality traits of double-muscled Piemontese bulls.

A trial was carried out on double-muscled Piemontese bulls to evaluate the effects of two rations differing in crude protein density (HP=14.5% DM and LP=10.8% DM) and top dressed or not with 80 g/d of rumen protected CLA (rpCLA) for a long period (336 d) on meat quality traits and CLA content. Forty-eight bulls were fed one of the four experimental diets based on corn silage and cereals and were slaughtered at an average age and body weight (BW) of 562 ± 18 d and 668 ± 56 kg, respectively. After slaughter the 5th rib cut was dissected into Longissimus thoracis (LT), other muscles (OM), inter-muscular fat (IF), cover fat (CF), and bones. Muscles and fatty tissues were analyzed for proximate composition and fatty acid (FA) profiles. Rib was composed by 81.1, 3.7, 1.6 and 13.6% of muscles, IF, FC and bone, respectively; LT and OM contained only 0.8 and 1.4% of lipid, respectively. The treatments did not influence these values, but rpCLA increased, compared to control, both c9,t11-CLA and t10,c12-CLA concentrations in all the tissues (P<0.01); t10,c12-CLA concentration was increased much more in muscles (+20 times) than in fatty tissues (from +0.2 to +0.9 times). This suggests that in the muscle this isomer is preferentially stored and/or less combusted with respect to other fatty acids. Low protein rations did not exert any influence on carcass and meat quality, as on growth performance, but reduced nitrogen excretion, their use for improving the environmental impact (process quality) of this meat production system is recommended.

Effects of low-protein diets and rumen-protected conjugated linoleic acid on production and carcass traits of growing double-muscled Piemontese bulls.

The effects of low-protein (LP) diets and rumen-protected CLA on DMI, ADG, carcass traits, and health status of double-muscled Piemontese young bulls were investigated. Forty-eight bull calves (BW = 237 ± 24 kg) were divided in 4 groups and housed in 12 fully slatted pens. Bulls were fed 2 diets differing in CP density [high-protein (HP) diet: CP = 145 g/kg of DM; LP diet: CP = 108 g/kg of DM] and top-dressed with 80 g/d of rumen-protected CLA or 65 g/d of hydrogenated soybean oil. Orts were collected weekly and feed intake was estimated on a pen basis, with 3 replicated pens for each treatment. Each bull was weighed monthly and examined for alterations of the locomotion system by using the locomotion score as an index of lameness and by counting the number of swollen joints. Carcass quality traits were measured at slaughter, after a feeding period of 332 d. Compared with HP, LP reduced ADG only during the first 4 mo of the trial (1.30 vs. 1.53 kg/d, P = 0.003). However, because of compensatory growth, over the whole trial, no significant effects attributable to CP or to additive were found on final BW (668 kg), ADG (1.19 kg/d), DMI (8.50 or 86 g/d per kg of BW(0.75)), dressing percentage (67.3%), carcass conformation (5.2 points), and carcass fat covering (1.87 points). Feed efficiency was affected by a CP × additive interaction (P = 0.030), with CLA improving feed efficiency when added to the LP diets, whereas feed efficiency was reduced with the HP diets. The addition of both LP and CLA reduced the number of bulls presenting swollen joints (P = 0.001), and LP improved the locomotion score (P = 0.021) compared with HP. It was concluded that 10.8 g/kg of CP density in the diet is sufficient for double-muscled Piemontese bulls. The reduction in CP density from 145 to 108 g/kg of DM, in addition to reducing the feeding cost, allows a strong reduction in N consumption without negative consequences on growth performance and carcass traits.