D. O’Brien

The influence of strain of Holstein-Friesian cow and feeding system on greenhouse gas emissions from pastoral dairy farms

The purpose of this study was to model the effect of 3 divergent strains of Holstein-Friesian cows in 3 pasture-based feed systems on greenhouse gas (GHG) emissions. The 3 strains of Holstein-Friesian compared were high-production North American (HP), high-durability North American (HD), and New Zealand (NZ). The 3 feed systems were a high grass allowance system (MP, control); high stocking rate system (HS); and high concentrate supplementation system (HC). The MP system had an overall stocking rate of 2.47 cows/ha and received 325 kg of dry matter concentrate per cow in early lactation. The HS system had a similar concentrate input to the MP system, but had an overall stocking rate of 2.74 cows/ha. The HC system had a similar overall stocking rate to the MP system, but 1,445 kg of dry matter concentrate was offered per cow. A newly developed integrated economic-GHG farm model was used to evaluate the 9 milk production systems. The GHG model estimates on-farm (emissions arising within the farms physical boundaries) and production system (incorporating all emissions associated with the production system up to the point milk leaves the farm gate) GHG emissions. Production system GHG emissions were always greater than on-farm emissions, and the ranking of the 9 systems was usually consistent under both methods. The exception was the NZ strain that achieved their lowest GHG emission per unit of product in the HC system when indirect emissions were excluded, but their lowest emission was in the HS system when indirect emissions were included. Generally, the results showed that as cow strain changed from lower (HD and NZ) to higher genetic potential (HP) for milk production, the GHG emission per kilogram of milk solids increased. This was because of a decline in cow fertility in the HP strain that resulted in a higher number of nonproductive animals, leading to a lower total farm milk solids production and an increase in emissions from nonproductive animals. The GHG emission per hectare increased for all strains moving from MP to HS to HC feed systems and this was associated with increases in herd total feed intake. The most profitable combination was the NZ strain in the HS system and this combination resulted in a 12% reduction in production system GHG emission per hectare compared with the NZ strain in the HC system, which produced the highest emissions. This demonstrates that grass-based systems can achieve high profitability and decreased GHG emissions simultaneously.

A case study of the carbon footprint of milk from high-performing confinement and grass-based dairy farms

Life-cycle assessment (LCA) is the preferred methodology to assess carbon footprint per unit of milk. The objective of this case study was to apply an LCA method to compare carbon footprints of high-performance confinement and grass-based dairy farms. Physical performance data from research herds were used to quantify carbon footprints of a high-performance Irish grass-based dairy system and a top-performing United Kingdom (UK) confinement dairy system. For the US confinement dairy system, data from the top 5% of herds of a national database were used. Life-cycle assessment was applied using the same dairy farm greenhouse gas (GHG) model for all dairy systems. The model estimated all on- and off-farm GHG sources associated with dairy production until milk is sold from the farm in kilograms of carbon dioxide equivalents (CO2-eq) and allocated emissions between milk and meat. The carbon footprint of milk was calculated by expressing GHG emissions attributed to milk per tonne of energy-corrected milk (ECM). The comparison showed that when GHG emissions were only attributed to milk, the carbon footprint of milk from the Irish grass-based system (837 kg of CO2-eq/t of ECM) was 5% lower than the UK confinement system (884 kg of CO2-eq/t of ECM) and 7% lower than the US confinement system (898 kg of CO2-eq/t of ECM). However, without grassland carbon sequestration, the grass-based and confinement dairy systems had similar carbon footprints per tonne of ECM. Emission algorithms and allocation of GHG emissions between milk and meat also affected the relative difference and order of dairy system carbon footprints. For instance, depending on the method chosen to allocate emissions between milk and meat, the relative difference between the carbon footprints of grass-based and confinement dairy systems varied by 3 to 22%. This indicates that further harmonization of several aspects of the LCA methodology is required to compare carbon footprints of contrasting dairy systems. In comparison to recent reports that assess the carbon footprint of milk from average Irish, UK, and US dairy systems, this case study indicates that top-performing herds of the respective nations have carbon footprints 27 to 32% lower than average dairy systems. Although differences between studies are partly explained by methodological inconsistency, the comparison suggests that potential exists to reduce the carbon footprint of milk in each of the nations by implementing practices that improve productivity.

Relating the carbon footprint of milk from Irish dairy farms to economic performance

Mitigating greenhouse gas (GHG) emissions per unit of milk or the carbon footprint (CF) of milk is a key issue for the European dairy sector given rising concerns over the potential adverse effects of climate change. Several strategies are available to mitigate GHG emissions, but producing milk with a low CF does not necessarily imply that a dairy farm is economically viable. Therefore, to understand the relationship between the CF of milk and dairy farm economic performance, the farm accountancy network database of a European Union nation (Ireland) was applied to a GHG emission model. The method used to quantify GHG emissions was life cycle assessment (LCA), which was independently certified to comply with the British standard for LCA. The model calculated annual on- and off-farm GHG emissions from imported inputs (e.g., electricity) up to the point milk was sold from the farm in CO2-equivalent (CO2-eq). Annual GHG emissions computed using LCA were allocated to milk based on the economic value of dairy farm products and expressed per kilogram of fat- and protein-corrected milk (FPCM). The results showed for a nationally representative sample of 221 grass-based Irish dairy farms in 2012 that gross profit averaged € 0.18/L of milk and € 1,758/ha and gross income was € 40,899/labor unit. Net profit averaged € 0.08/L of milk and € 750/ha and net income averaged € 18,125/labor unit. However, significant variability was noted in farm performance across each financial output measure. For instance, net margin per hectare of the top one-third of farms was 6.5 times higher than the bottom third. Financial performance measures were inversely correlated with the CF of milk, which averaged 1.20 kg of CO2-eq/kg of FPCM but ranged from 0.60 to 2.13 kg of CO2-eq/kg of FPCM. Partial least squares regression analysis of correlations between financial and environmental performance indicated that extending the length of the grazing season and increasing milk production per hectare or per cow reduced the CF of milk and increased farm profit. However, where higher milk production per hectare was associated with greater concentrate feeding, this adversely affected the CF of milk and economic performance by increasing both costs and off-farm emissions. Therefore, to mitigate the CF of milk and improve economic performance, grass-based dairy farms should not aim to only increase milk output, but instead target increasing milk production per hectare from grazed grass.

Defining a functional unit for dairy production LCA that reflects the transaction between the farmer and the dairy processor

PurposeThe two main functions of dairy farming are to produce raw milk and to generate an economic income for the farmer (Powell et al. in Nutr Cycl Agroecosyst 82:107–115, 2008), both of which drive the downstream value chain. Farm profit is mainly determined by the quantity and quality of milk, and at the same time, dairy farmers have a responsibility for animal welfare and the protection of human health through milk hygiene. When dairy farmers supply milk to a processor, the payment is based on both the quantity and the quality in terms of composition (fat and protein) and hygiene (total bacterial count and somatic cell count). Somatic cell count reflects the health status of the mammary gland and contributes to reduced shelf life and reduced cheese yield and quality, whilst total bacterial count reflects herd health and farm sanitation. The objective of this work was to create a new functional unit for raw milk at the farm gate/ processor gate, which could be used to better capture the economic function of milk, while still reflecting the quality criteria captured by energy corrected milk and fat and protein corrected milk.Materials and methodsBase price-adjusted milk (BPAM) is proposed as a functional unit to capture more of the functions of the transaction between the farmer and the processor. It expresses the volume of milk delivered as the equivalent volume at base price, such that greater milk solids increase the volume and poor hygiene decreases the volume. The BPAM was compared with energy-corrected milk and was tested using a survey of 54 farms in Ireland and eight scenarios compared with the observed values and an “ideal” scenario with no hygiene penalty imposed.Results and discussionIt was found that kg BPAM for the sample of farms was strongly correlated with kg ECM because of the overall hygiene standard from the sample of farms available. For specific farms at specific times, the hygiene properties contributed to the economic function of the milk in a way that could not be captured using energy-corrected milk. The scenario analysis indicated that high levels of biological contamination, if captured in the raw milk functional unit, could increase carbon footprint by > 200%.ConclusionsIt was concluded that BPAM may not be a necessary functional unit for all studies, but those that focused on the farmer and processor perspectives should consider using BPAM because it captures more of the obligatory properties of raw milk than just quality expressed in terms of milk solids.