Does increasing milk yield per cow reduce greenhouse gas emissions? A system approach

Milk yield per cow has continuously increased in many countries over the last few decades. In addition to potential economic advantages, this is often considered an important strategy to decrease greenhouse gas (GHG) emissions per kg of milk produced. However, it should be considered that milk and beef production systems are closely interlinked, as fattening of surplus calves from dairy farming and culled dairy cows play an important role in beef production in many countries. The main objective of this study was to quantify the effect of increasing milk yield per cow on GHG emissions and on other side effects. Two scenarios were modelled: constant milk production at the farm level and decreasing beef production (as co-product; Scenario 1); and both milk and beef production kept constant by compensating the decline in beef production with beef from suckler cow production (Scenario 2). Model calculations considered two types of production unit (PU): dairy cow PU and suckler cow PU. A dairy cow PU comprises not only milk output from the dairy cow, but also beef output from culled cows and the fattening system for surplus calves. The modelled dairy cow PU differed in milk yield per cow per year (6000, 8000 and 10 000 kg) and breed. Scenario 1 resulted in lower GHG emissions with increasing milk yield per cow. However, when milk and beef outputs were kept constant (Scenario 2), GHG emissions remained approximately constant with increasing milk yield from 6000 to 8000 kg/cow per year, whereas further increases in milk yield (10 000 kg milk/cow per year) resulted in slightly higher (8%) total GHG emissions. Within Scenario 2, two different allocation methods to handle co-products (surplus calves and beef from culled cows) from dairy cow production were evaluated. Results showed that using the 'economic allocation method', GHG emissions per kg milk decreased with increasing milk yield per cow per year, from 1.06 kg CO2 equivalents (CO2eq) to 0.89 kg CO2eq for the 6000 and 10 000 kg yielding dairy cow, respectively. However, emissions per kg of beef increased from 10.75 kg CO2eq to 16.24 kg CO2eq due to the inclusion of suckler cows. This study shows that the environmental impact (GHG emissions) of increasing milk yield per cow in dairy farming differs, depending upon the considered system boundaries, handling and value of co-products and the assumed ratio of milk to beef demand to be satisfied.     

Trends in greenhouse gas emissions from consumption and production of animal food products – implications for long-term climate targets

To analyse trends in greenhouse gas (GHG) emissions from production and consumption of animal products in Sweden, life cycle emissions were calculated for the average production of pork, chicken meat, beef, dairy and eggs in 1990 and 2005. The calculated average emissions were used together with food consumption statistics and literature data on imported products to estimate trends in per capita emissions from animal food consumption. Total life cycle emissions from the Swedish livestock production were around 8.5 Mt carbon dioxide equivalents (CO₂e) in 1990 and emissions decreased to 7.3 Mt CO₂e in 2005 (14% reduction). Around two-thirds of the emission cut was explained by more efficient production (less GHG emission per product unit) and one-third was due to a reduced animal production. The average GHG emissions per product unit until the farm-gate were reduced by 20% for dairy, 15% for pork and 23% for chicken meat, unchanged for eggs and increased by 10% for beef. A larger share of the average beef was produced from suckler cows in cow–calf systems in 2005 due to the decreasing dairy cow herd, which explains the increased emissions for the average beef in 2005. The overall emission cuts from the livestock sector were a result of several measures taken in farm production, for example increased milk yield per cow, lowered use of synthetic nitrogen fertilisers in grasslands, reduced losses of ammonia from manure and a switch to biofuels for heating in chicken houses. In contrast to production, total GHG emissions from the Swedish consumption of animal products increased by around 22% between 1990 and 2005. This was explained by strong growth in meat consumption based mainly on imports, where growth in beef consumption especially was responsible for most emission increase over the 15-year period. Swedish GHG emissions caused by consumption of animal products reached around 1.1 t CO₂e per capita in 2005. The emission cuts necessary for meeting a global temperature-increase target of 2° might imply a severe constraint on the long-term global consumption of animal food. Due to the relatively limited potential for reducing food-related emissions by higher productivity and technological means, structural changes in food consumption towards less emission-intensive food might be required for meeting the 2° target.     

Climate mitigation by dairy intensification depends on intensive use of spared grassland

Milk and beef production cause 9% of global greenhouse gas (GHG) emissions. Previous life cycle assessment (LCA) studies have shown that dairy intensification reduces the carbon footprint of milk by increasing animal productivity and feed conversion efficiency. None of these studies simultaneously evaluated indirect GHG effects incurred via teleconnections with expansion of feed crop production and replacement suckler‐beef production. We applied consequential LCA to incorporate these effects into GHG mitigation calculations for intensification scenarios among grazing‐based dairy farms in an industrialized country (UK), in which milk production shifts from average to intensive farm typologies, involving higher milk yields per cow and more maize and concentrate feed in cattle diets. Attributional LCA indicated a reduction of up to 0.10 kg CO₂e kg^?1 milk following intensification, reflecting improved feed conversion efficiency. However, consequential LCA indicated that land use change associated with increased demand for maize and concentrate feed, plus additional suckler‐beef production to replace reduced dairy‐beef output, significantly increased GHG emissions following intensification. International displacement of replacement suckler‐beef production to the “global beef frontier” in Brazil resulted in small GHG savings for the UK GHG inventory, but contributed to a net increase in international GHG emissions equivalent to 0.63 kg CO₂e kg^?1 milk. Use of spared dairy grassland for intensive beef production can lead to net GHG mitigation by replacing extensive beef production, enabling afforestation on larger areas of lower quality grassland, or by avoiding expansion of international (Brazilian) beef production. We recommend that LCA boundaries are expanded when evaluating livestock intensification pathways, to avoid potentially misleading conclusions being drawn from “snapshot” carbon footprints. We conclude that dairy intensification in industrialized countries can lead to significant international carbon leakage, and only achieves GHG mitigation when spared dairy grassland is used to intensify beef production, freeing up larger areas for afforestation.     

Keeping profitable cows in the herd: A lifetime cost-benefit assessment to support culling decisions

Increasing the productive lifespan of dairy cows is important to achieve a sustainable dairy industry, but making strategic culling decisions based on cow profitability is challenging for farmers. The objective of this study was to carry out a lifetime cost-benefit analysis based on production and health records and to explore different culling decisions among farmers. The cost-benefit analysis was conducted for 22 747 dairy cows across 114 herds in Quebec, Canada for which feed costs and the occurrence of diseases were reported. Costs and revenues related to productive lifespan were compared among cohorts of cows that left their respective herd at the end of their last completed lactation or stayed for a complete additional lactation. Hierarchical clustering analysis was carried out based on costs and revenues to explore different culling decisions among farmers. Our results showed that the knowledge of lifetime cumulative costs and revenues was of great importance to identify low-profitable cows at an earlier lactation, while only focusing on current lactation costs and revenues can lead to an erroneous assessment of profitability. While culling decisions were mostly based on current lactation costs and revenues and disregarded the occurrence of costly events on previous lactations, there was variation among farmers as we identified three different culling decision clusters. Monitoring cumulative costs and revenues would help farmers to identify low-profitable cows at an earlier lactation and make the decision to increase herd productive lifespan and farm profitability by keeping the most profitable cows.     

Animal board invited review: Specialising and intensifying cattle production for better efficiency and less global warming: contrasting results for milk and meat co-production at different scales

Cattle are the world’s largest consumers of plant biomass. Digestion of this biomass by ruminants generates high methane emissions that affect global warming. In the last decades, the specialisation of cattle breeds and livestock systems towards either milk or meat has increased the milk production of dairy cows and the carcass weight of slaughtered cattle. At the animal level and farm level, improved animal performance decreases feed use and greenhouse gas emissions per kg of milk or carcass weight, mainly through a dilution of maintenance requirements per unit of product. However, increasing milk production per dairy cow reduces meat production from the dairy sector, as there are fewer dairy cows. More beef cows are then required if one wants to maintain the same meat production level at country scale. Meat produced from the dairy herd has a better feed efficiency (less feed required per kg of carcass weight) and emits less methane than the meat produced by the cow-calf systems, because the intake of lactating cows is largely for milk production and marginally for meat, whereas the intake of beef cows is entirely for meat. Consequently, the benefits of breed specialisation assessed at the animal level and farm level may not hold when milk and meat productions are considered together. Any change in the milk-to-meat production ratio at the country level affects the numbers of beef cows required to produce meat. At the world scale, a broad diversity in feed efficiencies of cattle products is observed. Where both productions of milk per dairy cow and meat per head of cattle are low, the relationship between milk and meat efficiencies is positive. Improved management practices (feed, reproduction, health) increase the feed efficiency of both products. Where milk and meat productivities are high, a trade-off between feed efficiencies of milk and meat can be observed in relation to the share of meat produced in either the dairy sector or the beef sector. As a result, in developing countries, increasing productivities of both dairy and beef cattle herds will increase milk and meat efficiencies, reduce land use and decrease methane emissions. In other regions of the world, increasing meat production from young animals produced by dairy cows is probably a better option to reduce feed use for an unchanged milk-to-meat production ratio.     

Modelling impacts of performance on the probability of reproducing,and thereby on productive lifespan,allow prediction of lifetime efficiency in dairy cows

Reproductive success is a key component of lifetime efficiency – which is the ratio of energy in milk (MJ) to energy intake (MJ) over the lifespan, of cows. At the animal level, breeding and feeding management can substantially impact milk yield, body condition and energy balance of cows, which are known as major contributors to reproductive failure in dairy cattle. This study extended an existing lifetime performance model to incorporate the impacts that performance changes due to changing breeding and feeding strategies have on the probability of reproducing and thereby on the productive lifespan, and thus allow the prediction of a cow’s lifetime efficiency. The model is dynamic and stochastic, with an individual cow being the unit modelled and one day being the unit of time. To evaluate the model, data from a French study including Holstein and Normande cows fed high-concentrate diets and data from a Scottish study including Holstein cows selected for high and average genetic merit for fat plus protein that were fed high- v. low-concentrate diets were used. Generally, the model consistently simulated productive and reproductive performance of various genotypes of cows across feeding systems. In the French data, the model adequately simulated the reproductive performance of Holsteins but significantly under-predicted that of Normande cows. In the Scottish data, conception to first service was comparably simulated, whereas interval traits were slightly under-predicted. Selection for greater milk production impaired the reproductive performance and lifespan but not lifetime efficiency. The definition of lifetime efficiency used in this model did not include associated costs or herd-level effects. Further works should include such economic indicators to allow more accurate simulation of lifetime profitability in different production scenarios.     

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.     

The impact of a leptin gene SNP on beef calf weaning weights

Prior research indicates that a SNP at position 305 of exon 2 in the leptin gene affects milk production in dairy cows. Dairy cows with at least one copy of the T allele have been shown to have higher milk production than CC cows. If that effect carries over to beef breeds, it is reasonable to expect that CT and TT beef cows will wean heavier calves than CC beef cows. We tested this hypothesis for a herd of mixed breed cows using anova. Results indicated that both crossbred CT and TT beef cows wean significantly heavier beef calves than CC crossbred beef cows. A lack of observations generally hinders detection of significance in other breeds. However, two other comparisons were found to be significant. The results suggest further investigation into the link between leptin genotype and calf weaning weights. Aside from interest to animal scientists, these results have the potential to alter mating and replacement selection decisions by cow-calf producers, given the importance of weaning weights on profitability.     

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.     

Invited review: Improving feed efficiency in dairy production: challenges and possibilities

Despite substantial advances in milk production efficiency of dairy cattle over the last 50 years, rising feed costs remain a significant threat to producer profitability. There also is a greater emphasis being placed on reducing the negative impacts of dairy production on the environment; thus means to lower greenhouse gas (GHG) emissions and nutrient losses to the environment associated with cattle production are being sought. Improving feed efficiency among dairy cattle herds offers an opportunity to address both of these issues for the dairy industry. However, the best means to assess feed efficiency and make genetic progress in efficiency-related traits among lactating cows without negatively impacting other economically important traits is not entirely obvious. In this review, multiple measurements of feed efficiency for lactating cows are described, as well as the heritability of the traits and their genetic and phenotypic correlations with other production traits. The measure of feed efficiency, residual feed intake is discussed in detail in terms of the benefits for its selection, how it could be assessed in large commercial populations, as well as biological mechanisms contributing to its variation among cows, as it has become a commonly used method to estimate efficiency in the recent scientific literature.     

Reducing methane on-farm by feeding diets high in fat may not always reduce life cycle greenhouse gas emissions

Purpose

To consider whether feed supplements that reduce methane emissions from dairy cows result in a net reduction in greenhouse gas (GHG) intensity when productivity changes and emissions associated with extra manufacturing and management are included.

Methods

A life cycle assessment was undertaken using a model farm based on dairy farms in Victoria, Australia. The system boundary included the creation of farm inputs and on-farm activities up to the farm gate where the functional unit was 1 L of fat and protein corrected milk (FPCM). Electricity and diesel (scaled per cow), and fertiliser inputs (scaled on farm size) to the model farm were based on average data from a survey of farms. Fertiliser applied to crops was calculated per area of crop. Animal characteristics were based on available data from farms and literature. Three methane-reducing diets (containing brewers grain, hominy or whole cotton seed) and a control diet (cereal grain) were modelled as being fed during summer, with the control diet being fed for the remainder of the year in all cases.

Results and discussion

Greenhouse gas intensity (kg CO₂-eq/L FPCM) was lower than the control diet when the hominy (97 % compared with control) and brewers grain (98 %) diets were used but increased when the whole cottonseed diet was used (104 %). On-farm GHG emissions (kg CO₂-eq) were lower than the control diet when any of the methane-reducing diets were used (98 to 99.5 % of emissions when control diet fed). Diesel use in production and transport of feed supplements accounted for a large portion (63 to 93 %) of their GHG intensity (kg CO₂-eq/t dry matter). Adjusting fertiliser application, changing transport method, changing transport fuel, and using nitrification inhibitors all had little effect on GHG emissions or GHG intensity.

Conclusions

Although feeding strategies that reduce methane emissions from dairy cows can lower the GHG emissions up to the farm gate, they may not result in lower GHG intensities (g CO₂-eq/L FPCM) when pre-farm emissions are included. Both transport distance and the effect of the feed on milk production have important impacts on the outcomes.     

Production,partial cash flows and greenhouse gas emissions of simulated dairy herds with extended lactations

The transition period is the most critical period in the lactation cycle of dairy cows. Extended lactations reduce the frequency of transition periods, the number of calves and the related labour for farmers. This study aimed to assess the impact of 2 and 4 months extended lactations on milk yield and net partial cash flow (NPCF) at herd level, and on greenhouse gas (GHG) emissions per unit of fat- and protein-corrected milk (FPCM), using a stochastic simulation model. The model simulated individual lactations for 100 herds of 100 cows with a baseline lactation length (BL), and for 100 herds with lactations extended by 2 or 4 months for all cows (All+2 and All+4), or for heifers only (H+2 and H+4). Baseline lactation length herds produced 887 t (SD: 13) milk/year. The NPCF, based on revenues for milk, surplus calves and culled cows, and costs for feed, artificial insemination, calving management and rearing of youngstock, was k€174 (SD: 4)/BL herd per year. Extended lactations reduced milk yield of the herd by 4.1% for All+2, 6.9% for All+4, 1.1% for H+2 and 2.2% for H+4, and reduced the NPCF per herd per year by k€7 for All+2, k€12 for All+4, k€2 for H+2 and k€4 for H+4 compared with BL herds. Extended lactations increased GHG emissions in CO₂-equivalents per t FPCM by 1.0% for All+2, by 1.7% for All+4, by 0.2% for H+2 and by 0.4% for H+4, but this could be compensated by an increase in lifespan of dairy cows. Subsequently, production level and lactation persistency were increased to assess the importance of these aspects for the impact of extended lactations. The increase in production level and lactation persistency increased milk production of BL herds by 30%. Moreover, reductions in milk yield for All+2 and All+4 compared with BL herds were only 0.7% and 1.1% per year, and milk yield in H+2 and H+4 herds was similar to BL herds. The resulting NPCF was equal to BL for All+2 and All+4 and increased by k€1 for H+2 and H+4 due to lower costs for insemination and calving management. Moreover, GHG emissions per t FPCM were equal to BL herds or reduced (0% to −0.3%) when lactations were extended. We concluded that, depending on lactation persistency, extending lactations of dairy cows can have a positive or negative impact on the NPCF and GHG emissions of milk production.     

Impact of including growth,carcass and feed efficiency traits in the breeding goal for combined milk and beef production systems

Improving feed efficiency in dairy cattle could result in more profitable and environmentally sustainable dairy production through lowering feed costs and emissions from dairy farming. In addition, beef production based on dairy herds generates fewer greenhouse gas emissions per unit of meat output than beef production from suckler cow systems. Different scenarios were used to assess the profitability of adding traits, excluded from the current selection index for Finnish Ayrshire, to the breeding goal for combined dairy and beef production systems. The additional breeding goal traits were growth traits (average daily gain of animals in the fattening and rearing periods), carcass traits (fat covering, fleshiness and dressing percentage), mature live weight (LW) of cows and residual feed intake (RFI) traits. A breeding scheme was modeled for Finnish Ayrshire under the current market situation in Finland using the deterministic simulation software ZPLAN+. With the economic values derived for the current production system, the inclusion of growth and carcass traits, while preventing LW increase generated the highest improvement in the discounted profit of the breeding program (3.7%), followed by the scenario where all additional traits were included simultaneously (5.1%). The use of a selection index that included growth and carcass traits excluding LW, increased the profit (0.8%), but reduced the benefits resulted from breeding for beef traits together with LW. A moderate decrease in the profit of the breeding program was obtained when adding only LW to the breeding goal (−3.1%), whereas, adding only RFI traits to the breeding goal resulted in a minor increase in the profit (1.4%). Including beef traits with LW in the breeding goal showed to be the most potential option to improve the profitability of the combined dairy and beef production systems and would also enable a higher rate of self-sufficiency in beef. When considering feed efficiency related traits, the inclusion of LW traits in the breeding goal that includes growth and carcass traits could be more profitable than the inclusion of RFI, because the marginal costs of measuring LW can be expected to be lower than for RFI and it is readily available for selection. In addition, before RFI can be implemented as a breeding objective, the genetic correlations between RFI and other breeding goal traits estimated for the studied population as well as information on the most suitable indicator traits for RFI are needed to assess more carefully the consequences of selecting for RFI.     

Livestock greenhouse gas emissions and mitigation potential in Europe

The livestock sector contributes considerably to global greenhouse gas emissions (GHG). Here, for the year 2007 we examined GHG emissions in the EU27 livestock sector and estimated GHG emissions from production and consumption of livestock products; including imports, exports and wastage. We also reviewed available mitigation options and estimated their potential. The focus of this review is on the beef and dairy sector since these contribute 60% of all livestock production emissions. Particular attention is paid to the role of land use and land use change (LULUC) and carbon sequestration in grasslands. GHG emissions of all livestock products amount to between 630 and 863 Mt CO₂e, or 12–17% of total EU27 GHG emissions in 2007. The highest emissions aside from production, originate from LULUC, followed by emissions from wasted food. The total GHG mitigation potential from the livestock sector in Europe is between 101 and 377 Mt CO₂e equivalent to between 12 and 61% of total EU27 livestock sector emissions in 2007. A reduction in food waste and consumption of livestock products linked with reduced production, are the most effective mitigation options, and if encouraged, would also deliver environmental and human health benefits. Production of beef and dairy on grassland, as opposed to intensive grain fed production, can be associated with a reduction in GHG emissions depending on actual LULUC emissions. This could be promoted on rough grazing land where appropriate.     

A methodology framework for weighting genetic traits that impact greenhouse gas emission intensities in selection indexes

A methodological framework was presented for deriving weightings to be applied in selection indexes to account for the impact genetic change in traits will have on greenhouse gas emissions intensities (EIs). Although the emission component of the breeding goal was defined as the ratio of total emissions relative to a weighted combination of farm outputs, the resulting trait-weighting factors can be applied as linear weightings in a way that augments any existing breeding objective before consideration of EI. Calculus was used to define the parameters and assumptions required to link each trait change to the expected changes in EI for an animal production system. Four key components were identified. The potential impact of the trait on relative numbers of emitting animals per breeding female first has a direct effect on emission output but, second, also has a dilution effect from the extra output associated with the extra animals. Third, each genetic trait can potentially change the amount of emissions generated per animal and, finally, the potential impact of the trait on product output is accounted for. Emission intensity weightings derived from this equation require further modifications to integrate them into an existing breeding objective. These include accounting for different timing and frequency of trait expressions as well as a weighting factor to determine the degree of selection emphasis that is diverted away from improving farm profitability in order to achieve gains in EI. The methodology was demonstrated using a simple application to dairy cattle breeding in Ireland to quantify gains in EI reduction from existing genetic trends in milk production as well as in fertility and survival traits. Most gains were identified as coming through the dilution effect of genetic increases in milk protein per cow, although gains from genetic improvements in survival by reducing emissions from herd replacements were also significant. Emission intensities in the Irish dairy industry were estimated to be reduced by ~5% in the last 10 years because of genetic trends in production, fertility and survival traits, and a further 15% reduction was projected over the next 15 years because of an observed acceleration of genetic trends.     

A review of the causes of poor fertility in high milk producing dairy cows

Fertility in dairy cows has declined over the past five decades as milk production per cow has increased. Many hypotheses have been proposed to explain this including issues of genetics, physiology, nutrition and management, and these factors have been investigated at the animal, organ and cellular level at critical time points of the productive life of dairy cows. This paper reviews the physiological events and their causes and consequences affecting fertility in dairy cows and summarises these in a downloadable poster. We consider the following points to have the greatest negative impact on fertility and that they need to be prioritised in efforts to ameliorate the problem (others have been included in the review). Firstly, minimise negative energy balance and resolve any infection of the post partum uterus. Secondly, expression and detection of oestrus followed by insemination with high quality semen (day 0). Thirdly, ovulation and fertilisation of a high quality oocyte (day 1). Fourthly, an early increase in progesterone secretion from the corpus luteum (days 3-7). Fifthly, the uterine endometrium must produce an early and appropriate environment to stimulate embryo development (days 6-13). This leads to sixthly, a large embryo producing adequate quantities of interferon tau (days 14-18) that alters uterine prostaglandin secretion and signals maternal recognition of pregnancy (days 16-18). Future strategies to improve dairy cow fertility are needed for the benefit of the dairy industry and for cow welfare and should be based upon an integrative approach of these events.     

Evaluation of production efficiencies at pasture of lactating suckler cows of diverse genetic merit and replacement strategy

Feed costs account for the largest proportion of direct cost within suckler beef production systems. By identifying the cow type with enhanced capability of converting grazed herbage to beef output across lactations, suckler cow systems would become more efficient and sustainable. The objective of this study was to estimate grass DM intake (GDMI) and production efficiency among lactating suckler cows of diverse genetic merit for the national Irish maternal index (Replacement Index) which includes cow efficiency components such as milk yield and feed intake. Data from 131 cows of diverse genetic merit within the Replacement Index, across two different replacement strategies (suckler or dairy sourced), were available over two grazing seasons. Milk yield, GDMI, cow live weight (BW) and body condition score (BCS) were recorded during early, mid and late-lactation, with subsequent measures of production efficiency extrapolated. Genetic merit had no significant effect on any variables investigated, with the exception of low genetic merit (LOW) cows being 22 kg heavier in BW than high genetic merit (HIGH) cows (P < 0.05). Beef cows were 55 kg heavier in BW (P < 0.001), had a 0.31 greater BCS (P < 0.05) and 0.30 Unité Fourragère Lait (UFL) greater energy requirement for maintenance compared to dairy sourced beef × dairy crossbred (BDX) cows (P < 0.001). The BDX had 0.8 kg greater GDMI, produced 1.8 kg more milk (P < 0.001), had a 0.8 UFL greater energy requirement for lactation and produced weanlings that were 17 kg heavier in BW than beef cows (P < 0.05). Subsequent efficiency variables of milk per 100 kg BW (P < 0.001), milk per kg GDMI (P < 0.001) and GDMI per 100 kg BW (P < 0.001) were more favourable for BDX. The correlations examined showed GDMI had moderate positive correlations (P < 0.001) with intake per 100 kg BW, net energy intake per kg milk yield, RFI and intake per 100 kg calf weaning weight but was weakly negatively correlated to milk yield per kg GDMI (P < 0.001). No difference was observed across genetic merit for beef cows for any of the traits investigated. Results from the current study showed that, while contrasting replacement strategies had an effect on GDMI and production efficiency, no main effect was observed on cows diverse in genetic merit for Replacement Index. Nonetheless, utilising genetic indexes in the suckler herd is an important resource for selecting breeding females for the national herd and phenotypic performance generated from this study can be included in future genetic evaluations to improve reliability of genetic values.     

Global environmental costs of China's thirst for milk

China has an ever‐increasing thirst for milk, with a predicted 3.2‐fold increase in demand by 2050 compared to the production level in 2010. What are the environmental implications of meeting this demand, and what is the preferred pathway? We addressed these questions by using a nexus approach, to examine the interdependencies of increasing milk consumption in China by 2050 and its global impacts, under different scenarios of domestic milk production and importation. Meeting China's milk demand in a business as usual scenario will increase global dairy‐related (China and the leading milk exporting regions) greenhouse gas (GHG) emissions by 35% (from 565 to 764 Tg CO_2eq) and land use for dairy feed production by 32% (from 84 to 111 million ha) compared to 2010, while reactive nitrogen losses from the dairy sector will increase by 48% (from 3.6 to 5.4 Tg nitrogen). Producing all additional milk in China with current technology will greatly increase animal feed import; from 1.9 to 8.5 Tg for concentrates and from 1.0 to 6.2 Tg for forage (alfalfa). In addition, it will increase domestic dairy related GHG emissions by 2.2 times compared to 2010 levels. Importing the extra milk will transfer the environmental burden from China to milk exporting countries; current dairy exporting countries may be unable to produce all additional milk due to physical limitations or environmental preferences/legislation. For example, the farmland area for cattle‐feed production in New Zealand would have to increase by more than 57% (1.3 million ha) and that in Europe by more than 39% (15 million ha), while GHG emissions and nitrogen losses would increase roughly proportionally with the increase of farmland in both regions. We propose that a more sustainable dairy future will rely on high milk demanding regions (such as China) improving their domestic milk and feed production efficiencies up to the level of leading milk producing countries. This will decrease the global dairy related GHG emissions and land use by 12% (90 Tg CO_2eq reduction) and 30% (34 million ha land reduction) compared to the business as usual scenario, respectively. However, this still represents an increase in total GHG emissions of 19% whereas land use will decrease by 8% when compared with 2010 levels, respectively.     

Estimating the economic impact of subclinical ketosis in dairy cattle using a dynamic stochastic simulation model

The objective of this study was to estimate the economic impact of subclinical ketosis (SCK) in dairy cows. This metabolic disorder occurs in the period around calving and is associated with an increased risk of other diseases. Therefore, SCK affects farm productivity and profitability. Estimating the economic impact of SCK may make farmers more aware of this problem, and can improve their decision-making regarding interventions to reduce SCK. We developed a dynamic stochastic simulation model that enables estimating the economic impact of SCK and related diseases (i.e. mastitis, metritis, displaced abomasum, lameness and clinical ketosis) occurring during the first 30 days after calving. This model, which was applied to a typical Dutch dairy herd, groups cows according to their parity (1 to 5+), and simulates the dynamics of SCK and related diseases, and milk production per cow during one lactation. The economic impact of SCK and related diseases resulted from a reduced milk production, discarded milk, treatment costs, costs from a prolonged calving interval and removal (culling or dying) of cows. The total costs of SCK were €130 per case per year, with a range between €39 and €348 (5 to 95 percentiles). The total costs of SCK per case per year, moreover, increased from €83 per year in parity 1 to €175 in parity 3. Most cows with SCK, however, had SCK only (61%), and costs were €58 per case per year. Total costs of SCK per case per year resulted for 36% from a prolonged calving interval, 24% from reduced milk production, 19% from treatment, 14% from discarded milk and 6% from removal. Results of the sensitivity analysis showed that the disease incidence, removal risk, relations of SCK with other diseases and prices of milk resulted in a high variation of costs of SCK. The costs of SCK, therefore, might differ per farm because of farm-specific circumstances. Improving data collection on the incidence of SCK and related diseases, and on consequences of diseases can further improve economic estimations.