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It has previously been shown that fermentation may contribute substantially to small intestinal carbohydrate disappearance. The fact that the energetic efficiency of starch fermentation is considerably less than that of enzymatic digestion of starch, makes it of nutritional importance to quantify the level of postruminal starch fermentation for dairy cows. Hence, we subjected six rumen-fistulated Holstein-Friesian dairy cows (48 ± 17 days in milk) to 5 d of continuous abomasal infusions of 0.0, 2.5, and 5.0 mol NH4Cl/d, with and without 3 kg ground maize/d, followed by 2 d of rest in a 6 × 6 Latin square design. A total mixed ration (TMR) consisting of (DM basis) 70% grass silage and 30% concentrate was fed at 95% of ad libitum intake. Separation of postruminal starch disappearance into enzymatically digested starch and fermented starch was based on the measurement of natural 13C enrichment of the TMR, abomasally infused ground maize, and resulting 13C enrichment of faeces. Within each cow, 0.0, 2.5, and 5.0 mol NH4Cl/d without ground maize served as control for the same levels of NH4Cl with 3 kg ground maize/d. Abomasal infusion of ground maize was associated with increased total DM and starch intake, faecal starch excretion, and digestibility of starch, and with decreased digestibility of DM and N. The increased faecal volatile fatty acid (VFA) output and 13C enrichment of the individual VFA indicate increased starch fermentation with abomasally infused ground maize. On average, 1 311 g starch/d was postruminally fermented, representing 60.8% of total starch intake. Overall, postruminal starch fermentation of early-lactation dairy cows abomasally infused with 3 kg ground maize/d is considerable and may result in substantial amounts of VFA rather than glucose production.

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.

Rumen sensors provide specific information to help understand rumen functioning in relation to health disorders and to assist in decision-making for farm management. This review focuses on the use of rumen sensors to measure ruminal pH and discusses variation in pH in both time and location, pH-associated disorders and data analysis methods to summarize and interpret rumen pH data. Discussion on the use of rumen sensors to measure redox potential as an indication of the fermentation processes is also included. Acids may accumulate and reduce ruminal pH if acid removal from the rumen and rumen buffering cannot keep pace with their production. The complexity of the factors involved, combined with the interactions between the rumen and the host that ultimately determine ruminal pH, results in large variation among animals in their pH response to dietary or other changes. Although ruminal pH and pH dynamics only partially explain the typical symptoms of acidosis, it remains a main indicator and may assist to optimize rumen function. Rumen pH sensors allow continuous monitoring of pH and of diurnal variation in pH in individual animals. Substantial drift of non-retrievable rumen pH sensors, and the difficulty to calibrate these sensors, limits their application. Significant within-day variation in ruminal pH is frequently observed, and large distinct differences in pH between locations in the rumen occur. The magnitude of pH differences between locations appears to be diet dependent. Universal application of fixed conversion factors to correct for absolute pH differences between locations should be avoided. Rumen sensors provide high-resolution kinetics of pH and a vast amount of data. Commonly reported pH characteristics include mean and minimum pH, but these do not properly reflect severity of pH depression. The area under the pH × time curve integrates both duration and extent of pH depression. The use of this characteristic, as well as summarizing parameters obtained from fitting equations to cumulative pH data, is recommended to identify pH variation in relation to acidosis. Some rumen sensors can also measure the redox potential. This measurement helps to understand rumen functioning, as the redox potential of rumen fluid directly reflects the microbial intracellular redox balance status and impacts fermentative activity of rumen microorganisms. Taken together, proper assessment and interpretation of data generated by rumen sensors requires consideration of their limitations under various conditions.

This study investigated the relationships between methane (CH4) emission and fatty acids, volatile metabolites (V) and non-volatile metabolites (NV) in milk of dairy cows. Data from an experiment with 32 multiparous dairy cows and four diets were used. All diets had a roughage : concentrate ratio of 80 : 20 based on dry matter (DM). Roughage consisted of either 1000 g/kg DM grass silage (GS), 1000 g/kg DM maize silage (MS), or a mixture of both silages (667 g/kg DM GS and 333 g/kg DM MS; 333 g/kg DM GS and 677 g/kg DM MS). Methane emission was measured in climate respiration chambers and expressed as production (g/day), yield (g/kg dry matter intake; DMI) and intensity (g/kg fat- and protein-corrected milk; FPCM). Milk was sampled during the same days and analysed for fatty acids by gas chromatography, for V by gas chromatography–mass spectrometry, and for NV by nuclear magnetic resonance. Several models were obtained using a stepwise selection of (1) milk fatty acids (MFA), V or NV alone, and (2) the combination of MFA, V and NV, based on the minimum Akaike’s information criterion statistic. Dry matter intake was 16.8±1.23 kg/day, FPCM yield was 25.0±3.14 kg/day, CH4 production was 406±37.0 g/day, CH4 yield was 24.1±1.87 g/kg DMI and CH4 intensity was 16.4±1.91 g/kg FPCM. The observed CH4 emissions were compared with the CH4 emissions predicted by the obtained models, based on concordance correlation coefficient (CCC) analysis. The best models with MFA alone predicted CH4 production, yield and intensity with a CCC of 0.80, 0.71 and 0.69, respectively. The best models combining the three types of metabolites included MFA and NV for CH4 production and CH4 yield, whereas for CH4 intensity MFA, NV and V were all included. These models predicted CH4 production, yield and intensity better with a higher CCC of 0.92, 0.78 and 0.93, respectively, and with increased accuracy (Cb) and precision (r). The results indicate that MFA alone have moderate to good potential to estimate CH4 emission, and furthermore that including V (CH4 intensity only) and NV increases the CH4 emission prediction potential. This holds particularly for the prediction model for CH4 intensity.

Grass silage is typically fed to dairy cows in temperate regions. However, in vivo information on methane (CH4) emission from grass silage of varying quality is limited. We evaluated the effect of two rates of nitrogen (N) fertilisation of grassland (low fertilisation (LF), 65 kg of N/ha; and high fertilisation (HF), 150 kg of N/ha) and of three stages of maturity of grass at cutting: early maturity (EM; 28 days of regrowth), mid maturity (MM; 41 days of regrowth) and late maturity (LM; 62 days of regrowth) on CH4 production by lactating dairy cows. In a randomised block design, 54 lactating Holstein–Friesian dairy cows (168±11 days in milk; mean±standard error of mean) received grass silage (mainly ryegrass) and compound feed at 80 : 20 on dry matter basis. Cows were adapted to the diet for 12 days and CH4 production was measured in climate respiration chambers for 5 days. Dry matter intake (DMI; 14.9±0.56 kg/day) decreased with increasing N fertilisation and grass maturity. Production of fat- and protein-corrected milk (FPCM; 24.0±1.57 kg/day) decreased with advancing grass maturity but was not affected by N fertilisation. Apparent total-tract feed digestibility decreased with advancing grass maturity but was unaffected by N fertilisation except for an increase and decrease in N and fat digestibility with increasing N fertilisation, respectively. Total CH4 production per cow (347±13.6 g/day) decreased with increasing N fertilisation by 4% and grass maturity by 6%. The smaller CH4 production with advancing grass maturity was offset by a smaller FPCM and lower feed digestibility. As a result, with advancing grass maturity CH4 emission intensity increased per units of FPCM (15.0±1.00 g CH4/kg) by 31% and digestible organic matter intake (33.1±0.78 g CH4/kg) by 15%. In addition, emission intensity increased per units of DMI (23.5±0.43 g CH4/kg) by 7% and gross energy intake (7.0±0.14% CH4) by 9%, implying an increased loss of dietary energy with advancing grass maturity. Rate of N fertilisation had no effect on CH4 emissions per units of FPCM, DMI and gross energy intake. These results suggest that despite a lower absolute daily CH4 production with a higher N fertilisation rate, CH4 emission intensity remains unchanged. A significant reduction of CH4 emission intensity can be achieved by feeding dairy cows silage of grass harvested at an earlier stage of maturity.

The objectives were to investigate the effect of feeding and visiting behavior of dairy cattle on CH 4 and H 2 production measured with voluntary visits to the GreenFeed system (GF) and to determine whether these effects depended on basal diet (BD) and 3-nitrooxypropanol (3-NOP) supplementation. The experiment involved 64 lactating dairy cattle (146 ± 45 DIM at the start of trial; mean ± SD) in 2 overlapping crossover trials, each consisting of 2 measurement periods. Cows within block were randomly allocated to 1 of 3 types of BD: a grass silage-based diet consisting of 30% concentrates and 70% grass silage (DM basis); a grass silage and corn silage mixed diet consisting of 30% concentrates, 42% grass silage, and 28% corn silage (DM basis); or a corn silage-based diet consisting of 30% concentrates, 14% grass silage, and 56% corn silage (DM basis). Each type of BD was subsequently supplemented with 0 and 60 mg 3-NOP/kg of DM in one crossover or 0 and 80 mg 3-NOP/kg of DM in the other crossover. Diets were provided in feed bins that automatically recorded feed intake and feeding behavior, with additional concentrate fed in the GF. All visits to the GF that resulted in a spot measurement of both CH 4 and H 2 emission were analyzed in relation to feeding behavior (e.g., meal size and time interval to preceding meal) as well as GF visiting behavior (e.g., duration of visit). Feeding and GF visiting behavior were related to CH 4 and H 2 production measured with the GF, in particular the meal size before a GF measurement and the time interval between a GF measurement and the preceding meal. Relationships between gas production and both feeding and GF visiting behavior were affected by type of BD as well as 3-NOP supplementation. With an increase of the time interval between a GF measurement and the preceding meal, CH 4 production decreased with 0 mg 3-NOP/kg of DM but increased with 60 and 80 mg 3-NOP/kg of DM, whereas type of BD did not affect these relationships. In contrast, CH 4 production increased with 0 mg 3-NOP/kg of DM but decreased with 60 and 80 mg 3-NOP/kg of DM upon an increase in the size of the meal preceding a GF measurement. With an increase of the time interval between a GF measurement and the preceding meal, or with a decrease of the size of the meal preceding a GF measurement, H 2 production decreased for all treatments, although the effect was generally somewhat stronger for 60 and 80 mg 3-NOP/kg of DM than for 0 mg 3-NOP/kg of DM. Hence, the timing of GF measurements next to feeding and GF visiting behavior are essential when assessing the effect of dietary treatment on the production of CH 4 and H 2 in a setting where a spot-sampling device such as a GF is used and where the measurements depend on voluntary visits from the cows., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

The objective was to determine the long-term effect of 3-nitrooxypropanol (3-NOP) on CH 4 emission and milk production characteristics from dairy cows receiving 3-NOP in their diet for a full year, covering all lactation stages of the dairy cows. Sixty-four late-lactation Holstein-Friesian cows (34% primiparous) were blocked in pairs, based on expected calving date, parity, and daily milk yield. The experiment started with an adaptation period of 1 wk followed by a covariate period of 3 wk in which all cows received the same basal diet and baseline measurements were performed. Directly after, cows within a block were randomly allocated to 1 of 2 dietary treatments: a diet containing on average 69.8 mg 3-NOP/kg DM (total ration level, corrected for intake of nonsupplemented GreenFeed bait) and a diet containing a placebo. Forage composition as well as forage-to-concentrate ratio altered with lactation stage (i.e., dry period and early, mid, and late lactation). Diets were provided as a total mixed ration, and additional bait was fed in GreenFeed units (C-Lock Inc.), which were used for emission measurements. Supplementation of 3-NOP did not affect total DMI, BW, or BCS, but resulted in a 6.5% increase in the yields of energy-corrected milk and fat- and protein-corrected milk (FPCM). Furthermore, milk fat and protein as well as feed efficiency were increased upon 3-NOP supplementation. Overall, a reduction of 21%, 20%, and 27% was achieved for CH 4 production (g/d), yield (g/kg DMI), and intensity (g/kg FPCM), respectively, upon 3-NOP supplementation. The CH 4 mitigation potential of 3-NOP was affected by the lactation stage dependent diet to which 3-NOP was supplemented. On average, a 16%, 20%, 16%, and 26% reduction in CH 4 yield (g/kg DMI) was achieved upon 3-NOP supplementation for the dry period, and early, mid, and late-lactation diets, respectively. The CH 4 mitigation potential of 3-NOP was affected by the length of 3-NOP supplementation within a lactation stage dependent diet and by variation in diet composition within a lactation stage dependent diet as a result of changes in grass and corn silage silos. In conclusion, 3-NOP reduced CH 4 emission from cows receiving 3-NOP for a year, with a positive effect on production characteristics. The CH 4 mitigation potential of 3-NOP was influenced by diet type, diet composition, and nutrition value, and the efficacy of 3-NOP appeared to decline over time but not continuously. Associated with changes in diet composition, increased efficacy of 3-NOP was observed at the start of the trial, at the start of a new lactation, and, importantly, at the end of the trial. These results suggest that diet composition has a large effect on the efficacy of 3-NOP, perhaps even larger than the week of supplementation after first introduction of 3-NOP. More studies are needed to clarify the long-term effects of 3-NOP on CH 4 emission and to further investigate what influence variation in diet composition may have on the mitigation potential of 3-NOP., (© 2024, The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

This study aimed to investigate the effect of administering a standardized blend of cinnamaldehyde, eugenol, and Capsicum oleoresin (CEC) to lactating dairy cattle for 84 d (i.e., 12 wk) on enteric CH 4 emission, feed intake, milk yield and composition, and body weight. The experiment involved 56 Holstein-Friesian dairy cows (145 ± 31.1 d in milk at the start of the trial; mean ± standard deviation) in a randomized complete block design. Cows were blocked in pairs according to parity, lactation stage, and current milk yield, and randomly allocated to 1 of the 2 dietary treatments: a diet including 54.5 mg of CEC/kg of DM or a control diet without CEC. Diets were provided as partial mixed rations in feed bins, which automatically recorded individual feed intake. Additional concentrate was fed in the GreenFeed system that was used to measure emissions of CO 2 , CH 4 , and H 2 . Feeding CEC decreased CH 4 yield (g/kg DMI) by on average 3.4% over the complete 12-wk period and by on average 3.9% from 6 wk after the start of supplementation onward. Feeding CEC simultaneously increased feed intake and body weight, and tended to increase milk protein content, whereas no negative responses were observed. These results must be further investigated and confirmed in longer-term in vivo experiments., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Estimating daily enteric hydrogen (H 2 ) and methane (CH 4 ) 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 H 2 and CH 4 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 H 2 and CH 4 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 H 2 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 H 2 productions from 85% to 155% of the corresponding AUC. For the restricted feeding experiment, daily CH 4 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 CH 4 production for the twice daily ad libitum feeding experiment. In conclusion, sampling scheme had a major impact on predicted daily H 2 production, particularly with restricted feeding, whereas daily CH 4 production was less severely affected by sampling scheme., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

It has previously been shown that fermentation may contribute substantially to small intestinal carbohydrate disappearance. The fact that the energetic efficiency of starch fermentation is considerably less than that of enzymatic digestion of starch, makes it of nutritional importance to quantify the level of postruminal starch fermentation for dairy cows. Hence, we subjected six rumen-fistulated Holstein-Friesian dairy cows (48 ± 17 days in milk) to 5 d of continuous abomasal infusions of 0.0, 2.5, and 5.0 mol NH 4 Cl/d, with and without 3 kg ground maize/d, followed by 2 d of rest in a 6 × 6 Latin square design. A total mixed ration (TMR) consisting of (DM basis) 70% grass silage and 30% concentrate was fed at 95% of ad libitum intake. Separation of postruminal starch disappearance into enzymatically digested starch and fermented starch was based on the measurement of natural 13 C enrichment of the TMR, abomasally infused ground maize, and resulting 13 C enrichment of faeces. Within each cow, 0.0, 2.5, and 5.0 mol NH 4 Cl/d without ground maize served as control for the same levels of NH 4 Cl with 3 kg ground maize/d. Abomasal infusion of ground maize was associated with increased total DM and starch intake, faecal starch excretion, and digestibility of starch, and with decreased digestibility of DM and N. The increased faecal volatile fatty acid (VFA) output and 13 C enrichment of the individual VFA indicate increased starch fermentation with abomasally infused ground maize. On average, 1 311 g starch/d was postruminally fermented, representing 60.8% of total starch intake. Overall, postruminal starch fermentation of early-lactation dairy cows abomasally infused with 3 kg ground maize/d is considerable and may result in substantial amounts of VFA rather than glucose production., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

This study aimed to evaluate trade-offs between enteric and manure CH 4 emissions, and the size of synergistic effects for CH 4 and nitrogenous emissions (NH 3 and N 2 O). Sixty-four Holstein-Friesian cows were blocked in groups of 4 based on parity, lactation stage, and milk yield. Cows within a block were randomly allocated to a dietary sequence in a crossover design with a grass silage-based diet (GS) and a corn silage-based diet (CS). The GS diet consisted of 50% grass silage and 50% concentrate, and CS consisted of 10% grass silage, 40% corn silage, and 50% concentrate (dry matter basis). The composition of the concentrate was identical for both diets. Cows were housed in groups of 16 animals, in 4 mechanically ventilated barn units for independent emission measurement. Treatment periods were composed of a 2-wk adaptation period followed by a 5-wk measurement period, 1 wk of which was without cows to allow separation of enteric and manure emissions. In each barn unit, ventilation rates and concentrations of CH 4 , CO 2 , NH 3 , and N 2 O in incoming and outgoing air were measured. Cow excretion of organic matter was higher for CS compared with GS. Enteric CH 4 and cow-associated NH 3 and N 2 O emissions (i.e., manure emissions excluded) were lower for CS compared with GS (-11, -40, and -45%, respectively). The CH 4 and N 2 O emissions from stored manure (i.e., in absence of cows) were not affected by diet, whereas that of NH 3 emission tended to be lower for CS compared with GS. In conclusion, there was no trade-off between enteric and manure CH 4 emissions, and there were synergistic effects for CH 4 and nitrogenous emissions when grass silage was exchanged for corn silage, without balancing the diets for crude protein content, in this short-term study., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

We studied the effect of dietary linseed oil (LSO) supplementation and DGAT1 K232A (DGAT1) polymorphism on the triacylglycerol composition and crystallization of bovine milk fat. LSO supplementation increased unsaturated triacylglycerols, notably in the C52-C54 carbon range, while reducing the saturated C29-C49 triacylglycerols. These changes were associated with an increase in the low-melting fraction and the crystal lamellar thickness, as well as a reduction in the medium and high-melting fractions and the formation of the most abundant crystal type at 20 °C (β'-2 polymorph). Furthermore, DGAT1 KK was associated with higher levels of odd-chain saturated triacylglycerols than DGAT1 AA, and it was also associated with an increase in the high-melting fraction and the endset melting temperature. An interaction between diet and DGAT1 for the unsaturated C54 triacylglycerols accentuated the effects of LSO supplementation with DGAT1 AA. These findings show that genetic polymorphism and cows' diet can have considerable effects on milk fat properties., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier Ltd.)

Ruminants, particularly dairy and beef cattle, contribute to climate change through mostly enteric methane emissions. Several mitigating options have been proposed, including the feed additive 3-nitrooxypropanol (3-NOP). The objectives of this study were to explain the variability in the mitigating effect of 3-NOP and to investigate the interaction between diet composition and 3-NOP dose, using meta-analytical approaches. Data from 13 articles (14 experiments) met the selection criteria for inclusion in the meta-analysis, and 48 treatment means were used for the analysis. Mean differences were calculated as 3-NOP treatment mean minus control treatment mean and then expressed as a percentage of the control mean. Three types of models were developed: (1) one including 3-NOP dose, overall mean, and individual covariate; (2) a combination of neutral detergent fiber (NDF), 3-NOP dose, and overall mean; and (3) one selected model from all combinations of up to 5 covariates, which were compared using a leave-one-out cross validation method. Models including only 3-NOP dose resulted in a significant reduction of 32.7%, 30.9%, and 32.6% for CH 4 production (g/d), yield (g/kg dry matter intake), and intensity (g/kg energy-corrected milk), respectively, at an average 3-NOP dose of 70.5 mg/kg dry matter (DM). The greater the NDF content in the diet, the lower the reduction efficiency for a given 3-NOP dose. For 10 g/kg DM increase in NDF content from its mean (329 g of NDF/kg of DM) the 3-NOP effect on CH 4 production was impaired by 0.633%, the 3-NOP effect on CH 4 yield by 0.647%, and the 3-NOP effect on CH 4 intensity by 0.723%. The analysis based on leave-one-out cross validation showed an increase in NDF and crude fat content reduces efficacy of 3-NOP and an increase in 3-NOP dose increases efficacy. A 1% (10 g/kg) DM decrease in dietary NDF content from its mean may increase the efficacy of 3-NOP in reducing CH 4 production by 0.915%. A 1% (10 g/kg DM) decrease in dietary crude fat content from its mean enhances the efficacy of 3-NOP on CH 4 production by 3.080% at a given dose and NDF level. For CH 4 yield, next to 3-NOP dose, dietary NDF content and dietary crude fat content were included in the selected model, but also dietary starch content with an opposite direction to NDF and crude fat. The effect of 3-NOP dose on CH 4 intensity was similar to its effect on CH 4 production, whereas the effect of dietary NDF content was slightly lower. Expanding the previously published models with the newly available data published from trials since then improved model performance, hence demonstrating the value of regularly updating meta-analyses if a wider range of data becomes available., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

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., (© 2022, The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

The objective of this study was to investigate whether the CH 4 mitigation potential of 3-nitrooxypropanol (3-NOP) in dairy cattle was affected by basal diet (BD) composition. The experiment involved 64 Holstein-Friesian dairy cows (146 ± 45 d in milk at the start of trial; mean ± SD) in 2 overlapping crossover trials, each consisting of 2 measurement periods. Cows were blocked according to parity, d in milk, and milk yield, and randomly allocated to 1 of 3 diets: a grass silage-based diet (GS) consisting of 30% concentrates and 70% grass silage (DM basis), a grass silage- and corn silage-mixed diet (GSCS) consisting of 30% concentrates, 42% grass silage, and 28% corn silage (DM basis), or a corn silage-based diet (CS) consisting of 30% concentrates, 14% grass silage, and 56% corn silage (DM basis). Two types of concentrates were formulated, viz. a concentrate for the GS diet and a concentrate for the CS diet, to meet the energy and protein requirements for maintenance and milk production. The concentrate for the GSCS diet consisted of a 50:50 mixture of both concentrates. Subsequently, the cows within each type of BD received 2 treatments in a crossover design: either 60 mg of 3-NOP/kg of DM (NOP60) and a placebo with 0 mg of 3-NOP/kg of DM (NOP0) in one crossover or 80 mg of 3-NOP/kg of DM (NOP80) and NOP0 in the other crossover. Diets were provided as total mixed ration in feed bins, which automatically recorded feed intake. Additional concentrate was fed in the GreenFeed system that was used to measure emissions of CH 4 and H 2 . The CS diets resulted in a reduced CH 4 yield (g/kg DMI) and CH 4 intensity (g/kg milk). Feeding 3-NOP resulted in a decreased DMI. Milk production and composition did not differ between NOP60 and NOP0, whereas milk yield and the yield of major components decreased for NOP80 compared with NOP0. Feed efficiency was not affected by feeding 3-NOP. Interactions between BD and supplementation of 3-NOP were observed for the production (g/d) and yield (g/kg DMI) of both CH 4 and H 2 , indicating that the mitigating effect of 3-NOP depended on the composition of the BD. Emissions of CH 4 decreased upon 3-NOP supplementation for all BD, but the decrease in CH 4 emissions was smaller for GS (-26.2% for NOP60 and -28.4% for NOP80 in CH 4 yield) compared with both GSCS (-35.1% for NOP60 and -37.9% for NOP80 for CH 4 yield) and CS (-34.8% for NOP60 and -41.6% for NOP80 for CH 4 yield), with no difference between the latter 2 BD. Emissions of H 2 increased upon 3-NOP supplementation for all BD, but the H 2 yield (g/kg DMI) increased 3.16 and 3.30-fold, respectively, when NOP60 and NOP80 were supplemented to GS, and 4.70 and 4.96 fold, respectively, when NOP60 and NOP80 were supplemented to CS. In conclusion, 3-NOP can effectively decrease CH 4 emissions in dairy cows across diets, but the level of CH 4 mitigation is greater when supplemented in a corn silage-based diet compared with a grass silage-based diet., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

The objectives of this study were to induce hindgut and metabolic acidosis via abomasal infusion of corn starch and β-hydroxybutyrate (BHB), respectively, and to determine the effects of these physiological states in early-lactation dairy cows. In a 6 × 6 Latin square design, 6 rumen-fistulated Holstein-Friesian dairy cows (66 ± 18 d in milk) were subjected to 5 d of continuous abomasal infusion treatments followed by 2 d of rest. The abomasal infusion treatments followed a 3 × 2 factorial design, with 3 levels of corn starch and 2 levels of BHB. The infusions were water as control, 1.5 kg of corn starch/d, 3.0 kg of corn starch/d, 8.0 mol BHB/d, 1.5 kg of corn starch/d + 8.0 mol BHB/d, or 3.0 kg of corn starch/d + 8.0 mol BHB/d. A total mixed ration consisting of 35.0% grass silage, 37.4% corn silage, and 27.6% concentrate (on a dry matter basis) was fed at 90% of ad libitum intake of individual cows. The experiment was conducted in climate respiration chambers to facilitate determination of energy and N balance. Fecal pH decreased with each level of corn starch infused into the abomasum and was 6.49, 6.00, and 5.15 with 0.0, 1.5, and 3.0 kg of corn starch/d, respectively, suggesting that hindgut acidosis was induced with corn starch infusion. No systemic inflammatory response was observed and the permeability of the intestine or hindgut epithelium was not affected by the more acidic conditions. This induced hindgut acidosis was associated with decreased digestibility of nutrients, except for crude fat and NDF, which were not affected. Induced hindgut acidosis did not affect milk production and composition and energy balance, but increased milk N efficiency. Abomasal infusion of BHB resulted in a compensated metabolic acidosis, which was characterized by a clear disturbance of acid-base status (i.e., decreased blood total CO 2 , HCO 3 , and base excess, and a tendency for decreased urinary pH), whereas blood pH remained within a physiologically normal range. Abomasal infusion of BHB resulted in increased concentrations of BHB in milk and plasma, but both remained well below the critical threshold values for subclinical ketosis. Induced compensated metabolic acidosis, as a result of abomasally infused BHB, increased energy retained as body fat, did not affect milk production and composition or inflammatory response, but increased intestinal permeability., (Copyright © 2021 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

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 13 C 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 13 C enrichment excess of CO 2 in breath from a pulsed-dose of [1- 13 C]octanoate. Passage kinetics of roughage, concentrates, and MR were also estimated using fecal excretion curves obtained after ingestion of chromium-mordanted roughage, Yb 2 O 3 , and Co-EDTA, respectively. We conclude that [1- 13 C]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., (Copyright © 2021 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

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 NH 4 Cl, 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 NH 4 Cl/d, 5.0 mol of NH 4 Cl/d, 3.0 kg of ground corn/d, or the combination of ground corn with either of the 2 NH 4 Cl 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 NH 4 Cl 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 HCO 3 concentration < 25.0 mmol/L, and a negative base excess) was observed with 5.0 mol of NH 4 Cl/d, 3.0 kg of ground corn/d + 2.5 mol of NH 4 Cl/d, and 3.0 kg of ground corn/d + 5.0 mol of NH 4 Cl/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 NH 4 Cl/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 NH 4 Cl 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 Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

Supplementing a diet with nitrate is regarded as an effective and promising methane (CH 4 ) mitigation strategy by competing with methanogens for available hydrogen through its reduction of ammonia in the rumen. Studies have shown major reductions in CH 4 emissions with nitrate supplementation, but with large variation in response. The objective of this study was to quantitatively investigate the effect of dietary nitrate on enteric CH 4 production and yield and evaluate the variables with high potential to explain the heterogeneity of between-study variability using meta-analytical models. A data set containing 56 treatments from 24 studies was developed to conduct a meta-analysis. Dry matter (DM) intake, nitrate dose (g/kg of DM), animal body weight, roughage proportion of diet, dietary crude protein and neutral detergent fiber content, CH 4 measurement technique, and type of cattle (beef or dairy) were considered as explanatory variables. Average DM intake and CH 4 production for dairy cows (16.2 ± 2.93 kg/d; 311 ± 58.8 g/d) were much higher than for beef cattle (8.1 ± 1.57 kg/d; 146 ± 50.9 g/d). Therefore, a relative mean difference was calculated and used to conduct random-effect and mixed-effect model analysis to eliminate the large variations between types of animal due to intake. The final mixed-effect model for CH 4 production (g of CH 4 /d) had 3 explanatory variables and included nitrate dose, type of cattle, and DM intake. The final mixed-effect model for CH 4 yield (g of CH 4 /kg of DM intake) had 2 explanatory variables and included nitrate dose and type of cattle. Nitrate effect sizes on CH 4 production (dairy: -20.4 ± 1.89%; beef: -10.1 ± 1.52%) and yield (dairy: -15.5 ± 1.15%; beef: -8.95 ± 1.764%) were significantly different between the 2 types of cattle. When data from slow-release nitrate sources were removed from the analysis, there was no significant difference in type of cattle anymore for CH 4 production and yield. Nitrate dose enhanced the mitigating effect of nitrate on CH 4 production and yield by 0.911 ± 0.1407% and 0.728 ± 0.2034%, respectively, for every 1 g/kg of DM increase from its mean dietary inclusion (16.7 g/kg of DM). An increase of 1 kg of DM/d in DM intake from its mean dietary intake (11.1 kg of DM/d) decreased the effect of nitrate on CH 4 production by 0.691 ± 0.2944%. Overall, this meta-analysis demonstrated that nitrate supplementation reduces CH 4 production and yield in a dose-dependent manner, and that elevated DM intake decreases the effect of nitrate supplementation on CH 4 production. Furthermore, the stronger antimethanogenic effect on CH 4 production and yield in dairy cows than in beef steers could be related to use of slow-release nitrate in beef cattle., (Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The aim of this study was to determine the methane (CH 4 ) 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 CH 4 production (g/d) at 27 and 83 DIM, but decreased CH 4 production at 55 and 111 DIM by an average of 18.5%. This response in CH 4 production is most likely due to the differences observed in feed intake across the different stages of lactation because CH 4 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 H 2 production and intensity 12-fold; with the control diet, H 2 yield did not differ between the different stages of lactation, whereas with the 3-NOP treatment H 2 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 CH 4 emissions (while increasing H 2 emission) in early lactation Holstein-Friesian cows with positive effects on apparent total-tract digestibility of nutrients., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

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., Competing Interests: As previously indicated in the Funding section, the research described in this study was funded by TI Food and Nutrition, who also provided support in the form of salaries for authors JDV, JEE and SvG. This does not alter any of the authors adherence to PLOS ONE policies on sharing data and materials. The authors confirm that there are no further financial, professional or personal competing interests to declare.

Rumen sensors provide specific information to help understand rumen functioning in relation to health disorders and to assist in decision-making for farm management. This review focuses on the use of rumen sensors to measure ruminal pH and discusses variation in pH in both time and location, pH-associated disorders and data analysis methods to summarize and interpret rumen pH data. Discussion on the use of rumen sensors to measure redox potential as an indication of the fermentation processes is also included. Acids may accumulate and reduce ruminal pH if acid removal from the rumen and rumen buffering cannot keep pace with their production. The complexity of the factors involved, combined with the interactions between the rumen and the host that ultimately determine ruminal pH, results in large variation among animals in their pH response to dietary or other changes. Although ruminal pH and pH dynamics only partially explain the typical symptoms of acidosis, it remains a main indicator and may assist to optimize rumen function. Rumen pH sensors allow continuous monitoring of pH and of diurnal variation in pH in individual animals. Substantial drift of non-retrievable rumen pH sensors, and the difficulty to calibrate these sensors, limits their application. Significant within-day variation in ruminal pH is frequently observed, and large distinct differences in pH between locations in the rumen occur. The magnitude of pH differences between locations appears to be diet dependent. Universal application of fixed conversion factors to correct for absolute pH differences between locations should be avoided. Rumen sensors provide high-resolution kinetics of pH and a vast amount of data. Commonly reported pH characteristics include mean and minimum pH, but these do not properly reflect severity of pH depression. The area under the pH × time curve integrates both duration and extent of pH depression. The use of this characteristic, as well as summarizing parameters obtained from fitting equations to cumulative pH data, is recommended to identify pH variation in relation to acidosis. Some rumen sensors can also measure the redox potential. This measurement helps to understand rumen functioning, as the redox potential of rumen fluid directly reflects the microbial intracellular redox balance status and impacts fermentative activity of rumen microorganisms. Taken together, proper assessment and interpretation of data generated by rumen sensors requires consideration of their limitations under various conditions.

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., (The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

3-Nitrooxypropanol (NOP) is a promising methane (CH 4 ) inhibitor. Recent studies have shown major reductions in CH 4 emissions from beef and dairy cattle when using NOP but with large variation in response. The objective of this study was to quantitatively evaluate the factors that explain heterogeneity in response to NOP using meta-analytical approaches. Data from 11 experiments and 38 treatment means were used. Factors considered were cattle type (dairy or beef), measurement technique (GreenFeed technique, C-Lock Inc., Rapid City, SD; sulfur hexafluoride tracer technique; and respiration chamber technique), dry matter (DM) intake, body weight, NOP dose, roughage proportion, dietary crude protein content, and dietary neutral detergent fiber (NDF) content. The mean difference (MD) in CH 4 production (g/d) and CH 4 yield (g/kg of DM intake) was calculated by subtracting the mean of CH 4 emission for the control group from that of the NOP-supplemented group. Forest plots of standardized MD indicated variable effect sizes of NOP across studies. Compared with beef cattle, dairy cattle had a much larger feed intake (22.3 ± 4.13 vs. 7.3 ± 0.97 kg of DM/d; mean ± standard deviation) and CH 4 production (351 ± 94.1 vs. 124 ± 44.8 g/d). Therefore, in further analyses across dairy and beef cattle studies, MD was expressed as a proportion (%) of observed control mean. The final mixed-effect model for relative MD in CH 4 production included cattle type, NOP dose, and NDF content. When adjusted for NOP dose and NDF content, the CH 4 -mitigating effect of NOP was less in beef cattle (-22.2 ± 3.33%) than in dairy cattle (-39.0 ± 5.40%). An increase of 10 mg/kg of DM in NOP dose from its mean (123 mg/kg of DM) enhanced the NOP effect on CH 4 production decline by 2.56 ± 0.550%. However, a greater dietary NDF content impaired the NOP effect on CH 4 production by 1.64 ± 0.330% per 10 g/kg DM increase in NDF content from its mean (331 g of NDF/kg of DM). The factors included in the final mixed-effect model for CH 4 yield were -17.1 ± 4.23% (beef cattle) and -38.8 ± 5.49% (dairy cattle), -2.48 ± 0.734% per 10 mg/kg DM increase in NOP dose from its mean, and 1.52 ± 0.406% per 10 g/kg DM increase in NDF content from its mean. In conclusion, the present meta-analysis indicates that a greater NOP dose enhances the NOP effect on CH 4 emission, whereas an increased dietary fiber content decreases its effect. 3-Nitrooxypropanol has stronger antimethanogenic effects in dairy cattle than in beef cattle., (Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The objective of the present study was to compare the prediction potential of milk Fourier-transform infrared spectroscopy (FTIR) for CH 4 emissions of dairy cows with that of gas chromatography (GC)-based milk fatty acids (MFA). Data from 9 experiments with lactating Holstein-Friesian cows, with a total of 30 dietary treatments and 218 observations, were used. Methane emissions were measured for 3 consecutive days in climate respiration chambers and expressed as production (g/d), yield (g/kg of dry matter intake; DMI), and intensity (g/kg of fat- and protein-corrected milk; FPCM). Dry matter intake was 16.3 ± 2.18 kg/d (mean ± standard deviation), FPCM yield was 25.9 ± 5.06 kg/d, CH 4 production was 366 ± 53.9 g/d, CH 4 yield was 22.5 ± 2.10 g/kg of DMI, and CH 4 intensity was 14.4 ± 2.58 g/kg of FPCM. Milk was sampled during the same days and analyzed by GC and by FTIR. Multivariate GC-determined MFA-based and FTIR-based CH 4 prediction models were developed, and subsequently, the final CH 4 prediction models were evaluated with root mean squared error of prediction and concordance correlation coefficient analysis. Further, we performed a random 10-fold cross validation to calculate the performance parameters of the models (e.g., the coefficient of determination of cross validation). The final GC-determined MFA-based CH 4 prediction models estimate CH 4 production, yield, and intensity with a root mean squared error of prediction of 35.7 g/d, 1.6 g/kg of DMI, and 1.6 g/kg of FPCM and with a concordance correlation coefficient of 0.72, 0.59, and 0.77, respectively. The final FTIR-based CH 4 prediction models estimate CH 4 production, yield, and intensity with a root mean squared error of prediction of 43.2 g/d, 1.9 g/kg of DMI, and 1.7 g/kg of FPCM and with a concordance correlation coefficient of 0.52, 0.40, and 0.72, respectively. The GC-determined MFA-based prediction models described a greater part of the observed variation in CH 4 emission than did the FTIR-based models. The cross validation results indicate that all CH 4 prediction models (both GC-determined MFA-based and FTIR-based models) are robust; the difference between the coefficient of determination and the coefficient of determination of cross validation ranged from 0.01 to 0.07. The results indicate that GC-determined MFA have a greater potential than FTIR spectra to estimate CH 4 production, yield, and intensity. Both techniques hold potential but may not yet be ready to predict CH 4 emission of dairy cows in practice. Additional CH 4 measurements are needed to improve the accuracy and robustness of GC-determined MFA and FTIR spectra for CH 4 prediction., (Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Several in vivo CH 4 measurement techniques have been developed but are not suitable for precise and accurate large-scale measurements; hence, proxies for CH 4 emissions in dairy cattle have been proposed, including the milk fatty acid (MFA) profile. The aim of the present study was to determine whether recently developed MFA-based prediction equations for CH 4 emission are applicable to dairy cows with different diacylglycerol o-acyltransferase 1 (DGAT1) K232A polymorphism and fed diets with and without linseed oil. Data from a crossover design experiment were used, encompassing 2 dietary treatments (i.e., a control diet and a linseed oil diet, with a difference in dietary fat content of 22 g/kg of dry matter) and 24 lactating Holstein-Friesian cows (i.e., 12 cows with DGAT1 KK genotype and 12 cows with DGAT1 AA genotype). Enteric CH 4 production was measured in climate respiration chambers and the MFA profile was analyzed using gas chromatography. Observed CH 4 emissions were compared with CH 4 emissions predicted by previously developed MFA-based CH 4 prediction equations. The results indicate that different types of diets (i.e., with or without linseed oil), but not the DGAT1 K232A polymorphism, affect the ability of previously derived prediction equations to predict CH 4 emission. However, the concordance correlation coefficient was smaller than or equal to 0.30 for both dietary treatments separately, both DGAT1 genotypes separately, and the complete data set. We therefore concluded that previously derived MFA-based CH 4 prediction equations can neither accurately nor precisely predict CH 4 emissions of dairy cows managed under strategies differing from those under which the original prediction equations were developed., (Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

This study aimed to quantify the relationship between CH 4 emission and fatty acids, volatile metabolites, and nonvolatile metabolites in milk of dairy cows fed forage-based diets. Data from 6 studies were used, including 27 dietary treatments and 123 individual observations from lactating Holstein-Friesian cows. These dietary treatments covered a large range of forage-based diets, with different qualities and proportions of grass silage and corn silage. Methane emission was measured in climate respiration chambers and expressed as production (g per day), yield (g per kg of dry matter intake; DMI), and intensity (g per kg of fat- and protein-corrected milk; FPCM). Milk samples were analyzed for fatty acids by gas chromatography, for volatile metabolites by gas chromatography-mass spectrometry, and for nonvolatile metabolites by nuclear magnetic resonance. Dry matter intake was 15.9 ± 1.90 kg/d (mean ± SD), FPCM yield was 25.2 ± 4.57 kg/d, CH 4 production was 359 ± 51.1 g/d, CH 4 yield was 22.6 ± 2.31 g/kg of DMI, and CH 4 intensity was 14.5 ± 2.59 g/kg of FPCM. The results show that changes in individual milk metabolite concentrations can be related to the ruminal CH 4 production pathways. Several of these relationships were diet driven, whereas some were partly dependent on FPCM yield. Next, prediction models were developed and subsequently evaluated based on root mean square error of prediction (RMSEP), concordance correlation coefficient (CCC) analysis, and random 10-fold cross-validation. The best models with milk fatty acids (in g/100 g of fatty acids; MFA) alone predicted CH 4 production, yield, and intensity with a RMSEP of 34 g/d, 2.0 g/kg of DMI, and 1.7 g/kg of FPCM, and with a CCC of 0.67, 0.44, and 0.75, respectively. The CH 4 prediction potential of both volatile metabolites alone and nonvolatile metabolites alone was low, regardless of the unit of CH 4 emission, as evidenced by the low CCC values (<0.35). The best models combining the 3 types of metabolites as selection variables resulted in the inclusion of only MFA for CH 4 production and CH 4 yield. For CH 4 intensity, MFA, volatile metabolites, and nonvolatile metabolites were included in the prediction model. This resulted in a small improvement in prediction potential (CCC of 0.80; RMSEP of 1.5 g/kg of FPCM) relative to MFA alone. These results indicate that volatile and nonvolatile metabolites in milk contain some information to increase our understanding of enteric CH 4 production of dairy cows, but that it is not worthwhile to determine the volatile and nonvolatile metabolites in milk to estimate CH 4 emission of dairy cows. We conclude that MFA have moderate potential to predict CH 4 emission of dairy cattle fed forage-based diets, and that the models can aid in the effort to understand and mitigate CH 4 emissions of dairy cows., (Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

DNA based methods have been widely used to study the complexity of the rumen microbiota, and it is well known that the method of DNA extraction is a critical step in enabling accurate assessment of this complexity. Rumen fluid (RF) and fibrous content (FC) fractions differ substantially in terms of their physical nature and associated microorganisms. The aim of this study was therefore to assess the effect of four DNA extraction methods (RBB, PBB, FDSS, PQIAmini) differing in cell lysis and/or DNA recovery methods on the observed microbial diversity in RF and FC fractions using samples from four rumen cannulated dairy cows fed 100% grass silage (GS100), 67% GS and 33% maize silage (GS67MS33), 33% GS and 67% MS (GS33MS67), or 100% MS (MS100). An ANOVA statistical test was applied on DNA quality and yield measurements, and it was found that the DNA yield was significantly affected by extraction method ( p < 0.001) and fraction ( p < 0.001). The 260/280 ratio was not affected by extraction ( p = 0.08) but was affected by fraction ( p = 0.03). On the other hand, the 260/230 ratio was affected by extraction method ( p < 0.001) but not affected by fraction ( p = 0.8). However, all four extraction procedures yielded DNA suitable for further analysis of bacterial, archaeal and anaerobic fungal communities using quantitative PCR and pyrosequencing of relevant taxonomic markers. Redundancy analysis (RDA) of bacterial 16S rRNA gene sequence data at the family level showed that there was a significant effect of rumen fraction ( p = 0.012), and that PBB ( p = 0.012) and FDSS ( p = 0.024) also significantly contributed to explaining the observed variation in bacterial community composition. Whilst the DNA extraction method affected the apparent bacterial community composition, no single extraction method could be concluded to be ineffective. No obvious effect of DNA extraction method on the anaerobic fungi or archaea was observed, although fraction effects were evident for both. In summary, the comprehensive assessment of observed communities of bacteria, archaea and anaerobic fungi described here provides insight into a rational basis for selecting an optimal methodology to obtain a representative picture of the rumen microbiota.

Complex interactions between rumen microbiota, cow genetics, and diet composition may exist. Therefore, the effect of linseed oil, DGAT1 K232A polymorphism (DGAT1), and the interaction between linseed oil and DGAT1 on CH 4 and H 2 emission, energy and N metabolism, lactation performance, ruminal fermentation, and rumen bacterial and archaeal composition was investigated. Twenty-four lactating Holstein-Friesian cows (i.e., 12 with DGAT1 KK genotype and 12 with DGAT1 AA genotype) were fed 2 diets in a crossover design: a control diet and a linseed oil diet (LSO) with a difference of 22 g/kg of dry matter (DM) in fat content between the 2 diets. Both diets consisted of 40% corn silage, 30% grass silage, and 30% concentrates (DM basis). Apparent digestibility, lactation performance, N and energy balance, and CH 4 emission were measured in climate respiration chambers, and rumen fluid samples were collected using the oral stomach tube technique. No linseed oil by DGAT1 interactions were observed for digestibility, milk production and composition, energy and N balance, CH 4 and H 2 emissions, and rumen volatile fatty acid concentrations. The DGAT1 KK genotype was associated with a lower proportion of polyunsaturated fatty acids in milk fat, and with a higher milk fat and protein content, and proportion of saturated fatty acids in milk fat compared with the DGAT1 AA genotype, whereas the fat- and protein-corrected milk yield was unaffected by DGAT1. Also, DGAT1 did not affect nutrient digestibility, CH 4 or H 2 emission, ruminal fermentation or ruminal archaeal and bacterial concentrations. Rumen bacterial and archaeal composition was also unaffected in terms of the whole community, whereas at the genus level the relative abundances of some bacterial genera were found to be affected by DGAT1. The DGAT1 KK genotype was associated with a lower metabolizability (i.e., ratio of metabolizable to gross energy intake), and with a tendency for a lower milk N efficiency compared with the DGAT1 AA genotype. The LSO diet tended to decrease CH 4 production (g/d) by 8%, and significantly decreased CH 4 yield (g/kg of DM intake) by 6% and CH 4 intensity (g/kg of fat- and protein-corrected milk) by 11%, but did not affect H 2 emission. The LSO diet also decreased ruminal acetate molar proportion, the acetate to propionate ratio, and the archaea to bacteria ratio, whereas ruminal propionate molar proportion and milk N efficiency increased. Ruminal bacterial and archaeal composition tended to be affected by diet in terms of the whole community, with several bacterial genera found to be significantly affected by diet. These results indicate that DGAT1 does not affect enteric CH 4 emission and production pathways, but that it does affect traits other than lactation characteristics, including metabolizability, N efficiency, and the relative abundance of Bifidobacterium. Additionally, linseed oil reduces CH 4 emission independent of DGAT1 and affects the rumen microbiota and its fermentative activity., (The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).)

This study investigated the relationships between methane (CH4) emission and fatty acids, volatile metabolites (V) and non-volatile metabolites (NV) in milk of dairy cows. Data from an experiment with 32 multiparous dairy cows and four diets were used. All diets had a roughage : concentrate ratio of 80 : 20 based on dry matter (DM). Roughage consisted of either 1000 g/kg DM grass silage (GS), 1000 g/kg DM maize silage (MS), or a mixture of both silages (667 g/kg DM GS and 333 g/kg DM MS; 333 g/kg DM GS and 677 g/kg DM MS). Methane emission was measured in climate respiration chambers and expressed as production (g/day), yield (g/kg dry matter intake; DMI) and intensity (g/kg fat- and protein-corrected milk; FPCM). Milk was sampled during the same days and analysed for fatty acids by gas chromatography, for V by gas chromatography-mass spectrometry, and for NV by nuclear magnetic resonance. Several models were obtained using a stepwise selection of (1) milk fatty acids (MFA), V or NV alone, and (2) the combination of MFA, V and NV, based on the minimum Akaike's information criterion statistic. Dry matter intake was 16.8±1.23 kg/day, FPCM yield was 25.0±3.14 kg/day, CH4 production was 406±37.0 g/day, CH4 yield was 24.1±1.87 g/kg DMI and CH4 intensity was 16.4±1.91 g/kg FPCM. The observed CH4 emissions were compared with the CH4 emissions predicted by the obtained models, based on concordance correlation coefficient (CCC) analysis. The best models with MFA alone predicted CH4 production, yield and intensity with a CCC of 0.80, 0.71 and 0.69, respectively. The best models combining the three types of metabolites included MFA and NV for CH4 production and CH4 yield, whereas for CH4 intensity MFA, NV and V were all included. These models predicted CH4 production, yield and intensity better with a higher CCC of 0.92, 0.78 and 0.93, respectively, and with increased accuracy (C b ) and precision (r). The results indicate that MFA alone have moderate to good potential to estimate CH4 emission, and furthermore that including V (CH4 intensity only) and NV increases the CH4 emission prediction potential. This holds particularly for the prediction model for CH4 intensity.

Efforts to reduce the carbon footprint of milk production through selection and management of low-emitting cows require accurate and large-scale measurements of methane (CH 4 ) emissions from individual cows. Several techniques have been developed to measure CH 4 in a research setting but most are not suitable for large-scale recording on farm. Several groups have explored proxies (i.e., indicators or indirect traits) for CH 4 ; ideally these should be accurate, inexpensive, and amenable to being recorded individually on a large scale. This review (1) systematically describes the biological basis of current potential CH 4 proxies for dairy cattle; (2) assesses the accuracy and predictive power of single proxies and determines the added value of combining proxies; (3) provides a critical evaluation of the relative merit of the main proxies in terms of their simplicity, cost, accuracy, invasiveness, and throughput; and (4) discusses their suitability as selection traits. The proxies range from simple and low-cost measurements such as body weight and high-throughput milk mid-infrared spectroscopy (MIR) to more challenging measures such as rumen morphology, rumen metabolites, or microbiome profiling. Proxies based on rumen samples are generally poor to moderately accurate predictors of CH 4 , and are costly and difficult to measure routinely on-farm. Proxies related to body weight or milk yield and composition, on the other hand, are relatively simple, inexpensive, and high throughput, and are easier to implement in practice. In particular, milk MIR, along with covariates such as lactation stage, are a promising option for prediction of CH 4 emission in dairy cows. No single proxy was found to accurately predict CH 4 , and combinations of 2 or more proxies are likely to be a better solution. Combining proxies can increase the accuracy of predictions by 15 to 35%, mainly because different proxies describe independent sources of variation in CH 4 and one proxy can correct for shortcomings in the other(s). The most important applications of CH 4 proxies are in dairy cattle management and breeding for lower environmental impact. When breeding for traits of lower environmental impact, single or multiple proxies can be used as indirect criteria for the breeding objective, but care should be taken to avoid unfavorable correlated responses. Finally, although combinations of proxies appear to provide the most accurate estimates of CH 4 , the greatest limitation today is the lack of robustness in their general applicability. Future efforts should therefore be directed toward developing combinations of proxies that are robust and applicable across diverse production systems and environments., (The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).)

Diurnal patterns of ruminal fermentation metabolites and microbial communities are not commonly assessed when investigating variation in ruminal CH 4 production. The aims of this study were to monitor diurnal patterns of: (i) gaseous and dissolved metabolite concentrations in the bovine rumen, (ii) H 2 and CH 4 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. H 2 and CH 4 emission (mass per unit of time) was measured in respiration chambers from day 13 to 17. A 100-fold increase in ruminal H 2 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 H 2 and CH 4 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 (log 10 16S ribosomal RNA gene copies based) were affected by time, and were increased by linseed oil supplementation. Archaeal concentrations (log 10 16S ribosomal RNA gene copies based) tended to be affected by time and were not affected by diet, despite linseed oil supplementation decreasing CH 4 emission, tending to decrease the partial pressure of CH 4 , 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, H 2 , and CH 4 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., (© 2016 Society of Chemical Industry.)

Methane (CH4) emission of dairy cows contributes significantly to the carbon footprint of the dairy chain; therefore, a better understanding of CH4 formation is urgently needed. The present study explored the milk metabolome by gas chromatography-mass spectrometry (milk volatile metabolites) and nuclear magnetic resonance (milk nonvolatile metabolites) to better understand the biological pathways involved in CH4 emission in dairy cattle. Data were used from a randomized block design experiment with 32 multiparous Holstein-Friesian cows and 4 diets. All diets had a roughage:concentrate ratio of 80:20 (dry matter basis) and the roughage was grass silage (GS), corn silage (CS), or a mixture of both (67% GS, 33% CS; 33% GS, 67% CS). Methane emission was measured in climate respiration chambers and expressed as CH4 yield (per unit of dry matter intake) and CH4 intensity (per unit of fat- and protein-corrected milk; FPCM). No volatile or nonvolatile metabolite was positively related to CH4 yield, and acetone (measured as a volatile and as a nonvolatile metabolite) was negatively related to CH4 yield. The volatile metabolites 1-heptanol-decanol, 3-nonanone, ethanol, and tetrahydrofuran were positively related to CH4 intensity. None of the volatile metabolites was negatively related to CH4 intensity. The nonvolatile metabolites acetoacetate, creatinine, ethanol, formate, methylmalonate, and N-acetylsugar A were positively related to CH4 intensity, and uridine diphosphate (UDP)-hexose B and citrate were negatively related to CH4 intensity. Several volatile and nonvolatile metabolites that were correlated with CH4 intensity also were correlated with FPCM and not significantly related to CH4 intensity anymore when FPCM was included as covariate. This suggests that changes in these milk metabolites may be related to changes in milk yield or metabolic processes involved in milk synthesis. The UDP-hexose B was correlated with FPCM, whereas citrate was not. Both metabolites were still related to CH4 intensity when FPCM was included as covariate. The UDP-hexose B is an intermediate of lactose metabolism, and citrate is an important intermediate of Krebs cycle-related energy processes. Therefore, the negative correlation of UDP-hexose B and citrate with CH4 intensity may reflect a decrease in metabolic activity in the mammary gland. Our results suggest that an integrative approach including milk yield and composition, and dietary and animal traits will help to explain the biological metabolism of dairy cows in relation to methane CH4 emission., (Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)