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This study aimed (1) to provide estimates of total mean retention times of milk replacer (MR), concentrates, and roughage in veal calves fed a mixed diet; (2) to determine the effect of level and type of solid feed (SF) on passage kinetics of MR, concentrates, and roughages in veal calves; and (3) to compare passage kinetics in veal calves using the fecal excretion curves of indigestible markers and a noninvasive 13C tracer breath test approach to determine whether the latter technique can serve as an alternative. At the start of the trial, 48 Holstein-Friesian calves (6 wk of age; 68 ± 7.7 kg of body weight; BW) were assigned to 1 of 4 dietary treatments (for statistical analysis, only 39 calf observations were used). Three treatments contained chopped wheat straw as roughage in the SF mixture in a concentrate:roughage ratio of 90:10 (dry matter basis). The SF level was 20 g/kg of metabolic BW per day (low straw), 30 g/kg of metabolic BW per day (middle straw), or 40 g/kg of metabolic BW per day (high straw). The fourth treatment (high hay) contained long perennial ryegrass hay as roughage in the SF mixture in a concentrate:roughage ratio of 70:30 (dry matter basis, at 40 g/kg of metabolic BW per day). The quantity of MR was fixed for the high straw treatment, whereas the amount of MR for the other treatments during the adaptation period was adjusted based on a pair gain strategy (i.e., exchanging ration components but keeping similar net energy). At the end of the adaptation period, calves ranged from 12 to 15 wk of age with an average BW of 123 ± 8.6 kg. Passage kinetics of concentrates were estimated by measuring 13C enrichment excess of CO2 in breath from a pulsed-dose of [1-13C]octanoate. Passage kinetics of roughage, concentrates, and MR were also estimated using fecal excretion curves obtained after ingestion of chromium-mordanted roughage, Yb2O3, and Co-EDTA, respectively. We conclude that [1-13C]octanoate cannot serve as a measure for oro-duodenal transit of concentrates because of unrealistic estimates. Based on the fecal excretion curves, we concluded that the total mean retention time of MR (i.e., time to peak; the moment that the excretion curve reaches peak concentration) was, on average, 12.4 h, and that the passage kinetics of MR was not affected by the level or type of SF. The mean retention time of concentrates was shorter (21.4 h) than that of both straw (59.1 h) and hay (36.8 h), and was not affected by the level or type of SF. Also, the mean retention time of the slowest compartment (i.e., the rumen) was shorter for concentrates (39.6 h) than that of straw (110.0 h) and hay (59.2 h). Contrary, the passage of roughage was affected by level and type of SF. Long hay increased time to peak by 22.3 h and decreased ruminal mean retention time by 50.8 h relative to chopped straw, indicating that the passage rate of long hay is faster than that of chopped straw. We conclude that the level and type of SF only affects the passage kinetics of roughage and not that of MR and concentrates.

Next to rumen acidosis, other forms of acidosis may also affect lactational performance of cows. Therefore, the effects of hindgut acidosis, induced via abomasal infusion of ground corn, and metabolic acidosis, induced via abomasal infusion of NH4Cl, were studied in cows in early lactation. Observations were made on intake and digestibility of nutrients, lactation performance, energy and N partitioning, blood acid-base status, and rumen and hindgut fermentation characteristics. In a 6 × 6 Latin square design, 6 rumen-fistulated, second-lactation Holstein-Friesian dairy cows (48 ± 17 d in milk) were subjected to 5 d of continuous abomasal infusions of water as control, or solutions of 2.5 mol of NH4Cl/d, 5.0 mol of NH4Cl/d, 3.0 kg of ground corn/d, or the combination of ground corn with either of the 2 NH4Cl levels, followed by 2 d of rest. Treatment solutions were administered via peristaltic pumps through infusion lines attached to the rumen cannula plug and an abomasal infusion line with a flexible disk (equipped with holes to allow digesta passage) to secure its placement through the sulcus omasi. A total mixed ration consisting of 70% grass silage and 30% concentrate (on dry matter basis) was fed at 95% of ad libitum intake of individual cows. The experiment was conducted in climate respiration chambers to determine feed intake, lactation performance, and energy and N balance. Abomasal infusion of NH4Cl affected the acid-base status of the cows, but more strongly when in combination with abomasal infusion of ground corn. Metabolic acidosis (defined as a blood pH < 7.40, blood HCO3 concentration < 25.0 mmol/L, and a negative base excess) was observed with 5.0 mol of NH4Cl/d, 3.0 kg of ground corn/d + 2.5 mol of NH4Cl/d, and 3.0 kg of ground corn/d + 5.0 mol of NH4Cl/d. Metabolic acidosis was associated with decreased milk lactose content, metabolic body weight, energy retained as protein, and fecal N excretion, and increased urine N excretion, and tended to decrease intake of nutrients. Digestibility of several nutrients increased with 5.0 mol of NH4Cl/d, likely as a result of decreased intake. Abomasal ground corn infusion resulted in hindgut acidosis, where fecal pH decreased from 6.86 without ground corn to 6.00 with ground corn, regardless of NH4Cl level. The decrease in fecal pH was likely the result of increased hindgut fermentation, evidenced by increased fecal volatile fatty acid concentrations. Hindgut acidosis was associated with decreased digestibility of nutrients, except for starch, which increased, and crude fat, which was not affected. No systemic inflammatory response was observed, suggesting that the hindgut epithelium was not severely affected by the more acidic conditions or barrier damage. Abomasal infusion of ground corn increased milk yield, milk protein and lactose yield, fecal N excretion, N use efficiency, and total energy retained as well as energy retained in fat, and reduced milk fat content and urine N excretion.

The aim of this study was to determine the methane (CH4) mitigation potential of 3-nitrooxypropanol and the persistency of its effect when fed to dairy cows in early lactation. Sixteen Holstein-Friesian cows (all multiparous; 11 cows in their second parity and 5 cows in their third parity) were blocked in pairs, based on actual calving date, parity, and previous lactation milk yield, and randomly allocated to 1 of 2 dietary treatments: a diet including 51 mg of 3-nitrooxypropanol/kg of dry matter (3-NOP) and a diet including a placebo at the same concentration (CON). Cows were fed a 35% grass silage, 25% corn silage, and 40% concentrate (on dry matter basis) diet from 3 d after calving up to 115 d in milk (DIM). Every 4 weeks, the cows were housed in climate respiration chambers for 5 d to measure lactation performance, feed and nutrient intake, apparent total-tract digestibility of nutrients, energy and N metabolism, and gaseous exchange (4 chamber visits per cow in total, representing 27, 55, 83, and 111 DIM). Feeding 3-NOP did not affect dry matter intake (DMI), milk yield, milk component yield, or feed efficiency. These variables were affected by stage of lactation, following the expected pattern of advanced lactation. Feeding 3-NOP did not affect CH4 production (g/d) at 27 and 83 DIM, but decreased CH4 production at 55 and 111 DIM by an average of 18.5%. This response in CH4 production is most likely due to the differences observed in feed intake across the different stages of lactation because CH4 yield (g/kg of DMI) was lower (on average 16%) at each stage of lactation upon feeding 3-NOP. On average, feeding 3-NOP increased H2 production and intensity 12-fold; with the control diet, H2 yield did not differ between the different stages of lactation, whereas with the 3-NOP treatment H2 yield decreased from 0.429 g/kg of DMI at 27 DIM to 0.387 g/kg of DMI at 111 DIM. The apparent total-tract digestibility of dry matter, organic matter, neutral detergent fiber, and gross energy was greater for the 3-NOP treatment. In comparison to the control treatment, 3-NOP did not affect energy and N balance, except for a greater metabolizable energy intake to gross energy intake ratio (65.4 and 63.7%, respectively) and a greater body weight gain (average 0.90 and 0.01% body weight change, respectively). In conclusion, feeding 3-NOP is an effective strategy to decrease CH4 emissions (while increasing H2 emission) in early lactation Holstein-Friesian cows with positive effects on apparent total-tract digestibility of nutrients.

The digestive physiology of ruminants is sufficiently different (e.g., with respect to mean retention time of digesta, digestibility of the feed offered, digestion, and fermentation characteristics)that caution is needed before extrapolating results from one type of ruminant to another. The objectives of the present study were (1)to provide an overview of some essential differences in rumen physiology between dairy cattle, beef cattle, and sheep that are related to methane (CH 4 )emission; and (2)to evaluate whether dietary strategies to mitigate CH 4 emission with various modes of action are equally effective in dairy cattle, beef cattle, and sheep. A literature search was performed using Web of Science and Scopus, and 94 studies were selected from the literature. Per study, the effect size of the dietary strategies was expressed as a proportion (%)of the control level of CH 4 emission, as this enabled a comparison across ruminant types. Evaluation of the literature indicated that the effectiveness of forage-related CH 4 mitigation strategies, including feeding more highly digestible grass (herbage or silage)or replacing different forage types with corn silage, differs across ruminant types. These strategies are most effective for dairy cattle, are effective for beef cattle to a certain extent, but seem to have minor or no effects in sheep. In general, the effectiveness of other dietary mitigation strategies, including increased concentrate feeding and feed additives (e.g., nitrate), appeared to be similar for dairy cattle, beef cattle, and sheep. We concluded that if the mode of action of a dietary CH 4 mitigation strategy is related to ruminant-specific factors, such as feed intake or rumen physiology, the effectiveness of the strategy differs across ruminant types, whereas if the mode of action is associated with methanogenesis-related fermentation pathways, the strategy is effective across ruminant types. Hence, caution is needed when translating effectiveness of dietary CH 4 mitigation strategies across different ruminant types or production systems.

This review evaluates the effects of silage characteristics on enteric methane (CH 4 ) emission from ruminants by performing a meta-analysis. A total of 17 studies were selected from the literature, and the relationship between CH 4 yield (g/kg dry matter [DM] intake) and silage characteristics was determined using a mixed model univariate regression procedure. For grass silage, organic matter digestibility (%; R 2 =0.74) and crude protein content (g/kg DM; R 2 =0.36) were negatively associated, and neutral detergent fibre (NDF) content (g/kg DM; R 2 =0.44) was positively associated with CH 4 yield. This indicates that increased grass silage quality consistently decreases CH 4 yield and may be an effective enteric CH 4 mitigation strategy. Similarly, optimizing maize silage quality appears to be an effective enteric CH 4 mitigation strategy, because NDF content (g/kg DM; R 2 =0.60) was positively associated with CH 4 yield. Upon replacing grass silage with maize silage, dietary starch content (g/kg DM; R 2 =0.62) and silage replacement level (%; R 2 =0.33) were negatively associated, and NDF content (g/kg DM; R 2 =0.34) was positively associated with CH 4 yield. These results indicate that replacing grass silage with maize silage consistently decreases CH 4 yield and may be an effective enteric CH 4 mitigation strategy. In contrast, replacement of alfalfa silage with maize silage was not associated with CH 4 yield and does not appear to be an effective strategy to decrease CH 4 yield. In conclusion, management practices to improve silage quality are a potent mitigation strategy to reduce enteric CH 4 emission per unit of feed fed to ruminants, and implications of silage quality have to be addressed when assessing greenhouse gas emissions in ruminant production.

Enteric methane (CH4 ) production is among the main targets of greenhouse gas mitigation practices for the dairy industry. A simple, robust and inexpensive measurement technique applicable on a large scale to estimate CH4 emission from dairy cattle would therefore be valuable. Milk fatty acids (MFA) are related to CH4 production because of the common biochemical pathway between CH4 and fatty acids in the rumen. A summary of studies that investigated the predictive power of MFA composition for CH4 emission indicated good potential, with predictive power ranging between 47% and 95%. Until recently, gas chromatography (GC) was the principal method used to determine the MFA profile, but GC is unsuitable for routine analysis. This has led to the application of mid-infrared (MIR) spectroscopy. The major advantages of using MIR spectroscopy to predict CH4 emission include its simplicity and potential practical application at large scale. Disadvantages include the inability to predict important MFA for CH4 prediction, and the moderate predictive power for CH4 emission. It may not be sufficient to predict CH4 emission based on MIR alone. Integration with other factors, like feed intake, nutrient composition of the feed, parity, and lactation stage may improve the prediction of CH4 emission using MIR spectra. © 2016 Society of Chemical Industry.

The objective of the present study was to characterize the rumen bacterial and archaeal communities in dairy cows fed different ratios of maize silage (MS) and grass silage (GS), and place the findings in the context of ruminal fermentation as well as previously reported methane (CH4) emissions. Rumen fluid from 12 rumen cannulated dairy cows was collected after 10 and 17 days of feeding one of four diets, all of which had the same roughage to concentrate ratio of 80:20 based on dry matter (DM). Roughage in the four diets (GS100, GS0, GS67, GS33) consisted of either 1000 g/kg DM GS (GS100), 1000 g/kg DM MS (GS0), or a mixture of both silages in different proportions [667 g/kg DM GS and 333 g/kg DM MS (GS67); 333 g/kg DM GS and 677 g/kg DM MS (GS33)]. Total volatile fatty acid (VFA) concentrations and the molar proportions of the ruminal VFA were not affected by diet. Only the molar proportion of isovalerate was affected by time, being lower on day 17 than on day 10. Bacterial and archaeal concentrations were not affected by diet but increased from day 10 to day 17. The bacterial community composition was affected by diet, time and diet × time, whereas the archaeal community composition was only affected by diet. Several bacterial and archaeal genus level groups were associated with diet, but not with time. Analysis indicated the increased use of hydrogen by succinate and lactate producing bacteria is likely to at least partially explain the previously reported lower CH4 emissions from MS fed dairy cows. Furthermore, time had a significant effect on both bacterial and archaeal concentrations, and also bacterial community composition. This indicates that the rumen microbiota had not stabilized after 10 days of feeding the experimental diets.

Enteric methane (CH4) is produced as a result of microbial fermentation of feed components in the gastrointestinal tract of ruminant livestock. Methane has no nutritional value for the animal and is predominately released into the environment through eructation and breath. Therefore, CH4 not only represents a greenhouse gas contributing to global warming, but also an energy loss, making enteric CH4 production one of the main targets of greenhouse gas mitigation practices for the dairy industry. Obviously, reduction of CH4 emission could be achieved by simply reducing livestock numbers. However, the global demand for dairy products has been growing rapidly and is expected to further grow in the future. Therefore, it is critical to minimize environmental impact to produce high-quality dairy products. The overall aim of this PhD research was, therefore, to develop a proxy for CH4 emission that can be measured in milk of dairy cows. There are currently a number of potentially effective dietary CH4 mitigation practices available for the livestock sector. The results of Chapter 3 show that replacing fiber-rich grass silage with starch-rich corn silage in a common forage-based diet for dairy cattle offers an effective strategy to decrease enteric CH4 production without negatively affecting dairy cow performance, although a critical level of starch in the diet seems to be needed. Little is known whether host genetics may influence the CH4 emission response to changes in diet. Therefore, the interaction between host DGAT1 K232A polymorphism with dietary linseed oil supplementation was evaluated in Chapter 7. The results of Chapter 7 indicate that DGAT1 K232A polymorphism is associated with changes in milk composition, milk N efficiency, and diet metabolizability, but does not affect digestibility and enteric CH4 emission, whereas linseed oil reduces CH4 emission independent of the DGAT1 K232A polymorphism. Accurate and repeatable measurements of CH4 emission from individual dairy cows are required to assess the efficacy of possible mitigation strategies. There are several techniques to estimate or measure enteric CH4 production of dairy cows, including climate respiration chambers, but none of these techniques are suitable for large scale precise and accurate measurements. Therefore, the potential of various metabolites in milk, including milk fatty acids (MFA), as a proxy (i.e., indicators or animal traits that are correlated with enteric CH4 production) for CH4 emission of dairy cows gained interest. Until recently, gas chromatography was the principal method used to determine the MFA profile, but this technique is unsuitable for routine analysis. This has led to the application of Fourier-transform infrared spectroscopy (FTIR) for determination of the MFA profile. Chapter 2 provides an overview of the recent research that relates MFA with CH4 emission, and discusses the opportunities and limitations of using FTIR to estimate, indirectly via MFA or directly, CH4 emission of dairy cattle. The recent literature on the relationship between MFA and CH4 emission gives inconsistent results. Where some studies found a clear and strong relation, other studies consider MFA to be unreliable predictors for CH4 emitted by dairy cows. Even the studies that do find a clear relation between MFA and CH4 emissions do not describe similar prediction models using the same MFA. These discrepancies can be the result of many factors, including dietary composition and lactation stage. Additionally, literature showed that the major advantages of using FTIR to predict CH4 emission include its simplicity and potential practical application on a large scale. Disadvantages include the inability to predict important MFA for the prediction of CH4 emission, and the moderate power of FTIR to directly predict CH4 emission. The latter was also demonstrated in Chapter 9, in which the CH4 prediction potential of MFA was compared with that of FTIR using data from 9 experiments (n = 218 individual cow observations) covering a broad range of roughage-based diets. The results indicate that MFA have a greater potential than FTIR spectra to estimate CH4 emissions, and that both techniques have potential to predict CH4 emission of dairy cows, but also limited current applicability in practice. Much focus has been placed on the relationship between MFA and CH4 emission, but milk also contains other metabolites, such as volatile and non-volatile metabolites. Currently, milk volatile metabolites have been used for tracing animal feeding systems and milk non-volatile metabolites were shown to be related to the health status of cows. In Chapter 4, the relationship between CH4 emission and both volatile and non-volatile metabolites was investigated, using data and milk samples obtained in the study described in Chapter 3. In general, the non-volatile metabolites were more closely related to CH4 emissions than the volatile metabolites. More specifically, the results indicate that CH4 intensity (g/kg fat- and protein-corrected milk; FPCM) may be related to lactose synthesis and energy metabolism in the mammary gland, as reflected by the milk non-volatile metabolites uridine diphosphate-hexose B and citrate. Methane yield (g/kg dry matter intake) on the other hand, may be related to glucogenic nutrient supply, as reflected by the milk non-volatile acetone. Based on the metabolic interpretations of these relationships, it was hypothesized that the addition of both volatile and non-volatile metabolites in a prediction model with only MFA would enhance its predictive power and, thus, leads to a better proxy in milk for enteric CH4 production of dairy cows. This was investigated in Chapter 5, again using data and milk samples described in Chapter 3. The results indicate that MFA alone have moderate to good potential to estimate CH4 emission. Furthermore, including volatile metabolites (CH4 intensity only) and non-volatile metabolites increases the CH4 emission prediction potential. The work presented in Chapters 3, 4 and 5, was based upon a small range of diets (i.e., four roughage-based diets in which grass silage was replaced partly or fully by corn silage) of one experiment. Therefore, in Chapter 6, the relationship between CH4 emission and the milk metabolome in dairy cattle was further quantified. Data (n = 123 individual cow observations) were used encompassing a large of roughage-based diets, with different qualities and proportions of grass, grass silage and corn silage. The results show that changes in individual milk metabolite concentrations can be related to the ruminal CH4 production pathways. These relationships are most likely the result from changes in dietary composition that affect not only enteric CH4 production, but also the profile of volatile and non-volatile metabolites in milk. Overall, the results indicate that both volatile and non-volatile metabolites in milk might provide useful information and increase our understanding of CH4 emission of dairy cows. However, the development of CH4 prediction models revealed that both volatile and non-volatile metabolites in milk hold little potential to predict CH4 emissions despite the significant relationships found between individual non-volatile metabolites and CH4 emissions. Additionally, combining MFA with milk volatile metabolites and non-volatile metabolites does not improve the CH4 prediction potential relative to MFA alone. Hence, it is concluded that it is not worthwhile to determine the volatile and non-volatile metabolites in milk in order to estimate CH4 emission of dairy cows. Overall, in comparison with FTIR, volatile and non-volatile metabolites, the MFA are the most accurate and precise proxy in milk for CH4 emission of dairy cows. However, most of MFA-based models to predict CH4 emission tend to be accurate only for the production system and the environmental conditions under which they were developed. In Chapter 8 it was demonstrated that previously developed MFA-based prediction equations did not predict CH4 emission satisfactory of dairy cows with different DGAT1 genotypes or fed diets with or without linseed oil. Therefore, the greatest shortcoming today of MFA-based CH4 prediction models is their lack of robustness. Additionally, MFA have restricted practical application, meaning that most MFA retained in the current CH4 prediction models cannot be determined routinely because of the use of gas chromatography. The MFA that can be determined with the use of infrared spectroscopy are however no promising predictors for CH4 emission. Furthermore, MFA have only a moderate CH4 prediction potential. This together suggests that it might not be the best option to focus in the future on MFA alone as a proxy for CH4 emission of dairy cows. The FTIR technique has a low to moderate CH4 prediction potential. However, FTIR has a great potential for practical high throughput application, facilitating repeated measurements of the same cow potentially reducing random noise. Results of this thesis also demonstrated that FTIR spectra do not have the potential to detect differences in CH4 emission between diets which are, in terms of forage level and quality, commonly fed in practice. Moreover, the robustness of FTIR spectra is currently unknown. Hence, it remains to be investigated whether FTIR spectra can predict CH4 emissions from dairy cows housed under different conditions from those under which the FTIR-based prediction equations were developed. It is therefore concluded that the accuracy and precision to predict CH4 emission using FTIR needs to increase, and the capacity of FTIR to evaluate the differences in CH4 emission between dairy cows and different types of diets needs to improve, in order to actually be a valuable proxy for CH4 emission of dairy cows.

Diurnal patterns of ruminal fermentation metabolites and microbial communities are not commonly assessed when investigating variation in ruminal CH4 production. The aims of this study were to monitor diurnal patterns of: (i) gaseous and dissolved metabolite concentrations in the bovine rumen, (ii) H2 and CH4 emitted, and (iii) the rumen microbiota. Furthermore, the effect of dietary inclusion of linseed oil on these patterns was assessed. Four rumen cannulated multiparous cows were used in a cross-over design with two 17 days periods and two dietary treatments: a control diet and a linseed oil supplemented diet [40% maize silage, 30% grass silage, 30% concentrate on dry matter (DM) basis for both diets; fat contents of 33 vs. 56 g/kg of DM]. On day 11, rumen contents were sampled for 10 h after morning feeding to profile gaseous and dissolved metabolite concentrations and microbiota composition. H2 and CH4 emission (mass per unit of time) was measured in respiration chambers from day 13 to 17. A 100-fold increase in ruminal H2 partial pressure (contribution to the total pressure of rumen headspace gases) was observed at 0.5 h after feeding. This peak was followed by a decline to basal level. Qualitatively similar patterns after feeding were also observed for H2 and CH4 emission, ethanol and lactate concentrations, and propionate molar proportion, although the opposite pattern was seen for acetate molar proportion. Associated with these patterns, a temporal biphasic change in the microbial composition was observed as based on 16S ribosomal RNA with certain taxa specifically associated with each phase. Bacterial concentrations (log10 16S ribosomal RNA gene copies based) were affected by time, and were increased by linseed oil supplementation. Archaeal concentrations (log10 16S ribosomal RNA gene copies based) tended to be affected by time and were not affected by diet, despite linseed oil supplementation decreasing CH4 emission, tending to decrease the partial pressure of CH4, and tending to increase propionate molar proportion. Linseed oil supplementation affected microbiota composition, and was most associated with an uncultivated Bacteroidales taxon. In summary, our findings support the importance of diurnal dynamics for the understanding of VFA, H2, and CH4 production.

Enteric methane (CH4 ) production is among the main targets of greenhouse gas mitigation practices for the dairy industry. A simple, robust and inexpensive measurement technique applicable on a large scale to estimate CH4 emission from dairy cattle would therefore be valuable. Milk fatty acids (MFA) are related to CH4 production because of the common biochemical pathway between CH4 and fatty acids in the rumen. A summary of studies that investigated the predictive power of MFA composition for CH4 emission indicated good potential, with predictive power ranging between 47% and 95%. Until recently, gas chromatography (GC) was the principal method used to determine the MFA profile, but GC is unsuitable for routine analysis. This has led to the application of mid-infrared (MIR) spectroscopy. The major advantages of using MIR spectroscopy to predict CH4 emission include its simplicity and potential practical application at large scale. Disadvantages include the inability to predict important MFA for CH4 prediction, and the moderate predictive power for CH4 emission. It may not be sufficient to predict CH4 emission based on MIR alone. Integration with other factors, like feed intake, nutrient composition of the feed, parity, and lactation stage may improve the prediction of CH4 emission using MIR spectra. © 2016 Society of Chemical Industry.