Genome-wide association study for methane emission traits in Danish Holstein cattle

Selecting for lower methane emitting cows requires insight into the most biologically relevant phenotypes for methane emission, which are close to the breeding goal. Several methane phenotypes have been suggested over the last decade. However, the (dis)similarity of their underlying genetic architecture and correlation structures are poorly understood. Therefore, the objective of this study was to test association of SNP and genomic regions through GWAS on 8 CH₄ emission traits in Danish Holstein cattle. The traits studied were methane concentration (MeC; ppm), methane production (MeP ; g/d), 2 definitions of residual methane (RMETc and RMETp: MeC and MeP regressed on metabolic body weight and energy-corrected milk, respectively), 2 definitions of methane intensity (MeI; MeIc = MeC/ECM and MeIp = MeP/ECM); 2 definitions of methane yield per kilogram of dry matter intake (MeY; MeYc = MeC/dry matter intake and MeYp = MeP/dry matter intake). A total of 1,962 cows with genotypes (Illumina BovineSNP50 Chip or Eurogenomic custom SNP chip) and repeated records of the above-mentioned 8 methane traits were analyzed. Strong associations were found with 3 traits (MeC, MeP, and MeYc) on chromosome 13 and with 5 traits (MeC, MeP, MeIp, MeYp, and MeYc) on chromosome 26. For MeIc, MeIp, RMETc, MeYc, and MeYp, some suggestive association signals were identified on chromosome 1. Genomic segments of 1 Mbp (n = 2,525) were tested for their association with these traits, which identified between 33 to 54 significantly associated regions. In a pairwise comparison, MeC and MeP were the traits that shared the highest number of significant segments (17). The same trend was observed when comparing SNP significantly associated with the traits MeC and MeP shared from 23 to 25 SNP (most of which were located in chromosomes 11, 13, and 26). Based on our results on GWAS and genetic correlations, we conclude that MeC is (genetically) more closely linked to MeP than any of the other methane traits analyzed.     

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.     

Genetic parameters for methane emission traits in Australian dairy cows

Methane is a greenhouse gas of high interest to the dairy industry, with 57% of Australia's dairy emissions attributed to enteric methane. Enteric methane emissions also constitute a loss of approximately 6.5% of ingested energy. Genetic selection offers a unique mitigation strategy to decrease the methane emissions of dairy cattle, while simultaneously improving their energy efficiency. Breeding objectives should focus on improving the overall sustainability of dairy cattle by reducing methane emissions without negatively affecting important economic traits. Common definitions for methane production, methane yield, and methane intensity are widely accepted, but there is not yet consensus for the most appropriate method to calculate residual methane production, as the different methods have not been compared. In this study, we examined 9 definitions of residual methane production. Records of individual cow methane, dry matter intake (DMI), and energy corrected milk (ECM) were obtained from 379 animals and measured over a 5-d period from 12 batches across 5 yr using the SF₆ tracer method and an electronic feed recording system, respectively. The 9 methods of calculating residual methane involved genetic and phenotypic regression of methane production on a combination of DMI and ECM corrected for days in milk, parity, and experimental batch using phenotypes or direct genomic values. As direct genomic values (DGV) for DMI are not routinely evaluated in Australia at this time, DGV for FeedSaved, which is derived from DGV for residual feed intake and estimated breeding value for bodyweight, were used. Heritability estimates were calculated using univariate models, and correlations were estimated using bivariate models corrected for the fixed effects of year-batch, days in milk, and lactation number, and fitted using a genomic relationship matrix. Residual methane production candidate traits had low to moderate heritability (0.10 ± 0.09 to 0.21 ± 0.10), with residual methane production corrected for ECM being the highest. All definitions of residual methane were highly correlated phenotypically (>0.87) and genetically (>0.79) with one another and moderately to highly with other methane candidate traits (>0.59), with high standard errors. The results suggest that direct selection for a residual methane production trait would result in indirect, favorable improvement in all other methane traits. The high standard errors highlight the importance of expanding data sets by measuring more animals for their methane emissions and DMI, or through exploration of proxy traits and combining data via international collaboration.     

Blood plasma traits associated with genetic merit for feed utilization in Holstein cows

The objective of this study was to evaluate the potential of selection for feed utilization on associated blood plasma metabolite and hormone traits. Dry matter intake (DMI) was recorded in 970 Holsteins from 11 commercial farms in Pennsylvania and used to derive dry matter efficiency (DME; fat-corrected milk yield/DMI), crude protein efficiency (CPE; protein yield/crude protein intake), and residual feed intake (RFI, defined as actual feed intake minus expected feed intake for maintenance and milk production, based on calculation of DMI adjusted for yield, body weight, and body condition score). Estimated breeding values for the 4 feed utilization traits (DMI, DME, CPE, and RFI), yield traits, body traits, and days open were standardized according to their respective genetic standard deviations. Up to 631 blood samples from 393 cows from 0 to 60 d in milk (DIM) were evaluated for blood plasma concentrations of glucose, nonesterified fatty acids (NEFA), β-hydroxybutyrate (BHB), creatinine, urea, growth hormone (GH), 3,5,3′-triiodothyronine (T3), and other parameters. Blood plasma traits were regressed on DIM, lactation number, herd, and standardized genetic merit. Cows with higher genetic merit for yield had significantly higher concentrations of GH, NEFA (milk and protein yield), and BHB (fat yield) from 31 to 60 DIM, but lower concentrations of glucose from 0 to 30 DIM, and T3 (milk yield, 0–60 DIM). The high GH–low glucose–low T3 concentration pattern was further accentuated for cows with genetic merit for enhanced feed efficiency (higher DME and lower RFI). Cows with a genetic tendency to be thin (low body condition score) also had elevated GH concentrations, but lower blood glucose, creatinine, and T3 concentrations. Those characteristics associated with enhanced feed efficiency (higher GH and lower glucose and T3 concentrations) were unfavorably associated with fertility, as indicated by elevated days open. Elevated NEFA and BHB concentrations were also associated with extended days open. Consideration of metabolic profiles when evaluating feed efficiency might be a method of maintaining high levels of health and reproductive fitness when selecting for feed efficiency.     

Methane production,rumen fermentation,and diet digestibility of Holstein and Jersey dairy cows being divergent in residual feed intake and fed at 2 forage-to-concentrate ratios

Improving feed efficiency of dairy cows through breeding is expected to reduce enteric methane production per unit of milk produced. This study examined the effect of 2 forage-to-concentrate ratios on methane production, rumen fermentation, and nutrient digestibility in Holstein and Jersey dairy cows divergent in residual feed intake (RFI). Before experimental onset, RFI was estimated using a random regression model on phenotypic herd data. Ten lactating Holstein and 10 lactating Jersey cows were extracted from the herd and allocated to a high or low pre-experimental RFI group of 5 animals each within breed. Cows were fed ad libitum with total mixed rations either low (LC) or high (HC) in concentrates during 3 periods in a crossover design with a back-cross and staggered approach. Forage-to-concentrate ratio was 68:32 for LC and 39:61 for HC. Cows adapted to the diets in 12 to 24 d and feces were subsequently collected on 2 d. Afterward, gas exchange was measured in respiration chambers and rumen liquid was collected once after cows exited the chambers. Pre-experimental RFI was included in the statistical analysis as a class (low and high RFI) or continuous variable. Methane per kilogram of dry matter intake (DMI) was lower for Holsteins than Jerseys and the response to increased concentrate level was more pronounced for Holsteins than Jerseys (27.2 vs.13.8%); a similar pattern was found for the acetate:propionate ratio. However, methane production per kilogram of energy-corrected milk (ECM) was unaffected by breed. Further, total-tract digestibility of neutral detergent fiber was higher for Jerseys than Holsteins. For RFI as a class variable, DMI, methane production regardless of the expression, and digestibility were unaffected by RFI. For RFI as a continuous variable, DMI was lower and methane per kilogram of DMI was higher for cows with negative (efficient) than positive (inefficient) RFI values, and neutral detergent fiber digestibility was higher for Holsteins with negative than positive RFI values, but not for Jerseys. Daily methane production and methane per kilogram of ECM were unaffected by RFI. In conclusion, methane per kilogram of DMI of Jerseys was lowered to a smaller extent in response to the HC diet than of Holsteins. When pre-experimental RFI was used as a continuous variable, higher methane per kilogram of DMI was found for cows with negative RFI than positive RFI values, but not for methane per kilogram of ECM. These findings call for validation in larger studies.     

The genetic and biological basis of feed efficiency in mid-lactation Holstein dairy cows

The objective of this study was to identify genomic regions and candidate genes associated with feed efficiency in lactating Holstein cows. In total, 4,916 cows with actual or imputed genotypes for 60,671 single nucleotide polymorphisms having individual feed intake, milk yield, milk composition, and body weight records were used in this study. Cows were from research herds located in the United States, Canada, the Netherlands, and the United Kingdom. Feed efficiency, defined as residual feed intake (RFI), was calculated within location as the residual of the regression of dry matter intake (DMI) on milk energy (MilkE), metabolic body weight (MBW), change in body weight, and systematic effects. For RFI, DMI, MilkE, and MBW, bivariate analyses were performed considering each trait as a separate trait within parity group to estimate variance components and genetic correlations between them. Animal relationships were established using a genomic relationship matrix. Genome-wide association studies were performed separately by parity group for RFI, DMI, MilkE, and MBW using the Bayes B method with a prior assumption that 1% of single nucleotide polymorphisms have a nonzero effect. One-megabase windows with greatest percentage of the total genetic variation explained by the markers (TGVM) were identified, and adjacent windows with large proportion of the TGVM were combined and reanalyzed. Heritability estimates for RFI were 0.14 (±0.03; ±SE) in primiparous cows and 0.13 (±0.03) in multiparous cows. Genetic correlations between primiparous and multiparous cows were 0.76 for RFI, 0.78 for DMI, 0.92 for MBW, and 0.61 for MilkE. No single 1-Mb window explained a significant proportion of the TGVM for RFI; however, after combining windows, significance was met on Bos taurus autosome 27 in primiparous cows, and nearly reached on Bos taurus autosome 4 in multiparous cows. Among other genes, these regions contain β-3 adrenergic receptor and the physiological candidate gene, leptin, respectively. Between the 2 parity groups, 3 of the 10 windows with the largest effects on DMI neighbored windows affecting RFI, but were not in the top 10 regions for MilkE or MBW. This result suggests a genetic basis for feed intake that is unrelated to energy consumption required for milk production or expected maintenance as determined by MBW. In conclusion, feed efficiency measured as RFI is a polygenic trait exhibiting a dynamic genetic basis and genetic variation distinct from that underlying expected maintenance requirements and milk energy output.     

Assessing feed efficiency in early and mid lactation and its associations with performance and health in Holstein cows

Objectives were to evaluate the associations between residual dry matter (DM) intake (RFI) and residual N intake (RNI) in early lactation, from 1 to 5 wk postpartum, and in mid lactation, from 9 to 15 wk postpartum, and assess production performance and risk of diseases in cows according to RFI in mid lactation. Data from 4 experiments including 399 Holsteins cows were used in this study. Intakes of DM and N, yields of milk components, body weight, and body condition were evaluated daily or weekly for the first 105 d postpartum. Milk yield by 305 d postpartum was also measured. Incidence of disease was evaluated for the first 90 d postpartum and survival up to 300 d postpartum. Residual DM and N intake were calculated in early and mid lactation as the observed minus the predicted values, which were based on linear models that accounted for major energy or N sinks, including daily milk energy or N output, metabolic body weight, and daily body energy or N changes, and adjusting for parity, season of calving, and treatment within experiment. Cows were ranked by RFI and RNI in mid lactation and categorized into quartiles (Q1 = smallest RFI, to Q4 = largest RFI). Increasing efficiency in mid lactation resulted in linear decreases in RFI (depicted from Q1 to Q4; ?0.93, ?0.05, ?0.04, and 0.98 kg/d), DMI (16.0, 16.9, 17.3, and 18.4 kg/d), net energy for lactation (NE_L) intake (26.8, 28.4, 29.0, and 30.8 Mcal/d), and NE_L balance (?9.0, ?8.1, ?8.2, and ?5.5 Mcal/d) during early lactation, but no differences were observed in body NE_L or N changes or yield of energy-corrected milk in the first 5 wk of lactation. Residual DM intake in mid lactation was associated with RFI (Pearson r = 0.43, and Spearman ρ = 0.32) and RNI (r = 0.44, ρ = 0.36) in early lactation, and with RNI in mid lactation (r = 0.91, ρ = 0.84). Similarly, RNI in mid lactation was associated with RNI in early lactation (r = 0.42, ρ = 0.35). During the first 15 wk postpartum, more efficient cows in mid lactation consumed 3.5 kg/d less DM (Q1 = 19.3 vs. Q4 = 22.8 kg/d) and were more N efficient (Q1 = 31.6 vs. Q4 = 25.8%), at the same time that yields of milk (Q1 = 39.0 vs. Q4 = 39.4 kg/d), energy-corrected milk (Q1 = 38.6 vs. Q4 = 39.3 kg/d), and milk components did not differ compared with the quartile of least efficient cows. Furthermore, RFI in mid lactation was not associated with 305-d milk yield, incidence of diseases in the first 90 d postpartum, or survival by 300 d postpartum. Collectively, rankings of RFI and RNI are associated and repeatable across lactation stages. The most feed-efficient cows were also more N efficient in early and mid lactation. Phenotypic selection of RFI based on measurements in mid lactation is associated with improved efficiency without affecting production or health in dairy cows.     

The effects of feeding 3-nitrooxypropanol on methane emissions and productivity of Holstein cows in mid lactation

The objective of the current study was to determine the effects of adding 3-nitrooxypropanol to the diet of lactating Holstein cows on methane emissions, rumen fermentation, ruminal microbial profile, and milk production. Twelve ruminally cannulated Holstein cows in midlactation were used in a crossover design study with 28-d periods. Cows were fed a diet containing 38% forage on a dry matter basis with either 2,500 mg/d of 3-nitrooxypropanol (fed as 25 g of 10% 3-nitrooxypropanol on silicon dioxide) or 25 g/d of silicon dioxide (control). After a 21-d diet adaptation period, dry matter intake (DMI) and milk yield were recorded daily. Rumen fluid and digesta were collected on d 22 and 28 for volatile fatty acid analysis and microbial profiling. Enteric methane emissions were measured on d 23 to 27 using the sulfur hexafluoride tracer gas technique. Feeding 3-nitrooxypropanol did not affect DMI; however, methane production was reduced from 17.8 to 7.18 g/kg of DMI. No change in milk or milk component yields was observed, but cows fed 3-nitrooxypropanol gained more body weight than control cows (1.06 vs. 0.39 kg/d). Concentrations of total volatile fatty acids in ruminal fluid were not affected by treatment, but a reduction in acetate proportion and a tendency for an increase in propionate proportion was noted. As such, a reduction in the acetate-to-propionate ratio was observed (2.02 vs. 2.36). Protozoa counts were not affected by treatment; however, a reduction in methanogen copy count number was observed when 3-nitrooxypropanol was fed (0.95 vs. 2.69 × 10⁸/g of rumen digesta). The data showed that feeding 3-nitrooxypropanol to lactating dairy cows at 2,500 mg/d can reduce methane emissions without compromising DMI or milk production.     

Genetic (co-)variation of methane emissions,efficiency, and production traits in Danish Holstein cattle along and across lactations

Methane emissions in ruminant livestock has become a hot topic, given the pressure to reduce greenhouse gas emissions drastically in the European Union over the next 10 to 30 yr. During the 2021 United Nations Climate Change conference, countries also made collective commitments to curb methane emissions by 2050. Genetic selection for low-methane-emitting animals, particularly dairy cows, is one possible strategy for mitigation. However, it is essential to understand how methane emissions in lactating animals vary along lactation and across lactations. This understanding is useful when making decisions for future phenotyping strategies, such as the frequency and duration of phenotyping within and across lactations. Therefore, the objectives of this study were to estimate (1) genetic parameters for 2 methane traits: methane concentration (MeC) and methane production (MeP) at 2 parity levels in Danish Holstein cows across the entire lactation using random regression models; (2) genetic correlations within and between methane traits across the entire lactation; and (3) genetic correlations between the methane traits and economically important traits throughout first lactation. Methane concentration (n = 19,639) records of 575 Danish Holstein cows from a research farm measured between 2013 and 2020 were available. Subsequently, CH₄ production in grams/day (MeP; n = 13,866) was calculated; MeP and MeC for first and second lactation (L1 and L2) were analyzed as separate traits: MeC_L1, MeP_L1, MeC_L2, and MeP_L2. Heritabilities, variance components, and genetic correlations within and between the 4 CH₄ traits were estimated using random regression models with Legendre polynomials. The additive genetic and permanent environmental effects were modeled using second-order Legendre polynomial for lactation weeks. Estimated heritabilities for MeP_L1 ranged between 0.11 and 0.49, for MeC_L1 between 0.10 and 0.28, for MeP_L2 between 0.14 and 0.36, and for MeC_L2 between 0.13 and 0.29. In general, heritability estimates of MeC traits were lower and more stable throughout lactation and were similar between lactations compared with MeP. Genetic correlations (within trait) at different lactation weeks were generally highly positive (0.7) for most of the first lactation, except for the correlation of early lactation (<10 wk) with late lactation (>40 wk) where the correlation was the lowest (<0.5). Genetic correlations between methane traits were moderate to highly correlated during early and mid lactation. Finally, MeP_L1 has stronger genetic correlations with energy-corrected milk and dry matter intake compared with MeC_L1. In conclusion, both traits are different along (and across) lactation(s) and they correlated differently with production, maintenance, and intake traits, which is important to consider when including one of them in a future breeding objective.     

Genetic background of methane emission by Dutch Holstein Friesian cows measured with infrared sensors in automatic milking systems

International environmental agreements have led to the need to reduce methane emission by dairy cows. Reduction could be achieved through selective breeding. The aim of this study was to quantify the genetic variation of methane emission by Dutch Holstein Friesian cows measured using infrared sensors installed in automatic milking systems (AMS). Measurements of CH₄ and CO₂ on 1,508 Dutch Holstein Friesian cows located on 11 commercial dairy farms were available. Phenotypes per AMS visit were the mean of CH₄, mean of CO₂, mean of CH₄ divided by mean of CO₂, and their log₁₀-transformations. The repeatabilities of the log₁₀-transformated methane phenotypes were 0.27 for CH₄, 0.31 for CO₂, and 0.14 for the ratio. The log₁₀-transformated heritabilities of these phenotypes were 0.11 for CH₄, 0.12 for CO₂, and 0.03 for the ratio. These results indicate that measurements taken using infrared sensors in AMS are repeatable and heritable and, thus, could be used for selection for lower CH₄ emission. Furthermore, it is important to account for farm, AMS, day of measurement, time of day, and lactation stage when estimating genetic parameters for methane phenotypes. Selection based on log₁₀-transformated CH₄ instead of the ratio would be expected to give a greater reduction of CH₄ emission by dairy cows.     

Effect of active dry yeast on lactation performance,methane production,and ruminal fermentation patterns in early-lactating Holstein cows

This study was conducted to examine the effect of active dry yeast (ADY) supplementation on lactation performance, ruminal fermentation patterns, and CH₄ emissions and to determine an optimal ADY dose. Sixty Holstein dairy cows in early lactation (52 ± 1.2 DIM) were used in a randomized complete design. Cows were blocked by parity (2.1 ± 0.2), milk production (35 ± 4.6 kg/d), and body weight (642 ± 53 kg) and assigned to 1 of 4 treatments. Cows were fed ADY at doses of 0, 10, 20, or 30 g/d per head for 91 d, with 84 d for adaptation and 7 d for sampling. Although dry matter intake was not affected by ADY supplementation, the yield of actual milk, 4% fat-corrected milk, milk fat yield, and feed efficiency increased quadratically with increasing ADY supplementation. Yields of milk protein and lactose increased linearly with increasing ADY doses, whereas milk urea nitrogen concentration and somatic cell count decreased quadratically. Ruminal pH and ammonia concentration were not affected by ADY supplementation, whereas ruminal concentration of total volatile fatty acid increased quadratically. Digestibility of dry matter, organic matter, neutral detergent fiber, acid detergent fiber, nonfiber carbohydrate, and crude protein increased quadratically with increasing ADY supplementation. Supplementation of ADY did not affect blood concentration of total protein, triglyceride, aspartate aminotransferase, and alanine aminotransferase, whereas blood urea nitrogen, cholesterol, and nonesterified fatty acid concentrations decreased quadratically with increasing ADY supplementation. Methane production was not affected by ADY supplementation when expressed as grams per day or per kilogram of actual milk yield, dry matter intake, digested organic matter, and digested nonfiber carbohydrate, whereas a trend of linear and quadratic decrease of CH₄ production was observed when expressed as grams per kilogram of fat-corrected milk and digested neutral detergent fiber. In conclusion, feeding ADY to early-lactating cows improved lactation performance by increasing nutrient digestibility. The optimal ADY dose should be 20 g/d per head.     

Genetic parameters for predicted methane production and potential for reducing enteric emissions through genomic selection

Mitigation of enteric methane (CH₄) emission in ruminants has become an important area of research because accumulation of CH₄ is linked to global warming. Nutritional and microbial opportunities to reduce CH₄ emissions have been extensively researched, but little is known about using natural variation to breed animals with lower CH₄ yield. Measuring CH₄ emission rates directly from animals is difficult and hinders direct selection on reduced CH₄ emission. However, improvements can be made through selection on associated traits (e.g., residual feed intake, RFI) or through selection on CH₄ predicted from feed intake and diet composition. The objective was to establish phenotypic and genetic variation in predicted CH₄ output, and to determine the potential of genetics to reduce methane emissions in dairy cattle. Experimental data were used and records on daily feed intake, weekly body weights, and weekly milk production were available from 548 heifers. Residual feed intake (MJ/d) is the difference between net energy intake and calculated net energy requirements for maintenance as a function of body weight and for fat- and protein-corrected milk production. Predicted methane emission (PME; g/d) is 6% of gross energy intake (Intergovernmental Panel on Climate Change methodology) corrected for energy content of methane (55.65 kJ/g). The estimated heritabilities for PME and RFI were 0.35 and 0.40, respectively. The positive genetic correlation between RFI and PME indicated that cows with lower RFI have lower PME (estimates ranging from 0.18 to 0.84). Hence, it is possible to decrease the methane production of a cow by selecting more-efficient cows, and the genetic variation suggests that reductions in the order of 11 to 26% in 10 yr are theoretically possible, and could be even higher in a genomic selection program. However, several uncertainties are discussed; for example, the lack of true methane measurements (and the key assumption that methane produced per unit feed is not affected by RFI level), as well as the limitations of predicting the biological consequences of selection. To overcome these limitations, an international effort is required to bring together data on feed intake and methane emissions of dairy cows.     

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.     

Comparison of methane production,intensity, and yield throughout lactation in Holstein cows

Genetic selection to reduce methane (CH₄) emissions from dairy cows is an attractive means of reducing the impact of agricultural production on climate change. In this study, we investigated the feasibility of such an approach by characterizing the interactions between CH₄ and several traits of interest in dairy cows. We measured CH₄, dry matter intake (DMI), fat- and protein-corrected milk (FPCM), body weight (BW), and body condition score (BCS) from 107 first- and second-parity Holstein cows from December 2019 to November 2021. Methane emissions were measured using a GreenFeed device and expressed in terms of production (MeP, in g/d), yield (MeY, in g/kg DMI), and intensity (MeI, in g/kg FPCM). Because of the limited number of cows, only animal parameters were estimated. Both MeP and MeI were moderately repeatable (>0.45), whereas MeY presented low repeatability, especially in early lactation. Mid lactation was the most stable and representative period of CH₄ emissions throughout lactation, with animal correlations above 0.9. The average animal correlations of MeP with DMI, FPCM, and BW were 0.62, 0.48, and 0.36, respectively. The MeI was negatively correlated with FCPM (<−0.5) and DMI (>−0.25), and positively correlated with BW and BCS. The MeY presented stable and weakly positive correlations with the 4 other traits throughout lactation, with the exception of slightly negative animal correlations with FPCM and DMI after the 35th week. The MeP, MeI, and MeY were positively correlated at all lactation stages and, assuming animal and genetic correlations do not strongly differ, selection on one trait should lead to improvements in all. Overall, selection for MeI is probably not optimal as its change would result more from CH₄ dilution in increased milk yield than from real decrease in methane emission. Instead, MeY is related to rumen function and is only weakly associated with DMI, FPCM, BW, and BCS; it thus appears to be the most promising CH₄ trait for selection, provided that this would not deteriorate feed efficiency and that a system of large-scale phenotyping is developed. The MeP is easier to measure and thus may represent an acceptable alternative, although care would need to be taken to avoid undesirable changes in FPCM and BW.     

Relationship between residual feed intake and digestibility for lactating Holstein cows fed high and low starch diets

We determined if differences in digestibility among cows explained variation in residual feed intake (RFI) in 4 crossover design experiments. Lactating Holstein cows (n = 109; 120 ± 30 d in milk; mean ± SD) were fed diets high (HS) or low (LS) in starch. The HS diets were 30% (±1.8%) starch and 27% (±1.2%) neutral detergent fiber (NDF); LS diets were 14% (±2.2%) starch and 40% (±5.3%) NDF. Each experiment consisted of two 28-d treatment periods, with apparent total-tract digestibility measured using indigestible NDF as an internal marker during the last 5 d of each period. Individual cow dry matter (DM) intake and milk yield were recorded daily, body weight was measured 3 to 5 times per week, and milk components were analyzed 2 d/wk. Individual DM intake was regressed on milk energy output, metabolic body weight, body energy gain, and fixed effects of parity, experiment, cohort (a group of cows that received treatments in the same sequence) nested within experiment, and diet nested within cohort and experiment, with the residual being RFI. High RFI cows ate more than expected and were deemed less efficient. Residual feed intake correlated negatively with digestibility of starch for both HS (r = ?0.31) and LS (r = ?0.23) diets, and with digestibilities of DM (r = ?0.30) and NDF (r = ?0.23) for LS diets but was not correlated with DM or NDF digestibility for HS diets. For each cohort within an experiment, cows were classified as high RFI (HRFI; >0.5 SD), medium RFI (MRFI; ±0.5 SD), and low RFI (LRFI; <?0.5 SD). Digestibility of DM was similar (~66%) among HRFI and LRFI for HS diets but greater for LRFI when fed LS diets (64 vs. 62%). For LS diets, digestibility of DM could account for up to 31% of the differences among HRFI and LRFI for apparent diet energy density, as determined from individual cow performance, indicating that digestibility explains some of the between-animal differences for the ability to convert gross energy into net energy. Some of the differences in digestibility between HRFI and LRFI were expected because cows with high RFI eat at a greater multiple of maintenance, and greater intake is associated with increased passage rate and digestibility depression. Based on these data, we conclude that a cow’s digestive ability explains none of the variation in RFI for cows eating high starch diets but 9 to 31% of the variation in RFI when cows are fed low starch diets. Perhaps differences in other metabolic processes, such as tissue turnover, heat production, or others related to maintenance, can account for more variation in RFI than digestibility.     

Differences in net fat oxidation,heat production,and liver mitochondrial DNA copy numbers between high and low feed-efficient dairy cows

Improving feed utilization efficiency in dairy cattle could have positive economic and environmental effects that would support the sustainability of the dairy industry. Identifying key differences in metabolism between high and low feed-efficient animals is vital to enhancing feed conversion efficiency. Therefore, our objectives were (1) to determine whether cows grouped by either high or low feed efficiency have measurable differences in net fat and carbohydrate metabolism that account for differences in heat production (HP), and if so, whether these differences also exists under conditions of feed withdrawal when the effect of feeding on HP is minimized, and (2) to determine whether the abundance of mitochondria in the liver can be related to the high or low feed-efficient groups. Ten dairy cows from a herd of 15 (parity = 2) were retrospectively grouped into either a high (H) or a low (L) feed-efficient group (n = 5 per group) based on weekly energy-corrected milk (ECM) divided by dry mater intake (DMI) from wk 4 through 30 of lactation. Livers were biopsied at wk ?4, 2, and 12, and blood was sampled weekly from wk ?3 to 12 relative to parturition. Blood was subset to be analyzed for the transition period (wk ?3 to 3) and from wk 4 to 12. In wk 5.70 ± 0.82 (mean ± SD) postpartum (PP), cows spent 2 d in respiration chambers (RC), in which CO₂, O₂, and CH₄ gases were measured every 6 min for 24 h. Fatty acid oxidation (FOX), carbohydrate oxidation (COX), metabolic respiratory quotient (RQ), and HP were calculated from gas measurements for 23 h. Cows were fed ad libitum (AD-LIB) on d 1 and had feed withdrawn (RES, restricted diet) on d 2. Additional blood samples were taken at the end of the AD-LIB and RES feeding periods in the RC. During wk 4 to 30 PP, H had greater DMI/kg of metabolic body weight (BW^0.75), ECM per kilogram of BW^0.75 yield, and ECM/DMI ratio, compared with L, but a lower body condition score between wk 4 and 12 PP. In the RC period, we detected no differences in BW, DMI, or milk yield between groups. We also detected no significant group or group by feeding period interactions for plasma metabolites except for Revised Quantitative Insulin Sensitivity Check Index, which tended to have a group by feeding period interaction. The H group had lower HP and HP per kilogram of BW^0.75 compared with L. Additionally, H had lower FOX and FOX per kilogram of BW^0.75 compared with L during the AD-LIB period. Methane, CH₄ per kilogram of BW^0.75, and CH₄ per kilogram of milk yield were lower in H compared with L, but, when adjusted for DMI, CH₄/DMI did not differ between groups, nor did HP/DMI. Relative mitochondrial DNA copy numbers in the liver were lower in the L than in the H group. These results suggest that lower feed efficiency in dairy cows may result from fewer mitochondria per liver cell as well as a greater whole-body HP, which likely partially results from higher net fat oxidation.     

Estimates of genetic parameters for feeding behavior traits and their associations with feed efficiency in Holstein cows

Residual feed intake (RFI) is commonly used to measure feed efficiency but individual intake recording systems are needed. Feeding behavior may be used as an indicator trait for feed efficiency using less expensive precision livestock farming technologies. Our goal was to estimate genetic parameters for feeding behavior and the genetic correlations with feed efficiency in Holstein cows. Data consisted of 75,877 daily feeding behavior records of 1,328 mid-lactation Holstein cows in 31 experiments conducted from 2009 to 2020 with an automated intake recording system. Feeding behavior traits included number of feeder visits per day, number of meals per day, duration of each feeder visit, duration of each meal, total duration of feeder visits, intake per visit, intake per meal [kg of dry matter (DM)], feeding rate per visit, and feeding rate per meal (kg of DM per min). The meal criterion was estimated as 26.4 min, which means that any pair of feeder visits separated by less than 26.4 min were considered part of the same meal. The statistical model included lactation and days in milk as fixed effects, and experiment-treatment, animal, and permanent environment as random effects. Genetic parameters for feeding behavior traits were estimated using daily records and weekly averages. Estimates of heritability for daily feeding behavior traits ranged from 0.09 ± 0.02 (number of meals; mean ± standard error) to 0.23 ± 0.03 (feeding rate per meal), with repeatability estimates ranging from 0.23 ± 0.01 (number of meals) to 0.52 ± 0.02 (number of feeder visits). Estimates of heritability for weekly averages of feeding behavior traits ranged from 0.19 ± 0.04 (number of meals) to 0.32 ± 0.04 (feeding rate per visit), with repeatability estimates ranging from 0.46 ± 0.02 (duration of each meal) to 0.62 ± 0.02 (feeding rate per visit and per meal). Most of the feeding behavior measures were strongly genetically correlated, showing that with more visits or meals per day, cows spend less time in each feeder visit or meal with lower intake per visit or meal. Weekly averages for feeding behavior traits were analyzed jointly with RFI and its components. Number of meals was genetically correlated with milk energy (0.48), metabolic body weight (?0.27), and RFI (0.19). Duration of each feeder visit and meal were genetically correlated with milk energy (0.43 and 0.44, respectively). Total duration of feeder visits per day was genetically correlated with DM intake (0.29), milk energy (0.62), metabolic body weight (?0.37), and RFI (0.20). Intake per visit and meal were genetically correlated with DM intake (0.63 and 0.87), milk energy (0.47 and 0.69), metabolic body weight (0.47 and 0.68), and RFI (0.31 and 0.65). Feeding rate was genetically correlated with DM intake (0.69), metabolic body weight (0.67), RFI (0.47), and milk energy (0.21). We conclude that measures of feeding behavior could be useful indicators of dairy cow feed efficiency, and individual cows that eat at a slower rate may be more feed efficient.     

Feeding behavior parameters and temporal patterns in mid-lactation Holstein cows across a range of residual feed intake values

Residual feed intake (RFI) is a measurement of the difference between actual and predicted feed intake when adjusted for energy sinks; more efficient cows eat less than predicted (low RFI) and inefficient cows eat more than predicted (high RFI). Data evaluating the relationship between RFI and feeding behaviors (FB) are limited in dairy cattle; therefore, the objective of this study was to determine daily and temporal FB in mid-lactation Holstein cows across a range of RFI values. Mid-lactation Holstein cows (n = 592 multiparous; 304 primiparous) were enrolled in 17 cohorts at 97 ± 26 d in milk (± standard deviation), and all cows within a cohort were fed a common diet using automated feeding bins. Cow RFI was calculated as the difference between predicted and observed dry matter intake (DMI) after accounting for parity, days in milk, milk energy, metabolic body weight and change, and experiment. The associations between RFI and FB at the level of meals and daily totals were evaluated using mixed models with the fixed effect of RFI and the random effects of cow and cohort. Daily temporal FB analyses were conducted using 2-h blocks and analyzed using mixed models with the fixed effects of RFI, time, RFI × time, and cohort, and the random effect of cow (cohort). There was a positive linear association between RFI and DMI in multiparous cows and a positive quadratic relationship in primiparous cows, where the rate of increase in DMI was less at higher RFI. Eating rate, DMI per meal, and size of the largest daily meal were positively associated with RFI. Daily temporal analysis of FB revealed an interaction between RFI and time for eating rate in multiparous and primiparous cows. The eating rate increased with greater RFI at 11 of 12 time points throughout the day, and eating rate differed across RFI between multiple time points. There tended to be an interaction between RFI and time for eating time and bin visits in multiparous cows but not primiparous cows. Overall, there was a time effect for all FB variables, where DMI, eating time and rate, and bin visits were greatest after the initial daily feeding at 1200 h, increased slightly after each milking, and reached a nadir at 0600 h (6 h before feeding). Considering the relationship between RFI and eating rate, additional efforts to determine cost-effective methods of quantifying eating rate in group-housed dairy cows is warranted. Further investigation is also warranted to determine if management strategies to alter FB, especially eating rate, can be effective in increasing feed efficiency in lactating dairy cattle.