| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
ANIMAL PRODUCTION |
Agriculture and Agri-Food Canada, Research Centre, Lethbridge, AB, Canada
 |
Abstract |
|---|
 Top Abstract IntroductionExperimental ProceduresResultsDiscussionImplicationsLiterature Cited |
|---|
Key Words: Beef Cattle • Carbon Dioxide • Feed Additives • Greenhouse Gases • Methane
|
Introduction |
|---|
|
TopAbstractIntroductionExperimental ProceduresResultsDiscussionImplicationsLiterature Cited |
|---|
). For the cattle industry, decreasing CH4 losses can represent an improvement in feed efficiency. Thus, mitigating CH4 losses from cattle has both long-term environmental and short-term economic benefits.
Diet modifications can help mitigate CH4 emissions from cattle. Dietary manipulations reduce CH4 emissions by decreasing the fermentation of OM in the rumen, shifting the site of digestion from the rumen to the intestines, diverting H away from CH4 production during ruminal fermentation, or by inhibiting methanogenesis by ruminal bacteria (Johnson and Johnson, 1995; Benchaar et al., 2001).
Ionophores have been shown to decrease CH4 emissions from cattle, although effects may be transient (Johnson and Johnson, 1995). Furthermore, continued future use of antimicrobials in animal production is tenuous. Several alternative feed additives have been recently shown in vitro to reduce CH4 emissions, including organic acids (Asanuma et al., 1999), enzymes (Colombatto et al., 2003a), and yeast (Sacchararomyces cerevisiae; Mutsvangwa et al., 1992). However, there is limited information to demonstrate the effects of these additives in vivo. Some chemical compounds, such as methane inhibitors, have been demonstrated to reduce CH4 (Garcia- López et al., 1996; Miller and Wolin, 2001; Itabashi, 2002); however, these compounds are not approved in Canada.
The purpose of our study was to investigate the effect of several ingredients and feed additives that are currently registered for feeding to cattle on enteric CH4 production.
|
Experimental Procedures |
|---|
|
TopAbstractIntroductionExperimental ProceduresResultsDiscussionImplicationsLiterature Cited |
|---|
.
Experimental Design
The two experiments were each designed as a 4 x 4 Latin square. Each experiment used eight cattle fed four dietary treatments during four 21-d periods. The experiments were offset by 1 wk to facilitate measurements. During the first 16 d of each period, the cattle were housed in individual pens (4.9 x 1.8 m) bedded with straw in a sheltered barn. Daily feed intake and ruminal fermentation were measured during this phase. Before the morning feeding on d 17, the cattle were moved to four chambers for measurements of CH4, CO2, and total-tract digestibility. Two animals were housed in each chamber. The cattle were paired at the start of the experiment such that the total weight of cattle per chamber was similar. The pairing of animals was consistent throughout the experiment, such that animals within a chamber received the same treatment. The first day within the chambers was considered an adjustment period, allowing the steers to adapt before measurements were recorded for three consecutive 24-h days starting at midnight. On the morning of the last day of each period, the cattle were removed from the chambers and transported to their individual stalls in the barn. Interruptions to the chamber flux measurements occurred daily at 0730, when the floor was cleaned, when fecal samples were taken at 0930, when cattle were fed, and at 1530, when fecal samples were again taken.
Cattle, Diet, and Treatments
Sixteen Holstein steers weighing 311.6 ± 12.3 kg at the start of the experiment were used (eight steers per experiment). The cattle were selected for their temperament and then conditioned to the metabolism stalls over a period of several months before experimentation. This was done to minimize the stress on the cattle during the experiments.
During the experiments, the steers received a basal diet containing 75% whole crop barley silage, 19% steam-rolled barley, and 6% supplement (DM basis). Diet composition is shown in Table 1. The diet was formulated using NRC (1996) recommendations to contain 14% CP, and to meet or exceed the mineral and vitamin requirements of cattle gaining 1 kg/d.
|
). The level of fat added to the diet was close to the maximum range typically recommended for use in cattle diets (NRC, 2001). The source organism for the enzyme product was Bacillus licheniformis and the protease activity was determined to be 4,507 U/mL (SD = 161.0; n = 5). Protease activity was determined at pH 6.0 and 39°C (i.e., ruminal conditions) using 0.4% (wt/vol) azocasein as substrate (Bhat and Wood, 1989). Briefly, a reaction mixture containing 0.5 mL of azocasein, 0.5 mL of citrate-phosphate buffer, and 25 µL of enzyme (diluted 1:100 in distilled water) was incubated at 39°C for 15 min. The unhydrolyzed azocasein was precipitated by adding 80 µL of 25% (wt/vol) trichloroacetic acid and then removed by centrifugation (2,040 x g for 10 min at room temperature). A 0.5-mL supernatant sample was mixed with 0.5 mL of 0.5 M NaOH and the absorbance read at 420 nm against a reagent blank. Enzyme (no substrate) and substrate (no enzyme) blanks were also included for correction. One unit of protease activity was defined as the absorbance measured at 420 nm by the action of 10 µg of a standard protease (Streptomyces griseus, Type XIV, Sigma Chemicals, St. Louis, MO), assayed under identical conditions. The enzyme product contained negligible cellulase (using carboxymethylcellulose), xylanase (using xylan from birchwood), and 
-amylase (using soluble starch) activities when measured under ruminal conditions (39°C and pH 6.0). In Exp. 2, treatments were: control (no additive); Procreatin-7 yeast (SAF Agri; 4 g/d; Saccharomyces cerevisiae; 1.5 x 1010 cfu/g); Levucell SC yeast (Lallemand, Inc.; 1 g/d; Saccharomycces cerevisiae, strain CNCM I-1077; 2 x 1010 cfu units/g); and fumaric acid (Bartek Ingredients Inc.; 80 g/d). The feeding rates used for the yeast products were those recommended by the respective suppliers.
In both experiments, the treatments were hand mixed into the diet at the time of feeding. The basal diet was prepared daily using a feed mixer (Data Ranger, American Calan, Inc., Northwood, NH) and feed was offered once daily for ad libitum intake (at least 10% orts). Quantities of feed offered and refused were recorded daily for each animal. Samples of diet and refusals were retained weekly for determination of DM content. The DMI was calculated daily for each steer as the DM offered minus the DM refused.
Chamber Design
The calculation of CO2 and CH4 emissions was based on their respective concentration measurements associated with airflows into and out of each chamber. The chambers were 4.4 m wide x 3.7 m deep x 3.9 m tall (63.5 m3; model C1330, Conviron Inc., Winnipeg, Manitoba, Canada). Within each chamber, the animals were individually restrained in metabolism stalls that measured 2.5 m long x 0.9 m wide, elevated from the floor by 15 cm.
The ventilation of each chamber consisted of individual fresh-air intakes and chamber exhaust ducts (i.d. 30.5 cm), with dedicated fans in each duct. The air volume of each chamber was exchanged approximately every 5 min. Fresh intake air (0.28 m3/s) was fed directly into a sealed box containing a pair of fans (squirrel-type) that recycled the air inside the chamber (Figure 1). The recycled air entered the chamber through three raised floor vents running the length of the chamber, located between the animal stalls and between the stalls and walls of the chamber. The recycled air was filtered before leaving the chamber through vents above the stalls. Between the air filter located in the room and the low-pressure side of the recycling fans was a condenser unit that kept the recycled air at a constant temperature (15°C). The well-mixed air inside the chamber was essential to ensure a representative sample of air through the chamber exhaust duct (0.22 m3/s). An automated actuator device on each chamber, which normally allowed some fresh intake air to be diverted to the exhaust, was closed so that all fresh air entered the chamber.
|
Chamber Flow and Concentration Measurements
The air velocity (model 8330, TSI Inc., Shoreview, MN) and air temperature (thermocouple junction with shielded cable) were measured in the fresh-air intake and chamber exhaust ducts of each chamber. The air velocity measurements were made manually three times daily during the time the cattle were housed in the chambers. This was necessary to confirm the consistency of air exchange throughout the day. An average of five points across the diameter of each duct was used in characterizing air velocity.
The concentration (ppm, volume basis) of CO2 in the intake and exhaust ducts of each chamber was measured by pumping a sample of the air stream in each duct through infrared gas analyzers. Each chamber was equipped with a dedicated CO2 gas analyzer. For the first 5 min, the intake air stream was sampled for chambers 1 and 2 (using dedicated analyzers 1 and 2), whereas the other two analyzers (3 and 4) sampled the exhaust air stream of chambers 3 and 4. For the subsequent 5 min, the system was reconfigured so that analyzers 1 and 2 sampled the exhaust air stream, while analyzers 3 and 4 sampled intake air streams. In this manner, both the intake air and exhaust air were sampled in each chamber every 10 min using the same analyzer for each chamber. The CO2 concentration analog output from each analyzer was sampled every 5 s and the average recorded every 5 min using a datalogger (model CR23X, Campbell Scientific Inc., Logan, UT). Three of the CO2 analyzers (model LI-6262, LI-COR Inc., Lincoln, NE) also measured dew point temperature (Td) and were programmed to correct CO2 concentration for dilution and pressure broadening effects due to water vapor in the air stream. The fourth CO2 analyzer (model LI-6252, LI-COR Inc.) was not capable of monitoring H2O directly but was fed an analog Td signal from the companion analyzer. The CO2 concentration and Td measured by each analyzer required barometric pressure that was monitored with an external pressure transducer (model CS105 barometer, Vaisala Inc., Vantaa, Finland). The pressure transducer was wired to the datalogger that disseminated the barometric value via an analog signal back to each CO2 analyzer.
The concentrations (ppm) of CH4 for each chamber were monitored differently than those of CO2. In this case, only the fresh air intake concentration was sampled using an infrared gas analyzer (model Ultramat 5E, Siemens Inc., Karlsruhe, Germany) with a 0 to 50 ppm range. Air was pumped (1 LPM; model TD3LS7, Brailsford and Co., Inc., Rye, NY) sequentially from each of the chamber’s fresh-air intakes for 15 min, and the logger recorded the average concentration every 5 min. The first 5 min of each 15-min sampling interval was ignored because this corresponded to the time required by the analyzer to adjust to the new air stream concentration. The CH4 concentration of the chamber exhaust air was measured indirectly using an open path laser (GasView MC, Boreal Lasers Inc., Spruce Grove, Alberta, Canada) mounted inside each chamber between the animal stalls at 1.5 m above the central floor return-air vent. Exhaust methane concentration, measured periodically with the infrared methane analyzer, was regressed against chamber concentration, measured using the laser. A consistent relationship was found between each chamber’s CH4 concentration (well-mixed air) and each chamber’s exhaust air CH4 concentration (Table 2). These data showed a high degree of precision (Pearson correlation) and accuracy (Concordance correlation; Lin, 1995) between the chamber laser methane concentrations and that measured in the exhaust duct with the infrared methane analyzer. These corrections were applied to the chamber laser concentration data to derive exhaust concentration.
|
Flux Calculations
The CH4 emission generated for each chamber (FCH4; g/s) was calculated for each 10-min period from the fresh-air intake (i) and chamber exhaust (e) concentration (Ci and Ce, respectively; ppm) and mean weekly air velocity (Vi and Ve, respectively; m/s) data:
 |
where MW is the molecular weight of CH4 (16 g/mol), P is the barometric pressure (Pa), R is the universal gas constant (8.31 J•mol–1•deg K–1), T is the stream air temperature (°K), and A is the cross sectional area of the duct (0.146 m2). The T/P-value is a correction for the air velocity meter. The calculation of CO2 emissions (FCO2) for each chamber was determined using the same equation, where MW was 14 g/mol.
Errors in the emission calculation were associated with the measurement sensitivity of the gas concentration analyzers and the measurement sensitivity and temporal variability in air velocity within the intake and exhaust ducts. The open-path laser specified a sensitivity of ± 0.27 ppm, whereas that for the infrared gas analyzer was ± 0.25 ppm. The error in air velocity meter was ± 0.025 m/s, and the error in assuming constant airflow over 3-d measurement periods was ± 0.14 m/s. The probable error analysis of these individual terms in the flux equation indicates an overall error in flux estimates of 7%; however, these errors were consistent among chambers implying treatment sensitivity would be much greater.
Correction factors accounting for between-chamber differences were applied to all flux data, decreasing the chamber effect to a random effect in the statistical analysis. The correction factors were developed by releasing a controlled amount of pure CH4 from a gas cylinder at the same rate into each empty chamber (sequentially). The flux of CH4 from each chamber was determined when the exhaust concentration reached steady state. The test was conducted three times during the experiment, and the ratio of maximal flux (always chamber 4) to chamber flux was determined. The average correction factors relative to chamber 4 were 1.01, 1.14, 1.13, and 1.00 for chambers 1 to 4, respectively. These chamber corrections were also applied to the CO2 flux data. This procedure decreased the variability in emissions attributed to chambers to within 3%, and improved the sensitivity to treatment differences.
Ruminal Fermentation Measurements
Ruminal pH was measured once per animal on d 14 of the period 3.5 h after feeding. A rubber tube was inserted into the rumen via the esophagus and rumen contents (400 mL) removed using an electric pump. Samples were monitored visually to ensure they were not contaminated with saliva. The pH was measured immediately using a pH meter (Accumet model 25, Denver Instrument Co., Arvada, CO). The whole contents were squeezed through four layers of cheesecloth. Five milliliters of the filtrate was combined with 1 mL of 25% (wt/vol) of meta-phosphoric acid and stored frozen (–30°C) until VFA analysis.
Digestibility
Total-tract digestibility of nutrients was determined using an external marker. The marker was prepared using chromic oxide and ground barley. Ten grams of marker, providing approximately 2 g of Cr, was top dressed once daily onto the feed the last 10 d of each period. In all cases, the entire allotment of marker was consumed. A representative sample of the marker was retained each period for Cr analysis. Fecal samples (100 g wet weight) were collected twice daily during the last 4 d of each period. During this time, the cattle were housed in metabolism stalls within the chambers; thus, the samples were obtained from the rectum of each animal or from the floor when rectal samples were not available. Fecal samples were composited by steer and period as collected, and immediately frozen. The pooled samples were later dried at 55°C for 48 h in a forced-air oven, ground through a 1-mm screen, and analyzed for analytical DM, GE, NDF, ADF, and Cr. An additional fecal sample (100 g wet weight) was also taken from each animal before dosing the marker each period. These samples were analyzed for DM and Cr. The Cr concentration in the feces taken predosing was used to adjust for residual marker excretion. The Cr concentration in fecal samples obtained before dosing was in all cases less than 1% of the Cr concentration in the fecal samples composited by period; thus, this adjustment was trivial. Chromium was assumed to be completely indigestible and the digestibility of DM was calculated as follows:
 |
where DMI was the DM consumed on the same days that fecal samples were collected. Digestibility of GE, NDF, and ADF was calculated using the same approach.
Chemical Analyses
All chemical analyses were performed on each sample in duplicate, and where the coefficient of variation for the replicate analysis was > 5%, the analysis was repeated.
Ruminal VFA were quantified using colonic acid as the internal standard, and gas chromatography (model 5890, Hewlett Packard, Little Falls, DE) with a capillary column (30 m x 0.25 mm i.d., 1 µm phase thickness, bonded polyethylene glycol, Supelco Nukol, Sigma-Ald-rich Canada, Oakville, Ontario, Canada), and flame ionization detection. The oven temperature was 100°C for 1 min, which was then ramped by 20°C/min to 140°C, and then by 8°C/min to 200°C/min, and held at this temperature for 5 min. The injector temperature was 200°C, the detector temperature was 250°C, and the carrier gas was helium.
Analytical DM was determined by drying the samples at 135°C for 2 h, followed by hot weighing. The OM content was calculated as the difference between 100 and the percentage of ash (AOAC, 1995; Method 942). Gross energy was determined using an adiabatic calorimeter (model 1241, Parr, Moline, IL). The NDF and ADF were determined in the ANKOM200 fiber analyzer (Ankom Technology Corp., Fairport, NY) using heat stable -amylase and sodium sulfite. For the measurement of CP (N x 6.25), samples were ground using a ball mill (Mixer Mill MM2000; Retsch, Haan, Germany) to a fine powder. Nitrogen was quantified by flash combustion with gas chromatography and thermal conductivity detection (Carlo Erba Instruments, Milan, Italy). Chromium, Ca and P were determined by inductively coupled plasma emission spectrometry (SpectoCirosCCD, Specto Analytical Instruments, GmbH & Co., Kleve, KG, Germany) after dry ashing and extraction of the respective mineral.
Calculations and Statistical Analyses
Cumulative daily CH4 emissions from each chamber were calculated for 3 d each period. The daily CH4 flux (13.3 Mcal/kg CH4) determined for each chamber was expressed as a proportion of GE intake and DE intake of the two cattle within the chamber on that same day. The daily CH4 flux was also expressed per unit of DMI for the two cattle within the chamber on that same day.
One animal fed the Levucell SC yeast in Period 3 went off-feed while in the chamber. Thus, for Period 3, the gas emission data for this chamber were removed from the analysis. Data were analyzed for each experiment with the mixed model procedure of SAS (SAS Inst., Inc., Cary, NC). The individual animal was the experimental unit for intake, digestibility, and ruminal fermentation variables because these data were obtained from individual animals with separate access to the feed. The chamber, representing data for two animals, was the experimental unit for CH4 and CO2 measurements. The model for intake, digestibility, and ruminal fermentation variables included the fixed effects of treatment. Animal and period were considered as random effects and the restricted maximum likelihood method was used to estimate the variance components. The model used for CH4 measurements included the fixed effect of treatment, and the random effects of period and chamber, with day of sampling (1 to 3) within each period treated as a repeated measure. Differences among means were tested using a protected (P < 0.05) LSD test. Treatment effects were declared significant at P < 0.05 and trends were discussed at P < 0.15.
|
Results |
|---|
|
TopAbstractIntroductionExperimental ProceduresResultsDiscussionImplicationsLiterature Cited |
|---|
) and 8.89 kg/d for those in Exp. 2 (Table 4). Overall, treatments had no effect (P = 0.11) on DMI, although there was a trend for higher intake when the animals were fed enzyme or monensin compared with the control diet (Table 3). Moving the steers to the chambers decreased intake by 15% in Exp. 1 (Table 5) and by 19% in Exp. 2 (Table 6), such that intake averaged 7.54 and 7.16 kg/d, respectively. It is speculated that the drop in intake when steers were moved from individual pens to metabolic stalls in chambers was due to the stress associated with the change in environment, as well as the decreased energy expenditure due to the decreased activity of the cattle during the time they were in the metabolic stalls. Once in the chambers, steers receiving Levucell SC yeast had lower (P = 0.02) DMI than the control group, but the intake of the cattle fed the other treatments was not different (P > 0.05) from the control group (Table 6).
|
|
|
|
). Although there were no differences in total VFA concentration (mean of 76.7 mM) among treatments in Exp. 1, proportions of individual VFA differed. Steers fed either monensin or sunflower oil had higher (P = 0.03) concentrations of propionate and lower (P = 0.01) concentrations of acetate than those in the control group. Consequently, acetate:propionate ratios averaged 3.06 for the monensin treatment and 3.10 for the oil treatment compared with 3.75 for the control group (P < 0.05). Concentrations of acetate, propionate, and acetate:propionate ratio were intermediate (P > 0.05) for the steers receiving enzyme. In addition, branch chain VFA and iso-valerate concentrations were higher (P < 0.05), and caproate concentration was lower (P = 0.001), for steers receiving monensin or oil than for those in the control group. The yeast and fumaric acid treatments used in Exp. 2 had no effect on ruminal pH or VFA (Table 4).
Digestibility
Supplementing the diet with sunflower oil increased the intake of GE by 1.5 Mcal/d (P = 0.29) compared with the control, but this difference was not statistically significant (Table 5). However, intakes of NDF and ADF tended (P = 0.06) to be lower for animals fed oil because of the dilution effect of adding 5% oil to the diet.
Adding oil to the diet had a negative effect on fiber digestion. Compared with the Control, the NDF digestibility was decreased by 23% (P = 0.03), and ADF digestibility was reduced by 29% (P = 0.06) as the result of feeding oil. Digestibilities of DM (P = 0.14) and GE (P = 0.15) for cattle fed oil were numerically lower but not different than for the control.
Supplementing the diet with proteolytic enzyme decreased (P = 0.05) digestibility of DM in the total tract by 8%. This was mostly the result of a reduction in fiber digestibility. The NDF digestibility of cattle fed enzymes was 14% lower (P = 0.10) and ADF digestibility was 15% lower (P = 0.22) than for control animals, although these differences were not statistically significant.
Monensin had no effect on tract digestibility of nutrients. Furthermore, the yeast and fumaric acid treatments used in Exp. 2, had no effect on digestibility of nutrients in the total tract (Table 6).
Methane Emissions
Before correcting CH4 emissions for DMI or energy intake (Table 7), sunflower oil reduced (P = 0.001) CH4 by 22% compared with the control (Exp. 1). In contrast, monensin (P = 0.44) and enzyme (P = 0.82) had no effect on CH4 emissions. When CH4 emissions were corrected for differences in feed intake, the effect of sunflower oil on lowering (P = 0.006) CH4 emissions was maintained. Monensin also tended (P = 0.08) to lower CH4 emissions per kilogram of DMI by 8.6% compared with the control due to numerically higher intake and numerically lower CH4 emissions.
|
The yeast and fumaric acid treatments used in Exp. 2 had no effect (P > 0.05) on CH4 emissions (Table 8). The CH4 emissions per kilogram of DMI (P = 0.39) and as a percentage of GE intake (P = 0.39) were not significantly different for steers fed Procreatin-7 yeast compared with control steers (3% less CH4 per kilogram of DMI and 3% less GE intake was lost as CH4).
|
|
Discussion |
|---|
|
TopAbstractIntroductionExperimental ProceduresResultsDiscussionImplicationsLiterature Cited |
|---|
). Actual growth rate during the study averaged 0.92 ± 0.10 kg/d for steers in Exp. 1 and 0.83 ± 0.15 kg/d for those in Exp. 1. Effects of treatments on gain were not reported as they were thought not to be representative of the commercial situation because the animals were restrained while in the chambers.
For cattle fed the control diet, about 6.5% of the ingested energy was lost as CH4. These data confirm the report by Johnson and Johnson (1995) that feedlot cattle fed backgrounding-type diets and replacement cattle fed high forage diets typically lose 6 to 6.5% of their ingested energy as CH4.
Adding sunflower oil to the diet substantially decreased CH4 emissions, corroborating numerous previous studies that reported reduced CH4 emissions using other types of fats (Machmüller and Kreuzer, 1999; Dohme et al., 2000). Adding fat to ruminant diets has been shown to decrease CH4 losses mainly by decreasing ruminally fermentable substrate, but also by providing an alternative H sink in the rumen and by inhibiting protozoa (Johnson and Johnson, 1995). In our study, adding sunflower oil to the diet clearly decreased ruminal fermentability of the fiber as evidenced by lower acetate concentration, higher propionate concentration, and a lower acetate:propionate ratio. Total-tract digestibility of fiber was also substantially reduced, even though decreases in total tract fiber digestion are usually not as severe as reductions in ruminal fiber digestion. Thus, although ruminal fiber digestion was not measured directly in this study, other variables indicated considerable reduction in ruminal fiber digestion. The reduction in ruminal fiber digestion likely accounted for a large proportion of the reduction in CH4 emissions. Decreased fiber digestion due to added fat was reported previously for high levels of added fat (Jenkins, 1993). The mechanism for reduced fiber digestibility due to added fat may be related to the process of hydrogenation of the unsaturated fatty acids in the rumen. If the ability of the microorganisms to saturate the fatty acids is exceeded, then unsaturated fatty acids accumulate and interfere with microbial digestion (NRC, 2001). In our study, the DE content of the diet was not increased by the addition of 5% fat because the additional DE supplied by the oil was offset by the decrease in fiber digestion. Based on our results, adding sunflower oil to the diet can be used to decrease CH4 emissions, but total energy intake may not be increased because of negative effects on fiber use.
Monensin also tended to lower CH4 emissions, albeit to a lesser extent than sunflower oil. Ionophores such as monensin are typically used in commercial feedlot cattle diets to modulate intake, control bloat, and improve feed efficiency (Elanco Animal Health, 2003). In this study, monensin did not lower feed intake, but the decreased concentration of acetate, increased concentrate of propionate, and reduced actetate:propionate ratio were consistent with the known mode of action of monensin (Schelling, 1984). The approximately 9% decrease in CH4 emissions as a proportion of GE observed for monensin in this study is within the range (slight to 25%) reported previously (Johnson and Johnson, 1995). Several recent studies have reported that the effects of monensin on CH4 emissions are short-lived, as reviewed by Johnson and Johnson (1995). Our results confirm that monensin in a high-forage diet is a viable strategy to decrease CH4 emissions in the short term; however, a feeding trial of greater length is required to determine the long-term effect of monensin on CH4 emissions.
No other treatment significantly affected CH4 emissions, although the 3% decrease in feed energy lost as CH4 observed for cattle fed Procreatin-7 yeast was noteworthy. Although this reduction in CH4 was small and not statistically significant, the cost of feeding yeast was considerably less than the cost of feeding sunflower oil (i.e., approximately one-seventh). In this case, the decrease in energy lost as CH4 was the result of slightly higher feed intake combined with similar CH4 emissions compared with the control group. The means by which this yeast product might have decreased the proportion of feed energy lost as CH4 is not certain, but was likely due to a shift in specific microbial populations within the overall community in the rumen (Newbold et al., 1996). There is some limited work to suggest that live yeast cells can stimulate the use of H by acetogenic strains of ruminal bacteria, thereby enhancing the formation of acetate and decreasing the formation of CH4 (Chaucheyras et al., 1995). However, in our study, there were no differences in VFA concentrations, suggesting that any possible changes in microbial fermentation were too subtle to elicit a change in VFA concentrations.
The different response observed for the two yeast products used in this study is not surprising. It is well known that the effects of yeast are strain-dependent (Newbold et al., 1996). The two products used in our study differed in strain of Saccharomyces cerevisiae used, as well as the number of yeast cells supplemented. Although the Procreatin-7 yeast had no effect on ruminal fermentation or digestibility, it coincided with slightly higher feed intake of cattle inside the chambers during CH4. This finding lends support to the anecdotal evidence observed commercially that yeast can have a positive influence on feed intake and is useful in decreasing the effects of stress on feed intake in unadapted cattle.
The enzyme product used in this study was not effective in reducing CH4 losses. Colombatto et al. (2003a) reported that in continuous culture, supplementing a diet based on alfalfa hay, corn silage, and rolled corn with a proteolytic enzyme enhanced ruminal fiber digestion without increasing CH4 emissions. Those findings contrast with the observations in the current study, in which proteolytic enzyme had no effect on total-tract fiber digestibility. The differences between studies are attributed to the differences in diets used. The key enzyme activities required to increase fiber digestion depend on the composition of the diet on which the enzymes are expected to act (Colombatto et al., 2003b). Thus, a particular enzyme formulation is not likely to be effective for all diets. Although protease enzyme was found to be useful in enhancing degradability of alfalfa fiber (Colombatto et al., 2003a), the results from this study suggest this is not the case for barley silage. Similarly, Colombatto et al. (2003b) reported that the enzyme products that increased degradation of alfalfa hay were not the same ones that increased degradation of corn silage.
Fumarate is a direct metabolic precursor of propionate, and thus, it has the potential to decrease methane emissions by directing H into succinate rather than into methane (López et al., 1999). However, at the level of supplementation used in our study, fumaric acid was not effective in reducing CH4 losses. This finding contrasts to in vitro (Asanuma et al., 1999; López et al. 1999) and in vivo (Bayaru et al. 2001) studies that reported fumaric acid decreased CH4. It is possible that a higher level of supplementation than that used in the current study would be needed to alter CH4 production in vivo. It is estimated that the level of supplementation in this study provided about 15 mM of fumaric acid (assuming a ruminal volume of 40 L; 116.07 g/mol), although these calculations do not account for fluid dilution rate and passage of fumaric acid from the rumen in vivo, factors that do not occur in vitro. In vitro, López et al. (1999) used up to 10 mM, and Asanuma et al. (1999) used up to 30 mM. In vivo, Bayaru et al. (2001) fed about twice the amount of fumaric acid (20 g/kg DMI) to cattle as that used in the current study (12 g/kg DMI) and, surprisingly, methane production decreased by 23%. However, in that study, only two animals per treatment were used, and CH4 measurements were made using ventilated hoods, which are known to be problematic.
The lack of an effect of fumaric acid on CH4 emissions was consistent with the lack of effect on VFA, notably propionate proportions. The lack of an effect of fumaric acid on ruminal pH was expected because of the high-forage diet used. Previous studies have shown that organic acids can be beneficial in promoting higher ruminal pH and lactate uptake by ruminal organisms when high-grain diets are fed (Martin et al., 1999). However, with high-forage diets, lactate production in the rumen is minimal; thus, organic acids are not expected to affect ruminal pH.
The daily CO2 emission averaged 3.44 kg per animal in our experiments, similar to the average CH4 emission of 3.77 kg per animal, expressed as CO2 equivalent (using a warming potential of 23 for CH4 relative to CO2). Our CO2 emissions were similar to the 3.2 kg of CO2•animal–1•d–1 reported by Kinsman et al. (1995) for dairy cows housed in a closed ventilated barn equipped with instruments to directly measure CO2. However, our CO2 emissions are greater than the 1.0 and 1.3 kg of CO2•animal–1•d–1 (using a conversion factor of 1,870 L/kg) reported for yearling beef heifers by Boadi et al. (2002). The discrepancy between CO2 emissions reported in our study and those reported by Boadi et al. (2002) is probably a reflection of the techniques used. Boadi et al. (2002) used open-circuit calorimetry, which consisted of a ventilated hood that enclosed the animal’s head, as well as the sulfur hexafluoride tracer gas technique. Estimates of CO2 emissions were 20% lower using the hoods compared with the tracer technique, but both techniques were considered highly variable. Despite CO2 emissions being large, the respired CO2 by livestock is not reported by the Intergovermental Panel on Climate Change (2001), presumably because it is a rerelease of CO2 recently captured by photosynthesis. Over our two experiments, an average loss of carbon as CO2 and CH4 amounted to 1.97 kg of C•animal–1•d–1.
In summary, approximately 6.5% of the GE consumed by growing cattle fed a high-forage, back-grounding diet is lost as CH4. Several feed additives and ingredients that are currently registered for feeding to cattle can be used to reduce the proportion of GE lost as CH4. Methane emissions, expressed as a percentage of GE, were decreased by 21% using sunflower oil and by 9% using Rumensin. Additionally, one of the yeast products examined numerically decreased CH4, as a percentage of GE, by 3%. However, it must be acknowledged that this study was short-term, and that typical production scenarios would not entail 3-wk feeding periods. It has been documented previously that that the effectiveness of treatments, such as ionophores, in lowering CH4 can diminish over time (Johnson and Johnson, 1995). However, the objective of this study was to identify additives and feed ingredients that were effective, at least in the short-term, in decreasing CH4 emissions. The long-term effect of compounds identified in this study will be examined in subsequent research.
|
Implications |
|---|
|
TopAbstractIntroductionExperimental ProceduresResultsDiscussionImplicationsLiterature Cited |
|---|
|
Footnotes |
|---|
3 Present address: Departamento de Producción Animal, Facultad de Agronomía, Universidad de Buenos Aires, Av. San Martín 4453 (C1417DSQ), Buenos Aires, Argentina (e-mail: colombat{at}agro.uba.ar).
2 Correspondence: Box 3000, 5403 1st Ave. South (phone: 403-327-4561; fax: 403-317-2182; e-mail: mcginn{at}agr.gc.ca; beauchemin{at}agr.gc.ca).
Received for publication January 15, 2004. Accepted for publication July 7, 2004.
|
Literature Cited |
|---|
|
TopAbstractIntroductionExperimental ProceduresResultsDiscussionImplicationsLiterature Cited |
|---|
This article has been cited by other articles:
|
|
 |
|
  E. Kebreab, K. A. Johnson, S. L. Archibeque, D. Pape, and T. Wirth Model for estimating enteric methane emissions from United States dairy and feedlot cattle J Anim Sci, October 1, 2008; 86(10): 2738 - 2748. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. Grainger, M. J. Auldist, T. Clarke, K. A. Beauchemin, S. M. McGinn, M. C. Hannah, R. J. Eckard, and L. B. Lowe Use of Monensin Controlled-Release Capsules to Reduce Methane Emissions and Improve Milk Production of Dairy Cows Offered Pasture Supplemented with Grain J Dairy Sci, March 1, 2008; 91(3): 1159 - 1165. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 G. Fonty, K. Joblin, M. Chavarot, R. Roux, G. Naylor, and F. Michallon Establishment and Development of Ruminal Hydrogenotrophs in Methanogen-Free Lambs Appl. Envir. Microbiol., October 15, 2007; 73(20): 6391 - 6403. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
E. M. Ungerfeld, R. A. Kohn, R. J. Wallace, and C. J. Newbold A meta-analysis of fumarate effects on methane production in ruminal batch cultures J Anim Sci, October 1, 2007; 85(10): 2556 - 2563. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. L. Ellis, E. Kebreab, N. E. Odongo, B. W. McBride, E. K. Okine, and J. France Prediction of Methane Production from Dairy and Beef Cattle J Dairy Sci, July 1, 2007; 90(7): 3456 - 3466. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J.-S. Eun and K. A. Beauchemin Enhancing In Vitro Degradation of Alfalfa Hay and Corn Silage Using Feed Enzymes J Dairy Sci, June 1, 2007; 90(6): 2839 - 2851. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
E. Pavan, S. K. Duckett, and J. G. Andrae Corn oil supplementation to steers grazing endophyte-free tall fescue. I. Effects on in vivo digestibility, performance, and carcass traits J Anim Sci, May 1, 2007; 85(5): 1330 - 1339. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
N. E. Odongo, R. Bagg, G. Vessie, P. Dick, M. M. Or-Rashid, S. E. Hook, J. T. Gray, E. Kebreab, J. France, and B. W. McBride Long-Term Effects of Feeding Monensin on Methane Production in Lactating Dairy Cows J Dairy Sci, April 1, 2007; 90(4): 1781 - 1788. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
K. A. Beauchemin and S. M. McGinn Methane emissions from beef cattle: Effects of fumaric acid, essential oil, and canola oil J Anim Sci, June 1, 2006; 84(6): 1489 - 1496. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. D. Nkrumah, E. K. Okine, G. W. Mathison, K. Schmid, C. Li, J. A. Basarab, M. A. Price, Z. Wang, and S. S. Moore Relationships of feedlot feed efficiency, performance, and feeding behavior with metabolic rate, methane production, and energy partitioning in beef cattle J Anim Sci, January 1, 2006; 84(1): 145 - 153. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J.-S. Eun and K. A. Beauchemin Effects of a Proteolytic Feed Enzyme on Intake, Digestion, Ruminal Fermentation, and Milk Production J Dairy Sci, June 1, 2005; 88(6): 2140 - 2153. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
K. A. Beauchemin and S. M. McGinn Methane emissions from feedlot cattle fed barley or corn diets J Anim Sci, March 1, 2005; 83(3): 653 - 661. [Abstract] [Full Text] [PDF]
|
|
| ||
