Development of a Robust Sensor Calibration for a Commercially Available Rising Platemeter to Estimate Herbage Mass on Temperate Seminatural Pastures

Rising platemeters are commonly used in Ireland and New Zealand for managing intensive pastures. To assess the applicability of a commercial rising platemeter operating with a microsonic sensor to estimate herbage mass with its own equation, the objectives were (i) to validate the original equation; (ii) to identify possible factors hampering its accuracy and precision; and (iii) to develop a new equation for heterogeneous swards. A comprehensive dataset (n = 1511) was compiled on the pastures of dairy farms. Compressed sward heights were measured by the rising platemeter. Herbage mass was harvested to determine reference herbage availability. The adequacy of estimating herbage mass was assessed using root mean squared error (RMSE) and mean bias. As the adequacy of the original equation was low, a new equation was developed using multiple regression models. The mean bias and the RMSE for the new equation were overall low with 201 kg dry matter/ha and 34.6%, but it tended to overestimate herbage availability at herbage mass < 500 kg dry matter/ha and underestimate it at >2500 kg dry matter/ha. Still, the newly developed equation for the microsonic sensor-based rising platemeter allows for accurate and precise estimation of available herbage mass on pastures.

Methane Emission, Carbon Footprint and Productivity of Specialized Dairy Cows Supplemented with Bitter Cassava (Manihot esculenta Crantz)

The objective of this research was to determine the effect of cassava (Manihot esculenta Crantz) supplementation on enteric methane (CH4) emissions, carbon footprint, and production parameters in dairy cows. Daily concentrate supply for Jersey and Jersey * Holstein breeds was evaluated in four treatments (T): T1: 100% commercial concentrate; T2: 70% concentrate + 30% cassava leaves; T3: 70% concentrate + 30% cassava roots; and T4: 70% concentrate + 15% cassava leaves + 15% cassava root chips. Measurements of CH4 emissions were performed using the polytunnel technique. Average daily dry matter intake ranged from 7.8 to 8.5 kg dry matter (DM). Cassava leaves were characterized by a high crude protein (CP) content (171 g CP/kg DM), with 5 times more neutral detergent fiber (NDF) content than cassava root (587 vs. 108 g NDF/kg DM). Average enteric CH4 emissions per animal ranged from 194 to 234 g/d (p > 0.05). The carbon footprint was reduced by replacing 30% of the concentrate with cassava leaves and/or roots. Energy-corrected milk production was 1.15 times higher in Jersey * Holstein animals than Jersey cows (47 vs. 55 kg). Therefore, supplementation with cassava leaves and/or roots is a nutritionally and environmentally sustainable strategy.

Increasing farm size is an effective way to decrease the carbon footprint in dairy cattle production

The purpose of this study was to investigate the effects of the farm size on the carbon footprint of dairy cattle farms in Isparta province in Türkiye. For this purpose, face-to-face interviews were conducted with 159 farms which represent 1866 dairy cattle farms in Isparta province. The number of animals on the farm was converted into animal unit (AU) and the farms were divided into three groups. Accordingly, farms were classified as small, medium, and large farms. The carbon footprint produced per AU in the farm was the sum of feed, enteric fermentation, CH4 from manure, CO2 from manure, N2O from manure, and anthropogenic emissions. The milk produced in the farms was standardized according to 4% fat and 3.3% protein (FPCM) and the ratio of meat to milk was found by dividing the total live weight gain produced except for cows by FPCM. Accordingly, 65% of the greenhouse gas emissions of dairy farms were allocated to milk and 35% to meat. Of the total emissions, enteric fermentation and emission on feed contributed the highest proportion. Results showed that when using the IPCC (2021) global warming potential (GWP) values, the carbon footprint for 1 kg of FPCM milk was 1.26 kg CO2-eq on average, whereas the carbon footprint for 1 kg of meat was 11.78 kg CO2-eq on average. Results showed that as farm size increased carbon footprint for a kilogram of FPCM and meat decreased and this showed the effectiveness of farm size on decreasing carbon footprint per unit of product.

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

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

A Longitudinal Study with a Laser Methane Detector (LMD) Highlighting Lactation Cycle-Related Differences in Methane Emissions from Dairy Cows

Reversing climate change requires broad, cohesive, and strategic plans for the mitigation of greenhouse gas emissions from animal farming. The implementation and evaluation of such plans demand accurate and accessible methods for monitoring on-field CH4 concentration in eructating breath. Therefore, this paper describes a longitudinal study over six months, aiming to test a protocol using a laser methane detector (LMD) to monitor CH4 emissions in semi-extensive dairy farm systems. Over 10 time points, CH4 measurements were performed in dry (late gestation) and lactating cows at an Azorean dairy farm. Methane traits including CH4 concentration related to eructation (E_CH4) and respiration (R_CH4), and eructation events, were automatically computed from CH4 measured values using algorithms created for peak detection and analysis. Daily CH4 emission was estimated from each profile’s mean CH4 concentration (MEAN_CH4). Data were analyzed using a linear mixed model, including breed, lactation stage, and parity as fixed effects, and cow (subject) and time point as random effects. The results showed that Holsteins had higher E_CH4 than Jersey cows (p < 0.001). Although a breed-related trend was found in daily CH4 emission (p = 0.060), it was not significant when normalized to daily milk yield (p > 0.05). Methane emissions were lower in dry than in lactation cows (p < 0.05) and increased with the advancement of the lactation, even when normalizing it to daily milk yield (p < 0.05). Primiparous cows had lower daily CH4 emissions related to R_ CH4 compared to multiparous (p < 0.001). This allowed the identification of periods of higher CH4 emissions within the milk production cycle of dairy cows, and thus, the opportunity to tailor mitigation strategies accordingly.

Agricultural greenhouse gas emissions of an Indian village - Who's to blame: crops or livestock?

A carbon footprint assessment, combining various scales of analysis and including a territorial assessment, is proposed to estimate the greenhouse gas (GHG) emissions from crops and livestock in an Indian village impacted by both Green (for crops) and White (for milk) revolutions. It is based on the GHG assessment of 10 cropping systems, 8 livestock farming systems and 9 production systems using the comparative agriculture and Life Cycle Assessment (LCA) approaches. Results show that mineral fertilisation, irrigation and methane from paddy fields are the main drivers of emissions at plot level. Livestock farming systems emit from 4.7 tCO_2eq/female to 8.6 tCO_2eq/female, enteric fermentation being the first source of emission. Disparities at farm level are huge, ranging from 9 to 733 tCO_2eq. At village level, emissions yield 37 tCO_2eq/ha and livestock contributes to 60 % of GHG emissions. The high GHG emissions are a legacy of the Green and White Revolutions: the livestock population is high, fed on highly emissive fodder and concentrates and produces little milk. The results enhance our understanding of the share of carbon emissions from crops and livestock at farm and territorial level. They pinpoint the environmental and socio-economic downsides of livestock farming intensification.

Contrasting Fecal Methanogenic and Bacterial Profiles of Organic Dairy Cows Located in Northwest Washington Receiving Either a Mixed Diet of Pasture and TMR or Solely TMR

Currently, little is known regarding fecal microbial populations and their associations with methanogenic archaea in pasture-based dairy cattle. In this study, we assessed the fecal microbiome of organic dairy cows across different time points receiving a mixed diet of pasture and total mixed ration (TMR) or TMR only. We hypothesized that the fecal methanogenic community, as well as co-occurrence patterns with bacteria, change across diets. To test these hypotheses, we analyzed TMR and pasture samples, as well as the V3-V4 region of 16S rRNA of fecal samples collected over the course of a one-year study period from 209 cows located on an organic dairy in Northwest Washington. The inherent variability in pasture quality, quantity, availability, and animal preference can lead to diverse dietary intakes. Therefore, we conducted a k-means clustering analysis to identify samples from cows that were associated with either a pasture-based diet or a solely TMR diet. A total of 4 clusters were identified. Clusters 1 and 3 were mainly associated with samples primarily collected from cows with access to pasture of varying quality and TMR, cluster 2 was formed by samples from cows receiving only TMR, and cluster 4 was a mix of samples from cows receiving high-quality pasture and TMR or TMR only. Interestingly, we found little difference in the relative abundance of methanogens between the community clusters. There was evidence of differences in diversity between pasture associated bacterial communities and those associated with TMR. Cluster 4 had higher diversity and a less robust co-occurrence network based on Spearman correlations than communities representing TMR only or lower-quality pasture samples. These findings indicate that varied bacterial communities are correlated with the metabolic characteristics of different diets. The overall good pasture and TMR quality in this study, combined with the organic allowance for feeding high levels of TMR even during the grazing season, might have contributed to the lack of differences in the fecal archaeal community from samples associated with a mixed pasture and TMR diet, and a TMR only diet. Mitigation strategies to decrease methane emissions such as increasing concentrate to forage ratio, decreasing pasture maturity and adopting grazing systems targeting high quality pasture have been shown to be efficient for pasture-based systems. However, the allowance for organic dairy producers to provide up to an average of 70% of a ruminant's dry matter demand from dry matter fed (e.g., TMR), suggests that reducing enteric methane emissions may require the development of novel dietary strategies independent of pasture management.

Production performance, nutrient use efficiency, and predicted enteric methane emissions in dairy cows under confinement or grazing management system

There has been an intense debate regarding the economic, social, and environmental sustainability of confinement versus grazing dairy systems. Our goal was to conduct a meta-analysis to compare dry matter intake, milk yield and composition, nutrient use efficiency (i.e., feed efficiency, milk N efficiency), and predicted enteric CH₄ emissions using studies that simultaneously evaluated confinement and grazing. We were able to include in the meta-analysis 8 peer-reviewed articles that met the following selection criteria: (1) publication between 1991 and 2021 in English language, (2) report either SEM or SD, (3) inclusion of at least 1 confinement [total mixed ration or fresh cut herbage fed indoors (i.e., zero-grazing)] and 1 grazing treatment in the same study, and (4) use of markers (internal or external) to estimate herbage dry matter intake. Two unpublished experiments were added to the data set resulting in a total of 10 studies for comparing confinement and grazing. The magnitude of the effect (i.e., effect size) was evaluated using weighted raw mean differences between grazing and confinement systems for a random effect model. Enteric CH₄ production was predicted as follows: CH₄ (g/d) = 33.2 (13.54) + 13.6 (0.33) × dry matter intake + 2.43 (0.245) × neutral detergent fiber. Dry matter intake (–9.5%), milk yield (–9.3%), milk fat yield (–5.8%), milk protein yield (–10%), and energy-corrected milk (–12%) all decreased in grazing versus confined dairy cows. In contrast, concentration of milk fat and feed efficiency (energy-corrected milk/dry matter intake) were not affected by management system. Whereas milk protein concentration increased, milk nitrogen (N) efficiency (milk N/N intake) tended to decrease in grazing compared with confinement. Predicted enteric CH₄ production was 6.1% lower in grazing than confined dairy cows. However, CH₄ yield (g/kg of dry matter intake) and CH₄ intensity (g/kg of energy-corrected milk) did not change between confinement and grazing. In conclusion, while production performance decreased in grazing dairy cows, nutrient use efficiency and predicted enteric CH₄ emissions were relatively similar in both management systems. Results of our meta-analysis should be interpreted with caution due to the small number of studies that met our inclusion criteria leading to a limited number of treatment mean comparisons.

Dairy farmer practices and attitudes relating to pasture-based and indoor production systems in Scotland

This study assesses the practices and views of Scottish dairy farmers relating to pasture-based and indoor systems. There are the debates about the environmental, economic and animal welfare implications of these systems. Indoor dairy farming is a contentious practice among the public. While this controversy is sometimes represented as a lack of public understanding, there is a need for more research on farmers' views to facilitate discussion in the industry. A survey was posted to 909 dairy farmers in Scotland with questions about their grazing practices and attitudes to grazing and indoor systems. 254 surveys were completed, online and in paper form. There was a 26% response rate to the paper version of the survey. The results showed that 19% of respondents housed some or all the cows all year-round. 68% agreed or strongly agreed that cows should graze for part of the year and 51% agreed or strongly agreed that welfare was better if cows grazed for part of the year. These views coexisted with the view that management was more important than the type of system for determining profitability or welfare outcomes (83% and 82% strongly agree or agree respectively). Respondents whose system involved grazing and respondents who had spent longer in farming were moderately more likely to agree that cows should have access to pasture, and slightly less likely to agree that management was more important than system for determining welfare outcomes. The results indicate that the picture is more complicated than the public rejecting indoor dairy farming and those in the industry accepting it. The results showed that a majority preference for cows to graze co-existed with the view that management was more important than system. In terms of industry and policy recommendations, the research suggests that measures should be taken to safeguard farmers' ability to graze through for instance research and advisory support on grazing; ensuring different systems are not penalised in the development of dairy sector environmental measures and recommendations; and potentially supply chains that financially rewards farmers for grazing.

Dairy farmer practices and attitudes relating to grass-based, high-feed-input, and indoor production systems in Ireland

Grazing has become a less common dairy farming practice in most European countries. Ireland is an exception with its predominantly grass-based system. After the removal of European milk quotas, farmers were encouraged to expand within a grass-based paradigm rather than pursuing yield increases through feeding more concentrate. This research assessed Irish dairy farmer attitudes toward grass-based, higher-feed-input, and indoor paradigms. A paradigm of agriculture is a shared understanding about how agriculture should be carried out. Grass-based, higher-feed-input, and indoor paradigms propose different solutions to economic, environmental, and animal-welfare challenges facing dairy farming. An online survey was distributed to Irish dairy farmers in August 2018, which received 396 responses. There was support among respondents for the grass-based paradigm of maximizing milk from forage and minimizing concentrate use, with 73% of respondents strongly agreeing or agreeing this was the best option for Irish dairy farmers. The results suggest there were not significant ideological disagreements among respondents about the economic, environmental, and animal-welfare merits of different paradigms. Rather, the results showed respondents supported grass-based or higher-feed-input paradigms for different reasons as follows: profitability and lifestyle for the former, and the ability to expand production without access to additional land and less dependence on weather for the latter. These findings could be of interest in countries where grazing is less widely practiced, but where there is a desire to increase the uptake of grazing practices. Messaging about the profitability and simplicity of the grass-based system clearly resonated with respondents, and could be replicated in other countries. There is a desire within the Irish government, industry, and advisory bodies to keep dairy expansion within a grass-based paradigm. The results suggested individuals may diverge from this paradigm not because they disagree with messaging about its benefits, but rather if difficulties with land access or managing weather variability lead them to expand through feeding more concentrate. To maintain production within the grass-based paradigm, more opportunities could be created for farmers who are restricted from further expansion, such as alternative supply chains or payments for environmental services.

Incorporation of the grazing utilization subindex and new updates to the Pasture Profit Index

Grazing efficiency has been shown to differ between perennial ryegrass varieties. Such differences affect the utilization of grass within grazing systems, influencing the profitability of grass-based ruminant production systems. The Pasture Profit Index (PPI) is an economic merit grass variety selection tool developed to identify varieties with the greatest economic potential for grass-based dairy production systems. A new grass utilization subindex was developed and incorporated into the PPI to identify varieties with superior grazing efficiency. The subindex rewards varieties with superior grazing efficiency, measured as Residual grazed height, as these varieties allow increased amounts of herbage dry matter to be used by grazing animals. The economic values of all other traits within the PPI were reviewed and updated to ensure that the index was reflective of the current economic scenarios with appropriate assumptions included in the models, thus ensuring that varieties excelling in the agronomic traits with the greatest effect on profitability were recognized. The difference between the highest and lowest performing varieties for the grass utilization trait ranged from €23 to -€24. A range of €211 to €43 was recorded between the highest and lowest ranked varieties within the updated PPI. Spearman's rank correlation between the updated and original PPI lists was 0.96. The introduction of the utilization subindex will allow farmers to make informed variety selection decisions when reseeding pasture, particularly on their grazing platforms and it will allow a demand-based communication process between the farmer and the grass merchant or breeder, ultimately affecting trait selection for future breeding strategies.

Canola Meal versus Soybean Meal as Protein Supplements in the Diets of Lactating Dairy Cows Affects the Greenhouse Gas Intensity of Milk

Soybean meal (SBM) and canola meal (CM) are protein supplements used in lactating dairy cow diets and, recently, an enteric methane-mitigating effect (i.e., lower Ym value) was reported for CM. Before recommending CM as a greenhouse gas (GHG) mitigation strategy, it is necessary to examine the net impact on total GHG emissions from milk production. The objective was to determine whether using CM rather than SBM in lactating dairy cow diets decreases GHG per kilogram of fat and protein corrected milk (FPCM), and whether the decrease depends upon where the meals are produced. Cradle to farm-gate life cycle assessments were conducted for a simulated dairy farm in eastern (Quebec) and western (Alberta) Canada. Scenarios examined the source of protein meal, location where meals were produced, and the methane-mitigating effect of CM. The Holos model was used to estimate GHG emissions from animals, manure, crop production, imported feeds, and energy use. GHG intensities (CO2e/kg FPCM) were 0.85-1.02 in the east and 1.07-1.11 in the west for the various scenarios, with enteric methane comprising 34 to 40% of total emissions. CM produced in western Canada with a low up-stream emission factor and low Ym value reduced CO2e/kg FPCM by 3% (western farm) to 6.6% (eastern farm) compared with SBM. We conclude that using CM rather than SBM in the diet of lactating dairy cows can be a GHG mitigation strategy depending upon where it is produced and whether it decreases enteric methane emissions.

Milk Quality and Carbon Footprint Indicators of Dairy Sheep Farms Depend on Grazing Level and Identify the Different Management Systems

Currently, there are very few studies in the dairy sheep sector associating milk quality and indicators regarding carbon footprint and their link to grazing levels. For 1 year, monthly milk samples and records related to environmental emissions and management systems were collected through surveys from 17 dairy sheep farms in the region of Castilla y León (Spain), in order to relate this information to the use of natural pastures under free grazing. Indicators were constructed on the collected data and subjected to a multivariate statistical procedure that involved a factor analysis, a cluster analysis and a population canonical analysis. By applying multivariate statistical techniques on milk quality and carbon footprint indicators, it was possible to identify the management system of the farms. From an environmental point of view, farms with a higher grazing level (cluster 4) were more sustainable, as they had the lowest carbon footprint (lower CO₂, N₂O and CO₂ equivalent emissions per sheep and year) and the lowest energy consumption levels, which were gradually lower than those of farms in cluster 3; both indicators were much lower than those of farms in clusters 1 and 2. The milk quality of cluster 1 and 2 farms was significantly lower in terms of total protein and fat content, dry extract, omega-3 fatty acid levels and α-tocopherol content than farms in clusters 3 and 4, which had higher accessibility to grazing resources. In sum, the higher the use of natural resources, the lower the external inputs the farms required and the lower environmental impact and energy costs they have.

The Impact of Seasonality in Pasture-Based Production Systems on Milk Composition and Functionality

Seasonal calving, pasture-based dairy systems are widely practiced in countries with a temperate climate and plentiful rainfall such as Ireland and New Zealand. This approach maximizes milk production from pasture and, consequently, is a low-cost, low-input dairy production system. On the other hand, the majority of global milk supply is derived from high input indoor total mixed ration systems where seasonal calving is not practiced due to the dependence on ensiled silages, grains and concentrated feeds, which are available year-round. Synchronous changes in the macro and micronutrients in milk are much more noticeable as lactation progresses through early, mid and late stages in seasonal systems compared to non-seasonal systems-which can have implications on the processability and functionality of milk.

Nutrition-Oriented Reformulation of Extruded Cereals and Associated Environmental Footprint: A Case Study

The global food system faces a dual challenge for the decades ahead: to (re)formulate foods capable to feed a growing population while reducing their environmental footprint. In this analysis, nutritional composition, recipe, and sourcing data were analyzed alongside five environmental indicators: climate change (CC), freshwater consumption scarcity (FWCS), abiotic resource depletion (ARD), land use impacts on biodiversity (LUIB), and impacts on ecosphere/ecosystems quality (IEEQ) to assess improvement after three reformulation cycles (2003, 2010, 2018) in three extruded breakfast cereals. A life cycle assessment (LCA) was performed using life cycle inventory (LCI) composed by both primary data from the manufacturer and secondary data from usual third-party LCI datasets. Reformulation led to improved nutritional quality for all three products. In terms of environmental impact, improvements were observed for the CC, ARD, and IEEQ indicators, with average reductions of 12%, 14%, and 2% between 2003 and 2018, respectively. Conversely, the FWCS and LUIB indicators were increased by 57% and 70%, respectively. For all indicators but ARD, ingredients contributed most to the environmental impact. This study highlights the need for further focus on the selection of less demanding ingredients and improvements in agricultural practices in order to achieve environmental and nutritional improvements.

Valuing carbon capture in agricultural production: examples from Sweden

Agriculture is regarded as a net emitter of greenhouse gases (GHG), but sequesters huge amounts of carbon in soils, bioenergy substrates, and food products. The global accounting system for climate impact based on life cycle assessment (LCA) methodology only takes account of costs (emissions), and not income (carbon and energy binding), leading to the conclusion that agricultural activities should decrease to mitigate climate change. This study considered an alternative accounting system, carbon capture LCA (CC-LCA), that allocates value to carbon sequestration in agricultural products. For two case farms in Sweden (arable, dairy), CC-LCA was applied to (1) calculate the carbon footprint of agricultural production by accounting for net GHG emissions from farm production, rather than gross emissions only, and (2) assess the net impact of mineral nitrogen fertilizer. For the arable farm, CC-LCA revealed net carbon binding of 4 Mg CO2-eq per hectare (net sink), compared with emissions of 1.6 Mg CO2-eq per hectare in LCA. For the dairy farm, both approaches showed emissions of about 10 Mg CO2-eq per dairy cow, mainly due to ruminant digestion. The results also showed that mineral nitrogen fertilizer effectively contributed to carbon sequestration. Compared with an unfertilized wheat crop, a fertilizer dose of 200 kg N ha−1 was estimated to bind about eight-fold more GHG and energy in grain than was released or used during fertilizer production and crop cultivation. Thus, we argue that future strategies aiming for climate-friendly products and practices must acknowledge that agriculture sequesters carbon in products.

Potential to reduce greenhouse gas emissions through different dairy cattle systems in subtropical regions

Carbon (C) footprint of dairy production, expressed in kg C dioxide (CO2) equivalents (CO2e) (kg energy-corrected milk (ECM))-1, encompasses emissions from feed production, diet management and total product output. The proportion of pasture on diets may affect all these factors, mainly in subtropical climate zones, where cows may access tropical and temperate pastures during warm and cold seasons, respectively. The aim of the study was to assess the C footprint of a dairy system with annual tropical and temperate pastures in a subtropical region. The system boundary included all processes up to the animal farm gate. Feed requirement during the entire life of each cow was based on data recorded from Holstein × Jersey cow herds producing an average of 7,000 kg ECM lactation-1. The milk production response as consequence of feed strategies (scenarios) was based on results from two experiments (warm and cold seasons) using lactating cows from the same herd. Three scenarios were evaluated: total mixed ration (TMR) ad libitum intake, 75, and 50% of ad libitum TMR intake with access to grazing either a tropical or temperate pasture during lactation periods. Considering IPCC and international literature values to estimate emissions from urine/dung, feed production and electricity, the C footprint was similar between scenarios, averaging 1.06 kg CO2e (kg ECM)-1. Considering factors from studies conducted in subtropical conditions and actual inputs for on-farm feed production, the C footprint decreased 0.04 kg CO2e (kg ECM)-1 in scenarios including pastures compared to ad libitum TMR. Regardless of factors considered, emissions from feed production decreased as the proportion of pasture went up. In conclusion, decreasing TMR intake and including pastures in dairy cow diets in subtropical conditions have the potential to maintain or reduce the C footprint to a small extent.

Effect of Feed Concentrate Intake on the Environmental Impact of Dairy Cows in an Alpine Mountain Region Including Soil Carbon Sequestration and Effect on Biodiversity

Several studies on the environmental impacts of livestock enterprises are based on the application of life cycle assessments (LCA). In Alpine regions, soil carbon sequestration can play an important role in reducing environmental impacts. However, there is no official methodology to calculate this possible reduction. Biodiversity plays an important role in the Alpine environment and is affected by human activities, such as cattle farming. Our aim was to estimate the carbon footprint (CF) of four different dairy production systems (different in breeds and feeding intensity) by using the LCA approach. The present study included 44 dairy Alpine farms located in the autonomous province of Bolzano in northern Italy. Half of the farms (n = 22) kept Alpine Grey and the other half (n = 22) Brown Swiss cattle. Within breeds, the farms were divided by the amount of concentrated feed per cow and day into high concentrate (HC) and low concentrate (LC). This resulted in 11 Alpine Grey low concentrate (AGLC) farms feeding an average amount of 3.0 kg concentrated feed/cow/day and 11 Alpine Grey high concentrate (AGHC) farms with an average amount of 6.3 kg concentrated feed/cow/day. Eleven farms kept Brown Swiss cows with an average amount of 3.7 kg concentrated feed/cow/day (BSLC) and another 11 farms feeding on average 7.6 kg concentrated feed/cow/day (BSHC). CF for the four systems was estimated using the LCA approach. The functional unit was 1 kg of fat and protein corrected milk (FPCM). Furthermore, two methodologies have been applied to estimate soil carbon sequestration and effect on biodiversity. The system with the lowest environmental impact in terms of CF was BSHC (1.14 kg CO2-eq/kg of FPCM), while the most impactful system was the AGLC group (1.55 kg CO2-eq/kg of FPCM). Including the CF reduction due to soil carbon sequestered from grassland, it decreased differently for the two applied methods. For all four systems, the main factor for CF was enteric emission, while the main pollutant was biogenic CH4. Conversely, AGLC had the lowest impact when the damage to biodiversity was considered (damage score = 0.41/kg of FPCM, damage to ecosystem diversity = 1.78 E-07 species*yr/kg FPCM). In comparison, BSHC had the greatest impact in terms of damage to biodiversity (damage score = 0.56/kg of FPCM, damage to ecosystem diversity = 2.49 E-07 species*yr/kg FPCM). This study indicates the importance of including soil carbon sequestration from grasslands and effects on biodiversity when calculating the environmental performance of dairy farms.

Regional environmental assessment of dairy farms

A comprehensive, yet in depth, assessment is needed of the environmental impacts of dairy farms at regional and national scales to better track improvements made by the industry. With Pennsylvania as an example, a method using process-level simulation and cradle-to-farm gate life cycle assessment was developed and used to assess important environmental footprints of dairy farms within a state. Representative dairy farms of various sizes and management practices throughout 7 regions of the state were simulated with the Integrated Farm System Model. Environmental footprints varied widely among farms, with this variation influenced primarily by soil characteristics and climate and secondarily by farm management. Therefore, prescriptive mitigation strategies for individual farms are more effective than uniform enforcement of specific strategies across the state. Footprints for the whole state were determined by totaling values among farms and regions based on the amounts of milk produced by each. Pennsylvania dairy farms were determined to emit 4,555 with an uncertainty of ±415 Gg of CO₂ equivalent of greenhouse gas with an intensity of 0.99 ± 0.09 kg of CO₂ equivalent/kg of fat- and protein-corrected milk (FPCM) produced. Fossil energy consumption was 12,324 ± 1,946 TJ or 2.69 ± 0.42 MJ/kg of FPCM. Blue (nonprecipitation) water consumption was 64.1 ± 13.5 Tg with an intensity of 14.0 ± 3.0 kg/kg of FPCM. A total of all forms of reactive N loss was 43.2 ± 5.0 Gg with an intensity of 9.4 ± 1.1 g/kg of FPCM. These metrics were equivalent to 1.6% of the greenhouse gas emissions, 0.4% of fossil energy use, and 0.8% of fresh water consumption reported for the state. Thus, greenhouse gas emissions, fossil energy use, and blue water use associated with dairy farm production are relatively small compared with total estimates for the state. Perhaps the greatest environmental concern is that of ammonia emission, where dairy farms accounted for about half the estimated emissions of the state. This method can be applied to assessments of the dairy industry at larger regional and national scales.

Economic and Environmental Analysis of Small-Scale Anaerobic Digestion Plants on Irish Dairy Farms

The European Union’s (EU) climate and energy package requires all EU countries to reduce their greenhouse gas (GHG) emissions by 20% by 2020. Based on current trends, Ireland is on track to miss this target with a projected reduction of only 5% to 6%. The agriculture sector has consistently been the single largest contributor to Irish GHG emissions, representing 33% of all emissions in 2017. Small-scale anaerobic digestion (SSAD) holds promise as an attractive technology for the treatment of livestock manure and the organic fraction of municipal wastes, especially in low population communities or standalone waste treatment facilities. This study assesses the viability of SSAD in Ireland, by modelling the technical, economic, and environmental considerations of operating such plants on commercial Irish dairy farms. The study examines the integration of SSAD on dairy farms with various herd sizes ranging from 50 to 250 dairy cows, with co-digestion afforded by grass grown on available land. Results demonstrate feedstock quantities available on-farm to be sufficient to meet the farm’s energy needs with surplus energy exported, representing between 73% and 79% of the total energy generated. All scenarios investigated demonstrate a net CO2 reduction ranging between 2059–173,237 kg CO2-eq. yr−1. The study found SSAD systems to be profitable within the plant’s lifespan on farms with dairy herds sizes of >100 cows (with payback periods of 8–13 years). The simulated introduction of capital subvention grants similar to other EU countries was seen to significantly lower the plant payback periods. The insights generated from this study show SSAD to be an economically sustainable method for the mitigation of GHG emissions in the Irish agriculture sector.

Dairy intensification: Drivers, impacts and alternatives

Dairy production systems have rapidly intensified over the past several decades. Dairy farms in many world regions are larger and concentrated in fewer hands. Higher productivity can increase overall economic gains but also incurs site-specific social and environmental costs. In this paper, we review the drivers and impacts of dairy intensification. We identify in the literature four prominent concerns about dairy intensification: the environment, animal welfare, socioeconomic well-being, and human health. We then critically assess three frameworks-sustainable intensification, multifunctionality, and agroecology-which promise win-win solutions to these concerns. We call for research and policy approaches that can better account for synergies and trade-offs among the multiple dimensions of dairy impacts. Specifically, we suggest the need to (1) consider dairy system transitions within broader processes of social-environmental change and (2) investigate how certain framings and metrics may lead to uneven social-environmental outcomes. Such work can help visualize transformations towards more equitable, ethical, and sustainable food systems.

Temporal, spatial, and management variability in the carbon footprint of New Zealand milk

The carbon footprint of milk from year-round grazed-pasture dairy systems and its variability has had limited research. The objective of this study was to determine temporal, regional, and farm system variability in the carbon footprint of milk from New Zealand (NZ) average dairy production. Farm production and input data were collected from a national database for 2010/11 to 2017/18 across regions of NZ and weighted on relative production supplied to the major dairy cooperative Fonterra to produce an NZ-average. Total greenhouse gas emissions were calculated using a life cycle assessment methodology for the cradle-to-farm gate, covering all on- and off-farm contributing sources. The NZ-average carbon footprint of milk varied from 0.81 kg of CO₂ equivalent (CO₂eq)/kg of fat- and protein-corrected milk (FPCM) in 2010/11 (with widespread drought) to 0.75 to 0.78 kg of CO₂eq/kg of FPCM in 2013/14 to 2017/18, with a trend for a small decrease over time. Regional variation occurred with highest carbon footprint values for the Northland region due to greatest climatic and soil limitations on pasture production. Dairy cattle diet was approximately 85% from grazed pasture with up to 15% from brought-in feeds (mainly forages and by-products). The CO₂ emissions from direct fuel and electricity use constituted <2% of total CO₂eq emissions, whereas enteric methane was near 70% of the total. An estimate of potential contribution from direct land use change (plantation forest to pasture) was 0.13 kg of CO₂eq/kg of FPCM. This was not included because nationally there has been a net increase in forest land and a decrease in pasture land over the last 20 yr. Data used were highly representative, as evident by the same estimated carbon footprint from 368 farms (in 2017/18) from the national database compared with that from a direct survey of 7,146 farms. New Zealand-specific nitrous oxide emission factors were used, based on many validated field trials and as used in the NZ greenhouse gas inventory, resulting in an 18% lower carbon footprint than if default Intergovernmental Panel on Climate Change factors had been used. Evaluation of the upper and lower quartiles of farms based on per-cow milk production (6,044 vs. 3,542 kg of FPCM/cow) showed a 15% lower carbon footprint for the upper quartile of farms, illustrating the potential for further decrease in carbon footprint with improved farm management practices.

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.

Food Footprint as a Measure of Sustainability for Grazing Dairy Farms

Livestock productions require significant resources allocation in the form of land, water, energy, air, and capital. Meanwhile, owing to increase in the global demand for livestock products, it is wise to consider sustainable livestock practices. In the past few decades, footprints have emerged as indicators for sustainability assessment. In this study, we are introducing a new footprint measure to assess sustainability of a grazing dairy farm while considering carbon, water, energy, and economic impacts of milk production. To achieve this goal, a representative farm was developed based on grazing dairy practices surveys in the State of Michigan, USA. This information was incorporated into the Integrated Farm System Model (IFSM) to estimate the farm carbon, water, energy, and economic impacts and associated footprints for ten different regions in Michigan. A multi-criterion decision-making method called VIKOR was used to determine the overall impacts of the representative farms. This new measure is called the food footprint. Using this new indicator, the most sustainable milk production level (8618 kg/cow/year) was identified that is 19.4% higher than the average milk production (7215 kg/cow/year) in the area of interest. In addition, the most sustainable pasture composition was identified as 90% tall fescue with 10% white clover. The methodology introduced here can be adopted in other regions to improve sustainability by reducing water, energy, and environmental impacts of grazing dairy farms, while maximizing the farm profit and productions.

Environmental impacts and resource use of milk production on the North China Plain, based on life cycle assessment

Life cycle assessment methodology was used to quantify the environmental impacts and resource use of milk production on the North China Plain, the largest milk production area in China. Variation in environmental burden caused by cow productivity was evaluated, as well as scenario analysis of the effects of improvement practices. The results indicated that the average environmental impact potential and resource use for producing 1kg of fat and protein corrected milk was 1.34kgCO₂eq., 9.27gPO₄^3-eq., 19.5gSO₂eq., 4.91MJ, 1.83m² and 266L for global warming potential (GWP), eutrophication potential (EP), acidification potential (AP), non-renewable energy use (NREU), land use (LU) and blue water use (BWU; i.e. water withdrawal), respectively. Feed production was a significant determinant of GWP, NREU, LU and BWU, while AP and EP were mainly affected by manure management. Scenario analysis showed that reducing use of concentrates and substituting with alfalfa hay decreased GWP, EP, AP, NREU and LU (by 1.0%-5.5%), but caused a significant increase of BWU (by 17.2%). Using imported soybean instead of locally-grown soybean decreased LU by 2.6%, but significantly increased GWP and NREU by 20% and 6.9%, respectively. There was no single perfect manure management system, with variable effects from different management practices. The environmental burden shifting observed in this study illustrates the importance of assessing a wide range of impact categories instead of single or limited indicators for formulating environmental policies, and the necessity of combining multiple measures to decrease the environmental burden. For the North China Plain, improving milking cow productivity and herd structure (i.e. increased proportion of milking cows), combining various manure management systems, and encouraging dairy farmers to return manure to nearby crop lands are promising measures to decrease multiple environmental impacts.

Milk production Life Cycle Assessment: A comparison between estimated and measured emission inventory for manure handling

Measuring emissions from manure management operations (from the barns to the land) is a challenging task, subject to different uncertainties related to the spatial-temporal variability in the process leading to gaseous release. At the same time, emissions inventory is a prerequisite of Life Cycle Assessment (LCA) studies. Manure management emissions are usually estimated using equations developed by Intergovernmental Panel on Climate Change (IPCC, in the case of greenhouse gases emissions) and European Environmental Agency (EEA) for Nitrogen-related emissions. In the present study, the environmental impacts associated to three Italian dairy farms were calculated through a comparative LCA using two different approaches for complying the emission inventory. In the "estimated" approach (E) the commonly adopted IPCC and EEA equations were used, while in the "measured" approach (M) emissions actually measured were taken as input data to quantify the emissions associated to manure management. The results showed that the IPCC equation underestimates the manure management emissions, leading to a 10-42% lower global warming potential comparing E to M approach. On the other hand, ammonia related impact categories showed higher values if they were calculated using the estimated approach, underling that a safer level of estimation is maintained.

The carbon footprint of integrated milk production and renewable energy systems - A case study

Dairy farms have been widely acknowledged as a source of greenhouse gas (GHG) emissions. The need for a more environmentally friendly milk production system will likely be important going forward. Whereas methane (CH₄) enteric emissions can only be reduced to a limited extent, CH₄ manure emissions can be reduced by implementing mitigation strategies, such as the use of an anaerobic digestion (AD). Furthermore, implementing a photovoltaic (PV) electricity generation system could mitigate the fossil fuels used to cover the electrical needs of farms. In the present study to detect the main environmental hotspots of milk production, a Life Cycle Assessment was adopted to build the Life Cycle Inventory according to ISO 14040 and 14044 in a conventional dairy farm (1368 animals) provided by AD and PV systems. The Intergovernmental Panel on Climate Change tiered approach was adopted to associate the level of emission with each item in the life cycle inventory. The functional unit refers to 1kg of fat-and-protein-corrected-milk (FPCM). In addition to milk products, other important co-products need to be considered: meat and renewable energy production from AD and PV systems. A physical allocation was applied to attribute GHG emissions among milk and meat products. Renewable energy production from AD and PV systems was considered, discounting carbon credits due to lower CH₄ manure emissions and to the minor exploitation of fossil energy. The CF of this farm scenario was 1.11kg CO₂eq/kg FPCM. The inclusion of AD allowed for the reduction of GHG emissions from milk production by 0.26kg CO₂eq/kg FPCM. The PV system contribution was negligible due to the small dimensions of the technology. The results obtained in this study confirm that integrating milk production with other co-products, originated from more efficient manure management, is a successful strategy to mitigate the environmental impact of dairy production.

Greenhouse gas balance of mountain dairy farms as affected by grassland carbon sequestration

Recent studies on milk production have often focused on environmental impacts analysed using the Life Cycle Assessment (LCA) approach. In grassland-based livestock systems, soil carbon sequestration might be a potential sink to mitigate greenhouse gas (GHG) balance. Nevertheless, there is no commonly shared methodology. In this work, the GHG emissions of small-scale mountain dairy farms were assessed using the LCA approach. Two functional units, kg of Fat and Protein Corrected Milk (FPCM) and Utilizable Agricultural Land (UAL), and two different emissions allocations methods, no allocation and physical allocation, which accounts for the co-product beef, were considered. Two groups of small-scale dairy farms were identified based on the Livestock Units (LU) reared: <30 LU (LLU) and >30 LU (HLU). Before considering soil carbon sequestration in LCA, performing no allocation methods, LLU farms tended to have higher GHG emission than HLU farms per kg of FPCM (1.94 vs. 1.59 kg CO₂-eq/kg FPCM, P ≤ 0.10), whereas the situation was reversed upon considering the m² of UAL as a functional unit (0.29 vs. 0.89 kg CO₂-eq/m², P ≤ 0.05). Conversely, considering physical allocation, the difference between the two groups became less noticeable. When the contribution from soil carbon sequestration was included in the LCA and no allocation method was performed, LLU farms registered higher values of GHG emission per kg of FPCM than HLU farms (1.38 vs. 1.10 kg CO₂-eq/kg FPCM, P ≤ 0.05), and the situation was likewise reversed in this case upon considering the m² of UAL as a functional unit (0.22 vs. 0.73 kg CO₂-eq/m², P ≤ 0.05). To highlight how the presence of grasslands is crucial for the carbon footprint of small-scale farms, this study also applied a simulation for increasing the forage self-sufficiency of farms to 100%. In this case, an average reduction of GHG emission per kg of FPCM of farms was estimated both with no allocation and with physical allocation, reaching 27.0% and 28.8%, respectively.

Grazing intensity affects the environmental impact of dairy systems

Dairy products are major components of the human diet but are also important contributors to global environmental impacts. This study evaluated greenhouse gas (GHG) emissions, net energy intensity (NEI), and land use of confined dairy systems with increasing levels of pasture in the diet. A Wisconsin farm was modeled to represent practices adopted by dairy operations in a humid continental climate typical in the Great Lakes region and other climates that have large differences in seasonal temperatures. Five grazing scenarios (all of which contained some portion of confinement) were modeled based on different concentrations of dry matter intake from pasture and feed supplementation from corn grain, corn silage, and soybean meal. Scenarios that incorporate grazing consisted of 5 mo of pasture feeding from May to September and 7 mo of confined feeding from October to April. Environmental impacts were compared within the 5 scenarios that incorporate grazing and across 2 entirely confined scenarios with and without on-farm electricity production through anaerobic digestion (AD). To conduct a fair comparison, all scenarios were evaluated based on the same total amount of milk produced per day where resource inputs were adjusted according to the characteristics of each scenario. A cradle-to-farm gate life cycle assessment evaluated the environmental burdens that were partitioned by allocation between milk and meat and by system expansion when biogas-based electricity was produced. Overall, results for all scenarios were comparable. Enteric methane was the greatest contributor to GHG emissions, and the production of crops was the most energy-intense process. For the confined scenario without AD, GHG emissions were 0.87 kg of CO₂ equivalents, NEI was 1.59 MJ, and land use was 1.59 m²/kg of fat- and protein-corrected milk (FPCM). Anaerobic digestion significantly reduced emissions to 0.28 kg of CO₂ equivalents/kg of FPCM and reduced NEI to -1.26 MJ/kg of FPCM, indicating a net energy producing system and highlighting the potential of AD to improve the sustainability of confined systems. For scenarios that combined confinement and grazing, GHG emissions ranged from 0.84 to 0.92 kg of CO₂ equivalents, NEI ranged from 1.42 to 1.59 MJ, and land use ranged from 1.19 to 1.26 m²/kg of FPCM. All environmental impacts were minimized in scenarios that supplemented enough feed to increase milk yield but maintained dry matter intake from pasture at a level high enough to reduce material and energy use.

Anaerobic digestion and milking frequency as mitigation strategies of the environmental burden in the milk production system

The aim of the study was to assess, through a cradle to farm gate Life Cycle Assessment, different mitigation strategies of the potential environmental impacts of milk production at farm level. The environmental performances of a conventional intensive dairy farm in Northern Italy (baseline scenario) were compared with the results obtained: from the introduction of the third daily milking and from the adoption of anaerobic digestion (AD) of animal slurry in a consortium AD plant. The AD plant, fed only with animal slurries coming also from nearby farms. Key parameters concerning on-farm activities (forage production, energy consumptions, agricultural machines maintenance, manure and livestock management), off-farm activities (production of fertilizers, pesticides, bedding materials, purchased forages, purchased concentrate feed, replacement animals, agricultural machines manufacturing, electricity, fuel) and transportation were considered. The functional unit was 1kg fat and protein corrected milk (FPCM) leaving the farm gate. The selected environmental impact categories were: global warming potential, acidification, eutrophication, photochemical oxidation and non-renewable energy use. The production of 1kg of FPCM caused, in the baseline scenario, the following environmental impact potentials: global warming potential 1.12kg CO2 eq; acidification 15.5g SO2 eq; eutrophication 5.62g PO4(3-) eq; photochemical oxidation 0.87g C2H4 eq/kg FPCM; energy use 4.66MJeq. The increase of milking frequency improved environmental performances for all impact categories in comparison with the baseline scenario; in particular acidification and eutrophication potentials showed the largest reductions (-11 and -12%, respectively). In anaerobic digestion scenario, compared to the baseline one, most of the impact potentials were strongly reduced. In particular the most important advantages were in terms of acidification (-29%), global warming (-22%) and eutrophication potential (-18%). The AD of cow slurry is confirmed as an effective strategy to mitigate the environmental impact of milk production at farm level.