Fat And Protein Corrected Milk Research Articles

Effects of extending dairy cow longevity by adjusted reproduction management decisions on partial net return and greenhouse gas emissions: A dynamic stochastic herd simulation study

Prolonging dairy cattle longevity is regarded as one of the options to contribute to more sustainable milk production. Since failure to conceive is one of the main reasons for culling, this study investigates how adjustments in reproduction management affect partial net return at herd level and greenhouse gas emissions per unit of milk, using a dynamic stochastic simulation model. The effects of reproduction decisions that extend cattle longevity on milk yield, calving interval and pregnancy rate were derived from actual performance of Dutch commercial dairy cows over multiple lactations. The model simulated lactations, calving and health status events of individual cows for herds of 100 cows. Scenarios evaluated differed in the maximum number of consecutive artificial insemination (AI) attempts (4, 5 or 6 services), or the production threshold (20, 15, or 10 kg milk per day) at which cows that failed to conceive are culled (reproductive culling). Annual partial net return was computed from revenues of sold milk, calves and slaughtered cows, and the costs from feed consumption, rearing replacement heifers, AI services and treatment for clinical mastitis and lameness. Greenhouse gas emissions were computed for feed production, enteric fermentation, and manure management, and were expressed as total CO2 equivalents. Average age at culling increased with an increased maximum number of AI services. This increase was larger when going from a maximum of 4 to 5 AI attempts (108 d) than from a maximum of 5 to 6 attempts (47 d). Similarly, the average age at culling increased from 1,968 to 2,040 and 2,132 d when the threshold for reproductive culling decreased from 20, to 15 and 10 kg milk per day, respectively. Average annual partial net return increased by 1.1% from €165,850 per 100 cows at a maximum of 4 AIs to €167,670 per 100 cows at a maximum of 6 AIs, and increased by 4.3% from €161,210 per 100 cows at a reproductive culling threshold of 10 kg/day to €168,190 per 100 cows at a threshold of 20 kg/day. Greenhouse gas emissions decreased by 1.2% from 0.926 to 0.915 kg CO2 equivalents per kg fat-and-protein-corrected milk (FPCM) with an increase in a maximum number of AIs from 4 to 6 AIs. Conversely, greenhouse gas emissions increased by 0.2% from 0.926 kg at a threshold of reproductive culling of 20 kg/day to 0.928 kg CO2 equivalents per kg FPCM at a threshold of 10 kg/day. Although lowering the threshold for reproductive culling has the potential to extend cattle longevity more than increasing the maximum number of AI services, only the increase in AI services benefits a farm's partial net return, while reducing greenhouse gas emissions.

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.

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 week followed by a covariate period of 3 weeks 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 non-supplemented 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 which were used for emission measurements. Supplementation of 3-NOP did not affect total dry matter intake (DMI), body weight or body condition score, 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 diet, 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 impact 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 suggests 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. Further studies are needed to clarify the long-term effect of 3-NOP on CH4 emission and to further investigate the effect that variation in diet composition may have on the mitigation potential of 3-NOP.

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.

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, 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 SenseHubTM collars from October 2019 to July 2022 in 6 herd located in the Walloon Region of Belgium. A multi-trait 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 to record 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 (SCS)) (−0.39) were estimated. The genetic correlation matrix allows to explain a high part of the variation for the reaction to heat stress of 2 economical traits (fat- and protein-corrected milk (FPCM): 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 are still limited.

Grass clover swards: A way out for Dutch dairy farms under legislative pressure?

CONTEXTPolicy measures have been taken to improve water quality in the Netherlands. These measures include the abolishment of derogation, which allowed dairy farmers to go beyond the maximum application of 170 kg nitrogen (N) from organic fertiliser per hectare, and additional measures of the 7th Nitrates Action program. Grass-clover swards, known for their symbiotic N fixation, could be a strategy to deal with stricter N policies and can potentially improve the environmental sustainability and economic viability of Dutch dairy farms. OBJECTIVEThe aim was to assess the effects of stricter N policies on the farm structure, farm income and environmental performance of a representative Dutch dairy farm on a sandy soil, and to assess the effect of incorporating perennial ryegrass-red white clover (GCrw) swards and perennial ryegrass-white clover (GCw) swards into the grassland management of this farm using a model. METHODSA whole-dairy farm linear programming model was used with the objective function to maximize farm income. The model was combined with a farm nutrient balance and life-cycle assessment to determine the impact on nutrient surpluses and greenhouse gas emissions. We modelled a representative Dutch dairy farm with perennial ryegrass (PRG) before and after implementing stricter N policies. Thereafter, the implications of implementing GCrw and GCw swards was assessed. RESULTS AND CONCLUSIONSIncluding the policy measures increased the share of maize land (+12%), decreased the number of dairy cows (-9 cows), reduced farm income (€-18,858 yr-1), led to similar greenhouse gas emissions (∼800 kg carbon dioxide equivalents (CO2-eq) per tonne (t) of fat and protein corrected milk (FPCM)), and resulted in a lower N surplus (-65 kg ha-1 yr-1) and phosphate surplus (-4.4 kg ha-1 yr-1) for a scenario with only PRG. The use of GCrw and GCw swards could partly compensate for the reduction in farm income (€+9,255 up to +14,706 yr-1). A combination of PRG, GCrw and GCw resulted in the highest farm income. The use of grass-clover swards only had the most positive effect on greenhouse gas emissions (767 kg CO2-eq t-1 FPCM) and N surplus (113 kg ha-1 yr-1). Sensitivity analysis showed the importance of yields and feed characteristics on the obtained farm income. SIGNIFICIANCEGrass-clover swards might partly compensate for the negative economic consequences of stricter N policies for Dutch dairy farms. Furthermore, implementing grass-clover swards reduced the GHG emission intensity of milk, but not always nutrient surpluses per hectare of farm land.

Factors influencing the carbon footprint of milk production on dairy farms with different feeding strategies in western Europe

Greenhouse gas emissions from dairy production represent a major source of emissions especially in Western Europe where the sector has grown over the past decade. Different feeding strategies have evolved and there is a need to identify effective mitigation measures. Life cycle assessment (LCA) was used to examine carbon footprints (CFs) of milk production across 71 commercial dairy farms in Ireland, Northern Ireland, England, Spain (Galicia and Basque regions), Portugal and France based on monthly data collection over two years. Emissions up to the farm gate were calculated within a global boundary with both higher tier emission factors (HTEF) applicable in respective countries, and default emission factors (DEF). The global warming potential (GWP) used was the GWP100 metric, however results were also calculated using GWP20 for comparison. Functional units were: (i) one tonne fat and protein corrected milk (FPCM); (ii) 1 ha of on-farm agricultural area (FAA); (iii) 1 ha of global agricultural area (GAA). Farms were categorised based on the proportion of time that cows spent grazing. Mean CF per tonne FPCM (FPCM-CF) were 1,129, 1237 and 1519 kg CO2e for grazing (>220d grazing; n = 16), mixed (up to 219d grazing; n = 17) and housed farms (0d grazing; n = 38), respectively. housed had the widest range, from 884 to 2494 kg CO2e/tonne FPCM, and included the farm with the overall lowest FPCM-CF. housed also had the highest mean CF per ha FAA: 44.1 tonne CO2e, followed by mixed (15.2 tonne) and grazing (11.6 tonne). CF (tonne CO2e) per ha GAA followed the same ranking: housed (15.1), mixed (9.8) and grazing (9.2). There was no difference in ranking of the feeding strategies using DEF in comparison with HTEF. A stepwise regression analysis identified feed efficiency and age at first calving as important factors in determining FPCM-CF for all farms. Furthermore, N surplus was important for grazing &mixed farms. The proportion of uncovered slurry storage, milk yield per cow and the amount of bought in concentrate per cow were important for housed farms. Wide variation in CFs implies considerable potential for lowering emissions per tonne FPCM and per ha FAA and GAA, but it is imperative that mitigation measures are tailored to feeding strategy.

Environmental impact of grass-based cattle farms: A life cycle assessment of nature-based diversification scenarios

Diversification is widely considered to positively influence the environmental sustainability of livestock farming. Multiple options exist to diversify cattle farms, but few have been examined at a systems level for grass-based livestock farms. Three nature-based diversification options recommended for livestock farms were examined in this study: mixed grass–white clover swards (GWC), organic farming (OFS) and agroforestry (AGF). They were applied on dairy and suckler calf-to-beef farming systems common in the Republic of Ireland. Both of these bovine systems were evaluated over a 3-year period (2017–2019) and were nationally representative. The environmental impact and resource use of dairy and suckler calf-to-beef systems were modelled using life cycle assessment (LCA). The system boundary of the LCA model extended from the extraction of raw materials to the sale of milk and cattle from the farm, i.e. cradle to farm-gate. Six of the major environmental impacts of cattle farming were simulated; global warming potential (GWP), non-renewable energy (NRE) depletion, land occupation (LO), acidification potential (ACP), freshwater and marine eutrophication potential (FEP and MEP). Impacts were scaled to the following functional units: land area, fat and protein corrected milk (FPCM) for dairy and carcass weight (CW) for beef. The result illustrated that GWC swards reduced the GWP of milk production by 9% and cut the GWP of beef LW by 3%. Per unit of product, this strategy decreased ACP by 4%–5%, NRE depletion by 13%–19% and LO by 6%–7%. However, it increased MEP by 5%–12% due to clover fixing more N than it replaced. Cattle farms based on GWC were more productive than conventional farms, but tended to increase impacts per hectare. Organic farming had the lowest environmental impacts per unit of land and reduced GWP and NRE depletion. Without carbon sequestration, organic farming had the opposite effect on GWP of FPCM and increased ACP and MEP per product unit. Declines in productivity in organic systems led to the rise in these impacts per unit of product and increases in LO relative to conventional systems. Partial conversion (10%–20%) of grassland to silvopasture decreased milk and beef output, and slightly improved environmental performance. Carbon sequestration was greater in silvopasture than in grassland, albeit LCA models struggle to accurately quantify the influence of management change on this process. This issue can be overcome through more field and modelling research on sequestration. Further research is also required on combining diversification options to optimise the environmental sustainability of cattle farming.

Cradle-to-grave life cycle assessment of buffalo mozzarella cheese supply chain in central Italy

Public opinion about environmental aspects is generating a widespread concern, which contributes to lead consumers to choose sustainable products. Livestock systems are responsible for the emissions of different pollutants and, as a consequence, this is reflected in the environmental sustainability of animal-based products.This study was aimed at evaluating the environmental impacts of buffalo mozzarella cheese with a cradle-to-grave life cycle assessment approach from the primary production of milk to the end-of-life of buffalo mozzarella cheese. The functional units were 1 kg of buffalo Fat and Protein Corrected Milk (FPCM) evaluated at farm gate and 1 kg of consumed buffalo mozzarella cheese evaluated at consumers’ home.The study enrolled 9 buffalo dairy farms, 2 dairy plants and 4 markets where 243 customers were surveyed. Processes of raw milk production, mozzarella cheese making, transports, retail and home consumption were considered. The accounted environmental impacts were: climate change (CC), terrestrial acidification (TA), freshwater eutrophication (FE), marine eutrophication (ME), ozone depletion (OD), ecotoxicity (EC), human toxicity (HT), land use (LU) and fossil depletion (FD). Buffalo farming was the primary hotspot accounting for more than 50% throughout all impact categories and having a major role in CC, TA, FE, ME, OD and LU. The energy consumption of cheese making had a contribution of 29% in HT, whereas the use of high-emitting vehicles by consumers accounted for 23% and 17% in EC and FD, respectively. To reduce several sources of pollution and mitigate the environmental impacts of buffalo mozzarella cheese, the LCA hotspots identification can lead to the development of specific mitigating strategies to improve sustainability along the supply chain. The development of farm-based models may better assess environmental impacts, the mitigation achieved by the implemented best practices and the “pollution swapping” effect to evaluate the effectiveness of the mitigation strategy.

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.

Impact of Climate Change and Heat Stress on Milk Production in Korean Holstein Cows: A Large-Scale Data Analysis.

This study investigated the effects of heat stress on milk production in Korean Holstein cows using large-scale data. Heat stress was assessed using the temperature-humidity index (THI). Weather records (2016 to 2020) were collected from 70 regional weather stations using an installed automated surface observing system (ASOS). A dataset of 2,094,436 milk production records from 215,276 Holstein cows obtained from the Dairy Cattle Genetic Improvement Center was analyzed. Stepwise selection was used to select the input variables, including the daily maximum THI (THI_max). Least-squares means were calculated for milk yield, fat and protein corrected milk (FPCM), fat and protein yield, fat-to-protein ratio, solids not fat, and lactation persistency. Segmented linear regression analysis determined the break points (BPs) of the THI_max. Over the five years, heat stress exposure increased, particularly from May to September. This study identified BPs around THI_max of 80-82 for milk yield and FPCM. Similar patterns for other milk traits were observed, which significantly decreased beyond their respective BPs. These findings indicate that THI variations adversely affect milk yield and composition in dairy cows, highlighting the importance of appropriate feeding management strategies to ensure the optimal productivity of Holstein cows under varying climatic conditions.

Dynamic lactation responses to dietary crude protein oscillation in diets adequate and deficient in metabolizable protein in Holstein cows

Limited research has examined the interaction between dietary crude protein (CP) level and CP feeding pattern. We tested CP level (low protein [LP], 13.8%; high protein [HP], 15.5% CP, dry matter [DM] basis) and CP feeding pattern (OF = oscillating, SF = static) using a 2 × 2 factorial in 16 mid- to late-lactation Holsteins (initially 128 ± 12 d in milk; mean ± SD). Cows ate total mixed rations formulated by exchanging soy hulls and ground corn with solvent soybean meal to keep constant ratios of neutral detergent fiber to starch (1.18:1), rumen-degradable protein to CP (0.61:1), and forage-to-concentrate (1.5:1) in DM. The OF treatments alternated diets every 48 h to vary CP above and below the mean CP level (OF-LP = 13.8% ± 1.8%; OF-HP = 15.5% ± 1.8% CP [DM basis]) whereas diets were constant in SF (SF-LP = 13.8%; SF-HP = 15.5% CP [DM basis]). In four 28-d periods, 8 rumen-cannulated and 8 noncannulated cows formed 2 Latin rectangles. On d 25 to 28 of each period, each cow's feed intake and milk production were recorded, and samples were taken of orts (1×/d) and milk (2×/d). We fit linear mixed models with fixed CP level, CP feeding pattern, and period effects, and a random intercept for cow, computing least squares means and standard errors. Neither CP level, CP feeding pattern, nor the interaction affected DM intake, feed efficiency, or production of milk, fat- and protein-corrected milk (FPCM), fat, true protein, or lactose. Milk urea-N (MUN) yield was lesser for LP. The LP and OF conditions decreased MUN concentration. The CP level tended to interact with CP feeding pattern so that milk protein concentration was greatest for OF-HP. The OF and LP conditions increased the ratio of true protein to MUN yield. Within OF, cosinor mixed models of selected variables showed that cows maintained production of FPCM across dietary changes, but MUN followed a wave-pattern at a 2-d delay relative to dietary changes. A tendency for lesser MUN with OF contradicted prior research and suggested potential differences in urea-N metabolism between OF and SF. Results showed that cows maintained production of economically-relevant components regardless of CP feeding pattern and CP level. Contrary to our hypothesis, the effects of 48-h oscillating CP were mostly consistent across CP levels, suggesting that productivity is resilient to patterned variation in dietary CP over time even when average CP supply is low (13.8% of DM) and despite 48 h restrictions at 12.2% CP.

Assessment of carbon footprint of milk production and identification of its major determinants in smallholder dairy farms in Karnataka, India

Indian dairy enterprise is dominated by smallholder dairy farms that contribute 72% of the country's total milk production. These smallholder dairy farms are often considered to emit substantial greenhouse gases (GHG) but are poor in productive performances. Therefore, it is crucial to estimate the carbon footprint (CF) of milk production of the smallholder Indian dairy farms. The primary objectives of the study were (1) Assessing the CF of milk production of smallholder dairy farms through life cycle analysis in south-interior Karnataka, India; (2) Identifying the hotspots of GHG emissions and significant factors influencing the CF of milk production in smallholder dairy production system. The study accounted GHG emissions from different sources and considered multiple functions of the smallholder production system. Estimations were made based on primary data collected from 47 farms and associated secondary data. For estimating the CF of milk production, the emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) on a CO2-equivalent (CO2-eq) basis from feed production, enteric fermentation, manure management, transport and energy usage were allocated to fat- and protein-corrected milk (FPCM) based on mass balance, price (crop byproducts and residues) and feed digestibility. Principal component analysis and stepwise linear regression analysis were performed to identify the major factors influencing the CF. The average total GHG emissions (kg CO2-eq yr-1 farm-1) attributable to milk production based on mass, economic, and digestibility allocations were 8,936, 8,641, and 8,759, respectively. The contributions of CH4, N2O, and CO2 to the total farm GHG emission were 70.6%, 20.5%, and 7.69%, respectively. The major emission hotspots were CH4 emission from enteric fermentation (66.8%) and GHG emission from feed production (23.0%). The average CF of cradle-to-dairy cooperative milk production varied from 1.45 to 1.81 kg CO2-eq kg FPCM-1. The CF of milk production was more than 2-fold greater, when milk yield was below 3,500 kg lactating cow-1 yr-1. The FPCM yield 100 kg body weight-1, dry matter intake, and CH4 emission from manure management were the strongest determinants of the CF and explained 83.4% of the observed variation. The study emphasized the importance of considering multiple functions of a mixed crop-livestock-based dairy production system for estimating CF per unit of product. The results suggest that maintaining high-yielding dairy animals and adopting appropriate feeding strategies for better feed utilization are the possible effective interventions for reducing the CF of milk production.

A Living Lab approach for sustainable intensification of dairy production: A case study of an organic and a conventional farm in northern Italy

Working on feed production and feeding strategies is one of the key ways of mitigating dairy impacts and of increasing dairy efficiency and the nutritional quality of milk, all of which are priorities for global dairy sector stakeholders. Feed production, both on farm and off-farm, is one of the main contributors to dairy farm greenhouse gas (GHG) emissions, and it is known that the adopted feeding strategies influence farm nutrient balance, nutrient losses to the environment, and milk fatty acid profile. This study has been aimed at improving farm efficiency, environmental sustainability, and milk nutritional quality by acting on the management of the cropping system, and by promoting the on-farm production of feeds of high nutritional quality and high fiber digestibility in order to improve the self-sufficiency of metabolizable energy (ME) and protein (CP) for animal feeding. A multi-year study was conducted to analyze the shift in cropping system management on an organic farm and on a conventional dairy farm, considered as a “lighthouses”, and which were part of a Living Lab. Two 3-year pre-change periods (PRE) and two 3-year post-change periods (POST) with 2 years of transition were considered. The main actions performed on the management of the forage system involved changes in the crop destination, in the harvest schedule and in the conservation methods. All the data necessary to determine the dry matter (DM) yield, the forage quality, in terms of crude protein (CP), the metabolizable energy (ME), the nitrogen balance, and the carbon footprint of the two farms were measured or collected on farm. One kg of fat and protein corrected milk (FPCM) was used as a functional unit. In the POST periods, the milk production intensity (t FPCM/ha) improved and the ME and CP self-sufficiency of the heard increased on both farms. Both farms showed a 9.8% reduction of the Carbon Footprint (CF), and a reduction in the nitrogen surplus at the farm level. The amounts of C18:3 n-3 and n-3 fatty acids increased on both farms in the POST period. The results of this work show that it is possible to intensify milk production and mitigate the impacts of dairy farms by acting on the management of the forage system and on the feed strategies, using a synergistic Living Lab approach to achieve sustainable intensification.

Impact of smallholder cattle farms on the environment: a study.

With increasing evidence of global warming, the pressure is building to limit greenhouse gas emission from many human activities including dairy production systems. In this context, the present study was conducted to estimate the carbon footprint (CF) of cattle milk produced in the Hisar district of Haryana, India. The data about feeding practices, crops grown, manure management systems, etc. was collected through personal interviews with cattle-rearing rural male farmers chosen through multistep random sampling. The life cycle assessment (LCA) methodology was adopted to estimate carbon footprint, with the system boundary being "Cradle to farm gate." The latest methodologies prescribed by the IPCC were used to estimate GHG emissions using the tier-2 approach. The current study has presented a detailed and recent GHG inventory from smallholder cattle farms at the village level. On the basis of the inventory analysis, a simplified life cycle-based analysis is used in order to quantify the carbon footprint of fat- and protein-corrected milk (FPCM). The carbon footprint of cattle milk was estimated at 2.13 kg CO2-eq/kilogram FPCM. Enteric fermentation was the most potent contributor to GHG, contributing around 35.5% of the total emissions, followed by manure management (13.8%) and soil management (8.2%). Further studies to accurately estimate carbon footprint are advocated besides suggesting ways to reduce GHG emissions and using efficient production technologies.

Evaluation of 3 northwest European seaweed species on enteric methane production and lactational performance of Holstein-Friesian dairy cows

Seaweeds have been studied for their ability to reduce enteric methane emissions of ruminants when fed as a feed supplement. In vivo research with dairy cattle is mainly limited to the seaweed species Ascophyllum nodosum and Asparagopsis taxiformis, whereas in vitro gas production research covers a broader range of brown, red, and green seaweed species from different regions. The objective of the present study was to determine the effect of Chondrus crispus (Rhodophyta), Saccharina latissima (Phaeophyta), and Fucus serratus (Phaeophyta), 3 common northwest European seaweeds, on enteric methane production and lactational performance of dairy cattle. Sixty-four Holstein-Friesian dairy cattle (16 primiparous, 48 multiparous) averaging (mean ± standard deviation) 91 ± 22.6 d in milk and 35.4 ± 8.13 kg/d fat- and protein-corrected milk yield (FPCM) were randomly assigned to 1 of 4 treatments in a randomized complete block design. Cows were fed a partial mixed ration [54.2% grass silage, 20.8% corn silage, and 25.0% concentrate; dry matter (DM) basis] with additional concentrate bait in the milking parlor and the GreenFeed system (C-Lock Inc.). The 4 treatments consisted of a control diet without seaweed supplement (CON), or CON supplemented with 150 g/d (fresh weight of dried seaweed) of either C. crispus (CC), S. latissima (SL), or a 50/50 mix (DM basis) of F. serratus and S. latissima. Milk yield (28.7 vs. 27.5 kg/d, respectively), fat- and protein-corrected milk (FPCM) yield (31.4 vs. 30.2 kg/d, respectively), milk lactose content (4.57 vs. 4.52%, respectively), and lactose yield (1,308 vs. 1,246 g/d, respectively) increased for SL compared with CON. Milk protein content was lower for SL compared with the other treatments. Milk fat and protein contents; yields of fat, protein, lactose, and FPCM; feed efficiency; milk nitrogen efficiency; and somatic cell count did not differ between CON and the other treatments. Depending on week of experiment, milk urea content was higher for SL compared with CON and CC. No effects were observed of the treatments compared with CON for DM intake, number of visits to the GreenFeed, or gas emission (production, yield, or intensity) of CO2, CH4, and H2. In conclusion, the seaweeds evaluated did not decrease enteric CH4 emissions and did not negatively affect feed intake and lactational performance of dairy cattle. Milk yield, FPCM yield, milk lactose content, and lactose yield increased, and milk protein content decreased, with S. latissima.

Management factors affecting the environmental impact of cereal-based dairy farms

This study aimed to assess the environmental impact (cradle-to-farm gate LCA) of milk production of cereal-based dairy farms in northern Italy and to analyse which traits related to farm management (MAN_F), lactating cows’ ration composition (DIET_F), and animal responses (ANI_F) could be identified as main determinants to address specific mitigation strategies. Data originated from 28 dairy farms. The functional unit was 1 kg of fat- and protein-corrected milk (FPCM). Impact categories were global warming (GWP), acidification (AP) and eutrophication (EP) potentials and land occupation (LO). Impact values were analysed with a linear model to test separately the effects of MAN_F, DIET_F and ANI_F variables. One kg FPCM was associated with an average impact of 1.10 kg CO2-eq (GWP), 17.1 g SO2-eq (AP), 6.0 g PO4-eq (EP), and 1.3 m2/y (LO). Regarding MAN_F, GWP and LO linearly decreased with increasing values of stocking rate and feed self-sufficiency (FSS), whereas minimum EP was found for intermediate FSS values (50% DM). Regarding DIET_F, GWP linearly decreased at increasing levels of dietary inclusion of cereal silages, whereas AP and EP linearly decreased at decreasing dietary crude protein (CP) content values. Among ANI_F, GWP and EP were quadratically associated with milk yield (MY), evidencing the lowest values at intermediate MY (9100 ± 477 kg FPCM/cow per 305d-lactation). The GWP, AP and EP decreased with decreasing age at first calving. These results can contribute at drawing good practices for farmers and consultants to promote more environmentally sustainable dairy production while supporting farm functioning and farmers’ income. HIGHLIGHTS Farm and animal determinants of Life Cycle Assessment of cereal-based dairy farms were studied. Mitigation effects can be achieved by operating on farm organisation, cow’s diet, and animal responses. Good practices for farmers and consultants can be proposed for a better dairy production sustainability.

Comparison of methane production, intensity, and yield throughout lactation in Holstein cows

Genetic selection to reduce methane (CH4) emissions from dairy cows is an attractive means of reducing the impact of agricultural production on climate change. In this study, we investigated the feasibility of such an approach by characterizing the interactions between CH4 and several traits of interest in dairy cows. We measured CH4, dry matter intake (DMI), fat- and protein-corrected milk (FPCM), body weight (BW), and body condition score (BCS) from 107 first- and second-parity Holstein cows from December 2019 to November 2021. Methane emissions were measured using a GreenFeed device and expressed in terms of production (MeP, in g/d), yield (MeY, in g/kg DMI), and intensity (MeI, in g/kg FPCM). Because of the limited number of cows, only animal parameters were estimated. Both MeP and MeI were moderately repeatable (>0.45), whereas MeY presented low repeatability, especially in early lactation. Mid lactation was the most stable and representative period of CH4 emissions throughout lactation, with animal correlations above 0.9. The average animal correlations of MeP with DMI, FPCM, and BW were 0.62, 0.48, and 0.36, respectively. The MeI was negatively correlated with FCPM (<-0.5) and DMI (>-0.25), and positively correlated with BW and BCS. The MeY presented stable and weakly positive correlations with the 4 other traits throughout lactation, with the exception of slightly negative animal correlations with FPCM and DMI after the 35th week. The MeP, MeI, and MeY were positively correlated at all lactation stages and, assuming animal and genetic correlations do not strongly differ, selection on one trait should lead to improvements in all. Overall, selection for MeI is probably not optimal as its change would result more from CH4 dilution in increased milk yield than from real decrease in methane emission. Instead, MeY is related to rumen function and is only weakly associated with DMI, FPCM, BW, and BCS; it thus appears to be the most promising CH4 trait for selection, provided that this would not deteriorate feed efficiency and that a system of large-scale phenotyping is developed. The MeP is easier to measure and thus may represent an acceptable alternative, although care would need to be taken to avoid undesirable changes in FPCM and BW.

Carbon footprint of South Dakota dairy production system and assessment of mitigation options.

Livestock production contributes to greenhouse gas (GHG) emissions. However, there is a considerable variability in the carbon footprint associated with livestock production. Site specific estimates of GHG emissions are needed to accurately focus GHG emission reduction efforts. A holistic approach must be taken to assess the environmental impact of livestock production using appropriate geographical scale. The objective of this study was to determine baseline GHG emissions from dairy production in South Dakota using a life cycle assessment (LCA) approach. A cradle-to-farm gate LCA was used to estimate the GHG emissions to produce 1 kg of fat and protein corrected milk (FPCM) in South Dakota. The system boundary was divided into feed production, farm management, enteric methane, and manure management as these activities are the main contributors to the overall GHG emissions. The production of 1 kg FPCM in South Dakota dairies was estimated to emit 1.23 kg CO2 equivalents. The major contributors were enteric methane (46%) and manure management (32.7%). Feed production and farm management made up 14.1 and 7.2%, respectively. The estimate is similar to the national average but slightly higher than the California dairy system. The source of corn used in the dairies influences the footprint. For example, South Dakota corn had fewer GHG emissions than grain produced and transported in from Iowa. Therefore, locally and more sustainably sourced feed input will contribute to further reducing the environmental impacts. Improvements in efficiency of milk production through better genetics, nutrition animal welfare and feed production are expected to further reduce the carbon footprint of South Dakota dairies. Furthermore, anaerobic digesters will reduce emissions from manure sources.

ASSESSMENT OF GREENHOUSE GAS EMISSIONS FROM DAIRY FARMING USING THE COOL FARM TOOL

Climate change is one of the greatest challenges mankind has ever faced and could lead to potentially devastating global problems, with a need for urgent mitigation and adaptation. Agriculture, especially livestock farming, is a major driver of climate change through its contribution to the total emissions of greenhouse gases (GHGs). The dairy sector has been identified as an important source of GHG emissions, mainly via carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). In this study, total CO2 equivalent (CO2e) emissions were assessed from a dairy farm (65 dairy cows) located in Romania using the Cool Farm Tool calculator (CFT). We specifically aimed to calculate: (1) the total CO2 equivalent (CO2e) and CO2e per kg FPCM (fat- and protein-corrected milk); (2) methane emissions from enteric fermentation; (3) GHGs resulting from feeding practices; (4) GHGs from manure management; and (5) a simulation of two different scenarios and their impact on GHG emissions. Our results showed annual GHG emissions of 553,170 kg CO2e, almost half of which were released through enteric fermentation. Lactating cows were the major contributor to total GHG emissions, while heifers released the lowest emissions. The two scenarios simulated in this study showed that both the changes made in dairy diet composition and livestock manure management could result in lower GHG emissions. These results confirm the importance and utility of the CFT for the quantification of GHG emissions in dairy farms and its important role as a decision support tool to guide the adoption of good agricultural practices.