A review of whole farm systems models of greenhouse gas emissions from beef and dairy cattle production systems

Relevance of farm-scale indicators and tools for farmers to assess sustainability of their mixed crop-ruminant livestock systems

Ensuring the sustainability and circularity of mixed crop-ruminant livestock systems is essential if they are to deliver on the enhancement of long-term productivity and profitability with a smaller footprint. The objectives of this study were to select indicators in the environmental, economic and social dimensions of sustainability of crop-livestock systems, to assess if these indicators are relevant in the operational schedule of farmers, and to score the indicators in these farm systems. The scoring system was based on relevance to farmers, data availability, frequency of use, and policy. The study was successful in the assemblage of a suite of indicators comprising three dimensions of sustainability and the development of criteria to assess the usefulness of these indicators in crop-ruminant livestock systems in distinct agro-climatic regions across the globe. Except for ammonia emissions, indicators within the Emissions to air theme obtained high scores, as expected from mixed crop-ruminant systems in countries transitioning towards low emission production systems. Despite the inherent association between nutrient losses and water quality, the sum of scores was numerically greater for the former, attributed to a mix of economic and policy incentives. The sum of indicator scores within the Profitability theme (farm net income, expenditure and revenue) received the highest scores in the economic dimension. The Workforce theme (diversity, education, succession) stood out within the social dimension, reflecting the need for an engaged labor force that requires knowledge and skills in both crop and livestock husbandry. The development of surveys with farmers/stakeholders to assess the relevance of farm-scale indicators and tools is important to support direct actions and policies in support of sustainable mixed crop-ruminant livestock farm systems.

Environmental impacts of extensive beef production in Colombia by life cycle assessment: a case study

The increase in the negative effects of global change promotes the search for alternatives to supply the demand for food worldwide aligned with the Sustainable Development Goals (SDGs) to ensure food security. Animal protein, which is a main source of nutrients in the diet of today's society, especially beef, which is one of the most demanded products nowadays, has been criticized not only for its high water consumption and land occupation for production but also for the emission of greenhouse gases (GHG) from enteric methane generated in the fermentation process within the bovine rumen and deforestation for the adaptation of pastures. This study is mainly motivated by the lack of quantifiable scientific information in Colombia on the environmental impacts of beef production. Therefore, it is intended to estimate some of the impacts of beef production in extensive systems using the life cycle assessment (LCA) method under a particular scenario considering all the production phases (from raw material to fattening, where the cattle are ready to be slaughtered). The study was conducted with data supplied by a farm in Antioquia, Colombia, and the functional unit (FU) was defined as 1 kg of live weight (LW). The scope of this study was gate-to-gate. "The 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories" (IPCC  2006; IPCC 2019) was used to calculate methane and nitrous oxide emissions. LCA modeling was developed with Ecoinvent database v3.8 and the Umberto LCA + software. It was found that the most affected category of damage was ecosystem quality, which represents 77% of the total, followed by human health at 17% and resources at 6%. The category impact of agricultural land occupation is the one that represents the most significant contribution to the ecosystem quality endpoint, with a percentage of 87%, due to the soil's compaction and the loss of the soil's properties. Additionally, the obtained carbon footprint for the system was 28.9 kg of CO2-eq/kg LW.

Forage peanut legume as a strategy for improving beef production without increasing livestock greenhouse gas emissions

The transformation of pastures from a degraded state to sustainable productivity is a major challenge in tropical livestock production. Stoloniferous forage legumes such as Arachis pintoi (forage peanut) are one of the most promising alternatives for intensifying pasture-based beef livestock operations with reduced greenhouse gas (GHG) emissions. This 2-year study assessed beef cattle performance, nutrient intake and digestibility, and balance of GHG emissions in three pasture types (PT): (1) mixed Palisade grass - Urochloa brizantha (Hochst. ex A. Rich.) R.D. Webster (syn. Brachiaria brizantha Stapf cv. Marandu) and forage peanut (A. pintoi Krapov. & W.C. Greg. cv. BRS Mandobi) pastures (Mixed), (2) monoculture Palisade grass pastures with 150 kg of N/ha per year (Fertilised), and (3) monoculture Palisade grass without N fertiliser (Control). Continuous stocking with a variable stocking rate was used in a randomised complete block design, with four replicates per treatment. The average daily gain and carcass gain were not influenced by the PT (P = 0.439 and P = 0.100, respectively) and were, on average, 0.433 kg/animal per day and 83.4 kg/animal, respectively. Fertilised and Mixed pastures increased by 102 and 31.5%, respectively, the liveweight gain per area (kg/ha/yr) compared to the Control pasture (P < 0.001). The heifers in the Mixed pasture had lower CH4 emissions (g/animal per day; P = 0.009), achieving a reduction of 12.6 and 10.1% when compared to the Fertilised and Control pastures, respectively. Annual (N2O) emissions (g/animal) and per kg carcass weight gain were 59.8 and 63.1% lower, respectively, in the Mixed pasture compared to the Fertilised pasture (P < 0.001). Mixed pasture mitigated approximately 23% of kg CO2eq/kg of carcass when substituting 150 kg of N/ha per year via fertiliser. Mixed pastures with forage peanut are a promising solution to recover degraded tropical pastures by providing increased animal production with lower GHG emissions.

Life-cycle comparisons of economic and environmental consequences for pig production with four different models in China

China, the world's largest consumer and producer of pork in the world, is attracting increasing attention due to the environmental impacts of its pig production. Previous studies seldom comprehensively compare the environmental impacts of the pig production system with different models, resulting in different intensities of environmental impacts. We aim to comprehensively evaluate Chinese pig production with different breeding models and explore a more sustainable way for pig production. We use life cycle assessment (LCA) to evaluate and compare environmental impacts of pig production system with four main breeding models in China from 1998 to 2020: domestic breeding, small-scale breeding, medium-scale breeding, and large-scale breeding. The life cycle encompasses fertilizer production, feed production, feed processing, pig raising, waste treatment, and slaughtering. The impact categories including energy consumption (EN), global warming (GWP), acidification (AP), eutrophication (EU), water use (WD), and land occupation (LO) are expressed with "100 kg live weight of fattening pig at farm gate." The results show that driven by governmental support, growing meat demand, and cost advantage, the scale breeding especially large-scale breeding simultaneously yielded greater net economic benefit and less environmental impact compared to other breeding models especially the domestic breeding. Due to mineral fertilizer application, feed production contributed over 50% of the total environmental impacts. Notably, the composition of feeds exerted significant influence on the environmental impacts arising from fertilizer production and feed processing. Furthermore, attributable to the substantial use of electricity and heat, as well as the concomitant emissions, pig raising contributed the largest GWP, while ranking second in terms of AP and EU. Notably, waste management constituted the third-largest EU, AP, and WD. In addition to promote scale breeding, we put forth several sustainable measures encompassing feed composition, cultivation practices, fertilizer utilization, and waste management for consideration.

Life cycle assessment of greenhouse gas emission from the dairy production system - review

Climate change is altering ecological systems and poses a serious threat to human life. Climate change also seriously influences on livestock production by interfering with growth, reproduction, and production. Livestock, on the other hand, is blamed for being a significant contributor to climate change, emitting 8.1 gigatonnes of CO2-eq per year and accounting for two-thirds of global ammonia emissions. Methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2) are three major greenhouse gases (GHG) that are primarily produced by enteric fermentation, feed production, diet management, and total product output. Ruminants account for three-quarters of total CO2-equivalent (CO2-eq) emissions from the livestock sector. The global dairy sector alone emits 4.0% of global anthropogenic GHG emissions. Hence, dairy farming needs to engage in environmental impact assessment. Public concern for a sustainable and environmentally friendly farming system is growing, resulting in the significant importance of food-based life cycle assessment (LCA). Over the last decade, LCA has been used in agriculture to assess total GHG emissions associated with products such as milk and manure. It includes the production of farm inputs, farm emissions, milk processing, transportation, consumer use, and waste. LCA studies on milk production would assist us in identifying the specific production processes/areas that contribute to excessive greenhouse gas emissions when producing milk and recommending appropriate mitigation strategies to be implemented for a clean, green, and resilient environment.

Greenhouse Gas Emissions and Crossbred Cow Milk Production in a Silvopastoral System in Tropical Mexico

In Mexico, pasture degradation is associated with extensive pastures; additionally, under these conditions, livestock activities contribute considerably to greenhouse gas (GHG) emissions. Among the options to improve grazing systems and reduce GHG emissions, silvopastoral systems (SPS) have been recommended. The objectives of this work were to quantify the N outflow in a soil-plant-animal interface, as well as the CH₄ emissions and milk production in an SPS with woody legumes (Leucaena leucocephala) that is associated with stargrass (Cynodon nlemfuensis). This was then compared with stargrass in a monoculture system (MS) in the seasons (dry and rainy period) over a two-year period. Dung was collected from the animals of each of the grazing systems and applied fresh to the land plots. Fresh dung and urine were collected from the cows of each grazing system and were applied to the experimental plots. In addition, the soil CH₄ and N₂O contents were measured to quantify the emissions. Average milk yield by seasons was similar: MS (7.1 kg per animal unit (AU)/day^-1) and SPS (6.31 kg per AU/day^-1). Cows in the MS had a mean N intake of 171.9 g/UA day^-1 without seasonal variation, while the SPS animals' mean N intake was 215.7 g/UA day^-1 for both seasons. For the urine applied to soil, the N₂O outflow was higher in the MS (peak value = 1623.9 μg N-N₂O m^-2 h^-1). The peak value for the SPS was 755.9 μg of N-N₂O m^-2 h^-1. The N₂O emissions were higher in the rainy season (which promotes denitrification). The values for the feces treatment were 0.05% (MS) and 0.01% (SPS). The urine treatment values were 0.52% (MS) and 0.17% (SPS). The emissions of CH₄ showed that the feces of the SPS systems resulted in a higher accumulation of gas in the rainy season (29.8 g C ha^-1), followed by the feces of the MS system in the dry season (26.0 g C ha^-1). Legumes in the SPS helped to maintain milk production, and the N₂O emissions were lower than those produced by the MS (where the pastures were fertilized with N).

Chilean public attitudes towards beef production systems

Much is discussed about the characteristics, efficiency, and externalities of indoor housing and pasture-based beef production systems, but little is known about how these features influence public attitudes towards beef production. This study aimed to explore Chilean citizens' attitudes towards beef production systems and their underlying reasons. Citizens (n = 1,084) were recruited to participate in a survey and given information about one beef production system: indoor housing, continuous grazing or regenerative grazing. Participants had more favourable attitudes (from 1 = most negative attitudes to 5 = most positive attitudes) towards pasture-based systems (regenerative grazing = 2.94; continuous grazing = 2.83) than towards indoor housing (1.94), mainly due to concerns with animal welfare and environmental impacts. Productivity was not as important as the other sustainability aspects for participants as they were not willing to do that trade-off. Support for beef production may benefit if production systems adopt characteristics that are perceived by the public as positive for the environment and animal welfare.

Can the broiler industry rely on results of existing life cycle assessment and environmental assessments studies to inform broilers' nutritional strategies?

The goal of this systematic review is to investigate the applicability of the results from existing life cycle analysis (LCA) and environmental assessments studies in informing nutritional strategies for environmentally sustainable poultry meat production. This paper reports on a Rapid Evidence Assessment (REA) of articles published between 2000 and 2020. The studies reviewed were conducted in developed countries including UK, France, Germany, Sweden, Norway, The Netherlands, Denmark, Belgium, Canada, and USA. All articles were written in English. The REA includes studies on LCA of differing strains of meat poultry and production systems, studies on poultry manure emission and studies on environmental assessments of plant-based feed ingredients. The review covered studies on soil carbon dynamics associated with plant-based ingredients. Web of Science, Scopus, and PubMed were used to obtain the 6,142 population articles. The multistage screening process resulted in 29 studies from which 15 studies included LCA while the rest 14 studies analyzed NH₃ emission of broilers. All studies based on LCA were descriptive and did not include replications. Only 12 studies assessed the effect of interventions to reduce NH₃ emission of broiler litter using replicated layout designs. It is concluded that the broiler industry in UK, EU, and North America cannot rely on results of existing LCA and environmental assessments studies to inform their nutritional strategy and poultry meat production due to a shortage of reliable in vivo data assessing interventions in controlled studies.

Environmental advantages of coproducing beef meat in dairy systems

Beef meat, one of the more environmentally costly animal-based foods, can be produced in two general ways, as the main product on specialised farms or as a co-product on dairy farms. In this study, two cases (a semi-confinement dairy farm (A) and a pasture-based dairy farm (B)) have been analysed by means of LCA to evaluate the environmental impacts associated with the coproduction of beef meat. In both cases, purchased feed production was found to be the main cause of environmental impacts in most of the categories considered. Additionally, cow emissions to air were the main contributor for the global warming category. Comparing the two dairy systems, notably lower environmental impacts were obtained for B in 13 of the 18 categories analysed. Regarding CF, 8.10 and 8.88 kg CO₂eq/kg LW were obtained for A and B, respectively. These CF values were within the wide range found in the literature for beef meat (1.2-42.6 kg CO₂eq/kg LW). Beef calves and cull cows are an important output of dairy farming, so that coproduction enables milk and meat with lower CF and associated environmental impacts to be obtained. In addition, the variability of the data found in literature and the lack of LCA studies based on real data for beef meat coproduced on dairy farms evidence the importance of in-depth study of this interesting topic.

Life cycle assessment of Parmigiano Reggiano PDO cheese with product environmental footprint method: A case study implementing improved slurry management strategies

The environmental impact of Parmigiano Reggiano PDO cheese was quantified using the Product Environmental Footprint Category Rules (PEFCRs) in a Traditional System (TS) and in an Improved Management System (IMS). The TS differs from IMS with respect to slurry management (raw slurry storage vs anaerobic digestion and storage of the liquid fraction of digestate) and application of nutrients to the field (by slurry tanker with a diverter plate vs soil injection at pre-sowing and side dressing). Two additional scenarios were evaluated by considering the possible environmental enhancement achievable by reducing enteric methane production and by using soybean grain produced in Italy as the protein source for animals' diets. The environmental impact was quantified both for 1 kg of fat and protein corrected milk (FPCM) and for the production of 10 g dry matter equivalent of cheese as single score. For the first assessment, the environmental impact results were 124 and 112 μPt kg FPCM^-1 for TS and IMS, respectively. In the second case, it was 10.8 μPt and 9.9 μPt 10 g dry matter equivalent^-1 of cheese, for TS and IMS, respectively. The specific cost for reducing the GHG emissions in this production chain was equal to 34 € Mg^-1 milk produced. Finally, although specific studies should consider the reduction of enteric methane emissions and the use of soybean grain nationally produced as feed source, the scenarios evaluated in this study highlighted some potential for environmental improvements. Even small environmental improvements to the Parmigiano Reggiano PDO cheese supply chain can bring substantial improvements to the sustainability of the food market, because of the widespread demand on the global market of Parmigiano Reggiano and of its chance of attracting consumers who are sensitive to environmental problems.

Greenhouse Gas Emissions from Beef Cattle Breeding Based on the Ecological Cycle Model

Over the past few decades, the supply of beef has increasingly become available with the great improvement of the quality of life, especially in developing countries. However, along with the demand for meat products of high quality and the transformation of dietary structure, the impact of massive agricultural greenhouse gas emissions on the environmental load cannot be ignored. Therefore, the objective of this study is to predict the annual greenhouse gas emissions of 10 million heads of beef cattle under both the ecological cycle model (EC model) and the non-ecological cycle model (non-EC model), respectively, in order to compare the differences between these two production models in each process, and thus explore which one is more sustainable and environmentally friendly. To this end, through the life cycle assessment (LCA), this paper performs relevant calculations according to the methodology of 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (2019 IPCC Inventories). The results have shown that the total GHG emissions of the non-EC model were almost 4 times higher than those of the EC model, and feed-grain cultivation and manure management were main emission sources in both models. The non-EC model produced significantly more emissions than the EC model in each kind of GHG, especially the largest gap between these two was in CO₂ emissions that accounted for 68.01% and 56.17% of the respective planting and breeding systems. This study demonstrates that the transformation of a beef cattle breeding model has a significant direct impact on cutting agricultural GHG emissions, and persuades other countries in the similar situation to vigorously advocate ecological cycling breeding model instead of the traditional ones so that promotes coordinated development between planting industry and beef cattle breeding industry.

LCA to Estimate the Environmental Impact of Dairy Farms: A Case Study

Intensive farming is responsible for extreme environmental impacts under different aspects, among which global warming represents a major reason of concern. This is a quantitative problem linked to the farm size and a qualitative one, depending on farming methods and land management. The dairy sector is particularly relevant in terms of environmental impact, and new approaches to meeting sustainability goals at a global scale while meeting society’s needs are necessary. The present study was carried out to assess the environmental impact of dairy cattle farms based on a life cycle assessment (LCA) model applied to a case study. These preliminary results show the possibility of identifying the most relevant impacts in terms of supplied products, such as animal feed and plastic packaging, accounting for 19% and 15% of impacts, respectively, and processes, in terms of energy and fuel consumption, accounting for 53% of impacts overall. In particular, the local consumption of fossil fuels for operations within the farm represents the most relevant item of impact, with a small margin for improvement. On the other hand, remarkable opportunities to reduce the impact can be outlined from the perspective of stronger partnerships with suppliers to promote the circularity of packaging and the sourcing of animal feed. Future studies may include the impact of drug administration and the analysis of social aspects of LCA.

Assessing the carbon footprint across the supply chain: Cow milk vs soy drink

Since livestock product consumption could have a significant effect on tackling climate change, in the few last years, there has been an increasing consumer demand for non-dairy alternatives. Despite plant-based beverages being considered crucial to foster the transition towards sustainable diet models, no studies have yet compared the level of emissions of plant-based beverages with animal-based ones. The present study aims at computing the carbon footprint of cow milk and that of soy drink and evaluating the carbon footprint results in the light of the substitutability of cow's milk with soy drink, analyzing the potential environmental, economic and nutritional trade-offs between the two products. Results highlight that, considering the environmental perspective, soy drink could be a valid substitute of cow milk: its production has a lower carbon footprint, allowing for the achievement of food security objectives. However, focusing on the economic and nutritional perspectives, the high average consumer price of soy drink is associated with an overall lower nutritional level. In order to reach the same nutritional value as 1 L of cow milk in terms of protein intake, the consumption of soy drink should be increased by 13%. Furthermore, soy drink consumption implies paying 66% more than for cow milk, when considering the same protein content.

Understanding methane emission from stored animal manure: A review to guide model development

National inventories of methane (CH₄ ) emission from manure management are based on guidelines from the Intergovernmental Panel on Climate Change using country-specific emission factors. These calculations must be simple and, consequently, the effects of management practices and environmental conditions are only crudely represented in the calculations. The intention of this review is to develop a detailed understanding necessary for developing accurate models for calculating CH₄ emission from liquid manure, with particular focus on the microbiological conversion of organic matter to CH₄ . Themes discussed are (a) the liquid manure environment; (b) methane production processes from a modeling perspective; (c) development and adaptation of methanogenic communities; (d) mass and electron conservation; (e) steps limiting CH₄ production; (f) inhibition of methanogens; (g) temperature effects on CH₄ production; and (h) limits of existing estimation approaches. We conclude that a model must include calculation of microbial response to variations in manure temperature, substrate availability and age, and management system, because these variables substantially affect CH₄ production. Methane production can be reduced by manipulating key variables through management procedures, and the effects may be taken into account by including a microbial component in the model. When developing new calculation procedures, it is important to include reasonably accurate algorithms of microbial adaptation. This review presents concepts for these calculations and ideas for how these may be carried out. A need for better quantification of hydrolysis kinetics is identified, and the importance of short- and long-term microbial adaptation is highlighted.

Evaluation of Feed Strategies and Changes of Stocking Rate to Decrease the Carbon Footprint in a Traditional Cow-Calf System: A Simulation Model

One of the main production challenges associated with climate change is the reduction of carbon emissions. Increasing the efficiency of resource utilization is one way to achieve this purpose. The modification of production systems through improved reproductive, genetic, feed, and grazing management practices has been proposed to increase technical–economic efficiency, even though the “environmental viability” of these modifications has not always been evaluated. The objective of this study was to evaluate the use of feeding and management strategies on the carbon footprint (CF) and economic variables in the traditional cow–calf system in southern Chile using a simulation model. The modifications evaluated corresponded to combinations of stocking rate, use of creep feeding practices with different supplementation levels, and the incorporation of feed additives to the supplement, using factorial experiments. Additionally, the scenarios were evaluated with and without carbon sequestration. The CF for the baseline scenarios was 12.5 ± 0.3 kg of CO_2−eq/kg of live weight (LW) when carbon sequestration was considered and 13.0 ± 0.4 kg of CO_2−eq/kg of LW in the opposite case. Changes in stocking rate, supplementation level, and consideration of carbon sequestration in pasture and soil had a significant effect on the CF in all simulated scenarios. The inclusion of additives in the supplement did not have a significant effect on production costs. With regard to reducing greenhouse gas (GHG) emissions, incorporating canola oil presented the best average results. The model developed made the selection of environmentally viable feed strategies or management adaptations possible.

Life cycle assessment of pasture-based suckler steer weanling-to-beef production systems: Effect of breed and slaughter age

Demand for beef produced from pasture-based diets is rising as it is perceived to be healthier, animal friendly and good for the environment. Animals reared on a solely grass forage diet, however, have a lower growth rate than cereal-fed animals and consequently are slaughtered at an older age. This study focused on the former by conducting life cycle assessments of beef production systems offering only fresh or conserved grass, and comparing them to a conventional pasture-based beef production system offering concentrate feeding during housing. The four suckler weanling-to-beef production systems simulated were: (i) Steers produced to slaughter entirely on a grass forage diet at 20 months (GO-20); (ii) Steers produced to slaughter entirely on a grass forage diet at 24 months (GO-24); (iii) Steers produced to slaughter on a grass forage diet with concentrate supplementation during housing (GC-24), and (iv) Steers produced to slaughter entirely on a grass forage diet at 28 months (GO-28). Two breed types were evaluated: early-maturing and late-maturing (LM). The environmental impacts assessed were global warming potential (GWP), non-renewable energy (NRE), acidification potential (AP), eutrophication potential (marine (MEP) and freshwater) were expressed per animal, per kg live weight gain (LWG), kg carcass weight gain, and kg meat weight gain (MWG). The GO-20 production system had the lowest environmental impact across all categories and functional units for both breeds. Extending age at slaughter increased environmental impact across all categories per animal. The LWG response of EM steers to concentrate feed supplementation in GC-24 was greater than the increase in total environmental impact resulting in GC-24 having a lower environmental impact across categories per kg product than GO-24. Concentrate feed supplementation had a similar effect on LM steers with the exception of NRE and AP. The increase in daily LWG in the third grazing season in comparison to the second grazing and housing resulted in GO-28 having lower GWP, NRE, AP, and MEP per kg product than GO-24. Early-maturing steers had lower environmental impact than LM when expressed per kg LWG. However the opposite occurred when impacts were expressed per kg MWG, despite LM steers producing the least LWG. The LM steers compensated for poor LWG performance by having superior carcass traits, which caused the breed to have the lowest environmental impact per kg MWG. The results reaffirms the importance of functional unit and suggests reducing the environmental impact of LWG does not always translate into improvements in the environmental performance of meat.

Modelling the Distribution of the Red Macroalgae Asparagopsis to Support Sustainable Aquaculture Development

Fermentative digestion by ruminant livestock is one of the main ways enteric methane enters the atmosphere, although recent studies have identified that including red macroalgae as a feed ingredient can drastically reduce methane produced by cattle. Here, we utilize ecological modelling to identify suitable sites for establishing aquaculture development to support sustainable agriculture and Sustainable Development Goals 1 and 2. We used species distributions models (SDMs) parameterized using an ensemble of multiple statistical and machine learning methods, accounting for novel methodological and ecological artefacts that arise from using such approaches on non-native and cultivated species. We predicted the current distribution of two Asparagopsis species to high accuracy around the coast of Ireland. The environmental drivers of each species differed depending on where the response data was sourced from (i.e., native vs. non-native), suggesting that the length of time A. armata has been present in Ireland may mean it has undergone a niche shift. Subsequently, researchers looking to adopt SDMs to support aquaculture development need to acknowledge emerging conceptual issues, and here we provide the code needed to implement such research, which should support efforts to effectively choose suitable sites for aquaculture development that account for the unique methodological steps identified in this research.

The simulated environmental impact of incorporating white clover into pasture-based dairy production systems

White clover (WC) offers an alternative source of nitrogen (N) for pasture-based systems. Substituting energy- and carbon-intensive synthetic N fertilizers with N derived from biological fixation by WC has been highlighted as a promising environmental mitigation strategy through the omission of emissions, pollutants, and energy usage during the production and application of synthetic fertilizer. Therefore, the objective was to investigate the effect of the inclusion of WC in perennial ryegrass (PRG) swards on the environmental impact of pasture-based dairy systems. Cradle-to-farm gate life cycle assessment of 3 pasture-based dairy systems were conducted: (1) a PRG-WC sward receiving 150 kg of N/ha per year (CL150), (2) a PRG-WC sward receiving 250 kg of N/ha per year (CL250), and (3) a PRG-only sward receiving 250 kg of N/ha per year (GR250). A dairy environmental model was updated with country-specific N excretion equations and recently developed N₂O, NH₃, and NO₃^- emission factors. The environmental impact categories assessed were global warming potential, nonrenewable energy, acidification potential, and eutrophication potential (marine and freshwater). Impact categories were expressed using 2 functional units: per hectare and per metric tonne of fat- and protein-corrected milk. The GR250 system had the lowest milk production and highest global warming potential, nonrenewable energy, and acidification potential per tonne of fat- and protein-corrected milk for all systems. The CL250 system produced the most milk and had the highest environmental impact across all categories when expressed on an area basis. It also had the highest marine eutrophication potential for both functional units. The impact category freshwater eutrophication potential did not differ across the 3 systems. The CL150 system had the lowest environmental impact across all categories and functional units. This life cycle assessment study demonstrates that the substitution of synthetic N fertilizer with atmospheric N fixed by WC has potential to reduce the environmental impact of intensive pasture-based dairy systems in temperate regions, not only through improvement in animal performance but also through the reduction in total emissions and pollutants contributing to the environmental indicators assessed.

Environmental Impacts of Milking Cows in Latvia

Increasing pressures surrounding efficiency and sustainability are key global drivers in dairy farm management strategies. However, for numerous resource-based, social, and economic reasons sustainable intensification strategies are herd-size dependent. In this study, we investigated the environmental impacts of Latvia’s dairy farms with different management practices. The herd size-dependent management groups varied from extensively managed small herds with 1–9 cows, extending to stepwise more intensively managed herds with 10–50, 51–100, 100–200, and over 200 milking cows. The aim is to compare the environmental impacts of different size-based production strategies on Latvia’s dairy farms. The results show that the gross greenhouse gas emissions differ by 29%: from 1.09 kg CO2 equivalents (CO2e) per kg of raw milk for the farms with 51–100 cows, down to 0.84 kg CO2e/kg milk for farms with more than 200 cows. However, the land use differs even more—the largest farms use 2.25 times less land per kg of milk than the smallest farms. Global warming potential, marine eutrophication, terrestrial acidification, and ecotoxicity were highest for the mid-sized farms. If current domestic, farm-based protein feeds were to be substituted with imported soy feed (one of the most popular high-protein feeds) the environmental impacts of Latvian dairy production would significantly increase, e.g., land use would increase by 18% and the global warming potential by 43%. Environmental policy approaches for steering the farms should consider the overall effects of operation size on environmental quality, in order to support the best practices for each farm type and steer systematic change in the country. The limitations of this study are linked to national data availability (e.g., national data on feed production, heifer breeding, differences among farms regards soil type, manure management, the proximity to marine or aquatic habitats) and methodological shortcomings (e.g., excluding emissions of carbon sequestration, the use of proxy allocation, and excluding social and biodiversity impacts in life-cycle assessment). Further research is needed to improve the data quality, the allocation method, and provide farm-size-specific information on outputs, heifer breeding, manure storage, and handling.

Carbon Footprint Assessment of Spanish Dairy Cattle Farms: Effectiveness of Dietary and Farm Management Practices as a Mitigation Strategy

Simple Summary

Livestock production has been identified as an important source of greenhouse gas emissions. The current study was conducted to quantify the carbon footprint of Spanish dairy farms and to evaluate the potential of nutritional and management practices for mitigating methane emissions at farm level. The carbon footprint ranged from 0.67 to 0.98 kg CO₂-eq/kg of energy corrected milk. Simulation scenarios showed that methane emissions and the carbon footprint of milk could be reduced more through management practices rather than dietary strategies. Modelling may provide policy makers, farmers and stakeholders valuable information for planning and developing strategies to reduce the carbon footprint associated with milk production.

Abstract

Greenhouse gas emissions and the carbon footprint (CF) were estimated in twelve Spanish dairy farms selected from three regions (Mediterranean, MED; Cantabric, CAN; and Central, CEN) using a partial life cycle assessment through the Integrated Farm System Model (IFSM). The functional unit was 1 kg of energy corrected milk (ECM). Methane emissions accounted for the largest contribution to the total greenhouse gas (GHG) emissions. The average CF (kg CO₂-eq/kg of ECM) was 0.84, being the highest in MED (0.98), intermediate in CEN (0.84), and the lowest in CAN (0.67). Two extreme farms were selected for further simulations: one with the highest non-enteric methane (MED1), and another with the highest enteric methane (CAN2). Changes in management scenarios (increase milk production, change manure collection systems, change manure-type storage method, change bedding type and installation of an anaerobic digester) in MED1 were evaluated with the IFSM model. Changes in feeding strategies (reduce the forage: concentrate ratio, improve forage quality, use of ionophores) in CAN2 were evaluated with the Cornell Net Carbohydrate and Protein System model. Results indicate that changes in management (up to 27.5% reduction) were more efficient than changes in dietary practices (up to 3.5% reduction) in reducing the carbon footprint.

Dairy Cow Health and Greenhouse Gas Emission Intensity

The purpose of this review is to identify the main influencing factors related to dairy cow health as it impacts the intensity of greenhouse gas emissions considering known data presented in the literature. For this study, we define the emission intensity as CO2 equivalents per kilogram of milk. In dairy cows, a high dry matter (DM) intake (25 kg/d) leads to an higher absolute methane emission compared to a lower DM intake (10 kg/d). However, the emission intensity is decreased at a high performance level. The emissions caused by DM intake to cover the energy requirement for maintenance are distributed over a higher milk yield. Therefore, the emission intensity per kilogram of product is decreased for high-yielding animals with a high DM intake. Apart from that, animal diseases as well as poor environmental or nutritional conditions are responsible for a decreased DM intake and a compromised performance. As a result, animal diseases not only mean reduced productivity, but also increased emission intensity. The productive life-span of a dairy cow is closely related to animal health, and the impact on emission intensity is enormous. A model calculation shows that cows with five to eight lactations could have a reduced emission intensity of up to 40% compared to animals that have left the herd after their first lactation. This supports the general efforts to increase longevity of dairy cows by an improved health management including all measures to prevent diseases.

Methane production and estimation from livestock husbandry: A mechanistic understanding and emerging mitigation options

Globally, livestock is an important contributor to methane (CH₄) emissions. This paper reviewed the various CH₄ measurement and estimation techniques and mitigation approaches for the livestock sector. Two approaches for enteric livestock CH₄ emission estimation are the top-down and bottom-up. The combination of both could further improve our understanding of enteric CH₄ emission and possible mitigation measures. We discuss three mitigation approaches: reducing emissions, avoiding emissions, and enhancing the removal of emissions from livestock. Dietary management, livestock management, and breeding management are viable reducing emissions pathways. Dietary manipulation is easily applicable and can bring an immediate response. Economic incentive policies can help the livestock farmers to opt for diet, breeding, and livestock management mitigation approaches. Carbon pricing creates a better option to achieve reduction targets in a given period. A combination of carbon pricing, feeding management, breeding management, and livestock management is more feasible and sustainable CH₄ emissions mitigation strategy rather than a single approach.

Can technology help achieve sustainable intensification? Evidence from milk recording on Irish dairy farms

This article explores the potential of a farm technology to simultaneously improve farm efficiency and provide wider environmental and social benefits. Identifying these 'win-win-win' strategies and encouraging their widespread adoption is critical to achieve sustainable intensification. Using a nationally representative sample of 296 Irish dairy farms from 2015, propensity score matching is applied to measure the impact of milk recording on a broad set of farm sustainability indicators. The findings reveal that the technology enhances economic sustainability by increasing dairy gross margin and milk yield per cow. Furthermore, social sustainability is improved through a reduction in milk bulk tank somatic cell count (an indicator of animal health and welfare status). Conversely, milk recording (as it is currently implemented) does not impact farm environmental sustainability, represented by greenhouse gas emission efficiency. While the study shows that milk recording is a 'win-win' strategy, ways of improving current levels of utilisation are discussed so that milk recording achieves its 'win-win-win' potential in the future.

Organic Farming as a Strategy to Reduce Carbon Footprint in Dehesa Agroecosystems: A Case Study Comparing Different Livestock Products

This study employs life cycle assessment (LCA) for the calculation of the balance (emissions minus sequestration) of greenhouse gas emissions (GHG) in the organic livestock production systems of dehesas in the southwest region of Spain. European organic production standards regulate these systems. As well as calculating the system's emissions, this method also takes into account the soil carbon sequestration values. In this sense, the study of carbon sequestration in organic systems is of great interest from a legislation viewpoint. The results reveal that the farms producing meat cattle with calves sold at weaning age provide the highest levels of carbon footprint (16.27 kg of carbon dioxide equivalent (CO2eq)/kg of live weight), whereas the farms with the lowest levels of carbon emissions are montanera pig and semi-extensive dairy goat farms, i.e., 4.16 and 2.94 kg CO2eq/kg of live weight and 1.19 CO2eq/kg of fat and protein corrected milk (FPCM), respectively. Enteric fermentation represents 42.8% and 79.9% of the total emissions of ruminants' farms. However, in pig farms, the highest percentage of the emissions derives from manure management (36.5%-42.9%) and animal feed (31%-37.7%). The soil sequestration level has been seen to range between 419.7 and 576.4 kg CO2eq/ha/year, which represents a considerable compensation of carbon emissions. It should be noted that these systems cannot be compared with other more intensive systems in terms of product units and therefore, the carbon footprint values of dehesa organic systems must always be associated to the territory.

Predicting nitrous oxide emissions after the application of solid manure to grassland in the United Kingdom

Nitrous oxide (N₂ O) emission from agricultural soils represents a significant source of greenhouse gas to the atmosphere. We evaluated the suitability of a modified Soil and Water Assessment Tool (SWAT) model to estimate the N₂ O flux from the application of solid manure at two grassland sites (North Wyke [NW] and Pwllpeiran [PW]) in the United Kingdom. The simulated N₂ O emissions were validated against field observations measured in 2011 and 2012 for model calibration and validation, respectively. The SWAT model predicts water-filled pore space (WFPS) very well with Nash-Sutcliffe efficiency (NSE), R² , RMSE, and percentage bias (PBIAS) values of 0.67, .72, 0.06, and 3.64, respectively, during the calibration period for NW site, whereas it gives 0.68, .69, 0.07, and 3.04, respectively during the validation period. At PW, the model predicted the NSE, R² , RMSE, and PBIAS of 0.55, .69, 0.04, and -4.5, respectively, during calibration and 0.63, .71, 0.05, and -2.6, respectively, during the validation period. Compared with WFPS, the model resulted in a slightly lower fit for N₂ O emissions for NW (NSE = 0.47, R²  = .63 during calibration, and NSE = 0.55, R²  = .58 during validation) and for PW (NSE = 0.54, R²  = .71 for calibration, and NSE = 0.47, R²  = .69 for validation). Results revealed that the SWAT model performed reasonably well in representing the dynamics of N₂ O emissions after solid manure application to grassland.

LIFE BEEF CARBON: a common framework for quantifying grass and corn based beef farms' carbon footprints

Europe’s roadmap to a low-carbon economy aims to cut greenhouse gas (GHG) emissions 80% below 1990 levels by 2050. Beef production is an important source of GHG emissions and is expected to increase as the world population grows. LIFE BEEF CARBON is a voluntary European initiative that aims to reduce GHG emissions per unit of beef (carbon footprint) by 15% over a 10-year period on 2172 farms in four large beef-producing countries. Changes in farms beef carbon footprint are normally estimated via simulation modelling, but the methods current models apply differ. Thus, our initial goal was to develop a common modelling framework to estimate beef farms carbon footprint. The framework was developed for a diverse set of Western Europe farms located in Ireland, Spain, Italy and France. Whole farm and life cycle assessment (LCA) models were selected to quantify emissions for the different production contexts and harmonized. Carbon Audit was chosen for Ireland, Bovid-CO₂ for Spain and CAP’2ER for France and Italy. All models were tested using 20 case study farms, that is, 5 per country and quantified GHG emissions associated with on-farm live weight gain. The comparison showed the ranking of beef systems gross carbon footprint was consistent across the three models. Suckler to weaning or store systems generally had the highest carbon footprint followed by suckler to beef systems and fattening beef systems. When applied to the same farm, Carbon Audit’s footprint estimates were slightly lower than CAP’2ER, but marginally higher than Bovid-CO₂. These differences occurred because the models were adapted to a specific region’s production circumstances, which meant their emission factors for key sources; that is, methane from enteric fermentation and GHG emissions from concentrates were less accurate when used outside their target region. Thus, for the common modelling framework, region-specific LCA models were chosen to estimate beef carbon footprints instead of a single generic model. Additionally, the Carbon Audit and Bovid-CO₂ models were updated to include carbon removal by soil and other environmental metrics included in CAP’2ER, for example, acidification. This allows all models to assess the effect carbon mitigation strategies have on other potential pollutants. Several options were identified to reduce beef farms carbon footprint, for example, improving genetic merit. These options were assessed for beef systems, and a mitigation plan was created by each nation. The cumulative mitigation effect of the LIFE BEEF CARBON plan was estimated to exceed the projects reduction target (−15%).

The Carbon Footprint of Energy Consumption in Pastoral and Barn Dairy Farming Systems: A Case Study from Canterbury, New Zealand

Dairy farming is constantly evolving to more intensive systems of management, which involve more consumption of energy inputs. The consumption of these energy inputs in dairy farming contributes to climate change both with on-farm emissions from the combustion of fossil fuels, and by off-farm emissions due to production of farm inputs (such as fertilizer, feed supplements). The main purpose of this research study was to evaluate energy-related carbon dioxide emissions, the carbon footprint, of pastoral and barn dairy systems located in Canterbury, New Zealand. The carbon footprints were estimated based on direct and indirect energy sources. The study results showed that, on average, the carbon footprints of pastoral and barn dairy systems were 2857 kgCO2 ha−1 and 3379 kgCO2 ha−1, respectively. For the production of one tonne of milk solids, the carbon footprint was 1920 kgCO2 tMS−1 and 2129 kgCO2 tMS−1, respectively. The carbon emission difference between the two systems indicates that the barn system has 18% and 11% higher carbon footprint than the pastoral system, both per hectare of farm area and per tonne of milk solids, respectively. The greater carbon footprint of the barn system was due to more use of imported feed supplements, machinery usage and fossil fuel (diesel and petrol) consumption for on-farm activities.

Review: Analysis of the process and drivers for cellular meat production

Cell-based meat, also called 'clean', lab, synthetic or in vitro meat, has attracted much media interest recently. Consumer demand for cellular meat production derives principally from concerns over environment and animal welfare, while secondary considerations include consumer and public health aspects of animal production, and food security. The present limitations to cellular meat production include the identification of immortal cell lines, availability of cost-effective, bovine-serum-free growth medium for cell proliferation and maturation, scaffold materials for cell growth, scaling up to an industrial level, regulatory and labelling issues and at what stage mixing of myo-, adipo- and even fibrocytes can potentially occur. Consumer perceptions that cell-based meat production will result in improvements to animal welfare and the environment have been challenged, with the outcome needing to wait until the processes used in cell-based meat are close to a commercial reality. Challenges for cell-based meat products include the simulation of nutritional attributes, texture, flavour and mouthfeel of animal-derived meat products. There is some question over whether consumers will accept the technology, but likely there will be acceptance of cell-based meat products, in particular market segments. Currently, the cost of growth media, industry scale-up of specific components of the cell culture process, intellectual property sharing issues and regulatory hurdles mean that it will likely require an extended period for cellular meat to be consistently available in high-end restaurants and even longer to be available for the mass market. The progress in plant-based meat analogues is already well achieved, with products such as the ImpossibleTM Burger and other products already available. These developments may make the development of cellular meat products obsolete. But the challenges remain of mimicking not only the nutritional attributes, flavour, shape and structure of real meat, but also the changes in regulation and labelling.

ASN-ASAS SYMPOSIUM: FUTURE OF DATA ANALYTICS IN NUTRITION: Mathematical modeling in ruminant nutrition: approaches and paradigms, extant models, and thoughts for upcoming predictive analytics1,2

This paper outlines typical terminology for modeling and highlights key historical and forthcoming aspects of mathematical modeling. Mathematical models (MM) are mental conceptualizations, enclosed in a virtual domain, whose purpose is to translate real-life situations into mathematical formulations to describe existing patterns or forecast future behaviors in real-life situations. The appropriateness of the virtual representation of real-life situations through MM depends on the modeler's ability to synthesize essential concepts and associate their interrelationships with measured data. The development of MM paralleled the evolution of digital computing. The scientific community has only slightly accepted and used MM, in part because scientists are trained in experimental research and not systems thinking. The scientific advancements in ruminant production have been tangible but incipient because we are still learning how to connect experimental research data and concepts through MM, a process that is still obscure to many scientists. Our inability to ask the right questions and to define the boundaries of our problem when developing models might have limited the breadth and depth of MM in agriculture. Artificial intelligence (AI) has been developed in tandem with the need to analyze big data using high-performance computing. However, the emergence of AI, a computational technology that is data-intensive and requires less systems thinking of how things are interrelated, may further reduce the interest in mechanistic, conceptual MM. Artificial intelligence might provide, however, a paradigm shift in MM, including nutrition modeling, by creating novel opportunities to understand the underlying mechanisms when integrating large amounts of quantifiable data. Associating AI with mechanistic models may eventually lead to the development of hybrid mechanistic machine-learning modeling. Modelers must learn how to integrate powerful data-driven tools and knowledge-driven approaches into functional models that are sustainable and resilient. The successful future of MM might rely on the development of redesigned models that can integrate existing technological advancements in data analytics to take advantage of accumulated scientific knowledge. However, the next evolution may require the creation of novel technologies for data gathering and analyses and the rethinking of innovative MM concepts rather than spending resources in collecting futile data or amending old technologies.

Livestock Performance for Sheep and Cattle Grazing Lowland Permanent Pasture: Benchmarking Potential of Forage-Based Systems

Here we describe the livestock performance and baseline productivity over a two-year period, following the establishment of the infrastructure on the North Wyke Farm Platform across its three farmlets (small farms). Lowland permanent pastures were continuously stocked with yearling beef cattle and ewes and their twin lambs for two years in three farmlets. The cattle came into the farmlets as suckler-reared weaned calves at 195 ± 32.6 days old weighing 309 ± 45.0 kg, were housed indoors for 170 days then turned out to graze weighing 391 ± 54.2 kg for 177 days. Therefore, it is suggested for predominantly grass-based systems with minimal supplementary feeding that target live weight gains should be 0.5 kg/day in the first winter, 0.9 kg/day for summer grazing and 0.8 kg/day for cattle housed and finished on silage in a second winter. The sheep performance suggested that lambs weaned at 100 days and weighing 35 kg should finish at 200 days weighing 44 to 45 kg live weight with a killing out percentage of 44%. Good levels of livestock production are possible with grass and forage-based systems using little or no additional supplementary concentrate feeds.

How do farm models compare when estimating greenhouse gas emissions from dairy cattle production?

The European Union Effort Sharing Regulation (ESR) will require a 30% reduction in greenhouse gas (GHG) emissions by 2030 compared with 2005 from the sectors not included in the European Emissions Trading Scheme, including agriculture. This will require the estimation of current and future emissions from agriculture, including dairy cattle production systems. Using a farm-scale model as part of a Tier 3 method for farm to national scales provides a more holistic and informative approach than IPCC (2006) Tier 2 but requires independent quality control. Comparing the results of using models to simulate a range of scenarios that explore an appropriate range of biophysical and management situations can support this process by providing a framework for placing model results in context. To assess the variation between models and the process of understanding differences, estimates of GHG emissions from four farm-scale models (DairyWise, FarmAC, HolosNor and SFARMMOD) were calculated for eight dairy farming scenarios within a factorial design consisting of two climates (cool/dry and warm/wet)×two soil types (sandy and clayey)×two feeding systems (grass only and grass/maize). The milk yield per cow, follower:cow ratio, manure management system, nitrogen (N) fertilisation and land area were standardised for all scenarios in order to associate the differences in the results with the model structure and function. Potential yield and application of available N in fertiliser and manure were specified separately for grass and maize. Significant differences between models were found in GHG emissions at the farm-scale and for most contributory sources, although there was no difference in the ranking of source magnitudes. The farm-scale GHG emissions, averaged over the four models, was 10.6 t carbon dioxide equivalents (CO2e)/ha per year, with a range of 1.9 t CO2e/ha per year. Even though key production characteristics were specified in the scenarios, there were still significant differences between models in the annual milk production per ha and the amounts of N fertiliser and concentrate feed imported. This was because the models differed in their description of biophysical responses and feedback mechanisms, and in the extent to which management functions were internalised. We conclude that comparing the results of different farm-scale models when applied to a range of scenarios would build confidence in their use in achieving ESR targets, justifying further investment in the development of a wider range of scenarios and software tools.

Strategic grazing management towards sustainable intensification at tropical pasture-based dairy systems

Agricultural systems are responsible for environmental impacts that can be mitigated through the adoption of more sustainable principles. Our objective was to investigate the influence of two pre-grazing targets (95% and maximum canopy light interception during pasture regrowth; LI_95% and LI_Max, respectively) on sward structure and herbage nutritive value of elephant grass cv. Cameroon, and dry matter intake (DMI), milk yield, stocking rate, enteric methane (CH₄) emissions by Holstein × Jersey dairy cows. We hypothesized that grazing strategies modifying the sward structure of elephant grass (Pennisetum purpureum Schum.) improves nutritive value of herbage, increasing DMI and reducing intensity of enteric CH₄ emissions, providing environmental and productivity benefits to tropical pasture-based dairy systems. Results indicated that pre-sward surface height was greater for LI_Max (≈135 cm) than LI_95% (≈100 cm) and can be used as a reliable field guide for monitoring sward structure. Grazing management based on LI_95% criteria improved herbage nutritive value and grazing efficiency, allowing greater DMI, milk yield and stocking rate by dairy cows. Daily enteric CH₄ emission was not affected; however, cows grazing elephant grass at LI_95% were more efficient and emitted 21% less CH₄/kg of milk yield and 18% less CH₄/kg of DMI. The 51% increase in milk yield per hectare overcame the 29% increase in enteric CH₄ emissions per hectare in LI_95% grazing management. Thereby the same resource allocation resulted in a 16% mitigation of the main greenhouse gas from pasture-based dairy systems. Overall, strategic grazing management is an environmental friendly practice that improves use efficiency of allocated resources through optimization of processes evolving plant, ruminant and their interface, and enhances milk production efficiency of tropical pasture-based systems.

Do Large Slaughterhouses Promote Sustainable Intensification of Cattle Ranching in Amazonia and the Cerrado?

This study investigated the influence of large slaughterhouses on five variables, two related to environment impact (land use change rate and greenhouse gases emissions (GE)), and three related to cattle-ranching intensification (protein from crops, calories from crops and stocking rate). In Amazonia, the results show a reduction of the land use change rate and GE in zones both with and without the influence of large slaughterhouses. The hypothesis that slaughterhouses are leverage points to reduce deforestation in the biome was not confirmed. The slaughterhouses also seem to have no effect on cattle ranching intensification, as protein and calories production increased significantly in both zones, while the stocking rates did not change in the influence zones. In the Cerrado, cattle-ranching intensification is a reality, and is occurring independently of the presence of large slaughterhouses. In conclusion, the results show no evidence that large slaughterhouses have promoted either cattle-ranching intensification or improvements in the sustainability of the cattle-ranching activity in Amazonia and the Cerrado.

A review of whole farm-system analysis in evaluating greenhouse-gas mitigation strategies from livestock production systems

Recognition is increasingly given to the need of improving agricultural production and efficiency to meet growing global food demand, while minimising environmental impacts. Livestock forms an important component of global food production and is a significant contributor to anthropogenic greenhouse-gas (GHG) emissions. As such, livestock production systems (LPS) are coming under increasing pressure to lower their emissions. In developed countries, LPS have been gradually reducing their emissions per unit of product (emissions intensity; EI) over time through improvements in production efficiency. However, the global challenge of reducing net emissions (NE) from livestock requires that the rate of decline in EI surpasses the productivity increases required to satisfy global food demand. Mechanistic and dynamic whole farm-system models can be used to estimate farm-gate GHG emissions and to quantify the likely changes in farm NE, EI, farm productivity and farm profitability as a result of applying various mitigation strategies. Such models are also used to understand the complex interactions at the farm-system level and to account for how component mitigation strategies perform within the complexity of these interactions, which is often overlooked when GHG mitigation research is performed only at the component level. The results of such analyses can be used in extension activities and to encourage adoption, increase awareness and in assisting policy makers. The present paper reviews how whole farm-system modelling has been used to assess GHG mitigation strategies, and the importance of understanding metrics and allocation approaches when assessing GHG emissions from LPS.

Problems of benchmarking greenhouse gas emissions in dairy agriculture

Purpose

The purpose of this paper is to examine the suitability of free carbon calculators aimed at the agricultural industry, for use in greenhouse gas (GHG) emission benchmarking, using the European dairy industry as an example.

Design/methodology/approach

Carbon calculators which were claimed to be applicable to European dairy farms were identified and tested using six production scenarios based on data from real European farms supplemented using published literature. The resulting GHG emission estimates, together with estimates apportioned using three functional units, were then compared to determine the robustness of the benchmarking results.

Findings

It was found that although there was a degree of agreement between the seven identified carbon calculators in terms of benchmarking total farm emissions, once a suitable functional unit was applied little agreement remained. Tools often ranked farms in different orders, thereby calling into question the robustness of benchmarking in the studied sector.

Research limitations/implications

The scenario-based approach taken has identified issues liable to result in a lack of benchmarking robustness within this sector; however, there remains considerable scope to evaluate these findings in the field, both within this sector and others in the agricultural industry.

Practical implications

The results suggest that there are significant hurdles to overcome if GHG emission benchmarking is to aid in driving forward the environmental performance of the dairy industry. In addition, eco-labelling foods based on GHG benchmarking may be of questionable value.

Originality/value

At a time when environmental benchmarking is of increasing importance, this paper seeks to evaluate its applicability to sectors in which there is considerable scope for variation in the results obtained.

Research on Coordination Mechanism and Low-Carbon Technology Strategy for Agricultural Product Supply Chain

As the future orientation of economic and agricultural development, low-carbon agriculture is devoted to reducing the energy inputs and greenhouse gas emissions during the agriculture production. So, it's urgent to take some actions to transit from the current high carbon economy to a low-carbon and high resource efficient economy. This paper examines a two-echelon agricultural product supply chain with a producer and a processor and the market demand is influenced by the retail price and the level of low-carbon technology. The optimal solutions in the decentralized and centralized agricultural product supply chain with or without low-carbon technology are studied. To make the decentralized agricultural product supply chain perform as well as the centralized agricultural product supply chain, the coordination mechanism of the low-carbon supply chain that few of papers focused explicitly on is designed. Finally, extensive numerical experiments are conducted to study the behaviors of supply chain members.

Development of methane conversion factor models for Zebu beef cattle fed low-quality crop residues and by-products in tropical regions

The enteric methane conversion factor (Y_m) is an important country‐specific value for the provision of precise enteric methane emissions inventory reports. The objectives of this meta‐analysis were to develop and evaluate the empirical Y_m models for the national level and the farm level for tropical developing countries according to the IPCC's categorization. We used datasets derived from 18 in vivo feeding experiments from 1999 to 2015 of Zebu beef cattle breeds fed low‐quality crop residues and by‐products. We found that the observed Y_m value was 8.2% gross energy (GE) intake (~120 g methane emission head⁻¹ day⁻¹) and ranged from 4.8% to 13.7% GE intake. The IPCC default model (tier 2, Y_m = 6.5% ± 1.0% GE intake) underestimated the Y_m values by up to 26.1% compared with its refinement of 8.4% ± 0.4% GE intake for the national‐level estimate. Both the IPCC default model and the refined model performed worse in predicting Y_m trends at the farm level (root mean square prediction error [MSPE] = 15.1%–23.1%, concordance correlation coefficient [CCC] = 0.16–0.18, R² = .32). Seven of the extant Y_m models based on a linear regression approach also showed inaccurately estimated Y_m values (root MSPE = 16.2%–36.0%, CCC = 0.02–0.27, R² < .37). However, one of the developed models, which related to the complexity of the energy use efficiencies of the diet consumed to Y_m, showed adequate accuracy at the farm level (root MSPE = 9.1%, CCC = 0.75, R² = .67). Our results thus suggest a new Y_m model and future challenges for estimating Zebu beef cattle production in tropical developing countries.