33 research outputs found
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Effect of Mootral™ – a garlic and citrus extract based feed additive - on enteric methane emissions in feedlot cattle
Enteric methane (CH4) production is the main source of greenhouse gas emissions from livestock globally with beef cattle contributing 5.95% of total global greenhouse gas emissions. Various mitigation strategies have been developed to reduce enteric emissions with limited success. In vitro studies have shown a reduction in CH4 emissions when using garlic and citrus extracts. However, there is paucity of data regarding in vivo studies investigating the effect of garlic and citrus extracts in cattle. The objective of this study was to quantitatively evaluate the response of Angus Ă— Hereford cross steers consuming the feed additive Mootral, which contains extracts of both garlic and citrus, on CH4 yield (g/kg dry matter intake [DMI]). Twenty steers were randomly assigned to two treatments: control (no additive) and Mootral supplied at 15 g/d in a completely randomized design with a 2-wk covariate and a 12-wk data collection periods. Enteric CH4 emissions were measured using the GreenFeed system during the covariate period and experimental weeks 2, 6, 9, and 12. CH4 yield (g/kg DMI) by steers remained similar in both treatments for weeks 2 to 9. In week 12, there was a significant decrease in CH4 yield (23.2%) in treatment compared to control steers mainly because the steers were consuming all the pellets containing the additive. However, overall CH4 yield (g/kg DMI) during the entire experimental period was not significantly different. Carbon dioxide yield (g/kg DMI) and oxygen consumption (g/kg DMI) did not differ between treatments during the entire experimental period. DMI, average daily gain, and feed efficiency also remained similar in control and supplemented steers. The in vivo results showed that Mootral may have a potential to be used as a feed additive to reduce enteric CH4 production and yield in beef cattle but needs further investigation under various dietary regimen
Bayesian mechanistic modeling of thermodynamically controlled volatile fatty acid, hydrogen and methane production in the bovine rumen
Dynamic modeling of mechanisms driving volatile fatty acid and hydrogen production in the rumen microbial ecosystem contributes to the heuristic prediction of CH4 emissions from dairy cattle into the environment. Existing mathematical rumen models, however, lack the representation of these mechanisms. A dynamic mechanistic model was developed that simulates the thermodynamic control of hydrogen partial pressure (pH2 ) on volatile fatty acid (VFA) fermentation pathways via the NAD+ to NADH ratio in fermentative microbes, and methanogenesis in the bovine rumen. This model is unique and closely aligns with principles of reaction kinetics and thermodynamics. Model state variables represent ruminal carbohydrate substrates, bacteria and protozoa, methanogens, and gaseous and dissolved fermentation end products. The model was extended with static equations to model the hindgut metabolism. Feed composition and twice daily feeding were used as model inputs. Model parameters were estimated to experimental data using a Bayesian calibration procedure, after which the uncertainty of the parameter distribution on the model output was assessed. The model predicted a marked peak in pH2 after feeding that rapidly declined in time. This peak in pH2 caused a decrease in NAD+ to NADH ratio followed by an increased propionate molar proportion at the expense of acetate molar proportion, and an increase in CH4 production that steadily decreased in time, although the magnitude of increase for CH4 emission was less than for pH2 . A global sensitivity analysis indicated that parameters that determine the fractional passage rate and NADH oxidation rate altogether explained 86% of the variation in predicted daily CH4 emission. Model evaluation indicated over-prediction of in vivo CH4 emissions shortly after feeding, whereas under-prediction was indicated at later times. The present rumen fermentation modeling effort uniquely provides the integration of the pH2 controlled NAD+ to NADH ratio for dynamically predicting metabolic pathways that yield VFA, H2 and CH4.</p
Smoothing spline assessment of the accuracy of enteric hydrogen and methane production measurements from dairy cattle using various sampling schemes
ABSTRACT: Estimating daily enteric hydrogen (H2) and methane (CH4) emitted from dairy cattle using spot sampling techniques requires accurate sampling schemes. These sampling schemes determine the number of daily samplings and their intervals. This simulation study assessed the accuracy of daily H2 and CH4 emissions from dairy cattle using various sampling schemes for gas collection. Gas emission data were available from a crossover experiment with 28 cows fed twice daily at 80% to 95% of the ad libitum intake, and an experiment that used a repeated randomized block design with 16 cows twice daily fed ad libitum. Gases were sampled every 12 to 15 min for 3 consecutive days in climate respiration chambers. Feed was fed in 2 equal portions per day in both experiments. Per individual cow-period combination, generalized additive models were fitted to all diurnal H2 and CH4 emission profiles. Per profile, the models were fitted using the generalized cross-validation, REML, REML while assuming correlated residuals, and REML while assuming heteroscedastic residuals. The areas under the curve (AUC) of these 4 fits were numerically integrated over 24 h to compute the daily production and compared with the mean of all data points, which was considered the reference. Next, the best of the 4 fits was used to evaluate 9 different sampling schemes. This evaluation determined the average predicted values sampled at 0.5, 1, and 2 h intervals starting at 0 h from morning feeding, at 1 and 2 h intervals starting at 0.5 h from morning feeding, at 6 and 8 h intervals starting at 2 h from morning feeding, and at 2 unequally spaced intervals with 2 or 3 samples per day. Sampling every 0.5 h was needed to obtain daily H2 productions not different from the selected AUC for the restricted feeding experiment, whereas less frequent sampling had predictions varying from 47% to 233% of the AUC. For the ad libitum feeding experiment, sampling schemes had H2 productions from 85% to 155% of the corresponding AUC. For the restricted feeding experiment, daily CH4 production needed samplings every 2 h or shorter, or 1 h or shorter, depending on sampling time after feeding, whereas sampling scheme did not affect CH4 production for the twice daily ad libitum feeding experiment. In conclusion, sampling scheme had a major impact on predicted daily H2 production, particularly with restricted feeding, whereas daily CH4 production was less severely affected by sampling scheme
Bayesian mechanistic modeling of thermodynamically controlled volatile fatty acid, hydrogen and methane production in the bovine rumen
Dynamic modeling of mechanisms driving volatile fatty acid and hydrogen production in the rumen microbial ecosystem contributes to the heuristic prediction of CH4 emissions from dairy cattle into the environment. Existing mathematical rumen models, however, lack the representation of these mechanisms. A dynamic mechanistic model was developed that simulates the thermodynamic control of hydrogen partial pressure (pH2 ) on volatile fatty acid (VFA) fermentation pathways via the NAD+ to NADH ratio in fermentative microbes, and methanogenesis in the bovine rumen. This model is unique and closely aligns with principles of reaction kinetics and thermodynamics. Model state variables represent ruminal carbohydrate substrates, bacteria and protozoa, methanogens, and gaseous and dissolved fermentation end products. The model was extended with static equations to model the hindgut metabolism. Feed composition and twice daily feeding were used as model inputs. Model parameters were estimated to experimental data using a Bayesian calibration procedure, after which the uncertainty of the parameter distribution on the model output was assessed. The model predicted a marked peak in pH2 after feeding that rapidly declined in time. This peak in pH2 caused a decrease in NAD+ to NADH ratio followed by an increased propionate molar proportion at the expense of acetate molar proportion, and an increase in CH4 production that steadily decreased in time, although the magnitude of increase for CH4 emission was less than for pH2 . A global sensitivity analysis indicated that parameters that determine the fractional passage rate and NADH oxidation rate altogether explained 86% of the variation in predicted daily CH4 emission. Model evaluation indicated over-prediction of in vivo CH4 emissions shortly after feeding, whereas under-prediction was indicated at later times. The present rumen fermentation modeling effort uniquely provides the integration of the pH2 controlled NAD+ to NADH ratio for dynamically predicting metabolic pathways that yield VFA, H2 and CH4.</p
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Correction: Thermodynamic Driving Force of Hydrogen on Rumen Microbial Metabolism: A Theoretical Investigation.
[This corrects the article DOI: 10.1371/journal.pone.0161362.]
Correction: Thermodynamic Driving Force of Hydrogen on Rumen Microbial Metabolism: A Theoretical Investigation
[This corrects the article DOI: 10.1371/journal.pone.0161362.]