Fat And Protein Corrected Milk Research Articles

Carbon footprint, non-renewable energy and land use of dual-purpose cattle systems in Colombia using a life cycle assessment approach

Dual-purpose cattle systems (DPS) include more than 75% of all dairy cows in Latin America and produce 40% of total milk production. Colombia has the fourth largest cattle herd in Latin America, and DPS account for 39% of the cattle population, and 58% of national milk production. Therefore, focusing on reducing the carbon footprint (CF) of DPS can have a huge contribution on mitigating the environmental impacts of the cattle farming sector. The present study aimed to estimate, based on a farm gate life cycle assessment (LCA) approach, the environmental impact of 1313 dual-purpose farms in Colombia. The study also aimed at identifying the main hotspots of negative environmental impacts and proposing possible mitigation options and their cost-effectiveness. The impact categories such as CF, non-renewable energy use, and land use were estimated using the 2019 Refinement to 2006 IPCC, databases, and locally estimated emission factors. Three methods of allocating environmental burdens to meat and milk products were applied. A principal component multivariate analysis (PCA) and a Hierarchical Clustering on Principal Components (HCPC) were performed. The largest source of greenhouse gas (GHG) in dual-purpose cattle systems comes directly from enteric fermentation, and manure deposited on pasture. The proportion of environmental burdens allocated to meat differed, with the economic method assigning the greater burden (36%), followed by energy content (30%) and mass production (13%). Four farms clusters and two production strategies were identified, a more intensive strategy with high proportion of improved pastures and higher fertilizer application rates (Clusters 1 and 2), and a more extensive with low input of fertilizers and grazing on natural pastures (Clusters 3 and 4). The CF values ranged between 2.1 and 4.2 CO2-eq per kg fat and protein corrected milk (FPCM) and between 9.0 and 18.3 CO2-eq per kg meat among clusters. CF, land use, and non-renewable energy use were lowest for clusters 1 and 3. Concerning cost-effectiveness, the adoption of improved pastures is a negative-cost measure and a promising climate change mitigation option. Overall, the CF could be reduced by around 25 to 48% for milk and meat. Therefore, our results suggest that it is possible to reduce GHG emissions by adopting improved pastures, better agricultural management practices, efficient fertilizer usage, and using the optimal stocking rate. It is expected that these reductions can be achieved with at negative costs.

Comparing the environmental efficiency of milk and beef production through life cycle assessment of interconnected cattle systems

Dairy production has a substantial environmental impact. Currently, most studies analysing the environmental burdens of milk production employ attributional Life Cycle Assessment (LCA), for cradle to farm-gate analysis of dairy systems. This approach calculates environmental footprints per kg fat and protein corrected milk (FPCM). However, milk and beef production are inherently interconnected, and a narrow focus on milk production neglects wider synergies and trade-offs across cattle systems, outside dairy farm boundaries. For the first time, we applied an expanded boundary LCA of coupled dairy and beef production in Latin America, considering 1 kg FPCM plus 100 g of beef as functional unit (FU) to reflect the current global beef:milk demand ratio and taking into account the complexities of Costa Rican cattle production systems. Boundaries encompassed fattening of surplus dairy calves and incurred or avoided suckler-beef production needed to deliver the FU. A database of 552 Costa Rican farms (203 beef and 349 dairy farms) was analysed using a farm LCA model to generate results across five impact categories (Global Warming Potential – GWP; Eutrophication; Acidification; Abiotic Resource Depletion; and Land Occupation - LO). Normalised scores indicated that cattle systems contribute most strongly to per capita GWP and LO burdens. Cradle to farm-gate attributional LCA showed that milk produced by dual-purpose farms had the largest GWP and LO footprints, whilst specialist farms had the smallest footprints, per kg FPCM. The expanded boundary LCA showed that dual-purpose farms generated smaller GWP footprints per kg FPCM plus 100 g beef than specialised dairy farms, though still required more land. Key factors were the herd structure, influencing the amount of beef produced, and milk yields per animal, reflecting the level of dairy specialisation. This new evidence on the environmental efficiency of cattle production systems emphasises the imperative to consider both milk and beef production as well as multiple environmental pressures across interconnected milk and beef production systems when designing sustainable intensification mitigation strategies.

Variation in the carbon footprint of milk production on smallholder dairy farms in central Kenya

Milk production by smallholders in Africa has a high carbon footprint (CF) and is predicted to increase significantly in the coming decades. This study, based on data from a sample of 382 farms in central Kenya, is the first assessment of the CF of milk production in Sub-Saharan Africa based on a large dataset of actual farm management practices. The aims of the study were (1) to determine whether there are significant differences in the CF of farms with different feeding systems (i.e., zero-grazing, grazing and mixed systems), and (2) to identify factors associated with variability in CF between farms. This analysis is used to identify options for mitigating GHG emissions from Kenya’s growing dairy production. Average CF ranged between 2.19 and 3.13 kg CO2e/kg fat and protein corrected milk (FPCM), depending on the GWPs and allocation method used. Analysis based on variability in farm management showed that CF was similar between farms with zero-grazing and mixed feeding systems, and significantly higher on farms with grazing only feeding systems, but no difference was detected when input parameter uncertainty was considered. At individual cow level, variation in milk yields explained more than 70% of the variation in GHG intensity. At farm level, milk yield explained less than half of variation in CF. CF was correlated with feed characteristics, manure management practices and herd size and composition. In particular, the level of concentrate use was positively correlated with CF, and was the most important factor explaining variation in CF not attributable to variation in milk yield. Our findings suggest that promoting balanced feed rations and feeding concentrate according to cows’ needs across the lactation cycle could provide opportunities to both increase milk production and reduce the CF of milk production on smallholder farms in central Kenya. Supporting smallholder farmers to implement these mitigation options will require interventions at several levels in feed supply chains in the dairy sector.

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.

Environmental impact and efficiency of use of resources of different mountain dairy farming systems

In the European Alps traditional, low-input dairy farming systems still coexist with modern high-input intensive systems. This study aimed at evaluating the effect of different Alpine farming systems on the environmental footprint, production efficiency (gross energy conversion ratio, ECR) and competition between feed and food (potentially human-edible gross energy conversion ratio, HeECR). Data originated from 37 dairy farms located in the Trento province (eastern Italian Alps), from which four dairy systems were derived by performing non-hierarchical cluster analysis based on farm facilities and management features (traditional, either with tie or loose stalls, and intensive, either with or without use of silages, systems). Environmental footprint was computed using a cradle-to-farm gate Life Cycle Assessment model. One kg fat- and protein-corrected Milk (FPCM) and 1 m2 of agricultural land were used as functional units. Global warming (GWP), acidification (AP) and eutrophication (EP) potentials, cumulative energy demand (CED) and land occupation (LO) were included as impact categories. System boundaries included herd and manure management, on-farm feedstuffs production and purchased feedstuffs and materials. Mean impact values per 1 kg FPCM were 1.0 ± 0.3 kg CO2-eq (GWP), 21.1 ± 4.3 g SO2-eq. (AP), 6.3 ± 1.2 g PO4-eq. (EP), 5.0 ± 2.0 MJ (CED), 1.4 ± 0.5 m2/y (LO), whereas per 1 m2 were 0.8 ± 0.3 kg CO2-eq (GWP), 16.3 ± 4.2 g SO2-eq. (AP), 4.9 ± 1.3 g PO4-eq. (EP), 3.8 ± 1.8 MJ (CED). Mean ECR was 5.17 ± 0.89 MJ/MJ, with 88% of gross energy provided by non-human edible feedstuffs. A large variability was found both between and within dairy systems, in terms of environmental footprint and production efficiency. Impact values were slightly greater per unit of product and lower per unit of area in traditional than in intensive farms, although generally without significant differences. Production efficiency of traditional farms was 17% lower in terms of ECR but 59% greater in terms of HeECR, due to a lower proportion of purchased concentrates in animal rations, with a positive contribution to food balance and diet self-sufficiency. These results indicate that the transition from traditional towards intensive systems improved only slightly the environmental footprint of dairy farming, but increased markedly its dependence on external concentrate feeds and the feed-food competition. In perspective, different aspects of mountain dairy systems, such as the conversion into food of human non edible feeds, the low impacts at the local scale, the ability to conserve grasslands under a land-sharing perspective, and in general the associated ecosystem services, should be considered when aiming to improve their environmental sustainability.

Looking for high-production and sustainable diets for lactating cows: A survey in Italy

The aim of the present study was to evaluate, through a survey conducted on commercial farms, the global warming potential (GWP) of different lactating cow total mixed rations (TMR) and to identify the best dietary strategies to increase feed efficiency (FE) and reduce enteric CH4 emission. A total of 171 dairy herds were selected: data about dry matter intake (DMI), lactating cow TMR composition, and milk production and composition were provided by farmers. Diet GWP (kg of CO2 equivalents; CO2eq) was calculated as sum of GWP (kg of CO2eq) of each included ingredient, considering inputs needed at field level, feed processing, and transport. For soybean solvent meal, land use change was included in the assessment. Enteric methane production (g/d) was estimated [using the equation CH4 (g/d) = 2.54 + 19.14 × DMI] to calculate CH4 emission for kilograms of fat- and protein-corrected milk (FPCM). The data set was analyzed by generalized linear model and logistic analysis using SAS 9.4 (SAS Institute Inc., Cary, NC). The frequency distribution showed wide variation among farms for GWP (kg of CO2eq) of TMR: approximately 25% of the surveyed farms showed a diet GWP of 15 kg of CO2eq, 20% showed a GWP of 13 kg of CO2eq, and 16.7% showed a GWP of 17 kg of CO2eq. The variation among farms was due to the feedstuffs used. Among feedstuffs, soybean meal (SBM) had the highest correlation with the GWP of the TMR as shown by the following equation: TMR GWP (kg of CO2eq) = 2.49 × kg of SBM + 6.9 (R2 = 0.547). Moreover, diets with inclusion of SBM >15% of dry matter (DM) did not result in higher milk production than diets with a lower inclusion of SBM (≤15%). Average daily milk production of cows was 29.8 [standard deviation (SD) 4.83] kg with fat and protein contents of 3.86% (SD 0.22) and 3.40% (SD 0.14), respectively. The average DMI (kg/d) of lactating cows was 22.3 (SD 2.23). Logistic analysis demonstrated that corn silage ≤30% of diet DM was associated with higher FE. Almost 50% of farms had an average value of 15.0 g of CH4/kg of FPCM and about 30% of farms had an average of 12.5 g of CH4/kg of FPCM. The results demonstrated that lower enteric CH4 production was related to inclusion (% of diet DM) of ≤12% alfalfa hay and >30% corn silage. Diets with >34% neutral detergent fiber had higher CH4 production (>14.0 g/kg of FPCM) than those with lower neutral detergent fiber content. In contrast, lower enteric CH4 production (≤14.0 g/kg of FPCM) was related to diets characterized by net energy of lactation (NEL) >1.61 Mcal/kg and >4% ether extract. The variability in TMR GWP shows significant potential for reducing the GWP of a diet through choice and inclusion levels of ingredients (mainly SBM) and the possibility of decreasing methane enteric emission associated with milk production on a commercial scale.

Dairy sheep carbon footprint and ReCiPe end-point study

Abstract Sheep milk production is an important livestock sector for the European Mediterranean countries including the regions of southern Italy. The main objective of this study was to investigate the carbon footprint and the related damages generated by dairy sheep farming by using a simplified LCA approach based on the ReCiPe End-point method. We used 1 kg of Fat and Protein Corrected Milk (FPCM) as functional unit (FU). The average flock size was about 400 animals and the average farm size was about 66 ha. In addition to milk all farms produced meat and wool. Therefore, we performed an economic allocation by dividing all inputs and outputs among milk and the other two co-products (meat and wool), based on farm financial statements. The CF impact determined by 1 kg of FPCM was 3.78 kg CO2-eq. The highest CF impact was mainly due to the enteric fermentation, producing biogenic CH4 as the prevalent chemical compound, followed by the production of meadow hay. Based on the ReCiPe End-point method the impact of 1 kg of FPCM from dairy sheep farming was 7.35 E-06 Disability Adjusted Life Years, whereas the Damage to Ecosystem Diversity was 3.29 E-07 Species*year and the value of the Damage to Resource Availability 0.025 $. In conclusion, the environmental management and sustainability of sheep farms should be constantly controlled with the aim of minimizing their impacts without compromising the competitiveness of this productive sector.

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.

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

Simple SummaryThis paper attempts to analyze the impact of organic livestock farming in dehesas through the analysis and review of the carbon footprint of seven extensive organic farming systems in various dehesas in the southwest of Spain. The method used was life cycle assessment, taking into account both greenhouse emissions and carbon sequestration. Greenhouse emissions estimated are those derived from livestock digestion, manure management, soil management, and off-farm inputs (feeding, fuels, and electricity). Carbon sequestration calculations consider carbon fixation due to pasture and crop waste and carbon fixation in soil due to manure fertilization. The farms under study represent all the species bred in the farms and all the habitual farming systems existing in dehesas, with the following types being under analysis: beef cattle, sheep for meat, Iberian pigs, and dairy goats. The emissions identified in the farms under study have been found to be lower than those from conventional farms, with values of 16.27 and 10.43 kg CO2eq/kg of live weight for beef cattle, 13.24 and 11.42 kg CO2eq/kg of live weight for sheep, 1.19 kg CO2eq/kg of milk for goats, and 4.16 and 2.94 kg CO2eq/kg of live weight for pigs. The levels of carbon sequestration are also noticeably higher, with compensation being up to 89% in meat producing ruminants’ farms, 100% in dairy goats’ farms, and values compensating the total emissions in the case of Iberian montanera pig farms.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.

Water footprint and economic water productivity assessment of eight dairy cattle farms based on field measurement

Water scarcity prevailing in the drylands is threatening the sustainability of livestock production systems. The water footprint (WF) indicator was proposed as a metric of water use. This study aimed to determine the WF and the economic water productivity (EWP) of 1 kg of fat and protein-corrected milk (FPCM) in eight dairy farms (n = 8; animals = 117 ± 62; area = 198 ± 127; 95% confidence level) in northern Tunisia. Then, to assess the effects of three simulation scenarios targeting the reduction of the WF of milk production (scenario A: using triticale silage to replace, on DM basis, the silage of maize, sorghum or ray-grass; scenario B: reducing by 56% the wastage of water devoted to milking, cooling, cleaning and servicing; scenario C: using concentrate feeds imported from Brazil and Argentina instead of that imported from France). A year-round monitoring of on-farm practices was performed using water-meters and recording equipment installed in key locations in the target dairy farms: (i) water used for feed production, (ii) cow watering, (iii) servicing water, (v) crop and forage production and (iv) economic and production performance were controlled by water source (green and blue). Over the eight farms evaluated, milk production consumed on average 1.36 ± 0.41 m3/kg FPCM, of which 0.93 ± 0.40 m3/kg FPCM was green water and 0.42 ± 0.30 m3/kg FPCM was blue water. However, virtual water of 1 kg FPCM averaged 43% ± 14.3%. Water used for feed production for lactating cows represents approximately 87% ± 6% of the total WF of milk production. However, drinking and servicing water contributed by 3.75% ± 2% and 9% ± 5% to the total WF of milk, respectively. The EWP assessment revealed that the selected dairy farms had a relatively small gross margin per m3 of water averaging US$ 0.05 ± 0.04. The variation in WF of milk was mainly associated with diets’ ingredients, which affected milk productivity and water consumption. Scenario analysis indicated that using feed with less water requirements or importing feeds from countries where its water consumption is low could reduce consumptive water use for milk production by up to 16%. The efficient use of servicing water could reduce blue WF of milk by up to 4%. The implementation of these measures would lead to potential total water savings in the Tunisian dairy sector of 646 million m3 per year (30%).

Management options to reduce the environmental impact of dairy goat milk production

Although numbers are still low compared to cattle rearing, intensive dairy goat farms have been widely spreading in the Italian livestock systems. Since goats are quite rustic, they can easily adapt to different management practices; however, improving the efficiency can make the difference, both in productivity and on the environmental impact attributed to goat milk production.In the present study, the Life Cycle Assessment (LCA) approach was used to quantify the potential environmental impact of goat milk production system in 17 farms in Lombardy (Northern Italy). Together with the environmental assessment, statistical analysis was carried out in order to determine whether it was possible to identify any relation among the variables that characterise this farming system.From an environmental point of view, it has been shown that the lower the individual milk production, the more it affects the environmental impact: specifically, the carbon footprint appears higher than the one emitted by cattle milk production. Climate Change resulted, on average, equal to 2.67 kg CO2 eq/kg Fat and Protein Corrected Milk (FPCM) with a wide variability (min: 1.12 kg CO2 eq/kg FPCM; max: 5.05 kg CO2 eq/kg FPCM). Purchased feed was the main hotspot for several environmental impact categories (such as freshwater eutrophication, land use and mineral, fossil and renewable resources depletion). Enteric emissions and emissions from manure storage were hotspots for climate change, particulate matter and terrestrial acidification. The C sequestration during crop cultivation was not considered. As shown by the statistical analysis, the main driver which influenced the 6 main impact categories was, in fact, individual milk production. The environmental assessment was also performed considering a second Functional Unit (FU) (i.e. 1 ha of land) and the statistical analysis conducted on this FU showed the relevance of livestock intensity. In addition to this, the statistical analysis also showed how a restricted land availability can negatively affect the environmental outcome. This study represents one of the first studies on the environmental impact assessment of dairy goat milk production. Additionally, studying two FUs and using a statistical analysis approach helped to identify the main management options to which farmers should pay attention to improve goat milk production from an environmental point of view.

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.

Evaluation of Water Scarcity Footprint for Taiwanese Dairy Farming.

Raw milk production in Taiwan has increased year after year, which means that the environmental impact might also be intensified in certain regions. To balance both consumer demand and environmental sustainability, evaluating the potential impact and understanding the causal relationship between production and environment is imperative. This study applied the life cycle assessment (LCA) protocol to explore water consumption for raw milk production from cradle to farm gate of five dairy farms in Hsinchu County and evaluate the stress-weighted water scarcity footprint (WSF) as well as the water scarcity productivity (WSP) of the 16 Taiwanese counties and cities. Results indicated that the highest stress-weighted WSF of the dairy farms for raw milk production was located in northern and central Taiwan and was around 44.8 H2Oeq/kg fat- and protein-corrected milk (FPCM). On the other hand, both the smallest stress-weighted WSF (about 2.2 H2Oeq/kg FPCM) and the highest WSP (0.749 kg FPCM/m3 water) of the dairy farms were located in Nantou and Chiayi Counties, because these two counties were the least water-stressed regions in Taiwan. The achievement of this study could be the first and important reference for the sustainable production of raw milk and optimizing the industrial policy of dairy farming by policy makers.

Improvements to dairy farms for environmental sustainability in Grana Padano and Parmigiano Reggiano production systems

Grana Padano (GP) and Parmigiano Reggiano (PR) are the two most important Italian PDO cheeses. To improve the environmental sustainability of their production, a Life Cycle Assessment (LCA) was completed on 84 dairy farms located in the province of Mantova (Northern Italy). In particular, 33 farms delivered milk for GP production, whereas 51 farms to dairies for PR production. In GP farms, maize silage represented 33.7% of total farmland and alfalfa represented 28.1%. While in PR farms, alfalfa represented 63.6% of total farmland. Fat and Protein Corrected Milk (FPCM) and Dairy Efficiency (DE, calculated as kg of produced FPCM per kg of DM intake) were different in the two production system: FPCM was 30.2 ± 4.32 kg/d in GP farms and 25.0 ± 4.71 kg/d in PR farms; DE was 1.35 ± 0.26 in GP farms, and 1.15 ± 0.22 in PR farms. Mitigation strategies to improve both environmental and economic sustainability were suggested focussing on forage crop production, milk production, herd management and off-farm purchased feed. From the preliminary results, there is evidence that improvements are needed. Climate Change (kg CO2 eq/kg FPCM) and Land Use (kg Carbon deficit/kg FPCM) were similar (1.38 ± 0.33 and 19.3 ± 7.08 for GP system; 1.46 ± 0.37 and 21.8 ± 11.4 for PR system). The most efficient farms in terms of milk production and DE generally showed the best environmental and economic sustainability, while the others show worse outcomes, mainly due to poor DE, livestock-management issues, feed purchase and ration composition.Highlights84 farms producing milk for Grana Padano and Parmigiano Reggiano cheese were studied in the Province of Mantova.Life Cycle Assessment was used to quantify the environmental impacts of farms and statistical analysis was helpful to identify 6 clusters.Farm, animal and milk efficiencies were poor and mitigation strategies to improve the sustainability of milk production were suggested.

Production, partial cash flows and greenhouse gas emissions of simulated dairy herds with extended lactations

The transition period is the most critical period in the lactation cycle of dairy cows. Extended lactations reduce the frequency of transition periods, the number of calves and the related labour for farmers. This study aimed to assess the impact of 2 and 4 months extended lactations on milk yield and net partial cash flow (NPCF) at herd level, and on greenhouse gas (GHG) emissions per unit of fat- and protein-corrected milk (FPCM), using a stochastic simulation model. The model simulated individual lactations for 100 herds of 100 cows with a baseline lactation length (BL), and for 100 herds with lactations extended by 2 or 4 months for all cows (All+2 and All+4), or for heifers only (H+2 and H+4). Baseline lactation length herds produced 887 t (SD: 13) milk/year. The NPCF, based on revenues for milk, surplus calves and culled cows, and costs for feed, artificial insemination, calving management and rearing of youngstock, was k€174 (SD: 4)/BL herd per year. Extended lactations reduced milk yield of the herd by 4.1% for All+2, 6.9% for All+4, 1.1% for H+2 and 2.2% for H+4, and reduced the NPCF per herd per year by k€7 for All+2, k€12 for All+4, k€2 for H+2 and k€4 for H+4 compared with BL herds. Extended lactations increased GHG emissions in CO2-equivalents per t FPCM by 1.0% for All+2, by 1.7% for All+4, by 0.2% for H+2 and by 0.4% for H+4, but this could be compensated by an increase in lifespan of dairy cows. Subsequently, production level and lactation persistency were increased to assess the importance of these aspects for the impact of extended lactations. The increase in production level and lactation persistency increased milk production of BL herds by 30%. Moreover, reductions in milk yield for All+2 and All+4 compared with BL herds were only 0.7% and 1.1% per year, and milk yield in H+2 and H+4 herds was similar to BL herds. The resulting NPCF was equal to BL for All+2 and All+4 and increased by k€1 for H+2 and H+4 due to lower costs for insemination and calving management. Moreover, GHG emissions per t FPCM were equal to BL herds or reduced (0% to −0.3%) when lactations were extended. We concluded that, depending on lactation persistency, extending lactations of dairy cows can have a positive or negative impact on the NPCF and GHG emissions of milk production.

Optimal Housing and Manure Management Strategies to Favor Productive and Environment-Friendly Dairy Farms in Québec, Canada: Part I. Representative Farm Simulations

Abstract. Tie-stall housing (93%) and solid manure management (44%) are used on many dairy farms in the province of Québec, Canada. However, this could change in the near future because the rise in average herd size and the popularity of milking robots are such that the industry expects an increase in free-stall dairies managing manure with liquid systems. This shift could affect the carbon (C), nitrogen (N), and phosphorus (P) footprints of Québec’s dairy production. In this context, whole-farm modeling (N-CyCLES), considering all the production cycle, provides a tool for evaluating the economics and environmental impacts of standard housing and manure management systems (Part I) in combination with different mitigation approaches (Part II). Two representative dairy farms in southwestern Québec (SWQ; 45.3° N, 73.2° W) and eastern Québec (EQ; 48.45° N, 68.1° W) were simulated considering four scenarios involving combinations of tie-stall or free-stall housing and solid or liquid manure management. Maximum farm net income (FNI) was $0.33 and $0.18 kg-1 of fat- and protein-corrected milk (FPCM) for the SWQ and EQ farms, respectively, with N and P footprints of 12.22 to 16.99 g N kg-1 and 0.52 to 0.79 g P kg-1 of FPCM in SWQ, and 11.48 to 15.39 g N kg-1 and 1.41 to 1.88 g P kg-1 of FPCM in EQ. Greenhouse gas (GHG) emissions reached 1.78 to 1.87 kg CO2e kg-1 and 1.67 to 1.71 kg CO2e kg-1 of FPCM in SWQ and EQ, respectively. The SWQ farm was associated with greater production of cash crops but also greater imports of fertilizers and purchased feeds, which negatively affected the N footprint and GHG emissions. Housing and manure management types did not influence FNI. Free-stall dairies were associated with greater N surpluses. Nevertheless, they emitted slightly less GHG than tie-stall dairies. Dairy farms under liquid manure management imported less fertilizers and produced less GHG despite greater CH4 emissions. As a result, the current transition toward free-stall barns and liquid manure systems in Québec seems advantageous from an environmental standpoint without compromising economic profitability. Keywords: Climate change, Dairy cow, Farm net income, Free stall, Greenhouse gas emission, Manure handling, Mitigation, Nutrient footprint, Tie stall, Whole-farm model.

Carbon footprint of dairy goat production systems: A comparison of three contrasting grazing levels in the Sierra de Grazalema Natural Park (Southern Spain)

The main objective of this study was to analyze the carbon footprint (CF) of grazing dairy goat systems in a natural park according to their grazing level. A total of 16 representative grazing goat farms in southern Spain were selected and grouped into three farming systems: low productivity grazing farms (LPG), more intensified grazing farms (MIG) and high productivity grazing farms (HPG). Their CF was analyzed, including greenhouse gas emissions and soil C sequestration according to the farms' grazing level and milk productivity, taking into account different functional units (one kilogram of fat and protein corrected milk (FPCM) and one hectare) and milk correction. Results showed that all variables differed according to the milk correction applied as the values for cow's milk correction were 41% lower than for sheep's milk correction. Total emissions and contributions of soil carbon sequestration differed according to farming system group; LPG farms had higher total emissions than MIG and HPG farms, however total carbon sequestration was lower in the MIG farms than in the LPG and HPG farms. The CF values ranged from 2.36 to 1.76 kg CO2e kg−1 FPCM for sheep's milk correction and from 1.40 to 1.04 kg CO2e kg−1 FPCM for cow's milk correction. No differences were found between farming system groups in either of the two cases but when calculations took hectare of land as a functional unit, the contribution of MIG farms to the CF was 85% higher than LPG and HPG farms. Therefore it is important to take into account the functional unit used to calculate the CF by analyzing this indicator in a broader context, and including carbon sequestration by grazing livestock in the calculation. In order to reduce the CF of this type of system, it is advisable to make appropriate use of the natural resources and to reach an optimum level of milk productivity, high enough for pastoral livestock farming to be viable.

A Comprehensive Energy Analysis and Related Carbon Footprint of Dairy Farms, Part 2: Investigation and Modeling of Indirect Energy Requirements

Dairy cattle farms are continuously developing more intensive systems of management, which require higher utilization of durable and non-durable inputs. These inputs are responsible for significant direct and indirect fossil energy requirements, which are related to remarkable emissions of CO2. This study focused on investigating the indirect energy requirements of 285 conventional dairy farms and the related carbon footprint. A detailed analysis of the indirect energy inputs related to farm buildings, machinery and agricultural inputs was carried out. A partial life cycle assessment approach was carried out to evaluate indirect energy inputs and the carbon footprint of farms over a period of one harvest year. The investigation highlights the importance and the weight related to the use of agricultural inputs, which represent more than 80% of the total indirect energy requirements. Moreover, the analyses carried out underline that the assumption of similarity in terms of requirements of indirect energy and related carbon emissions among dairy farms is incorrect especially when observing different farm sizes and milk production levels. Moreover, a mathematical model to estimate the indirect energy requirements of dairy farms has been developed in order to provide an instrument allowing researchers to assess the energy incorporated into farm machinery, agricultural inputs and buildings. Combining the results of this two-part series, the total energy demand (expressed in GJ per farm) results in being mostly due to agricultural inputs and fuel consumption, which have the largest share of the annual requirements for each milk yield class. Direct and indirect energy requirements increased, going from small sized farms to larger ones, from 1302–5109 GJ·y−1, respectively. However, the related carbon dioxide emissions expressed per 100 kg of milk showed a negative trend going from class &lt;5000 to &gt;9000 kg of milk yield, where larger farms were able to emit 48% less carbon dioxide than small herd size farm (43 vs. 82 kg CO2-eq per 100 kg Fat- and Protein-Corrected Milk (FPCM)). Decreasing direct and indirect energy requirements allowed reducing the anthropogenic gas emissions to the environment, reducing the energy costs for dairy farms and improving the efficient utilization of natural resources.

A Comprehensive Energy Analysis and Related Carbon Footprint of Dairy Farms, Part 1: Direct Energy Requirements

Dairy cattle farms are continuously developing more intensive systems of management which require higher utilization of durable and not-durable inputs. These inputs are responsible of significant direct and indirect fossil energy requirements which are related to remarkable emissions of CO2. This study aims to analyze direct energy requirements and the related carbon footprint of a large population of conventional dairy farms located in the south of Italy. A detailed survey of electricity, diesel and Liquefied Petroleum Gas (LPG) consumptions has been carried out among on-farm activities. The results of the analyses showed an annual average fuel consumption of 40 kg per tonne of milk, while electricity accounted for 73 kWh per tonne of milk produced. Expressing the direct energy inputs as primary energy, diesel fuel results the main resource used in on-farm activities, accounting for 72% of the total fossil primary energy requirement, while electricity represents only 27%. Moreover, larger farms were able to use more efficiently the direct energy inputs and reduce the related emissions of carbon dioxide per unit of milk produced, since the milk yield increases with the herd size. The global average farm emissions of carbon dioxide equivalent, due to all direct energy usages, accounted for 156 kg CO2-eq per tonne of Fat and Protein Corrected Milk (FPCM), while farms that raise more than 200 heads emitted 36% less than the average value. In this two-part series, the total energy demand (Part 1 + Part 2) per farm is mainly due to agricultural inputs and fuel consumption, which have the largest quota of the annual requirements for each milk yield class. These results also showed that large size farms held lower CO2-eq emissions when referred to the mass of milk produced.

Components of feed affecting water footprint of feedlot dairy farm systems in Northern China

Abstract Freshwater consumption in animal agriculture is a significant factor affecting water resources and water environmental sustainability. Water footprint (WF), as a comprehensive assessment indicator, can be used to assess the consumptive water use in the dairy sector. The aim of this study was to assess the effects of feed components on the water consumption and WF of milk production for collective feedlot systems in China. Fourteen dairy farms, with a range of dairy cow numbers, were used as examples for the analysis. The results indicated that the average WF of milk was 882 L kg−1 FPCM (fat-and-protein-corrected milk), ranging from 639 to 1307 L kg−1 FPCM. The WF from Chinese wildrye hay, maize grain, alfalfa hay and soybean meal production accounted for 30.4%, 16.4%, 14.5% and 10.9% of the total WF, respectively, whereas the WF from embedded in animal products, respiratory vapour losses and other service water was 11.4%, implying that water consumption due to evapotranspiration from feed production was the major driver of the milk WF for the collective feedlot system in China. The variation in WF among the different dairy farms was mainly associated with the different components in the feed, which affected not only the milk productivity and feed conversion efficiency, but also the water consumption for milk production. Increase in the proportion of Chinese wildrye hay in roughages reduced the milk productivity of the cow and also increased the WF of milk. Scenario analysis indicated that using feed that consumes less water to produce or importing feed from a country where its water consumption is lower could reduce the consumptive water use for milk production by up to 22%. The results show how changing feed components and origin can reduce the freshwater consumption in livestock sectors in China.