Relationships between methane production and milk fatty acid profiles in dairy cattle

Review of equations to predict methane emissions in dairy cows from milk fatty acid profiles and their application to commercial dairy farms

Greenhouse gas emission from the activities of all productive sectors is currently a topic of foremost importance. The major contributors in the livestock sector are ruminants, especially dairy cows. This study aimed to evaluate and compare 21 equations for predicting enteric methane emissions (EME) developed on the basis of milk traits and fatty acid profiles, which were selected from 46 retrieved through a literature review. We compiled a reference database of the detailed fatty acid profiles, determined by GC, of 992 lactating cows from 85 herds under 4 different dairy management systems. The cows were classified according to DIM, parity order, and dairy system. This database was the basis on which we estimated EME using the selected equations. The EME traits estimated were methane yield (20.63 ± 2.26 g/kg DMI, 7 equations), methane intensity (16.05 ± 2.76 g/kg of corrected milk, 4 equations), and daily methane production (385.4 ± 68.2 g/d, 10 equations). Methane production was also indirectly calculated by multiplying the daily corrected milk yield by the methane intensity (416.6 ± 134.7 g/d, 4 equations). We also tested for the effects of DIM, parity, and dairy system (as a correction factor) on the estimates. In general, we observed little consistency among the EME estimates obtained from the different equations, with exception of those obtained from meta-analyses of a range of data from different research centers. We found all the EME predictions to be highly affected by the sources of variation included in the statistical model: DIM significantly affected the results of 19 of the 21 equations, and parity order influenced the results of 13. Different patterns were observed for different equations with only some of them in accordance with expectations based on the cow's physiology. Finally, the best predictions of daily methane production were obtained when a measure of milk yield was included in the equation or when the estimate was indirectly calculated from daily milk yield and methane intensity.

Comparison of miR-106b, miR-191, and miR-30d expression dynamics in milk with regard to its composition in Holstein and Ayrshire cows

OBJECTIVE

Milk composition varies considerably and depends on paratypical, genetic, and epigenetic factors. MiRNAs belong to the class of small non-coding RNAs; they are one of the key tools of epigenetic control because of their ability to regulate gene expression at the post-transcriptional level. We compared the relative expression levels of miR-106b, miR-191, and miR-30d in milk to demonstrate the relationship between the content of these miRNAs with protein and fat components of milk in Holstein and Ayrshire cattle.

METHODS

Milk fat, protein, and casein contents were determined in the obtained samples, as well as the content of the main fatty acids (g/100 g milk), including: saturated acids, such as myristic (C14:0), palmitic (C16:0), and stearic (C18:0) acids; monounsaturated acids, including oleic (C18:1) acid; as well as long-, medium- and short-chain, polyunsaturated, and trans fatty acids. Real-time stem-loop one-tube reverse transcription polymerase chain reaction with TaqMan probes was used to measure the miRNA expression levels.

RESULTS

The miRNA expression levels in milk samples were found to be decreased in the first two months in Holstein breed, and in the first four months in Ayrshire breed. Correlation analysis did not reveal any dependence between changes in the expression level of miRNA and milk fat content, but showed a multidirectional relationship with individual milk fatty acids. Positive associations between the expression levels of miR-106b and miR-30d and protein and casein content were found in the Ayrshire breed. Receiver operating characteristic curve analysis showed that miR-106b and miR-30d expression levels can cause changes in fatty acid and protein composition of milk in Ayrshire cows, whereas miR-106b expression level determines the fatty acid composition in Holsteins.

CONCLUSION

The data obtained in this study showed that miR-106b, miR-191, and miR-30d expression levels in milk samples have peculiarities associated with breed affiliation and the lactation period.

Use of methane production data for genetic prediction in beef cattle: A review

Methane (CH4) is a greenhouse gas that is produced and emitted from ruminant animals through enteric fermentation. Methane production from cattle has an environmental impact and is an energetic inefficiency. In the beef industry, CH4 production from enteric fermentation impacts all three pillars of sustainability: environmental, social, and economic. A variety of factors influence the quantity of CH4 produced during enteric fermentation, including characteristics of the rumen and feed composition. There are several methodologies available to either quantify or estimate CH4 production from cattle, all with distinct advantages and disadvantages. Methodologies include respiration calorimetry, the sulfur-hexafluoride tracer technique, infrared spectroscopy, prediction models, and the GreenFeed system. Published studies assess the accuracy of the various methodologies and compare estimates from different methods. There are advantages and disadvantages of each technology as they relate to the use of these phenotypes in genetic evaluation systems. Heritability and variance components of CH4 production have been estimated using the different CH4 quantification methods. Agreement in both the amounts of CH4 emitted and heritability estimates of CH4 emissions between various measurement methodologies varies in the literature. Using greenhouse gas traits in selection indices along with relevant output traits could provide producers with a tool to make selection decisions on environmental sustainability while also considering productivity. The objective of this review was to discuss factors that influence CH4 production, methods to quantify CH4 production for genetic evaluation, and genetic parameters of CH4 production in beef cattle.

Differences in Donor Animal Production Stage Affect Repeatability of In Vitro Rumen Fermentation Kinetics

In vitro gas production techniques (IVGPT) are widely used to screen feeds and feed additives to reduce the number of animals needed for experiments, which in turn, reduces costs and increases animal welfare. However, information about repeatability is scarce. The objective of this study was to evaluate the variation from in vitro gas production fermentations in the same laboratory using the same feed substrate. The source of rumen fluid used in the fermentations was from two different farms with either cannulated lactating dairy cows or cannulated fasting heifers, representing two distinct stages of production (donor types). Seventeen 24 h fermentations, undertaken during a year, were used to evaluate the variation between the following parameters: gas curve parameters, baseline-corrected total gas production (TGP (mL at Standard Temperature and Pressure (STP))/g incubated dry matter (DM)), methane concentration (%) and yield (mL gas at STP/g DM), pH and degraded dry matter (dDM). Significant differences between donor types were found for the pH of the rumen fluid from individual animals and pH of fermented fluid. However, no significant differences were observed within donor type. The means for methane concentration and yield, after 24 h of fermentation, were not significantly different between or within donor types. Rate of early gas production was significantly different between donor types, but baseline-corrected TGP was not significantly different at 24 h. No dDM differences after 24 h of fermentation between or within donor types were detected. Gas production curves were different between donor types, being either a monophasic version of the sigmoidal model or an exponential curve for the heifers and the production animals, respectively. No differences were observed within type. Repeatability of rumen fluid (CVRF), calculated as the coefficient of variation, and the associated parameters, which were investigated, was best for methane yield (CVRFALL = 0.3%) and least for TGP at 3 h (CVRFALL = 3%). Repeatability was dependent on donor type.

Enteric and manure emissions from Holstein-Friesian dairy cattle fed grass silage-based or corn silage-based diets

This study aimed to evaluate trade-offs between enteric and manure CH4 emissions, and the size of synergistic effects for CH4 and nitrogenous emissions (NH3 and N2O). 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 CH4, CO2, NH3, and N2O in incoming and outgoing air were measured. Cow excretion of organic matter was higher for CS compared with GS. Enteric CH4 and cow-associated NH3 and N2O emissions (i.e., manure emissions excluded) were lower for CS compared with GS (-11, -40, and -45%, respectively). The CH4 and N2O emissions from stored manure (i.e., in absence of cows) were not affected by diet, whereas that of NH3 emission tended to be lower for CS compared with GS. In conclusion, there was no trade-off between enteric and manure CH4 emissions, and there were synergistic effects for CH4 and nitrogenous emissions when grass silage was exchanged for corn silage, without balancing the diets for crude protein content, in this short-term study.

Review: Diving into the cow hologenome to reduce methane emissions and increase sustainability

Interest on methane emissions from livestock has increased in later years as it is an anthropogenic greenhouse gas with an important warming potential. The rumen microbiota has a large influence on the production of enteric methane. Animals harbour a second genome consisting of microbes, collectively referred to as the "microbiome". The rumen microbial community plays an important role in feed digestion, feed efficiency, methane emission and health status. This review recaps the current knowledge on the genetic control that the cow exerts on the rumen microbiota composition. Heritability estimates for the rumen microbiota composition range between 0.05 and 0.40 in the literature, depending on the taxonomical group or microbial gene function. Variables depicting microbial diversity or aggregating microbial information are also heritable within the same range. This study includes a genome-wide association analysis on the microbiota composition, considering the relative abundance of some microbial taxa previously associated to enteric methane in dairy cattle (Archaea, Dialister, Entodinium, Eukaryota, Lentisphaerae, Methanobrevibacter, Neocallimastix, Prevotella and Stentor). Host genomic regions associated with the relative abundance of these microbial taxa were identified after Benjamini-Hoschberg correction (Padj < 0.05). An in-silico functional analysis using FUMA and DAVID online tools revealed that these gene sets were enriched in tissues like brain cortex, brain amigdala, pituitary, salivary glands and other parts of the digestive system, and are related to appetite, satiety and digestion. These results allow us to have greater knowledge about the composition and function of the rumen microbiome in cattle. The state-of-the art strategies to include methane traits in the selection indices in dairy cattle populations is reviewed. Several strategies to include methane traits in the selection indices have been studied worldwide, using bioeconomical models or economic functions under theoretical frameworks. However, their incorporation in the breeding programmes is still scarce. Some potential strategies to include methane traits in the selection indices of dairy cattle population are presented. Future selection indices will need to increase the weight of traits related to methane emissions and sustainability. This review will serve as a compendium of the current state of the art in genetic strategies to reduce methane emissions in dairy cattle.

Methane release from enteric fermentation and manure management of domestic water buffalo in Nepal

Methane (CH₄) emission in livestock arises from enteric fermentation (EnF) and manure management (MM). This study develops the country-specific CH₄ emission factors (EFs) in both EnF and MM for domestic water buffalo (Bubalus bubalis) and estimates total CH₄ emission in Nepal using Intergovernmental Panel on Climate Change (IPCC) Tier 2 methodology. Seasonal field data were collected on morphological characteristics, feed characteristics, and manure management practices of the buffalo. The buffalo population was divided into five age groups, and at least 35 buffalo individuals were measured from each age group in the Hilly and Plain regions of Nepal in the winter and summer seasons. Buffalo adult male (BAM) had the highest body weight of 530 ± 53 kg in the plain region and 514 ± 65 kg in the Hill region. Similarly, the weight of buffalo calf (BC) was 91 ± 25 kg in the plain region and 77 ± 26 kg in the Hill region. For different age groups of buffalo, EnF EFs ranged from 34 ± 8 to 90 ± 10 kg CH₄ head^-1 year^-1 and MM EFs ranged from 2.5 ± 0.5 to 7.5 ± 0.5 kg CH₄ head^-1 year^-1. The estimated EnF and MM EFs of buffalo were not statistically different by region (p > 0 .05). The total CH₄ flux from buffalo was 347.8 Gg year^-1 in Nepal, contributing 322.2 Gg year^-1 from EnF and 25.6 Gg year^-1 from MM. The country-specific EFs are highly recommended for precise computing of the national emissions and carrying out mitigation action.

Effects of replacement of barley with oats on milk fatty acid composition in dairy cows fed grass silage-based diets

This study consists of milk fatty acid (FA) data collected during 2 in vivo experiments. For this study, 8 cows from each experiment were included in a replicated 4 × 4 Latin square design. At the start of experiment 1 (Exp1) cows were at (mean ± standard deviation) 87 ± 34.6 d in milk, 625 ± 85.0 kg of body weight, and 32.1 ± 4.17 kg/d milk yield and at the start of experiment 2 (Exp2) cows were at 74 ± 18.2 d in milk, 629 ± 87.0 kg of body weight, and 37.0 ± 3.2 kg/d milk yield. In Exp1, we examined the effects of gradual replacement of barley with hulled oats (oats with hulls) on milk FA composition. The basal diet was grass silage and rapeseed meal (58 and 10% of diet DM, respectively), and the 4 grain supplements were formulated so that barley was gradually replaced by hulled oats at levels of 0, 33, 67, and 100% on dry matter basis. In Exp2, we examined (1) the effects of replacing barley with both hulled and dehulled oats (oats without hulls) and (2) the effects of gradual replacement of hulled oats with dehulled oats on milk FA composition. The basal diet was grass silage and rapeseed meal (60 and 10% of diet DM, respectively), and the 4 pelleted experimental concentrates were barley, hulled oats, a 50:50 mixture of hulled and dehulled oats, and dehulled oats on dry matter basis. In Exp1, gradual replacement of barley with hulled oats decreased relative proportions of 14:0, 16:0, and total saturated FA (SFA) in milk fat linearly, whereas proportions of 18:0, 18:1, total monounsaturated FA, and total cis unsaturated FA increased linearly. Transfer efficiency of total C18 decreased linearly when barley was replaced by hulled oats in Exp1. In Exp2, relative proportions of 14:0, 16:0, and total SFA were lower, whereas proportions of 18:0, 18:1, monounsaturated FA, and cis unsaturated FA were higher in milk from cows fed the oat diets than in milk from cows fed the barley diet. Moreover, in Exp2, gradual replacement of hulled oats with dehulled oats slightly decreased the relative proportion of 14:0 in milk fat but did not affect the proportions of 16:0, 18:0, 18:1, total SFA, monounsaturated FA, trans FA, or polyunsaturated FA. In Exp2, transfer efficiency of total C18 was lower when cows were fed the oat diets than when fed the barley diet and decreased linearly when hulled oats were replaced with dehulled oats. Predictions of daily CH₄ emissions (g/d) using the on-farm available variables energy-corrected milk yield and body weight were not markedly improved by including milk concentrations of individual milk FA in prediction equations. In conclusion, replacement of barley with oats as a concentrate supplement for dairy cows fed a grass silage-based diet could offer a practical strategy to change the FA composition of milk to be more in accordance with international dietary guidelines regarding consumption of SFA.

Estimates of the genetic contribution to methane emission in dairy cows: a meta-analysis

The present study aimed to perform a meta-analysis using the three-level model to integrate published estimates of genetic parameters for methane emission traits [methane yield (METY), methane intensity (METINT), and methane production (METP)] in dairy cows. Overall, 40 heritability estimates and 32 genetic correlations from 17 papers published between 2015 and 2021 were used in this study. The heritability estimates for METY, METINT, and METP were 0.244, 0.180, and 0.211, respectively. The genetic correlation estimates between METY and METINT with corrected milk yield for fat, protein, and or energy (CMY) were negative (- 0.433 and - 0.262, respectively). Also, genetic correlation estimates between METINT with milk fat and protein percentages were 0.254 and 0.334, respectively. Although the genetic correlation estimate of METP with daily milk yield was 0.172, its genetic correlation with CMY was 0.446. All genetic correlation estimates between METP with milk fat and protein yield or percentage ranged from 0.005 (between METP-milk protein yield) to 0.185 (between METP-milk protein percentage). The current meta-analysis confirmed the presence of additive genetic variation for methane emission traits in dairy cows that could be exploited in genetic selection plans.

Selecting for Feed Efficient Cows Will Help to Reduce Methane Gas Emissions

In the last decade, several countries have included feed efficiency (as residual feed intake; RFI) in their breeding goal. Recent studies showed that RFI is favorably correlated with methane emissions. Thus, selecting for lower emitting animals indirectly through RFI could be a short-term strategy in order to achieve the intended reduction set by the EU Commission (-55% for 2030). The objectives were to 1) estimate genetic parameters for six methane traits, including genetic correlations between methane traits, production, and feed efficiency traits, 2) evaluate the expected correlated response of methane traits when selecting for feed efficiency with or without including methane, 3) quantify the impact of reducing methane emissions in dairy cattle using the Danish Holstein population as an example. A total of 26,664 CH4 breath records from 647 Danish Holstein cows measured over 7 years in a research farm were analyzed. Records on dry matter intake (DMI), body weight (BW), and energy corrected milk (ECM) were also available. Methane traits were methane concentration (MeC, ppm), methane production (MeP; g/d), methane yield (MeY; g CH4/kg DMI), methane intensity (MeI; g CH4/kg ECM), residual methane concentration (RMeC), residual methane production (RMeP, g/d), and two definitions of residual feed intake with or without including body weight change (RFI1, RFI2). The estimated heritability of MeC was 0.20 ± 0.05 and for MeP, it was 0.21 ± 0.05, whereas heritability estimates for MeY and MeI were 0.22 ± 0.05 and 0.18 ± 0.04, and for the RMeC and RMeP, they were 0.23 ± 0.06 and 0.16 ± 0.02, respectively. Genetic correlations between methane traits ranged from moderate to highly correlated (0.48 ± 0.16–0.98 ± 0.01). Genetic correlations between methane traits and feed efficiency were all positive, ranging from 0.05 ± 0.20 (MeI-RFI2) to 0.76 ± 0.09 (MeP-RFI2). Selection index calculations showed that selecting for feed efficiency has a positive impact on reducing methane emissions’ expected response, independently of the trait used (MeP, RMeP, or MeI). Nevertheless, adding a negative economic value for methane would accelerate the response and help to reach the reduction goal in fewer generations. Therefore, including methane in the breeding goal seems to be a faster way to achieve the desired methane emission reductions in dairy cattle.

Predicting enteric methane emission in lactating Holsteins based on reference methane data collected by the GreenFeed system

Methane emission is not included in the current breeding goals for dairy cattle mainly due to the expense and difficulty in obtaining sufficient data to generate accurate estimates of the relevant traits. While several models have been developed to predict methane emission from milk spectra using reference methane data obtained by the respiration chamber, SF6 and sniffer methods, the prediction of methane emission from milk mid-infrared (MIR) spectra using reference methane data collected by the GreenFeed system has not yet been explored. Methane emission was monitored for 151 cows using the GreenFeed system. Prediction models were developed for daily and average (for the trial period of 12 or 14 days) methane production (g/d), yield (g/kg DM intake (DMI)) and intensity (g/kg of fat- and protein-corrected milk) using partial least squares regression. The predictions were evaluated in 100 repeated validation cycles, where animals were randomly partitioned into training (80%) and testing (20%) populations for each cycle. The best performing model was observed for average methane intensity using MIR, parity and DMI with validation coefficient of determination (R²_val) and RMSE of prediction of 0.66 and 4.7 g/kg of fat- and protein-corrected milk, respectively. The accuracy of the best models for average methane production and average methane yield were poor (R²_val = 0.28 and 0.12, respectively). A lower accuracy of prediction was observed for methane intensity and production (R²_val = 0.42 and 0.17) when daily records were used while prediction for methane yield was comparable to that for average methane yield (R²_val = 0.16). Our results suggest the potential to predict methane intensity with moderate accuracy. In this case, prediction models for average methane values were generally better than for daily measures when using the GreenFeed system to obtain reference methane emission measurements.

Milk metabolome reveals variations on enteric methane emissions from dairy cows fed a specific inhibitor of the methanogenesis pathway

Metabolome profiling in biological fluids is an interesting approach for exploring markers of methane emissions in ruminants. In this study, a multiplatform metabolomics approach was used for investigating changes in milk metabolic profiles related to methanogenesis in dairy cows. For this purpose, 25 primiparous Holstein cows at similar lactation stage were fed the same diet supplemented with (treated, n = 12) or without (control, n = 13) a specific antimethanogenic additive that reduced enteric methane production by 23% with no changes in intake, milk production, and health status. The study lasted 6 wk, with sampling and measures performed in wk 5 and 6. Milk samples were analyzed using 4 complementary analytical methods, including 2 untargeted (nuclear magnetic resonance and liquid chromatography coupled to a quadrupole-time-of-flight mass spectrometer) and 2 targeted (liquid chromatography-tandem mass spectrometry and gas chromatography coupled to a flame ionization detector) approaches. After filtration, variable selection and normalization data from each analytical platform were then analyzed using multivariate orthogonal partial least square discriminant analysis. All 4 analytical methods were able to differentiate cows from treated and control groups. Overall, 38 discriminant metabolites were identified, which affected 10 metabolic pathways including methane metabolism. Some of these metabolites such as dimethylsulfoxide, dimethylsulfone, and citramalic acid, detected by nuclear magnetic resonance or liquid chromatography-mass spectrometry methods, originated from the rumen microbiota or had a microbial-host animal co-metabolism that could be associated with methanogenesis. Also, discriminant milk fatty acids detected by targeted gas chromatography were mostly of ruminal microbial origin. Other metabolites and metabolic pathways significantly affected were associated with AA metabolism. These findings provide new insight on the potential role of milk metabolites as indicators of enteric methane modifications in dairy cows.

Intramuscular Fatty Acids in Meat Could Predict Enteric Methane Production by Fattening Lambs

Methane (CH4) emissions pose a serious problem for the environmental sustainability of ruminant production. The aim of the present study was to explore the usefulness of the intramuscular fatty acid (FA) profile to estimate CH4 production of lambs fattened under intensive feeding systems. A statistical regression analysis of intramuscular FA derived from ruminal metabolism was carried out to assess the best predictive model of CH4 production (g/d) in lambs fed with different diets. CH4 was calculated with three distinct equations based on organic matter digestibility (OMD) at maintenance feeding levels. The OMD of the experimental diets was determined in an in vivo digestibility trial by means of the indicator method. Regression models were obtained by stepwise regression analysis. The three optimized models showed high adjusted coefficients of determination (R2adj = 0.74-0.93) and concordance correlation coefficients (CCC = 0.89-0.98), as well as small root mean square prediction errors (RMSPE = 0.29-0.40 g/d). The best single predictor was vaccenic acid (trans-11 C18:1), a bioactive FA that is formed in the rumen to a different extent depending on dietary composition. Based on our data and further published lamb research, we propose a novel regression model for CH4 production with excellent outcomes: CH4 (g/d) = -1.98 (±1.284)-0.87 (±0.231) × trans-11 C18:1 + 0.79 (±0.045) × BW (R2adj = 0.97; RMSPE = 0.76 g/d; CCC = 0.98). In conclusion, these results indicate that specific intramuscular FA and average BW during fattening could be useful to predict CH4 production of lambs fed high concentrate diets.

Feeding Grazing Dairy Cows With Different Energy Sources on Recovery of Human-Edible Nutrients in Milk and Environmental Impact

The use of grazing systems for milk production is widely used globally because it is a lower-cost feeding system. However, under tropical conditions, the energy content of pastures became is a limitation to improve animal performance and efficiency while reducing the environmental impact. The objective of our study was to evaluate the impact of supplying different dietary sources of energy to lactating dairy cows grazing tropical pastures on the recovery of human-edible (HE) nutrients in milk and the environmental impact. Two experiments were conducted simultaneously. In experiment 1, forty early lactating dairy cows were used in a randomized block design. In experiment 2, four late-lactating rumen-cannulated dairy cows were used in a 4 × 4 Latin Square design. All cows had free access to pasture and treatments were applied individually as a concentrate supplement. Treatments were flint corn grain-processing method either as fine ground (FGC) or steam-flaked (SFC) associated with Ca salts of palm fatty acids supplementation either not supplemented (CON) or supplemented (CSPO). We observed that feeding cows with SFC markedly reduced urinary nitrogen excretion by 43%, and improved milk nitrogen efficiency by 17% when compared with FGC. Additionally, we also observed that feeding supplemental fat improved milk nitrogen efficiency by 17% compared with cows receiving CON diets. A tendency for decreased methane (CH4) per unit of milk (−31%), CH4 per unit of milk energy output (−29%), and CH4 per unit of milk protein output (−31%) was observed when CSPO was fed compared with CON. Additionally, SFC diets increased HE recovery of indispensable amino acids by 7–9% when compared with FGC diets, whereas feeding supplemental fat improved HE recovery of indispensable amino acids by 17–19% compared with CON. Altogether, this study increased our understanding of how manipulating energy sources in the dairy cow diet under tropical grazing conditions can benefit HE nutrient recovery and reduce nutrient excretion.

Effects of 3-nitrooxypropanol and varying concentrate feed proportions in the ration on methane emission, rumen fermentation and performance of periparturient dairy cows

The climate-relevant enteric methane (CH₄) formation represents a loss of feed energy that is potentially meaningful for energetically undersupplied peripartal dairy cows. Higher concentrate feed proportions (CFP) are known to reduce CH₄ emissions in cows. The same applies to the feed additive 3-nitrooxypropanol (3-NOP), albeit through different mechanisms. It was hypothesised that the hydrogen not utilised for CH₄ formation through the inhibition by 3-NOP would be sequestered by propionate formation triggered by higher CFP so that it could thereby give rise to a synergistically reduced CH₄ emission. In a 2 × 2-factorial design, low (LC) or high (HC) CFP were either tested without supplements (CON_LC, CON_HC) or combined with 3-NOP (NOP_LC, 48.4 mg/kg dry matter (DM); NOP_HC, 51.2 mg 3-NOP/kg DM). These four rations were fed to a total of 55 Holstein cows from d 28 ante partum until d 120 post partum. DM intake (DMI) was not affected by 3-NOP but increased with CFP (CFP; p < 0.001). CH₄/DMI and CH₄/energy-corrected milk (ECM) were mitigated by 3-NOP (23% NOP_LC, 33% NOP_HC) (p < 0.001) and high CFP (12% CON, 22% 3-NOP groups) (CFP × TIME p < 0.001). Under the conditions of the present experiment, the CH₄ emissions of NOP_LC increased to the level of the CON groups from week 8 until the end of trial (3-NOP × CFP × TIME; p < 0.01). CO₂ yield decreased by 3-NOP and high CFP (3-NOP × CFP; p < 0.001). The reduced body weight loss and feed efficiency in HC groups paralleled a more positive energy balance being most obvious in NOP_HC (3-NOP × CFP; p < 0.001). ECM was lower for NOP_HC compared to CON_HC (3-NOP × CFP; p < 0.05), whereas LC groups did not differ. A decreased fat to protein ratio was observed in HC groups and, until week 6 post partum, in NOP_LC. Milk lactose and urea increased by 3-NOP (3-NOP; p < 0.05). 3-NOP and high CFP changed rumen fermentation to a more propionic-metabolic profile (3-NOP; CFP; p < 0.01) but did not affect rumen pH. In conclusion, CH₄ emission was synergistically reduced when high CFP was combined with 3-NOP while the CH₄ mitigating 3-NOP effect decreased with progressing time when the supplement was added to the high-forage ration. The nature of these interactions needs to be clarified.

Inhibition of enteric methanogenesis in dairy cows induces changes in plasma metabolome highlighting metabolic shifts and potential markers of emission

There is scarce information on whether inhibition of rumen methanogenesis induces metabolic changes on the host ruminant. Understanding these possible changes is important for the acceptance of methane-reducing practices by producers. In this study we explored the changes in plasma profiles associated with the reduction of methane emissions. Plasma samples were collected from lactating primiparous Holstein cows fed the same diet with (Treated, n = 12) or without (Control, n = 13) an anti-methanogenic feed additive for six weeks. Daily methane emissions (CH₄, g/d) were reduced by 23% in the Treated group with no changes in milk production, feed intake, body weight, and biochemical indicators of health status. Plasma metabolome analyses were performed using untargeted [nuclear magnetic resonance (NMR) and liquid chromatography-mass spectrometry (LC–MS)] and targeted (LC–MS/MS) approaches. We identified 48 discriminant metabolites. Some metabolites mainly of microbial origin such as dimethylsulfone, formic acid and metabolites containing methylated groups like stachydrine, can be related to rumen methanogenesis and can potentially be used as markers. The other discriminant metabolites are produced by the host or have a mixed microbial-host origin. These metabolites, which increased in treated cows, belong to general pathways of amino acids and energy metabolism suggesting a systemic non-negative effect on the animal.

Dietary mitigation of enteric methane emissions from ruminants: A review of plant tannin mitigation options

Methane gas from livestock production activities is a significant source of greenhouse gas (GHG) emissions which have been shown to influence climate change. New technologies offer a potential to manipulate the rumen biome through genetic selection reducing CH4 production. Methane production may also be mitigated to varying degrees by various dietary intervention strategies. Strategies to reduce GHG emissions need to be developed which increase ruminant production efficiency whereas reducing production of CH4 from cattle, sheep, and goats. Methane emissions may be efficiently mitigated by manipulation of natural ruminal microbiota with various dietary interventions and animal production efficiency improved. Although some CH4 abatement strategies have shown efficacy in vivo, more research is required to make any of these approaches pertinent to modern animal production systems. The objective of this review is to explain how anti-methanogenic compounds (e.g., plant tannins) affect ruminal microbiota, reduce CH4 emission, and the effects on host responses. Thus, this review provides information relevant to understanding the impact of tannins on methanogenesis, which may provide a cost-effective means to reduce enteric CH4 production and the influence of ruminant animals on global GHG emissions.

Infrared Spectrometry as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock Systems

High-throughput phenotyping technologies are growing in importance in livestock systems due to their ability to generate real-time, non-invasive, and accurate animal-level information. Collecting such individual-level information can generate novel traits and potentially improve animal selection and management decisions in livestock operations. One of the most relevant tools used in the dairy and beef industry to predict complex traits is infrared spectrometry, which is based on the analysis of the interaction between electromagnetic radiation and matter. The infrared electromagnetic radiation spans an enormous range of wavelengths and frequencies known as the electromagnetic spectrum. The spectrum is divided into different regions, with near- and mid-infrared regions being the main spectral regions used in livestock applications. The advantage of using infrared spectrometry includes speed, non-destructive measurement, and great potential for on-line analysis. This paper aims to review the use of mid- and near-infrared spectrometry techniques as tools to predict complex dairy and beef phenotypes, such as milk composition, feed efficiency, methane emission, fertility, energy balance, health status, and meat quality traits. Although several research studies have used these technologies to predict a wide range of phenotypes, most of them are based on Partial Least Squares (PLS) and did not considered other machine learning (ML) techniques to improve prediction quality. Therefore, we will discuss the role of analytical methods employed on spectral data to improve the predictive ability for complex traits in livestock operations. Furthermore, we will discuss different approaches to reduce data dimensionality and the impact of validation strategies on predictive quality.

Between-cow variation in milk fatty acids associated with methane production

We evaluated the between-cow (b-cow) variation and repeatability in omasal and milk fatty acids (FA) related to methane (CH4) emission. The dataset was originated from 9 studies with rumen-cannulated dairy cows conducted using either a switch-back or a Latin square design. Production of CH4 per mole of VFA (Y_CH4VFA) was calculated based on VFA stoichiometry. Experiment, diet within experiment, period within experiment, and cow within experiment were considered as random factors. Empirical models were developed between the variables of interest by univariate and bivariate mixed model regression analysis. The variation associated with diet was higher than the b-cow variation with low repeatability (< 0.25) for milk odd- and branch-chain FA (OBCFA). Similarly, for de novo synthesized milk FA, diet variation was ~ 3-fold greater than the b-cow variation; repeatability for these FA was moderate to high (0.34-0.58). Also, for both cis-9 C18:1 and cis-9 cis-12 cis-15 C18:3 diet variation was more than double the b-cow variation, but repeatability was moderate. Among the de novo milk FA, C4:0 was positively related with stoichiometric Y_CH4VFA, while for OBCFA, anteiso C15:0 and C15:0 were negatively related with it. Notably, when analyzing the relationship between omasal FA and milk FA we observed positive intercept estimates for all the OBCFA, which may indicate endogenous post-ruminal synthesis of these FA, most likely in the mammary gland. For milk iso C13:0, iso C15:0, anteiso C15:0, and C15:0 were positively influenced by omasal proportion of their respective FA and by energy balance. In contrast, the concentration of milk C17:0, iso C18:0, C18:0, cis-11 C18:1, and cis-9 cis-12 cis-15 C18:3 were positively influenced by omasal proportion of their respective FA but negatively related to calculated energy balance. Our findings demonstrate that for most milk FA examined, a larger variation is attributed to diet than b-cow differences with low to moderate repeatability. While some milk FA were positively or negatively related with Y_CH4VFA, there was a pronounced effect of calculated energy balance on these estimates. Additionally, even though OBCFA have been indicated as markers of rumen function, our results suggest that endogenous synthesis of these FA may occur, which therefore, may limit the utilization of milk FA as a proxy for CH4 predictions for cows fed the same diet.

3-Nitrooxypropanol decreases methane emissions and increases hydrogen emissions of early lactation dairy cows, with associated changes in nutrient digestibility and energy metabolism

The aim of this study was to determine the methane (CH₄) 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 CH₄ production (g/d) at 27 and 83 DIM, but decreased CH₄ production at 55 and 111 DIM by an average of 18.5%. This response in CH₄ production is most likely due to the differences observed in feed intake across the different stages of lactation because CH₄ 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 H₂ production and intensity 12-fold; with the control diet, H₂ yield did not differ between the different stages of lactation, whereas with the 3-NOP treatment H₂ 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 CH₄ emissions (while increasing H₂ emission) in early lactation Holstein-Friesian cows with positive effects on apparent total-tract digestibility of nutrients.

Mitigation of greenhouse gases in dairy cattle via genetic selection: 1. Genetic parameters of direct methane using noninvasive methods and proxies of methane

Records of methane emissions from 1,501 cows on 14 commercial farms in 4 regions of Spain were collected from May 2018 to June 2019. Methane concentrations (MeC) were measured using a nondispersive infrared methane detector installed within the feed bin of the automatic milking system during 14- to 21-d periods. Rumination time (RT; min/d) was collected using collars with a tag that registered time (minutes) spent eating and ruminating. The means of MeC and methane production (MeP) were 1,254.28 ppm and 182.49 g/d, respectively; mean RT was 473.38 min/d. Variance components for MeC, MeP, and RT were estimated with REML using pedigree and genomic information in a single-step model. Heritabilities for MeC and MeP were 0.11 and 0.12, respectively. Rumination time showed a slightly larger heritability estimate (0.17). The genetic correlation between MeP and MeC was high (>0.95), suggesting that selection on either trait would lead to a positive correlated response on the other. Negative correlations were estimated between RT and MeC (-0.24 ± 0.38) and MeP (-0.43 ± 0.35). Methane concentration and MeP had slightly positive correlations with milk yield (0.17 ± 0.39 and 0.21 ± 0.36), protein percentage (0.08 ± 0.32 and 0.30 ± 0.45), protein yield (0.22 ± 0.41 and 0.31 ± 0.35), fat percentage (0.02 ± 0.40 and 0.27 ± 0.36), and fat yield (0.27 ± 0.28 and 0.29 ± 0.28) from bivariate analyses. Rumination time had positive correlations with milk yield (0.41 ± 0.75) and protein yield (0.26 ± 0.57) and negative correlations with fat yield (-0.45 ± 0.32), protein percentage (-0.15 ± 0.38), and fat percentage (-0.40 ± 0.47). A positive approximated genetic correlation was estimated between fertility and MeC (0.10 ± 0.05) and MeP (0.18 ± 0.05), resulting in slightly higher CH₄ production when selecting for better fertility [days open estimated breeding values (EBV) are expressed with mean 100 and SD 10, inversely related to days from calving to conception; that is, greater days open EBV implies better fertility]. Positive correlations were also estimated for stature with MeC and MeP (0.30 ± 0.04 and 0.43 ± 0.04, respectively). Other type traits (chest width, udder depth, angularity, and capacity) were positively correlated with methane traits, possibly because of higher milk yield and higher feed intake from these animals. Rumination time showed positive EBV correlations with production traits and type traits, and negative correlations with somatic cell count and body condition score. Based on the genetic correlations and heritabilities estimated in this study, methane is measurable and heritable, and estimates of genetic correlations suggest no strong opposition to current breeding objectives in Spanish Holsteins.

Dose-response effect of 3-nitrooxypropanol on enteric methane emissions in dairy cows

This experiment was designed to test the effect of inclusion rate of 3-nitrooxypropanol (3-NOP), a methane inhibitor, on enteric methane emissions in dairy cows. The study was conducted with 49 multiparous Holstein cows in a randomized complete block design in 2 phases; phase 1 was with 28 cows, and phase 2 with 21 cows. Cows were fed a basal total mixed ration ad libitum and were blocked based on days in milk, milk yield, and enteric methane emissions during a 14-d covariate period. Treatments were control (no 3-NOP) and 40, 60, 80, 100, 150, and 200 mg of 3-NOP/kg of feed dry matter. Following a 14-d adaptation period, enteric gaseous emissions (methane, carbon dioxide, and hydrogen) were measured using the GreenFeed system (C-Lock Inc., Rapid City, SD) over a 3-d period. Compared with the control, inclusion rate of 3-NOP quadratically decreased daily enteric methane emissions from 22 to 40%. Maximum mitigation effect was achieved with the 3 highest 3-NOP doses (with no statistical difference among 100, 150, and 200 mg/kg). The decrease in methane emission yield and emission intensity ranged from 16 to 36% and from 25 to 45%, respectively. Emissions of hydrogen quadratically increased 6- to 10-fold, compared with the control; the maximum increase was with 150 mg/kg 3-NOP. Treatment did not affect daily emissions of carbon dioxide, but a linear increase in carbon dioxide emission yield was observed with increasing 3-NOP doses. Dry matter intake and milk yield of the cows was not affected by 3-NOP. Milk fat concentration and yield were increased by 3-NOP due to increased concentration of de novo synthetized short-chain fatty acids in milk. Inclusion of 3-NOP also tended to increase milk urea nitrogen but had no other effects on milk components. In this short-term experiment, 3-NOP decreased enteric methane emissions without affecting dry matter intake or milk yield and increased milk fat in dairy cows. Maximum mitigation effect was achieved at 100 to 200 mg/kg of feed dry matter.

Impact of inbreeding on milk fatty acids of a Brazilian Holstein cattle

Context Reproductive technologies may either contribute to the increase of genetic gains or inbreeding levels in dairy cattle breeding programs and herds. In general, studies have evaluated the impacts of inbreeding on traditional traits, such as production and reproduction. However, studies on novel traits, such as milk fatty acids profile, are scarce in the literature. Aim We aimed to evaluate the impact of inbreeding levels on milk fatty acids profile measured in a Brazilian Holstein cattle population. Methods Monthly records of the percentages (%) of palmitic, stearic, oleic, total saturated, unsaturated, monounsaturated and polyunsaturated fatty acids in milk were collected from 2047 Holstein cows between May and December 2012. The pedigree file contained 7963 animals over seven generations. The inbreeding trend was evaluated by linear regression of inbreeding coefficients on generations. The inbreeding impacts on breeding and phenotypic values were evaluated by linear regression of breeding values and phenotypic values on generations respectively. Breeding values were obtained by a Bayesian approach based on an animal model that included the systematic effect of contemporary group, cubic effect of days in milk as a covariate, and the random direct additive genetic and animal permanent environmental effects. Key results The average inbreeding coefficient was 0.28% for all animals, and 1.39% for inbred animals. Inbreeding tended to increase 0.24% per generation (P-value &lt;0.0001). The regression coefficients of phenotypic values on inbreeding were not significant for saturated, unsaturated, monounsaturated, palmitic, stearic and oleic fatty acids (P-values &gt;0.18, 0.10, 0.16, 0.26, 0.51 and 0.09 respectively); whereas for polyunsaturated fatty acids, they were significant (P-value &lt;0.04), with an increase of –0.000978% on phenotypic values for each 1% increase in inbreeding. The regression coefficients of breeding values on inbreeding were not significant for unsaturated, monounsaturated, polyunsaturated, stearic and oleic fatty acids (P-values &gt;0.33, 0.78, 0.48, 0.32 and 0.07 respectively). However, they were significant for saturated and palmitic fatty acids (P-values &lt;0.03 and 0.0001 respectively), presenting an increase of 0.000689% and 0.000283% respectively on breeding values for each 1% increase in inbreeding. Conclusions There was a significant increase in inbreeding coefficients over the studied generations; however, the impacts on both breeding and phenotypic values were small, when significant. Implications Our study may contribute to the understanding of how inbreeding levels may affect the fatty acids profile in a Brazilian Holstein cattle population, as well as encourage future research on this subject.

Enteric Methane Emissions of Dairy Cows Predicted from Fatty Acid Profiles of Milk, Cream, Cheese, Ricotta, Whey, and Scotta

Enteric methane emissions (EME) of ruminants contribute to global climate change, but any attempt to reduce it will need an easy, inexpensive, and accurate method of quantification. We used a promising indirect method for estimating EMEs of lactating dairy cows based on the analysis of the fatty acid (FA) profile of their milk. The aim of this preliminary study was to assess milk from four single samplings (morning whole, evening whole, evening partially skimmed, and vat milks) as alternatives to reference whole milk samples from two milkings. Three fresh products (cream, cheese, and ricotta), two by-products (whey and scotta), and two long-ripened cheeses (6 and 12 months) were also assessed as alternative sources of information to reference milk. The 11 alternative matrices were obtained from seven experimental cheese- and ricotta-making sessions carried out every two weeks following the artisanal Malga cheese-making procedure using milk from 148 dairy cows kept on summer highland pastures. A total of 131 samples of milk, dairy products, and by-products were analyzed to determine the milk composition and to obtain detailed FA profiles using bi-dimensional gas-chromatography. Two equations taken from a published meta-analysis of methane emissions measured in the respiration chambers of cows on 30 different diets were applied to the proportions of butyric, iso-palmitic, iso-oleic, vaccenic, oleic, and linoleic acids out of total FAs to predict methane yield per kg of dry matter ingested and methane intensity per kg of fat and protein corrected milk produced by the cows. Methane yield and intensity could be predicted from single milk samples with good accuracy (trueness and precision) with respect to those predicted from reference milk. The fresh products (cream, cheese and ricotta) generally showed good levels of trueness but low precision for predicting both EME traits, which means that a greater number of samples needs to be analyzed. Among by-products, whey could be a viable alternative source of information for predicting both EME traits, whereas scotta overestimated both traits and showed low precision (due also to its very low fat content). Long-ripened cheeses were found to be less valuable sources of information, although six-month cheese could, with specific correction factors, be acceptable sources of information for predicting the methane yield of lactating cows. These preliminary results need to be confirmed by further study on different dairy systems and cheese-making technologies but offer new insight into a possible easy method for monitoring the EME at the field level along the dairy chain.

Genome-Wide Association Studies for Methane Production in Dairy Cattle

Genomic selection has been proposed for the mitigation of methane (CH₄) emissions by cattle because there is considerable variability in CH₄ emissions between individuals fed on the same diet. The genome-wide association study (GWAS) represents an important tool for the detection of candidate genes, haplotypes or single nucleotide polymorphisms (SNP) markers related to characteristics of economic interest. The present study included information for 280 cows in three dairy production systems in Mexico: 1) Dual Purpose (n = 100), 2) Specialized Tropical Dairy (n = 76), 3) Familiar Production System (n = 104). Concentrations of CH₄ in a breath of individual cows at the time of milking (MEIm) were estimated through a system of infrared sensors. After quality control analyses, 21,958 SNPs were included. Associations of markers were made using a linear regression model, corrected with principal component analyses. In total, 46 SNPs were identified as significant for CH₄ production. Several SNPs associated with CH₄ production were found at regions previously described for quantitative trait loci of composition characteristics of meat, milk fatty acids and characteristics related to feed intake. It was concluded that the SNPs identified could be used in genomic selection programs in developing countries and combined with other datasets for global selection.

Development of an equation to estimate the enteric methane emissions from Holstein dairy cows in Canada

The aim of this study was to use dietary factors, including the type of fats, and animal characteristics, to predict enteric methane (CH4) emissions from dairy cows under Canadian conditions. For this purpose, 193 individual observations from six different trials assessing the impact of dietary modification on enteric CH4 production were analyzed. Animal [milk yield (MY), milk fat content, milk protein content, days in milk, body weight (BW), and dry matter intake (DMI)] and dietary variables [organic matter, crude protein, neutral detergent fiber (NDF), acid detergent fiber (ADF), starch, ether extract (EE), rumen-inert fat, and unprotected fat (EE – rumen-inert fat)] were tested. A 5-fold cross validation was used to obtain the following equation: CH4 (g d−1) = −1260.4 + 1.9 × MY (kg d−1) + 62.8 × milk fat (%) –18.4 × milk protein (%) + 11.0 × DMI (kg d−1) + 0.3 × BW (kg) + 58.3 × NDF (% of DM) − 0.8 × NDF2 (% of DM) + 1.9 × starch (% of DM) − 2.5 × EE – rumen-inert fat (% of DM). The mean estimate from the proposed equation (474 g CH4 cow−1 d−1; r = 0.83, RMSE = 40.0) was close to the observed mean emission (476 g CH4 cow−1 d−1). The proposed model has a higher precision to predict CH4 emission from cows fed typical Canadian diets than other models, and it can be used to evaluate CH4 mitigation strategies.

Volatile Fatty Acids in Ruminal Fluid Can Be Used to Predict Methane Yield of Dairy Cows

The dry matter intake (DMI) of forage-fed cattle can be used to predict their methane emissions. However, many cattle are fed concentrate-rich diets that decrease their methane yield. A range of equations predicting methane yield exist, but most use information that is generally unavailable when animals are fed in groups or grazing. The aim of this research was to develop equations based on proportions of ruminal volatile-fatty-acids to predict methane yield of dairy cows fed forage-dominant as well as concentrate-rich diets. Data were collated from seven experiments with a total of 24 treatments, from 215 cows. Forage in the diets ranged from 440 to 1000 g/kg. Methane was measured either by open-circuit respiration chambers or a sulfur hexafluoride (SF6) technique. In all experiments, ruminal fluid was collected via the mouth approximately four hours after the start of feeding. Seven prediction equations were tested. Methane yield (MY) was equally best predicted by the following equations: MY = 4.08 × (acetate/propionate) + 7.05; MY = 3.28 × (acetate + butyrate)/propionate + 7.6; MY = 316/propionate + 4.4. These equations were validated against independent published data from both dairy and beef cattle consuming a wide range of diets. A concordance of 0.62 suggests these equations may be applicable for predicting methane yield from all cattle and not just dairy cows, with root mean-square error of prediction of 3.0 g CH4/kg dry matter intake.

Effects of 3-nitrooxypropanol on rumen fermentation, lactational performance, and resumption of ovarian cyclicity in dairy cows

This study examined the effect of 3-nitrooxypropanol (3-NOP), a substance under investigation, on enteric methane (CH₄) emission, rumen fermentation, lactational performance, sensory properties of milk, and the resumption of ovarian cyclicity in early-lactation dairy cows. Fifty-six multi- and primiparous Holstein cows, including 8 that were rumen cannulated, were used in a 15-wk randomized complete block design experiment. Cows were blocked based on parity and previous lactation milk yield (MY) or predicted MY, and within each block were randomly assigned to one of 2 treatments: (1) control (CON), administered no 3-NOP, or (2) 3-NOP applied at 60 mg/kg of feed dry matter (3-NOP). Enteric CH₄ emission was measured during experimental wk 2, 6, 9, and 15, using the GreenFeed system. Dry matter intake (DMI) and MY data were collected daily throughout the experiment, and milk composition samples were collected 7 times during the experiment. Milk samples were collected from 14 to 60 (±2) d after calving, 3 d per week, and assayed for progesterone concentration to determine resumption of ovarian activity. Compared with CON, 3-NOP decreased daily CH₄ emission by 26%, CH₄ yield (CH₄ per kg of DMI) by 21%, and CH₄ emission intensity [CH₄ per kg of MY or energy-corrected milk (ECM)] by 25%. Enteric emission of carbon dioxide was decreased by 5%, and hydrogen emission was increased 48-fold by 3-NOP. Inclusion of 3-NOP decreased concentration of total volatile fatty acids (by 9.3%) and acetate but increased butyrate molar proportion, ethanol, and formate concentrations in ruminal fluid. Dry matter intake was lower for 3-NOP compared with CON, but DMI expressed as a percentage of body weight was not different between treatments. Treatment had no effect on milk and ECM, body weight change, or body condition score. Milk composition and milk fat and protein yields were not affected by treatment, except that concentrations of short-chain fatty acids in milk were increased by 3-NOP. Nutrient digestibility and blood metabolites and hormones were not affected by 3-NOP, except that insulin was decreased by 3-NOP. There was no effect of 3-NOP on postpartum resumption of ovarian activity, including days to first and second luteal phases, length of first and second luteal phases, and interval from first to second luteal phase. Sensory properties of milk from cows fed 3-NOP and cheese made from that milk were not affected by treatment. In this experiment, 3-NOP decreased daily enteric CH₄ emission, emission yield, and emission intensity, improved feed efficiency, and did not affect lactational performance or onset of ovarian activity in early-lactation dairy cows.

Differences in methane production, yield and intensity and its effects on metabolism of dairy heifers

The effects of divergent phenotypic classification in crossbreed Holstein × Gyr dairy heifers for methane emissions in relation to performance, digestibility, energy and nitrogen partition, blood metabolites and temperature of body surface were evaluated. Thirty-five heifers were classified as high and low emission for CH₄ production (g/day), yield (g/kg dry matter intake) and intensity (g/kg average daily gain). Digestibility was evaluated by total collection of feces and urine. Gas exchanges were obtained in open-circuit respiratory chambers. A completely randomized design was used and divergent groups were compared by Fisher's test. No differences were found in intake traits between groups of CH₄ production and intensity. The low yield group had higher intake. For digestibility and temperature at different body sites were no differences between variables. High production group had higher energy losses as methane and heat production. Low intensity group had higher digestible energy, energy balance and ratio between metabolizable and digestible energy. Urinary nitrogen was 14.3% lower for low production group. There was a difference between methane yield divergent groups for nitrogen intake, digestible and retained. Energy and nitrogen partitioning traits are correlated to the animals divergent for methane production and yield. The low production group presented lower blood insulin concentration. It was not possible to identify divergent animals for CH₄ emission using the infrared thermography technique.

Short communication: Genetic correlations between methane and milk production, conformation, and functional traits

Livestock produce CH₄, contributing to the global warming effect. One of the currently investigated solutions to reduce CH₄ production is selective breeding. The goal of this study was to estimate the genetic correlations between CH₄ and milk production, conformation, and functional traits used in the selection index for Polish-Holstein cows. In total, 34,429 daily CH₄ production observations collected from 483 cows were available, out of which 281 cows were genotyped. The CH₄ was measured using a so-called sniffer device installed in an automated milking system. Breeding values for CH₄ were estimated with the use of single-step genomic BLUP, and breeding values for remaining traits were obtained from the Polish national genomic evaluation. Genetic correlations between CH₄ production and remaining traits were estimated using bivariate analyses. The estimated genetic correlations were in general low. The highest values were estimated for fat yield (0.21), milk yield (0.15), chest width (0.15), size (0.15), dairy strength (0.11), and somatic cell count (0.11). These estimates, as opposed to estimates for the remaining traits, were significantly different from zero.

Methane prediction based on individual or groups of milk fatty acids for dairy cows fed rations with or without linseed

Milk fatty acids (MFA) are a proxy for the prediction of CH₄ emission from cows, and prediction differs with diet. Our objectives were (1) to compare the effect of diets on the relation between MFA profile and measured CH₄ production, (2) to predict CH₄ production based on 6 data sets differing in the number and type of MFA, and (3) to test whether additional inclusion of energy-corrected milk (ECM) yield or dry matter intake (DMI) as explanatory variables improves predictions. Twenty dairy cows were used. Four diets were used based on corn silage (CS) or grass silage (GS) without (L0) or with linseed (LS) supplementation. Ten cows were fed CS-L0 and CS-LS and the other 10 cows were fed GS-L0 and GS-LS in random order. In feeding wk 5 of each diet, CH₄ production (L/d) was measured in respiration chambers for 48 h and milk was analyzed for MFA concentrations by gas chromatography. Specific CH₄ prediction equations were obtained for L0-, LS-, GS-, and CS-based diets and for all 4 diets collectively and validated by an internal cross-validation. Models were developed containing either 43 identified MFA or a reduced set of 7 groups of biochemically related MFA plus C16:0 and C18:0. The CS and LS diets reduced CH₄ production compared with GS and L0 diets, respectively. Methane yield (L/kg of DMI) reduction by LS was higher with CS than GS diets. The concentrations of C18:1 trans and n-3 MFA differed among GS and CS diets. The LS diets resulted in a higher proportion of unsaturated MFA at the expense of saturated MFA. When using the data set of 43 individual MFA to predict CH₄ production (L/d), the cross-validation coefficient of determination (R²_CV) ranged from 0.47 to 0.92. When using groups of MFA variables, the R²_CV ranged from 0.31 to 0.84. The fit parameters of the latter models were improved by inclusion of ECM or DMI, but not when added to the data set of 43 MFA for all diets pooled. Models based on GS diets always had a lower prediction potential (R²_CV = 0.31 to 0.71) compared with data from CS diets (R²_CV = 0.56 to 0.92). Models based on LS diets produced lower prediction with data sets with reduced MFA variables (R²_CV = 0.62 to 0.68) compared with L0 diets (R²_CV = 0.67 to 0.80). The MFA C18:1 cis-9 and C24:0 and the monounsaturated FA occurred most often in models. In conclusion, models with a reduced number of MFA variables and ECM or DMI are suitable for CH₄ prediction, and CH₄ prediction equations based on diets containing linseed resulted in lower prediction accuracy.

Effects of starch-rich or lipid-supplemented diets that induce milk fat depression on rumen biohydrogenation of fatty acids and methanogenesis in lactating dairy cows

Optimizing milk production efficiency implies diets allowing low methane (CH4) emissions and high dairy performance. We hypothesize that nature of energy (starch v. lipids) and lipid supplement types (monounsaturated fatty acid (MUFA) v. polyunsaturated fatty acid (PUFA) mitigate CH4 emissions and can induce low milk fat content via different pathways. The main objective of this experiment was to study the effects of starch-rich or lipid-supplemented diets that induce milk fat depression (MFD) on rumen biohydrogenation (RBH) of unsaturated fatty acids (FA) and enteric CH4 emissions in dairy cows. Four multiparous lactating Holstein cows (days in milk=61±11 days) were used in a 4×4 Latin square design with four periods of 28 days. Four dietary treatments, three of which are likely to induce MFD, were based (dry matter basis) on 56% maize silage, 4% hay and 40% concentrates rich in: (1) saturated fatty acid (SFA) from Ca salts of palm oil (PALM); (2) starch from maize grain and wheat (MFD-Starch); (3) MUFA (cis-9 C18:1) from extruded rapeseeds (MFD-RS); and (4) PUFA (C18:2n-6) from extruded sunflower seeds (MFD-SF). Intake and milk production were measured daily. Milk composition and FA profile, CH4 emissions and total-tract digestibility were measured simultaneously when animals were in open-circuit respiration chambers. Fermentation parameters were analysed from rumen fluid samples taken before feeding. Dry matter intake, milk production, fat and protein contents, and CH4 emissions were similar among the four diets. We observed a higher milk SFA concentration with PALM and MFD-Starch, and lower milk MUFA and trans-10 C18:1 concentrations in comparison to MFD-RS and MFD-SF diets, while trans-11 C18:1 remained unchanged among diets. Milk total trans FA concentration was greater for MFD-SF than for PALM and MFD-Starch, with the value for MFD-RS being intermediate. Milk C18:3n-3 content was higher for MFD-RS than MFD-SF. The MFD seems more severe with MFD-SF and MFD-RS than PALM and MFD-Starch diets, because of a decrease in milk SFA concentration and a stronger shift from trans-11 C18:1 to trans-10 C18:1 in milk. The MFD-SF diet increased milk trans FA (+60%), trans-10 C18:1 (+31%), trans-10,cis-12 CLA (+27%) and PUFA (+36%) concentrations more than MFD-RS, which explains the numerically lowest milk fat yield and indicates that RBH pathways of PUFA differ between these two diets. Maize silage-based diets rich in starch or different unsaturated FA induced MFD with changes in milk FA profiles, but did not modify CH4 emissions.

Genome-wide association identifies methane production level relation to genetic control of digestive tract development in dairy cows

The global temperatures are increasing. This increase is partly due to methane (CH4) production from ruminants, including dairy cattle. Recent studies on dairy cattle have revealed the existence of a heritable variation in CH4 production that enables mitigation strategies based on selective breeding. We have exploited the available heritable variation to study the genetic architecture of CH4 production and detected genomic regions affecting CH4 production. Although the detected regions explained only a small proportion of the heritable variance, we showed that potential QTL regions affecting CH4 production were located within QTLs related to feed efficiency, milk-related traits, body size and health status. Five candidate genes were found: CYP51A1 on BTA 4, PPP1R16B on BTA 13, and NTHL1, TSC2, and PKD1 on BTA 25. These candidate genes were involved in a number of metabolic processes that are possibly related to CH4 production. One of the most promising candidate genes (PKD1) was related to the development of the digestive tract. The results indicate that CH4 production is a highly polygenic trait.

Short communication: The effect of linseed oil and DGAT1 K232A polymorphism on the methane emission prediction potential of milk fatty acids

Several in vivo CH₄ measurement techniques have been developed but are not suitable for precise and accurate large-scale measurements; hence, proxies for CH₄ 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 CH₄ 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 CH₄ production was measured in climate respiration chambers and the MFA profile was analyzed using gas chromatography. Observed CH₄ emissions were compared with CH₄ emissions predicted by previously developed MFA-based CH₄ 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 CH₄ 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 CH₄ prediction equations can neither accurately nor precisely predict CH₄ emissions of dairy cows managed under strategies differing from those under which the original prediction equations were developed.

Consequences of genetic selection for environmental impact traits on economically important traits in dairy cows

Methane (CH4) emission is an important environmental trait in dairy cows. Breeding aiming to mitigate CH4 emissions require the estimation of genetic correlations with other economically important traits and the prediction of their selection response. In this study, test-day CH4 emissions were predicted from milk mid-infrared spectra of Holstein cows. Predicted CH4 emissions (PME) and log-transformed CH4 intensity (LMI) computed as the natural logarithm of PME divided by milk yield (MY). Genetic correlations of PME and LMI with traits used currently were approximated from correlations between estimated breeding values of sires. Values were for PME with MY 0.06, fat yield (FY) 0.09, protein yield (PY) 0.13, fertility 0.17; body condition score (BCS) –0.02; udder health (UDH) 0.22; and longevity 0.22. As expected by its definition, values were negative for LMI with production traits (MY –0.61; FY –0.15 and PY –0.40) and positive with fertility (0.36); BCS (0.20); UDH (0.08) and longevity (0.06). The genetic correlations of 33 type traits with PME ranged from –0.12 to 0.25 and for LMI ranged from –0.22 to 0.18. Without selecting PME and LMI (status quo) the relative genetic change through correlated responses of other traits were in PME by 2% and in LMI by –15%, but only due to the correlated response to MY. Results showed for PME that direct selection of this environmental trait would reduce milk carbon foot print but would also affect negatively fertility. Therefore, more profound changes in current indexes will be required than simply adding environmental traits as these traits also affect the expected progress of other traits.

Critical analysis of excessive utilization of crude protein in ruminants ration: impact on environmental ecosystem and opportunities of supplementation of limiting amino acids-a review

Protein quality plays a key role than quantity in growth, production, and reproduction of ruminants. Application of high concentration of dietary crude protein (CP) did not balance the proportion of these limiting amino acids (AA) at duodenal digesta of high producing dairy cow. Thus, dietary supplementation of rumen-protected AA is recommended to sustain the physiological, productive, and reproductive performance of ruminants. Poor metabolism of high CP diets in rumen excretes excessive nitrogen (N) through urine and feces in the environment. This excretion is usually in the form of nitrous oxide, nitric oxide, nitrate, and ammonia. In addition to producing gases like methane, hydrogen carbon dioxide pollutes and has a potentially negative impact on air, soil, and water quality. Data specify that supplementation of top-limiting AA methionine and lysine (Met + Lys) in ruminants' ration is one of the best approaches to enhance the utilization of feed protein and alleviate negative biohazards of CP in ruminants' ration. In conclusion, many in vivo and in vitro studies were reviewed and reported that low dietary CP with supplemental rumen-protected AA (Met + Lys) showed a good ability to reduce N losses or NH₃. Also, it helps in declining gases emission and decreasing soil or water contamination without negative impacts on animal performance. Finally, further studies are needed on genetic and molecular basis to explain the impact of Met + Lys supplementation on co-occurrence patterns of microbiome of rumen which shine new light on bacteria, methanogen, and protozoal interaction in ruminants.

The relationship between milk metabolome and methane emission of Holstein Friesian dairy cows: Metabolic interpretation and prediction potential

This study aimed to quantify the relationship between CH₄ 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, CH₄ production was 359 ± 51.1 g/d, CH₄ yield was 22.6 ± 2.31 g/kg of DMI, and CH₄ 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 CH₄ 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 CH₄ 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 CH₄ prediction potential of both volatile metabolites alone and nonvolatile metabolites alone was low, regardless of the unit of CH₄ 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 CH₄ production and CH₄ yield. For CH₄ 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 CH₄ production of dairy cows, but that it is not worthwhile to determine the volatile and nonvolatile metabolites in milk to estimate CH₄ emission of dairy cows. We conclude that MFA have moderate potential to predict CH₄ emission of dairy cattle fed forage-based diets, and that the models can aid in the effort to understand and mitigate CH₄ emissions of dairy cows.