Factors Affecting Enteric Emission Methane and Predictive Models for Dairy Cows (original) (raw)
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Methane emissions from enteric fermentation in dairy cows, 1990-2008
Tourist Studies, 2011
The Dutch protocol for the national inventory estimates the methane emission of the average Dutch dairy cow based on a Tier 3 approach. A dynamic, mechanistic model is used to represent the enteric fermentation processes, using annual national statistics on feed intake and feed composition as model inputs. Dutch dairy rations are based mainly on roughage (3/4 of dry matter
Evaluation of enteric methane prediction equations for dairy cows used in whole farm models
Global Change Biology, 2010
The importance of evaluating greenhouse gas (GHG) emissions from dairy cows within the whole farm setting is being realized as more important than evaluating these emissions in isolation. Current whole farm models aimed at evaluating GHG emissions make use of simple regression equations to predict enteric methane (CH 4) production. The objective of the current paper is to evaluate the performance of nine CH 4 prediction equations that are currently being used in whole farm GHG models. Data used to evaluate the prediction equations came from a collection of individual (IND) and treatment averaged (TRT) data. Equations were compared based on mean square prediction error (MSPE) and concordance correlation coefficient (CCC) analysis. In general, predictions were poor, with root MSPE (as a percentage of observed mean) values ranging from 20.2 to 52.5 for the IND database and from 24.0 to 38.2 for the TRT database and CCC values ranging from 0.009 to 0.493 for the IND database and from 0.000 to 0.271 for the TRT database. Overall, the equations of Moe & Tyrrell and IPCC Tier II performed best on the IND dataset, and the equations of Moe & Tyrrell and Kirchgener et al., performed best on the TRT dataset. Results show that the simple more generalized equations performed worse than those that attempted to represent important aspects of diet composition, but in general significant amounts of bias and deviation of the regression slope from unity existed for all equations. The low prediction accuracy of CH 4 equations in whole farm models may introduce substantial error into inventories of GHG emissions and lead to incorrect mitigation recommendations.
Global change biology, 2018
Enteric methane (CH) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CHis complex, expensive and impractical at large scales; therefore, models are commonly used to predict CHproduction. However, building robust prediction models requires extensive data from animals under different management systems worldwide. The objectives of this study were to (1) collate a global database of enteric CHproduction from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CHproduction (g/d per cow), yield [g/kg dry matter intake (DMI)], and intensity (g/kg energy corrected milk) and their respective relationships; (3) develop intercontinental and regional models and cross-validate their performance; and (4) assess the trade-off between availability of on-farm inputs and CHprediction accuracy. The intercontinental database covered Europe (EU), the US (US), Chile (CL), Australia (AU), and New Zealand (...
Mitigation strategies to reduce enteric methane emissions from dairy cows: update review
Canadian Journal of …, 2004
2004. Mitigation strategies to reduce enteric methane emissions from dairy cows: Update review. Can. J. Anim. Sci. 84: 319-335. Enteric methane (CH 4 ) emission is a major contributor to Canadian greenhouse gas emissions, and also a loss of feed energy during production. The objective of this paper is to provide an update on current management practices and new dietary strategies recently proposed to reduce CH 4 emissions from ruminants. Existing mitigation strategies for dairy, e.g., the addition of ionophores, fats, use of high-quality forages, and increased use of grains, have been well researched and applied. These nutritional changes reduce CH 4 emissions by manipulating ruminal fermentation, directly inhibiting methanogens and protozoa, or by diverting hydrogen ions away from methanogens. Current literature has identified new CH 4 mitigation options. These include the addition of probiotics, acetogens, bacteriocins, archaeal viruses, organic acids, plant extracts (e.g., essential oils) to the diet, as well as immunization, and genetic selection of cows. These new strategies are promising, but more research is needed to validate these approaches and to assess in vivo their effectiveness in reducing CH 4 production by dairy cows. It is also important to evaluate CH 4 mitigation strategies in terms of the total greenhouse gas budget and to consider the cost associated with the various strategies. More basic understanding of the natural differences in digestion efficiencies among animals as well as a better knowledge of methanogens and their interaction with other organisms in the rumen would enable us to exploit the potential of some of the new CH 4 mitigation strategies for dairy cattle production. Chiquette, J. et Massé, D. 2004. Stratégies visant à réduire les dégagements de méthane entérique des vaches laitières: bilan. Can. J. Anim. Sci. 84: 319-335. Le méthane (CH 4 ) d'origine entérique contribue dans une large mesure aux émissions canadiennes de gaz à effet de serre et entraîne une perte de l'énergie tirée des aliments durant la production. Le présent article fait le point sur les pratiques de zootechnie actuelles et sur les stratégies d'engraissement récemment proposées pour réduire les dégagements de CH 4 des ruminants. Les stratégies d'atténuation existantes (addition d'ionophores, matière grasse, utilisation de fourrages de grande qualité, plus grande utilisation de grains) ont fait l'objet de maintes recherches et sont désormais bien appliquées. Les changements nutritionnels qu'elles introduisent diminuent les émissions de CH 4 en modifiant la fermentation dans le rumen, en inhibant directement la production de méthanogènes et la population de protozoaires ainsi qu'en détournant les ions hydrogène des méthanogènes. La documentation scientifique mentionne de nouvelles méthodes pour atténuer la libération de CH 4 . Ces méthodes comprennent l'ajout de probiotiques, d'acétogènes, de bactériocine, de virus archaïques, d'acides organiques et d'extraits végétaux (huiles essentielles) à la ration des animaux de même que l'immunisation et la sélection génétique des vaches. Ces nouvelles stratégies semblent prometteuses, mais elles doivent faire l'objet de recherches plus poussées si on veut les valider et évaluer in vivo l'efficacité avec laquelle elles réduisent la production de CH 4 par les vaches laitières. Les stratégies d'atténuation doivent aussi être évaluées d'après la production globale de gaz à effet de serre et on doit tenir compte des coûts qui s'y associent. On devrait parvenir à une meilleure compréhension des différences naturelles affectant la digestion des animaux ainsi qu'acquérir des connaissances sur les méthanogènes et la façon dont ils interagissent avec d'autres unicellulaires du rumen en vue de mieux exploiter le potentiel de certaines nouvelles stratégies d'atténuation au niveau de l'élevage des bovins laitiers.
A Review on the Mitigation Strategies for Reducing Enteric Methane Emissions from Dairy Cows
Advances in Life Science and Technology, 2016
The objective of this paper is to provide updated information on current management practices and new dietary strategies recently developed to reduce CH4 emissions from ruminants. Enteric methane (CH4) emission is a major contributor to greenhouse gas emissions, and also a loss of feed energy during production. The Existing mitigation strategies for dairy cattle are the addition of ionophores, fats, use of high-quality forages, and increased use of grains, have been well researched and applied. These nutritional changes reduce CH4 emissions by manipulating ruminal fermentation, directly inhibiting methanogens and protozoa, or by diverting hydrogen ions away from methanogens. Currently new CH4 mitigation options have identified. These include the addition of probiotics, acetogens, bacteriocins, archaeal viruses, organic acids, plant extracts (e.g., essential oils) to the diet, as well as immunization, and genetic selection of cows. These new strategies are promising, but more research is needed to validate these approaches and to assess in vivo their effectiveness in reducing CH4 production by dairy cows. It is also important to evaluate CH4 mitigation strategies in terms of the total greenhouse gas budget and to consider the cost associated with the various strategies. More basic understanding of the natural differences in digestion efficiencies among animals as well as a better knowledge of methanogens and their interaction with other organisms in the rumen would enable us to exploit the potential of some of the new CH4 mitigation strategies for dairy cattle production.
Animal Feed Science and Technology, 2011
The protocol for the National Inventory of agricultural greenhouse gas emissions in The Netherlands includes a dynamic and mechanistic model of animal digestion and fermentation as an Intergovernmental Panel on Climate Change (IPCC) Tier 3 approach to estimate enteric CH 4 emission by dairy cows. The model differs from an IPCC Tier 2 approach in that it predicts hydrogen sources (i.e., production of acetate and butyrate, microbial growth on amino acids as an N source) and sinks (i.e., production of propionate and the remainder of the volatile fatty acids (VFA), microbial growth on ammonia as an N source, saturation of unsaturated long chain fatty acids) in the rumen and large intestine, and elimination of excess hydrogen by methanogenesis. As a result, the model predicts CH 4 emission by considering various dietary characteristics, including the types of carbohydrate, protein, fat, intrinsic degradation characteristics of feeds, as well as ruminal fractional passage rates, fluid volume and acidity, instead of assuming a fixed CH 4 energy conversion factor in the Tier 2 approach. Annual statistics of diet and performance of the average dairy cow in The Netherlands from 1990 until 2008 indicate that dry matter intake and yield of fat and crude protein corrected milk (FPCM) per cow/year increased by 20 and 34% respectively. Based on annual data for diet and FPCM, the model predicted an increase in enteric CH 4 emission from 111 (1990) to 128 (2008) kg/cow/year. As a result, CH 4 emission per kg FPCM milk decreased by 13%. The predicted fraction of gross energy intake lost as CH 4 energy gradually declined and was close to 0.06, which is the IPCC (1997) Tier 2 default value of 0.06 for dairy cows, but ∼10% lower than the IPCC (2006) updated value of 0.065. The 15% uncertainty value for predicted CH 4 emissions for a reference diet was lower than the 20% assumed under Tier 2. Our analysis indicated that uncertainty of model predictions of CH 4 emission is determined mostly by errors in feed intake estimation, in the representation of the stoichiometry of production of VFA from fermented substrate, and in the acidity of rumen contents. Further uncertainty of predicted CH 4 emission was due to errors in estimation of dietary composition Abbreviations: CP, crude protein; D, potentially degradable fraction in the rumen; DM, dry matter; FPCM, fat and protein corrected milk; GE, gross energy; GHG, greenhouse gas; IPCC, Intergovernmental Panel on Climate Change; MCF, CH4 energy conversion factor; MEF, CH4 emission factor; NE l , net energy for lactation; ST, starch; SU, sugars and soluble carbohydrates; U, undegradable fraction in the rumen; VEM, unit used to express net energy for lactation in the Dutch NEL system for dairy cows; VFA, volatile fatty acids; W, washable fraction of feeds in the rumen.
Cow of the Future Research Priorities for Mitigating Enteric Methane Emissions from Dairy
The Innovation Center for U.S. Dairy has set a goal of reducing enteric methane missions (per lb. fluid milk) from dairy cattle by 25% by 2020 by implementing the Cow of the Future project. It was clearly stated by that "improving livestock productivity so that less methane is emitted per unit of product is the most promising and cost effective technique for reducing emissions in the U.S.". It is also clear that historical improvements in dairy production have reduced methane emissions per unit of milk substantially . Implementation of existing technologies and management practices in the U.S. dairy industry along with continued genetic progress in milk yields is expected to result in 10 to 12% reductions of methane emissions per unit of milk over the next decade. To achieve the additional 13 to 15% reduction to reach the overall goal of 25% requires investment in research to identify and develop new strategies and technologies. Conservative estimates suggest that additional reductions of 15 to 30% can be achieved, dependent upon the development of new strategies and technologies and their adoption by the U.S. dairy industry (figure below).
Landbauforschung, 2019
The aim of this study was to compare metrics for quantifying enteric methane (CH4) emissions from individual cows during milking using frequent spot measurements and peak analysis methods. An infrared gas analyser was used to measure the CH4 emitted by cows, and eructation peaks were identi fied using a Signal Processing Toolbox provided by Matlab. CH4 emissions were quantified by gas peak height, peak amplitude and average concentration, and were expressed in grams per day and CH4 yield (grams per kilogram of dry matter intake (DMI)). Peak analysis measurements of CH4 were obtained from 36 cows during 2,474 milkings, during which cows were fed a ration containing between 39 and 70 % forage. Spot measurements of CH4 were compared to a separate dataset of 196 chamber CH4 records from another group of 105 cows, which were fed a ration containing between 25 and 80 % forage. The results showed that the metrics of CH4 peak height and CH4 peak amplitude demonstrated similar positive relat...
Sustainability
This study determined the breed and the season-specific methane (CH4) conversion factor (Ym) and the emission factor (EF) for the enteric CH4 of dairy steers. The Ym values for Holstein and Jersey steers at different seasons were calculated using the IPCC 2006 equations by incorporating the input and/or output value of the chemical composition of feed, methane production, methane yield, dry matter intake, and methane energy emission. EFs were categorized into five types depending on the 2019 refinement to the IPCC 2006 Tier 2 equations used. EFA was calculated from Equation 10.21A (New), while other EFs were estimated from the Equation 10.21 which were designated according to the gross energy intake (GEI) and Ym as EFB (GEIi and Ym), EFC (GEIii and Ym), EFD (GEIii and Ym (6.3)), and EFE (GEIii and Ym (4.0)). The calculated overall Ym for Holstein and Jersey steers were 4.90 and 7.49, while the recorded EF of group EFA were 56.44 and 67.42 kg CH4/head/year for Holstein and Jersey ste...
Canadian Journal of Animal Science
Estimating enteric methane production for beef cattle using empirical prediction models compared with IPCC Tier 2 methodology. Can. J. Anim. Sci. xx: xxx-xxx. The IPCC (2006), Tier 2 methodology and 16 empirical models together with dietary information were used to estimate daily Methane (CH 4) production and Ym (CH 4 energy expressed as a percentage of gross energy intake) for mature cows (lactating, dry) and growing steers (backgrounding, grazing, finishing) in Eastern and Western Canada. Monthly simulations accounted for changes in body weight, feed intake and diet composition. Coefficient of variation (CV) and uncertainty (95% confidence interval divided by mean) were used to estimate variability. Estimates of CH 4 (g d-1) and Ym from models differed from IPCC estimates. For models, the CV of Ym ranged from 0.8 to 29.7% and uncertainty from 0.9 to 45.2% over the production phases of the animals in contrast to the fixed Ym used by IPCC. When information on diet composition is lacking, a Ym value of 7.0 to 7.3% can be used for beef cows depending on stage and location, and 6.4 to 6.6% for growing cattle fed high forage diets, while 4.8% is recommended for finishing diets instead of the default values of 6.5% for high forage diets and 3.0% for finishing diets typically used in the IPCC Tier 2 method.