Cattle, climate and complexity: food security, quality and sustainability of the Australian cattle industries.

BACKGROUND: Marked increases in atmospheric CO2 concentrations are largely associated with the release of sequestered carbon in fossil fuels. While emissions of green-house gasses (GHG) from cattle have significant global warming potential, these are biogenic sources and substantially involve carbon in natural cycles, rather than fossil fuel. Cattle use human inedible feeds and by-products of human food production to produce nutrient-dense foods of great value to humans. INTERVENTIONS TO REDUCE GHG PRODUCTION: Reductions in land clearing and burning of grasslands and increased carbon sequestration in soils and trees have potential to substantially reduce GHG emissions. Increased efficiencies of production through intensified feeding and enteric modification have markedly reduced intensity of GHG emissions for cattle in Australia. Genetic selection for lower emissions has modest, but cumulative potential to reduce GHG (mostly CH4 ) emissions and intensity. Improved reproductive performance can reduce intensity of GHG emissions, especially in beef production. Feeds and technologies that reduce GHG production and intensity include improved pastures, grain feeding, dietary lipids, nitrates, ionophores, seaweed, 3-NOP, hormonal growth promotants in beef, and improved diets for peri-parturient dairy cattle. There is considerable potential to further reduce emissions from cattle using the technologies reviewed. INTERVENTIONS TO REDUCE HEAT STRESS: Cattle are susceptible to heat stress and ameliorating interventions include tree and shelter belts, shade, housing, cooling with fans and water and dietary manipulations. CONCLUSIONS: Numerous interventions can reduce GHG emissions and intensity from cattle. There are opportunities to increase carbon capture and maintain biodiversity in Australia's extensive rangelands, but these require quantification and application. We can reduce the intensity of CH4 emissions for cattle in Australia and simultaneously improve their well-being.

Breeding for reduced methane emission and feed-efficient Holstein cows: An international response.

Selecting for lower methane (CH4) emitting animals is one of the best approaches to reduce CH4 given that genetic progress is permanent and cumulative over generations. As genetic selection requires a large number of animals with records and few countries actively record CH4, combining data from different countries could help to expedite accurate genetic parameters for CH4 traits and build a future genomic reference population. Additionally, if we want to include CH4 in the breeding goal, it is important to know the genetic correlations of CH4 traits with other economically important traits. Therefore, the aim of this study was first to estimate genetic parameters of 7 suggested methane traits, as well as genetic correlations between methane traits and production, maintenance, and efficiency traits using a multicountry database. The second aim was to estimate genetic correlations within parities and stages of lactation for CH4. The third aim was to evaluate the expected response of economically important traits by including CH4 traits in the breeding goal. A total of 15,320 methane production (MeP, g/d) records from 2,990 cows belonging to 4 countries (Canada, Australia, Switzerland, and Denmark) were analyzed. Records on dry matter intake (DMI), body weight (BW), body condition score, and milk yield (MY) were also available. Additional traits such as methane yield (MeY; g/kg DMI), methane intensity (MeI; g/kg energy-corrected milk), a genetic standardized methane production, and 3 definitions of residual methane production (g/d), residual feed intake, metabolic BW (MBW), BW change, and energy-corrected milk were calculated. The estimated heritability of MeP was 0.21, whereas heritability estimates for MeY and MeI were 0.30 and 0.38, and for the residual methane traits heritability ranged from 0.13 to 0.16. Genetic correlations between different methane traits were moderate to high (0.41 to 0.97). Genetic correlations between MeP and economically important traits ranged from 0.29 (MY) to 0.65 (BW and MBW), being 0.41 for DMI. Selection index calculations showed that residual methane had the most potential for inclusion in the breeding goal when compared with MeP, MeY, and MeI, as residual methane allows for selection of low methane emitting animals without compromising other economically important traits. Inclusion of residual feed intake in the breeding goal could further reduce methane, as the correlation with residual methane is moderate and elicits a favorable correlated response. Adding a negative economic value for methane could facilitate a substantial reduction in methane emissions while maintaining an increase in milk production.

Genetic parameters for methane emission traits in Australian dairy cows.

Methane is a greenhouse gas of high interest to the dairy industry, with 57% of Australia's dairy emissions attributed to enteric methane. Enteric methane emissions also constitute a loss of approximately 6.5% of ingested energy. Genetic selection offers a unique mitigation strategy to decrease the methane emissions of dairy cattle, while simultaneously improving their energy efficiency. Breeding objectives should focus on improving the overall sustainability of dairy cattle by reducing methane emissions without negatively affecting important economic traits. Common definitions for methane production, methane yield, and methane intensity are widely accepted, but there is not yet consensus for the most appropriate method to calculate residual methane production, as the different methods have not been compared. In this study, we examined 9 definitions of residual methane production. Records of individual cow methane, dry matter intake (DMI), and energy corrected milk (ECM) were obtained from 379 animals and measured over a 5-d period from 12 batches across 5 yr using the SF6 tracer method and an electronic feed recording system, respectively. The 9 methods of calculating residual methane involved genetic and phenotypic regression of methane production on a combination of DMI and ECM corrected for days in milk, parity, and experimental batch using phenotypes or direct genomic values. As direct genomic values (DGV) for DMI are not routinely evaluated in Australia at this time, DGV for FeedSaved, which is derived from DGV for residual feed intake and estimated breeding value for bodyweight, were used. Heritability estimates were calculated using univariate models, and correlations were estimated using bivariate models corrected for the fixed effects of year-batch, days in milk, and lactation number, and fitted using a genomic relationship matrix. Residual methane production candidate traits had low to moderate heritability (0.10 ± 0.09 to 0.21 ± 0.10), with residual methane production corrected for ECM being the highest. All definitions of residual methane were highly correlated phenotypically (>0.87) and genetically (>0.79) with one another and moderately to highly with other methane candidate traits (>0.59), with high standard errors. The results suggest that direct selection for a residual methane production trait would result in indirect, favorable improvement in all other methane traits. The high standard errors highlight the importance of expanding data sets by measuring more animals for their methane emissions and DMI, or through exploration of proxy traits and combining data via international collaboration.

Supplementing the diet of dairy cows with fat or tannin reduces methane yield, and additively when fed in combination.

Addition of fats to the diets of ruminants has long been known to result in a reduction in enteric methane emissions. Tannins have also been used to reduce methane emissions but with mixed success. However, the effect of feeding fat in combination with tannin is unknown. Eight ruminally cannulated Holstein-Friesian cows were fed four diets in a double Latin-square, full crossover sequence. The treatments were 800 ml/day of water (CON), 800 g/day of cottonseed oil, 400 g/day of tannin, and 800 g/day of cottonseed oil and 400 g/day of tannin in combination (fat- and tannin-supplemented diet). Methane emissions were measured using open-circuit respiration chambers. Intake of basal diets was not different between treatments. Cows fed cottonseed oil had greater milk yield (34.9 kg/day) than those fed CON (32.3 kg/day), but the reduced concentration of milk fat meant there was no difference in energy-corrected milk between treatments. Methane yield was reduced when either cottonseed oil (14%) or tannin (11%) was added directly to the rumen, and their effect was additive when given in combination (20% reduction). The mechanism of the anti-methanogenic effect remains unclear but both fat and tannin appear to cause a reduction in fermentation in general rather than cause a change in the type of fermentation.

Metabolic modeling using statistical and spreadsheet software: Application to the glucose minimal model.

Kinetic non-linear metabolic models are used extensively in medical research and increasingly for clinical diagnostic purposes. An example of such a model is the Glucose Minimal Model by Bergman and colleagues [1]. This model is similar to pharmacokinetic/pharmacodynamic models in that like pharmacokinetic/pharmacodynamic models, it is based on a small number of fairly simple ordinary differential equations and it aims to determine how the changing concentration of one blood constituent influences the concentration of another constituent. Although such models may appear prima facie, to be relatively simple, they have gained a reputation of being difficult to fit to data, especially in a consistent and repeatable fashion. Consequently, researchers and clinicians have generally relied on dedicated software packages to do this type of modeling. This article describes the use of statistical and spreadsheet software for fitting the Glucose Minimal Model to data from an insulin modified intravenous glucose tolerance test (IM-IVGTT). A novel aspect of the modeling is that the differential equations that are normally used to describe insulin action and the disposition of plasma glucose are first solved and expressed in their explicit forms so as to facilitate the estimation of Glucose Minimal Model parameters using the nonlinear (nl) optimization procedure within statistical and spreadsheet software. The most important clinical parameter obtained from the Glucose Minimal Model is insulin sensitivity (SI). Using IM-IVGTT data from 42 horses in one experiment and 48 horses in a second experiment, we demonstrate that estimates of SI derived from the Glucose Minimal Model fitted to data using STATA and Excel, are highly concordant with SI estimates obtained using the industry standard software, MinMod Millennium. This work demonstrates that there is potential for statistical and spreadsheet software to be applied to a wide range of kinetic non-linear modeling problems.

Influence of proportion of wheat in a pasture-based diet on milk yield, methane emissions, methane yield, and ruminal protozoa of dairy cows.

Wheat is the most common concentrate fed to grazing dairy cows in Australia, but no studies have examined the effects of wheat proportion in a pasture-based diet on milk production and methane emissions. In this 47-d experiment, 32 Holstein dairy cows were offered 1 of 4 diets during d 1 to 36. Cows in each of the dietary treatment groups were individually offered no wheat (W0) or wheat at 3 kg of dry matter (DM)/d (W3), 6 kg of DM/d (W6), or 9 kg of DM/d (W9). The remainder of the diet was 2.2 kg of DM of concentrate mix and freshly harvested perennial ryegrass (Lolium perenne) such that all individual cows were offered a total diet of approximately 20.2 kg of DM/d. From d 37 to 47 the diets of cows receiving treatments W0 and W3 remained unchanged, but cows in treatments W6 and W9 received the W3 diet. Individual cow feed intakes, milk yields, milk compositions, and methane emissions were measured for d 31 to 35 (period 1) and d 45 to 47 (period 2). During period 1, the mean intakes of cows offered the W0, W3, W6, and W9 diets were 19.2, 20.4, 20.2, and 19.8 kg of DM/d. Diet caused differences in energy-corrected milk, and means for W0, W3, W6, and W9 were 29.5, 32.4, 33.0, and 32.9 kg/d, respectively. Milk fat percentage differed with respective means of 3.93, 3.94, 3.69, and 3.17. Diets also caused differences in methane emissions, with means for W0, W3, W6, and W9 of 440, 431, 414, and 319 g/d. During period 1, the cows fed the W9 diet produced less methane and had lower methane yields (g/kg of DMI) and intensities (g/kg of energy-corrected milk) than cows fed the W3 diet. However, in period 2 when the wheat intake of cows in the W9 treatment was reduced to the same level as in the W3 treatment, their methane emissions, yields, and intensities were similar to those offered the W3 treatment, yet protozoa numbers in ruminal fluid were still much lower than those in cows offered the W3 treatment. Our research shows that for diets based on perennial ryegrass and crushed wheat, only the diet containing more than 30% crushed wheat resulted in substantially depressed milk fat concentration and reduced methane emissions, methane yield, and methane intensity. Thus, although feeding a diet with a high proportion of wheat can cause substantial methane mitigation, it can come at the cost of depression in milk fat concentration.

Individual milk fatty acids are potential predictors of enteric methane emissions from dairy cows fed a wide range of diets: Approach by meta-analysis.

There is a need to quantify methane (CH4) emissions with alternative methods. For the past decade, milk fatty acids (MFA) could be used as proxies to predict CH4 emissions from dairy cows because of potential common rumen biochemical pathways. However, equations have been developed based on a narrow range of diets and with limited data. The objectives of this study were to (1) construct a set of empirical models based on individual data of CH4 emissions and MFA from a large number of lactating dairy cows fed a wide range of diets; (2) further increase the models' level of complexity (from farm to research level) with additional independent variables such as dietary chemical composition (organic matter, neutral detergent fiber, crude protein, starch, and ether extract), dairy performance (milk yield and composition), and animal characteristics (days in milk or body weight); and (3) evaluate the performance of the developed models on independent data sets including measurements from individual animals or average measurements of groups of animals. Prediction equations based only on MFA [C10:0, iso C17:0 + trans-9 C16:1,cis-11 C18:1, and trans-11,cis-15 C18:2 for CH4 production (g/d); iso C16:0, cis-11 C18:1, trans-10 C18:1, and cis-9,cis-12 C18:2 for CH4 yield (g/kg of dry matter intake, DMI); and iso C16:0, cis-15 C18:1, and trans-10 + trans-11 C18:1 for CH4 intensity (g/kg of milk)] had a root mean squared error of 65.1 g/d, 2.8 g/kg of DMI, and 2.9 g/kg of milk, respectively, whereas complex equations that additionally used DMI, dietary neutral detergent fiber, ether extract, days in milk, and body weight had a lower root mean squared error of 46.6 g/d, 2.6 g/kg of DMI, and 2.7 g/kg of milk, respectively). External evaluation with individual or mean data not used for equation development led to variable results. When evaluations were performed using individual cow data from an external data set, accurate predictions of CH4 production (g/d) were obtained using simple equations based on MFA. Better performance was observed on external evaluation with individual data for the simple equation of CH4 production (g/d, based on MFA), whereas better performance was observed on external evaluation mean data for the simple equation of CH4 yield (g/kg of DMI). The performance of evaluation of the models is dependent on the domain of validity of the evaluation data sets used (individual or mean).

Modification of the sterol profile in milk through feeding.

The fortification of milk with phytosterols is an increasingly common practice to enhance the sterol profile and offer consumers potential health benefits. This study investigated whether cattle feed can influence the profile of phytosterols and cholesterol in the milk produced as an alternative to direct fortification of milk. Five experiments were performed using feeds commonly used by Australian dairy farmers and selected formulated rumen-protected feeds. Statistical significances were observed for some individual plant sterols and cholesterol in milk under these differing feeding regimens compared with the respective controls. In the case of the phytosterols, where the daily recommended consumption is typically 2 g per day, the total phytosterols were <0.12 mg/100 mL of milk. An experiment using a rumen-protected feed with high phytosterol levels suggested a decreased transfer of cholesterol to the milk by as much as 20%, although further work is required to confirm these preliminary results. Overall, the study suggests that different feeding practices have minimal effect on the resulting sterol profile of the milk.

Effect of dietary fat supplementation on methane emissions from dairy cows fed wheat or corn.

Diets that contain high proportions of either wheat or supplementary fat have been individually reported to reduce enteric methane production. The objective of this research was to determine the effect of dietary fat supplementation on methane emissions and milk yield from cows fed diets containing either corn or wheat grains. It was hypothesized that cows fed a diet containing wheat would produce less methane and have lower methane yield (methane per kg of dry matter intake; MY) than cows fed a diet containing corn and that methane mitigation from fat supplementation would occur irrespective of the type of grain in the basal diet. The experiment involved 32 Holstein-Friesian dairy cows allocated to 1 of 4 treatment groups (n = 8) and individually fed different diets restricted to approximately 90% of their mean ad libitum intake measured during a covariate period. All animals were offered 11.5 kg of dry matter/d of alfalfa hay, 1.8 kg of dry matter/d of solvent-extracted canola meal, and 1 of 4 dietary supplements. Dietary supplements were 8 kg of dry matter/d of either corn or wheat, or these same treatments with the addition of 0.8 kg of canola oil. In this 5-wk experiment, d 1 to 7 served as the covariate period, d 8 to 14 as the transition period, d 15 to 28 as the adaptation period, and d 29 to 35 as the experimental period. Cows were fed their full treatment diets from d 15 to 35 during which time milk production and feed intake were measured daily. During d 29 to 35, methane production was measured for individual cows daily using the sulfur hexafluoride tracer method. The resulting averages for milk production and feed intake were analyzed by analysis of covariance with factorial grain by fat as treatment structure, animal as the unit within blocks, and the corresponding milk production or feed intake covariate averages as principal covariate. Data on milk fatty acids, ruminal fluid data on pH, ammonia, volatile fatty acids, protozoa, and methane were analyzed by ANOVA using the same treatment and blocking structures excluding the principal covariate. Cows fed a diet containing wheat had greater MY than cows fed a diet containing corn. Irrespective of the type of grain in the diet, increasing the fat concentration from 2 to 6% dry matter reduced MY. It is concluded that the grain component in the basal diet does not affect the mitigating effects of dietary fat supplements on MY.

Adaptation responses in milk fat yield and methane emissions of dairy cows when wheat was included in their diet for 16 weeks.

Short-term studies have shown that feeding dairy cows diets containing a high proportion (>40%) of wheat may result in reduced milk fat concentration and reduced CH4 emissions (g of CH4/cow per d), but no long-term studies have been done on these responses. This study compared the milk production and CH4 responses when 24 dairy cows were fed diets containing high proportions of either wheat or corn over 16 wk. Cows were assigned to 2 groups and offered a diet (CRN) containing 10.0 kg of dry matter/d of crushed corn grain, 1.8 kg of dry matter/d of canola meal, 0.2 kg of dry matter/d of minerals, and 11.0 kg of dry matter/d of chopped alfalfa hay or a similar diet (WHT) in which wheat replaced the corn. Dry matter intake and milk yields of individual cows were measured daily. Methane emissions from individual cows were measured using controlled climate respiration chambers over 2 consecutive days during each of wk 4, 10, and 16. Milk composition was measured on the 2 d when cows were in chambers during wk 4, 10, and 16. Over the 16-wk experimental period, total dry matter intake remained relatively constant and similar for the 2 dietary treatment groups. At wk 4, CH4 emission, CH4 yield (g of CH4/kg of dry matter intake), milk fat yield, and milk fat concentration were substantially less in cows fed the WHT diet compared with the same metrics in cows fed the CRN diet; but these differences were not apparent at wk 10 and 16. The responses over time in these metrics were not similar in all cows. In 4 cows fed the WHT diet, CH4 yield, milk fat concentration, and milk fat yield remained relatively constant from wk 4 to 16, whereas for 5 fed the WHT diet, their CH4 emissions, milk fat yields, and milk fat concentrations almost doubled between wk 4 and 16. In the short term (4 wk), the inclusion of approximately 45% wheat instead of corn in the diet of cows resulted in reductions of 39% in CH4 yield, 35% in milk fat concentration, and 40% in milk fat yield. However, these reductions did not persist to wk 10 or beyond. Our data indicate that cows do not all respond in the same way with some "adaptive" cows showing a marked increase in CH4 yield, milk fat concentration, and milk fat yield after wk 4, whereas in other "nonadaptive" cows, these metrics were persistently inhibited to 16 wk. This research shows that short-term studies on dietary interventions to mitigate enteric CH4 emissions may not always predict the long-term effects of such interventions.

Symposium review: Uncertainties in enteric methane inventories, measurement techniques, and prediction models.

Ruminant production systems are important contributors to anthropogenic methane (CH4) emissions, but there are large uncertainties in national and global livestock CH4 inventories. Sources of uncertainty in enteric CH4 emissions include animal inventories, feed dry matter intake (DMI), ingredient and chemical composition of the diets, and CH4 emission factors. There is also significant uncertainty associated with enteric CH4 measurements. The most widely used techniques are respiration chambers, the sulfur hexafluoride (SF6) tracer technique, and the automated head-chamber system (GreenFeed; C-Lock Inc., Rapid City, SD). All 3 methods have been successfully used in a large number of experiments with dairy or beef cattle in various environmental conditions, although studies that compare techniques have reported inconsistent results. Although different types of models have been developed to predict enteric CH4 emissions, relatively simple empirical (statistical) models have been commonly used for inventory purposes because of their broad applicability and ease of use compared with more detailed empirical and process-based mechanistic models. However, extant empirical models used to predict enteric CH4 emissions suffer from narrow spatial focus, limited observations, and limitations of the statistical technique used. Therefore, prediction models must be developed from robust data sets that can only be generated through collaboration of scientists across the world. To achieve high prediction accuracy, these data sets should encompass a wide range of diets and production systems within regions and globally. Overall, enteric CH4 prediction models are based on various animal or feed characteristic inputs but are dominated by DMI in one form or another. As a result, accurate prediction of DMI is essential for accurate prediction of livestock CH4 emissions. Analysis of a large data set of individual dairy cattle data showed that simplified enteric CH4 prediction models based on DMI alone or DMI and limited feed- or animal-related inputs can predict average CH4 emission with a similar accuracy to more complex empirical models. These simplified models can be reliably used for emission inventory purposes.

Influence of feeding supplements of almond hulls and ensiled citrus pulp on the milk production, milk composition, and methane emissions of dairy cows.

Almond hulls and citrus pulp have been fed to dairy cows with variable responses for milk production, but no information exists on their effect on enteric methane emissions. This experiment examined the effects of dietary supplementation with either almond hulls or ensiled citrus pulp on the milk yield, milk composition, and enteric methane emissions of dairy cows. Thirty-two Holstein dairy cows in mid lactation were offered 1 of 3 diets over a 28-d experiment. Twelve cows received a control (CON) diet, 10 cows a diet containing almond hulls (ALH), and 10 cows a diet containing ensiled citrus pulp (CIT). All cows were offered 6.0 kg of dry matter (DM)/d of crushed corn, 2.0 kg of DM/d of cold-pressed canola, and 0.2 kg of DM/d of a mineral mix. In addition, cows fed the CON diet were offered 14.5 kg of DM/d of alfalfa cubes; cows fed the ALH diet were offered 10.5 kg of DM/d of alfalfa cubes and 4.0 kg of DM/d of almond hulls; and cows on the CIT diet were offered 11.5 kg of DM/d of alfalfa cubes and 3.0 kg of DM/d of ensiled citrus pulp. Milk yield was measured daily and milk composition was measured on 4 d of each week. Individual cow methane emissions were measured by a sulfur hexafluoride tracer technique on d 24 to 28 of the experiment. The mean milk yield of cows fed the CON diet (27.4 kg/d) was greater than the mean milk yield of cows fed the ALH diet (24.6 kg/cow per day), whereas the mean milk yield of cows fed the CIT diet (26.2 kg/cow per day) was not different from the mean milk yield from cows fed the other 2 diets. Dietary treatment did not influence the concentrations of milk fat, protein, and lactose or fat yields, but the mean protein yield from cows fed the CON diet (0.87 kg/d) was greater than that from cows fed the ALH diet (0.78 kg/d) but not different to those fed the CIT diet (0.85 kg/d). In general, we found no differences in the proportion of individual fatty acids in milk. The mean pH of ruminal fluid from cows offered the CON diet was not different to the pH in the ruminal fluids of cows offered the ALH or the CIT diets. The mean methane emissions (g/d) and yields (g/kg of DM intake) were not influenced by dietary treatment. These findings indicate that, although almond hulls and ensiled citrus pulp can be used as a low-cost feed supplement, almond hulls did negatively affect milk production and neither inhibited enteric methane emissions.

Wheat is more potent than corn or barley for dietary mitigation of enteric methane emissions from dairy cows.

Wheat is the most common concentrate fed to dairy cows in Australia, but few studies have examined the effects of wheat feeding on enteric methane emissions, and no studies have compared the relative potencies of wheat, corn, and barley for their effects on enteric methane production. In this 35-d experiment, 32 Holstein dairy cows were offered 1 of 4 diets: a corn diet (CRN) of 10.0 kg of dry matter (DM)/d of single-rolled corn grain, 1.8 kg of DM/d of canola meal, 0.2 kg of DM/d of minerals, and 11.0 kg of DM/d of chopped alfalfa hay; a wheat diet (WHT) similar to the CRN diet but with the corn replaced by single-rolled wheat; a barley diet (SRB) similar to the CRN diet but with the corn replaced by single-rolled barley; and a barley diet (DRB) similar to the CRN diet but with the corn replaced by double-rolled barley. Individual cow feed intakes, milk yields, and milk compositions were measured daily but reported for the last 5 d of the experiment. During the last 5 d of the experiment, individual cow methane emissions were measured using the SF6 tracer technique for all cows, and ruminal fluid pH was continuously measured by intraruminal sensors for 3 cows in each treatment group. The average DM intake of cows offered the CRN, WHT, SRB, and DRB diets was 22.2, 21.1, 22.6, and 22.6 kg/d. The mean energy-corrected milk of cows fed the WHT diet was less than that of cows fed the other diets. This occurred because the milk fat percentage of cows fed the WHT diet was significantly less than that of cows fed the other diets. The mean methane emissions and methane yields of cows fed the WHT diet were also significantly less than those of cows fed the other diets. Indeed, the CRN, SRB, and DRB diets were associated with 49, 73, and 78% greater methane emissions, respectively, compared with the emissions from the WHT diet. Methane yield was found to be most strongly related to the minimum daily ruminal fluid pH. This study showed that although the inclusion of wheat in the diet of dairy cows could be an effective strategy for substantially reducing their methane emissions, it also reduced their milk fat percentage and production of milk fat and energy-corrected milk.

Analysis of pasture supplementation strategies by means of a mechanistic model of ruminal digestion and metabolism in the dairy cow.

Effective pasture supplementation is critical to the efficiency of resource management in milk production. We understand a great deal about ruminal and metabolic processes in dairy cattle that control efficiency but we need to improve our ability to predict effects of practical feeding strategies based on the basic biological processes of the cow. Therefore, a large-scale pasture supplementation study was used to explore the details of both practical management and the underlying biological principles and processes involved. This included a multiple lactation study coupled with shorter-term experiments that tested the type and rate of supplementation. Basal supplementation strategies were (1) pasture allowance [14 kg of dry matter (DM)/d per cow] supplemented with milled barley grain fed twice daily in the milking parlor and pasture silage provided in the paddock; the ratio of grain:forage fed as supplement was 0.75:0.25 (control; DM basis); (2) the same pasture allowance plus the same amounts of milled barley grain and pasture silage, but the supplements were mixed and chopped before being fed immediately after each milking; and (3) the same pasture allowance and offered a partial mixed ration comprising barley (25%) and corn grain (30% of DM), corn silage (20% of DM), and alfalfa hay (25% of DM) after each milking. In late lactation (227 d in milk), a short-term experiment was done feeding the same pasture allowances but with the 3 supplements offered at 6, 8, 10, and 12 kg of DM/d for an 11-d measurement period following adaptation to the diet to each of the 3 long-term supplementation groups. Production responses were recorded and ruminal volatile fatty acids (VFA) and pH were measured in a subset of animals. Model descriptions of yields of milk and milk constituents as well as mean concentrations of ruminal fluid VFA and ruminal fluid pH were compared with measured values resulting when dairy cows were fed 12 different pasture-based diets with different levels and types of dietary supplement. Inputs into the model were measured dry matter intake and feed composition on the 12 combined treatments as well as initial body weight and composition. The model described milk and milk component production within 1 standard deviation of the treatment means (less than 5% of the mean as measured in the root mean square error). The simulated proportions of ruminal acetate, propionate, and butyrate were consistent with observed effects of supplemental treatments and rate of supplementation; however, the error analysis showed room for improvement. The model described, to a general extent, the changes in ruminal pH; however, this investigation showed that the equations that describe ruminal pH need to be improved or modified. These results show that the fundamental knowledge of ruminal and organ metabolism in this mechanistic model is sufficient to describe the qualitative responses to complicated dietary strategies, but our quantitative understanding of the parameters involved such as degradation and absorption kinetics and ruminal pH still demands more specific research.

Short communication: Comparison of the GreenFeed system with the sulfur hexafluoride tracer technique for measuring enteric methane emissions from dairy cows.

The objective of this study was to compare 2 commonly used techniques for measuring methane emissions from ruminant animals: the GreenFeed (GF) system and the sulfur hexafluoride (SF6) technique. The study was part of a larger experiment in which a methane inhibitor, 3-nitrooxypropanol, fed at 4 application rates (0, 40, 60, and 80 mg/kg of feed dry matter) decreased enteric methane emission by an average of 30% (measured by both GF and SF6) in a 12-wk experiment with 48 lactating Holstein cows fed a total mixed ration. The larger experiment used a randomized block design and was conducted in 2 phases (February to May, phase 1, and June to August, phase 2), with 2 sets of 24 cows in each phase. Using both GF and SF6 techniques, methane emission data were collected simultaneously during experimental wk 2, 6, and 12 (phase 1) and 2, 9, and 12 (phase 2), which corresponded to a total of 6 sampling periods. During each sampling period, 8 spot samples of gas emissions (staggered over a 3-d period) were collected from each cow using GF, as well as 3×24-h collections using the SF6 technique. Methane emission data were averaged per cow for the statistical analysis. The mean methane emission was 373 (standard deviation=96.3) and 405 (standard deviation=156) g/cow per day for GF and SF6, respectively. Coefficients of variation for the 2 methods were 25.8 and 38.6%, respectively; correlation and concordance between the 2 methods were 0.40 and 0.34, respectively. The difference in methane emission between the 2 methods (SF6 - GF) within treatment was from 46 to 144 and 24 to 27 g/d for phases 1 and 2, respectively. In the conditions of this experiment, the SF6 technique produced larger variability in methane emissions than the GF method. The overall difference between the 2 methods was on average about 8%, but was not consistent over time, likely influenced by barn ventilation and background methane and SF6 concentrations.

Incorporating mixed rations and formulated grain mixes into the diet of grazing cows: Effects on milk composition and coagulation properties, and the yield and quality of Cheddar cheese.

Effects of different strategies for feeding supplements to grazing dairy cows on the composition and coagulation properties of milk and the subsequent yield and quality of Cheddar cheese were measured. The experiment used milk from 72 Holstein-Friesian cows, averaging 45d in milk, fed according to 1 of 3 feeding strategies: (1) cows grazed a restricted allowance of perennial ryegrass pasture [approximately 14kg of dry matter (DM)/cow per day, to ground level] supplemented with milled wheat grain fed in the milking parlor and alfalfa hay offered in the paddock (control); (2) same pasture and allowance as control, supplemented with a formulated grain mix containing wheat grain, corn grain, and canola meal fed in the parlor and alfalfa hay fed in the paddock (FGM); or (3) same pasture and allowance as control, supplemented with a partial mixed ration comprising the same formulated grain mix but mixed with alfalfa hay and presented on a feed pad after each milking (PMR). For all strategies, supplements provided the same metabolizable energy and grain:forage ratio (78:22, DM basis). Within each feeding strategy, milk was sampled from cows receiving either 8 or 16kg (DM) of supplement/cow per day. There were 2 replicated groups of 6 cows per supplement amount per dietary strategy; approximately 250L of milk was sampled from each for analyses of composition and coagulation properties and the manufacture of Cheddar cheese. The experiment had a 14-d adaptation period and a 14-d measurement period. For cows fed according to the control strategy, those fed 16kg/cow per day produced milk with lower concentrations of milk fat than cows fed 8kg/cow per day. This effect was not observed for cows fed according to the FGM and PMR strategies. Milk from cows fed 16kg of DM/cow per day according to the control strategy yielded less Cheddar cheese than milk from cows fed according to the PMR strategy, with cheese yields from FGM cows being intermediate. Amount of supplement offered had minor effects on percentages of some fatty acids. We observed few other effects of feeding strategy on milk composition, types of milk protein, milk coagulation properties, or the composition and quality of the resultant Cheddar cheese. These data show that, compared with the traditional control strategy, feeding PMR or FGM may increase milk fat concentration and the subsequent yield of Cheddar cheese without compromising cheese composition or quality.

Response of plasma glucose, insulin, and nonesterified fatty acids to intravenous glucose tolerance tests in dairy cows during a 670-day lactation.

This experiment investigated the metabolic response of dairy cows undergoing an extended lactation to a frequently sampled intravenous glucose tolerance test. The experiment used 12 multiparous Holstein cows that calved in late winter in a seasonally calving pasture-based system and were managed for a 670-d lactation by delaying rebreeding. In each of four 5-wk experimental periods commencing at approximately 73, 217, 422, and 520 (±9.1) days in milk (DIM), cows were offered a diet of perennial ryegrass (73 and 422 DIM) or pasture hay and silage (217 and 520 DIM) supplemented with 1kg of DM grain (control; CON) or 6kg of DM grain (GRN) as a ration. Daily energy intake was approximately 160 and 215 MJ of metabolizable energy/cow for the CON and GRN treatments, respectively. At all other times, cows were managed as a single herd and grazed pasture supplemented with grain to an estimated minimum daily total intake of 180 MJ of metabolizable energy/cow. Cows were fitted with an indwelling jugular catheter during the final week of each experimental period. The standard intravenous glucose tolerance test using 0.3g of glucose per kilogram of body weight was performed on each cow at approximately 100, 250, 460, and 560 DIM. Plasma concentrations of glucose, insulin, and nonesterified fatty acids (NEFA) responses were measured. Milk yield, milk solids yield, body weight, and basal plasma glucose were greater in the GRN compared with the CON treatment. The area under the plasma response curve relative to baseline (AUC) for glucose, insulin, and NEFA and their apparent fractional clearance rates indicated varied whole body responsiveness to insulin in terms of glucose metabolism throughout the 670-d lactation. The glucose AUC 0 to 20 min postinfusion was increased at 560 DIM, indicating reduced utilization of glucose by the mammary gland at this stage of lactation. The NEFA clearance rate, 6 to 30 min postinfusion, was greater at 460 and 560 DIM. These data indicated an increase in lipogenic activity or a decrease in lipolysis as lactation progressed, suggestive of an overall increase in responsiveness to insulin in terms of whole body lipid metabolism as lactation progressed. These observations are consistent with decreased priority of lactation beyond 300 DIM. Cows in the GRN treatment had decreased whole body responsiveness to hyperglycemia compared with CON cows in terms of glucose clearance and AUC for the glucose response. Variation in the response curves of plasma glucose, NEFA, and insulin was predominantly a result of stage of lactation and not diet. This may be due to changes in mammary gland uptake of glucose that is independent of insulin and the responsiveness of peripheral tissues to the actions of insulin at different stages of the lactation that are independent of diet.

Grape marc reduces methane emissions when fed to dairy cows.

Grape marc (the skins, seeds, stalk, and stems remaining after grapes have been pressed to make wine) is currently a by-product used as a feed supplement by the dairy and beef industries. Grape marc contains condensed tannins and has high concentrations of crude fat; both these substances can reduce enteric methane (CH4) production when fed to ruminants. This experiment examined the effects of dietary supplementation with either dried, pelleted grape marc or ensiled grape marc on yield and composition of milk, enteric CH4 emissions, and ruminal microbiota in dairy cows. Thirty-two Holstein dairy cows in late lactation were offered 1 of 3 diets: a control (CON) diet; a diet containing dried, pelleted grape marc (DGM); and a diet containing ensiled grape marc (EGM). The diet offered to cows in the CON group contained 14.0kg of alfalfa hay dry matter (DM)/d and 4.3kg of concentrate mix DM/d. Diets offered to cows in the DGM and EGM groups contained 9.0kg of alfalfa hay DM/d, 4.3kg of concentrate mix DM/d, and 5.0kg of dried or ensiled grape marc DM/d, respectively. These diets were offered individually to cows for 18d. Individual cow feed intake and milk yield were measured daily and milk composition measured on 4d/wk. Individual cow CH4 emissions were measured by the SF6 tracer technique on 2d at the end of the experiment. Ruminal bacterial, archaeal, fungal, and protozoan communities were quantified on the last day of the experiment. Cows offered the CON, DGM, and EGM diets, ate 95, 98, and 96%, respectively, of the DM offered. The mean milk yield of cows fed the EGM diet was 12.8kg/cow per day and was less than that of cows fed either the CON diet (14.6kg/cow per day) or the DGM diet (15.4kg/cow per day). Feeding DGM and EGM diets was associated with decreased milk fat yields, lower concentrations of saturated fatty acids, and enhanced concentrations of mono- and polyunsaturated fatty acids, in particular cis-9,trans-11 linoleic acid. The mean CH4 emissions were 470, 375, and 389g of CH4/cow per day for cows fed the CON, DGM, and EGM diets, respectively. Methane yields were 26.1, 20.2, and 21.5g of CH4/kg of DMI for cows fed the CON, DGM, and EGM diets, respectively. The ruminal bacterial and archaeal communities were altered by dietary supplementation with grape marc, but ruminal fungal and protozoan communities were not. Decreases of approximately 20% in CH4 emissions and CH4 yield indicate that feeding DGM and EGM could play a role in CH4 abatement.

Investigating the effect of two methane-mitigating diets on the rumen microbiome using massively parallel sequencing.

Variation in the composition of microorganisms in the rumen (the rumen microbiome) of dairy cattle (Bos taurus) is of great interest because of possible links to methane emission levels. Feed additives are one method being investigated to reduce enteric methane production by dairy cattle. Here we report the effect of 2 methane-mitigating feed additives (grapemarc and a combination of lipids and tannin) on rumen microbiome profiles of Holstein dairy cattle. We used untargeted (shotgun) massively parallel sequencing of microbes present in rumen fluid to generate quantitative rumen microbiome profiles. We observed large effects of the feed additives on the rumen microbiome profiles using multiple approaches, including linear mixed modeling, hierarchical clustering, and metagenomic predictions. The effect on the fecal microbiome profiles was not detectable using hierarchical clustering, but was significant in the linear mixed model and when metagenomic predictions were used, suggesting a more subtle effect of the diets on the lower gastrointestinal microbiome. A differential representation analysis (analogous to differential expression in RNA sequencing) showed significant overlap in the contigs (which are genome fragments representing different microorganism species) that were differentially represented between experiments. These similarities suggest that, despite the different additives used, the 2 diets assessed in this investigation altered the microbiomes of the samples in similar ways. Contigs that were differentially represented in both experiments were tested for associations with methane production in an independent set of animals. These animals were not treated with a methane-mitigating diet, but did show substantial natural variation in methane emission levels. The contigs that were significantly differentially represented in response to both dietary additives showed a significant enrichment for associations with methane production. This suggests that these methane-mitigating diets have altered the rumen microbiome toward naturally low methane-emitting microbial profiles. The contig sequences are predominantly new and include Faecalibacterium spp. The contigs we have identified here are potential biomarkers for low-methane-emitting cattle.

Effects of feeding algal meal high in docosahexaenoic acid on feed intake, milk production, and methane emissions in dairy cows.

This study examined effects on milk yield and composition, milk fatty acid concentrations and methane (CH4) emissions when dairy cows were offered diets containing different amounts of algal meal. The algal meal contained 20% docosahexaenoic acid (DHA) and cows were offered either 0, 125, 250, or 375 g/cow per d of algal meal corresponding to 0, 25, 50, or 75 g of DHA/cow per d. Thirty-two Holstein cows in mid lactation were allocated to 4 treatment groups, and cows in all groups were individually offered 5.9k g of dry matter (DM) per day of concentrates [683 g/kg of cracked wheat (Triticum aestivum), 250 g/kg of cold-pressed canola, 46 g/kg of granulated dried molasses, and 21 g/kg of mineral mix] and ad libitum alfalfa (Medicago sativa) hay. The algal meal supplement was added to the concentrate allowance and was fed during the morning and afternoon milking, whereas the alfalfa hay was fed individually in pens. Cows were gradually introduced to their diets over 7d and then fed their treatment diets for a further 16d. Dry matter intake and milk yield were measured daily, and milk composition was measured on a sample representative of the daily milk yield on Thursday of each week. For the last 2d of the experiment, cows were individually housed in respiration chambers to allow measurement of CH4 emissions. Dry matter intake, milk yield and milk composition were also measured while cows were in the respiration chambers. Cows ate all their offered concentrates, but measured intake of alfalfa decreased with increasing dose of DHA by 16.2, 16.4, 15.1, and 14.3 kg of DM/d, respectively. Milk yield (22.6, 23.5, 22.6, and 22.6 kg/cow per d) was not affected by DHA dose, but milk fat concentrations (49.7, 37.8, 37.0, and 38.3g/kg) and, consequently, milk fat yields (1.08, 0.90, 0.83, and 0.85 kg/d) decreased with addition of DHA. The feeding of algal meal high in DHA was associated with substantial increases in the concentrations of DHA (0.04, 0.36, 0.60, and 0.91 g/100g of milk fatty acids) and conjugated linoleic acid C18:2 cis-9,trans-11 (0.36, 1.09, 1.79, and 1.87 g/100g of milk fatty acids). Addition of DHA did not affect total emissions of CH4 (543, 563, 553, and 520 g/cow per d), nor emissions in terms of milk production (24.9, 22.1, 24.3, and 23.4 g of CH4/kg of milk), but emissions were increased with respect to total intake (22.6, 23.5, 24.5, and 24.4 g of CH4/kg of DM). These findings indicate that CH4 emissions were not reduced when dairy cows were fed a forage-based diet supplemented with DHA from algal meal.