Environmental Impact Of Dairy Production Research Articles

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.

Dairy cow longevity and farm economic performance: Evidence from Swedish dairy farms

The longevity of dairy cows is mainly determined by farmers' subjective culling decisions and can be linked to the environmental impact of dairy production and to the social acceptance of the industry. Still, the economic impacts of dairy cow longevity are not well understood. The aim of this study was therefore to examine how herd average dairy cow longevity is related to the farm economic outcome. We used 3 indicators of economic outcome: technical efficiency, profitability and average milk yield per cow. We used 2 indicators of dairy cow longevity: average herd length of life and average herd length of productive life. The study was based on a unique and detailed data set from Swedish dairy agriculture, where herd management data from the national dairy herd recording scheme were combined with farm level economic variables, the Swedish farm accountancy survey, for a total of 1,959 observations over the time period 2010 - 2018. The regression results highlight that both measures of average herd dairy cow longevity have an overall positive and statistically significant association with farm level economic performance. These associations had an inverted U-shape which implies that the association is first positive and then declines. Descriptive statistics indicate that the point where the maximum economic performance is attained varied across the economic indicators. Our results are relevant for individual dairy farmers and their advisors who are interested in understanding how herd average longevity relates to economic performance on the farms. Our results are also important from a greater sustainability perspective: linking them to previous knowledge about the positive environmental and social sustainability benefits from keeping cows longer, highlights there may be dairy cow longevity-associated tradeoffs between those benefits and the farm economic outcomes.

The environmental impact of permanent meadows-based farms: A comparison among different dairy farm management systems of an Italian cheese

The environmental impact of dairy production is heavily influenced by milk farm efficiency, farm characteristics, and farming activities, such as feed management. The existing research on the environmental impacts of the differently managed dairy farm systems is often in contrast and difficult to be compared. Thus, the present study aimed to assess the environmental impacts of milk used for the same cheese by comparing four dairy farm systems different for feed management choices, geographical area, herd size and milk productivity. A Life Cycle Assessment was performed following the Product Environmental Footprint methodology using primary data collected in 70 farms and one average cheese factory. The results showed that the raw milk production phase was the most significant contributor to the environmental impacts of cheese production. The self-produced feed and purchased feed resulted as the main hotspot processes, covering 64–77 % of the total impact. In fact, among the four different farm systems, the Permanent Meadows Farms showed the best environmental performance, with the lowest values registered for 14 of 19 impact indicators. Similar impacts were observed for the North Italy Representative Farms, while Small Plain Farms disclosed the highest outcomes, resulting most impacting than the Mountain Farms. Results demonstrate that different feed management choices can affect the final cheese impact and could be considered by private and public policies focused on green transformation objectives.

Influence of precision livestock farming on the environmental performance of intensive dairy goat farms

The implementation of Precision Livestock Farming (PLF) concepts has been pointed out as an indirect strategy that could potentially help mitigating the environmental impacts of livestock production systems. To date, few studies have focused on analyzing specifically the relationship among PLF adoption and environmental performance, so sustainability benefits have not yet been quantified for many technologies. Moreover, studies evaluating the environmental impact of dairy production have traditionally focused on cattle, and when exploring sheep or goats, they have often involved extensive, low-productive systems, providing an incomplete picture of the sector. In this study we apply life cycle assessment (LCA) to analyze the environmental impact associated to intensive dairy goat production, and to explore the influence of adopting a smart-farming PLF platform on the environmental performance of a group of dairy goat farms in Spain. The PLF-platform relies on systematic on-farm monitoring of individual animal data, coupled with big data processing and interpretation, which supports farmers to take adequate -and timely-farm management decisions. In order to capture its influence, two different periods were analyzed in five selected farms: a baseline year just before innovation was implemented (2014) and four years after (2018), when most of the effect of improved management was reflected. Results after the PLF-platform implementation showed significant reductions (−11%) in greenhouse gas emissions and similar trends in other impact categories (9–16% reductions). The PLF platform provided a precise monitoring of the productivity, genetic merit and physiological state of each animal, allowing adequate criteria for a number of decision-making processes, such as selecting animals for breeding, replacement or culling. This optimization led to an increase in the genetic selection progress, ultimately reflected on milk productivity. Moreover, a reduction of unproductive periods such as first partum age or dry period length was often achieved. As a result of this general improvement, the efficiency of resource usage in relation to milk (and meat) production was increased, with positive effect on the environmental performance. Production of 1 kg of fat and protein corrected milk (FPCM) resulted in 1.53–1.71 kg CO2 eq. Results in other impacts categories were also in a similar range than previously reported values for highly productive dairy systems, including dairy cattle, which stresses the important role that small ruminant farming can play on environmentally sustainable livestock production, particularly in the Mediterranean context.

Minimize environmental impact of dairy production through improve the life cycle. Part 1: Pollution load from Dairy wastewater in 6 of October Industrial City.

Minimize environmental impact of dairy production through improve the life cycle. Part 1: Pollution load from Dairy wastewater in 6 of October Industrial City.

Role of dairy and alternative plant products in a healthy and sustainable diet

Dairy products and plant alternatives are two food groups that are part of the Spanish population's diet. Both have a very different nutritional composition - unlike plant products, the high nutritional density of dairy products makes it easier to meet nutrient requirements at different stages of life. Although the environmental impact of dairy production is greater than that of plant-based products, it falls below that of other food groups such as red meat, including pork and beef. Dairy and plant alternatives meet critical points of the sustainable diet definition, and several food guides from countries around the world are including them within healthy and sustainable eating patterns. For this reason, it is necessary to clarify that both products can be part of a healthy and sustainable diet, although they belong to different food groups, which are not interchangeable and should not be used alternatively.

Effect of Cow Start Bolus Supplementation on Early Lactation Health and Performance Indicators in a Group of Older, At-Risk Dairy Cows

Whilst older cows can be some of the most profitable producers on the farm, as well as helping to reduce the environmental impact of dairy production and improving consumer perception of dairy farming, they can also be more prone to early lactation metabolic challenges and at higher risk of culling or death in early lactation. Research into nutritional supplementation strategies specifically to support older, at-risk herd members has not, to the author’s knowledge, been carried out and leaves a dearth of knowledge as to how best to support the successful transition of this valuable cohort of cows from gestation into peak lactation. The objective of this study was to evaluate the effect of supplementation with a combined calcium, magnesium and antioxidant bolus (Cow Start) on key early lactation health and performance indicators in a cohort of older, higher yielding dairy cows that may be expected to be at greater risk of developing key post-partum metabolic disorders. High yielding multiparous (n=38) cows averaging 4.7 lactations at calving were enrolled in this study and randomly assigned to either a control (CON, n=19) group or a Cow Start oral bolus supplemented (CSC, n=19) group. The CON group experienced a clinical milk fever (Blood Ca < 1.5 mM) incidence rate of 15.7% compared to 0% for the CSC group. Cows in the CSC group recorded a treatment effect of a significantly (P < 0.01) higher blood calcium status compared to CON. Energy Corrected Milk volumes showed a statistical trend of an increase (P < 0.10) from day 5 until day 60 of lactation for the CSC group (+1.8 kg/day) when compared to CON, also milk fat kg (P < 0.05) and combined fat and protein kg yields (P < 0.10) were increased in the CSC group when compared to the CON group. Results of this study suggest that supplementation of older at-risk cows with a combined calcium, magnesium and antioxidant (Cow Start) oral bolus can reduce the incidence rate of clinical milk fever and exposure to sub-clinical milk fever, whilst also improving blood calcium status and increasing milk production parameters in early lactation when compared to CON.

Composition, Mineral and Fatty Acid Profiles of Milk from Goats Fed with Different Proportions of Broccoli and Artichoke Plant By-Products.

In the Mediterranean region, artichoke and broccoli are major crops with a high amount of by-products that can be used as alternative feedstuffs for ruminants, lowering feed costs and enhancing milk sustainability while reducing the environmental impact of dairy production. However, nutritional quality of milk needs to be assured under these production conditions and an optimal inclusion ratio of silages should be determined. This work aimed to evaluate the effect of three inclusion levels (25%, 40%, and 60%) of these silages (artichoke plant, AP, and broccoli by-product, BB) in goat diets on milk yield, composition, and mineral and fatty profiles. Treatments with 60% inclusion of AP and BB presented the lowest milk yield. No differences were found on the milk mineral profile. Inclusion of AP in the animals’ diet improved the milk lipid profile from the point of view of human health (AI, TI) compared to BB due to a lower saturated fatty acid content (C12:0, C14:0, and C16:0) and a higher concentration of polyunsaturated fatty acids (PUFA), especially vaccenic acid (C18:1 trans11) and rumenic acid (CLA cis9, trans11), without any differences with the control treatment.

A quantitative assessment of Beneficial Management Practices to reduce carbon and reactive nitrogen footprints and phosphorus losses on dairy farms in the US Great Lakes region

Assessing and improving the sustainability of dairy production is essential to secure future food production. Implementation of Beneficial Management Practices (BMP) can mitigate GHG emissions and nutrient losses and reduce the environmental impact of dairy production, but comprehensive, whole-farm studies that evaluate the efficacy of multiple BMPs to reduce multiple environmental impacts and that include an assessment of productivity and farm profitability, are scarce. We used a process-based model (IFSM) to assess the efficacy of (10+) individual BMPs to reduce the carbon (C) footprint expressed per unit of milk produced of two model dairy farms, a 1500 cow farm and a 150 cow farm, with farming practices representative for the Great Lakes region. In addition to the C footprint, we assessed the effect of BMP implementation on the reactive nitrogen (N) footprint and total phosphorus (P) losses (per unit of milk produced), as well as milk production and farm profitability. We evaluated individual farm-component specific BMPs, that is, 5 dietary manipulations, 3 (150 cow farm) or 4 (1500 cow farm) manure interventions, and 6 field interventions, as well as an integrated whole-farm mitigation strategy based on the best performing individual BMPs. Our results show that reductions in the C footprint expressed per unit of milk are greatest with individual manure management interventions (4–20% reduction) followed by dietary manipulations (0–12% reduction) for both farm types. Field management BMPs had a modest effect on reducing this footprint (0–3% reduction), but showed substantial potential to reduce the reactive N footprint (0–19% reduction) and P losses (1–47% reduction). We found that the whole-farm mitigation strategy can substantially reduce the C footprint, reactive N footprint and total P loss of both farms with predicted reductions of approximately 41%, 41% and 46% respectively, while increasing milk production and the net return per cow by approximately 11% and 27%. To contextualize IFSM predictions for the whole-farm mitigation, we compared components of IFSM predictions to those of three other process-based models (CNCPS, Manure-DNDC and EPIC). While we did observe differences in model predictions for individual flows (particularly P erosion and P leaching losses), with exception of the total P loss, the models generally predicted similar overall mitigation potentials. Overall, our analysis shows that an integrated set of BMPs can be implemented to reduce GHG emissions and nutrient losses of dairy farms in the Great Lakes region without sacrificing productivity or profit to the farmer.

The environmental impact of dairy production on poorly drained soils under future climate scenarios for Ireland

The environmental impact of dairy production in Ireland has been widely studied and it is known that regional differences in management and impact are driven by climate. Climate change projections for Ireland predict increasing temperature, change in rainfall patterns and decreasing in solar radiation, varying by agroclimatic region. This study evaluated the environmental impacts of low-cost, grass-based, rotational-grazing dairy production on poorly drained soils under climate change. The Dairy_sim model was used to determine the theoretical optimum dairy system management for five different locations in Ireland assuming a poorly drained soil resource under baseline (1981–2000) and future climate scenarios (2041–2060, high and low emissions scenarios). An optimum system was defined as having maximum grass production and grazed grass in the diet, minimum necessary silage, minimum imported feed, minimum housing days and a very small silage surplus. Life cycle assessment was then used to quantify the environmental impacts (climate change, eutrophication and acidification) for all scenarios. The dairy production systems were predicted to be more productive in the future, with climate change impacts per unit milk reduced or the same, acidification impacts reduced and eutrophication impacts reduced. The absolute emissions driving climate change and eutrophication were predicted to significantly increase for the future low emission scenario, and emissions driving acidification were predicted to slightly increase. The predictions indicate that system adaptation to mitigate absolute emissions are needed rather than just policies that focus on impacts per unit output.

Effects of diet and manure storage method on carbon and nitrogen dynamics during storage and plant nitrogen uptake

Altering dairy cattle diets to reduce both enteric methane (CH4) production and nitrogen (N) excretion are valuable tools for mitigating the environmental impact of dairy production. We examined the impact of altering diets on changes in physicochemical properties of manure during storage and short term plant N availability. Manure collected from cattle fed diets with differing forage and crude protein (CP) content were stored via two methods (slurry and static pile) for 29 weeks and sampled at week 0, 1, 2, 3, 4, 9, 14, 19, 24, and 29. There was no effect of diet on C and N dynamics during storage for either storage treatment. Mass losses of total carbon (C) were 10% greater for the static pile manure treatment than the slurry (P<0.01). Total N losses ranged from were approximately 46% with no treatment differences. The soil 2-week plant available N was 67% less in the static pile than the slurry treatment, while the short-term plant N use efficiency was similar for both the static pile and slurry treatments (22–24%). Due to the high inorganic N content of slurry following storage, greater care may be needed to ensure that environmental losses do not occur.

Computational model of methane and ammonia emissions from dairy barns: Development and validation

The increased global demand for milk and other dairy products over the past decades is a cause for concern due to the potential for environmental impact. Ammonia produced by housed dairy cows can contribute to the formation of particulate matter and nitrous oxide which both contribute to the greenhouse effect. The methane produced by these cows also contributes to the greenhouse effect. Scientists and engineers face the challenge of developing methods to reduce the environmental impact of dairy production while not inhibiting the ability of producers to keep up with demand. Emission of methane and ammonia are highly dependent on feed composition, barn design and operation, manure management making this a challenging topic to study experimentally. Using computational models to simulate the generation and dispersion of gaseous species within dairy housing can facilitate the exploration of cost-effective gas mitigation strategies. Thus a steady-state computational fluid dynamics (CFD) model capable of simulating biologically based generation of methane, ammonia, and heat and their transport within the domain was developed and validated. The effect of buoyancy forces on the accuracy and stability of the solutions was explored. The model was validated with experimental data collected from emission chambers located at USDA-ARS Dairy Forage Research Center in Wisconsin, USA. Concentration of ammonia and methane, due to controlled injections from cylinders and biological generations from a dairy cow, were measured in the chambers using a FTIR gas analyzer. Results of the validated CFD model could be used to predict gaseous emissions under a range of environmental, design, and experimental treatment parameters.

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

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

Revised digestive parameter estimates for the Molly cow model

The Molly cow model represents nutrient digestion and metabolism based on a mechanistic representation of the key biological elements. Digestive parameters were derived ad hoc from literature observations or were assumed. Preliminary work determined that several of these parameters did not represent the true relationships. The current work was undertaken to derive ruminal and postruminal digestive parameters and to use a meta-approach to assess the effects of interactions among nutrients and identify areas of model weakness. Model predictions were compared with a database of literature observations containing 233 treatment means. Mean square prediction errors were assessed to characterize model performance. Ruminal pH prediction equations had substantial mean bias, which caused problems in fiber digestion and microbial growth predictions. The pH prediction equation was reparameterized simultaneously with the several ruminal and postruminal digestion parameters, resulting in more realistic parameter estimates for ruminal fiber digestion, and moderate reductions in prediction errors for pH, neutral detergent fiber, acid detergent fiber, and microbial N outflow from the rumen; and postruminal digestion of neutral detergent fiber, acid detergent fiber, and protein. Prediction errors are still large for ruminal ammonia and outflow of starch from the rumen. The gain in microbial efficiency associated with fat feeding was found to be more than twice the original estimate, but in contrast to prior assumptions, fat feeding did not exert negative effects on fiber and protein degradation in the rumen. Microbial responses to ruminal ammonia concentrations were half saturated at 0.2mM versus the original estimate of 1.2mM. Residuals analyses indicated that additional progress could be made in predicting microbial N outflow, volatile fatty acid production and concentrations, and cycling of N between blood and the rumen. These additional corrections should lead to an even more robust representation of the effects of dietary nutrients on ruminal metabolism and nutrient absorption, of animal performance, and the environmental impact of dairy production.

Suitability of bronopol preservative treated milk for fatty acid determination

This work aimed to test if milk preserved with bronopol can be reliably used for fatty acid determination. Dairy production and milk quality are often monitored regularly to assess performance and contribute to selection indices. With evidence that fat composition can be influenced by selective breeding, there might be an interest in using samples collected in routine testing to evaluate individual cow fatty acid profiles, contributing to breeding indices. However, most recording services use a preservative such as bronopol and there is no published record if this influences subsequent fatty acid analysis. This study used milk from an oil seed supplementation trial, generating a wide range of milk fatty acid profiles, to test if the concentration of 31 individual fatty acids determined by GC were influenced by bronopol. Provided preserved samples are subsequently frozen, milk treated with bronopol can reliably be used to evaluate fatty acid composition in most cases; however bronopol might influence a few long-chain fatty acids present in relatively low concentrations. This is one small step towards simplifying milk compositional analysis but it could ultimately streamline the inclusion of milk fat quality into breeding indices, either with a view to 'healthier' milk or potentially reducing methane output and the environmental impact of dairy production.

The environmental impact of dairy production: 1944 compared with 20071

A common perception is that pasture-based, low-input dairy systems characteristic of the 1940s were more conducive to environmental stewardship than modern milk production systems. The objective of this study was to compare the environmental impact of modern (2007) US dairy production with historical production practices as exemplified by the US dairy system in 1944. A deterministic model based on the metabolism and nutrient requirements of the dairy herd was used to estimate resource inputs and waste outputs per billion kg of milk. Both the modern and historical production systems were modeled using characteristic management practices, herd population dynamics, and production data from US dairy farms. Modern dairy practices require considerably fewer resources than dairying in 1944 with 21% of animals, 23% of feedstuffs, 35% of the water, and only 10% of the land required to produce the same 1 billion kg of milk. Waste outputs were similarly reduced, with modern dairy systems producing 24% of the manure, 43% of CH(4), and 56% of N(2)O per billion kg of milk compared with equivalent milk from historical dairying. The carbon footprint per billion kilograms of milk produced in 2007 was 37% of equivalent milk production in 1944. To fulfill the increasing requirements of the US population for dairy products, it is essential to adopt management practices and technologies that improve productive efficiency, allowing milk production to be increased while reducing resource use and mitigating environmental impact.

A life cycle based method to minimise environmental impact of dairy production through product sequencing

The trend of increasing the number of dairy products for sale affects their environmental impact in a life cycle perspective. During dairy processing, the production schedule is affected by more frequent product changes, hence also cleaning operations. This causes more milk waste, use of cleaning agents and water. The amount of milk waste depends on the product change technique used, which is determined by the characteristics of the product. A method was designed to calculate the sequence, which, for a given set of yoghurt products, minimises milk waste. A heuristic method, based on the strive to minimise production waste combined with production rules, was worked out. To determine whether the heuristic solution gives the best possible sequence from an environmental perspective, an optimisation was also made. The analytical method used for optimisation was able to handle 21 products and verified the heuristic method for a waste minimised sequence up to that level. It is also highly probable that for sequences including a greater number of items waste can be minimised with the same heuristic method. A successful demonstration of the possibility to make a more complete environmental assessment was fulfilled by connecting the sequencing model to conventional life cycle assessment methodology.