Selective breeding as a mitigation tool for methane emissions from dairy cattle

Effects of live yeast on milk yield, feed efficiency, methane emissions and fertility of high-yielding dairy cows

Live yeast (Saccharomyces cerevisiae) products have the potential to increase milk yield of dairy cows in early lactation by improving rumen fermentation. Greater milk yields, however, are sometimes associated with poorer reproductive performance. This study aimed to assess the effect of a live yeast supplement on milk yield, methane emissions and reproduction indicators in high-yielding dairy cows. Fifty Holstein cows were paired according to month of calving, parity and predicted milk yield, and allocated at random to either a Control diet or a diet containing live Yeast (Actisaf® Sc 47, 1 × 1010 cfu/g, Phileo by Lesaffre) supplying 1 × 1011 cfu/cow per day (10 g). Diets were fed to cows from 7 to 128 days in milk. Live yeast resulted in higher yields of milk (50.1 vs 47.5 kg/day), energy-corrected milk (ECM; 50.5 vs 47.7 kg/day), fat-corrected milk (49.2 vs 46.3 kg/day) and milk fat (1 945 vs 1 823 g/day), compared with Control. There was no effect of treatment on DM intake (DMI), so cows fed on Yeast had greater feed efficiency (2.11 vs 1.98 kg ECM/kg DMI). Enhanced milk yield and feed efficiency were attributed to higher digestibility coefficients for DM (0.80 vs 0.77), NDF (0.66 vs 0.62) and gross energy (0.81 vs 0.78) in cows fed on Yeast compared with Control. Rumen pH, redox potential and volatile fatty acid concentrations, methane emissions, plasma metabolites and immunity indicators, and health events were not affected by treatment. There was no effect of treatment on days from calving to first milk progesterone rise above 3 ng/ml, days to first insemination, days to conception, conception rate, number of inseminations or incidence of atypical ovarian cycles. It was concluded that live yeast enhanced digestibility, milk yield and feed efficiency in high-yielding dairy cows, and that despite increased milk yield, methane emissions, reproduction and health indicators were maintained at the same levels as control cows.

Unraveling the genetic basis of methane emission in dairy cattle: a comprehensive exploration and breeding approach to lower methane emissions

Ruminant animals, such as dairy cattle, produce CH4, which contributes to global warming emissions and reduces dietary energy for the cows. While the carbon foot print of milk production varies based on production systems, milk yield and farm management practices, enteric fermentation, and manure management are major contributors togreenhouse gas emissions from dairy cattle. Recent emerging evidence has revealed the existence of genetic variation for CH4 emission traits among dairy cattle, suggests their potential inclusion in breeding goals and genetic selection programs. Advancements in high-throughput sequencing technologies and analytical techniques have enabled the identification of potential metabolic biomarkers, candidate genes, and SNPs linked to methane emissions. Indeed, this review critically examines our current understanding of carbon foot print in milk production, major emission sources, rumen microbial community and enteric fermentation, and the genetic architecture of methane emission traits in dairy cattle. It also emphasizes important implications for breeding strategies aimed at halting methane emissions through selective breeding, microbiome driven breeding, breeding for feed efficiency, and breeding by gene editing.

Invited review: Quantifying multiple burdens of dairy cattle production diseases and reproductive inefficiency-Current knowledge and proposed metrics

The economic burden of diseases and reproductive inefficiency in dairy cattle is evident and has been quantified. Dairy diseases and reproductive inefficiency are however associated with other issues as well, including animal welfare, environmental pressure, and public health risks. Quantifying these other issues is becoming important to help farmers make decisions. Quantification of the noneconomic burdens of diseases and reproductive inefficiency is rare and lacks an overview of approaches and metrics. The first aim of this paper is to provide trends for associating diseases and reproductive inefficiency with economic and noneconomic burdens of disease. The second aim is to provide a review of approaches and metrics used to quantify the noneconomic burdens of disease and reproductive inefficiency. For the economic burden of diseases and reproductive performance, only an overview of the approaches used to quantify the burden is provided. The final aim is to propose approaches and metrics for future quantification of noneconomic burdens caused by individual diseases. A literature search was conducted in Web of Science to identify scientific articles on mastitis, lameness, metabolic disorders, and reproductive inefficiency in dairy cows. The search was restricted to articles published between January 1, 2010 and December 31, 2022 and resulted in 7,565 articles. The total number of articles that mentioned the economic, animal welfare, public health, and environmental burden was 1,253, 428, 291, and 77, respectively. An increase in the percentage of articles mentioning the economic, animal welfare, and public health burden was observed between 2010 and 2022. Despite the 2,049 articles that mentioned one of the burdens, the results showed that approximately 10% of the articles quantified one or more of these burdens. The economic burden of diseases and reproductive inefficiency has been quantified in 154 articles and very few articles quantified the noneconomic burdens (9 articles for environment, 29 articles for public health, and 2 articles for animal welfare). Eleven articles were identified that quantified multiple burdens, and in all these studies the economic burden was combined with a noneconomic burden through a modeling approach (mainly simulation). We propose to link the noneconomic burdens to biological simulation models, and thus develop bioburden simulation models. Well-established approaches and metrics can be used to quantify economic, environmental, and public health burdens. For the economic impact, costs per cow per year can be assessed. A life cycle assessment can be performed for environmental impact and the public health impact can be assessed by a defined daily dose for antimicrobial use and disability-adjusted life years for zoonotic diseases. Regarding animal welfare, approaches and metrics to quantify the welfare impact of a diseased animal are not well established. For animal welfare, we propose a welfare-adjusted life years approach. The mentioned approaches and metrics are a proposal, and it is up to the scientific community to use them or, based on empirics and research experience, propose changes so that we will end up with robust approaches and metrics that enable us to compare research results and provide more evidence for animal health decision makers.

Environmental sustainability and ruminant production: A UK veterinary perspective

Environmental sustainability is an issue of growing importance within the livestock industry, particularly for farmed ruminants. Changes to farming practices made to improve sustainability can have an impact on the health and welfare of animals, and so become the concern of veterinary practitioners. This review outlines the metrics used to measure sustainability and how sustainability interacts with ruminant health and welfare, allowing practitioners to incorporate environmental considerations into their existing livestock work. Topics covered include nutrition, disease control, genetics and stocking density.

Effects of extending dairy cow longevity by adjusted reproduction management decisions on partial net return and greenhouse gas emissions: A dynamic stochastic herd simulation study

Prolonging dairy cattle longevity is regarded as one of the options to contribute to more sustainable milk production. Because failure to conceive is one of the main reasons for culling, this study investigates how adjustments in reproduction management affect partial net return at herd level and greenhouse gas emissions per unit of milk, using a dynamic stochastic simulation model. The effects of reproduction decisions that extend cattle longevity on milk yield, calving interval and pregnancy rate were derived from actual performance of Dutch commercial dairy cows over multiple lactations. The model simulated lactations, calving, and health status events of individual cows for herds of 100 cows. Scenarios evaluated differed in the maximum number of consecutive AI attempts (4, 5, or 6 services), or the production threshold (20, 15, or 10 kg of milk/d) at which cows that failed to conceive are culled (reproductive culling). Annual partial net return was computed from revenues of sold milk, calves, and slaughtered cows, and the costs from feed consumption, rearing replacement heifers, AI services, and treatment for clinical mastitis and lameness. Greenhouse gas emissions were computed for feed production, enteric fermentation, and manure management, and were expressed as total CO2 equivalents (CO2-eq). Average age at culling increased with an increased maximum number of AI services. This increase was larger when going from a maximum of 4 to 5 AI attempts (108 d) than from a maximum of 5 to 6 attempts (47 d). Similarly, the average age at culling increased from 1,968 to 2,040 and 2,132 d when the threshold for reproductive culling decreased from 20, to 15 and 10 kg of milk/d, respectively. Average annual partial net return increased by 1.1% from €165,850 per 100 cows at a maximum of 4 AI to €167,670 per 100 cows at a maximum of 6 AI, and increased by 4.3% from €161,210 per 100 cows at a reproductive culling threshold of 10 kg/d to €168,190 per 100 cows at a threshold of 20 kg/d. Greenhouse gas emissions decreased by 1.2% from 0.926 to 0.915 kg CO2-eq per kg of fat- and protein-corrected milk (FPCM) with an increase in a maximum number of AI from 4 to 6 AI. Conversely, greenhouse gas emissions increased by 0.2% from 0.926 kg at a threshold of reproductive culling of 20 kg/d to 0.928 kg CO2-eq/kg FPCM at a threshold of 10 kg/d. Although lowering the threshold for reproductive culling has the potential to extend cattle longevity more than increasing the maximum number of AI services, only the increase in AI services benefits a farm's partial net return, while reducing greenhouse gas emissions.

Review: Improving residual feed intake modelling in the context of nutritional- and genetic studies for dairy cattle

The residual feed intake (RFI) model has recently gained popularity for ranking dairy cows for feed efficiency. The RFI model ranks the cows based on their expected feed intake compared to the observed feed intake, where a negative phenotype (eating less than expected) is favourable. Yet interpreting the biological implications of the regression coefficients derived from RFI models has proven challenging. In addition, multitrait modelling of RFI has been proposed as an alternative to the least square RFI in nutrition and genetic studies. To solve the challenge with the biological interpretation of RFI regression coefficients and suggest ways to improve the modelling of RFI, an interdisciplinary effort was required between nutritionists and geneticists. Therefore, this paper aimed to explore the challenges with the traditional least square RFI model and propose solutions to improve the modelling of RFI. In the traditional least square RFI model, one set of fixed effects is used to solve systematic effects (e.g., seasonal effects and age at calving) for traits with different means and variances. Thereby, measurement and model fitting errors can accumulate in the phenotype, resulting in undesirable effects. A multivariate RFI model will likely reduce this problem, as trait-specific fixed effects are used. In addition, regression coefficients for DM intake on milk energy tend to have more biologically meaningful estimates in multitrait RFI models, which indicates a confounding effect between the fixed effects and regression coefficients in the least square RFI model. However, defining precise expectations for regression coefficients from RFI models or sourcing for accurate feed norm coefficients seems difficult, especially if the coefficients are applied to a wide cattle population with varying diets or management systems, for example. To improve multitrait modelling of RFI, we suggest improving the modelling of changes in energy status. Furthermore, a novel method to derive the energy density of the diet and individual digestive efficiency is proposed. Digestive efficiency is defined as the part of the efficiency associated with digestive processes, which primarily reflects the conversion from gross energy to metabolisable energy. We show the model was insensitive to prior values of energy density in feed and that there was individual variation in digestive efficiency. The proposed method needs further development and validation. In summary, using multitrait RFI can improve the accuracy of the ranking of dairy cows' feed efficiency, consequently improving economic and environmental sustainability on dairy farms.

Relationship between Dairy Cow Health and Intensity of Greenhouse Gas Emissions

The dairy industry is facing criticism for its role in exacerbating global GHG emissions, as climate change becomes an increasingly pressing issue. These emissions mostly originate from methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2). An optimal strategy involves the creation of an economical monitoring device to evaluate methane emissions from dairy animals. Livestock production systems encounter difficulties because of escalating food demand and environmental concerns. Enhancing animal productivity via nutrition, feeding management, reproduction, or genetics can result in a decrease in CH4 emissions per unit of meat or milk. This CH4 unit approach allows for a more accurate comparison of emissions across different animal production systems, considering variations in productivity. Expressing methane emissions per unit allows for easier comparison between different sources of emissions. Expressing emissions per unit (e.g., per cow) highlights the relative impact of these sources on the environment. By quantifying emissions on a per unit basis, it becomes easier to identify high-emission sources and target mitigation efforts accordingly. Many environmental policies and regulations focus on reducing emissions per unit of activity or output. By focusing on emissions per unit, policymakers and producers can work together to implement practices that lower emissions without sacrificing productivity. Expressing methane emissions in this way aligns with policy goals aimed at curbing overall greenhouse gas emissions. While it is true that total emissions affect the atmosphere globally, breaking down emissions per unit helps to understand the specific contributions of different activities and sectors to overall greenhouse gas emissions. Tackling cattle health issues can increase productivity, reduce GHG emissions, and improve animal welfare. Addressing livestock health issues can also provide favourable impacts on human health by reducing the prevalence of infectious illnesses in livestock, thereby mitigating the likelihood of zoonotic infections transmitting to humans. The progress in animal health offers the potential for a future in which the likelihood of animal diseases is reduced because of improved immunity, more effective preventative techniques, earlier identification, and innovative treatments. The primary objective of veterinary medicine is to eradicate clinical infectious diseases in small groups of animals. However, as the animal population grows, the emphasis shifts towards proactive treatment to tackle subclinical diseases and enhance production. Proactive treatment encompasses the consistent monitoring and implementation of preventive measures, such as vaccination and adherence to appropriate nutrition. Through the implementation of these measures, the livestock industry may enhance both animal well-being and mitigate the release of methane and nitrous oxide, thereby fostering environmental sustainability. In addition, advocating for sustainable farming methods and providing farmers with education on the significance of mitigating GHG emissions can bolster the industry's endeavours to tackle climate change and infectious illnesses. This will result in a more robust and environmentally sustainable agriculture industry. This review seeks to conduct a thorough examination of the correlation between the health condition of cattle, the composition of milk produced, and the emissions of methane gas. It aims to identify areas where research is lacking and to provide guidance for future scientific investigations, policy making, and industry practices. The goal is to address the difficulties associated with methane emissions in the cattle industry. The primary global health challenge is to identify the causative relationship between climate change and infectious illnesses. Reducing CH4 and N2O emissions from digestive fermentation and animal manure can be achieved by improving animal well-being and limiting disease and mortality.

Recent Advances in Enteric Methane Mitigation and the Long Road to Sustainable Ruminant Production

Mitigation of methane emission, a potent greenhouse gas, is a worldwide priority to limit global warming. A substantial part of anthropogenic methane is emitted by the livestock sector, as methane is a normal product of ruminant digestion. We present the latest developments and challenges ahead of the main efficient mitigation strategies of enteric methane production in ruminants. Numerous mitigation strategies have been developed in the last decades, from dietary manipulation and breeding to targeting of methanogens, the microbes that produce methane. The most recent advances focus on specific inhibition of key enzymes involved in methanogenesis. But these inhibitors, although efficient, are not affordable and not adapted to the extensive farming systems prevalent in low- and middle-income countries. Effective global mitigation of methane emissions from livestock should be based not only on scientific progress but also on the feasibility and accessibility of mitigation strategies.

Exploring definitions of daily enteric methane emission phenotypes for genetic evaluations using a population of indoor-fed multi-breed growing cattle with feed intake data

Genetic selection has been identified as a promising approach for reducing enteric methane (CH4) emissions; a prerequisite for genetic evaluations; however, these are estimates of the necessary genetic parameters based on a population representative of where the genetic evaluations will be used. The objective of this study was, therefore, to derive genetic parameters for a series of definitions of CH4, carbon dioxide (CO2), and dry matter intake (DMI) as well as genetic correlations between CH4, CO2, and DMI in a bid to address the paucity of studies involving methane emissions measured in beef cattle using GreenFeed systems. Lastly, estimated breeding values (EBV) were generated for nine alternative definitions of CH4 using the derived genetic parameters; the EBV were validated against both phenotypic performance (adjusted for non-genetic effects) and the Legarra and Reverter method comparing EBV generated for a subset of the dataset compared to EBV generated from the entire dataset. Individual animal CH4 and CO2 records were available from a population of 1,508 multi-breed growing beef cattle using 10 GreenFeed Emission Monitoring systems. Nine trait definitions for CH4 and CO2 were derived: individual spot measures, the average of all spot measures within a 3-h, 6-h, 12-h, 1-d, 5-d, 10-d, and 15-d period and the average of all spot measures across the full test period (20 to 114 d on test). Heritability estimates from 1,155 animals, for CH4, increased as the length of the averaging period increased and ranged from 0.09 ± 0.03 for the individual spot measures trait to 0.43 ± 0.11 for the full test average trait; a similar trend existed for CO2 with the estimated heritability ranging from 0.17 ± 0.04 to 0.50 ± 0.11. Enteric CH4 was moderately to strongly genetically correlated with DMI with a genetic correlation of 0.72 ± 0.02 between the spot measures of CH4 and a 1-d average DMI. Correlations, adjusted for heritability, between the adjusted phenotype and (parental average) EBV ranged from 0.56 to 1.14 across CH4 definitions and the slope between the adjusted phenotype and EBV ranged from 0.92 to 1.16 (expectation = 1). Validation results from the Legarra and Reverter regression method revealed a level bias of between -0.81 and -0.45, a dispersion bias of between 0.93 and 1.17, and ratio accuracy (ratio of the partial evaluation accuracies on whole evaluation accuracies) from 0.28 to 0.38. While EBV validation results yielded no consensus, CH4 is a moderately heritable trait, and selection for reduced CH4 is achievable.

Holistic View and Novel Perspective on Ruminal and Extra-Gastrointestinal Methanogens in Cattle

Despite the extensive research conducted on ruminal methanogens and anti-methanogenic intervention strategies over the last 50 years, most of the currently researched enteric methane (CH4) abatement approaches have shown limited efficacy. This is largely because of the complex nature of animal production and the ruminal environment, host genetic variability of CH4 production, and an incomplete understanding of the role of the ruminal microbiome in enteric CH4 emissions. Recent sequencing-based studies suggest the presence of methanogenic archaea in extra-gastrointestinal tract tissues, including respiratory and reproductive tracts of cattle. While these sequencing data require further verification via culture-dependent methods, the consistent identification of methanogens with relatively greater frequency in the airway and urogenital tract of cattle, as well as increasing appreciation of the microbiome-gut-organ axis together highlight the potential interactions between ruminal and extra-gastrointestinal methanogenic communities. Thus, a traditional singular focus on ruminal methanogens may not be sufficient, and a holistic approach which takes into consideration of the transfer of methanogens between ruminal, extra-gastrointestinal, and environmental microbial communities is of necessity to develop more efficient and long-term ruminal CH4 mitigation strategies. In the present review, we provide a holistic survey of the methanogenic archaea present in different anatomical sites of cattle and discuss potential seeding sources of the ruminal methanogens.

New insights in improving sustainability in meat production: opportunities and challenges

Treating livestock as senseless production machines has led to rampant depletion of natural resources, enhanced greenhouse gas emissions, gross animal welfare violations, and other ethical issues. It has essentially instigated constant scrutiny of conventional meat production by various experts and scientists. Sustainably in the meat sector is a big challenge which requires a multifaced and holistic approach. Novel tools like digitalization of the farming system and livestock market, precision livestock farming, application of remote sensing and artificial intelligence to manage production and environmental impact/GHG emission, can help in attaining sustainability in this sector. Further, improving nutrient use efficiency and recycling in feed and animal production through integration with agroecology and industrial ecology, improving individual animal and herd health by ensuring proper biosecurity measures and selective breeding, and welfare by mitigating animal stress during production are also key elements in achieving sustainability in meat production. In addition, sustainability bears a direct relationship with various social dimensions of meat production efficiency such as non-market attributes, balance between demand and consumption, market and policy failures. The present review critically examines the various aspects that significantly impact the efficiency and sustainability of meat production.

Applying assisted reproductive technology and reproductive management to reduce CO2-equivalent emission in dairy and beef cattle: a review

Methane emission from beef and dairy cattle combined contributes around 4.5-5.0% of total anthropogenic global methane. In addition to enteric methane (CH4) produced by the rumen, cattle production also contributes carbon dioxide (CO2) (feed), nitrous oxide (N2O) (feed production, manure) and other CH4 (manure) to the total greenhouse gas (GHG) budget of beef and dairy production systems. The relative contribution in standard dairy systems is typically enteric CH4 58%, feed 29% and manure 10%. Herds with low production efficiency can have an enteric CH4 contribution up to 90%. Digestibility of feed can impact CH4 emission intensity. Low fertility herds also have a greater enteric CH4 contribution. Animals with good feed conversion efficiency have a lower emission intensity of CH4/kg of meat or milk. Feed efficient heifers tend to be lean and have delayed puberty. Fertility is a major driver of profit in both beef and dairy cattle, and it is highly important to apply multi-trait selection when shifting herds towards improved efficiency and reduced CH4. Single nucleotide polymorphisms (SNPs) have been identified for feed efficiency in cattle and are used in genomic selection. SNPs can be utilized in artificial insemination and embryo transfer to increase the proportion of cattle that have the attributes of efficiency, fertility and reduced enteric CH4. Prepubertal heifers genomically selected for favourable traits can have oocytes recovered to produce IVF embryos. Reproductive technology is predicted to be increasingly adopted to reduce generation interval and accelerate the rate of genetic gain for efficiency, fertility and low CH4 in cattle. The relatively high contribution of cattle to anthropogenic global methane has focussed attention on strategies to reduce enteric CH4 without compromising efficiency and fertility. Assisted reproductive technology has an important role in achieving the goal of multiplying and distributing cattle that have good efficiency, fertility and low CH4.

How does reproduction account for dairy farm sustainability?

Sustainability - the new hype of the 21st century has brought discomfort for the government and society. Sustainable agriculture is essential to face our most concerning challenges: climate change, food security, and the environmental footprint, all of which add to consumers' opinions and choices. Improvements in reproductive indexes can enhance animal production and efficiency, guaranteeing profit and sustainability. Estrus detection, artificial insemination (AI), embryo transfer (ET), estrus synchronization (ES), and multiple ovulations are some strategies used to improve animal reproduction. This review highlights how reproductive strategies and genetic selection can contribute to sustainable ruminant production. Improved reproductive indices can reduce the number of nonproductive cows in the herd, reducing methane emissions and land use for production while preserving natural resources.

Uncertainty in non-CO2 greenhouse gas mitigation contributes to ambiguity in global climate policy feasibility

Despite its projected crucial role in stringent, future global climate policy, non-CO2 greenhouse gas (NCGG) mitigation remains a large uncertain factor in climate research. A revision of the estimated mitigation potential has implications for the feasibility of global climate policy to reach the Paris Agreement climate goals. Here, we provide a systematic bottom-up estimate of the total uncertainty in NCGG mitigation, by developing 'optimistic', 'default' and 'pessimistic' long-term NCGG marginal abatement cost (MAC) curves, based on a comprehensive literature review of mitigation options. The global 1.5-degree climate target is found to be out of reach under pessimistic MAC assumptions, as is the 2-degree target under high emission assumptions. In a 2-degree scenario, MAC uncertainty translates into a large projected range in relative NCGG reduction (40-58%), carbon budget (±120 Gt CO2) and policy costs (±16%). Partly, the MAC uncertainty signifies a gap that could be bridged by human efforts, but largely it indicates uncertainty in technical limitations.

Influence of dairy farmers' knowledge on their attitudes towards breeding tools and genomic selection

Understanding farmers' attitudes towards traits is critical for developing appropriate breeding goals for dairy production. In response to a research gap in regards to the influence of farmers' knowledge of breeding tools, this study aimed to determine the effect of farmers' knowledge on their attitudes towards the use of breeding tools and traits in typical family-owned farms in Slovenia. An online questionnaire was sent to dairy farmers affiliated with Slovenian breeding associations, and 256 dairy farmers responded. The analysis was conducted in three steps. First, the basic response patterns according to the farmers' knowledge level were determined using latent class analysis. Second, farmers' attitudes towards breeding tools were assessed by 15 statements using principal component analysis. Finally, we were interested in the relationship between farmers' attitudes and knowledge about selection. The results showed that farmers had more knowledge about the benefits of genomic selection, followed by general knowledge about breeding values and the definition of genomic selection, and they had the least knowledge about the reference population. Farmers with more knowledge were statistically significantly more likely than farmers with less knowledge to have higher education, be younger, have a larger herd size, have higher milk production per cow, have the intent to increase herd size and milk quantity, and use genomically tested bulls. No significant relationship was found between belonging to a specific knowledge class and the main breed in the herd, the farmer's gender, production system, or farming in less-favoured areas. The results also show that farmers basically agree that they need written recorded performance data about a bull/cow to know exactly how good the animal is, that the genetic merit (breeding value) of bulls/cows adds to the performance of their progeny, that it is very important to maintain the breed characteristics of bulls/cows, that cooperation in being able to compare animals with other farmers is essential for improving herd performance, and that the possibilities of selecting dairy cows with genomic selection and monogenetic traits must be fully exploited, indicating a positive attitude towards genomic selection. The level of knowledge was shown to influence attitudes towards various aspects of breeding. It was found that the higher the level of knowledge, the more positive the attitude towards genetic and genomic selection, and the more negative the attitude towards traditional selection.

Quantifying methane emissions under field conditions under 2 different dairy production scenarios: Low-input versus high-input milk production

Livestock production systems with ruminants play a relevant role in the emission of the greenhouse gas CH₄, which is known to significantly contribute to global warming. Consequently, it is a major societal concern to develop strategies in mitigating such emissions. In addition to breeding toward low-emitting cows, management strategies could also help in reducing greenhouse gas emissions from dairy farms. However, information is required for appropriate decision making. To the best of our knowledge, this is the first study that considers different, already available equations to estimate CH₄ emissions of small-scale dairy farms in the mountain region, which largely differ from large dairy farms in the lowlands concerning management and production. For this study, 2 different production systems, both typical for small-scale dairy farming in mountain regions, were simultaneously run over 3 yr at an experimental farm as follows: (1) a high-input production system, characterized by intensive feeding with high amounts of external concentrates and maize silage, year-round housing, and high yielding Simmental cattle breed, and (2) a low-input production system, characterized by prevailing hay and pasture feeding and silage ban, thus covering most of the energy requirements by forage harvested on-farm and the use of the local Tyrolean Grey cattle breed. Results reveal that feeding management has a significant effect on the amount of CH₄ emissions. The low-input production system produced less CH₄ per cow and per day compared with the high-input production system. However, if calculated per kilogram of milk, the high-input scenario produced proportionally less CH₄ than the low-input one. Findings of this study highlight the potential to assess in a fast and cost-effective way the CH₄ emission in different dairy production systems. This information contributes to the debate about the future of sustainable milk production in mountain regions, where the production of feed resources is climatically constrained, and could be useful for breeding purposes toward lower CH₄-emissions.

Technology for Carbon Neutral Animal Breeding

Animal breeding techniques are to genetically select highly productive animals with less GHG emission intensity, thereby reducing the number of animals required to produce the same amount of food. Shotgun metagenomics provides a platform to identify rumen microbial communities and genetic markers associated with CH4 emissions, allowing the selection of cattle with less CH4 emissions. Moreover, breeding is a viable option to make real progress towards carbon neutrality with a very high rate of return on investment and a very modest cost per tonne of CO2 equivalents saved regardless of the accounting method. Other high technologies include the use of cloned livestock animals and the manipulation of traits by controlling target genes with improved productivity.

Bioeconomy and net-zero carbon: lessons from Trends in Biotechnology, volume 1, issue 1

Many biotechnology applications tend to be for low production volumes and relatively high-value products such as insulin and vaccines. More difficult to perfect at scale are bioprocesses for high-volume products with lower value, especially if the target product is a reduced chemical such as a solvent or a plastic. Historically, industrial microbiology succeeded under special circumstances when fossil feedstocks were either unavailable or expensive. Inevitably, as these circumstances relaxed, bioprocesses struggled to compete with petrochemistry. Why try to compete? Fossil resources will be phased out in the coming decades in the struggle with climate change. To reach net-zero carbon by 2050 will require all sectors to transition, not only energy and transportation. This may herald a new opportunity for industrial bioprocesses with much better tools.

Enteric methane research and mitigation strategies for pastoral-based beef cattle production systems

Ruminant livestock play a key role in global society through the conversion of lignocellulolytic plant matter into high-quality sources of protein for human consumption. However, as a consequence of the digestive physiology of ruminant species, methane (CH₄), which originates as a byproduct of enteric fermentation, is accountable for 40% of global agriculture's carbon footprint and ~6% of global greenhouse gas (GHG) emissions. Therefore, meeting the increasing demand for animal protein associated with a growing global population while reducing the GHG intensity of ruminant production will be a challenge for both the livestock industry and the research community. In recent decades, numerous strategies have been identified as having the potential to reduce the methanogenic output of livestock. Dietary supplementation with antimethanogenic compounds, targeting members of the rumen methanogen community and/or suppressing the availability of methanogenesis substrates (mainly H₂ and CO₂), may have the potential to reduce the methanogenic output of housed livestock. However, reducing the environmental impact of pasture-based beef cattle may be a challenge, but it can be achieved by enhancing the nutritional quality of grazed forage in an effort to improve animal growth rates and ultimately reduce lifetime emissions. In addition, the genetic selection of low-CH₄-emitting and/or faster-growing animals will likely benefit all beef cattle production systems by reducing the methanogenic potential of future generations of livestock. Similarly, the development of other mitigation technologies requiring minimal intervention and labor for their application, such as anti-methanogen vaccines, would likely appeal to livestock producers, with high uptake among farmers if proven effective. Therefore, the objective of this review is to give a detailed overview of the CH₄ mitigation solutions, both currently available and under development, for temperate pasture-based beef cattle production systems. A description of ruminal methanogenesis and the technologies used to estimate enteric emissions at pastures are also presented.

Phenotypic relationship and repeatability of methane emissions and performance traits in beef cattle using a GreenFeed system

Rumen methanogenesis results in the loss of 6% to 10% of gross energy intake in cattle and globally is the single most significant source of anthropogenic methane (CH4) emissions. The purpose of this study was to analyze greenhouse gas traits recorded in a commercial feedlot unit to gain an understanding into the relationships between greenhouse gas traits and production traits. Methane and carbon dioxide (CO2) data recorded via multiple GreenFeed Emission Monitoring (GEM), systems as well as feed intake, live weight, ultrasound scanning data, and slaughter data were available on 1,099 animals destined for beef production, of which 648 were steers, 361 were heifers, and 90 were bulls. Phenotypic relationships between GEM emission measurements with feed intake, weight traits, muscle ultrasound data, and carcass traits were estimated. Utilization of GEM systems, daily patterns of methane output, and repeatability of GEM system measurements across averaging periods were also assessed. Methane concentrations varied with visit number, duration, and time of day of visit to the GEM system. Mean CH4 and CO2 varied between sex, with mean CH4 of 256.1 g/day ± 64.23 for steers, 234.7 g/day ± 59.46 for heifers, and 156.9 g/day ± 55.98 for young bulls. A 10-d average period of GEM system measurements were required for steers and heifers to achieve a minimum repeatability of 0.60; however, higher levels of repeatability were observed in animals that attended the GEM system more frequently. In contrast, CO2 emissions reached repeatability estimates >0.6 for steers and heifers in all averaging periods greater than 2-d, suggesting that cattle have a moderately consistent CO2 emission pattern across time periods. Animals with heavier bodyweights were observed to have higher levels of CH4 (correlation = 0.30) and CO2 production (correlation = 0.61), and when assessing direct methane, higher levels of dry matter intake were associated with higher methane output (correlation = 0.31). Results suggest that reducing CH4 can have a negative impact on growth and body composition of cattle. Methane ratio traits, such as methane yield and intensity were also evaluated, and while easy to understand and compare across populations, ratio traits are undesirable in animal breeding, due to the unpredictable level of response. Methane adjusted for dry matter intake and liveweight (Residual CH4) should be considered as an alternative emission trait when selecting for reduced emissions within breeding goals.

Host genetics associated with gut microbiota and methane emission in cattle

In livestock sector, dairy animals alone produce 18% of the total greenhouse gas emissions globally as methane (CH₄). This Enteric methane is the largest component of total carbon footprints produced by livestock production system and its reduction is today's new challenge to make livestock farming sustainable for earth's environment. The production of enteric methane in ruminants is a complex phenomena involving different host factors like host genotype, rumen microbiome, host physiology along with dietary factors. Efforts have been made to reduce methane emissions largely through nutritional interventions and dietary supplements, but permanent reductions can be obtained through genetic means by selecting and breeding of low methane emitting animals. From genome-wide association studies, many important genomic QTL regions and single nucleotide polymorphisms involved in shaping the composition of the ruminal microbiome and thus their carbon footprints have been recognised, implying that methane emission traits are quantitative traits. The major bottleneck in implementation of reduced methane emission traits in the breeding programs is wide variation at phenotypic level, lack of precise methane measurements at individual level. Overall, the heritability for CH₄ production traits is moderate, and it can be used in breeding programmes to target changes in microbial composition to reduce CH₄ emission in the dairy industry for far-reaching environmental benefits at the cost of a minor reduction in genetic gain in production traits.

Board Invited Review: Enteric methane mitigation interventions

Mitigation of enteric methane (CH₄) presents a feasible approach to curbing agriculture’s contribution to climate change. One intervention for reduction is dietary reformulation, which manipulates the composition of feedstuffs in ruminant diets to redirect fermentation processes toward low CH₄ emissions. Examples include reducing the relative proportion of forages to concentrates, determining the rate of digestibility and passage rate from the rumen, and dietary lipid inclusion. Feed additives present another intervention for CH₄ abatement and are classified based on their mode of action. Through inhibition of key enzymes, 3-nitrooxypropanol (3-NOP) and halogenated compounds directly target the methanogenesis pathway. Rumen environment modifiers, including nitrates, essential oils, and tannins, act on the conditions that affect methanogens and remove the accessibility of fermentation products needed for CH₄ formation. Low CH₄-emitting animals can also be directly or indirectly selected through breeding interventions, and genome-wide association studies are expected to provide efficient selection decisions. Overall, dietary reformulation and feed additive inclusion provide immediate and reversible effects, while selective breeding produces lasting, cumulative CH₄ emission reductions.

The Nutritional Profiles of Five Important Edible Insect Species From West Africa-An Analytical and Literature Synthesis

Background: Undernutrition is a prevalent, serious, and growing concern, particularly in developing countries. Entomophagy—the human consumption of edible insects, is a historical and culturally established practice in many regions. Increasing consumption of nutritious insect meal is a possible combative strategy and can promote sustainable food security. However, the nutritional literature frequently lacks consensus, with interspecific differences in the nutrient content of edible insects generally being poorly resolved.

Aims and methods: Here we present full proximate and fatty acid profiles for five edible insect species of socio-economic importance in West Africa: Hermetia illucens (black soldier fly), Musca domestica (house fly), Rhynchophorus phoenicis (African palm weevil), Cirina butyrospermi (shea tree caterpillar), and Macrotermes bellicosus (African termite). These original profiles, which can be used in future research, are combined with literature-derived proximate, fatty acid, and amino acid profiles to analyse interspecific differences in nutrient content.

Results: Interspecific differences in ash (minerals), crude protein, and crude fat contents were substantial. Highest ash content was found in H. illucens and M. domestica (~10 and 7.5% of dry matter, respectively), highest crude protein was found in C. butyrospermi and M. domestica (~60% of dry matter), whilst highest crude fat was found in R. phoenicis (~55% of dry matter). The fatty acid profile of H. illucens was differentiated from the other four species, forming its own cluster in a principal component analysis characterized by high saturated fatty acid content. Cirina butyrospermi had by far the highest poly-unsaturated fatty acid content at around 35% of its total fatty acids, with α-linolenic acid particularly represented. Amino acid analyses revealed that all five species sufficiently met human essential amino acid requirements, although C. butyrospermi was slightly limited in leucine and methionine content.

Discussion: The nutritional profiles of these five edible insect species compare favorably to beef and can meet human requirements, promoting entomophagy's utility in combatting undernutrition. In particular, C. butyrospermi may provide a source of essential poly-unsaturated fatty acids, bringing many health benefits. This, along with its high protein content, indicates that this species is worthy of more attention in the nutritional literature, which has thus-far been lacking.