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ABSTRACT: Automated measurements of the ratio of concentrations of methane and carbon dioxide, [CH4]:[CO2], in breath from individual animals (the so-called “sniffer technique”) and estimated CO2 production can be used to estimate CH4 production, provided that CO2 production can be reliably calculated. This would allow CH4 production from individual cows to be estimated in large cohorts of cows, whereby ranking of cows according to their CH4 production might become possible and their values could be used for breeding of low CH4-emitting animals. Estimates of CO2 production are typically based on predictions of heat production, which can be calculated from body weight (BW), energy-corrected milk yield, and days of pregnancy. The objectives of the present study were to develop predictions of CO2 production directly from milk production, dietary, and animal variables, and furthermore to develop different models to be used for different scenarios, depending on available data. An international dataset with 2,244 records from individual lactating cows including CO2 production and associated traits, as dry matter intake (DMI), diet composition, BW, milk production and composition, days in milk, and days pregnant, was compiled to constitute the training dataset. Research location and experiment nested within research location were included as random intercepts. The method of CO2 production measurement (respiration chamber [RC] or GreenFeed [GF]) was confounded with research location, and therefore excluded from the model. In total, 3 models were developed based on the current training dataset: model 1 (“best model”), where all significant traits were included; model 2 (“on-farm model”), where DMI was excluded; and model 3 (“reduced on-farm model”), where both DMI and BW were excluded. Evaluation on test dat sets with either RC data (n = 103), GF data without additives (n = 478), or GF data only including observations where nitrate, 3-nitrooxypropanol (3-NOP), or a combination of nitrate and 3-NOP were fed to the cows (GF+: n = 295), showed good precision of the 3 models, illustrated by low slope bias both in absolute values (−0.22 to 0.097) and in percentage (0.049 to 4.89) of mean square error (MSE). However, the mean bias (MB) indicated systematic overprediction and underprediction of CO2 production when the models were evaluated on the GF and the RC test datasets, respectively. To address this bias, the 3 models were evaluated on a modified test dataset, where the CO2 production (g/d) was adjusted by subtracting (where measurements were obtained by RC) or adding absolute MB (where measurements were obtained by GF) from evaluation of the specific model on RC, GF, and GF+ test datasets. With this modification, the absolute values of MB and MB as percentage of MSE became negligible. In conclusion, the 3 models were precise in predicting CO2 production from lactating dairy cows.

The production of enteric methane in the gastrointestinal tract of livestock is considered as an energy loss in the equations for estimating energy metabolism in feeding systems. Therefore, the spared energy resulting from specific inhibition of methane emissions should be re-equilibrated with other factors of the equation. And, it is commonly assumed that net energy from feeds increases, thus benefitting production functions, particularly in ruminants due to the important production of methane in the rumen. Notwithstanding, we confirm in this work that inhibition of emissions in ruminants does not transpose into consistent improvements in production. Theoretical calculations of energy flows using experimental data show that the expected improvement in net energy for production is small and difficult to detect under the prevailing, moderate inhibition of methane production (≈25%) obtained using feed additives inhibiting methanogenesis. Importantly, the calculation of energy partitioning using canonical models might not be adequate when methanogenesis is inhibited. There is a lack of information on various parameters that play a role in energy partitioning and that may be affected under provoked abatement of methane. The formula used to calculate heat production based on respiratory exchanges should be validated when methanogenesis is inhibited. Also, a better understanding is needed of the effects of inhibition on fermentation products, fermentation heat, and microbial biomass. Inhibition induces the accumulation of H2, the main substrate used to produce methane, that has no energetic value for the host, and it is not extensively used by the majority of rumen microbes. Currently, the fate of this excess of H2 and its consequences on the microbiota and the host are not well known. All this additional information will provide a better account of energy transactions in ruminants when enteric methanogenesis is inhibited. Based on the available information, it is concluded that the claim that enteric methane inhibition will translate into more feed-efficient animals is not warranted.

ABSTRACT: Manure nitrogen (N) from cattle contributes to nitrous oxide and ammonia emissions and nitrate leaching. Measurement of manure N outputs on dairy farms is laborious, expensive, and impractical at large scales; therefore, models are needed to predict N excreted in urine and feces. Building robust prediction models requires extensive data from animals under different management systems worldwide. Thus, the study objectives were (1) to collate an international database of N excretion in feces and urine based on individual lactating dairy cow data from different continents; (2) to determine the suitability of key variables for predicting fecal, urinary, and total manure N excretion; and (3) to develop robust and reliable N excretion prediction models based on individual data from lactating dairy cows consuming various diets. A raw data set was created based on 5,483 individual cow observations, with 5,420 fecal N excretion and 3,621 urine N excretion measurements collected from 162 in vivo experiments conducted by 22 research institutes mostly located in Europe (n = 14) and North America (n = 5). A sequential approach was taken in developing models with increasing complexity by incrementally adding variables that had a significant individual effect on fecal, urinary, or total manure N excretion. Nitrogen excretion was predicted by fitting linear mixed models including experiment as a random effect. Simple models requiring dry matter intake (DMI) or N intake performed better for predicting fecal N excretion than simple models using diet nutrient composition or milk performance parameters. Simple models based on N intake performed better for urinary and total manure N excretion than those based on DMI, but simple models using milk urea N (MUN) and N intake performed even better for urinary N excretion. The full model predicting fecal N excretion had similar performance to simple models based on DMI but included several independent variables (DMI, diet crude protein content, diet neutral detergent fiber content, milk protein), depending on the location, and had root mean square prediction errors as a fraction of the observed mean values of 19.1% for intercontinental, 19.8% for European, and 17.7% for North American data sets. Complex total manure N excretion models based on N intake and MUN led to prediction errors of about 13.0% to 14.0%, which were comparable to models based on N intake alone. Intercepts and slopes of variables in optimal prediction equations developed on intercontinental, European, and North American bases differed from each other, and therefore region-specific models are preferred to predict N excretion. In conclusion, region-specific models that include information on DMI or N intake and MUN are required for good prediction of fecal, urinary, and total manure N excretion. In absence of intake data, region-specific complex equations using easily and routinely measured variables to predict fecal, urinary, or total manure N excretion may be used, but these equations have lower performance than equations based on intake.

A meta-analysis was conducted to evaluate the effects of protozoa concentration on methane emission from ruminants. A database was built from 59 publications reporting data from 76 in vivo experiments. The experiments included in the database recorded methane production and rumen protozoa concentration measured on the same groups of animals. Quantitative data such as diet chemical composition, rumen fermentation and microbial parameters, and qualitative information such as methane mitigation strategies were also collected. In the database, 31% of the experiments reported a concomitant reduction of both protozoa concentration and methane emission (g/kg dry matter intake). Nearly all of these experiments tested lipids as methane mitigation strategies. By contrast, 21% of the experiments reported a variation in methane emission without changes in protozoa numbers, indicating that methanogenesis is also regulated by other mechanisms not involving protozoa. Experiments that used chemical compounds as an antimethanogenic treatment belonged to this group. The relationship between methane emission and protozoa concentration was studied with a variance−covariance model, with experiment as a fixed effect. The experiments included in the analysis had a within-experiment variation of protozoa concentration higher than 5.3 log10 cells/ml corresponding to the average s.e.m. of the database for this variable. To detect potential interfering factors for the relationship, the influence of several qualitative and quantitative secondary factors was tested. This meta-analysis showed a significant linear relationship between methane emission and protozoa concentration: methane (g/kg dry matter intake)=−30.7+8.14×protozoa (log10 cells/ml) with 28 experiments (91 treatments), residual mean square error=1.94 and adjusted R2=0.90. The proportion of butyrate in the rumen positively influenced the least square means of this relationship.

This study evaluated effects of farming practice scenarios aiming to reduce greenhouse gas (GHG) emissions and subsequent alternative land use on environmental impacts of a beef cattle production system using the life cycle assessment approach. The baseline scenario includes a standard cow–calf herd with finishing heifers based on grazing, and a standard bull-fattening herd using a diet mainly based on maize silage, corresponding to current farm characteristics and management by beef farmers in France. Alternative scenarios were developed with changes in farming practices. Some scenarios modified grassland management (S1: decreasing mineral N fertiliser on permanent grassland; S2: decreasing grass losses during grazing) or herd management (S3: underfeeding of heifers in winter; S4: fattening female calves instead of being reared at a moderate growth rate; S5: increasing longevity of cows from 7 to 9 years; S6: advancing first calving age from 3 to 2 years). Other scenarios replaced protein sources (S7: partially replacing a protein supplement by lucerne hay for the cow–calf herd; S8: replacing soya bean meal with rapeseed meal for the fattening herd) or increased n-3 fatty acid content using extruded linseed (S9). The combination of compatible scenarios S1, S2, S5, S6 and S8 was also studied (S10). The impacts, such as climate change (CC, not including CO2 emissions/sequestration of land use and land-use change, LULUC), CC/LULUC (including CO2 emissions of LULUC), cumulative energy demand, eutrophication (EP), acidification and land occupation (LO) were expressed per kg of carcass mass and per ha of land occupied. Compared with the baseline, the most promising practice to reduce impacts per kg carcass mass was S10 (all reduced by 13% to 28%), followed by S6 (by 8% to 10%). For other scenarios, impact reduction did not exceed 5%, except for EP (up to 11%) and LO (up to 10%). Effects of changes in farming practices (the scenarios) on environmental impacts varied according to impact category and functional unit. For some scenarios (S2, S4, S6 and S10), permanent grassland area and LO per kg of carcass decreased by 12% to 23% and 9% to 19%, respectively. If the ‘excess’ permanent grassland was converted to fast-growing conifer forest to sequester carbon in tree and soil biomass, CC/LULUC per kg of carcass could be reduced by 20%, 25%, 27% and 48% for scenarios S2, S4, S6 and S10, respectively. These results illustrate the potential of farming practices and forest as an alternative land use to contribute to short- and mid-term GHG mitigation of beef cattle production systems.

The effects of defaunation on growth and digestion were measured in sheep fed fresh Digitaria decumbens grass cut at four stages of regrowth 14, 28, 42, and 56 days, and with different protein to energy (P/E) ratios. Two completely randomized designs trials (growth and digestion) were conducted using faunated animals, defaunated rams and protozoa free lambs. The digestion trial: eight faunated and eight defaunated rams fitted with ruminal and duodenal cannulas were fed 4 diets (diets D1 to D4) to measure digestion parameters. The dietary P/E ratios were 120 (D1), 130 (D2), 130 (D3), and 140 (D4) g PDIN/UFL (Protein Digested in the small Intestine supplied by microbial protein from rumen-degraded protein/Feed Unit for Lactation) and the grass stages of regrowth were 56, 42, 28, and 14 days, respectively. Increasing the dietary P/E ratios increased dry matter intake (DMI) and the total tract digestibility of organic matter (OM), NDF and CP. Defaunation decreased DMI, except for rams fed D4 diet. Defaunation also decreased total tract digestibility of OM except for rams fed D1 diet and that of NDF except for rams fed D1 and D4 diets. Increasing the dietary P/E ratios also increased nitrogen intake and ammonia (NH3) concentration in the rumen, whereas defaunation decreased them. The dietary P/E ratio increased non-NH3 nitrogen and microbial nitrogen duodenal flows and microbial efficiency. Defaunation did not affect duodenal flows of neither non-NH3 nitrogen and microbial nitrogen or microbial efficiency. The growth trial: 20 faunated and 20 protozoa free lambs were fed four diets (diets D5 to D8) to measure their average daily gain (ADG). The dietary P/E ratios were 60 (D5), 70 (D6), 80 (D7) and 100 (D8) g PDIN/UFL and the stages of regrowth were 56, 42, 28, and 14 days, respectively. DMI of lambs increased with P/E ratio. Protozoa free lambs had greater DMI than faunated ones when fed D7 diet (80.8 v. 74.9 g/kg LW0.75, respectively). The ADG of the lambs increased with P/E ratio. Fed on the same D5 diet, protozoa free lambs had greater ADG than faunated lambs (29.8 v. 11.6 g/day, respectively). In conclusion, animal response to defaunation was modulated by the P/E ratio of the D. decumbens grass diets. Defaunation increased ADG of lambs fed forage with the lowest P/E ratio, while digestion and nitrogen duodenal flows of rams fed the lowest P/E ratio were not affected.

Cet article fait le point des connaissances sur différentes pistes pour réduire la production de méthane entérique par les ruminants,en privilégiant les approches in vivo, et évalue les possibilités d'application pratique. Il est connu que l'accroissement du pourcentagede concentré dans la ration réduit la production de méthane par kg de matière sèche ingérée. Cet effet est toutefois plus sensible pourdes proportions élevées de concentré. Les céréales diminuent plus la production de méthane que les concentrés riches en fibres.L'addition de lipides à la ration a un effet significatif pour réduire les émissions de méthane. Parmi les fourrages, l'ensilage de maïsentraîne des émissions plus faibles que l'ensilage d'herbe ou le foin ; mais les différences induites entre stades de végétation de l'herbeou entre graminées et légumineuses sont faibles, et parfois controversées. De très nombreux extraits de plantes et autres additifsaux modes d'action divers ont été testés. Les plantes riches en tannins et les tannins extraits des plantes sont efficaces pour réduire leméthane mais le risque de diminution de la digestibilité de la ration doit être considéré. Les autres additifs nécessitent des étudessupplémentaires pour attester leur efficacité sur le long terme. Parmi les biotechnologies, celles visant à réorienter la productiond'hydrogène vers d'autres produits que le méthane sont séduisantes, mais pas encore mises au point. L'accroissement du niveau deproduction des animaux entraîne une réduction de la production de méthane qui est particulièrement marquée quand elle estrapportée au kg de lait ou de viande. Enfin, il y a des différences entre animaux dans l'efficacité globale de production, appréciée parl'ingestion rapportée à un même niveau de production. Les animaux les plus efficaces produisent moins de méthane par kg de lait oude viande. L'article met l'accent sur la nécessité de ne pas considérer la diminution du méthane seule, mais d'évaluer l'efficacité desstratégies proposées sur l'ensemble des GES.

Le méthane entérique représente respectivement 45 et 65% des émissions totales de méthane et des émissions d’origine agricole en France, et serait responsable d’environ 5% du réchauffement global dans notre pays. L’objectif de ce document est d’actualiser l’estimation des émissions annuelles de méthane entérique des diverses catégories des principales espèces d’animaux d’élevage dans l’esprit des recommandations du rapport 2006 de l’IPCC (Tier 3), en prenant en compte toutes les informations disponibles sur les types d’animaux et les méthodes d’élevage. Les émissions ont été estimées à partir des besoins énergétiques des animaux, convertis en Energie Métabolisable Ingérée (EMI), et de facteurs de conversion (Y’m) exprimés en kcal de méthane pour 100 kcal d’EMI. Des équations de prédiction des facteurs de conversion ont été calculées pour les diverses espèces ou catégories d’animaux. Les émissions de méthane par animal et par an (facteurs d’émission exprimés en kg) ont été calculées pour chaque catégorie d’animaux. Pour les vaches laitières le facteur d’émission est en moyenne égal à 117,7 pour une production laitière annuelle moyenne de 6300 kg. Il varie de 90 à 163 lorsque la production laitière passe de 3500 à 11 000 kg. Il est en moyenne de 86,7 pour les vaches allaitantes et 43 pour les bovins ruminants en croissance, 14,4 et 11 respectivement pour les brebis laitières et les brebis allaitantes, 14,3 pour les chèvres, 20,7 pour les équins et 0,8 pour les porcins. Les effectifs d’animaux des diverses catégories ont également été ré-estimées. Sur ces bases les émissions totales de méthane entérique en France s’élèvent à 1,41 million de tonnes en 2007. Les vaches laitières, les vaches allaitantes et les bovins en croissance contribuent respectivement à hauteur de 32 - 25 et 34% des émissions totales de méthane ; au total les bovins sont responsables de plus de 90% des émissions de méthane entérique. Les ovins contribuent pour 6,2% et les caprins, les équins et les porcins respectivement pour 1, 1,5 et 0,8% des émissions totales de méthane entérique.