Progress report for LNC23-493
Project Information
Enteric methane, manure, and feed production related greenhouse gas (GHG) are the three major sources of GHG emissions from dairy production systems. A mitigation strategy would be adopted by the producers if it is viable (i.e., the strategy can reduce environmental footprint while improving economic performance or profit). Most GHG mitigation strategies developed and investigated until now focus on the environmental sustainability while overlooking economic performance of a dairy production system. Several past simulation studies indicated tradeoff between economic and environmental sustainability of a dairy production system. However, a very few recent studies suggested synergy between GHG emissions intensity (i.e., carbon footprint) and economic performances rather than a trade-off between two sustainability indicators. This synergy was determined by the productivity of animals and feeding practices. Thus, we hypothesized that the relationship between carbon footprint and profitability will depend on production system and feeding management scenarios of the animals. Thus, our approach will include the collection of on-farm data from 30 farms (details in support letter) representing the production system of the chosen geographic region (South Dakota, Iowa & Minnesota). Type of data collected will include farm-size, herd structure, dietary ingredients and chemical composition, milk production, milk composition, manure yield and composition, collection, processing, storage and application of manure, feed ingredients produced and purchased, electricity, fossil fuels and fertilizers, dairy and non-dairy revenues and expenses etc. Then, we will build a cradle-to-farmgate model using life cycle assessment (LCA) tool with SimaPro software to determine carbon footprint for milk for the existed production systems under different dietary scenarios. Farm profitability on a per cow or per farm basis will be calculated for each production system including their management scenarios. The relationship between environmental and economic performances will provide the indication of which production and management scenario will be viable. Additionally, we anticipate creating an easy to use by the producers assessment tool (testing scale) to evaluate their own scenarios as well as future potential mitigation scenarios. The expected project findings will help dairy farmers/producers to identify and evaluate a production system and dietary management scenario that will be both economically profitable and environmentally friendly.
Objectives: Our objectives are to i) determine the carbon footprint and economic performances including their relationship of existing dairy production systems in North-Central region under varying production & dietary scenarios and ii) create an online tool that could be used by the producers to assess the sustainability of their own farm.
Audiences: Audiences will include dairy producers (small, medium, and large farm), graduate students, researchers, conference attendees and industry stakeholder.
Learning outcomes: Students will learn the life cycle assessment modeling tool while other audiences will understand the relationship between environmental footprint and farm economic performances including potential tradeoff or synergy.
Dairy cows have the unique capability of converting human non-edible fiber into high-quality edible food, milk. However, this conversion process is not highly efficient and this inefficiency leads to reduce farm profitability, and inefficiency related emissions and nutrient losses affect air and water quality negatively. In the United States (US), about 10% of total GHG emissions originate from agriculture sector (EPA, 2018) whereas the contribution of dairy sector is about 1.9% of the total US GHG emissions (Thoma et al., 2013). Three major GHG from the dairy production systems include carbon di-oxide (CO2), methane (CH4) and nitrous oxide (N2O) (Thoma et al., 2013) where CH4 and N2O have respectively 28 and 265 times more global warming potential (GWP) than CO2 (Myhre et al., 2013). Methane is emitted either from dairy animals (enteric emissions) or from manure management chain mainly during storage of manure. Nitrous oxide is emitted either from manure management chain or from crop/forage-field whereas major source of CO2 is feed production. Per unit of milk basis at the farm-gate level, the contribution of enteric, feed production and manure management emissions are approximately 35, 33, and 27%, respectively (Thoma et al., 2013).
Although GHG emissions per unit of milk production is decreasing over time due to mainly increased overall efficiency (i.e., dilution effect), yet total GHG emissions from the global dairy sector is increasing over time due to increased total milk production (e.g., 18% increment in milk production between 2005 and 2015) (FAO and GDP, 2018). Additionally, improved living standard along with continuous growth of global human population (mainly in Asia and Africa) which is predicted to exceed 9.3 billion by 2050 will increase demand of milk production by 58% resulting in increased total GHG emissions of the sector unless mitigation measures are developed and adopted (Uddin and Kebreab, 2020). Furthermore, the rate of emission from different sources varies depending on animal type (e.g., breed of cows), diet composition (e.g. NDF content and forage to concentrate or grain ratio), manure processing (e.g., solid-liquid separation), manure storage (e.g., liquid vs. solid), duration of manure storage, manure application rate, manure application timing (e.g., fall vs. spring), type of application (e.g., surface vs. incorporation), type of forage produced (e.g., legume vs. grass) etc. One of our recent study findings indicated that carbon footprint varies widely within and across dairy production regions depending on management condition of the individual farm (Figure 1; Uddin et al., 2022). These management conditions typically vary between producers within and across regions which may also lead to differential carbon and nitrogen utilization efficiencies. Although contribution of dairy sector to US GHG emissions is not huge compared to other big sector such as transportation and energy sector (EPA, 2018), however, emphasis has been given to reduce GHG emissions from US dairy sector to make the dairy sector environment friendly to the society and competitive to the world market. For instance, the US dairy industry has recently announced a net zero carbon initiative targeting carbon neutrality across regions by 2050 through implementing best management practices and new innovations (Innovation Center for US Dairy, 2019). This industry-wide bold climate change action points to the urgency of scientific research to create new innovations and evaluate existing innovations and technologies for their potential to achieving the stated-goal.
Recent studies also indicated the great potential of using certain feed additives such as 3-nitrooxypropanol (3-NOP), nitrate and certain species of seaweed either as modifier of rumen environment or direct inhibitor of methanogenesis (process of producing CH4 in the rumen by the methanogen). For instance, the 3-NOP can reduce upto 40% of enteric CH4 in dairy cows without affecting animal performances negatively (Arndt et al., 2021) whereas seaweed (Asparagopsis taxiformis species) has been shown to reduce enteric CH4 intensity (emission per unit of product) by 67% in dairy cows and upto 80% in beef steers (Roque et al., 2021). However, when evaluated at the farmgate-level accounting for emissions from manure management, feed production and farm energy using holistic LCA approach, the reduction of GHG emission for 3-NOP was 12% which is also indicating tradeoff between system components (Uddin et al., 2022). Thus, enteric CH4 mitigation strategies need to be evaluated at the farm-gate level accounting for tradeoff between components of the milk production systems (e.g., enteric, manure and feed production related emissions) aiming to avoid misleading conclusions (Wattiaux et al., 2019; Kebreab et al., 2019).
A mitigation strategy or production scenario that helps to improve environmental sustainability might not necessarily be economically sustainable or profitable. Since the adoption rate of the GHG mitigation strategies is highly influenced by the farm profitability, therefore, it is extremely important to understand the potential tradeoff or synergy between environmental and economic pillars of sustainability for dairy production systems under varying dietary and management scenarios. Several past simulation studies also indicated tradeoff between economic and environmental sustainability of a dairy production system (Moraes et al., 2015; Le et al. 2020; Njuki and Brav0-Ureta, 2015). However, a very few recent study suggested synergy between GHG emissions intensity (i.e., carbon footprint) and economic performances rather than a trade-off between two sustainability indicators (Jayasundara et al., 2019). This synergy was determined by the productivity of animal and feeding practices. Thus, we hypothesized that the relationship between carbon footprint and profitability will depend on production system and feeding management scenarios of the animals. Thus, our approach will include the direct collaborations with dairy producers and collection of on-farm data from 30 farms representing the production system of the chosen geographic region called I-29 Dairy Corridor. The ‘I-29 Corridor’ is a vital region to measure the pulse of the dairy industry. Interstate 29 (I-29) is a major artery connecting Nebraska, Iowa, Minnesota, South Dakota, and North Dakota. The I-29 Corridor is the 600+ miles from Fargo ND to Kansas City, KS and roughly 100 miles east and west of I-29. In this region, these states had an overall 5% growth in 2022, with South Dakota being the national growth leader with up to 15% growth in milk production. South Dakota’s agriculture industry contributes $32.5 billion to the state’s economy ($11.2 billion to the U.S. economy) and represents an increase of 132,105 (22%) jobs since 2014. Livestock production and industries are the most significant contributing sector, with $5.8 billion ($324.5 million from dairy cattle and milk production). South Dakota is wide-open with a very business friendly climate and the State has helped relocate dairy farms from other states like California or countries (e.g., The Netherlands, Ireland, Switzerland, and England) along the I-29 corridor. Across SD there are approximately 140 dairies and nearly 200 thousand lactating cows. Using the number of lactating cows as a guideline, we estimated there are nearly 100 dairy farms with less than 500 cows and 40 dairy farms with more than 1,000 cows. The uniqueness of this region also includes I-29 Moo University which represents a collaboration of land-grant Universities from Iowa, Minnesota, Nebraska, North Dakota, and South Dakota along with representatives from the dairy industry. The collaboration has allowed SD Dairy Extension Specialists to travel to dairies in Minnesota and Iowa to expand their knowledge and expertise while enhancing the sustainability of the dairy industry within the region. Proximity to markets and infrastructure such as Bel Brands, Valley Queen and Agropur milk processing plants is also a great support to the industry. Though small farms are still predominant in South Dakota and the I-29 region, yet big dairies are emerging in the region. The management systems and efficiencies including profitability varies by farm sizes. Thus, understanding the prevalent major production systems and management conditions of the region including economic and environmental sustainability would provide helpful guidance to the stake holders across the boards to support and continue the growing dairy industry of the region. Thus, our approach will produce output of carbon footprint and economic performances including their relationship of different dairy production scenarios. We also anticipate to create an online (easy to use and testing scale) sustainability assessment tool which will provide access to dairy farmers to assess their own farm scenario including future mitigation strategies. The expected project findings will help dairy farmers/producers to identify a production system and dietary scenario that will be both economically profitable and environment friendly.
References
Arndt, C., A.N. Hristov, W.J. Price, S.C. Mcclelland, and C. 2021. Arndt. Strategies to Mitigate 297 Enteric Methane Emissions by Ruminants-A Way to Approach the 2 . 0 °C Target. https://doi.org/10.31220/agriRxiv.2021.00040.
EPA, 2018. Inventory of U.S. greenhouse gas emissions and sinks. 1990-2017. https://www.epa.gov/ghgemissions/inventory-us-greenhouse-gas-emissions-and-sinks.
FAO and GDP, 2018. Climate change and the global dairy cattle sector – The role of the dairy sector in a low-carbon future. Rome. 36 pp. Licence: CC BY-NC-SA- 3.0 IGO. http://www.fao.org/3/CA2929EN/ca2929en.pdf.
Intergovernmental Panel on Climate Change (IPCC), 2019. Chapter 10: Emissions from Livestock and Manure Management. Volume 4: Agriculture, Forestry and Other Land 346 Use. 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories.
Kebreab, E., K.F. Reed, V.E. Cabrera, P.A. Vadas, G. Thoma, and J.M. Tricarico. 2019. A new modeling environment for integrated dairy system management 9. doi:10.1093/af/vfz004.
Myhre, G., Shindell, D., Breon, F. M., Collins, W., Fuglestvedt, J., Huang, J., Koch, D., Lamarque, J. F., Lee, D., Mendoza, B., Nakajima, T., Robock, A., Stephens, G., Takemura, T., Zhang, H. 2013. Anthropogenic and natural radiative forcing. In: Stocker, T. F., Qin, D., Plattner, G. K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., Midgley, P.M. (Eds.), Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 659e740.
Jayasundara, S., Worden, D., Weersink, A., Wright, T., VanderZaag, A., Gordon, R., and Wagner-Riddle, C. 2019. Improving farm profitability also reduces the carbon footprint of milk production in intensive dairy production systems, Journal of Cleaner Production, 229: 1018-1028. https://doi.org/10.1016/j.jclepro.2019.04.013.
Le, S., S. Jeffrey, and H. An. 2020. Greenhouse Gas Emissions and Technical Efficiency in Alberta Dairy Production: What Are the Trade-Offs? Journal of Agricultural and Applied Economics, 52(2), 177–193. https://doi.org/10.1017/aae.2019.41
Moraes, L. E., J. G. Fadel, A. R. Castillo, D. P. Casper, J. M. Tricarico, and E. Kebreab. 2015. Modeling the Trade-off Between Diet Costs and Methane Emissions: A Goal Programming Approach. Journal of Dairy Science, 98(8), 5557–5571. https://doi.org/10.3168/jds.2014-9138
Njuki, E., and B. E. Bravo-Ureta. 2015. The Economic Costs of Environmental Regulation in US Dairy Farming: A Directional Distance Function Approach. American Journal of Agricultural Economics, 97(4), 1087–1106. https://doi.org/10.1093/ajae/aav007
Roque, B.M., M. Venegas, R.D. Kinley, R. de Nys, T.L. Duarte, X. Yang, and E. Kebreab. 2021. Red seaweed (Asparagopsis taxiformis) supplementation reduces enteric methane by over 80 percent in beef steers. PLoS One 16:e0247820. https://doi.org/10.1371/journal.pone.0247820.
Thoma, G., J. Popp, D. Nutter, D. Shonnard, R. Ulrich, M. Matlock, D.S. Kim, Z. Neiderman, N. Kemper, C. East, and F. Adom. 2013. Greenhouse gas emissions from milk production and consumption in the United States: A cradle-to-grave life cycle assessment circa 2008. Int. Dairy J. 31:S3–S14.
https://doi.org/10.1016/j.idairyj.2012.08.013.
Uddin, M.E., and E. Kebreab. 2020. Review: Impact of Food and Climate Change on Pastoral Industries. Front. Sustain. Food Syst. 4:1–13.
https://doi.org/10.3389/fsufs.2020.543403.
Uddin, M.E., J. Tricarico and E. Kebreab. 2022. Impact of nitrate and 3-nitrooxypropanol on the carbon footprints of milk from cattle produced in confined-feeding systems across regions in the United States: A life cycle analysis. J. Dairy Sci. https://doi.org/10.3168/jds.2021-20988.
Wattiaux, M. A., M. E. Uddin, P. Letelier, R. D. Jackson, and R. A. Larson. 2019. Invited Review : Emission and mitigation of greenhouse gases from dairy farms : The cow, the manure , and the field. Appl. Anim. Sci. 35:238–254. https://doi.org/10.15232/aas.2018-01803 .
Research
The project hypothesizes that the relationship between the carbon footprint of milk production and farm profitability will vary depending on the production system (small, mid, and large farm operations) and feeding management scenarios. Specifically, it proposes that certain feeding and management practices can result in a synergistic relationship—where both economic (e.g., profit per cow or milk yield) and environmental (e.g., carbon footprint) sustainability are simultaneously improved—while other scenarios may show trade-offs. This relationship will be evaluated using on-farm data (from a survey and sample collection) and a comprehensive life cycle assessment focused on the pre- and post-harvesting life cycle assessment model.
Selection and Engagement of Dairy Producers/Farmers
As mentioned in the rationale section, our work will focus growing I-29 dairy corridor region emphasizing dairy production systems in South Dakota and the neighboring states such as Minnesota and Iowa. Our team personnel or members included two extension dairy specialists who have built excellent and long-standing rapport with the dairy producers in the region. Based on our informal conversation with the producers, we received producers inputs which we considered as extremely important and embedded in our project proposal. As part of our efforts, we have made the collaborative agreement with producers who have agreed to provide the data and samples required for this project. In return, we committed with the producers that each participated producer will be compensated with an equipment such as digital refractometer or based on the need of the participated farmer (worth of $500/farmer) and gift card (worth of $100/farmer). At this stage, we have included support letters from producers, however, our goal is to include at least 30 producers in this study covering mostly small, some medium and few large farms of the regions since small farms are still predominant in the region whereas large farms are emerging. The additional efforts are in-process to get support letters from all 30 producers who have agreed to provide required data and be part of this project. We aim to visit at least 3 times to each farm included in this project during implementation year 1 an 2 to gather required data and collect samples.
Collection of Foreground Data and Required Samples
The following foreground data and samples will be collected from each individual producer using on-site/on-farm survey or through collecting and analyzing samples:
1. Farm size and herd structure: We will collect acreage of land, herd composition (number of milking cows, dry cows, heifers raised off-farm, heifers raised on-farm, and young calves) data using on-site survey interview.
2. Production performances: Milk production and milk composition or components data will be collected from the producers' record. If milk component data is not available, then we will collect and analyze the bulk tank samples (6 sample per farm over 3 visits) for milk components.
3. Diet and feeds: Diet composition, produced (on-farm) dietary ingredients, purchased dietary ingredients, inputs for produced dietary ingredients (e.g., fossil fuel, fertilizer, insecticide, herbicide etc.) will also be collected from producers records. In case of unavailability (which we anticipate for small farms), we will collect total mixed ration samples for each category of animals and analyze for diet composition.
4. Manure management and composition: Manure yield, manure composition via sampling and analyzing manure, manure processing (if any such as solid and liquid separation), manure storage conditions, duration of storage, and manure application rate, timing (e.g., fall vs. spring) and methods (e.g., surface vs. injection or combination) related information will be collected.
5. Analyses of feed, milk and manure samples: If data are not available from the producers particularly dietary and chemical composition of the diet, milk and manure, then samples of feed, milk and manure will be collected and analyzed in duplicate for chemical composition. Milk samples will be analyzed for total solids, milk fat, milk protein, lactose and milk urea nitrogen (MUN). Feed samples will be analyzed for dry matter, ash, crude protein, starch, neutral detergent fiber (NDF), acid detergent fiber, microminerals (Ca, P, Na and K). Based on the dietary (total mixed ration) ingredient composition gathered from the producers, we will calculate dietary chemical composition for each animal category such as lactating cows, dry cows, young heifers, pregnant heifers using National Academy of Sciences, engineering, and Medicine (NASEM-2021) nutrient requirements of dairy cattle (8th revised edition) software. Soil samples collected from multiple site covering all farms and forage types will be analyzed for nutrient profile aiming to determine the manure recycle rate.
6. Farm fossil fuel and energy: Fossil fuel and energy needed to operate farm such as feeding, cooling & heating, watering, milking, transportation will also be collected to determine farm fossil fuel and energy related emissions.
7. Emission factors: As a common practice in life cycle assessment, emission factors will be calculated/estimated using either Intergovernmental Panel on Climate Change (IPCC, 2019) equation or available equation from the recent literature depending on availability of inputs data collected from the producers.
Additional Background Data Collection
In addition to foreground data, background data (e.g., emission factor for electricity and fossil fuel production, emissions related to transportation of purchased feeds and fertilizers) that will be needed to build our model will be collected from the credible sources representing the regional production practices and systems. Additionally, weather data such as temperature, humidity, precipitation/rainfall which affect manure and soil emissions will be collected from nearby station.
Model Development
A cradle-to-farmgate life cycle assessment (LCA) will be performed according to the Food and Agriculture Organization of the United Nations (FAO) Livestock Environmental Assessment Partnership guidelines (FAO, 2016a, b) to determine carbon footprint using SimaPro LCA software. If inputs data are available then we might consider to determine other relevant impact assessment such as water footprint and eutrophication potential . The boundary of the system will include animal production, feed production, manure management, and farm management (Figure 2). The functional unit will be 1 kg of fat-and -protein corrected milk [FPCM (kg/d) = milk production (kg/d) × (0.1226 × milk fat % + 0.0776 × true protein % + 0.253) (IDF, 2015). We will develop several LCA models to represent specific farm types (small, medium and large farm), manure management and feeding management (e.g., cover crop vs. no cover crop) scenarios. Each LCA model for the particular farm type and production management scenario will be used to determine baseline footprint.
Development of Sustainability Assessment Tool & Evaluation of Best Practices or Mitigation Strategies
The baseline LCA model developed will be made available to the producers as an online assessment tool for assessing sustainability (economic and environmental) of their own production scenario. The initial version of the online assessment tool will be used as testing scale which will further be refined using feedback from the users (out of the scope of this proposed study). Producers will be given access to this easy to use online assessment tool through an website where users can sign up and get accessed to the specific tool or model of their interest. In the online tool, users will be able to provide inputs such as herd structure information, milk production and component, diet composition, proportion of forages and grains produced or purchased, manure management to get the desired outputs which is carbon footprint of their interest. Additionally, users will also be able to choose best management practices, and potential or approved mitigation strategies (e.g. enteric methane mitigation strategies such as seaweed, 3-nitrooxypropanol) as inputs to determine the their effects on carbon footprint. Scenario assessment model will be developed as per method described by Uddin et al. (2022).
Dairy Farm Economic Performances and its Relationship with Carbon Footprint
To determine the viability of a farm or production scenario or mitigation practice, we need to determine both economic and environmental sustainability. To do so, dairy and non-dairy (e.g., cash crop) farm revenues and expenses data will be collected to determine economic indicators such as total farm profit per cow and dairy profit per cow or per kilogram of milk basis. Once we have environmental impact (e.g., carbon or water footprint or eutrophication potential) and economic performances, then we will build correlation between them to determine potential tradeoff or synergy between this two important pillars of sustainability.
References
Intergovernmental Panel on Climate Change (IPCC), 2019. Chapter 10: Emissions from Livestock and Manure Management. Volume 4: Agriculture, Forestry and Other Land 346 Use. 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories.
IDF. 2015. A Common Carbon Footprint Approach for the Dairy Sector. The IDF guide to standard life cycle assessment methodology. Bulletin of the International Diary Federation 479/2015. https://store.fil-idf.org/product/a-common-carbon-footprint-approach-for-the-dairy-sector-the-idf-guide-to-standard-life-cycle-assessment-methodology/.
Uddin, M.E., J. Tricarico and E. Kebreab. 2022. Impact of nitrate and 3-nitrooxypropanol on the carbon footprints of milk from cattle produced in confined-feeding systems across regions in the United States: A life cycle analysis. J. Dairy Sci. https://doi.org/10.3168/jds.2021-20988.
National Academies of Sciences, Engineering, and Medicine (NASEM). 2021. Nutrient Requirements of Dairy Cattle: Eighth Revised Edition. Washington, DC: The National Academies Press. https://doi.org/10.17226/25806.
We have a collaborative agreement with 30+ dairy producers from South Dakota, Iowa, and
Minnesota, mainly covering small, some medium, and a few large farms in the regions. At this
moment, we have received written letters from 14 producers who will be collaborating at the time of project submission.
Proposed participants:
- Dr. Md Elias Uddin, Assistant Professor, Department of Animal Science, University of
Connecticut, Storrs, CT, CT 06269 (Project Coordinator), - Dr. Maristela Rovai, Associate Professor, Dairy and Food Science Department, South
Dakota State University, Brookings, SD 57007 (Project Cooperator), - Dr. Patricia Villamediana, Extension Dairy Field Specialist, Dairy and Food Science
Department, South Dakota State University, Watertown SD 57201 (Project Cooperator) - Dr. Rebecca Larson, Associate Professor and Extension Specialist in Waste Management,
University of Wisconsin-Madison, 232 E Agricultural Engineering Building 460 Henry
Mall, Madison, WI 53706 - Graduate student researchers
- Undergraduate student researchers
- Internship students
Actual participants:
- Dr. Md Elias Uddin, Assistant Professor, Department of Animal Science, University of
Connecticut, Storrs, CT, CT 06269 (Project Coordinator), - Dr. Maristela Rovai, Associate Professor, Dairy and Food Science Department, South
Dakota State University, Brookings, SD 57007 (Project Coordinator), - Dr. Patricia Villamediana, Extension Dairy Field Specialist, Dairy and Food Science
Department, South Dakota State University, Watertown SD 57201 (Project Cooperator)
*no longer participating. She resigned from SDSU on 09/2024 - Dr. Rebecca Larson, Associate Professor and Extension Specialist in Waste Management, University of Wisconsin-Madison,
- Md Sadakatul Bari, (graduate student researcher).
- Undergraduate student researcher (not recruited yet)
- Internship student from Mexico (visa denied twice in December 2024 and February 2025)
- Internship Student from Spain (paperwork approved April 2025 and preparing the consulate interview)
We are confident we can complete the project activities within the designated timeframe.
However, unforeseen circumstances may necessitate a slight extension:
1. The Avian Flu situation in 2024 and earlier in 2025 slowed the project down.
2. In early 2025, the budget for purchasing material for this project was also delayed due
to the university's new internal requirements.
3. Dr. Villamediana resigned in September 2025, letting Dr. Maristela Rovai alone organize
the project in SD.
4. Students recruited have their visas denied entry into the US.
Despite these potential challenges, we remain dedicated to ensuring the project's successful
and timely execution.
Describe accomplishments for this activity:
- Recruitment/ Admission of graduate student: Md Sadakatul Bari has been recruited as
a graduate student (PhD) researcher under the supervision of Dr. Uddin at the
Department of Animal Science in the University of Connecticut (UCONN) in Fall 2024. - Procurement of SimaPro LCA software: The SimaPro LCA software (version 9.6.0.1) has
been successfully procured. - Training of graduate student: Md Sadakatul Bari, graduate student researcher has
received basic training on LCA from Dr. Uddin. He is now undergoing training in the
modeling tool SimaPro LCA software (version 9.6.0.1). - Review collection: The graduate student is conducting a comprehensive literature
review on the LCA of dairy farming and the environmental and economic performance
of various dairy production systems. - Initial model for LCA: The initial cradle-to-farmgate LCA model has developed by PI Uddin using LCA tool (SimaPro software), which will be modified and updated based on the data that will be collected from existing dairy production systems in North-Central region under varying production & dietary scenarios.
- Data collection: We have established a collaborative agreement with over 30 dairy producers across South Dakota, Iowa, and Minnesota, encompassing primarily small farms, along with some medium and a few large-scale operations. However, data collection has been hindered due to the outbreak of highly pathogenic avian influenza (HPAI), specifically the H5N1 strain, which has been detected in dairy cattle farms across the United States. As a result, producers are currently unwilling to share information. Hopefully, we can start our data collection in the summer, 2025.Also, Dr. Rovai class commitment and Dr. Villamediana resignation made things a little bit more complicated.
- Material purchases: Devices to be offered to participants are being negotiated between the company providing the refractometers and the university.
- Planning and protocol development for sample collection: We have formulated a comprehensive plan and protocol for data collection on various aspects of dairy farm operations across South Dakota, Iowa, and Minnesota, encompassing predominantly small farms, along with some medium and a few large-scale operations. The data collection will cover farm size, herd structure, dietary ingredients and their chemical composition, milk production, and composition, manure yield and composition, and the collection, processing, storage, and application of manure. Additionally, it will include information on feed ingredients (both produced and purchased), energy usage (electricity and fossil fuels), fertilizer application, and financial aspects such as dairy and non-dairy revenues and expenses.
- Questionnaire development for data collection: We have developed a comprehensive and detailed questionnaire to facilitate the systematic collection of the data above. For this questionnaire, Dr. Rovai facilitated real farm data (e.g., feed and financial analysis data) that helped design the protocol with key information needed to complete this project. This questionnaire is designed to capture essential information related to farm size, herd structure, dietary ingredients and their chemical composition, milk production and composition, manure yield and characteristics, and the collection, processing, storage, and application of manure. Furthermore, it includes sections to gather data on feed ingredients (both farm-produced and purchased), energy consumption (including electricity and fossil fuel usage), fertilizer application, and the financial performance of the farms, covering both dairy and non-dairy revenues and expenses. The questionnaire is structured to ensure accuracy, consistency, and ease of data collection from dairy producers across the South Dakota, Iowa, and Minnesota regions, where small farms dominate alongside some medium and a few large-scale operations.
Project Meetings:
In-person: Drs. Uddin and Rovai met in Florida (June 2024) while at ADSA and in Canada
(September 2024) while meeting with a USDA group to discuss the next steps of this
project.
Online: Several meetings between Drs. Uddin and Rovai and students to tune the
questionnaire, material purchases, etc.
Education
The educational approach in this project integrates experiential learning, interdisciplinary research, stakeholder engagement, technology-driven learning, outreach, and professional development to bridge academia and practical application. Graduate and undergraduate students actively participate in real-world data collection, sample analysis, modeling, receiving hands-on training in LCA, carbon footprint analysis, and economic evaluation. Their research involves collecting farm-level data on herd management, feed composition, manure handling, and farm profitability, providing them with a comprehensive understanding of dairy production systems.
Project Activities
Educational & Outreach Activities
Participation Summary:
No outreach conducted at this time.