Meta-Analysis and Ranking of the Most Effective Methane Reduction Strategies for Australia’s Beef and Dairy Sector

Abstract

Although Australia remains committed to the Paris Agreement and to reducing its greenhouse gas emissions, it was late in joining the 2021 Global Methane Pledge. Finding suitable methane (CH₄) mitigation solutions for Australia’s livestock industry should be part of this journey. Based on a 2020–2023 systematic literature review and multicriteria decision approach, this study analyses the available strategies for the Australian beef and dairy sector under three scenarios: baseline, where all assessment criteria are equally weighted; climate emergency, with a significant emphasis on CH₄ reduction for cattle in pasture and feedlot systems; and conservative, where priority is given to reducing costs. In total, 46 strategies from 27 academic publications were identified and classified as ‘Avoid’, ‘Shift’, or ‘Improve’ with respect to their impact on current CH₄ emissions. The findings indicate that ‘Avoid’ strategies of conversion of agricultural land to wetlands, salt marshes, and tidal forest are most efficient in the climate emergency scenario, while the ‘Improve’ strategy of including CH₄ production in the cattle breeding goals is the best for the conservative and baseline scenarios. A policy mix that encourages a wide range of strategies is required to ensure CH₄ emission reductions and make Australia’s livestock industry more sustainable.

1. Introduction

Methane (CH₄) is a potent greenhouse gas (GHG) that contributes to climate change. For an extended period, CH₄ was not a focus in discussions about climate change. More recently, however, there has been a growing acknowledgment among scientists and policymakers that prioritizing CH₄ reduction is of paramount significance [1] in addressing climate risks. This includes averting potential threats of biodiversity loss, wildfires, extreme weather events, and sea level rise. Agriculture and the global food systems, particularly the beef and dairy sector, are major sources of CH₄ emissions [2]. Although estimates vary [3], cattle’s contribution to GHG emissions is significant through gases produced in their digestive systems, the release of CH₄ during manure decomposition, and the land clearing required for grazing and feed production [4].

Identifying the most effective GHG reduction strategies is vital to mitigate the environmental impact of the beef and dairy sector, particularly as the atmospheric CH₄ concentration has experienced a staggering over twofold increase in the last two centuries [5,6,7]. Agriculture and food waste disposal are major contributors [8]. The impact of various GHGs on the climate is determined by two crucial characteristics: their atmospheric lifespan and their capacity to absorb energy [5]. Compared to carbon dioxide (CO₂), CH₄ stands out with a significantly shorter atmospheric lifetime, lasting approximately 12 years as opposed to the centuries-long persistence of CO₂ [1,5]. Despite its shorter duration, CH₄ possesses a higher energy-absorbing capability during its presence in the atmosphere. It exhibits an astonishing warming potency, surpassing CO₂ by over 80 times within the initial 20 years after entering the atmosphere [9]. This underscores the acute and immediate impact of CH₄ emissions on the greenhouse effect and climate change and the need for reduction strategies.

Many countries, including Australia, have committed to reducing their GHG emissions as part of the Paris Agreement [10]. Australia did not join initially the Global Methane Pledge launched in 2021 but has since taken steps to accelerate CH₄ mitigation from its liquified natural gas (LNG) operations [11]. Although livestock is a significant contributor to CH₄ emissions, Australia is yet to undertake any specific commitments. The Australian livestock industry, however, is looking at finding ways to reduce its CH₄ emissions in order to diminish its impacts on climate change.

Understanding the most effective CH₄ reduction strategies is essential for meeting the national commitments on the Paris Agreement and for contributing to the global efforts to combat climate change. Hence, governments and regulatory bodies need evidence-based information and insights to assess the livestock sector and develop targeted, impactful, and effective policies and regulations. Furthermore, the success of any mitigation strategy relies on its acceptance and implementation by the industry. Identifying and promoting strategies that are feasible, economically viable, and socially acceptable can encourage widespread adoption among farmers, consumers, and other stakeholders. As protein production efficiency varies with system design, factors, such as land use, enteric CH₄ production, and scientific progress must be considered in assessing the overall environmental footprint [12].

Australia holds the position of the second largest beef and beef exporter in the world, contributing 14% of all global beef exports [13]. To address the CH₄ emissions associated with ruminants and to boost production, animal nutrition models have evolved over the past six decades. The majority of research has focused on total mixed-ration diets typical of feedlot cattle, despite 96% of cattle in Australia grazing on pastures, and grazing breeding females constituting the largest source of CH₄ emissions in Australian agriculture [14,15,16,17].

According to Tedeschi [15], cattle are responsible for 10% of Australia’s CH₄ emissions and 14.5% of human-induced GHG emissions, based on a global warming potential estimated over 100 years (GWP 100). Since 1990, CH₄ emissions from Australian beef cattle have risen 11.8% to 1.4 million tonnes of CH₄ per year in 2021 [18]. The Australian beef and dairy sector predominately rely on pasture-based cattle, with feedlot finishing accounting for 4% of Australia’s herd consisting of 1 million beef cattle [19]. About 60% of the beef supply comes from extensive grazing [19] and 62% of the national herd grown in northern Australia primarily relies on native grasses with less than 5% of pastures sown with grass and legumes [13,20]. In the dairy industry, milk production has surged by 116% in the last 40 years resulting in a decrease in CH₄ intensity. This reduction is attributed to less seasonality and an increased reliance on fodder crops, supplements, and concentrates [14]. Australia’s cattle sector holds national and global significance, with cattle grazing on sown pastures in the southern regions or native grasses in the north.

The aim of this research is to rank the most effective strategies to reduce CH₄ emissions in Australia’s beef and dairy sector, in order to guide governments and decision-making processes for emission reductions in line with a 1.5 °C world, the desired outcome from the Paris Agreement. Ranking the most effective CH₄ reduction strategies for Australia’s beef and dairy sector allows informed policy decisions while optimizing resource allocation, promoting industry adoption, fulfilling international commitments, ensuring economic viability, and advancing scientific understanding in the context of climate change mitigation. This can also guide future scenario building and scientific investigations in CH₄ reduction.

2. Materials and Methods

Two methods were used to analyse the current CH₄ reduction strategies available for the Australian beef and dairy sector. A systematic literature review (SLR) was undertaken to determine the latest strategies available, and then a multi-criteria decision making (MCDM) approach was used to assess and rank them.

The tool used for the MCDM is the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Developed in the 1980s by Yoon and Hwang and further refined in 1995, this method [21] has proven successful in managing complex decision making with objectivity and transparency across a variety of areas, including environmental management, sustainable development, energy sustainability assessments, mega projects, and supply chain logistics, as well as smaller-size initiatives, such as sustainable hotel construction, and sector-specific solutions, such as reducing the carbon footprint of Brazilian beef exports [22,23,24,25,26,27,28,29]. According to TOPSIS, the best alternative is the one geometrically closest to the positive ideal solution and the farthest away from the negative ideal solution. As a technique to implement MCDM, TOPSIS has become a sound mathematical tool capable of guiding ideal solutions to challenging situations [16]. The application of MCDM through TOPSIS has resulted in a more efficient use of resources, improved decisions, and better risk management [22,23,24].

Given the multi-faceted nature of CH₄ reduction solutions and their different impacts and effects, TOPSIS was used to assess and rank the various alternatives available to policymakers. In the MCDM, specific weightings were assigned for the assessment categories based on various criteria to accommodate three scenarios (

Table 1. Indicator weighting of three scenarios to assess effectiveness of methane (CH₄) reduction strategies in the beef and dairy sector.

Scenario	Main Indicator Weighting	Remaining Indicator Weight
Baseline	None	All 8 indicators weigh 12.5%
Conservative	80% cost reduction	7 remaining indicators weigh 2.9%
Climate Emergency	40% CH4 reduction 40% all production systems	6 remaining indicators weigh 2.9%

). Firstly, in the baseline scenario, all indicators were equally weighted. Secondly, in the climate emergency scenario, a significant emphasis was placed on CH₄ reduction for all cattle, including both pasture and feedlot production systems. Lastly, in the conservative scenario, a prioritization was given to reducing costs.

A range of CH₄ reduction strategies for the Australian beef and dairy sector were classified using the conceptual framework recommended by the Intergovernmental Panel on Climate Change (IPCC), categorizing mitigation strategies or measures as ‘Avoid’, ‘Shift’, or ‘Improve’ (ASI) [30]. The ASI framework places emphasis on providing services for well-being and maintaining decent living standards for all, while concurrently addressing emissions reduction. It serves as a conceptual guide to categorize the finding of possible solutions based on the strategies identified through the SLR.

2.1. Systematic Literature Review

The Scopus database was used to compile the list of strategies employing the search terms ‘methane’ or ‘CH₄’ or ‘short-lived climate pollutant’ or ‘mid-term climate pollutant’ in combination with ‘reduction’ or ‘reduce’ or ‘strategy’ or ‘plan’ or ‘avoid’ or ‘shift’ or ‘improve’ or ‘lower’ or ‘solution’ and ‘meat’ or ‘bovine’ or ‘cattle’ or ‘dairy’ or ‘cow’ or ‘meat and dairy’ or ‘ruminant animal’ or ‘animal protein’. The geographical area was limited to Australia, and the time period was from 2020 to 2023. All abstracts of the publications resulting from the search were reviewed for relevance and only full-text, peer-reviewed publications in English were included. Publications focusing on sheep, nutritional content of plants, and increasing biogas potential were excluded. The resulting 27 publications (see Figure 1) were further categorized based on the treatment and control measuring CH₄ reduction in cattle. This categorization aligned with IPCC’s ASI framework for GHG mitigation [30].

‘Avoid’ measures are seen to be the most effective yet most challenging to implement as avoiding emissions requires significant behaviour changes and the establishment of political and institutional structures that facilitate and enable supporting low-carbon lifestyle actions, ultimately reducing the demand for beef and dairy products. ‘Shift’ measures are generally easier and more accessible to adopt and involve shifting or redirecting consumer demand away from remnant products through easily manageable changes, such as incorporating more meat-free days or opting for consuming cell-based cultured meats. ‘Improve’ measures focus on strategies which reduce emission intensity by increasing the yield of a meat or dairy product and therefore diminishing emissions per kilogram of product while also contributing to an overall reduction in emissions. Examples of ‘Improve’ measures include the manipulation of rumen, feed formulation, dietary supplements, feed consistency, feed additives, selective breeding, farm management, and GHG breeding indexes.

2.2. MCDM and TOPSIS

The CH₄ reduction strategies contained within the 27 SLR-identified articles are assessed through a MCDM using TOPSIS. This section includes an explanation of TOPSIS, highlighting the development of a set of indicators and metrics to build a decision matrix to assess the strategies. It then details the formulas used to calculate the rank of each CH₄ reduction strategy with respect to the ideal solution in the beef and dairy sector. As secondary data are being used, a sensitivity analysis is undertaken to scale weightings according to the three scenarios described above (see Table 1).

Required steps in TOPSIS are identification of indicators, selection of metrics and the development of a decision matrix. This allows for the extracted data to be analysed.

2.2.1. Indicator Development and Metrics

A search of the literature found a lack of assessment criteria or indicators targeting reduction in agricultural CH₄ emissions. Much of the MCDM research available relates to transportation and energy choices, such as the EU’s 2030 plan to step up climate ambition [32], energy efficiency, and conservation [33] or focus on corporate sustainability [34,35]. Nevertheless, parallels apply for this study. For example, assessment indicators are provided by UNEP [33] for governments to choose energy saving and energy-efficient energy systems, carbon capture, and storage and to reduce human health impacts and risks. Furthermore, overarching indicator themes have been obtained from sustainability assessment handbooks and MCDM guidelines [24,36].

Typically, indicators for assessing policy-making decisions include measurements for environmental, economic, social, global impact-related, technical, and other aspects. For example, UNEP [33] suggests a comprehensive set of indicators, comprising minimizing spending on technology, other types of spending, allowing for easy implementation, adhering to required timing of policy intervention, reducing GHG and black carbon emissions, enhancing resilience to climate change, stimulating private investments, improving economic performance, generating employment, contributing to fiscal sustainability, protecting environmental resources, preserving biodiversity, supporting ecosystem services, reducing poverty incidence, reducing inequality, improving health, preserving cultural heritage, contributing to political stability, and enhancing governance. Meanwhile, the European Commission [37] recommends policy assessment indicators such as air pollution impacts, synergies and trade-offs, capital and variable costs revenues gained, investment challenges, energy supply security, and impact on employment and households when assessing sustainable energy and transport options. Other indicators include social criteria, such as social acceptability, and the globalized impact of policy, including resource depletion [24].

These resources provide the context for applying the relevant parallels from energy and transport policy assessment in the context of reducing CH₄ in the beef and dairy industry.

Table 2. Assessment categories and indicators for assessment of CH₄ reduction strategies in the beef and dairy sector in Australia.

Categories	Indicators (Value in Brackets)	Supporting Information
Environmental Impact	CH4 reduction per litre of energy-corrected milk, per kilogram of trimmed boneless beef or baseline (%)	Energy-corrected metric, industry standardized unit of measurement in dairy industry [38]. Trimmed boneless beef according to Saner and Buseman [39].
Estimated Implementation Costs	Estimated AUD upfront capital costs for strategy implementation and/or operating expenditures Relative comparison of strategies scaled between 1 and 10	Similar to UNEP’s [33] Practical Framework for Planning Pro-Development Climate policy. Example indicators for energy efficiency, carbon capture and storage, and reducing human health impacts.
Technological Readiness	Research development stage: emerging (1) or established (2)	Based on Federal Agriculture Department [40].
Policy and Regulatory Landscape	Compliance with existing laws: No (1), Yes (2) New policy required: No (1), Yes (2)	Similar to UNEP’s [33] indicators for energy efficiency regarding easy institutional implementation. Data sourced from the systematic literature review (SLR) and secondary evidence.
Scalability and Replicability	Applicable production system: Feedlot (1), pasture-based (2), both (3) Applicability to both northern and southern regions: No (1), Yes (2) Applicability to all seasons: No (1), Yes (2)	Similar to UNEP’s [33] indicators for energy efficiency regarding easy institutional implementation. Data sourced from SLR and secondary evidence.

shows the criteria adopted for this study under the following categories:

• Environmental impact—CH₄ reduction;
• Economic impact—estimated intervention costs;
• Technological readiness—research development stage;
• Policy and regulatory landscape—compliance with existing laws, new policy required;
• Scalability and replicability—applicable across production systems, climatic zones, and seasons.

Environmental Impact

The environmental impact is measured by calculating the percentage reduction in CH₄ emissions per litre of energy-corrected milk (ECM) or kilogram of boneless beef values, where available. This approach ensures standardized consistency between feed inputs and product yields. The formula for calculating cost of kilogram of boneless trimmed beef is based on 63% of live animal as Hot Carcass Weight (HCW), and 65% of HCW is assumed to be measured in kilograms of trimmed boneless beef [39].

Economic Cost

The economic category is quantified by estimating the cost of the intervention in Australian dollars (AUD), assuming government subsidization or support upon adoption. As the research articles reviewed do not provide calculation for upfront capital or ongoing costs related to implementing CH₄ reduction strategies, relevant data are drawn from secondary sources, identified during this literature review. Given that most strategies are based on improving feed, a significant component of the financial cost and the metabolizable energy of cattle, the choice of feed can affect yield and the quality and quantity of outputs subject to variables such as the prevailing milk pricing. As such this cost element considers only the upfront or ongoing costs of supplying the chosen feed/supplement with the assumption that the government will absorb these costs if the intervention is adopted. After the calculation of the estimated pricing for all strategies, a comparative scale of 1–10 was established. For example, establishing a new industry and genetic research requiring more than AUD 100 million in grants and funding, was considered the highest cost, resulting in a score of ‘10’. By comparison, changes in farm management practices, such as alterations to feed, composting or increasing milk production targets were assigned a score of ‘1’ due to their comparatively lower cost.

Technological readiness

Technological readiness highlights the developmental stage of a strategy, which is particularly relevant when investing in innovation. Drawing upon Australia’s efforts to determine a strategy for net zero emissions in the agriculture sector, two distinct categories transpired regarding new technologies and practices, namely established and scalable, and emerging [40]. In such a context, strategies undergoing ‘in vitro’ lab testing, which have yet to transition from the laboratory setting to real-world application, are classed as not being technologically ready or assigned a ‘1’ for this indicator. A ‘2’ was assigned to strategies, or close variations, which are considered to be technologically ready for implementation if they have been previously established and demonstrated elsewhere.

Policy landscape

The policy landscape was assessed using a scale of 1 or 2. A scope of ‘2’ was assigned if a strategy complied with current legislation and/or regulations, while a ‘1’ was assigned for non-compliance or when a new policy was required.

Scalability

Scalability is an assessment of the applicability of the strategy across both feed and forage systems for beef and dairy systems, as well as across various climatic zones and seasons. A scale of 1 to 3 was employed for the production system, where ‘1’ represents application to only feedlot production, ‘2’ represents application to only grazing production, and ‘3’ indicates application for both production systems. Similarly, a ‘1’ or ‘2’ was assigned for applicability to both Northern and Southern production zones or seasons, where ‘1’ represents only limited applicability to specific seasons or production zones.

2.2.2. Decision Matrix

Using the 46 strategies identified in the 27 articles analysed, data on CH₄ reduction and other assessment categories were extracted to formulate the decision matrix. The creation of the decision matrix (outlined as the first step Equation (A3) in Appendix A) aims to assess the most effective available solution for CH₄ reduction in the beef and dairy sector and is shown in Appendix B. Where data regarding cost, policy landscape, and technological readiness were not available in the original articles, secondary sources were used.

2.2.3. TOPSIS Formulations

The TOPSIS formulas are used to calculate each strategy’s Euclidian distance to the most ideal solution, according to the assessment categories in Table 2 and data from Appendix C. These Euclidian distances are then used to create a ranking of the 10 most effective strategies [21]. In order to determine the most effective CH₄ reduction strategy in the beef and dairy sector, a decision matrix was constructed (refer to Appendix B). Equations (A1)–(A12) in Appendix A describe the process of decision matrix formulation, vector normalization, integration with baseline, conservative and climate emergency scenario weighting, determination of positive and ideal negative solutions, separation value calculation, and the final preference score calculation. Full results are located in Appendix D, and the results are discussed in the next section.

3. Results

This section presents the results derived from the systematic literature review and the MCDM through TOPSIS ranking. The top-ranking strategies for effective CH₄ reduction in the beef and dairy sector are revealed under the baseline, conservative, and climate emergency scenarios. They are informative for policymakers when considering effective CH₄ reduction policies in the beef and dairy sector.

3.1. Systematic Literature Review

The literature highlights the challenges associated with measuring CH₄ accurately and consistently due to a variety of methods and options available for modelling CH₄ production. Pryce and Haile-Mariam [41] state that the accuracy of CH₄ measurement varies on the chosen technique for capturing CH₄ data, ranging in affordability from enclosed respiration chambers, SF6 tracer techniques, handheld laser CH₄ detection, automated head chambers, or sensors in automated milking systems. Measurement of CH₄ in the industry also shows discrepancies as the reported direct value is 30% lower than that calculated by national inventory standards [19]. Furthermore, a more accurate representation of CH₄ environmental impact is debated in the literature with alternative CH₄ metrics such as GWP* [42]. This metric replaces the 100-year carbon equivalation with the calculated lifespan of CH₄ and other short-lived GHGs, enabling a more accurate calculation of CH₄ impact over its 12-year life span [42]. In this literature review, GWP* is used as a way to increase the contribution of CH₄ reduction in feedlot cattle supplemented with additives to the overall national herd efforts [43] as the standardized use of GWP100 “may not provide suitable information for every decision-making context” [18].

Tedeschi [15] suggests the mathematical models do not capture the energy expenditure of grazing cattle and may need to be ‘re-engineered’ to accommodate a sustainable perspective combining modelling concepts to encapsulate a decrease in CH₄ emissions. Defining suitable breeding objectives is also a challenge, with a wide range of choices available to model CH₄, such as CH₄ intensity, CH₄ yield, or gross CH₄ emissions and variability in CH₄ produced during different life stages [41]. The literature also captured post-farm emissions associated with the dairy sector [44] where a review of 15 lifecycle assessments and carbon footprints of dairy products was undertaken and included the GHG emissions in post farm-gate processing. These further contribute to the impact of beef and dairy industries with butter and cheese having the highest global warming potential with an average of 20–36 kg of CO₂e and 6.7–9.47 kg CO₂e per kg of product, respectively, when including activities, such as packaging, transportation, different processing methods in industries, and energy consumption.

3.1.1. ‘Avoid’ Strategies

Only one article specifically assessed ‘Avoid’ strategies to reduce CH₄ in the beef and dairy sector by measuring CH₄ emissions resulting from land-use changes and the impact of converting agricultural land back to its original habitat. Iram et al. [45] measured GHG fluxes with a flame ionization detector with nitrogen as a carrier gas from the soil of various sites in an agricultural area located on the Herbert River basin in Queensland. The studied sites produced CH₄ fluxes of 209 g of CH₄ per square metre per year compared to natural habitats of mangrove, freshwater tidal forest and saltmarshes with 0.73 g, 0.15 g, and 0.04 g of CH₄ per square metre per year, respectively. With unstocked wet pastures emitting 200 times more CH₄ than any other site, management practices such as converting wet pasture back to original habitats, including salt marshes, wetlands, and tidal forest, would reduce soil based CH₄ emissions by 99.95%. This paper highlights the potential for ‘Avoiding’ emissions though rehabilitation of agricultural lands back to original habitats.

3.1.2. ‘Shift’ Strategies

Two articles highlighted carbon pricing and cellular agriculture as strategies to shift CH₄ emissions by financially incentivizing low-CH₄ cattle and shifting production of dairy protein to cellular protein. The first ‘Shift’ strategy was a national carbon price that aims to encourage producers and consumers to shift to low-carbon farming alternatives. Richardson et al. [46] measured the effect of including a GHG sub-index into the national breeding program, against carbon prices ranging from AUD 150 to 1000 per t CO₂e and high- and low-accuracy residual CH₄ traits. The results showed that the current low accuracy of CH₄ prediction would reduce CH₄ by 0%, 0.09%, 0.36%, and 0.71% with a carbon pricing of AUD 150, AUD 250, AUD 500, and AUD 1000 per t CO₂e, respectively. A future greater CH₄ accuracy could reduce CH₄ by 3.92%, 5.7%, 6.69%, and 8.03% with a carbon price of AUD 150, AUD 250, AUD 500, and AUD 1000 per t CO₂e, respectively. A carbon price of AUD 1000/t CO₂e reduced CH₄ emissions up to 8.03% when the assumed accuracy in phenotyping is more certain. Davison et al. [47] also reviewed the effect of a modest carbon price of AUD 16.14/t CO₂e and calculated benefits to farmers up to AUD 500 million in net present value until 2030 if Asparagopsis or leucanena (forage legumes) were eligible for carbon credits.

The second ‘Shift’ strategy was researched by Behm et al. [48], who compared the life cycle of a cultured protein with cellular agriculture to dairy protein through a life cycle analysis (LCA). This LCA compared the protein component of milk only and concluded that cellular agriculture is more sustainable from climate and water perspective only if the required protein purity is lower and there is no need for chromatographic purification. Otherwise, protein production through cellular agriculture is similar to the most efficient traditional dairy production in New Zealand. As the LCA of cellular agriculture did not specifically compare CH₄ emissions to traditional dairy farms, only the carbon pricing was included in the following quantitative assessment of strategies.

3.1.3. ‘Improve’ Strategies

‘Improve’ strategies dominated the literature with 21 articles focusing on improving the efficiency or emissions intensity of beef and dairy production. A number of strategies measured CH₄ reduction via feed supplements, feed formulation, genetic selection, improved fertility, manure management, post-farm gate processing, and heat stress reduction.

Feed formulation

The strategies regarding the formulation included feeds such as grass, grain, or legume-based diets and feed supplements such as Asparagopsis taxiformis. Thomas et al. [12] compared the net protein contribution of grass-fed and grain-finished cattle and found that grass-fed cattle produced a higher CH₄ intensity, approximately 22.5% higher than grain-finished beef. The ability of pasture to provide full nutrition to cattle was researched by Mahanta et al. [49], who calculated that cattle can no longer gain the nutrition needed from pasture alone. Yet cultivated cereals, such as maze and sorghum, reduce enteric CH₄; however, cultivation, fertilization, harvesting, and preservation of feed contribute to the overall GHG emissions, and grain-based diets need to be assessed through LCA. This has ramifications for the strategy proposed by Moate et al. [14] who studied the effect of increasing the proportion of wheat in the diet of dairy cattle and found that the higher it is, the greater the reduction in CH₄ and increase in protein, but reduced milk fat. For dietary inclusions of wheat at 15%, 20%, and 45% of dry matter intake (DMI), CH₄ was reduced per kilogram of energy-corrected milk by 12.35%, 14.71%, and 21.18%, respectively.

Several articles, namely Badgery et al. [16], Stifkens et al. [50], and Mwangi et al. [13], investigated a number of legumes and herbs for impact on CH₄ reduction in ruminant diets. Badgery et al. [16] found that Biserrula pelecinus has great potential to reduce enteric CH₄ emissions, similarly to clover Trifolium subterraneum. Stifkens et al. [51] found that increasing the proportion of legumes such as Leucaena leucocephala in feed reduces CH₄ due to condensed tannins acting as a bioactive compound that reduce methanogenesis. A 36% inclusion of Leucaena leucocephala in the diet of cattle reduced CH₄ by 25.09% per kilogram of boneless trimmed beef. Mwangi et al. [13] studied the effect of increasing the proportions of Desmanthus Spp. in the diet of feedlot cattle and the effect on weight gain, fermentation in the rumen, and plasma metabolites in cattle.

Feed supplements and additives

Seaweeds have proven to be effective at reducing enteric CH₄ emissions. Ridoutt et al. [43] explored the supplement of Asparagopsis taxiformis, a red seaweed, on feedlot cattle’s CH₄ production and calculated a 1–4% reduction in Australia’s cattle sector. Parra et al. [51] assessed a range of additives to reduce CH₄ in grazing cattle and found the addition of biochar and nitrate, biochar and Asparagopsis, and citral extract to significantly reduce CH₄ emissions by 22.83%, 19.82%, and 41%, respectively. Lean and Moate [20] reviewed CH₄ reduction strategies in Australia and found that nitrate supplementation reduced emissions by 10% and feed supplemented with 3-nitro-oxypropanol (3-NOP) reduced CH₄ by 22% in beef cattle and 39% in dairy cattle. Australian research has inspired researchers in the United States to study a locally produced seaweed grown in the waters of California to reduce CH₄ in cattle. Of note from this study is the 75% reduction in CH₄ production with Asparagopsis taxiformis and Zonaria farlowii. Research results from Kinley et al. [52], who supplemented beef cattle with a very low dosage of Asparagopsis taxiformis, found that the average daily weight gain increased by 26% and resulted in a reduction in CH₄ of 35% per kg of boneless trimmed beef.

Selective breeding

Pryce and Haile-Mariam [41] argue for genetic selection as a long-term permanent solution by selecting low-emitter cows and traits that have beneficial effects on emissions. Richardson et al. [53] studied the impact of direct CH₄ traits, reduction in replacements, and increase in productivity on CH₄ reduction. Another study [46] determined that the Estimated Breeding Values for Residual Methane Production (EBVRMP) phenotypically corrected for ECM (kg of CH₄/year) is currently the most inheritable trait to reduce CH₄ production in beef. The researchers note that dairy cows appear to have bodyweight and feed intake as the greatest effect on CH₄ production.

Residual CH₄ is stated to be the most inheritable trait to measure low-emissions cows [54]; yet Richardson et al. [46] argue more data are required to confirm residual CH₄ as an accurate measure of selective breeding programs. Currently, high-quality CH₄ phenotypes are less than 10% reliable which is insufficient for inclusion in selective breeding objectives.

Inclusion of sub-indexes in breeding standards

Richardson et al. [55] caution in choosing genetic traits due to potential for unfavourable correlations with energy-corrected milk or difficult to predict responses to genetic selection. Manzanilla-Pech et al. [54] compared dry matter intake and residual feed intake against CH₄ production as a sub-index in Australia’s national breeding standards with CH₄ valued at various price points from nil to high and low negative values. Including residual food intake with a negative economic value in the breeding goal reduces the production of CH₄ compared to the base scenario. For example, this results in a 16.66% and 36.11% reduction in CH₄ based on DMI if CH₄ production is negatively valued at AUD 0.30 or AUD 0.60 per kg of CH₄, respectively. Pryce and Haile-Mariam [41] argue for inclusion of a heat stress/tolerance sub-index in the Balanced Performance Index as a way for the dairy industry to adapt to climate change.

Beef processing

Colley et al. [56] highlight the underreporting of CH₄ emissions generated from meat processing plants’ wastewater. The researchers undertook an LCA and found that CH₄ generated from on-site wastewaters was responsible for 34% of climate change impacts in small to medium processors.

Farm management

Bai et al. [57] compared farm strategies regarding manure management and compared turning to stockpiling of manure. The researchers determined a 53.85% decrease in CH₄ emission generated from manure after turning or windrow composting manure. Almeida et al. [17] argue for increased efficiency and production by triggering early puberty in breeding cows and reducing the post-weaning phase and associated feeding and emissions generated during non-productive times. Lean and Moate [20] found that providing ozonated water to cattle could reduce CH₄ by 20%.

3.2. MCDM/TOPSIS Results

In terms of the ASI framework, a mixture of ‘Avoid’ and ‘Improve’ measures were evident in the top ten ranked strategies for the baseline scenario and the climate emergency scenario. The conservatively weighted scenario, on the other hand, resulted in only ‘Improve’ strategies in the top ten. A breakdown of the strategies per scenario is presented in Figure 2. ‘Avoid’ strategies of land conversion pricing dominated the top four ranked strategies for the climate emergency and ranked 3rd and 4th in the baseline scenario. ‘Improve’ strategies, specifically those related to CH₄ being negatively valued in the breeding objective sub-index and citral extract supplementation ranked very highly for both baseline and conservatively weighted scenarios. Breeding indexes, supplementation with biochar and nitrates, and a greater proportion of wheat, grain, and legumes in dietary feed also ranked highly in the conservative and baseline top ten.

3.2.1. Baseline Scenario

A combination of ‘Improve’ and ‘Avoid’ strategies dominated the top three ranked strategies under the equalized weighting scenario (

Table 3. Ranked methane reduction strategies according to baseline equally-weighted indicators.

Ranking	Performance Ranking	Baseline Equally-Weighted Strategy
1	0.88414382	Methane included in breeding index and valued at 0.60 c per kg of CH4 based on dry matter intake (DMI)
2	0.87393197	Conversion of land from ponded pasture to freshwater tidal forest
3	0.87387	Conversion of land from ponded pasture to mangroves
4	0.86826467	Methane production negatively economically valued at −0.60 c per kg CH4 and resulting feed intake (RFI) included in breeding goals
5	0.86503572	Inclusion of citral extract at 0.1% of dry matter (DM)
6	0.85100814	Methane included in breeding index and valued at 0.30 c per kg of CH4 based on RFI
7	0.84991771	Inclusion of biochar and nitrates at 8% of DM
8	0.84673888	Wheat 45% of DMI
9	0.84619539	Conversion of land from ponded pasture to salt marsh
10	0.84062149	Grain-finished pasture cattle

). With all factors equally weighted, the best performing strategies were CH₄ negatively valued highly in sub-index of breeding standards based on DMI and conversion of ponded pastures to freshwater tidal forests or mangroves, resulting in a reduction in CH₄ by 58.33%, 99.93%, and 99.96%, respectively. High and low negative values of CH₄ included in breeding sub-index based on RFI reduced CH₄ by 47.22% and 27.78%, respectively, ranking 4th and 6th. Citral extract supplement in feed intake ranked 5th and reduced CH₄ emissions by 41%. The supplementation of feed with biochar and nitrates, provision of wheat at 45% of DMI, and grain-finished pasture cattle ranked 7th, 8th, and 10th, respectively, with 22.83%, 21.18%, and 22.25% reduction in CH₄. The ‘Avoid’ strategy converting ponded pastures to saltmarshes ranked 9th and reduced CH₄ by 99.98%. The performance scores ranged from 0.86 to 0.84 with rankings closest to 1 being the most effective solution.

3.2.2. Climate Emergency Scenario

As the IPCC’s mitigation strategies [30] encourage urgent and effective action, the climate emergency weighting prioritized CH₄ reduction in all cattle, feedlot and grazing. The top four results were ‘Avoid’ strategies through conversion of agricultural land to natural habitat. Conversion of wet pastures to freshwater tidal forests, mangroves or salt marshes reduced CH₄ emissions by 99.93%, 99.65%, and 99.98%, respectively. Conversion of dry pastures to salt marshes reduced CH₄ by 73.3%, ranked fourth, and feedlot cattle supplemented with Asparagopsis taxiformis ranked 6th with an 81% CH₄ reduction for 4% of the national herd’s population. Inclusion of CH₄ as a subindex in breeding objectives and negatively valued at 60 c ranked fifth and seventh for DMI and RFI values reducing CH₄ by 58.33% and 47.22%, respectively. Supplementing feed with citral extracts, manure management strategies, and a low negative value of CH₄ in GHG subindex reduced CH₄ by 41%, 53.85%, and 36.11%, respectively, ranking 8th, 9th, and 10th (

Table 4. Ranked methane reduction strategies according to climate emergency-weighted indicators.

Ranking	Performance Ranking	Climate Emergency-Weighted Strategy
1	0.94687926	Conversion of land from ponded pasture to freshwater tidal forest
2	0.94684681	Conversion of land from ponded pasture to mangroves
3	0.94637256	Conversion of land from ponded pasture to salt marsh
4	0.92307151	Conversion of land from dry pasture to salt marsh
5	0.89979906	Methane production negatively economically valued at −0.60 c per kg CH4 and DMI included in breeding goals
6	0.88987446	Feed lot cattle supplemented with Asparagopsis taxiformis
7	0.88001861	Methane production negatively economically valued at −0.60 c per kg CH4 and RFI included in breeding goals
8	0.87954682	Inclusion of citral extract at 0.1% of DM
9	0.86121429	Composting manure vs. stockpiling
10	0.85934594	Methane production negatively economically valued at −0.30 c and DMI included in breeding goals

). The performance ranking ranged from 0.94 to 0.86.

3.2.3. Conservative Scenario

When cost is weighted as the dominating indicator, ‘Improve’ strategies occupied all of the top ten most effective strategies (see

Table 5. Ranked methane reduction strategies according to conservatively-weighted indicators.

Ranking	Performance Ranking	Conservatively-Weighted Strategy
1	0.98219361	Methane production negatively economically valued at −0.60 c per kg CH4 and DMI included in breeding goals
2	0.97988897	Methane production negatively economically valued at −0.60 c per kg CH4 and RFI included in breeding goals
3	0.9794944	Inclusion of citral extract at 0.1% of DM
4	0.97761249	Inclusion of biochar and nitrates at 8% of DM
5	0.97737908	Methane production negatively economically valued at −0.30 c and DMI included in breeding goals
6	0.97714331	Proportion of wheat is 45% of DMI
7	0.9761628	Grain-finished feed formulation
8	0.97558359	36% Leucaena leucocephala feed formulation
9	0.97540405	Methane production negatively economically valued at −0.30 c and RFI included in breeding goals
10	0.97530739	Proportion of wheat is 20% of DMI

). The most effective solution in the conservative scenario is the inclusion of CH₄ at a high negative value as a national breeding subindex based on DMI, or RFI followed by the supplementation of feed with citral extract, reducing methane by 58.33%, 47.22%, and 41%, respectively. The inclusion of biochar and nitrates in feed ranked fourth, following by a low negative value of CH₄ included in national breeding subindex based on DMI, and cattle diet consisting of 45% wheat reducing CH₄ by 22.83%, 36.11%, and 21.18%. The remainder of ‘Improve’ relating to feed supplementation ranked 7th, 8th, and 10th with grain-finished pasture cattle, supplementation of Leucaena leucocephala, and cattle diet consisting of 20% wheat reduced CH₄ by 22.25%, 25.09%, and 14.71%. The ninth ranked strategy was a lower negative value of CH₄ included in the national breeding index based on the resulting feed intake (RFI) reducing CH₄ by 27.78%. The performance ranking of all ‘Improve’ strategies were within the 0.98 performance range (see Table 5).

4. Discussion

Focusing on research in Australia, this study seeks to answer how the beef and dairy sector can address CH₄ emissions. Global CH₄ levels are rising despite many attempts to control them, including through the Global Methane Pledge signed by over 150 countries [58], which was eventually supported by Australia. The food system is responsible for up to 37% of global GHG emissions and affects nearly every planetary boundary [59,60]. Ruminant animals are the main sources of CH₄ emissions through enteric fermentation and CH₄ levels are predicted to increase as global population grows to over 9.7 billion with rising consumption of meat and dairy per person as a dietary trend globally [61]. With food systems being called to be compliant with a 1.5 °C world, this research seeks to address what are estimated to be the most effective strategies to reduce CH₄ emission in the beef and dairy sector.

This literature review’s findings suggest two main concerns requiring CH₄ as a GHG, namely, metric and measurement challenges. They are discussed first before outlining the reduction strategies and interpreting the research findings regarding the ASI scenarios.

4.1. Methane Metric Challenges

All GHGs, including CH₄, are made equivalated to carbon dioxide’s molecular structure and lifespan of approximate 100 years represented as Global Warming Potential of 100 (GWP100) [62]. The IPCC’s 6th Assessment Report states that CH₄ emissions are equivalated to 27 times more potent than CO₂ over a 100-year timescale. This report also confirms the lifetime of CH₄ is 11.8 years in the atmosphere, making the potency much closer to 84 times as potent as carbon dioxide over the relevant approximately 20-year lifespan [63]. The argument for GWP* is supported in the literature, where the “*” represents the lifespan of the GHG in question [18,20].

Perez-Dominguez et al. [64] highlight the value of reflecting the true lifespan of CH₄ which can reverse temperature increases by 2070 if carbon pricing is adequately high enough. The universal application of GWP* raises risks according to Rogelj and Schleussner [65], who argue that implementing GWP* will create equality issues due to the unfair allocation of greater emissions to lower income countries that are agriculture-based, yet have not historically contributed to climate change. As the scope for this research is within the advanced economy of Australia, the application of GWP* to GHG metrics is deemed appropriate.

4.2. Measurement of Methane

The literature highlights the difficulty in measuring accurate CH₄ emissions which creates uncertainty regarding CH₄ production and impact [18,42,57]. This is supported in the wider literature, especially in agricultural settings where whole-of-farm activities are not included in national GHG inventories [66] and measurement of CH₄ differs dependent upon the stage of lactation as well as measurement method [67,68]. Given the projected 90% rise in CH₄ emissions attributable solely to meat production, coupled with an anticipated 1.8% growth in milk production by 2031 [69], CH₄ has historically been overshadowed by carbon in policy discussions until the global policy landscape changed with the adoption of the Global Methane Pledge in 2021 [58]. Australia also signed the methane pledge in October 2022 but has yet to develop a national strategy for its implementation [70].

Ruminants are animals with a rumen which contains a complex anaerobic microbial ecosystem that can ferment plant matter [71]. A rumen’s microbiome consists of bacteria, archaea, protozoa, bacteriophage, and fungi that produce CH₄ as a by-product of enteric fermentation [72]. The cattle population in Australia exceeds 24 million, and with each animal emitting an estimated average of 56 kg of CH₄ annually, this results in 1.3 million tonnes of CH₄ produced solely from cattle [53,73] or 105 million tonnes of CO₂e based on a twenty-year half-life (GWP20) of CH₄. These emissions are anticipated to rise, as global beef and dairy production is projected to increase by 6% in 2031, driven by consumer demand stemming from population growth and dietary trends [69]. Despite recent attention on CH₄ reduction following the Global Methane Pledge, no national CH₄ reduction strategy for Australia currently exists.

4.3. Methane Reduction Strategies

In the TOPSIS context, “most effective” is defined as the strategy closest to the positive ideal solution and farthest from the negative ideal solution [25]. For example, the most effective strategy could be one which reduces the highest amount of CH₄ emissions, incurring the smallest cost, with minimal detrimental trade-offs and providing substantial environmental and social benefits. This effectiveness is subject to consideration of many factors across different strategic approaches. A literature search indicates the absence of existing frameworks published and/or available for national governments, industries, or the general public to assess the effectiveness of various CH₄ reduction strategies. The only exception is an assessment of the New South Wales’s livestock sector, which considers the practicality, availability, risks, and barriers influencing the adoption of CH₄ reduction strategies [74].

Applying the novel indicator framework, a ranking of strategies using TOPSIS estimated that conversion of agricultural land to natural wetlands in the climate emergency scenario is the most effective strategy which favoured CH₄ reduction and both production systems. This ‘Avoid’ strategy measured a reduction in CH₄ emissions associated with soil up to 99%, excluding enteric CH₄, highlighting the significant of land use change in the agricultural sector. Rewilding, reforestation, and rehabilitation of natural habitat have been undertaken as a strategy by the Australian Department of Climate Change, Energy, the Environment and Water (DCCEEW) with a focus on restoring coastal wetlands, salt, and tidal marshes [75]. Whilst government funding for land rehabilitation is up to AUD 2 million dollars per site, a meta-analysis of successful land rehabilitation projects in developed economies determined the costs to be approximately AUD 40–50,000 per hectare for restoration of coastal wetlands and mangroves and approximately AUD 150,000 per hectare for restoration of salt marsh, which could be reduced significantly with volunteer and community support [76]. This strategy is limited to areas of coastal or river basins, but it applies to both Australia’s northern and southern production zones and complies with existing legislation. No new policy is required to continue rehabilitation efforts; however, upscaling of existing efforts may require incentivizing policies for cattle farmers to restore agricultural lands to natural habitats within the property boundaries.

In the baseline and conservative scenarios, the inclusion of a GHG subindex into the national breeding standards of Australian cattle ranked first as the most effective CH₄ reduction strategy. The highest reduction in CH₄ by 58.33% and 47.33% occurred when CH₄ production was negatively valued at AUD 0.60 c per kg of CH₄ and based on dry matter intake or residual feed intake, respectively. Negatively valuing CH₄ emissions in breeding objectives has support within this literature search with a focus on the selection of the most suitable phenotype for low-emission cattle. The inclusion of a CH₄ trait in breeding values such as the Balanced Performance Index is considered as a low-cost strategy requiring an update to the Australian Breeding Values and that is readily scaled to all beef and dairy sectors nationwide. Habitat restoration and the inclusion of a GHG subindex into the national breeding standards were ranked as the most effective strategies.

The top ten strategies to reduce CH₄ in a conservative scenario indicate no presence of ‘Avoid’ strategies, which is indicative of an economic focus. Land restoration strategies ranked very low in the conservative scenario due to the higher cost of land restoration compared to feed formulations and additives in a cost-saving scenario. Australian federal departments acknowledge the social and cultural benefits of wetland restoration [75] and land restoration policies align with IPCC’s mitigation of emissions approach to health and well-being typical of ‘Avoid’ scenarios.

No ‘Shift’ strategies ranked highly in any scenario in this study. When considering the IPCC’s assessment of demand-side strategies, plant-based diets represent the greatest ‘Shift’ potential of all ‘Shift’ strategies whilst increasing human health and well-being [30]. The IPCC acknowledges that feedback loops between dietary shifts and demand for production are often overlooked in LCA studies of dietary changes [77]. No research in this literature review presented Australian CH₄ reduction strategies which highlighted human health impacts. This indicates disconnect between human and environmental well-being.

‘Improve’ strategies dominated the conservative scenario with 100% of ‘Improve’ strategies in the top ten, 70% in the baseline, and 60% in the climate emergency scenario. Feed supplements, feed formulations, GHG subindexes and manure management dominated high-ranking ‘Improve’ strategies for all scenarios.

4.4. Strategies in Perspective

The dominance of ‘Improve’ strategies in the top strategies of the conservative scenario highlights the research focus on feed supplements for feedlot cattle and reduced economic capital. This focus on efficiency and feed inputs refers to reducing product-based emissions without regard for absolute emissions as demand is expected to grow and is reflected in Australia’s discussion paper about developing a net zero plan for agriculture [40]. The focus on improving breeding standards has highlighted the possibility of updating the Balanced Performance Index to include GHG emissions as a sub-index, but difficulties remain in determining an accurate genetic phenotype for low-emission cattle.

By comparison, the dominance of ‘Avoid’ strategies in the top strategies for climate emergencies highlights the focus to expand the narrow vision of efficiency per litre or kilogram of a product versus a whole-of-farm approach that includes overall emissions generated from the food system, including soil emissions, and can extend to processing and beyond-the-farm-gate processing. The Food and Agriculture Organization of the United Nations (FAO) [69] aligns with many of the ‘Improve’ strategies which contrast with IPCC’s [30] low-carbon high-wellbeing societies and the outcome of the meta-analysis of over 400 CH₄ reduction studies in the beef and dairy sector. While Arndt et al. [78] analysed the impact of combining various effective strategies, the authors found that a reduction in breeding activities through shifting to plant-based diets will ensure the agriculture sector achieves the 1.5 °C target by 2050.

4.5. Limitations of the Study

This study is limited by a range of methodological and research factors. Firstly, there was a lack of comprehensive data for most of the strategies included in the study, namely relating to the true cost of upfront capital required and ongoing costs of each strategy. Similarly, environmental impacts are limited to only CH₄ reduction and a fuller understanding of a strategy’s upstream and downstream effects via a lifecycle assessment would benefit the environmental categories greatly. Further limitations include the impacts of strategies on human health and social acceptability, which would align closer with the ASI framework and assessment of animal health as a result of any implemented strategies.

Also, this study is limited by the choice of methodology. Firstly, applying a ranking system does not allow a combination of strategies to be assessed, which may result in different outcomes. Additionally, this study is limited by reliance on secondary data and the lack of stakeholder engagement which could affect indicator attributes, weighting and social acceptability. Despite these limitations, this study still has value being the first and only available investigation to attempt ranking CH₄ reduction strategies in the Australian beef and dairy industry.

4.6. Recommendations and Future Research

By assessing the range of strategies available with robust qualitative evidence, supported by empirical data and robust methodology, this study can assist formulation of evidence-based targeted policies to address CH₄ emissions in Australia’s agricultural sector, in an approach similar to energy and transport decisions. Policymakers can leverage the insights gained from this research to develop informed and data-driven strategies aimed at mitigating CH₄ emissions. By acting on these recommendations and undertaking a MCDM approach to methodology, policymakers can capture the full benefits of converting agricultural land to natural habitat, which aligns with the need to critically engage in climate action this decade.

Based on the research and methodology described in the previous sections, it is recommended that policymakers implement ‘Avoid’ measures where feasibly possible to complement ‘Improve’ measures to achieve deep emissions reductions across the beef and dairy sector. Such a policy mix could include prioritization of agricultural land conversion and continued investment in research to determine accurate genetic phenotyping for greater certainty of CH₄ heritability traits to be included in national breeding objectives.

The identified limitations in this study pave the way for opportunities for future research, particularly in the context of deeper financial and environmental implications of CH₄ strategies focusing on Australia’s beef and dairy sector. Expanding the environmental assessment beyond CH₄ reduction to encompass a lifecycle assessment of strategies or content analysis to capture additional issues raised in the research would bolster the ecosystem-wide effects which can offer a more comprehensive view of the environmental impact, considering upstream and downstream effects and impact on planetary boundaries such as biodiversity impacts, land-use impacts, biogeochemical flows, water consumption, and resource consumption.

Methodologically speaking, future research could explore alternative evaluation frameworks that allow for the combination of strategies or assessment of data. This would address the limitation of the current ranking system and provide a more nuanced understanding of the synergies and trade-offs between different CH₄ reduction approaches. Additionally, narrowing the geographical scope of studies to a particular area or region would enhance the applicability of findings, ensuring a more convincing perspective to promote effective strategies.

Lastly, recognizing the importance of stakeholder engagement is vital and future research should incorporate views from all affected stakeholders to ensure a more accurate representation of concerns, priorities, perspectives and capture social acceptability. The co-creation of a decision-making framework can contribute to refining indicator attributes and weighting, making the assessment more reflective of the country’s diverse and dynamic landscape. Despite the acknowledged limitations, this study serves as a foundational step in ranking CH₄ reduction strategies, making future research opportunities even more critical in advancing the field and shaping evidence-based policies for beef and dairy production.

5. Concluding Remarks

To address the key research problem of what are the most effective strategies to reduce CH₄ emissions in the beef and dairy sector in Australia, a TOPSIS ranking method was undertaken which allowed us to estimate the most effective strategies available since 2020. With CH₄ reduction being a significant part of keeping the world a habitable space, addressing enteric emissions from ruminant animals remains critical. This research highlights the potency and lifespan of CH₄ as a key reason why this GHG is essential to reducing near- and long-term climate change impacts. With consistent formal underestimation of CH₄’s impact due to equivalating to carbon’s 100-year lifespan, accurate metrics, such as GWP* and standardized measurement of CH₄ techniques are needed to be implemented.

In total, 46 strategies from 27 articles on CH₄ reduction in Australia were ranked under three scenarios, namely, baseline, conservative, and climate emergency. The most effective were ‘Avoid’ strategies of conversion of agricultural land to wetlands, salt marshes, or tidal forest in the climate emergency scenario. By comparison, the most effective for the conservative and baseline scenarios was an ‘Improve’ strategy, namely the inclusion of CH₄ production in breeding goals associated with a high negative economic value. A policy mix of both measures is recommended for the industry to ensure significant and sustained emission reductions in line with industry, national, and international targets.