Does the diurnal pattern of enteric methane emissions from dairy cows change over time?

Diet manipulation and genetic selection are two important mitigation strategies for reducing enteric methane (CH₄) emissions from ruminant livestock. The aim of this study was to assess whether the diurnal pattern of CH₄ emissions from individual dairy cows changes over time when cows are fed on diets varying in forage composition. Emissions of CH₄ from 36 cows were measured during milking in an automatic (robotic) milking station in three consecutive feeding periods, for a total of 84 days. In Periods 1 and 2, the 36 cows were fed a high-forage partial mixed ration (PMR) containing 75% forage, with either a high grass silage or high maize silage content. In Period 3, cows were fed a commercial PMR containing 69% forage. Cows were offered PMR ad libitum plus concentrates during milking and CH₄ emitted by individual cows was sampled during 8662 milkings. A linear mixed model was used to assess differences among cows, feeding periods and time of day. Considerable variation was observed among cows in daily mean and diurnal patterns of CH₄ emissions. On average, cows produced less CH₄ when fed on the commercial PMR in feeding Period 3 than when the same cows were fed on high-forage diets in feeding Periods 1 and 2. The average diurnal pattern for CH₄ emissions did not significantly change between feeding periods and as lactation progressed. Emissions of CH₄ were positively associated with dry matter (DM) intake and forage DM intake. It is concluded that if the management of feed allocation remains constant then the diurnal pattern of CH₄ emissions from dairy cows will not necessarily alter over time. A change in diet composition may bring about an increase or decrease in absolute emissions over a 24-h period without significantly changing the diurnal pattern unless management of feed allocation changes. These findings are important for CH₄ monitoring techniques that involve taking measurements over short periods within a day rather than complete 24-h observations.     

Feeding behavior improves prediction of dairy cow voluntary feed intake but cannot serve as the sole indicator

Low-cost feeding-behavior sensors will soon be available for commercial use in dairy farms. The aim of this study was to develop a feed intake model for the individual dairy cow that includes feeding behavior. In a research farm, the individual cows’ voluntary feed intake and feeding behavior were monitored at every meal. A feed intake model was developed based on data that exist in commercial modern farms: ‘BW,’ ‘milk yield’ and ‘days in milking’ parameters were applied in this study. At the individual cow level, eating velocity seemed to be correlated with feed intake (R²=0.93 to 0.94). The eating velocity coefficient varied among individuals, ranging from 150 to 230 g/min per cow. The contribution of feeding behavior (0.28) to the dry matter intake (DMI) model was higher than the contribution of BW (0.20), similar to the contribution of fat-corrected milk (FCM)/BW (0.29) and not as large as the contribution of FCM (0.49). Incorporating feeding behavior into the DMI model improved its accuracy by 1.3 (38%) kg/cow per day. The model is ready to be implemented in commercial farms as soon as companies introduce low-cost feeding-behavior sensors on commercial level.     

Effects of dehydrated lucerne and soya bean meal on milk production and composition,nutrient digestion,and methane and nitrogen losses in dairy cows receiving two different forages

Dehydrated lucerne is used as a protein source in dairy cow rations, but little is known about the effects of lucerne on greenhouse gas production by animals. Eight Holstein dairy cows (average weight: 582 kg) were used in a replicated 4×4 Latin square design. They received diets based on either maize silage (M) or grass silage (G) (45% of diet on dry matter (DM) basis), with either soya bean meal (15% of diet DM) completed with beet pulp (15% of diet DM) (SP) or dehydrated lucerne (L) (30% of diet DM) as protein sources; MSP, ML, GSP and GL diets were calculated to meet energy requirements for milk production by dairy cows and degradable protein for rumen microbes. Dry matter intake (DMI) did not differ among diets (18.0 kg/day DMI); milk production was higher with SP diets than with L diets (26.0 v. 24.1 kg/day), but milk production did not vary with forage type. Milk fatty-acid (FA) composition was modified by both forage and protein sources: L and G diets resulted in less saturated FA, less linoleic acid, more trans-monounsaturated FA, and more linolenic acid than SP and M diets, respectively. Enteric methane (CH₄) production, measured by the SF₆ tracer method, was higher for G diets than for M diets, but did not differ with protein source. The same effects were observed when CH₄ was expressed per kg milk. Minor effects of diets on rumen fermentation pattern were observed. Manure CH₄ emissions estimated from faecal organic matter were negatively related to diet digestibility and were thus higher for L than SP diets, and higher for M than G diets; the resulting difference in total CH₄ production was small. Owing to diet formulation constraints, N intake was higher for SP than for L diets; interaction between forage type and protein source was significant for N intake. The same statistical effects were found for N in milk. Faecal and urinary N losses were determined from total faeces and urine collection. Faecal N output was lower for M than for G diets but did not differ between protein sources. Urinary N output did not differ between forage types, but was lower for cows fed L diets than for cows fed SP diets, potentially resulting in lower ammonia emissions with L diets. Replacing soya bean meal plus beet pulp with dehydrated lucerne did not change CH₄ production, but resulted in more N in faeces and less N in urine.     

Herd-level versus animal-level variation in methane emission prediction in grazing dairy cattle

In response to the increased concern over agriculture’s contribution to greenhouse gas (GHG) emissions, more detailed assessments of current methane emissions and their variation, within and across individual dairy farms and cattle, are of interest for research and policy development. This assessment will provide insights into possible changes needed to reduce GHG emissions, the nature and direction of these changes, ways to influence farmer behavior and areas to maximize the adoption of emerging mitigation technologies. The objectives of this study were to (1) quantify the variation in enteric fermentation methane emissions within and among seasonal calving dairy farms with the majority of nutritional requirements met through grazed pasture; (2) use this variation to assess the potential of new individual animal emission monitoring technologies and their impact on mitigation policy. We used a large database of cow performance records for milk production and survival from 2 398 herds in New Zealand, and simulation to account for unobserved variation in feed efficiency and methane emissions per unit of feed. Results showed an average of 120 ± 31.4 kg predicted methane (CH₄) per cow per year after accounting for replacement costs, ranging 8.9–323 kg CH₄/cow per year. Whereas milk production, survival and predicted live weight were reasonably effective at predicting both individual and herd average levels of per cow feed intake, substantial within animal variation in emissions per unit of feed reduced the ability of these variables to predict variation in per animal methane output. Animal-level measurement technologies predicting only feed intake but not emissions per unit of feed are unlikely to be effective for advancing national policy goals of reducing dairy farming enteric methane output. This is because farmers seek to profitably utilize all farm feed resources available, so improvements in feed efficiency will not result in the reduction in feed utilization required to reduce methane emissions. At a herd level, average per cow milk production and live weight could form the basis of assigning a farm-level point of obligation for methane emissions. In conclusion, a comprehensive national database infrastructure that was tightly linked to animal identification and movement systems, and captured live weight data from existing farm-level recording systems, would be required to make this effective. Additional policy and incentivization mechanisms would still be required to encourage farmer uptake of mitigation interventions, such as novel feed supplements or vaccines that reduce methane emissions per unit of feed.     

Are dairy cows with a more reactive temperament less efficient in energetic metabolism and do they produce more enteric methane?

It remains unknown whether dairy cows with more reactive temperament produce more enteric methane (CH₄) and are less bioenergetically efficient than the calmer ones. The objectives of this study were (a) to evaluate the relationship between cattle temperament assessed by traditionally used tests with energetic metabolism and enteric CH₄ emissions by crossbred dairy cows; (b) to assess how cows’ restlessness in respiration chambers affects energetic metabolism and enteric CH₄ emissions. Temperament indicators were evaluated for 28 primiparous F1 Holstein-Gyr cows tested singly in the handling corral (entrance time, crush score, flight speed, and flight distance) and during milking (steps, kicks, defecation, rumination, and kick the milking cluster off). Cows’ behaviors within respiration chambers were also recorded for each individual kept singly. Digestibility and calorimetry trials were performed to obtain energy partitioning and CH₄ measures. Cows with more reactive temperament in milking (the ones that kicked the milking cluster off more frequently) spent 25.24% less net energy on lactation (P = 0.04) and emitted 36.77% more enteric CH₄/kg of milk (P = 0.03). Furthermore, cows that showed a higher frequency of rumination at milking parlor allocated 57.93% more net energy for milk production (P < 0.01), spent 50.00% more metabolizable energy for milk production (P < 0.01) and 37.10% less CH₄/kg of milk (P = 0.04). Regarding the handling temperament, most reactive cows according to flight speed, lost 29.16% less energy as urine (P = 0.05) and tended to have 14.30% more enteric CH₄ production (P = 0.08), as well as cows with a lower entrance time (most reactive) that also lost 13.29% more energy as enteric CH₄ (P = 0.04). Temperament and restless behavior of Holstein-Gyr cows were related to metabolic efficiency and enteric CH₄ emissions. Cows’ reactivity and rumination in the milking parlor, in addition to flight speed and entrance time in the squeeze chute during handling in the corral, could be useful measures to predict animals more prone to metabolic inefficiency, which could negatively affect the sustainability of dairy systems.     

Potential use of milk mid-infrared spectra to predict individual methane emission of dairy cows

This study investigates the feasibility to predict individual methane (CH₄) emissions from dairy cows using milk mid-infrared (MIR) spectra. To have a large variability of milk composition, two experiments were conducted on 11 lactating Holstein cows (two primiparous and nine multiparous). The first experiment aimed to induce a large variation in CH₄ emission by feeding two different diets: the first one was mainly composed of fresh grass and sugar beet pulp and the second one of maize silage and hay. The second experiment consisted of grass and corn silage with cracked corn, soybean meal and dried pulp. For each milking period, the milk yields were recorded twice daily and a milk sample of 50 ml was collected from each cow and analyzed by MIR spectrometry. Individual CH₄ emissions were measured daily using the sulfur hexafluoride method during a 7-day period. CH₄ daily emissions ranged from 10.2 to 47.1 g CH₄/kg of milk. The spectral data were transformed to represent an average daily milk spectrum (AMS), which was related to the recorded daily CH₄ data. By assuming a delay before the production of fermentation products in the rumen and their use to produce milk components, five different calculations were used: AMS at days 0, 0.5, 1, 1.5 and 2 compared with the CH₄ measurement. The equations were built using Partial Least Squares regression. From the calculated R²_cv, it appears that the accuracy of CH₄ prediction by MIR changed in function of the milking days. In our experimental conditions, the AMS at day 1.5 compared with the measure of CH₄ emissions gave the best results. The R² and s.e. of the cross-validation were equal to 0.79 and 5.14 g of CH₄/kg of milk. The multiple correlation analysis performed in this study showed the existence of a close relationship between milk fatty acid (FA) profile and CH₄ emission at day 1.5. The lower R² (R² = 0.76) obtained between FA profile and CH₄ emission compared with the one corresponding to the obtained calibration (R²_c = 0.87) shows the interest to apply directly the developed CH₄ equation instead of the use of correlations between FA and CH₄. In conclusion, our preliminary results suggest the feasibility of direct CH₄ prediction from milk MIR spectra. Additional research has the potential to improve the calibrations even further. This alternative method could be useful to predict the individual CH₄ emissions at farm level or at the regional scale and it also could be used to identify low-CH₄-emitting cows.     

Impact of diet management and composition on vitamin B12 concentration in milk of Holstein cows

As vitamin B₁₂ is only synthesized by bacteria, ruminant products, especially dairy products, are excellent sources of this vitamin. This study aims to identify if diet and cow characteristics could affect vitamin B₁₂ concentration in milk of dairy cows. Information on 1484 first, 1093 second and 1763 third and greater parity Holstein cows in 100 herds was collected during three consecutive milkings. During the first morning milking, all dietary ingredients given to cows were sampled and quantities offered were recorded throughout the day. Nutrient composition of ingredients was obtained by wet chemistry to reconstitute nutrient composition of the ration. Milk samples were taken with in-line milk meters during the evening milking of the 1^st day and the morning milking of the 2nd day and were analyzed for vitamin B₁₂ concentration. Milk yields were recorded and milk components were separately analyzed for each milking. Daily vitamin B₁₂ concentration in milk was obtained using morning and evening vitamin B₁₂ concentrations weighted with respective milk yield, then divided by daily yield. To decrease the number of interdependent variables to include in the multivariable model, a principal component analysis was carried out. Daily milk concentration of vitamin B₁₂ averaged 3809±80 pg/ml, 4178±79 pg/ml and 4399±77 pg/ml for first, second and third, and greater lactation cows. Out of 11 principal components, six were significantly related to daily milk concentration of vitamin B₁₂ when entered in the multivariable model. Results suggested that vitamin B₁₂ concentration in milk was positively related to percentage of fiber and negatively related to starch as well as energy of the diet. Negative relationships were noted between vitamin B₁₂ concentration in milk and milk yield as well as milk lactose concentration and positive relationships were observed between vitamin B₁₂ concentration in milk and milk fat as well as protein concentrations. The percentages of chopped mixed silage and commercial energy supplement in the diet as well as cow BW were positively related to vitamin B₁₂ in milk and percentages of baled mixed silage, corn and commercial protein supplement in the ration were negatively related to vitamin B₁₂ concentration in milk. The pseudo-R² of the model was low (52%) suggesting that diet and cow characteristics have moderate impact on vitamin B₁₂ concentration in milk. Moreover, when entering solely the principal component related to milk production in the model, the pseudo-R² was 46%. In conclusion, it suggests that studied diet characteristics have a marginal impact on vitamin B₁₂ concentration in milk variation.     

Is there a relationship between genetic merit and enteric methane emission rate of lactating Holstein-Friesian dairy cows?

The present study was undertaken to examine the effect of cow genetic merit on enteric methane (CH₄) emission rate. The study used a data set from 32 respiration calorimeter studies undertaken at this Institute between 1992 and 2010, with all studies involving lactating Holstein-Friesian dairy cows. Cow genetic merit was defined as either profit index (PIN) or profitable lifetime index (PLI), with these two United Kingdom genetic indexes expressing the expected improvement in profit associated with an individual cow, compared with the population average. While PIN is based solely on milk production, PLI includes milk production and a number of other functional traits including health, fertility and longevity. The data set had a large range in PIN (n=736 records, −£30 to +£63) and PLI (n=548 records, −£131 to +£184), days in milk (18 to 354), energy corrected milk yield (16.0 to 45.6 kg/day) and CH₄ emission (138 to 598 g/day). The effect of cow genetic merit (PIN or PLI) was evaluated using ANOVA and linear mixed modelling techniques after removing the effects of a number of animal and diet factors. The ANOVA was undertaken by dividing each data set of PIN and PLI into three sub-groups (PIN:<£3, £3 to £15 and >£15, PLI:<£23, £23 to £67 and >£67) with these being categorised as low, medium and high genetic merit. Within the PIN and PLI data sets there was no significant differences among the three sub-groups in terms of CH₄ emission per kg feed intake or per kg energy corrected milk yield, or CH₄ energy (CH₄-E) output as a proportion of energy intake. Linear regression using the whole PIN and PLI data sets also demonstrated that there was no significant relationship between either PIN or PLI, and CH₄ emission per kg of feed intake or CH₄-E output as a proportion of energy intake. These results indicate that cow genetic merit (PIN or PLI) has little effect on enteric CH₄ emissions as a proportion of feed intake. Instead enteric CH₄ production may mainly relate to total feed intake and dietary nutrient composition.     

Non-invasive individual methane measurement in dairy cows

Attempts to lower the environmental footprint of milk production needs a sound understanding of the genetic and nutritional basis of methane (CH₄) emissions from the dairy production systems. This in turn requires accurate and reliable techniques for the measurement of CH₄ output from individual cows. Many of the available measurement techniques so far are either slow, expensive, labor intensive and are unsuitable for large-scale individual animal measurements. The main objectives of this study were to examine and validate a non-invasive individual cow CH₄ measurement system that is based on photoacoustic IR spectroscopy (PAS) technique implemented in a portable gas analysis equipment (F10), referred to as PAS-F10 method and to estimate the magnitude of between-animal variations in CH₄ output traits. Data were collected from 115 Nordic Red cows of the Minkiö experimental dairy farm, at the Natural Resources Institute Finland (Luke). Records on continuous daily measurements of CH₄, milk yield, feed intake and BW measurements over 2 years period were compiled for data analysis. The daily CH₄ output was calculated using carbon dioxide as a tracer method. Estimates from the non-invasive PAS-F10 technique were then tested against open-circuit indirect respiration calorimetric chamber measurements and against estimates from other widely used prediction models. Concordance analysis was used to establish agreement between the chamber and PAS-F10 methods. A linear mixed model was used for the analysis of the large continuous data. The daily CH₄ output of cows was 555 l/day and ranged from 330 to 800 l/day. Dry matter intake, level of milk production, lactation stage and diurnal variation had significant effects on daily CH₄ output. Estimates of the daily CH₄ output from PAS-F10 technique compared relatively well with the other techniques. The concordance correlation coefficient between combined weekly CH₄ output estimates of PAS-F10 and chamber was 0.84 with lower and upper confidence limits of 0.65 and 0.93, respectively. Similarly, when chamber CH₄ measurements were predicted from PAS-F10 measurements, the mean of two separate weekly PAS-F10 measurements gave the lowest prediction error variance than either of the separate weekly PAS-F10 measurements alone. This suggests that every other week PAS-F10 measurements when combined would improve the estimation of CH₄ output with PAS-F10 technique. The repeatability of daily CH₄ output from PAS-F10 technique ranged from 0.40 to 0.46 indicating that some between-animal variation exist in CH₄ output traits.     

The influence of grass silage-to-maize silage ratio and concentrate composition on methane emissions,performance and milk composition of dairy cows

It is well-established that altering the proportion of starch and fibre in ruminant diets can alter ruminal and post-ruminal digestion, although quantitative evidence that this reduces enteric methane (CH₄) production in dairy cattle is lacking. The objective of this study was to examine the effect of varying grass-to-maize silage ratio (70 : 30 and 30 : 70 DM basis), offered ad libitum, with either a concentrate that was high in starch or fibre, on CH₄ production, intake, performance and milk composition of dairy cows. A total of 20 cows were allocated to one of the four experimental diets in a two-by-two factorial design run as a Latin square with each period lasting 28 days. Measurements were conducted during the final 7 days of each period. Cows offered the high maize silage ration had a higher dry matter intake (DMI), milk yield, milk energy output and lower CH₄ emissions when expressed per kg DMI and per unit of ingested gross energy, but there was no difference in total CH₄ production. Several of the milk long-chain fatty acids (FA) were affected by forage treatment with the most notable being an increase in 18:0, 18:1 c9, 18:2 c9 c12 and total mono unsaturated FA, observed in cows offered the higher inclusion of maize silage, and an increase in 18:3 c9 c12 c15 when offered the higher grass silage ration. Varying the composition of the concentrate had no effect on DMI or milk production; however, when the high-starch concentrate was fed, milk protein concentration and milk FAs, 10:0, 14:1, 15:0, 16:1, increased and 18:0 decreased. Interactions were observed for milk fat concentration, being lower in cows offered high-grass silage and high-fibre concentrates compared with the high-starch concentrate, and FA 17:0, which was the highest in milk from cows fed the high-grass silage diet supplemented with the high-starch concentrate. In conclusion, increasing the proportion of maize silage in the diets of dairy cows increased intake and performance, and reduced CH₄ production, but only when expressed on a DM or energy intake basis, whereas starch-to-fibre ratio in the concentrate had little effect on performance or CH₄ production.     

Diet supplementation with cinnamon oil,cinnamaldehyde, or monensin does not reduce enteric methane production of dairy cows

This study was conducted to evaluate the effect of dietary addition of cinnamon oil (CIN), cinnamaldehyde (CDH), or monensin (MON) on enteric methane (CH₄) emission in dairy cows. Eight multiparous lactating Holstein cows fitted with ruminal cannulas were used in a replicated 4×4 Latin square design (28-day periods). Cows were fed (ad libitum) a total mixed ration ((TMR); 60 : 40 forage : concentrate ratio, on a dry matter (DM) basis) not supplemented (CTL), or supplemented with CIN (50 mg/kg DM intake), CDH (50 mg/kg DM intake), or monensin (24 mg/kg of DM intake). Dry matter intake (DMI), nutrient digestibility, N retention, and milk performance were measured over 6 consecutive days. Ruminal degradability of the basal diet (with no additive) was assessed using in sacco incubations (0, 2, 4, 8, 16, 24, 48, 72 and 96 h). Ruminal fermentation characteristics (pH, volatile fatty acids (VFA), and ammonia (NH₃)) and protozoa were determined over 2 days. Enteric CH₄ emissions were measured over 6 consecutive days using the sulfur hexafluoride (SF₆) tracer gas technique. Adding CIN, CDH or MON to the diet had no effects on DMI, N retention, in sacco ruminal degradation and nutrient digestibility of the diet. Ruminal fermentation characteristics and protozoa numbers were not modified by including the feed additives in the diet. Enteric CH₄ emission and CH₄ energy losses averaged 491 g/day and 6.59% of gross energy intake, respectively, and were not affected by adding CIN, CDH or MON to the diet. Results of this study indicate that CIN, CDH and MON are not viable CH₄ mitigation strategies in dairy cows.     

Effects of nitrogen fertilisation rate and maturity of grass silage on methane emission by lactating dairy cows

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

Individual variation and repeatability of methane production from dairy cows estimated by the CO2 method in automatic milking system

The objectives of this study were to investigate the individual variation, repeatability and correlation of methane (CH₄) production from dairy cows measured during 2 different years. A total of 21 dairy cows with an average BW of 619±14.2 kg and average milk production of 29.1±6.5 kg/day (mean±s.d.) were used in the 1^st year. During the 2^nd year, the same cows were used with an average BW of 640±8.0 kg and average milk production of 33.4±6.0 kg/day (mean±s.d.). The cows were housed in a loose housing system fitted with an automatic milking system (AMS). A total mixed ration was fed to the cows ad libitum in both years. In addition, they were offered concentrate in the AMS based on their daily milk yield. The CH₄ and CO₂ production levels of the cows were analysed using a Gasmet DX-4030. The estimated dry matter intake (EDMI) was 19.8±0.96 and 23.1±0.78 (mean±s.d.), and the energy-corrected milk (ECM) production was 30.8±8.03 and 33.7±5.25 kg/day (mean±s.d.) during the 1^st and 2^nd year, respectively. The EDMI and ECM had a significant influence (P<0.001) on the CH₄ (l/day) yield during both years. The daily CH₄ (l/day) production was significantly higher (P<0.05) during the 2^nd year compared with the 1^st year. The EDMI (described by the ECM) appeared to be the key factor in the variation of CH₄ release. A correlation (r=0.54) of CH₄ production was observed between the years. The CH₄ (l/day) production was strongly correlated (r=0.70) between the 2 years with an adjusted ECM production (30 kg/day). The diurnal variation of CH₄ (l/h) production showed significantly lower (P<0.05) emission during the night (0000 to 0800 h). The between-cows variation of CH₄ (l/day, l/kg EDMI and l/kg ECM) was lower compared with the within-cow variation for the 1^st and 2^nd years. The repeatability of CH₄ production (l/day) was 0.51 between 2 years. In conclusion, a higher EDMI (kg/day) followed by a higher ECM (kg/day) showed a higher CH₄ production (l/day) in the 2^nd year. The variations of CH₄ (l/day) among the cows were lower than the within-cow variations. The CH₄ (l/day) production was highly repeatable and, with an adjusted ECM production, was correlated between the years.     

Changes in in vitro gas and methane production from rumen fluid from dairy cows during adaptation to feed additives in vivo

The adaptation of dairy cows to methane (CH₄)-mitigating feed additives was evaluated using the in vitro gas production (GP) technique. Nine rumen-fistulated lactating Holstein cows were grouped into three blocks and within blocks randomly assigned to one of three experimental diets: Control (CON; no feed additive), Agolin Ruminant^R (AR; 0.05 g/kg dry matter (DM)) or lauric acid (LA; 30 g/kg DM). Total mixed rations composed of maize silage, grass silage and concentrate were fed in a 40 : 30 : 30 ratio on DM basis. Rumen fluid was collected from each cow at days −4, 1, 4, 8, 15 and 22 relative to the introduction of the additives in the diets. On each of these days, a 48-h GP experiment was performed in which rumen fluid from each individual donor cow was incubated with each of the three substrates that reflected the treatment diets offered to the cows. DM intake was on average 19.8, 20.1 and 16.2 kg/day with an average fat- and protein-corrected milk production of 30.7, 31.7 and 26.2 kg/day with diet CON, AR and LA, respectively. In general, feed additives in the donor cow diet had a larger effect on gas and CH₄ production than the same additives in the incubation substrate. Incubation substrate affected asymptotic GP, half-time of asymptotic CH₄ production, total volatile fatty acid (VFA) concentration, molar proportions of propionate and butyrate and degradation of organic matter (OMD), but did not affect CH₄ production. No substrate×day interactions were observed. A significant diet×day interaction was observed for in vitro gas and CH₄ production, total VFA concentration, molar proportions of VFA and OMD. From day 4 onwards, the LA diet persistently reduced gas and CH₄ production, total VFA concentration, acetate molar proportion and OMD, and increased propionate molar proportion. In vitro CH₄ production was reduced by the AR diet on day 8, but not on days 15 and 22. In line with these findings, the molar proportion of propionate in fermentation fluid was greater, and that of acetate smaller, for the AR diet than for the CON diet on day 8, but not on days 15 and 22. Overall, the data indicate a short-term effect of AR on CH₄ production, whereas the CH₄-mitigating effect of LA persisted.     

Differential effects of oilseed supplements on methane production and milk fatty acid concentrations in dairy cows

It is known that supplementing dairy cow diets with full-fat oilseeds can be used as a strategy to mitigate methane emissions, through their action on rumen fermentation. However, direct comparisons of the effect of different oil sources are very few, as are studies implementing supplementation levels that reflect what is commonly fed on commercial farms. The objective was to investigate the effect of feeding different forms of supplemental plant oils on both methane emissions and milk fatty acid (FA) profile. Four multiparous, Holstein-Friesian cows in mid-lactation were randomly allocated to one of four treatment diets in a 4×4 Latin square design with 28-day periods. Diets were fed as a total mixed ration with a 50 : 50 forage : concentrate ratio (dry matter (DM) basis) with the forage consisting of 75 : 25 maize silage : grass silage (DM). Dietary treatments were a control diet containing no supplemental fat, and three treatment diets containing extruded linseed (EL), calcium salts of palm and linseed oil (CPLO) or milled rapeseed (MR) formulated to provide each cow with an estimated 500 g additional oil/day (22 g oil/kg diet DM). Dry matter intake (DMI), milk yield, milk composition and methane production were measured at the end of each experimental period when cows were housed in respiration chambers for 4 days. There was no effect of treatment diet on DMI or milk protein or lactose concentration, but oilseed-based supplements increased milk yield compared with the control diet and milk fat concentration relative to control was reduced by 4 g/kg by supplemental EL. Feeding CPLO reduced methane production, and both linseed-based supplements decreased methane yield (by 1.8 l/kg DMI) and intensity (by 2.7 l/kg milk yield) compared with the control diet, but feeding MR had no effect on methane emission. All the fat supplements decreased milk total saturated fatty acid (SFA) concentration compared with the control, and SFA were replaced with mainly cis-9 18:1 but also trans FA (and in the case of EL and CPLO there were increases in polyunsaturated FA concentration). Supplementing dairy cow diets with these oilseed-based preparations affected milk FA profile and increased milk yield. However, only the linseed-based supplements reduced methane production, yield or intensity, whereas feeding MR had no effect.     

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.     

Low degradable protein supply to increase nitrogen efficiency in lactating dairy cows and reduce environmental impacts at barn level

Generally, <30% of dairy cattle’s nitrogen intake is retained in milk. Large amounts of nitrogen are excreted in manure, especially in urine, with damaging impacts on the environment. This study explores the effect of lowering dietary degradable nitrogen supplies – while maintaining metabolisable protein – on dairy cows’ performance, nitrogen use efficiency and gas emissions (NH₃, N₂O, CH₄) at barn level with tied animals. Two dietary N concentrations (CP: 12% DM for LowN; 18% DM for HighN) were offered to two groups of three lactating dairy cows in a split-plot design over four periods of 2 weeks. Diets were formulated to provide similar metabolisable protein supply, with degradable N either in deficit or in excess (PDIN of 84 and 114 g/kg DM for LowN and HighN, respectively). Cows ingested 0.8 kg DM/day less on the LowN diet, which was also 2.5% less digestible. Milk yield and composition were not significantly affected. N exported in milk was 5% lower (LowN: 129 g N/day; HighN: 136 g N/day; P<0.001) but milk protein yield was not significantly affected (LowN: 801 g/day; HighN: 823 g/day; P=0.10). Cows logically ingested less nitrogen on the LowN diet (LowN: 415 g N/day; HighN: 626 g N/day; P<0.001) resulting in a higher N use efficiency (N milk/N intake; LowN: 0.31; HighN: 0.22; P<0.001). N excreted in urine was almost four times lower on the LowN diet (LowN: 65 g N/day; HighN: 243 g N/day; P<0.001) while urinary urea N concentration was eightfold lower (LowN: 4.6 g/l; HighN: 22.9 g/l; P<0.001). Ammonia emission (expressed in g/h in order to remove periods of the day with potential interferences with volatile molecules from feed) was also lower on the LowN diet (LowN: 1.03 g/h per cow; HighN: 1.25 g/h per cow; P<0.05). Greenhouse gas emissions (N₂O and CH₄) at barn level were not significantly affected by the amount of dietary N. Offering low amounts of degradable protein with suitable metabolisable protein amounts to cattle improved nitrogen use efficiency and lowered ammonia emissions at barn level. This strategy would, however, need to be validated for longer periods, other housing systems (free stall barns) and at farm level including all stages of manure management.     

Estimating the impact of clinical mastitis in dairy cows on greenhouse gas emissions using a dynamic stochastic simulation model: a case study

The increasing attention for global warming is likely to contribute to the introduction of policies or other incentives to reduce greenhouse gas (GHG) emissions related to livestock production, including dairy. The dairy sector is an important contributor to GHG emissions. Clinical mastitis (CM), an intramammary infection, results in reduced milk production and fertility, increases culling and mortality of cows and, therefore, has a negative impact on the efficiency (output/input) of milk production. This may increase GHG emissions per unit of product. Our objective was to estimate the impact of CM in dairy cows on GHG emissions of milk production for the Dutch situation. A dynamic stochastic simulation model was developed to simulate the dynamics and losses of CM for individual lactations. Cows receive a parity (1 to 5+), a milk production and a calving interval (CI). Based on the parity, cows have a risk of CM, with a maximum of three cases in a lactation. Pathogens causing CM were classified as gram-positive bacteria, gram-negative bacteria, or other. Based on the parity and pathogen combinations, cows had a reduced milk production, discarded milk, prolonged CI and a risk of removal (culling and mortality) that reduce productivity of dairy cows and therefore increase GHG emissions per unit of product. Using life cycle assessment, emissions of GHGs were estimated from cradle to farm gate for processes along the milk production chain that are affected by CM. Processes included were feed production, enteric fermentation, and manure management. Emissions of GHGs were expressed as kg CO₂ equivalents per ton of fat-and-protein-corrected milk (kg CO₂e/t FPCM). Emissions of cows with CM increased on average by 57.5 (6.2%) kg CO₂e/t FPCM compared with cows without CM. This increase was caused by removal (39%), discarded milk (38%), reduced milk production (17%) and prolonged CI (6%). The GHG emissions increased by 48 kg CO₂e/t FPCM for cows with one case of CM, by 69 kg CO₂e/t FPCM for cows with two cases of CM and by 92 kg CO₂e/t FPCM for cows with three cases of CM compared with cows without CM. Preventing CM can be an effective strategy for farmers to reduce GHG emissions and can contribute to sustainable development of the dairy sector, because this also can improve the income of farmers and the welfare of cows. The impact of CM on GHG emissions, however, will vary between farms due to environmental conditions and management practices.     

Real-time evaluation of milk quality as reflected by clotting parameters of individual cow's milk during the milking session,between day-to-day and during lactation

Real-time analysis of milk coagulation properties as performed by the AfiLab™ milk spectrometer introduces new opportunities for the dairy industry. The study evaluated the performance of the AfiLab™ in a milking parlor of a commercial farm to provide real-time analysis of milk-clotting parameters –Afi-CF for cheese manufacture and determine its repeatability in time for individual cows. The AfiLab™ in a parlor, equipped with two parallel milk lines, enables to divert the milk on-line into two bulk milk tanks (A and B). Three commercial dairy herds of 220 to 320 Israeli Holstein cows producing ∼11 500 l during 305 days were selected for the study. The Afi-CF repeatability during time was found significant (P < 0.001) for cows. The statistic model succeeded in explaining 83.5% of the variance between Afi-CF and cows, and no significant variance was found between the mean weekly repeated recordings. Days in milk and log somatic cell count (SCC) had no significant effect. Fat, protein and lactose significantly affected Afi-CF and the empirical van Slyke equation. Real-time simulations were performed for different cutoff levels of coagulation properties where the milk of high Afi-CF cutoff value was channeled to tank A and the lower into tank B. The simulations showed that milk coagulation properties of an individual cow are not uniform, as most cows contributed milk to both tanks. Proportions of the individual cow's milk in each tank depended on the selected Afi-CF cutoff. The assessment of the major causative factors of a cow producing low-quality milk for cheese production was evaluated for the group that produced the low 10% quality milk. The largest number of cows in those groups at the three farms was found to be cows with post-intramammary infection with Escherichia coli and subclinical infections with streptococci or coagulase-negative staphylococci (∼30%), although the SCC of these cows was not significantly different. Early time in lactation together with high milk yield >50 l/day, and late in lactation together with low milk yield<15 l/day and estrous (0 to 5 days) were also important influencing factors for low-quality milk. However, ∼50% of the tested variables did not explain any of the factors responsible for the cow producing milk in the low – 10% Afi-CF.     

Farm-level emission intensities of smallholder cattle (Bos indicus; B. indicus–B. taurus crosses) production systems in highlands and semi-arid regions

Ruminants are central to the economic and nutritional life of much of sub-Saharan Africa, but cattle are now blamed for having a disproportionately large negative environmental impact through emissions of greenhouse gas (GHG). However, the mechanism underlying excessive emissions occurring only on some farms is imperfectly understood. Reliable estimates of emissions themselves are frequently lacking due to a paucity of reliable data. Employing individual animal records obtained at regular farm visits, this study quantified farm-level emission intensities (EIs) of greenhouse gases of smallholder farms in three counties in Western Kenya. CP was chosen as the functional unit to capture the outputs of both milk and meat. The results showed that milk is responsible for 80–85% of total CP output. Farm EI ranged widely from 20 to >1 000 kg CO₂-eq/kg CP. Median EIs were 60 (Nandi), 71 (Bomet), and 90 (Nyando) kg CO₂-eq/kg. Although median EIs referenced to milk alone (2.3 kg CO₂-eq/kg milk) were almost twice that reported for Europe, up to 50% of farms had EIs comparable to the mean Pan-European EIs. Enteric methane (CH₄) contributed >95% of emissions and manure ～4%, with negligible emissions attributed to inputs to the production system. Collecting data from individual animals on smallholder farms enabled the demonstration of extremely heterogeneous EI status among similar geographical spaces and provides clear indicators on how low EI status may be achieved in these environments. Contrary to common belief, our data show that industrial-style intensification is not required to achieve low EI. Enteric CH₄ production overwhelmingly drives farm emissions in these systems and as this is strongly collinear with nutrition and intake, an effort will be required to achieve an “efficient frontier” between feed intake, productivity, and GHG emissions.