Implications

Enteric methane production from dairy cows is a significant source of greenhouse gases emissions. A meta-analysis on calorimeter data describing methane emissions from Holstein-Friesian dairy cows was undertaken to examine if selecting for cow genetic merit (production efficiency) could be used as a mitigation tool for reduced enteric methane emissions. The results demonstrated that while high yielding cows produced more methane (g/day), cow genetic merit had no significant effect on methane emission as a proportion of feed intake (g/kg dry matter). Thus, feed intake appears to be the main driver of enteric methane emissions from dairy cattle.

Introduction

Atmospheric methane (CH₄) is one of the most potent and influential greenhouse gases. Globally, ruminant supply chains are estimated to produce 5.7 GT CO₂-eq to the atmosphere per annum, accounting for 80% of the livestock sector emissions (Opio et al., Reference Opio, Gerber, Mottet, Falcucci, Tempio, MacLeod, Vellinga, Henderson and Steinfeld2013). Consequently, there is increasing pressure to develop effective mitigation strategies to reduce CH₄ emissions from the livestock sector, especially enteric CH₄ emissions from ruminant livestock. During the last two decades, calorimeter data from research institutes has been used to develop a range of prediction models to facilitate an improved understanding of the effects of diet and animal factors on enteric CH₄ emissions (Mills et al., Reference Mills, Kebreab, Yates, Crompton, Cammell, Dhanoa, Agnew and France2003; Yan et al., Reference Yan, Mayne, Gordon, Porter, Agnew, Patterson, Ferris and Kilpatrick2010; Ellis et al., Reference Ellis, Dijkstra, France, Parsons, Edwards, Rasmussen, Kebreab and Banninkll2012). In addition, many nutritional strategies designed to reduce CH₄ emissions at an individual animal basis have been evaluated, including the use of dietary manipulation (e.g., improving forage quality, inclusion of concentrates, feed processing) and dietary additives (e.g., inhibitors, electron receptors, ionophores, plant bioactive compounds) (Hulshof et al., Reference Hulshof, Berndt, Gerrits, Dijkstra, van Zijderveld, Newbold and Perdok2012; Hristov et al., Reference Hristov, Oh, Firkins, Dijkstra, Kebreab, Waghorn, Makkar, Adesogan, Yang, Lee, Gerber, Henderson and Tricarico2013; Ramin and Huhtanen, Reference Ramin and Huhtanen2013). Although some of these ‘additive’ and ‘biotechnological’ approaches are promising, their long-term effects have not yet been extensively established.

Genetic improvement may offer an additional approach by which to reduce CH₄ emissions. For example, a number of recent studies have demonstrated that selection of cows with high genetic merit for milk yield normally results in an increase in feed intake and milk production, and a decrease in enteric CH₄ emissions per kg feed intake or milk yield, in comparison with cows of a relatively low genetic merit for milk yield (Chagunda et al., Reference Chagunda, Römer and Roberts2009; Bell et al., Reference Bell, Wall, Russell and Simm2010; Yan et al., Reference Yan, Mayne, Gordon, Porter, Agnew, Patterson, Ferris and Kilpatrick2010). This reduction in CH₄ emissions is likely to reflect a reduction in the proportion of consumed energy used for maintenance, the ability of higher genetic merit cows to mobilise body tissue for milk production (without an associated intake) combined with their ability to partition a greater proportion of consumed energy into milk rather than into body tissue (Veerkamp and Emmans, Reference Veerkamp and Emmans1995; Yan et al., Reference Yan, Mayne, Keady and Agnew2006). In the development of CH₄ emission inventory for a whole lactation, the effect of mobilisation of body tissue in early lactation would be offset by an additional intake in late lactation and the dry period for restoration of body condition. Similarly, beef cattle breeding programmes have been used to select cattle with a lower residual feed intake (RFI), which require a lower nutrient intake than expected for a given growth rate. There is evidence that cattle with lower RFI can have a 16% to 25% lower enteric CH₄ output per unit live weight gain (Herd et al., Reference Herd, Arthur, Hegarty and Archer2002; Hegarty et al., Reference Hegarty, Goopy, Herd and McCorkell2007). Therefore, the selection of cattle with high production efficiency is increasingly considered as a promising and cost-effective strategy to mitigate against enteric CH₄ emissions per unit of product. Nevertheless, it is unclear if selection for higher genetic merit for milk production and other functional traits has also led to the selection of cows with an inherent genetic capacity towards lower levels of methanogenesis, and if this could also be contributing to the lower CH₄ emission rate. There is, however, little information available within the literature on the relationship between cow genetic merit and enteric CH₄ emission rate.

At the Agri-Food and Biosciences Institute, over 1000 lactating dairy cows have been subject to respiration calorimeter measurements during the last 20 years to evaluate the effects of animal and dietary factors on energetic efficiencies and enteric CH₄ emission rate. The objectives of the present study were to use these data to develop a range of statistical models to investigate the relationship between cow genetic merit (for milk production and profitability) and the potential for enteric CH₄ emission rate.

Material and methods

Digestibility and calorimeter measurements

Nutrient digestibility, energy intake and output, and enteric CH₄ emissions used in the present study were measured in digestibility trials and by indirect open-circuit respiration calorimeter chambers. Before the commencement of nutrient utilisation measurements, all dairy cows were offered their experimental diets for at least 3 weeks in group-housed cubicle accommodation with free access to water. Afterwards, animals were restrained in individual stalls using a neck chain for between 5 to 8 days, with measurement of total feed intake and total collection of faeces and urine undertaken during the final 3 to 6 days. Animals were then housed in calorimeter chambers for 3 to 5 days with measurement of total gaseous exchange (CH₄, CO₂ and O₂) taking place during the final 2 to 4 days. All equipment, sampling procedures, analytical methods and calculations used in the calorimetric studies were described by Gordon et al. (Reference Gordon, Porter, Mayne, Unsworth and Kilpatrick1995) and calibration of the chambers by Yan et al. (Reference Yan, Agnew, Gordon and Porter2000). Energy corrected milk yield (ECMY) was calculated from measured milk energy output (E_l, MJ/day) divided by the calculated energy concentration (MJ/kg) of 1 kg of standard milk (concentrations of fat, protein and lactose=40, 32 and 48 g/kg, respectively). The energy content of 1 kg of standard milk was calculated using the equation given by Tyrrell and Reid (Reference Tyrrell and Reid1965; Equation (1)):

(1) $$\eqalignno{{\rm Energy}\ {\rm content}\ {\rm of}\ {\rm standard}\ {\rm milk}=\,&0.0{\rm 384}\,{\rm fat}{\plus}0.0{\rm 223}\,{\rm protein}\cr &{\plus}0.0{\rm 199}\,{\rm lactose }-{\rm }0.{\rm 1}0{\rm 8}\cr $$

where unit for energy content of standard milk is MJ/kg and for fat, protein and lactose is g/kg.

Results

The animal, diet and CH₄ emission data used in the present study are presented in Table 1. The dairy cows used in the present study were different in genetic merit with PIN ranging from −£30 to £63 and PLI from −£131 to £184. Reflecting the range in DM intake (7.4 to 25.0 kg/day) and ECMY (16.0 to 45.6 kg/day), there was a wide range in total enteric CH₄ emissions (138 to 598 g/day), CH₄ output per kg DM intake (13.8 to 33.5 g/kg) or ECMY (9.6 to 41.3 g/kg), and CH₄-E as a proportion of GE intake (0.041 to 0.095 MJ/MJ).

Table 1

Animal, diet and methane (CH₄) emission data used in the present study

DM=dry matter.

Within the PIN data set, there was a significant increase in DM intake, ME intake and ECMY with increasing PIN (P<0.001). Consequently, CH₄ emissions (g/day) also increased significantly with increasing PIN (P<0.001) (Table 2). However, there was no significant difference among the three sub-groups (P>0.05) in terms of CH₄ output as a proportion of DM intake, OM intake or ECMY, or CH₄-E as a proportion of GE intake or ME intake. Similarly, there was no significant difference (P>0.05) between PIN and CH₄ emission as a proportion of digestible DM intake or digestible OM intake, or CH₄-E as a proportion of DE intake (results not presented). Effects within the PLI subgroups were similar to those within PIN, except that the increases in DM intake, ME intake, ECMY and CH₄ emissions (g/day) between the low and medium PLI groups did not reach significance (P>0.05).

Table 2

Effect of cow genetic merit (profit index and profitable lifetime index: low, medium or high) on methane outputs of lactating Holstein-Friesian dairy cows

CH₄=methane emission; PIN=profit index; PLI=profitable lifetime index; CH₄-E=methane energy output; DM=dry matter; OM=organic matter; GE=gross energy; ME=metabolisable energy; ECMY=energy corrected milk yield.

^a,b,cWithin a row, means without a common superscript letter differ significantly (P<0.05).

Further evaluations of the effect of cow genetic merit were undertaken on the whole data set of PIN and PLI using linear mixed modelling technique. The results are presented in Table 3. No significant relationships were identified between PIN or PLI, and CH₄ emissions as a proportion of DM intake, OM intake or CH₄-E output as a proportion of GE intake or ME intake. The P values ranged from 0.585 to 0.931 for the PIN data set and 0.083 to 0.740 for the PLI data set. The corresponding R ² values were from 0.006 to 0.009 (PIN data set), and from 0.006 to 0.012 (PLI data set).

Table 3

Linear regressions between enteric methane emission rate and cow genetic merit –PIN PLI

CH₄=methane emission; PIN=profit index; PLI=profitable lifetime index; CH₄-E=methane energy output; DM=dry matter; OM=organic matter; GE=gross energy; ME=metabolisable energy.

^a Unit=g/kg for CH₄/DM intake and CH₄/OM intake; MJ/MJ for CH₄-E/GE intake and CH₄-E/ME intake.

Discussion

A number of experiments have been conducted within the United Kingdom to evaluate the effect of increasing cow genetic merit on energetic efficiency and enteric CH₄ emissions (Ferris et al., Reference Ferris, Gordon, Patterson, Mayne and Kilpatrick1999; Yan et al., Reference Yan, Mayne, Keady and Agnew2006; Bell et al., Reference Bell, Wall, Russell and Simm2010). These results demonstrated that in comparison with low genetic merit cows, high genetic merit cows had a lower enteric CH₄ emission per kg of DM intake and milk yield, and lower CH₄-E outputs as a proportion of GE intake. Similar results have also been reported with beef cattle, namely that increasing production efficiency reduces daily enteric CH₄ (L/kg^0.75) production rate (Nkrumah et al., Reference Nkrumah, Okine, Mathison, Schmid, Li, Basarab, Price, Wang and Moore2006) or CH₄ emissions (g/day) (Hegarty et al., Reference Hegarty, Goopy, Herd and McCorkell2007; Fitzsimons et al., Reference Fitzsimons, Kenny, Deighton, Fahey and McGee2013). In these two beef cattle experiments, the ‘high production efficiency’ animals were selected through a breeding programme designed to identify cattle with a low RFI value. Cattle with low RFI require less food than expected to achieve the same level of production. Therefore, the selection of dairy and beef cattle with high production efficiencies provides an effective tool to reduce enteric CH₄ emissions per unit of product (milk or meat).

Although a range of diet and animal factors (e.g., feeding level, animal productivity and forage proportion) have been observed to influence enteric CH₄ production, it is also possible that there is a physiological mechanism for lower CH₄ emissions with high genetic merit cattle. However, little information is available in the literature as to whether decreasing CH₄ emission rate with increasing genetic merit is as a result of higher feed intakes and improved quality of diets offered, or an inherent lower rumen methanogenesis potential, or both. The present study was designed to address this issue by applying a range of techniques, including linear mixed modelling and ANOVA, to a large data set of CH₄ emission and energy metabolism data measured in calorimeter chambers.

Within the present study the linear mixed modelling analysis found no significant relationship between cow genetic merit (PIN or PLI) and CH₄ emission as a proportion of feed intake or energy intake. The ANOVA also revealed that there was no significant difference in CH₄ emission as a proportion of feed intake or energy intake among the low, medium and high genetic merit (PIN or PLI) sub-groups. Bell et al. (Reference Bell, Wall, Simm and Russell2011) in a study involving 139 individual dairy cows compared lifetime CH₄ emissions as a proportion of ECMY and found that the lifetime values for CH₄/ECMY decreased from 55.4 to 31.4 g/kg when DM intake increased from 13.8 to 18.4 kg/day. Chagunda et al. (Reference Chagunda, Römer and Roberts2009) examined enteric CH₄ emissions from lactating dairy cows and found a significant difference in CH₄ emissions as a proportion of milk yield in high genetic merit dairy cows offered either low or high forage diets (11.8 v. 15.7 g/kg, respectively). Similarly, the low genetic merit cows offered a low forage diet had a significantly lower CH₄ emission per kg milk yield than when offered a high forage diet (12.9 v. 17.3 g/kg, respectively). Thus, these results indicate that the lower proportional CH₄ emission rate observed in previous production studies with high yielding cows, compared with low/medium yielding cows, are most likely due to their higher feed intakes and better quality diets offered.

A number of recent studies have assessed the potential association between enteric CH₄ emissions and microbial ecology of ruminal methanogens. Using the culture-independent methods, Zhou et al. (Reference Zhou, Hernandez-Sanabria and Guan2009, Reference Zhou, Hernandez-Sanabria and Guan2010) reported that while there was no significant difference in the total population of methanogens between cattle with different feed efficiencies, their rumen methanogenesis capacity was highly related to changes in feed intake and dietary composition. Jones et al. (Reference Jones, Phillips, Naylor and Mercer2011) found that changes in methanogenic communities in relation to RFI were dependent on feeding type and diet quality. Zhou et al. (Reference Zhou, Hernandez-Sanabria and Guan2010) reported predominant methanogenic species obtained from the low energy density diet shifted to a community containing more diverse predominant species with the high energy density diet. Therefore, the results obtained in the present study and in previous publications indicated that enteric CH₄ emission rate in cattle is mainly driven by feed intake and dietary nutrient compositions within the different studies.

The present data set was collated from 32 respiration calorimeter experiments undertaken at this Institute over an 18-year period. These studies required experimental animals to be housed in individual chambers, while CH₄ emissions, feed intake and milk yields were measured over a very short period (<1 week) at various stages of the lactation. Thus, the feed intake and milk yield data obtained in this type of study may not fully represent the milk production potential of cows over a full lactation. There is evidence indicating that daily CH₄ emission rates (g/day) of dairy cows varied considerably during lactation, but followed the variation curves of feed intake and milk production (Garnsworthy et al., Reference Garnsworthy, Craigon, Hernandez-Medrano and Saunders2012). Daily CH₄ emission rates also vary among cows on commercial farms (Bell et al., Reference Bell, Potterton, Craigon, Saunders, Wilcox, Hunter, Goodman and Garnsworthy2014). Therefore, further studies designed specially to compare the production capacity, rumen ecology and methanogenesis in dairy cows with different genetic merits (PIN or PLI) may be required to validate the results obtained in the present study.

Conclusions

The present meta-analysis study demonstrated that when using calorimetric data from Holstein-Friesian dairy cows at different stages of lactation cow genetic merit (PI and PLI) had no significant effect on enteric CH₄ emissions per kg feed intake or per MJ energy intake. The enteric CH₄ emission of dairy cattle appears to be related to feed intake and dietary nutrient composition. Breeding programmes that select dairy cows with high production efficiencies can reduce feed intake per kg milk yield, and thus reduce enteric CH₄ emissions per unit of feed intake or energy intake.