Methane emissions of stored manure from dairy cows fed conventional or brown midrib corn silage

The objective of this study was to examine the effects of feeding conventional corn silage (CCS) or brown midrib corn silage (BMCS) to dairy cows on CH₄ emissions from stored manure. Eight lactating cows were fed (ad libitum) a total mixed ration (forage:concentrate ratio 65:35; dry matter basis) containing 59% (dry matter basis) of either CCS or BMCS. Feces and urine were collected from each cow and mixed with residual sludge obtained from a manure storage structure. Manure was incubated for 17 wk at 20°C under anaerobic conditions (O₂-free N₂) in 500-mL glass bottles. Methane emissions and changes in chemical composition of the manure were monitored during the incubation period. The total amount of feces and urine excreted was higher for cows fed BMCS than for cows fed CCS [8.6 vs. 6.5 kg/d of volatile solids (VS)]. Manure from cows fed BMCS emitted more CH₄ than manure from cows fed CCS (173 vs. 146 L/kg of VS) throughout the incubation period. Similarly, VS and neutral detergent fiber losses throughout incubation were higher for manure from cows fed BMCS versus cows fed CCS (37.6 vs. 30.6% and 46.2 vs. 31.2%, respectively). Manure NH₃ concentration (79% of total manure N) was not affected by corn silage cultivar. Results of this study show that using a more digestible corn silage cultivar (BMCS vs. CCS) may increase the contribution of manure to CH₄ emissions, and may offset gain achieved by reducing enteric CH₄ emissions.     

Methane emissions of manure from dairy cows fed red clover- or corn silage-based diets supplemented with linseed oil

The objective of this study was to investigate the effects of forage source (red clover silage: RCS vs. corn silage: CS) and diet supplementation with linseed oil (LO) on CH₄ emissions of manure from dairy cows. For this purpose, 12 lactating cows were used in a 2 × 2 factorial arrangement of treatments. Cows were fed (ad libitum) RCS- or CS-based diets (forage:concentrate ratio 60:40; dry matter basis) without or with LO addition (4% dry matter). Feces and urine were collected from each cow and mixed with residual sludge obtained from a manure storage structure. Manure was incubated for 17 wk at 20°C under anaerobic conditions (O₂-free N₂) in 500-mL glass bottles. Methane emissions and changes in chemical composition of the manure were monitored during the entire incubation period. The total amount of feces and urine excreted by cows was not affected by dietary treatments and averaged 6.6 kg/d of volatile solids (VS). Compared with manure from cows fed RCS-based diets, maximum CH₄ production potential of manure from cows fed CS-based diets was 54% higher (182 vs. 118 L/kg of VS) throughout the incubation period. Maximum CH₄ production potential from manure also increased (by 17%) when cows were fed LO-supplemented diets compared with those fed nonsupplemented diets. Similar to maximum CH₄ production potential, VS degraded during incubation (i.e., VS loss) was higher from manure from cows fed CS-based diets versus cows fed RCS-based diets (30.6 vs. 22.5%), and increased (+3 percentage units, on average) with the addition of LO to the diets. Ammonia concentration in manure was higher when cows were fed CS-based diets compared with RCS-based diets, and declined with LO supplementation to CS and RCS diets. It is concluded that both dietary forage source and fat supplementation affect maximum CH₄ production potential from manure and this should be taken into account when such dietary options are recommended to mitigate enteric CH₄ emissions from dairy cows.     

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.     

Enteric methane emission from Jersey cows during the spring transition from indoor feeding to grazing

Organic dairy cows in Denmark are often kept indoors during the winter and outside at least part time in the summer. Consequently, their diet changes by the season. We hypothesized that grazing might affect enteric CH₄ emissions due to changes in the nutrition, maintenance, and activity of the cows, and they might differentially respond to these factors. This study assessed the repeatability of enteric CH₄ emission measurements for Jersey cattle in a commercial organic dairy herd in Denmark. It also evaluated the effects of a gradual transition from indoor winter feeding to outdoor spring grazing. Further, it assessed the individual-level correlations between measurements during the consecutive feeding periods (phenotype × environment, P × E) as neither pedigrees nor genotypes were available to estimate a genotype by environment effect. Ninety-six mixed-parity lactating Jersey cows were monitored for 30 d before grazing and for 24 d while grazing. The cows spent 8 to 11 h grazing each day and had free access to an in-barn automatic milking system (AMS). For each visit to the AMS, milk yield was recorded and logged along with date and time. Monitoring equipment installed in the AMS feed bins continuously measured enteric CH₄ and CO₂ concentrations (ppm) using a noninvasive “sniffer” method. Raw enteric CH₄ and CO₂ concentrations and their ratio (CH₄:CO₂) were derived from average concentrations measured during milking and per day for each cow. We used mixed models equations to estimate variance components and adjust for the fixed and random effects influencing the analyzed gas concentrations. Univariate models were used to precorrect the gas measurements for diurnal variation and to estimate the direct effect of grazing on the analyzed concentrations. A bivariate model was used to assess the correlation between the 2 periods (in-barn vs. grazing) for each gas concentration. Grazing had a weak P × E interaction for daily average CH₄ and CO₂ gas concentrations. Bivariate repeatability estimates for average CH₄ and CO₂ concentrations and CH₄:CO₂ were 0.77 to 0.78, 0.73 to 0.80, and 0.26, respectively. Repeatability for CH₄:CO₂ was low (0.26) but indicated some between-animal variation. In conclusion, grazing does not create significant shifts compared with indoor feeding in how animals rank for average CH₄ and CO₂ concentrations and CH₄:CO₂. We found no evidence that separate evaluation is needed to quantify enteric CH₄ and CO₂ emissions from Jersey cows during in-barn and grazing periods.     

Comparison of the sulfur hexafluoride tracer and respiration chamber techniques for estimating methane emissions and correction for rectum methane output from dairy cows

The objectives of the present study were to compare the sulfur hexafluoride (SF₆) and respiration chamber techniques for measuring methane (CH₄) emissions from dairy cows and to determine the proportion of CH₄ that is released through the rectum. Data used were derived from 20 early lactation dairy cows in a 2 × 2 factorial design study for 4 periods with 6 wk/period. The 4 treatment diets consisted of grass silage and 2 levels of concentrate (30 and 60% dry matter basis), with or without yeast supplement. At the end of each period, CH₄ emissions were measured simultaneously using the SF₆ and respiration chamber techniques when cows were housed in chambers. The SF₆ technique was also used when cows were housed in digestibility units (barn location) before and after respiratory chamber measurements (chamber location). The simultaneous measurements in chamber location revealed that CH₄ emission estimates by the SF₆ technique were similar to those by the respiration chamber technique in the first 3 periods, although the SF₆ estimates were significantly higher in period 4. The regression of all data from the 4 periods demonstrated a linear relationship between the SF₆ and respiration chamber measurements for total CH₄ emissions (g/d, R² = 0.69) and for CH₄ emissions per unit of milk yield (g/kg, R² = 0.88), and a quadratic relationship for CH₄ emissions per unit of dry matter intake (g/kg, R² = 0.64). The CH₄ emissions from the rectum were calculated as the difference between CH₄ estimates from the SF₆ technique when cows were housed in respiratory chambers and barn locations, which was 3% of the total CH₄ emissions from the mouth, nostrils, and rectum. The SF₆ estimates in the chamber location accounted for all sources of emissions, whereas those in the barn location, like that in grazing conditions, did not include CH₄ emission from the rectum. Therefore, the SF₆ measurements for grazing cattle should be adjusted for CH₄ emissions from the rectum (3% of total). We conclude that the SF₆ technique is reasonably accurate for estimating CH₄ emissions.     

Effect of concentrate level on enteric methane emissions,production performance,and rumen fermentation of Jersey cows grazing kikuyu-dominant pasture during summer

The effect of concentrate feeding level on enteric CH₄ emissions from cows grazing medium quality summer pasture is yet to be investigated. Sixty multiparous Jersey cows (9 rumen-cannulated) were used in a randomized complete block design study (with the cannulated cows in a 3 × 3 Latin square design) to investigate the effect of concentrate feeding level (0, 4, and 8 kg/cow per day; as-fed basis) on enteric CH₄ emissions, production performance, and rumen fermentation of dairy cows grazing summer pasture (17 cows plus 3 cannulated cows per treatment). Enteric CH₄ emissions were measured from 11 cows per treatment group during one 7-d measurement period using the sulfur hexafluoride tracer gas technique. Pasture dry matter intake (DMI) was determined parallel with the CH₄ measurement period using TiO₂ as an external marker, and milk yield, milk composition, cow condition, and pasture pre- and postgrazing measurements were also recorded. Daily total DMI (11.2 to 15.6 kg/cow), milk yield (9.1 to 18.2 kg/cow), energy-corrected milk (ECM; 11.2 to 21.6 kg/cow), and milk lactose content (44.1 to 46.7 g/kg) increased linearly, whereas pasture DMI (11.2 to 8.4 kg/cow) decreased linearly with increasing concentrate feeding level. Daily CH₄ production (323 to 378 g/d) increased linearly due to the increase in total DMI, whereas CH₄ yield (29.1 to 25.1 g/kg of DMI) and CH₄ intensity (35.5 to 21.1 g/kg of milk yield; and 28.8 to 17.6 g/kg of ECM) decreased linearly with increasing concentrate feeding level. Diurnal ruminal pH (6.45 to 6.32) and in sacco DM and neutral detergent fiber disappearance decreased linearly. Acetic and propionic acid were unaffected by treatment, whereas butyric acid (5.21 to 6.14 mM) increased linearly and quadratically with increasing concentrate feeding level. It was concluded that a high concentrate feeding level not only increases animal efficiency but is moreover a viable CH₄ mitigation option for dairy cows grazing kikuyu-dominant pasture in late summer when pasture is inherently fibrous.     

Ammonia emissions from dairy production in Wisconsin

Ammonia gas is the only significant basic gas that neutralizes atmospheric acid gases produced from combustion of fossil fuels. This reaction produces an aerosol that is a component of atmospheric haze, is implicated in nitrogen (N) deposition, and may be a potential human health hazard. Because of the potential impact of NH₃ emissions, environmentally and economically, the objective of this study was to obtain representative and accurate NH₃ emissions data from large dairy farms (>800 cows) in Wisconsin. Ammonia concentrations and climatic measurements were made on 3 dairy farms during winter, summer, and autumn to calculate emissions using an inverse-dispersion analysis technique. These study farms were confinement systems utilizing freestall housing with nearby sand separators and lagoons for waste management. Emissions were calculated from the whole farm including the barns and any waste management components (lagoons and sand separators), and from these components alone when possible. During winter, the lagoons’ NH₃ emissions were very low and not measurable. During autumn and summer, whole-farm emissions were significantly larger than during winter, with about two-thirds of the total emissions originating from the waste management systems. The mean whole-farm NH₃ emissions in winter, autumn, and summer were 1.5, 7.5, and 13.7% of feed N inputs emitted as NH₃-N, respectively. Average annual emission comparisons on a unit basis between the 3 farms were similar at 7.0, 7.5, and 8.4% of input feed N emitted as NH₃-N, with an annual average for all 3 farms of 7.6 ± 1.5%. These winter, summer, autumn, and average annual NH₃ emissions are considerably smaller than currently used estimates for dairy farms, and smaller than emissions from other types of animal-feeding operations.     

Technical note: Evaluation of interval between measurements and calculation method for the quantification of enteric methane emissions measured by respiration chamber

Respiration chambers share one analyzer working in parallel, and methane (CH₄) concentrations have to be measured at certain intervals. The maximum and minimum values in the kinetics of CH₄ emissions can be missed during the interval between measurements, which may influence the quantification of CH₄ emissions. Chambers must be opened for morning feeding and cleaning, which causes a loss of CH₄ data. Calculation methods are needed to estimate the lost CH₄ emission data, which may influence the estimated amount of daily CH₄ emissions. In this study, we measured the CH₄ emissions of 10 growing Chinese Holstein dairy heifers in respiration chambers. Methane concentrations were measured every 0.5 min to obtain the 23-h kinetics of CH₄ emissions, which were further selected at different intervals between measurements (i.e., 5, 30, 60, 120, 180, and 240 min) to evaluate the effects of interval on quantification of CH₄ emissions. The missing 1-h kinetics of CH₄ emissions before feeding were not measured, and 2 calculation methods were used to estimate the missing 1-h kinetics of CH₄ emissions: mean value of measuring period (the mean method) and the nearest value of measurement just before chamber opening (the nearest method). The results showed that the rates of CH₄ emission from 10 heifers varied from 4.56 to 11.42 g/h. The increment of intervals decreased maximum rate of CH₄ emission and increased minimum rate of CH₄ emission. Interval caused less than 5% of the difference in measuring CH₄ emissions. Although the mean method had greater estimated daily CH₄ emission than the nearest method, the difference was within 3%. The interval between measurements (≤3 h) and calculation method had little influence on enteric CH₄ emission measurements.     

Symposium review: Uncertainties in enteric methane inventories,measurement techniques,and prediction models

Ruminant production systems are important contributors to anthropogenic methane (CH₄) emissions, but there are large uncertainties in national and global livestock CH₄ inventories. Sources of uncertainty in enteric CH₄ emissions include animal inventories, feed dry matter intake (DMI), ingredient and chemical composition of the diets, and CH₄ emission factors. There is also significant uncertainty associated with enteric CH₄ measurements. The most widely used techniques are respiration chambers, the sulfur hexafluoride (SF₆) tracer technique, and the automated head-chamber system (GreenFeed; C-Lock Inc., Rapid City, SD). All 3 methods have been successfully used in a large number of experiments with dairy or beef cattle in various environmental conditions, although studies that compare techniques have reported inconsistent results. Although different types of models have been developed to predict enteric CH₄ emissions, relatively simple empirical (statistical) models have been commonly used for inventory purposes because of their broad applicability and ease of use compared with more detailed empirical and process-based mechanistic models. However, extant empirical models used to predict enteric CH₄ emissions suffer from narrow spatial focus, limited observations, and limitations of the statistical technique used. Therefore, prediction models must be developed from robust data sets that can only be generated through collaboration of scientists across the world. To achieve high prediction accuracy, these data sets should encompass a wide range of diets and production systems within regions and globally. Overall, enteric CH₄ prediction models are based on various animal or feed characteristic inputs but are dominated by DMI in one form or another. As a result, accurate prediction of DMI is essential for accurate prediction of livestock CH₄ emissions. Analysis of a large data set of individual dairy cattle data showed that simplified enteric CH₄ prediction models based on DMI alone or DMI and limited feed- or animal-related inputs can predict average CH₄ emission with a similar accuracy to more complex empirical models. These simplified models can be reliably used for emission inventory purposes.     

Methane production,ruminal fermentation characteristics,nutrient digestibility,nitrogen excretion,and milk production of dairy cows fed conventional or brown midrib corn silage

The objective of this study was to examine the effect of replacing conventional corn silage (CCS) with brown midrib corn silage (BMCS) in dairy cow diets on enteric CH₄ emission, nutrient intake, digestibility, ruminal fermentation characteristics, milk production, and N excretion. Sixteen rumen-cannulated lactating cows used in a crossover design (35-d periods) were fed (ad libitum) a total mixed ration (forage:concentrate ratio = 65:35, dry matter basis) based (59% dry matter) on either CCS or BMCS. Dry matter intake and milk yield increased when cows were fed BMCS instead of CCS. Of the milk components, only milk fat content slightly decreased when cows were fed the BMCS-based diet compared with when fed the CCS-based diet (3.81 vs. 3.92%). Compared with CCS, feeding BMCS to cows increased yields of milk protein and milk fat. Ruminal pH, protozoa numbers, total VFA concentration, and molar proportions of acetate and propionate were similar between cows fed BMCS and those fed CCS. Daily enteric CH₄ emission (g/d) was unaffected by dietary treatments, but CH₄ production expressed as a proportion of gross energy intake or on milk yield basis was lower for cows fed the BMCS-based diet than for cows fed the CCS-based diet. A decline in manure N excretion and a shift in N excretion from urine to feces were observed when BMCS replaced CCS in the diet, suggesting reduced potential of manure N volatilization. Results from this study show that improving fiber quality of corn silage in dairy cow diets through using brown midrib trait cultivar can reduce enteric CH₄ emissions as well as potential emissions of NH₃ and N₂O from manure. However, CH₄ emissions during manure storage may increase due to excretion of degradable OM when BMCS diet is fed, which merits further investigation.     

Impact of nitrate and 3-nitrooxypropanol on the carbon footprints of milk from cattle produced in confined-feeding systems across regions in the United States: A life cycle analysis

It is estimated that enteric methane (CH₄) contributes about 70% of all livestock greenhouse gas (GHG) emissions. Several studies indicated that feed additives such as 3-nitrooxypropanol (3-NOP) and nitrate have great potential to reduce enteric emissions. The objective of this study was to determine the net effects of 3-NOP and nitrate on farmgate milk carbon footprint across various regions of the United States and to determine the variability of carbon footprint. A cradle-to-farmgate life cycle assessment was performed to determine regional and national carbon footprint to produce 1 kg of fat- and protein-corrected milk (FPCM). Records from 1,355 farms across 37 states included information on herd structure, milk production and composition, cattle diets, manure management, and farm energy. Enteric CH₄, manure CH₄, and nitrous oxide were calculated with either the widely used Intergovernmental Panel on Climate Change Tier 2 or region-specific equations available in the literature. Emissions were allocated between milk and meat using a biophysical allocation method. Impacts of nitrate and 3-NOP on baseline regional and national carbon footprint were accounted for using equations adjusted for dry matter intake and neutral detergent fiber. Uncertainty analysis of carbon footprint was performed using Monte Carlo simulations to capture variability due to inputs data. Overall, the milk carbon footprint for the baseline, nitrate, and 3-NOP scenarios were 1.14, 1.09 (4.8% reduction), and 1.01 (12% reduction) kg of CO₂-equivalents (CO₂-eq)/kg of FPCM across US regions. The greatest carbon footprint for the baseline scenario was in the Southeast (1.26 kg of CO₂-eq/kg of FPCM) and lowest for the West region (1.02 kg of CO₂-eq/kg of FPCM). Enteric CH₄ reductions were 12.4 and 31.0% for the nitrate and 3-NOP scenarios, respectively. The uncertainty analysis showed that carbon footprint values ranged widely (0.88–1.52 and 0.56–1.84 kg of CO₂-eq/kg of FPCM within 1 and 2 standard deviations, respectively), suggesting the importance of site-specific estimates of carbon footprint. Considering that 101 billion kilograms of milk was produced by the US dairy industry in 2020, the potential net reductions of GHG from the baseline 117 billion kilograms of CO₂-eq were 5.6 and 13.9 billion kilograms of CO₂-eq for the nitrate and 3-NOP scenarios, respectively.     

Effect of concentrate feed level on methane emissions from grazing dairy cows

Although the effect of nutrition on enteric methane (CH₄) emissions from confined dairy cattle has been extensively examined, less information is available on factors influencing CH₄ emissions from grazing dairy cattle. In the present experiment, 40 Holstein-Friesian dairy cows (12 primiparous and 28 multiparous) were used to examine the effect of concentrate feed level (2.0, 4.0, 6.0, and 8.0 kg/cow per day; fresh basis) on enteric CH₄ emissions from cows grazing perennial ryegrass-based swards (10 cows per treatment). Methane emissions were measured on 4 occasions during the grazing period (one 4-d measurement period and three 5-d measurement periods) using the sulfur hexafluoride technique. Milk yield, liveweight, and milk composition for each cow was recorded daily during each CH₄ measurement period, whereas daily herbage dry matter intake (DMI) was estimated for each cow from performance data, using the back-calculation approach. Total DMI, milk yield, and energy-corrected milk (ECM) yield increased with increasing concentrate feed level. Within each of the 4 measurement periods, daily CH₄ production (g/d) was unaffected by concentrate level, whereas CH₄/DMI decreased with increasing concentrate feed level in period 4, and CH₄/ECM yield decreased with increasing concentrate feed level in periods 2 and 4. When emissions data were combined across all 4 measurement periods, concentrate feed level (2.0, 4.0, 6.0, and 8.0 kg/d; fresh basis) had no effect on daily CH₄ emissions (287, 273, 272, and 277 g/d, respectively), whereas CH₄/DMI (20.0, 19.3, 17.7, and 18.1 g/kg, respectively) and CH₄-E/gross energy intake (0.059, 0.057, 0.053, and 0.054, respectively) decreased with increasing concentrate feed levels. A range of prediction equations for CH₄ emissions were developed using liveweight, DMI, ECM yield, and energy intake, with the strongest relationship found between ECM yield and CH₄/ECM yield (coefficient of determination = 0.50). These results demonstrate that offering concentrates to grazing dairy cows increased milk production per cow and decreased CH₄ emissions per unit of milk produced.     

Methane emissions among individual dairy cows during milking quantified by eructation peaks or ratio with carbon dioxide

The aims of this study were to compare methods for examining measurements of CH₄ and CO₂ emissions of dairy cows during milking and to assess repeatability and variation of CH₄ emissions among individual dairy cows. Measurements of CH₄ and CO₂ emissions from 36 cows were collected in 3 consecutive feeding periods. In the first period, cows were fed a commercial partial mixed ration (PMR) containing 69% forage. In the second and third periods, the same 36 cows were fed a high-forage PMR ration containing 75% forage, with either a high grass silage or high maize silage content. Emissions of CH₄ during each milking were examined using 2 methods. First, peaks in CH₄ concentration due to eructations during milking were quantified. Second, ratios of CH₄ and CO₂ average concentrations during milking were calculated. A linear mixed model was used to assess differences between PMR. Variation in CH₄ emissions was observed among cows after adjusting for effects of lactation number, week of lactation, diet, individual cow, and feeding period, with coefficients of variation estimated from variance components ranging from 11 to 14% across diets and methods of quantifying emissions. No significant difference was detected between the 3 PMR in CH₄ emissions estimated by either method. Emissions of CH₄ calculated from eructation peaks or as CH₄ to CO₂ ratio were positively associated with forage dry matter intake. Ranking of cows according to CH₄ emissions on different diets was correlated for both methods, although rank correlations and repeatability were greater for CH₄ concentration from eructation peaks than for CH₄-to-CO₂ ratio. We conclude that quantifying enteric CH₄ emissions either using eructation peaks in concentration or as CH₄-to-CO₂ ratio can provide highly repeatable phenotypes for ranking cows on CH₄ output.     

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.     

Methodological guidelines: Cow milk mid-infrared spectra to predict reference enteric methane data collected by an automated head-chamber system

Various methodological protocols were tested on milk samples from cows fed diets affecting both methanogenesis and milk synthesis to identify the best approach for the prediction of GreenFeed system (GF) measured methane (CH₄) emissions by milk mid-infrared (MIR) spectroscopy. The models developed were also tested on a data set from cows fed chemical inhibitors of CH₄ emission [3-nitrooxypropanol (3NOP)] that just marginally affect milk composition. A total of 129 primiparous and multiparous Holstein cows fed diets with different methanogenic potential were considered. Individual milk yield (MY) and dry matter intake were recorded daily, whereas fat- and protein-corrected milk (FPCM) was recorded twice a week. The MIR spectra from 2 consecutive milkings were collected twice a week. Twenty CH₄ spot measurements with GF were taken as the basic measurement unit (BMU) of CH₄. The equations were built using partial least squares regression by splitting the database into calibration and validation data sets (excluding 3NOP samples). Models were developed for milk MIR spectra by milking and on day spectra obtained by averaging spectra from 2 consecutive milkings. Models based on day spectra were calibrated by using CH₄ reference data for a measurement duration of 1, 2, 3, or 4 BMU. Models built from the average of the day spectra collected during the corresponding CH₄ measurement periods were developed. Corrections of spectra by days in milk (DIM) and the inclusion of parity, MY, and FPCM as explanatory variables were tested as tools to improve model performance. Models built on day milk MIR spectra gave slightly better performances that those developed using spectra from a single milking. Long duration of CH₄ measurement by GF performed better than short duration: the coefficient of determination of validation (R²V) for CH₄ emissions expressed in grams per day were 0.60 vs. 0.52 for 4 and 1 BMU, respectively. When CH₄ emissions were expressed as grams per kilogram of dry of matter intake, grams per kilogram of MY, or grams per kilogram of FPCM, performance with a long duration also improved. Coupling GF reference data with the average of milk MIR spectra collected throughout the corresponding CH₄ measurement period gave better predictions than using day spectra (R²V = 0.70 vs. 0.60 for CH₄ as g/d on 4 BMU). Correcting the day spectra by DIM improved R²V compared with the equivalent DIM-uncorrected models (R²V = 0.67 vs. 0.60 for CH₄ as g/d on 4 BMU). Adding other phenotypic information as explanatory variables did not further improve the performance of models built on single day DIM-corrected spectra, whereas including MY (or FPCM) improved the performance of models built on the average of spectra (uncorrected by DIM) recorded during the CH₄ measurement period (R²V = 0.73 vs. 0.70 for CH₄ as g/d on 4 BMU). When validating the models on the 3NOP data set, predictions were poor without (R²V = 0.13 for CH₄ as g/d on 1 BMU) or with (R²V = 0.31 for CH₄ as g/d on 1 BMU) integration of 3NOP data in the models. Thus, specific models would be required for CH₄ prediction when cows receive chemical inhibitors of CH₄ emissions not affecting milk composition.     

Emissions of ammonia,nitrous oxide,methane, and carbon dioxide during storage of dairy cow manure as affected by dietary forage-to-concentrate ratio and crust formation

Sixteen 200-L barrels were used to determine the effects of dietary forage-to-concentrate (F:C) ratio on the rate of NH₃-N, N₂O, CH₄, and CO₂ emissions from dairy manure during a 77-d storage period. Manure was obtained from a companion study where cows were assigned to total mixed rations that included the following F:C ratio: 47:53, 54:46, 61:39, and 68:32 (diet dry matter basis) and housed in air-flow-controlled chambers constructed in a modified tiestall barn. On d 0 of this study, deposited manure and bedding from each emission chamber was thoroughly mixed, diluted with water (1.9 to 1 manure-to-water ratio) and loaded in barrels. In addition, on d 0, 7, 14, 28, 35, 49, 56, 63, 70, and 77 of storage, the rate of NH₃-N, N₂O, CH₄, and CO₂ emissions from each barrel were measured with a dynamic chamber and gas concentration measured with a photo-acoustic multi-gas monitor. Data were analyzed as a randomized complete block with 4 replications. Dietary F:C ratio had no effect on manure dry matter, total N and total ammoniacal-N (NH₃-N + NH₄⁺-N), or pH at the time of storage (mean ± SD: 10.6 ± 0.6%, 3.0 ± 0.2%, 93.1 ± 18.1 mg/dL, and 7.8 ± 0.5, respectively). No treatment differences were observed in the overall rate of manure NH₃-N, N₂O, CH₄, and CO₂ emissions (mean ± SD over the 77-d storage period; 117 ± 25, 30 ± 7, 299 ± 62, and 15,396 ± 753 mg/hr per m², respectively). The presence of straw bedding in manure promoted the formation of a surface crust that became air dried after about 1 mo of storage, and was associated with an altered pattern in NH₃-N and N₂O emissions in particular. Whereas NH₃-N emission rate was highest on d 0 and gradually decreased until reaching negligible levels on d 35, N₂O emission rate was almost zero the first 2 wk of storage, increased sharply to peak on d 35, and decreased subsequently. The emission rate of CH₄ and CO₂ peaked simultaneously on d 7, but decreased subsequently until the end of the storage period. In this study, C:N ratio of gaseous losses was 32:1, reflecting higher volatile C loss than volatile N loss during storage. On a CO₂-equivalent basis, the most important source of non-CO₂ greenhouse gas emitted was CH₄ until formation of an air-dried crust, but N₂O thereafter. Taken together, these results suggested that the formation of an air-dried crust resulting from the straw bedding present in the manure reduced drastically NH₃-N, and CH₄ emissions, but was conducive of N₂O production and emission.     

Effect of feeding fresh forage plantain (Plantago lanceolata) or ryegrass-based pasture on methane emissions,total-tract digestibility,and rumen fermentation of nonlactating dairy cows

Plantain (Plantago lanceolata) is an herb used to reduce the forage deficit of ryegrass-based pastures during the summer. This herb is being promoted for its reduced environmental impact in terms of nitrogen emissions, particularly reducing urinary nitrogen. However, the effect of plantain on emissions of enteric CH₄, the main greenhouse gas produced from ruminant-based production systems, is not known. The aim of the present trial was to determine CH₄ emissions and rumen fermentation characteristics of nonlactating dairy cows fed 100% plantain (PLT) or 100% perennial ryegrass (RG; Lolium perenne) in 2 experiments (E1 and E2). The forages were in a vegetative growth stage in E1 and were in a reproductive growth stage in E2. Methane emissions from 16 cows in each experiment were measured in respiration chambers for 2 d. Methane emissions per unit of dry matter intake (CH₄ yield) were 15 and 28% less for cows fed PLT than those fed RG in E1 and E2, respectively. Dry matter digestibility of PLT was 7 and 27% less than that of RG in E1 and E2, respectively, and CH₄ per unit of dry matter digested was similar for PLT and RG in both experiments. There were only minor (but some significant) differences in rumen fermentation characteristics between cows fed PLT and RG in both experiments. In conclusion, CH₄ yield was lower for cows fed PLT compared with those fed RG in both experiments and this reduction was largely explained by the lesser dry matter digestibility of PLT.     

Variation among individual dairy cows in methane measurements made on farm during milking

The objective of this study was to quantify on-farm variation between and within cows in methane emissions measured during milking, and to determine which factors are related to this variation. Methane emission rate during milking (MERm) was recorded at milking using methane analyzers installed in automatic (robotic) milking stations for 215 cows over a period of 5 mo. Between-cow variation in MERm (mean 2.07, SD 0.629 g/min), was greater than within-cow variation and was related to variation in body weight, milk yield, parity, and week of lactation. Estimation of daily methane emissions from MERm data, using an equation derived from comparisons with respiration chamber data, produced estimates that ranged from 278 to 456 g of CH₄/d and were commensurate with values predicted from metabolizable energy requirements for observed body weight and milk yield. It is concluded that methane emissions vary considerably between dairy cows housed under commercial conditions. This variation needs to be taken into account when performing inventories or testing mitigation strategies, but it might offer opportunities for genetic selection.     

Short communication: Development of an equation for estimating methane emissions of dairy cows from milk Fourier transform mid-infrared spectra by using reference data obtained exclusively from respiration chambers

Evaluation and mitigation of enteric methane (CH₄) emissions from ruminant livestock, in particular from dairy cows, have acquired global importance for sustainable, climate-smart cattle production. Based on CH₄ reference measurements obtained with the SF₆ tracer technique to determine ruminal CH₄ production, a current equation permits evaluation of individual daily CH₄ emissions of dairy cows based on milk Fourier transform mid-infrared (FT-MIR) spectra. However, the respiration chamber (RC) technique is considered to be more accurate than SF₆ to measure CH₄ production from cattle. This study aimed to develop an equation that allows estimating CH₄ emissions of lactating cows recorded in an RC from corresponding milk FT-MIR spectra and to challenge its robustness and relevance through validation processes and its application on a milk spectral database. This would permit confirming the conclusions drawn with the existing equation based on SF₆ reference measurements regarding the potential to estimate daily CH₄ emissions of dairy cows from milk FT-MIR spectra. A total of 584 RC reference CH₄ measurements (mean ± standard deviation of 400 ± 72 g of CH₄/d) and corresponding standardized milk mid-infrared spectra were obtained from 148 individual lactating cows between 7 and 321 d in milk in 5 European countries (Germany, Switzerland, Denmark, France, and Northern Ireland). The developed equation based on RC measurements showed calibration and cross-validation coefficients of determination of 0.65 and 0.57, respectively, which is lower than those obtained earlier by the equation based on 532 SF₆ measurements (0.74 and 0.70, respectively). This means that the RC-based model is unable to explain the variability observed in the corresponding reference data as well as the SF₆-based model. The standard errors of calibration and cross-validation were lower for the RC model (43 and 47 g/d vs. 66 and 70 g/d for the SF₆ version, respectively), indicating that the model based on RC data was closer to actual values. The root mean squared error (RMSE) of calibration of 42 g/d represents only 10% of the overall daily CH₄ production, which is 23 g/d lower than the RMSE for the SF₆-based equation. During the external validation step an RMSE of 62 g/d was observed. When the RC equation was applied to a standardized spectral database of milk recordings collected in the Walloon region of Belgium between January 2012 and December 2017 (1,515,137 spectra from 132,658 lactating cows in 1,176 different herds), an average ± standard deviation of 446 ± 51 g of CH₄/d was estimated, which is consistent with the range of the values measured using both RC and SF₆ techniques. This study confirmed that milk FT-MIR spectra could be used as a potential proxy to estimate daily CH₄ emissions from dairy cows provided that the variability to predict is covered by the model.