Protein-corrected Milk Research Articles

Use of CLEANED to Assess the Productive, Environmental, and Economic Impact of Dairy Farms in the Peruvian Amazon

Dairy farms in developing countries are key to fighting hunger and poverty. However, their environmental and economic impact in the tropical region of Peru has been scarcely studied. The CLEANED tool, developed by the Alliance of Bioversity International and the International Center for Tropical Agriculture, allows us to assess the productive situation and the environmental and economic impact of different dairy systems. The objective of the study was to use the CLEANED tool to evaluate the production, environmental, and economic impacts of extensive and semi-intensive dairy systems in the tropical region of Peru. Data from twelve dairy farms (six extensive and six semi-intensive systems), in two seasons (rainy and dry) were recorded using semi-structured surveys. The required area (ha/year), production (L milk/ha/year), environmental impact (water use in m3/product), and methane (CH4) and nitrous oxide (N2O) emissions in kg CO2eq/kg fat- and protein-corrected milk (FPCM) were estimated, and the economic analysis was performed for each livestock system. Results showed that the required area was of 28.9 and 32.6 ha, milk yield was 382 and 1254 L/ha/year, water use was 0.59 and 0.29 m3/kg FPCM, CH4 emissions were 1.7 and 1.0 kg CO2eq/kg FPCM, and N2O emissions were 0.22 and 0.17 kg CO2eq/kg FPCM, for the extensive and semi-intensive systems, respectively. The study revealed significant positive differences in semi-intensive livestock systems, including increased productivity, the reduced intensity of CH4 and N2O emissions, and greater profitability.

Transforming the feeding regime towards low-input increases the environmental impact of organic milk production on a case study farm in central germany

Abstract Purpose Despite the direct effect of the feeding regime on the environmental impacts of dairy farming systems, its level of intensity, particularly in organic systems, has rarely been investigated. This study compares the environmental impact of a high-input feeding regime with a grassland-based, low-input feeding regime scenario within an organic milk production system conducted on Gladbacherhof, the research farm of Justus Liebig University Giessen, in Central Germany. Methods An integrated Life Cycle Assessment (LCA) analysis was performed from a cradle-to-farm gate perspective to quantify five environmental impacts, namely Global Warming (GW), Non-Renewable Energy Use (NREU), Land Use (LU), Terrestrial Acidification (TA), and Freshwater Eutrophication (FE). All agronomic data of the Gladbacherhof research farm, averaged over the years 2010–2017, were included. When not directly measured on the farm, ecoinvent data were included. Results and discussion Contrary to our hypothesis, the results suggest that a grassland-based low-input system has a higher environmental impact as compared to a high-input system for each of the five impact categories when using fat and protein-corrected milk (FPCM) as the functional unit. A 50% reduction in concentrates and exclusion of maize silage from the feed ration in the modelled low-input production system lead to a 20% drop in milk yield. To balance the energy content in low-input feeding ration, longer grazing period and higher amount of hay, alfalfa, and grass silage are required. This in turn results in higher emissions from enteric fermentation, manure management, and feed production and hence in higher environmental impact, particularly for GW, TA, and FE. Conclusions This study is one of the few that directly explores the environmental impact of feeding intensity in an organic milk production system. Nevertheless, there is a lack of research on consolidated emission factors for several greenhouse gas (GHG) sources in organic livestock and cropping systems to perform more robust carbon footprint calculations that comply with the Intergovernmental Panel on Climate Change (IPCC) Tier 3 GHG reporting guidelines. To generalize the results at the regional or national scale, direct comparisons with a larger number of organic farms representative of high-input and low-input intensities are still essential.

Genetic parameters for methane production, intensity, and yield predicted from milk mid-infrared spectra throughout lactation in Holstein dairy cows

Genetic selection to reduce methane (CH4) emissions is a promising solution for reducing the environmental impact of dairy cattle production. Before such a selection program can be implemented, however, it is necessary to have a better understanding of the genetic determinism of CH4 emissions and how this might influence other traits of interest. In this study, we performed a genetic analysis of 6 CH4 traits predicted from milk mid-infrared spectra. We predicted 4 CH4 traits in g/d (MeP, calculated using different prediction equations), one in g/kg of fat- and protein-corrected milk (MeI), and one in g/kg of dry matter intake (MeY). Using an external data set, we determined these prediction equations to be applicable in the range of 70 to 200 DIM. We then estimated genetic parameters in this DIM range using random regression models on a large data set of 829,025 spectra collected between January 2013 and February 2023 from 167,514 first- and second-parity Holstein cows. The 6 CH4 traits were found to be genetically stable throughout and across lactations, with average genetic correlations within a lactation ranging from 0.93 to 0.98, and those between lactations ranging from 0.92 to 0.98. All 6 CH4 traits were also found to be heritable, with average heritability ranging from 0.24 to 0.45. The average pairwise genetic correlations between the 6 CH4 traits ranged from -0.15 to 0.77, revealing that they are genetically distinct, including the 4 measurements of MeP. Of the 6 traits, 2 measures of MeP and MeI did not present antagonistic genetic correlations with milk yield, fat and protein contents, and SCS, and can probably be included in breeding goals with limited impact on other traits of interest.

Quantification of the Environmental Impact of Feeding Yeast Probiotic Saccharomyces cerevisiae Actisaf Sc 47 in Dairy Cow: A Life Cycle Assessment Approach.

Today, one of the major challenges of dairy farmers is to reduce their environmental footprint to establish more effective, efficient, and sustainable production systems. Feed additives such as yeast probiotics could potentially allow them to achieve these objectives through the improvement of milk production, feed efficiency, and ration valorization, hence mitigating the environmental impacts of milk production. In this study, the life cycle assessment (LCA) principle was performed to estimate the environmental impact of the production and supplementation of a commercial yeast probiotic (Actisaf Sc 47) in three trials performed in three different countries that are representative for around 50% of the milk production in Europe: France (French trial), United Kingdom (UK trial), and Germany (German trial). For each trial, two groups of animals were compared: control, without Actisaf Sc 47 supplementation, used as baseline; and experimental, with Actisaf Sc 47 supplementation at 5 or 10 g/cow/day. Different impact categories were analyzed for each group to calculate the impact of producing 1 kg of fat- and protein-corrected milk. An initial analysis was done only during the period of Actisaf Sc 47 supplementation and showed than the supplementation with Actisaf Sc 47 reduced, on average by 5%, the carbon footprint during the three trials. A second analysis was done via the extrapolation of all the data of each trial to an annual farm level, including the lactation period (305 days), dry period (60 days), and the period with and without Actisaf Sc 47 supplementation. Reported at a farm annual scale, the average reduction allowed by Actisaf Sc 47 supplementation was 2.9, 2.05, 2.47, 1.67, 2.28, 2.18, 2.14, and 2.28% of the carbon footprint, land use, water use, resource use, acidification, freshwater eutrophication, marine eutrophication, and terrestrial eutrophication, respectively. On average, the production of 1 kg of fat- and protein-corrected milk by using Actisaf Sc 47 was shown to improve environmental impacts compared to control. Regarding Actisaf Sc 47 production, the LCA showed that the production of 1 kg of Actisaf Sc 47 emitted 2.1 kg CO2 eq with a negligible contribution to total the carbon footprint of milk ranging from 0.005 to 0.016%. The use of Actisaf Sc 47 in dairy cows could then result in different positive outcomes: improving performance and efficiency while reducing the global carbon footprint.

ENVIRONMENTAL AND ECONOMIC ASSESSMENT OF COMPOST BARN SYSTEM IN MILK PRODUCTION IN BRAZIL

Intensifying animal productivity in specific areas is recommended to reduce or mitigate greenhouse gas emissions associated with these production systems. This study evaluates the environmental and economic impacts of six dairy farm using an intensive Compost Bedding Pack Barns system in Minas Gerais, Brazil. A Life Cycle Assessment grounded in the IPCC 2006 guidelines, was conducted as a valuable tool in environmental management, providing a comprehensive understanding of the environmental costs from feed cultivation to milk distribution. The Life Cycle Assessment results showed an average carbon footprint of 1.48 kg of CO2 eq. per liter of fat- and protein-corrected milk. Alongside this, an economic and financial viability assessment using investment analysis tools indicated that, despite initial investments and high fixed and variable costs, the system presents strong economic results. These findings support the premise that intensifying productive systems can mitigate environmental impacts while ensuring financial profitability, enhancing the sustainability and competitiveness of Brazil's dairy industry.

Greenhouse gas emissions and nutrient use efficiency assessment of 6 New York organic dairies

Improving nutrient use efficiency and reducing GHG emissions are important environmental priorities for organic-certified dairy operations. The objectives of this research were to quantify annual nutrient use and GHG emissions in 6 organic New York dairy farms. Farm-gate nutrient mass balances (NMB) were estimated with the Cornell NMB calculator. Whole-farm GHG emissions were estimated using the Cool Farm Tool (CFT) and COMET. Farm-gate NMB were low, ranging from -6.5 to 19 kg N/ha for N1 (without legume N fixation), 26 to 71 kg N/ha for N2 (including N fixation), -2.4 to 8.2 kg P/ha for P, and 1.1 to 19.8 kg K/ha for K. Additional nutrient imports, coupled with nutrient management planning, adequate legume stands, and diet balancing may help improve P balances and ensure no N deficiencies in the system. Estimates of annual GHG emissions intensity ranged from 0.98 to 2.10 kg of CO2-equivalents (CO2-eq) per kilogram of fat- and protein-corrected milk (FPCM) estimated by CFT, and from 0.69 to 2.48 kg CO2-eq/kg FPCM estimated by COMET. Enteric fermentation, feed production, and fuel and energy use represented the largest sources of GHG. For farms with liquid manure storages, manure management was also a significant source. Estimates of soil carbon (C) stock changes from CFT were in agreement with or smaller than previous studies, and estimates from COMET were in agreement or greater. Variability and uncertainty in the results for soil C stock change indicate that more research and new protocols are needed. The effects of individual management changes on GHG emissions intensity were small, ranging from -8 to +7% in CFT, and -8% to +8% in COMET. The management changes that resulted in the largest reductions in GHG emissions intensity included increasing individual cow productivity and ratio of milk to total feed, and implementation of manure treatment systems.

Effects of calving interval of dairy cows on development, metabolism, and milk performance of their offspring

Extending the voluntary waiting period (VWP) for insemination in dairy cows is of interest as a strategy to reduce the frequency of calving events and inseminate at a moment with fewer fertility problems. Little is known about the calves born from dams with a different VWP followed by a different calving interval (CInt). The objective of the current study was to identify the effect of dam's CInt on body condition, metabolic status, and milk production of their offspring from birth until 100 DIM of the offspring's first lactation. Holstein-Friesian dairy cows (n = 154, 41 primiparous, 113 multiparous) were blocked according to parity, milk yield, and SCC and randomly assigned to a VWP of 50, 125, or 200 d. Female calves (n = 62) from cows with different CInt were monitored from birth until their first calving event as heifer. Certain dams were not successfully inseminated soon after the planned VWP, resulting in differences between the intended VWP and the actual CInt. Calves were regrouped according to their dam's actual CInt (CInt_1: 324-408 d; CInt_2: 409-468 d; CInt_3: 469-586 d). The dam's CInt did not affect calf birth weight. From birth to weaning, the calves born to dams in CInt_1 had a higher plasma nonesterified fatty acids (NEFA) concentration (0.34 mmol/L; CI: 0.30, 0.37) than CInt_2 (0.28 mmol/L; CI: 0.26, 0.31) and CInt_3 (0.26 mmol/L; CI: 0.24, 0.29) calves. Calves born to dams with a shorter CInt (CInt_1) had greater IgG and IgM against keyhole limpet hemocyanin (KLH) than CInt_3 (IgG: 6.05 ± 0.30 vs. 4.64 ± 0.30; IgM: 6.45 ± 0.17 vs. 5.89 ± 0.16, respectively; mean ± SE) before weaning. After weaning till calving, CInt_1 calves tended to have greater plasma NEFA concentration than CInt_3-calves. During the first 100 DIM, a longer CInt of the dams resulted in lower plasma IGF_1 (CInt_2), lower milk lactose (CInt_3), and lower fat- and protein-corrected milk (FPCM; CInt_2) in offspring, compared with shorter CInt of the dams (CInt_1). Collectively, a longer CInt in dams did not affect birth weight of their calves or BW during the weaning or rearing phase. From birth till weaning, a longer CInt in dams resulted in less anti-KLH IgG and lower plasma NEFA concentration in plasma of the calves. During the first lactation of their offspring, a longer CInt in dams can result in a lower plasma IGF_1 and FPCM during the first 100 DIM, although effects were not present in all CInt categories.

Challenges When Assessing Water-Related Environmental Impacts of Livestock Farming: A Case Study of a Cow Milk Production System in Catalonia

Water availability is a local issue of growing importance in Mediterranean areas where water scarcity linked to climate change and population growth is already leading to increased competition for this resource. This study is aimed at the following: (i) assessing the water-related environmental impacts (water use, freshwater ecotoxicity and eutrophication, marine eutrophication, acidification, human toxicity, and ionizing radiation) along the production chain of cow milk in Catalonia, northeastern Spain; and (ii) addressing the issues encountered (modelling choices, data gaps and inconsistencies) which t can affect the quality of results when performing a water-footprint comprehensive assessment, focusing on water use and associated water scarcity impacts. The scope included the process from the extraction of raw materials up to the distribution of the packaged fat- and protein-corrected milk to the distribution centres of the supermarket chains and markets. Results showed the farm stage to be determinant (contributing to over 60% of the impact), due to the impact of feed production. Impact results were in the range of the European benchmark given by the Product Environmental Footprint Category Rules for dairy products, except for the water scarcity footprint which was one order of magnitude larger than the reference value, due to water scarcity in Spain. Considering compound feed ingredients with a lower water scarcity footprint, and research into slurry treatment for its use as irrigation and cleaning water (without compromising safety and health) could help reduce this impact. Water accounting and traceability along the production chain could support the dairy industry to take responsibility for the consequences of their production choices.

Dietary concentrate supplementation increases milk production and reduces predicted greenhouse gas emission intensity in pasture-based commercial dairy farms

Controlled studies have extensively documented that concentrate supplements typically increase enteric CH4 emissions and milk yield and reduce emissions per unit of milk produced and dry matter intake. However, no studies have been conducted to determine the effect of concentrate on predicted greenhouse gas emissions from dairy farms representing the Australian pasture-based farming system. Thus, this study sought to determine how dietary concentrate supplementation affects enteric and manure CH4, and N2O of Australian pasture-based dairy farms. The Australian Dairy Carbon Calculator was used, which incorporates emission factors and methodologies used in the National Greenhouse Gas Inventory as reported to the Intergovernmental Panel on Climate Change. Primary data were collected and analyzed from 120 commercial farms in Australia's major dairy regions. Then the farms were divided into 4 groups based on their dietary concentrate supplementation: ≤1 (low; 15 farms), 1 to 2 (moderate; 35 farms), 2 to 3 (high; 35 farms), and ≥3 (very high; 35 farms) t of concentrate dry matter (tDM) per cow per year. Sources of greenhouse gas emissions were CO2 from concentrate production, enteric CH4, and manure CH4 and N2O. Total dry matter intake, milk yield, and daily enteric CH4 production (g/d) quadratically increased with concentrate level, whereas greenhouse gas emission intensity of milk production (kg of CO2 equivalent per kg of fat- and protein-corrected milk) decreased by 14% for farms supplementing with ≥3 tDM/cow per year compared with those supplementing with ≤1 tDM/cow per year of dietary concentrate. The N2O and CH4 emissions from manure increased quadratically and linearly, respectively, with the increasing supplementation of concentrate. Farms supplementing 2 to 3 tDM/cow per year showed substantial increases in gross income, gross margin, earnings before interest and tax, and net income ($/cow per year) compared with those supplementing of ≤1, 1 to 2, and ≥3 tDM/cow per year. Overall, increasing dietary concentrate supplementation for dairy cows resulted in increased milk production per cow, reduced greenhouse gas emissions per unit of milk produced, and increased income and profit. However, a comprehensive life cycle assessment study is needed to account for carbon sequestration by other farm components, such as pastures and trees, which were not considered in the present study. In addition, the present study was based on modeling and did not gather ground truth information for DMI, digestibility, crude protein, and urinary and fecal N excretion. Therefore, data should be interpreted with caution, and studies gathering such information are encouraged.

Environmental Performance of a Mixed Crop–Dairy Cattle Farm in Alexandria (Romania)

Agricultural specialization has increased considerably in Europe over the last decades, leading to the separation of crop and livestock production at both farm and regional levels. Such a transformation is often associated with higher environmental burdens due to excessive reliance on exogenous inputs and manure management issues. Reconnecting crop and livestock production via mixed farming systems (MFSs) could improve circularity and resilience, leading to reduced environmental impacts. The objective of this study was to evaluate the life cycle environmental performance of a commercial mixed crop–dairy cattle farm in Romania and to compare it against the corresponding specialized systems. The evaluation covered both dairy cattle production (milk and meat) and cash crops. Overall, the results show that the coupled system improves environmental performance by reducing the over-reliance on high-impact inputs like synthetic fertilizers and exogenous feed. The carbon footprint for the milk production of the studied system (1.17 kg CO2 eq.) per kg of fat- and protein-corrected milk (FPCM) was 10% lower than the mean value of common intensive milk production systems. The eutrophication impacts (2.52 × 10−4 kg P eq and 2.67 × 10−4 kg N eq./kg of FPCM) presented values of one order of magnitude less than their specialized counterparts. However, the impacts of the studied MFS, albeit lower than those for comparable specialized systems, still remain relatively high. In particular, methane emissions from enteric fermentation (0.54 kg CO2 eq./kg FPCM) were a major contributor to the carbon footprint. This highlighted the need to address the elevated emissions from enteric fermentation with better feed management, as well as improving and reinforcing the system’s self-sufficiency.

Grazing behavior of dairy cows under contrasting pasture allocation frequencies and areas

This study aimed to compare grazing behavior of dairy cows with highly contrasting pasture allocation frequencies. The study ran from September 9, 2022, to December 2, 2022 (12 wk), during a time when daily pasture growth was expected to exceed daily herd intake. Three pasture allocation frequencies were compared, each with 11 spring-calving cows grazing a 4-ha farmlet. The allocations were high frequency rotational grazing (HFRG; 32.5 m2/cow per allocation and 4 allocations/d), rotational grazing with weekly allocations (7RG; 909 m2/cow per allocation and each allocated area continuously grazed over 7 d), and continuous grazing (CG; 1,818 m2/cow per allocation). Animal behavior was monitored using IceQube accelerometers (Peacock Technology) and CowManager ear tags (Agis Automatisering BV). Milk yield and composition were measured and pasture cover was estimated. Daily eating time was highest for CG animals, whereas lying time, lying bouts, and ruminating time were lowest, with no differences between HFRG and 7RG. There were no differences in fat- and protein-corrected milk yield between farmlets; however, estimated accumulated pasture yield was greater with more frequent allocations. Although milk production did not differ between treatment groups, this appeared to be achieved through greater eating times when allocated pasture less frequently, at the expense of time spent lying.

Long-term effects of 3-nitrooxypropanol on methane emission and milk production characteristics in Holstein-Friesian dairy cows

The objective was to determine the long-term effect of 3-nitrooxypropanol (3-NOP) on CH4 emission and milk production characteristics from dairy cows receiving 3-NOP in their diet for a full year, covering all lactation stages of the dairy cows. Sixty-four late-lactation Holstein-Friesian cows (34% primiparous) were blocked in pairs, based on expected calving date, parity, and daily milk yield. The experiment started with an adaptation period of 1 wk followed by a covariate period of 3 wk in which all cows received the same basal diet and baseline measurements were performed. Directly after, cows within a block were randomly allocated to 1 of 2 dietary treatments: a diet containing on average 69.8 mg 3-NOP/kg DM (total ration level, corrected for intake of nonsupplemented GreenFeed bait) and a diet containing a placebo. Forage composition as well as forage-to-concentrate ratio altered with lactation stage (i.e., dry period and early, mid, and late lactation). Diets were provided as a total mixed ration, and additional bait was fed in GreenFeed units (C-Lock Inc.), which were used for emission measurements. Supplementation of 3-NOP did not affect total DMI, BW, or BCS, but resulted in a 6.5% increase in the yields of energy-corrected milk and fat- and protein-corrected milk (FPCM). Furthermore, milk fat and protein as well as feed efficiency were increased upon 3-NOP supplementation. Overall, a reduction of 21%, 20%, and 27% was achieved for CH4 production (g/d), yield (g/kg DMI), and intensity (g/kg FPCM), respectively, upon 3-NOP supplementation. The CH4 mitigation potential of 3-NOP was affected by the lactation stage dependent diet to which 3-NOP was supplemented. On average, a 16%, 20%, 16%, and 26% reduction in CH4 yield (g/kg DMI) was achieved upon 3-NOP supplementation for the dry period, and early, mid, and late-lactation diets, respectively. The CH4 mitigation potential of 3-NOP was affected by the length of 3-NOP supplementation within a lactation stage dependent diet and by variation in diet composition within a lactation stage dependent diet as a result of changes in grass and corn silage silos. In conclusion, 3-NOP reduced CH4 emission from cows receiving 3-NOP for a year, with a positive effect on production characteristics. The CH4 mitigation potential of 3-NOP was influenced by diet type, diet composition, and nutrition value, and the efficacy of 3-NOP appeared to decline over time but not continuously. Associated with changes in diet composition, increased efficacy of 3-NOP was observed at the start of the trial, at the start of a new lactation, and, importantly, at the end of the trial. These results suggest that diet composition has a large effect on the efficacy of 3-NOP, perhaps even larger than the week of supplementation after first introduction of 3-NOP. More studies are needed to clarify the long-term effects of 3-NOP on CH4 emission and to further investigate what influence variation in diet composition may have on the mitigation potential of 3-NOP.

Short communication: Correlation of methane production, intensity, and yield with residual feed intake throughout lactation in Holstein cows

The environmental impact of dairy production can be reduced in several ways, including increasing feed efficiency and reducing methane (CH4) emissions. There is no consensus on their relationship. This study aimed at estimating the correlations between residual feed intake (RFI) and CH4 emissions expressed in g/d methane production (MeP), g/kg of fat- and protein-corrected milk methane intensity (MeI), or g/kg of DM intake methane yield (MeY) throughout lactation. We collected CH4 data using GreenFeed devices from 107 Holstein cows, as well as production and intake phenotypes. RFI was predicted from DM intake, fat- and protein-corrected milk, BW, and body condition score. Five-trait random regression models were used to estimate the individual variance components of the CH4 and production traits, which were used to calculate the correlations between RFI and CH4 traits throughout lactation. We found positive correlations of RFI with MeP and MeI ranging from 0.05 to 0.47 throughout the lactation. Correlations between RFI and MeY are low and vary from positive to negative, ranging from −0.18 to 0.17. Both MeP and MeI are favorably correlated with RFI, as is MeY during the first half of lactation. These correlations are mostly favorable for genetic selection, but the confirmation of these results is needed with genetic correlations over a larger dataset.

A carbon footprint assessment for pasture-based dairy farming systems in South Africa

Environmental impact evaluation of intensive dairy farming systems has been of growing interest recently as agriculture has several negative influences on the surrounding environment, including eutrophication, declines in biodiversity, and pollution of nearby waterbodies. Dairy production in particular is characterized by the emission of greenhouse gasses (GHG) contributing toward climate change. In this study, the carbon footprint of South African pasture-based dairy farming systems was assessed using a farm-gate life-cycle assessment (LCA) approach. A total of 82 pasture-based dairy farms across South Africa were assessed (2012–2022). The average carbon footprint across all dairy farming systems was 1.36 ± 0.21 kg CO2eq kg−1 fat- and protein-corrected milk produced (FPCM), which is higher than similar studies performed outside South Africa. Enteric fermentation had the largest influence on the carbon footprint, indicating the key role of methane as an emission source in ruminant dominated livestock systems. A difference in milk production efficiency was found between farming systems with the lowest and highest carbon footprints. Pasture-based dairy farming systems must be managed with adaptive management such as regenerative agriculture. Future research agendas should explore modeling approaches to assess the economic and environmental impact of dairy production, formulating a holistic understanding of the system dynamics while also quantifying net carbon emissions or sinks.

A Business Case for Climate Neutrality in Pasture-Based Dairy Production Systems in Ireland: Evidence from Farm Zero C

Agriculture in Ireland is responsible for producing and exporting healthy, nutritional food pivotal for meeting the Sustainable Development Goals (SDGs) such as global food security, economic development and sustainable communities. However, the agricultural sector, dominated by a large bovine population, faces the challenge of reducing greenhouse gas (GHG) emissions to reach climate neutrality by 2050. The objective of the current study was to model the environmental and economic impact of simultaneously applying farm-level climate change mitigation strategies for a conventional grass-based dairy farm in Ireland. An average farm of 52 ha with a spring-calving herd of 93 was used as a reference scenario to create a business case. Partial budgeting was used to calculate the annual net benefit. A cradle-to-grave life cycle assessment (LCA) was used to model the reduction in GHG emissions, which was expressed as kg of carbon dioxide equivalent per kilogram of fat- and protein-corrected milk (kg CO2-eq/kg FPCM). The baseline for average emissions was 0.960 kg CO2-eq/kg FPCM. An average farm would reduce its annual emissions by 12% to 0.847 kg CO2-eq/kg FPCM in Scenario 1, where climate change mitigation strategies were applied on a minimal scale. For Scenario 2, the emissions are reduced by 36% to 0.614 kg CO2-eq/kg FPCM. In terms of annual savings on cash income, an increase of EUR 6634 and EUR 18,045 in net savings for the farm are realised in Scenarios 1 and 2, respectively. The business case provides evidence that farms can move towards climate neutrality while still remaining economically sustainable.

The Water Footprint of Pastoral Dairy Farming: The Effect of Water Footprint Methods, Data Sources and Spatial Scale

The water footprint of pastoral dairy milk production was assessed by analysing water use at 28 irrigated and 60 non-irrigated ‘rain-fed’ pastoral dairy farms in three regions of New Zealand. Two water footprint methods, the WFN-based blue water footprint impact index (WFIIblue) and the Available WAter REmaining (AWARE) water scarcity footprint (WFAWARE), were evaluated using different sets of global or local data sources, different rates of environmental flow requirements, and the regional or catchment scale of the analysis. A majority (~99%) of the consumptive water footprint of a unit of pastoral dairy milk production (L/kg of fat- and protein-corrected milk) was quantified as being associated with green and blue water consumption via evapotranspiration for pasture and feed used at the studied dairy farms. The quantified WFIIblue (-) and WFAWARE (m3 world eq./kg of FPCM) indices ranked in a similar order (from lowest to highest) regarding the water scarcity footprint impact associated with pastoral dairy milk production across the study regions and catchments. However, use of the global or local data sets significantly affected the quantification and comparative rankings of the WFIIblue and WFAWARE values. Compared to the local data sets, using the global data sets resulted in significant under- or overestimation of the WFIIblue and WFAWARE values across the study regions and catchments. A catchment-scale analysis using locally available data sets and calibrated models is recommended to robustly assess water consumption and its associated water scarcity impact due to pastoral dairy milk production in local catchments.

Adding behavior traits to select for heat tolerance in dairy cattle

The increase in periods of heat waves leads to an increase in heat stress events in dairy cattle leading to welfare issues, production losses, and health issues. However, the low frequency of milk recording data makes genetic evaluation for heat tolerance still a challenge. A possible solution could be to add behavior data captured through sensors which are recorded permanently, mostly reported on a daily basis. The objective of this study was to evaluate the potential gain of adding behavior traits as proxies for genetic evaluation of heat tolerance. Behavior traits including activity time (ACT), rumination time (RUM), and eating time (EAT) were recorded for 453 Holstein cows equipped with SenseHub (Allflex Livestock Intelligence) collars from October 2019 to July 2022 in 6 herd located in the Walloon Region of Belgium. A multitrait reaction norm model based on separate temperature and humidity index (THI) thresholds was used. Results showed that behavior traits present not only interesting characteristics for genetic evaluation of heat tolerance but also for heat stress detection in farms. Indeed, sensors allow recording of behavior for all events of heat stress in lactating and nonlactating animals. Moderate heritability values were also found for the behavior traits (0.14 for ACT, 0.19 for RUM, and 0.12 for EAT), and a high ratio between the general and thermotolerance additive genetic variances was obtained. In addition, positive correlations of thermotolerance for ACT and EAT with thermotolerance for milk production (fat- and protein-corrected milk: 0.45 and 0.28, respectively) and negative genetic correlations of thermotolerance for ACT with somatic cells (somatic cell score: −0.39) were estimated. The genetic correlation matrix allows us to explain a high part of the variation for the reaction to heat stress of 2 economic traits (fat- and protein-corrected milk: 59% and somatic cell score: 31%) based on behavior data. Based on these results, behavior traits could be used to assess heat stress in nonlactating cattle for which the number of genetic evaluations for heat tolerance is still limited.

Life cycle assessment of hemp-based milk alternative production in Lower Saxony, Germany, based on a material flow analysis of a pilot scale

PurposeRecently, demand for plant-based milk products (PBMP) has increased for multiple reasons, such as the rapid population growth expected to reach 9.7 billion by 2050, health concerns such as lactose intolerance, nutritional aspects, ethical reasons, and environmental concerns. This leads to increased demand for food and competition for natural resources. Hemp-based milk is an emerging dairy alternative, and stakeholders in the supply chain are becoming increasingly interested in learning about the environmental effects of its production. This article aims for a comparative life cycle assessment of hemp-based and bovine milk with fat and protein correction to account for the differences in macronutrient content.MethodsThe cradle-to-factory gate LCA relied on experimental cultivation and milk production in Lower Saxony, Germany. Inventory was based on primary data from fields and the pilot plant of DIL e. V. and on literature and ecoinvent database to develop a life cycle assessment (LCA) model. The LCA was performed using Simapro 9.3 software and IMPACT 2002+ impact assessment method. The life cycle stages include cultivation, harvesting, and milk production. The study compared hemp-based milk to bovine milk based on 1 kg fat and protein-corrected milk (FPCM) as a functional unit (FU). Co-products are taken into consideration using mass-economic allocation.ResultsThe results showed that hemp cultivation accounted for the highest impact (99%) in the production chain of hemp milk production. The GWP of 1 kg of FPCM hemp-based milk is 0.42 kg CO2 eq. The energy consumption for 1 kg of FPCM hemp-based milk is 4.73 MJ (12.26% lower than bovine milk). The other main factors impacting hemp-based milk production were terrestrial ecotoxicity (6.444E2 kg TEG soil) and aquatic ecotoxicity (2.458E2 kg TEG water). Hemp fiber was the co-product with 40% of the allocated impacts. The results are sensitive to the changes in fat-protein contents, functional unit, and system boundaries. The results demonstrated that the impacts of hemp milk production were within the range indicated for other PBMP production and 51.7% lower than bovine milk production in terms of GWP. This range primarily stems from field emissions, fertilizer application, and machinery usage during cultivation and harvest.ConclusionThe results of the comparisons of bovine milk and hemp-based milk were dependable on the FU. The hemp-based milk has the potential to be a more sustainable alternative to bovine milk due to considerably lower impacts in impact categories—land occupation (99% lower than bovine milk), global warming (52% lower than bovine milk), and ionizing radiation (23% lower than bovine milk). It is primarily due to less use of agricultural machinery, less land requirement, and lower NH3 emissions than bovine milk in various stages of milk production.

Enteric methane emission factors of smallholder dairy farming systems across intensification gradients in the central highlands of Ethiopia

BackgroundFollowing global pledges to reduce greenhouse gas (GHG) emissions by 30% by 2030 compared to the baseline level of 2020, improved quantification of GHG emissions from developing countries has become crucial. However, national GHG inventories in most Sub-Saharan African countries use default (Tier I) emission factors (EFS) generated by the Intergovernmental Panel on Climate Change (IPCC) to estimate enteric CH4 emissions from animal agriculture. The present study provides an improved enteric CH4 emission estimate (Tier II) based on animal energy requirements derived from animal characteristics and performance data collected from about 2500 cattle in 480 households from three smallholder farming systems to represent the common dairy farming in the central highlands of Ethiopia. Using average seasonal feed digestibility data, we estimated daily methane production by class of animal and farming system and subsequently generated improved EF.ResultsOur findings revealed that the estimated average EF and emission intensities (EI) vary significantly across farming systems. The estimated value of EF for adult dairy cows was 73, 69, and 34 kg CH4/cow/year for urban, peri-urban, and rural farming systems, respectively. Rural dairy farming had significantly higher emission intensity (EI) estimated at 1.78 CO2-eq per kg of fat protein-corrected milk (FPCM) than peri-urban and urban 0.71 and 0.64 CO2-eq kg−1 FPCM dairy farming systems, respectively. The EF estimates in this study are lower than the IPCC's (2019) default value for both stall-fed high-productive and dual-purpose low-productive cows.ConclusionsThe current findings can be used as a baseline for the national emission inventory, which can be used to quantify the effects of future interventions, potentially improving the country's commitment to reducing GHG emissions. Similarly, this study suggests that increased animal productivity through improved feed has a considerable mitigation potential for reducing enteric methane emissions in smallholder dairy farming systems in the study area.

The Carbon Footprint of a 5000-Milking-Head Dairy Operation in Central Texas

Texas is the third-largest milk-producing state in the U.S., with Central Texas being the second-largest milk-producing region in Texas. The average size of a dairy herd in Texas is 1829 cows. In Central Texas alone, there are 88,000 dairy cows. However, there is a lack of environmental impact research for this region. The overall objective of this case study is to evaluate the net carbon and carbon equivalent balances for a large dairy operation in Central Texas. The dairy selected for this study has a herd size of 5000 milking cows. The data assumptions were made regarding the selected dairy’s performance and production for the 2021 production year. These data include herd size and management, milk production, crop production, feed purchases, and on-farm energy usage. The USDA-Integrated Farm System Model (IFSM) was used to estimate the daily and annual greenhouse gas emissions and environmental footprint of the dairy by quantifying the operation’s carbon footprint based on its 2021 performance and management practices. Research outcomes identify and quantify sources of greenhouse gas (GHG) emissions produced on the dairy farm. Additionally, the carbon footprint (CF) was determined by estimating the CO2 equivalents (CO2-eq) emitted or sunk from animal and manure emissions, direct and indirect land emissions, net biogenic and anthropogenic CO2 emissions, and the production of resource inputs. The results of this case study indicated that the carbon footprint (CF) of the 5000-milking-head dairy in Central Texas was 0.40 lb. of CO2 per lb. of fat- and protein-corrected milk (FPCM) when considering biogenic CO2 and 0.83 lb. of CO2 per lb. of FPCM without biogenic CO2.