Access to services starts at Togetherall, a safe, clinically moderated peer-to-peer community, where members around the world are there to listen, support and give members’ mental wellbeing a boost. Through an anonymous profile, users can access a global network of peers, backed by the safeguarding of licensed clinicians overseeing the community around-the-clock. Access to the platform is available to members of a farm family aged 16 and older.

In addition to Togetherall’s global community, farmers and their families will have access to an agricultural sector sub-group to share or read others’ experiences in a safe, judgement-free zone.

“Farming is tough even on the best days. That’s why Farm Bureau has been committed to helping farmers and ranchers across the country get connected with the tools and resources they need to promote mental health and wellbeing—and to check in on their friends, neighbors and loved ones. Togetherall will help us all to do just that,” said AFBF President Zippy Duvall.” It’s OK not to be OK, but it’s not OK not to reach out when you’re hurting. We are grateful for how this partnership will strengthen our rural communities and provide the support we all need.

The Farm Family Wellness Alliance is made possible through a coalition of organizations, including Farm Foundation, American Farm Bureau Federation, Farm Credit, CoBank, Iowa Farm Bureau, CHS, Land O’Lakes, National Farmers Union, 4-H, FFA, Agriculture Future of America, Togetherall and Personal Assistance Services. This coalition makes it possible to offer services to farm families nationwide and deepens the impact of an earlier pilot initiative started in Iowa with the addition of the Togetherall peer-to-peer support platform.

“Farm Foundation has been working towards the goal of improving farmer access to mental health and other wellness services for several years, with the Farm Family Wellness Alliance pilot starting in 2020 after the derecho in Iowa,” said Shari Rogge-Fidler, president and CEO of Farm Foundation. “We are pleased to have been able to bring together this coalition of farmer-serving organizations into a partnership that allowed us to expand the program nationwide and will offer so much direct and immediate benefits to American farmers.”

Togetherall also offers a range of wellbeing tools, such as self-assessments and access to additional support services through a partnership with Personal Assistance Services. Topics covered include anxiety, depression, financial health, improving sleep and more.

“Navigating the challenges of farming can be tough, and other farmers are often the only other people who can understand the unique stressors of the industry. Anonymous, safe, online peer support is a critical component on the mental health support continuum, and especially important in reaching communities such as farmers, who may otherwise not reach out for support,” said Matthew McEvoy, CEO of Togetherall. “We are thrilled to partner with the Farm Family Wellness Alliance to offer Togetherall’s online, clinically moderated, peer support community to all farmers and their families across the US.”

The landmark alliance bringing Togetherall and Personal Assistance Services to farm families represents a broad swath of agricultural organizations, illustrating the far-reaching impacts of mental health and well-being in rural America.

“Farm Credit recognizes the challenges America’s farmers and ranchers face, especially related to mental health and stress. Fewer resources exist in rural areas as compared to urban areas,” said Todd Van Hoose, president and CEO of Farm Credit Council. “This free, anonymous, and safe access to mental health support offers assistance in a way nothing has before for rural Americans. We appreciate Farm Foundation’s leadership in bringing this resource to fruition.”

To learn more about the Farm Family Wellness Alliance and the services available through the Togetherall platform, visit booth 538 at the American Farm Bureau Federation Convention tradeshow floor (through Monday, Jan. 22) or go to www.farmfoundation.org/farm-family-wellness-alliance/.

The post Farm Family Mental Health and Wellbeing Services Revolutionized appeared first on Farm Foundation.

There is a critical need to better understand how the diversity of both farms and operators interact to affect engagement with and outcomes from agricultural policy. This includes how different farmer characteristics interact with agricultural policy to shape producer enrollment and participation in government programs, the allocation of resources for producer support, program access and eligibility, as well as evaluation and reform.

Through a mix of panel discussions and paper presentations, the goal the  Agricultural Policy, Economics, and Diverse Farms and Farmers virtual conference is to: 

• Expand on the existing knowledge base of how diversity in U.S. agriculture, both of farmers and farm operations, interacts with agricultural policy
• Initiate discussion on farmer equity and inclusion in U.S. agricultural policy
• To better understand data available to explore these linkages, as well as identify data gaps
• Foster networks of researchers, policymakers, and industry professionals working on these issues

Call for Abstracts
Farm Foundation seeks submissions of research papers at the intersection of agricultural policy, economics, and the diverse characteristics of U.S. farms and farmers. In particular, we encourage submissions of papers taking an empirical approach to these issues. The papers can be based on new research or can revisit previously analyzed data with a new focus on the themes of this conference. Submissions from researchers and students from minority-serving institutions are especially encouraged.

All abstracts should be limited to 350 words and must be submitted through the online application portal by January 25, 2024.  

The conference is being organized by USDA ERS and Farm Foundation.  

The post Farm Foundation® Call for Papers on Intersection of Ag Policy, Economics, and Diverse Farms and Farmers appeared first on Farm Foundation.

The program includes events and projects conducted throughout the year, including a mentorship with an ERS senior analyst, a research project, and participation in ag-focused forums and meetings, such as the USDA Ag Outlook Forum, AAEA’s Annual Meeting, and Farm Foundation Round Table meetings.

“This is just an incredible group of students,” says Program Manager Jenna Wicks. “Thanks to ERS’ continued generous partnership we are able to create a year of landmark opportunities for these program participants which will set them on rare footing as they enter their careers.”

The 2024 Agricultural Scholars are:

Kristiina Ala-Kokko, Kansas State University
Kristiina is a Ph.D. student in the Department of Agricultural Economics at Kansas State University. Her research focuses on issues related to agricultural production and policy, particularly seed technology adoption, conservation agriculture, and climate change. 

Ian  Bennett, University of Florida
Ian is a master’s student in the University of Florida’s Food and Resource Economics department. His research interests are sustainability, livestock, genetics, and the connections between agriculture and healthcare.

Courtney Cooper, University of Arkansas
Courtney is a second-year environmental dynamics Ph.D. student at the University of Arkansas, specializing in local and regional food systems, primarily focusing on the Mississippi Delta region.

Elizabeth Crespi, Johns Hopkins University Bloomberg School of Public Health
Elizabeth is a Ph.D. student and Center for a Livable Future Lerner Fellow at Johns Hopkins University Bloomberg School for Public Health. Her focus is on understanding how to support farmers in adopting sustainable agricultural practices.

Andre De Souza Coelho, University of the District of Columbia
Andre is a Ph.D. student in urban leadership and entrepreneurship, a researcher, and adjunct faculty at the University of the District of Columbia. He studies structural economics using input-output analysis to evaluate sustainable strategies, technologies, and policy implementation, now specifically investigating food systems. 

Suhina Deol, Washington State University
Suhina is an economics Ph.D. candidate at the Washington State University specializing in agricultural economics and econometrics. One of her papers examines psychological ownership effects and nonpecuniary returns to farming on water markets.

Aisling Hagan, University of Tennessee
Aisling is a first-year master’s student in agricultural and resource economics at the University of Tennessee. Her research focuses on food loss and waste reduction at the consumer-grocery retailer interface. 

Rachel Judd, Texas A&M University
Rachel is pursuing a doctorate in agricultural economics at Texas A&M University, where her research interests focus on water quality and availability in both agricultural and urban contexts.

Clare McGrady, Michigan State University
Clare is a second-year master’s student in the Department of Agricultural, Food, and Resource Economics at Michigan State University. Her thesis project explores the role of sanitary and phytosanitary measures on trade balances in East Africa and the implications on producer welfare.

William McWilliams, Virginia Tech University
William is a doctoral student in the department of Agricultural and Applied Economics at Virginia Tech University. His current research is focused on evaluating and improving the performance of current methods for forecasting food price inflation.

Matthew Melchor, Kansas State University
Matthew is an M.S. student in agricultural economics at Kansas State University. His research focuses on production livestock and animal health economics, understanding how they can be influenced by policy decisions and government regulations. 

Logan Moss,  University of Arkansas
Logan is pursuing an M.S. in Agricultural Economics with a research focus on agribusiness marketing and policy. He is passionate about advocating for producers and creating a more innovative and inclusive agri-food industry.

Mya Price, University of the District of Columbia
Mya is director of the Food Security Equity Impact Fund at Feeding America. In addition, she is pursuing her Ph.D. in Urban Leadership and Entrepreneurship from the University of the District of Columbia with a focus on urban government and political leadership.

Nicholas Reynolds, Florida Agricultural and Mechanical University
Nicholas is a graduate student and research assistant studying agribusiness at Florida A&M University.

Olivia Richard, San Diego State University
Olivia is in her first year of the M.A. in economics program at San Diego State University. Her future goals involve a career as an economist pursuing research and policy analysis for federal agencies, NGO’s, or policy-oriented non-profits.

John Robinson, North Carolina State University
John is a 4th-year Ph.D. student in agricultural economics and Koch Foundation Fellow at North Carolina State University. His areas of interest include grain marketing, risk management, and price analysis.

Lorin Rudin-Rush, University of Wisconsin-Madison
Lorin is in his first year as a Ph.D. student in agricultural and applied economics at the University of Wisconsin. His master’s research focused on food security and the COVID-19 pandemic in Africa.

Tyler Treakle, Arizona State University
Tyler is a Ph.D. student in sustainability at Arizona State University. He is interested in studying tradeoffs and interactions between species conservation and agricultural productivity using econometric and bioeconomic modeling approaches.

Rebecca Weir, University of Minnesota
Rebecca is in her third year of the applied economics Ph.D. program at the University of Minnesota. Her current research projects include analyzing county-level impacts from livestock consolidation in Minnesota and analyzing the impact of a collaborative on-farm advisory team on dairy farm profitability for Minnesota dairy farms.

Katherine Westerman, University of Rhode Island
Katherine is a master’s student in environmental and natural resource economics at the University of Rhode Island. Her research interests include regenerative agriculture and sustainable farm management to aid the diversification of farm products and the use of machine learning as a tool to assess agricultural policy effectiveness.

For more about each of the 2024 Agricultural Scholars and to learn more about the program at https://www.farmfoundation.org/programs-overview/agricultural-scholars/

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Farm Foundation President and CEO Shari Rogge-Fidler reflects on her experience at COP28 as part of the Solutions from the Land farmer delegation to Dubai. It was originally published as a LinkedIn article. Solutions from the Land has published additional comments on COP28 on their blog.

I had the distinct honor and privilege of being part of a delegation of US farmers attending the UN climate conference in Dubai, COP28.   As a 5th-generation farm owner and operator from Nebraska, my ancestors began life on the prairie in a sod house made from the soil.  Little did they know that farming was going to go through a huge transformation.  We have learned so much in the last few decades about the importance of soil and how it can be managed for the benefits of agriculture, humans and the environment, including sequestering carbon.

Farmers provide the basic human needs for people – food, fiber for clothing, energy – and ecosystem services for our planet.

For these reasons, it is critical to have farmers at the table for any discussions on changes in the food and agriculture system, to ensure their expertise is leveraged for increased effectiveness as well as preventing unintended consequences of policies and decisions that might detrimentally affect supplying the world with what they need for life.

I was part of the US delegation of 10 farmers who participated in the broader global farmer constituency of approximately 40-50 people from Africa, Asia, Australia, Europe and more.  We were part of the official “blue zone” where the negotiations occurred, which had approximately 18,000 people.  There was also a “green zone” and a total of 100, 000 people attending the broader activities of COP28.  The farmer constituency met daily to report on progress with the negotiations, highlight issues, and events where a farmer perspective would be helpful or necessary.

The key issues the farmer constituency focused on were ensuring the negotiation process moved forward for food and agriculture and not letting the wishes of a few countries to establish a new and permanent body delay the progress.  The second issue involved editing some of the key documents to include the word “farmer” in the lists of constituents called out as important in the negotiations and implementation, with the view that farmers need to be involved in providing input and guidance on any commitments and implementation.

The farmer constituency had the opportunity to make a formal statement in the room with the leaders of the negotiations early in the process and at the closing session.  We literally had a place and place card at the formal UN table that said “Farmer.”

We also met directly with other key leaders, including US Secretary Vilsack, as well as our own US negotiator and senior climate advisor to hear firsthand how the process was going and to provide feedback.

These opportunities were set in the context of the food and agriculture declaration launched on day one of COP28, garnering the most recently reported and growing number of 152 countries signing on with support, including the US.  We also experienced the historic milestone of a dedicated food and agriculture day, enabling many of the issues and opportunities to be highlighted through dialogues and presentations across the convention space.

The closing statement of the farmer constituency highlighted the disappointment of the documents not including farmers specifically, while mentioning the food system:

“We deeply believe that farmers’ voices must be heard. We call for a greater consideration of our priorities in all decisions that impact us. Climate finance must deliver for all farmers by involving them directly in the design and governance of climate programmes and targeting them as direct recipients of funds. The next round …must raise credible ambition and action for agriculture through the active engagement of farmers in the definition of goals and objectives. Farmers are part of the solution to climate change, and we stand ready to work with you beyond COP28.”

The negotiations lingered longer than the defined stop date, with countries driving for further alignment and agreement on fossil fuels before departing. Regardless of whether the COP process results in significant agreements, the private sector is driving ongoing change and their own commitments to support both climate mitigation and adaptation.

Much like when my ancestors were in the sod house at the cusp of change, so too are we now experiencing a “21st Century Agriculture Renaissance,” as Solutions from the Land calls it, with innovations and advancements making increased contributions to people and the planet.

Farmer voices and expertise needs to be leveraged for both public and private sector commitments to provide insights into the innovations and implications on farms.

Instead of building a sod house as our ancestors did, our family farm is building soil health and integrating technology and innovation for the benefit of many for generations to come.  Farmers around the world are working to build increased food security and nutrition, along with the many other benefits to society.  We gathered in Dubai to collaborate, build, and advance a vision for a vibrant food and agriculture system sustaining our planet throughout the 21st century and beyond.

The post Perspective on COP28: From a Prairie Sod House to Dubai appeared first on Farm Foundation.

Farm Foundation’s Agricultural Economics Fellow program is a yearlong program for a faculty agricultural economist. The 2024 fellowship is focused on integrated systems approaches to understanding and overcoming the challenges in developing a greater understanding of how trade and sustainability are interconnected and are impacting the food and agricultural sectors in the United States and beyond. Dr. Steinbach is Farm Foundation’s fourth Agricultural Economics Fellow and succeeds Drs. Trey Malone (University of Arkansas), Amanda Countryman (University of Colorado), and Alejandro Plastina (University of Iowa).  

In addition to being mentored by staff in USDA’s Office of the Chief Economist, Steinbach in turn will mentor participants in the Farm Foundation and USDA Economic Research Service Agricultural Scholars program, among other engagements.  

“We are pleased to welcome Dr. Steinbach to our Agricultural Economics Fellowship program,” says Martha King, vice president of programs and projects at Farm Foundation. “His research interests in international trade and agricultural policy set the stage for a fruitful collaboration towards advancing Farm Foundation’s ongoing work in agricultural trade and international sustainability policy.” 

Steinbach is the director of the Center for Agricultural Policy and Trade Studies and a faculty scholar of the Sheila and Robert Challey Institute for Global Innovation and Growth. He is also a visiting scholar and consultant at the United States Department of Agriculture. 

As part of his fellowship, Steinbach will author a Farm Foundation Issue Report. His recent work has appeared in Applied Economic Perspectives & Policy, Economics Letters, the NBER Working Paper Series, and Nature Communications. 

He holds master’s degrees from Humboldt University of Berlin and the University of California, Davis. In 2018, he completed his doctoral studies in economics with the Center for Economic Research at the Swiss Federal Institute of Technology in Zurich, Switzerland. 

The post Farm Foundation Announces 2024 Agricultural Economics Trade and Sustainability Fellow appeared first on Farm Foundation.

First, thanks to Climate Action for including me here as a farmer. I think that’s an important voice and I’m actually wearing three hats here at COP. The only reason I’m here at COP is because I’m first and foremost a farmer and I’m part of a farmer delegation. I was brought here by Solutions from the Land which I think is a really powerful name because farmers are providing solutions from the land. And then the third hat I’m wearing is with Farm Foundation, a 90-year-old think tank/do tank. I’m a practical farmer and Farm Foundation is trying to drive practical solutions. 

First of all, when we say, “connecting the value chain from farm to fork,” even though we usually say, “farm to fork,” it’s often the farms that are last in the conversation and last to the table and last in the solutions. I think we really need to invert that because as a 5th-generation farmer I’m so passionate about the role of farmers in driving solutions. We’re seeing a tsunami of innovations coming from farms all around the world and including on my own farm, and it’s not because we’ve been told to do this. It’s not because we’ve been told to save the planet. It’s not because we’re trying to hit sustainability goals for companies. It’s because we need to do that on our own operations to sustain it for the next generation. With all these innovations going on, it’s a very exciting time to be involved in agriculture.

I come with hope, despite in my first 24 hours of being here feeling frustrated already about COP as they eliminated the word “farmer” from the documents, for example, from the discussions. But the kind soul in the front row over here encouraged me, saying, “You know we don’t have to wait for COP. We are already doing these innovations in the private sector and can keep moving forward.” However, I would say there are four gaps that all of us collectively need to try to solve to drive innovations forward. Some of them are simple, some of them are more complex. The gaps that I see are language gaps, data gaps, resource gaps, and contract gaps for connecting the farm to fork.

Contract gaps: I’ll start with that one. It’s the easiest. So many farms are fragmented and not part of the contracts going on with the big food companies. Sometimes they want to be involved in those contracts, but they don’t know how to connect to the exciting things going on with the other end of the supply chain.

Language gaps: In our own little echo chambers, I think we all think we understand what regenerative ag is, for example. We talk about it, maybe every day. But in my farm community, if you polled our county, I don’t think anyone would know what the word “regenerative agriculture” means. That’s not the language that we use. That one seems like an easy one that we should be able to solve. I think soil health is the connector for us all so let’s connect solutions to soil health when we talk about regenerative agriculture.

Data gaps is one of the more complex ones to solve for. One of our panelists talked about metrics, but it’s not even just the metrics that matter. It’s the data and the data flow that is so disaggregated, fragmented, and we need data interoperability as well. That’s actually part of what Farm Foundation is trying to help solve, some of those pain points.

The fourth one is resource gaps. On my farm I would consider us early adopters. We’ve been doing no till and cover crops for several years. But I’d say we’ve reached a plateau in our ability to drive that forward. We’re having some problems with the stand of our cover crops. And we lack the resources to help us get to the next level in our solutions. I think that’s just one example of the resource gap that we need to try to fill if we want to continue to drive these solutions forward.

Despite those gaps, I come back to the fact that I am optimistic and hopeful. I think we all have to continue to collaborate to close those gaps to continue to drive innovation and solutions forward.

The post Four Gaps in Connecting the Value Chain from Farm to Fork appeared first on Farm Foundation.

This past October, I was honored to attend the Global Forum on Farm Policy Innovation (GFFPI), hosted at the Organisation for Economic Cooperation and Development (OECD) headquarters in Paris. This first-of-its-kind partnership between the Farm Foundation, the Australian Farm Institute, the Canadian Agri-Food Policy Institute, and the Forum for the Future of Agriculture served as a melting pot of ideas and expertise. The event’s primary focus was to leverage our shared passion for sustainability to nurture collaboration in international trade. By bringing together diverse stakeholders, GFFPI aimed to foster innovative policies and practices, driving the agenda of sustainable development through international trade in the global agri-food economy.

As an agricultural economist at the University of Arkansas, I appreciated the global urgency for all countries to collaborate toward a more sustainable agri-food system. I left the event with renewed optimism about the potential for international partnerships to address sustainability concerns via flexible, innovative agri-food trade policy. Here are three areas discussed at the event that I found particularly worth exploring via global collaboration.

1. Global Dialogue on Environmental Impact Reporting

The need for a deeper global dialogue on environmental impact reporting in the agri-food supply chain is of paramount importance. The rising prominence of environmental impact reporting emphasizes its growing influence across the agri-food value chain. As someone deeply engaged in agricultural sustainability, I view these developments with anticipation and caution. The surge in transparency and the increasing demands from consumers and policymakers for clear, honest disclosures have compelled companies to set ambitious emission reduction targets. Yet, robust measurement and reporting challenges are substantial, marked by a landscape rife with inconsistent standards and new directives like the EU’s Corporate Sustainability Reporting Directive mandating Scope 3 emissions reporting.

I applaud the move towards greater transparency, empowering more sustainable production and consumption practices. However, I am also mindful of the potential ramifications. The diversity in methodologies could either spur innovation or sow confusion. A critical concern is whether this surge in reporting might unintentionally marginalize smaller or lower-income producers, who may lack the resources for compliance. The escalation in environmental impact reporting is an irreversible trend that demands vigilance from everyone involved in the food system. Ensuring that the frameworks we adopt genuinely advance sustainability without erecting new barriers is imperative. We must engage critically in these discussions, striving for systems that are transparent, equitable, and supportive of sustainable advancements. In pursuing environmental accountability, we must not lose sight of the intended purpose: to foster a sustainable, inclusive, and equitable agri-food system.

2. Consumer Awareness and Engagement

Increasing consumer awareness and engagement is pivotal in the journey toward sustainable food production, a theme echoed strongly at GFFPI’s workshop. Consumers play a crucial role in driving demand for sustainably produced foods, making their awareness and choices fundamental in shaping the agri-food market. The discussions at the workshop highlighted that an informed consumer base can significantly influence agricultural practices by preferring products that align with sustainable and ethical standards.

Consider gene editing, a revolutionary technology for creating more sustainable food systems. This cutting-edge technique can help develop more resilient crops to climate change, require fewer resources, and yield higher nutritional value. However, the success of gene editing hinges on consumer perceptions and acceptance, as widespread global misperceptions pose a significant barrier to adopting and advancing gene-edited crops. Consumers, often unaware of the benefits of gene editing, might inadvertently impede progress in agricultural sustainability due to these misconceptions. Addressing these misperceptions requires concerted efforts to educate consumers about the global importance of agricultural technology. These efforts must include providing factual information about the reduced need for pesticides, the potential for increased crop yields, and the ability to fortify crops with essential nutrients.

The GFFPI event underscored the need for comprehensive strategies to educate and engage consumers, as informing consumer choices requires supporting innovative technologies that promise a more sustainable agri-food future. As we look towards sustainable solutions in agriculture, ensuring public understanding and acceptance of these new technologies becomes as important as the innovations themselves. In this endeavor, it is vital to recognize that consumer education is a two-way street. The agri-food industry must not only disseminate information but also actively listen to and address consumer concerns, meeting people where they are in their understanding and perceptions. This approach fosters a dialogue-based relationship where consumer feedback can guide and improve industry practices. Policies worth exploring might include clearer labeling, public awareness campaigns, and collaboration between policymakers, producers, and retailers to facilitate easier access to sustainable food choices. Such efforts are crucial in building a more sustainable agri-food system, where consumer choices are not just about personal preference but also about contributing to global sustainability goals. By engaging consumers as active participants in the sustainability conversation, we can ensure that evolution within the agri-food sector aligns with both environmental imperatives and societal needs.

3. Economic Viability and Productivity Through Technology and Innovation

Environmental sustainability in agriculture is incomplete without economic viability for producers. Achieving a balance between these two elements is essential for the long-term sustainability of the agri-food sector. At the core of this balance is the understanding that economic productivity and environmental stewardship are not mutually exclusive; they can be synergistic when approached through innovative technologies and practices.

Consider advancements like artificial intelligence (AI), which has the potential to revolutionize agricultural practices. AI can optimize resource use, enhance crop yields, and reduce environmental impacts, thereby increasing the economic viability of farming while adhering to sustainability principles. For instance, precision agriculture, powered by AI, allows for the precise application of water, fertilizers, and pesticides, reducing waste and environmental damage. Similarly, AI-driven data analytics can provide insights for better crop management and decision-making, enhancing productivity and sustainability.

Transitioning to sustainable practices often requires initial investments that can be challenging for farmers, particularly smallholders. Subsidies, incentives, and fair compensation might play a critical role. By offsetting the initial costs and risks associated with adopting new technologies and practices, these financial mechanisms can make it more feasible for farmers to transition toward sustainable agriculture. They also serve as a recognition of the environmental services that sustainable farming provides.

Modern sustainability challenges require modern, innovative solutions. Policy decisions must be mindful of supporting the development of technologies that are accessible and affordable for farmers of all scales and regions. Innovations should not only focus on high-tech solutions but also on sustainably improving traditional practices. For example, integrating indigenous knowledge with modern technology can lead to more holistic and effective agricultural practices.

The challenge lies in ensuring that these technological innovations and economic incentives are designed and implemented in a way that truly supports sustainable agriculture. Collaboration among governments, private sectors, researchers, and farmers is required to develop solutions that are practical, scalable, and aligned with both environmental and economic objectives. Indeed, advancements in the agri-food sector must continue to evolve in a way that supports the planet and its people, ensuring the economic viability of farming while safeguarding the environment for future generations.

Toward Heightened Global Cooperation

International cooperation is indispensable in addressing the multifaceted sustainability challenges in the agri-food system. The complexities of global food production and consumption patterns necessitate a collaborative approach that transcends borders, integrating long-term sustainability goals with practical, immediate actions. This approach involves harmonizing policies and practices across nations while acknowledging and respecting regional and cultural differences. Meaningful dialogue between the public and private sectors is pivotal. Governments can set the sustainability agenda through public policy, regulatory reform, and incentives, enabling sustainable practices. Through public-private partnerships, agricultural policy might accelerate the private sector’s capacity for innovation, allowing the private sector to bring new technologies and processes to the forefront. The symbiotic relationship between these two sectors is essential for driving meaningful progress towards sustainability.

Furthermore, international cooperation is key to emphasizing open trade, transparency, and establishing common standards. Open trade facilitates the exchange of goods, services, and knowledge, fostering an efficient and sustainable global marketplace. Transparency builds trust and accountability, ensuring that all stakeholders, from farmers to consumers, are well-informed and engaged. Common standards, meanwhile, provide a benchmark for sustainability, ensuring that practices and products meet agreed-upon environmental and social criteria. Flexibility is also crucial in this global framework. Agricultural practices are deeply rooted in local cultures and ecosystems; thus, solutions must be adaptable to different regional contexts. What works in one part of the world may not be suitable for another, and policies must be sensitive to these differences.

The GFFPI workshop underscored the importance of global collaboration in tackling sustainability challenges. As a participant, I witnessed firsthand the power of diverse perspectives coming together to shape a resilient and sustainable future for agriculture. This experience reinforced my belief in the collective commitment required to make a lasting impact. It’s not just about individual actions but how we, as a global community, can unite our efforts and resources to create a sustainable agri-food system that benefits global society. The path ahead is complex and challenging, but with continued collaboration, innovation, and commitment through events like the GFFPI workshop, we can forge a prosperous and sustainable future for generations to come.

A version of this blog first ran in the November 23, 2023, issue of Farm Institute Insights, a publication of the Australian Farm Institute. It is reposted with permission.

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To assist USDA in initial designs for their “Greenhouse Gas (GHG) Quantification Program,” Purdue Open Ag Technology and Systems Center (OATS), Semios, The Mixing Bowl, and Farm Foundation hosted the Building Beta Data Management Protocols for Soil Carbon GHG Quantification virtual “event storming” which took place on October 24, 2023.

Summary of the Meeting Discussion

Modeling and measuring soil carbon content is a soup of complexity.  Even deciding what to measure and how to measure it is difficult enough. Add to that the sometimes difficult to quantify variations in sampling protocols, labs, model needs, the meaning of terms, and the humans involved. And add to that the social and coordination complexities of differing goals across necessary stakeholders such as landowners, government, and industry, interoperability across many organizations for both lab results and records of farming practices, and the sheer spatial scale of estimating soil content across the entire country.

If that wasn’t enough, the models of the relationship between farming practices and changes in soil carbon content are themselves under active research and development which will likely lead to innovations that may constantly move the goalposts for data collection. Much like actual soup, this “complexity soup” must be eaten one spoonful at a time, and more spoons working together will get to the bottom of the bowl faster.  Success will require both generalized coordination and cooperation that builds a solid community of contributors as well as specialized early pipelines that get the first data flowing quickly as a basis to start iterating improvements.

What follows in this document is:

• Background on the Event Storm Activity
• Four Segment Timeline Overviews
• Summary of the Event Storm
• Identified Focus Areas & Ideas
• A Suggested Path Forward
• Appendix: References, Keyword Clusters & Tags

On Tuesday October 24, 2023, a diverse group of government, industry, and academic pioneers gathered for an “event storming” session to gain a shared understanding of the issues involved and solutions for “beta data management” systems involved with measuring soil carbon content and modeling the relationship between farming practices and change in soil carbon content, with a special focus on the United States Department of Agriculture (USDA) initiative to perform country-wide soil sampling and data collection which collects existing data, creates new data, and connects data with carbon models and researchers.  Over the course of just a few short hours, the group had collectively produced an online whiteboard with over 2,000 pieces of information toward this goal.

The goal of this event was to form a community-led understanding of data management surrounding the measurement of soil carbon content and to identify common pain points to be addressed in follow-up events and initiatives to help solve them. Participants jointly identified actions, actors, and data exchanges that occur, or need to occur — through a method known as “event storming.” The resulting Miro board with the virtual sticky-note-based results can be found here.

Event Storming Background

Traditional “event storming” tries to understand the big picture of a process by focusing on the “events” that take place and their approximate order in time. In a pre-pandemic world, this meant writing past-tense verbs (“events”) on orange sticky notes and sticking them on a wall as a big, in-person group of domain experts. In an attempt to approximate the rich conversational environment of in-person sessions, the supply chain was segmented into four separate but overlapping “sector timelines”: groups of sticky notes designed around optimizing a particular group of activities or goals. The larger group of event stormers was broken into four groups, each rotating through those segments while placing stickies and sharing their experiences and insights with the group. The four sector timelines were: Field Data Collection, Soil Lab, Feeding the Models, and Metadata Management.

In addition to events (represented with orange stickies), purple stickies represent “hot spots”: disagreements, ambiguities, etc. White stickies indicate “terms” that arise which comprise part of the domain language.

Finally, once the basic event flow has been established, blue stickies are added to represent decisions, questions, or “triggers” that are relevant to the people involved with the events in the timeline. The people themselves are shown on yellow stickies, and any data or information needed to make those decisions, answer those questions, or pull those triggers was added on green sticky notes.

The resulting “big picture” timelines give insight into what happens, who is making decisions, what questions need to be answered, and what data is needed at which points in time.

Segment Timeline Overviews

The virtual small groups succeeded in triggering some robust conversations, and the group as a whole produced rich event maps. We had a large and diverse group of participants, including farmers, agricultural service providers, ag tech companies, USDA personnel, academics, and researchers.  The broad expertise and differing windows through which participants viewed various parts of the problem resulted in a lot of knowledge sharing and great progress was made toward the goals of developing a shared understanding of the concepts and issues facing beta data management.  Of particular note was the unexpected poetic realization that rutabagas, despite encompassing a negligible amount of land use, have a particularly lyrical quality of “beta rutabaga data.”

FIELD DATA COLLECTION

Moderator: Prof. Ankita Raturi, Agricultural Informatics Lab & Open Ag Tech and Systems Center at Purdue University

When discussing field data collection in the context of soils in agricultural landscapes, the first image that comes to mind is a clod of rich, dark, fresh earth. We think of a laptop computer perched precariously on the edge of a truck, a trail of tests and emails, and the eventual chaos of wrangling a suite of datasheets from clipboards and electronic documents to start the journey. However, the lifecycle of a soil sample begins months, sometimes years, before it is collected, with discussions among farmers and other land stewards, researchers and technical assistance providers, extension agents and crop advisors as they establish a shared project goal and subsequently coordinate and collaborate an intricate sequence of field data collection events. This breakout session mapped three event clusters where these soil data stakeholders collaborate to determine: (1) how a soil field data collection plan is developed, (2) how sampling logistics are coordinated and executed, and (3) how the soils data are verified, validated, and ultimately prepared for downstream analysis and use.

Establishing a Project Goal

Some land stewards sample soils on their fields for their own understanding, using ad-hoc or on-demand data collection methods that likely have simpler logistics as they work independently to quickly ascertain some basic conditions of their field: pH, soil moisture, or otherwise, to inform an in-situ or in-season decision. However, land stewards increasingly participate in larger projects, where soils data are collected across landscapes as part of a goal-driven sampling project: to quantify soil carbon and GHG, to understand the movement of nutrients, and so on. In this scenario, the field data collection logistics are more complex. Individual land stewards must collect data using near-identical protocols, measure the same soil attributes, and even use the same labs for testing (as discussed in a separate session during this event). This level of coordination and collaboration inherently demands a more formalized methodology that is typically created through a rigorous planning process among soil data stakeholders.

In this session, participants converged on mapping this latter form of goal-driven and coordinated soil data collection, describing a semi-formal process where groups of data collectors are oriented toward common scientific questions. Individual data collectors, such as the land stewards themselves, will often have complementary site-specific goals related to soil health and land management. In this sense, the purpose of soil data collection is both to enhance scientific understanding on soil carbon and GHGs, as well as to improve management practices to support sustainability outcomes. 

Once a group of stakeholders are identified (e.g., land stewards, technical assistance providers, government regulators, scientists), a project manager will meet with the group to be able to establish specific, scientifically-feasible, and practical project goals. Participants noted the importance of thinking on protocol as an artifact with many parts: sampling methods, stratification strategies, data structures and vocabularies. These different components are informed by, of importance to, have impact on, and subject to constraints by, different stakeholders, which means that there is need to ensure clear communication, transparency, clarity, and consensus among the project stakeholders.

Background Data Preparation

Next, the project stakeholders need to determine who they need to consult to inform the protocol, as well as identify which data are needed to develop the protocol. In a listing exercise, participants named a non-trivial initial set of data they think are necessary for protocol design: field boundaries and field-level data; tract, PLU ecological site ID and other land identifiers; soil conditions including composition, texture and suborder; historical cropping history including crop rotations, planting and harvest dates; management practices including input application and tillage history (with amount, data, and type for each); existing and planned conservation practices; land use, vegetation, natural resources, drainage, hydrological groups and other environmental conditions; and probably more.

This significant baseline data creates a slew of complications. First, participants noted that there is a desire to identify what a “minimal” dataset constitutes and to come to a consensus across different soil data collection efforts on the necessity and utility of different data types. Digital field-level data, with semantic integrity is also hard to obtain. Each of the different types of data is collected for multiple, sometimes conflicting purposes: for crop management, for regulatory reporting, for ad-hoc understanding, and sometimes, the data simply does not exist. Data quality, format, structure, and reusability are also subject to the norms and limitations imposed by the data collection tools used. This varying level of data availability, granularity, and standardization means that the seemingly innocuous task of collecting background data to inform a soil data collection plan can devolve into a behemoth data science project in itself.

Create the Standard Operating Procedure (SOP)

Once the required background data are collected and prepared, they are used by project stakeholders to create an SOP or protocol. Three questions drive this event. What data needs to be collected and through which sampling methods? What is the stratification goal and strategy? Who will collect the data? Participants noted the need to strive for simplicity in the sampling and data collection process to improve data quality, consistency, and practicality.

Participants dug into the process for identifying a stratification methodology, as it is a critical component of a protocol design. At a minimum, a set of field boundaries must be shared for stratification. These boundaries, in conjunction with any other field-level data available, are used to create a soil sampling plan. The field maps may be compared with the background data to establish areas of variability and priority. The stakeholders must make many highly granular decisions, for instance: which soil characteristics are of key interest to measure; sampling hardware and how the act of sampling needs to occur (e.g., sampling depth, density, number); which labs to use for subsequent soil testing; and how to accommodate site-specific constraints (e.g., physiographic limitations). Once these decisions are agreed upon, stakeholders prepare appropriate data layers, sometimes conducting a mini-quality assurance process to determine data suitability and validity. Choice of stratification algorithm then depends on further decision points such as composite vs single core sampling requirements; project-level vs field-level stratification, and the feasibility of the proposed sampling effort.

Once a stratification and sample plan is created, several forms of stakeholder consultations must occur. Land stewards and field techs are consulted to understand site-specific constraints and, in an ideal situation, the SOP is customized for different sites through a common approach. The SOP documents are ideally shared with the scientific community for review if there are radically novel approaches utilized that have yet to be scientifically validated, as is often the case given the emerging soil science and related research. Participants noted that project stakeholders would ideally also consult with registries, particularly if the land stewards involved are interested in carbon credit and other ecosystem service marketplace programs. Similarly, consultation with agencies like NRCS involved in conversation planning to ease the downstream burden of cost-share program or regulatory reporting. Participants noted that while we often treat the SOP as though it is set in stone, it is typically modified once the sampling venture commences as things change. As SOP review with different stakeholders comes to a close, the level of granularity in an SOP may be increased further to provide step-by-step guidance for in-field staff and technicians who may actually conduct the soil sampling. The project stakeholders both create training materials and ideally conduct in-field training with soil samplers on how to enhance the SOP.

Given the gargantuan effort involved in protocol design, many questions remain. Does planning always translate to action? What is the minimal effort to create a scientifically valid field data collection SOP to understand soil health, quantify soil carbon and GHGs, and ultimately support improved land management actions.

Sampling Logistics

If a detailed, coherent and practical field data collection protocol is designed, then the actual in-season logistics of coordinating sampling dates with land stewards, and the actual act of sampling itself, are more straightforward. Sampling is scheduled with the land steward, or if their own team is responsible for the sampling, they coordinate amongst themselves. A trained field technician arrives at the site, plans their route among all the sample locations, and then simply samples according to plan at the predefined locations. Ideally, there is guidance in the SOP on how to adjust if there is something unexpected at the location itself (e.g., wet, too steep, there’s a tree!). The SOP should also contain guidance on how to select subsamples within the field.

The biggest pain point during the field data collection itself is ensuring that samplers collect the necessary metadata to ensure that the samples are not just meaningless, uncontextualized lumps of soil. Field-level data is ideally collected first, including land management with this-season conditions (e.g., harvested/current/intended crop). Samples, including subsamples, are ideally located to some level of positional accuracy and include, for instance, an interpretable sample ID, GPS data, collection date, sampling depth, soil conditions, type of sample (e.g., bulk or carbon), implement used (e.g. shovel or probe). The sample must also be bagged, tagged, and geolocated according to the lab where it will be sent. Participants noted the need for some level of quality control to be conducted on the sample data before leaving the field, including annotations of possible errors or changes.

Once the samples are collected, those that will be subject to lab testing require work orders to be verified and shipped with the samples to the lab. At this point, there is a suite of soil data events and challenges that occur on the lab-side, as discussed in the “Soil Lab” breakout group.

Data Verification, Validation, and Handoff

A common aphorism in statistics is that “all models are wrong, but some are useful. Participants noted, that similarly, all data are wrong, and the challenge lies in determining how to quantify how “wrong” the data is. That is, when we collect any data, there is some degree of error or uncertainty. Participants noted the importance of verification of soil data samples: for instance, bulk densities are very error prone in practice depending on how the sample was collected. While not all uncertainty can be accounted for, it is important for documentation and metadata to reflect how and where these issues may crop up. Data are also subject to bias (e.g., in where it was sampled); thus, it is important to ensure that there are some mechanisms to document assumptions and constraints in Quality Assurance and Quality Control (QA/QC) plans. There is also a need for methods to reduce errors as data and samples are passed from sampler to shipper to lab tests and back. Solutions may include simply tagging samples themselves with supplementary key identifiers in case of mixups. Sample documentation could also be linked to the lab results and site data.

Where data verification deals with accuracy and quantifying uncertainty, data validation involves ensuring that the data reflects the initial protocol adequately. A simple and common data validation example involves checking to see that the number of samples actually collected match the prescribed number of samples, and if not, why. However, participants noted the need for validation of the process itself! This could be in the form of community review of processes or some form of external review from analogous data stakeholders.

Once data is verified and validated, the issue of how to communicate that a sample is “certified” arises. Particularly as the data assembly process begins and different types of data with varying levels of accuracy, uncertainty, and quality are interconnected, there is a need to ensure data traceability back to the point of origin. As a field data collection wraps up, stakeholders may consolidate data into a master datasheet, upload it to a shared database, or simply file it away in a physical or digital folder. However, the reality of field data assembly also includes a mess of data spread across email inboxes, various record management systems, individual phones and computers, and many other formal and informal locations. Participants noted that many of the challenges in data assembly include the need for improved interoperability, whether through the adoption of compatible semantic standards or tools for data conversions. As discussions regarding data sharing begin among data stakeholders, issues around privacy, trust, governance, consent management, and concerns regarding FAIR data must be considered. The downstream complexities involved in using soils data and handling metadata were further discussed in the “Feeding the Models” and “Metadata Management” groups, respectively.

SOIL LAB

Moderator: Aaron Ault, Open Ag Tech and Systems Center at Purdue University

A natural assumption in the soil lab segment was that it starts after the samples have been collected in the field.  However, the “soil lab chosen” event made it clear that several parts of the timeline happen prior to digging in the dirt.  The timeline sorted itself into roughly three categories: prior to the soil sample arriving at the lab, between arrival and testing, and reporting of results.

Prior to Lab

Some information from the “prior to lab” stage needs to “leapfrog” the lab: i.e., the lab doesn’t care about them and doesn’t want the privacy implications of holding them, but the eventual models need such information.  Examples include the sampling locations (ideally GPS), environmental conditions during sampling, sampling protocols (including how cores were taken or combined), farmer practices (cover cropping, etc.), and potentially farmer sentiments on the location via questionnaire. Clearly, samples need identifiers that pass to the lab and then through the lab to line up results with this leapfrog data later.  This sort of data transfer generally happens already, either a priori in anticipation of a box of samples arriving at the lab or directly in the box itself.  This has a serious design implication in that if labs are chosen later to report results directly to USDA, the lab may in fact need to collect and relay information that they would rather not mess with.  It also means that the creator of the initial ID for a sample should be well-defined in the overall process.

Several participants voiced concerns about the consistency of lab results in practice. Some of this may be due to inconsistencies in sampling methodology, including efforts prior to collection. Adoption of scientifically grounded standard operating procedures, such as those developed by the Soil Health Institute, is recommended to improve consistency and reliability of collected data. Labs generally adhere to national Quality Assurance/Quality Control (QAQC) protocols administered via several potential agencies. However, this sort of QAQC happens prior to sampling and so is more generalized than the quality of results for a single box of samples. It therefore does not seem to guarantee the absence of testing anomalies on any given day. To combat this, the preferred method voiced among participants was to include duplicate soil samples (i.e. split the same cores into multiple bags) in each set of samples. This has the disadvantage of added cost, but the advantage of minimal coordination: only the person sending the samples needs to participate in the protocol in order to know what level of trust the resulting data should have.

Variations in lab logistics can cause some headaches for a national-scale program: some labs have specific Standard Operating Procedures for samples, such as the minimum amount of soil and type of bag used, which can provide practical barriers to nationwide consistent protocols. In addition, labs themselves may support different test assays with different methods. The MODUS standard hosted by Ag Gateway provides an excellent suite of test codes for clear, specific test assays and this data should certainly travel along with the lab results themselves.  This only identifies the test performed; however, an additional layer of requirement likely needs to specify which type of tests are allowed in order to participate.  Clearly, a lab certification component will be necessary for a national scale sampling program.

At the Lab

Once the box of samples arrives at the lab, the lab will generally scan QR codes on bags or otherwise record the identifiers for samples. Each sample’s requested assays can be included in the box or transmitted ahead of time and associated with the sample ID. It is unclear what level of data about samples in transit will be relevant, but some questions do exist, such as time spent in transit, temperature in transit, time in storage before testing at the lab, etc. 

The lab may homogenize a sample during testing, and the method used and resulting soil properties (texture, particle size, moisture content, etc.) may be important to record.

Some kinds of assays are more advanced and uncommon than others.  A baseline suite of test assays should be defined for generally available, inexpensive tests, and value-add suites of tests can also be performed in certain cases as warranted. The phrase “super sites” was used to describe soil sampling sites which may consistently order more advanced tests. From a modeler’s perspective, this is important because it means there will be a large dataset with simpler data, and a smaller dataset with more detailed and advanced data.  It is also possible that new methods for testing may become relevant throughout the program’s life cycle, so a framework for adapting to changing test schemes should be developed, ideally with an eye to understanding the comparability of old procedures to new ones in order to maximize the size of usable datasets.

Reporting

In general, labs report results to the person who sent the sample (and paid for it).  Reporting in the MODUS standard should be required for any national scale program as it will ensure interoperability among data and a clear means of identification of lab test procedures. Existing reporting tends to be missing critical data about the actual tests that were performed to get the results, and they are generally haphazardly organized in non-standard CSV’s or spreadsheets.  Work is ongoing on an open source tool and code libraries (https://oats-center.github.io/modus)  to make it easier to transition between spreadsheet and the MODUS standard.  Should a MODUS-based interoperability come to fruition in the soil health industry, it will finally enable the community to build tools and services that can deliver value to large swaths of stakeholders, including farmers, landowners, researchers, etc.

There is as yet an unclear path from lab to model researcher.  Some participants may be interested only in feeding their data into an existing model for a carbon certification, while others may be more interested in enabling research into the models themselves.  Modelers would prefer a reasonably centralized repository of hosted data with clear privacy and use restrictions.  This introduces a single point of failure for any participants involved in the sample collection side, and could be a very onerous privacy burden on the host of the data.  Centralization is also often inherently less secure since it allows malicious actors to focus on a single platform.  It may be that a hybrid approach leveraging interoperability among a network of data sites could provide a reasonable best of both worlds.

To the extent that the program wants to assemble data beyond prescriptive, paid-for direct sampling, some consideration should be paid to how to encourage participation. The set of potential soil testing labs is a much smaller target than the full set of all landowners and farmers, and therefore may provide a better avenue to adoption. A lab could be set up to provide a copy of results directly into a data collection platform as an add-on feature for a sample, thereby enabling them to also provide awareness to their customers of the program. However, this will still need to solve the problem of the “leapfrog” data which the lab does not historically collect. 

If the person who sent the sample to the lab intends for the sample to go directly into a model such as COMET, there may also be an opportunity to streamline that process as well.

FEEDING THE MODEL

Moderator: Rob Trice, founding partner of The Mixing Bowl & Better Food Ventures

The primary purpose of the USDA model is to improve our understanding of management practice efficacy to sequester GHG by providing estimates as accurately as possible. The two most important things about the model are that 1) it possesses the ability to ingest comprehensible information through data structures and ontologies it can understand, and 2) it possesses the ability to be updated so that over time it can be even more accurate by collecting and connecting with other, new data.

We know that, through research and data analysis, we will learn more about things like farm-level practice implementation. I.e., what will the impact of management practices–like cover crop application– be on soil carbon sequestration? We also know that additional soil analysis data will be added to the model in the future.

We also know that USDA will start building its model based on COMET and DayCent. COMET is a greenhouse gas accounting tool that is used to estimate greenhouse gas emissions and carbon sequestration from agricultural production. DayCent is a biogeochemical process model that is used to simulate soil carbon and nitrogen dynamics, as well as greenhouse gas emissions. COMET uses DayCent as its underlying model to simulate entity-scale greenhouse gas emissions. This means that COMET relies on DayCent to provide estimates of greenhouse gas emissions from various agricultural activities, such as crop production, livestock production, and manure management. COMET also provides users with the ability to input their own farm-specific data, such as crop types, management practices, and soil conditions. This allows COMET to generate more accurate estimates of greenhouse gas emissions for individual farms.

The USDA model will leverage COMET and DayCent and will be able to ingest new data from the field, from labs, from scientific researchers, and from others’ models and databases.

Harmonizing Data Collection

To be effective, both the model, and those contributing data to it, need to have a common set of terms and data fields to feed the model. For instance, looking at the example of cover crops, we need common terms to describe what was planted (legume or non-legume?), when, where, and, additionally, when the cover crop was terminated.

Exact data structures and semantics need to be communicated to those capturing data to be used in the model.

Defining “Required” Versus “Desired” Data

There is a natural tension that exists between making the model functional through ease of data collection by focusing on only a minimal set of “required” data versus also capturing potentially important (“desired”) information for the future. The qualified data collectors who are gathering field or lab data need to know clearly what to capture.

As an example, in addition to soil organic matter or soil organic carbon levels, perhaps we may want to collect information for future modeling related to soil mineral, microbial, DNA, enzyme levels enabled by technologies like portable FT-IR spectroscopy. 

Meta Data Management for the Model

In addition to data structures and semantics, we recognized that there is important data that must be collected about the data inputted into the model. For instance, we need to define scales for data capture (meters or inches?), location, time, (tool? method?) of data captured.

Regarding model input, we need to identify a QA/QC process and some methodology needs to be determined to handle “missing data” from imputation mechanisms.

Regarding the output from the model, we need to make sure users know what version of the model was used to determine an output. 

While there is another USDA working group– the Model & Tools Group– that will be responsible for measuring the efficacy of the model, determining measurement methods and metrics to assess the performance of the model, we recognize that we need a way for “the model to feed the model.” The model is intended to be dynamic (not static) and improvements to it need to be identified and rolled into the model somehow.

A separate Miro “room” looked at meta data for the overall modeling initiative and we want to make sure that group considers security of the ML models and identification of adversarial AI that could occur through different model harmonization.

Inter-Model Harmonization

We are aware of other international and proprietary efforts to quantify agriculture GHG and we need a way to harmonize or interoperate with those other models to the degree possible. AgMip, an organization established in 2010 with the sole purpose of making agriculture models interoperable and intercomparable, might be someone to partner with in this regard.

The figure below very accurately represents many of the data input and management challenges we identified.

Building a Community of Users

A last important point not to be overlooked is that USDA needs to build a community of model users. Three kind of users need to be accounted for:

Data Collectors & Inputters need to be communicated with so they clearly understand what data to collect and how to properly input data. This would not only include qualified data collectors but soil lab technicians so they understand what and how to analyze data.

Other Modelers need to be communicated with so they can help to harmonize and interoperate models so we get the benefit of more data.

End Users who will use the output from the model will really need to be identified and included in the development of the model. We identified the following end users:

• Other modelers & scientific researchers who will want to leverage the model’s data for their own modeling.
• Certifiers & reporters will want to use the model for purposes ranging from carbon registries to the EPA reporting on US carbon levels to the UN.
• Technical advisors for farms and ranches (like NRCS) who are looking to promote optimal climate-smart agriculture practice implementation that is crop and locale-specific based on the latest science and models.

METADATA MANAGEMENT

Moderator: Drew Zabrocki, co-founder of Centricity by Semios, Advisor, OATS Center at Purdue University and International Fresh Produce Association.

Conversations on Metadata Management underscored the importance of collaboration, data management, and technology in inspiring model creation, insights, and policy to improve soil health practices and promote sustainable agriculture.

The following summary points were raised in our discussions:

• There is a need for collaboration between different organizations and stakeholders, especially industry. There are many systems and standards—working together will assure the best outcomes.
• The need for transparent and extensible frameworks to make data more accessible and comparable.
• There will be changes. We need to incorporate standards and protocols for managing change.
• The use of open-source software and technology can help in data interoperability and standardization.
• The involvement of public and private actors in advancing a solution to meet the needs of all stakeholders.
• The significance of community-driven science and participatory research.
• The potential of soil data measurement, farm management information systems, and mapping technologies to unlock the full potential of the supporting insights tools.
• The importance of data sovereignty and transparency for all stakeholders.

Our discussions were focused in the following overarching areas: 

Data Sovereignty

Effective data governance and security require careful consideration of several key factors. These include establishing clear authority levels, documenting data privacy and consent management, defining data rights and obligations for stakeholders, ensuring transparent processes for data sharing, determining ownership, promoting interoperability, automating reporting, and implementing certification frameworks. By implementing these measures, businesses can foster accountability, protect privacy, and inspire trust in their data management practices.

During the discussion, we also delved into important topics such as interoperability, data sovereignty, automated attestation, and the utilization of open-source tools such as the AGAPE certification framework. Additionally, there was a focus on permitting labs to share soil test results with NRCS. We explored some of the challenges and potential solutions in these areas (see References), emphasizing the importance of maintaining control, trust, and collaboration for enhanced management and innovation across various domains.

Correlation & Connecting Systems

Data, with linked documentation and semantic resources, adds valuable context and insights. It can be connected to on-farm data systems and tools, enabling aggregation of metadata at various levels. Engaging with diverse systems assists in research, auditability, and supports predictive and analytical modeling. In this pursuit, prioritizing published and well-documented APIs is crucial. The versatility of data extends to educational programs, rendering it a valuable resource for teaching and learning. In summary, data presents endless opportunities for developing new models, exploration, and innovation.

Creating Value through Sharing & Insights  

The agricultural sector holds immense potential in utilizing the available data for various applications like analysis, modeling, and education. Ensuring statistical relevance and correlation through data analysis becomes crucial, which may involve making subsets or derivatives of data accessible to the public. Leveraging existing farm management information systems like Agworld or FarmOS can significantly enhance data quality and reliability. These tools, integrated with accurate and diverse data sources, are invaluable for conducting research and generating obfuscated data for multifaceted purposes.

Throughout these discussions, the importance of implementing continuous improvement frameworks and fostering an interactive process that incorporates stakeholder participation became evident. These conversations underscored the need to embrace opportunities for learning and growth in order to continually evolve and advance.  

Event Storm Summary

From soil data measurement and modeling for near-term regulatory needs to AI and machine learning that may unlock new insights, the potential for value creation is vast. Transparent standards, community-driven solution design, and built-in data sovereignty are crucial for all stakeholders.

This comprehensive discussion delved into various key areas crucial for effective data management and collaboration. It placed particular emphasis on standardized units of measurement, capturing and addressing uncertainties, and implementing strategies for continuous improvement. The importance of relating environmental data, establishing robust data governance practices, and seamlessly connecting systems was also brought to the forefront. Additionally, the conversation underscored the potential for unlocking value through information sharing and insights, while highlighting the need for ongoing improvement and active stakeholder engagement. Ultimately, this discussion served as a reminder of the paramount importance of data control, trust, and collaboration in driving effective management and fostering innovation across various domains.

Identified Focus Areas and Ideas

The concluding session of the event used arrows to denote areas of the board where solutions should be focused, and red stickies to suggest ideas, projects, or paths forward in those areas.

IDEAS FOR FIELD DATA COLLECTION

Participants offered a set of proposed recommendations and existing methods to mitigate the potential of a data preparation boondoggle:

1. Need for improved field data collection systems: The company OurSci takes the approach of creating common “question set” libraries that use community-identified standard vocabularies design to help “pre-align” data inputs with their downstream intended use, as exemplified in their field data collection tools SurveyStack and SoilStack. [axilab user research]

2. Need for improved interoperability among data collection systems: There is a need to adopt common agricultural vocabularies, ontologies, and data standards. Though there will always be stylistic differences among systems, participants note the need for community consensus on how we should be structuring farm data sharing through ongoing efforts to resolve this issue.  AgGateway, a consortium of agricultural and technology industry partners, has been developing the ADAPT Framework that consists of an Agricultural Application Data Model, and API, and a suite of data conversion plugins, all designed to meet their set of proposed industry standards to “simplify [data] communication between growers, their machines, and their partners.” The Purdue OATS Center takes yet another approach through [OADA + AGAPEcert].

3. Need for improved participatory data and protocol stewardship process: includes the collection of background data to determine baseline constraints and land status; Need to include more stakeholders in the protocol design process. In a collaborative effort among NRCS, Purdue Agricultural Informatics Lab, OurSci, FarmOS and OpenTEAM needs assessment.

4. Need for open soil data collection protocols: Through this entire process, participants note for the SOP to be a living but versioned document.

IDEAS FOR SOIL LAB

A few focus areas arose from the chaos near the end of the day.  The quality assurance process was highlighted as a focus area, with ideas for tackling that as certifications which can be passed along from a lab, and passed along from a set of samples with quality control duplicates which could provide a level of trust with the lab results as they move on through the models. 

The largest focus area was around institutionalizing the use of the MODUS standard for soil sampling lab results.  An idea for tackling this was to make tools that make it easier for people to use MODUS than not.  Building the MODUS community, participating in the Ag Gateway standards committee, adding MODUS requirements for program participation, and building open source tools and libraries are all in the mix.  Though it was in a different area of the board, there was a suggestion to build a database of supported bulk density methods and soil carbon methods used by specific labs which is an ongoing critical effort around the MODUS standard enabling the existing open source tooling to work with many different labs’ reporting.

Finally, in order to kick start the process, the suggestion was made at the “reporting to a centralized data repository” level to create an open source, redeployable implementation of a potential centralized platform.  This way, the API’s and schemas can be initialized and iterated across parallel proof-of-concept pipelines, while maximizing the likelihood that an eventual centralized platform (or network of platforms) will easily interoperate with smaller-scale early developments and industry platforms.

IDEAS FOR FEEDING THE MODELS

We identified four summary actions to be taken:

1. Define what data needs to be collected by data collectors or inputters and define the common data structures, ontologies, and associated metadata for model data. This includes defining a minimum data set necessary to start the model, additional data you might want to collect now for analysis, and also data you might want to collect in the future.
2. Develop a QA/QC process for data imputed into the model and develop policies for handling “missing data.”
3. Develop a process for harmonization or interoperability between this model and other models.
4. Develop “user communities” to make sure their needs are captured in the development of the model. Three kinds of users were identified:
   1) Data collectors & inputters to feed the model,
   2) Other researchers & modelers who may want to collaborate to refine the model, and
   3) End users who will utilize the output from the model.

IDEAS FOR METADATA MANAGEMENT

We identified the following actions to be taken:

1. Establish a comprehensive data dictionary detailing variables and units. Assistance for this project is available through the IRA-GHG initiative. For further details, please visit AgGateway’s website at www.aggateway.org.
2. Create a hierarchical data measurement protocol that’s been expertly validated. The aim is to seek a flexible solution that’s neither overly prescriptive nor restrictive.
3. Develop comprehensive guidance on metadata governance, security, and privacy by engaging all relevant stakeholders, including IT, legal, and technical experts. It is crucial to fully comprehend the intricacies of data privacy, consent management, and the rights and responsibilities of various parties involved.
4. Explore and outline data sharing protocols, data ownership, and the challenge of maintaining interoperability while upholding data sovereignty. Seek out industry best practices and leverage open-source tools for automated reporting, utilizing the OODA LOOP framework. For validation of claims without compromising sensitive information, consider the implementation of the AGAPECert automated certification framework.
5. Identify and resolve the need to manage uncertainty through the capture of temporal-geolocation information. Additionally, there is a requirement to record and report the measurement of uncertainty in the data.  
6. Determine publicly available data related to soil, which can be connected with other data available from stakeholders likely available in farm management systems (FMS). Develop methods for how the soil data can be reliably associated with on-farm metadata such as fields and boundaries.  Map use cases for how the data is aggregated at different levels, including farm, regional, and national, to assist in frameworks and guidance documents.

A Suggested Path Forward

Despite the number of branches we found on this complex tree, we certainly identified some low-hanging fruit ripe for the picking. The issues at hand are broad and solutions will inevitably affect a diverse group of differing interests (government, researchers, modelers, farmers, ag service professionals, carbon markets, etc.).  The picture is therefore like a wide panorama, and while a panorama can be beautiful, its beauty can be distracting and even paralyzing: the bigger the picture the longer you stare at it. Panoramas are best built as a series of interconnecting pieces: each individual piece seems much more tractable than the whole, so there is much less time needed for admiring the problem’s complexity. If each piece is built in isolation, the picture will never come together in the end, but if one looks only to “the big picture,” they can never get any piece of it actually done.

The key to success here is therefore both parallelism (building pieces of the picture) and end-to-end design (build a crude “total picture” to inform the design of the pieces).  The connection points between the pieces represent data interfaces between players and will become the lingua franca that glues it all together.  One cannot successfully design such things without the necessary feedback loop of hypothesis and verification: i.e., we think this is mostly the right model, now let’s try it as a proof of concept and see where we’re wrong so we can modify the model and try again.

To that end, the lowest hanging fruit that came out of this event was the idea of focusing on a full end-to-end, narrow use case, and building a toolset in the community that enables coordinated development across more use cases in parallel.

The narrow use case proposed was dubbed “Corn-to-Comet”: collect some actual soil samples and specific practice data (cover crops?) on a few actual fields that produce corn, get that data to the COMET model, get the COMET outputs back to the stakeholders, and end with an overall dataset in a form that could be available for other models and model researchers, all with appropriate consideration of reasonable privacy and use rights.  The actual crop/fields chosen for this pipeline should reflect whoever is willing to participate, so the crop may or may not be “corn” in the end.

Backstopping this effort would be the open source development of a deployable “USDA platform” concept. The final outcome of the overall picture will involve reporting soil samples and practice data to a USDA-maintained system which can make such data available to model researchers. With this “redeployable data platform,” individual developers or projects can stand up their own instance of what an eventual USDA platform would look like using consistent schemas and build their own pieces of the puzzle to interface with their instance of the platform.  Versions of the schemas and platform code will then serve as an incremental integration test between the various pieces, and its open source nature provides the feedback channel necessary for the big picture to come together.  The “Corn-to-Comet” pipeline would use this proof-of-concept tool, and as additional early pipelines are begun from other crops to other models they have some help and examples to get started.

Finally, to keep the valuable insights of the broad tent of community that participated in this event, a future event should be planned which gives participants a chance to talk through design issues with a parallel “hackathon” or “collabathon” among developers to build out real parts of the corn-to-comet pipeline as well as make some proof-of-concept new tools for other pipelines.

Appendix: References, Keyword Clusters & Tags

We made an effort to capture references, keyword clusters and tags related to the event storm activity. Many participants highlighted collaborations already underway that should be evaluated.

AGAPECert Certification Framework: The AGAPECert framework is an automated certification system that aims to validate claims, exchange derivatives, and link related data across domains without revealing private data. This could be a useful solution for ensuring trust and transparency in various domains where certification or complex security policies are required.

AgGateway: AgGateway is a non-profit industry consortium focused on agricultural data interoperability and standards. They manage the MODUS lab test data standard, which is widely used for reporting soil test results.

Agworld: The Agworld ecosystem allows you to collect data at every level of the operation and share this data with everyone that matters. Agworld operates on over one hundred million acres across a broad range of commodities and environments. APIs and integrations with leading technology providers enable all stakeholders to work together on the same set of (field tested) data.

Collaboration and Innovation: It’s important to provide an opportunity for public and private actors to collaborate and find innovative solutions that promote better science, new innovations, and sustainable agricultural practices.

Community Engagement: The team emphasized the importance of community-driven design, research, and engagement.

Data Infrastructure and Management: The IRA-GHG Quantification Program aims to harmonize data for scientific standards and interoperability. Coordinating feedback, developing technical specifications, and creating infrastructure for data management are key aspects of this program.

Data Interoperability & Sovereignty: Standardizing protocols and developing open-source software can help improve data sharing and integration across different stakeholders.  The Trellis Framework from Purdue University’s OATS (Open Ag Technology & Systems) Center was referred to as a resource for practical MODUS tools and the OADA and AGAPE toolsets for sovereign interoperability at scale.

Farm Foundation: Farm Foundation is a non-partisan, non-profit dedicated to accelerating people and ideas in agriculture. Their mission is to build trust and understanding at the intersections of agriculture and society by creating multi-stakeholder collaborations. Their strategic priority areas are digital agriculture, market development and access, sustainability, and farmer health.

OpenTEAM: OpenTEAM is an open technology ecosystem for agricultural management that aims to facilitate data interoperability and community-driven science. It brings together stakeholders from various sectors to collaborate on improving data systems in agriculture.

SoilBeat and EarthOptics: SoilBeat and EarthOptics are companies that leverage AI, machine learning, and real-time data mapping to provide insights into soil health. Their technologies help agronomists and farmers make informed decisions about nutrient management and regenerative practices.

Soil Data Management: The National Soil Survey Center and USDA-NRCS play a crucial role in collecting, processing, and delivering authoritative soil data. Their work supports conservation planning and land management efforts.

Soil Health Tech Stack: The “Soil Health Tech Stack” is a term coined by Seana Day in an article that outlines the challenges she sees based on, among other things, her work co-authoring the USFRA Transformative Investment report about how technology and finance could scale climate smart, soil-centric agriculture practices as well as on information gathered during the Farm Foundation Regenerative Ranching Data Round Up. The “Fixing the Soil Health Tech Stack” activities will build upon those efforts and others. As such, the event will leverage pasture/rangeland data but with the goal of extending solutions to all soil-based agriculture production ecosystems.

Tags

#data #comparability #defining

• It is important to agree on data standards and make it someone’s primary job to ensure data comparability
•  Developers play a crucial role in defining data models and schemas
•  Define data rights and obligations for different stakeholders
•  Determine how data will be shared and who owns the data

#design #database #structure

•  Design a flexible database that is not too prescriptive/restrictive
•  Design the database structure effectively

#measurements #define #accuracy

•  Consider using ISO19156 framework for observations and measurements
•  Explore ways to upscale measurements
•  Define units of measurement for reporting and storage
•  Define measurements of uncertainty and accuracy for field measurements

#protocols #data #expert

• Data lineage on lab results and field data should be published as part of versioned protocols
• Publish metadata standards as protocols
• Develop a data measurement protocol hierarchy vetted by experts
• End-users of data may require specific protocols for sampling

#documented #data

•  QA/QC standards should be documented to ensure data quality
•  Documentation should be linked to other data products for easy reference
•  Data collection purpose should be clearly documented
•  Data sample design should be documented to ensure representativeness
•  Data schemas should support inclusion of existing public datasets
•  Provide detailed documents to help users navigate the data

#changes #year #data

•  Implement change control for data schema/model changes
•  Handle fiscal year/periodic changes in data
•  Plan for iterative improvement process in February
•  Develop a data variable dictionary for easy reference

#standards

•  Consider ISO standards in database construction
•  Leverage the good aspects of ISO and other standards

#dimensions #geography #capturing

•  Standardize geography and time dimensions for better data integration
•  Consider capturing uncertainty with temporal-geolocation information

#methods #methodologies #computation

•  Methods should be documented for each observation
•  Document computation methodologies

#agreements #sharing #governance

•  Metadata governance, security, compliance requirements, search, and collaboration tags should be defined
•  Policy changes may be needed for data sharing within governance/consent agreements
•  Achieve interoperability while maintaining data sovereignty
•  Contractual agreements may be necessary for data sharing

#claims #automated #certification

•  Facilitate automated reporting of practices
•  Implement an automated certification framework to validate claims without revealing private data

This post-event report was contributed by Ankita Raturi, assistant professor of agriculture and biological engineering at the Agricultural Informatics Lab & Open Ag Tech and Systems Center Purdue University; Rob Trice, founder of The Mixing Bowl and Better Food Ventures; and Drew Zabrocki, co-founder of Centricity by Semios, advisor, OATS Center at Purdue University and International Fresh Produce Association.

Views expressed do not necessarily reflect the opinions of all participating organizations.

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On October 16-19^th, Myers attended the International Dairy Federation (IDF) World Dairy Summit in Chicago, Illinois, to hear how global dairy leaders are approaching some of the major issues impacting the dairy sector.

It is not often that the global dairy community gathers to discuss high-level issues that are specific to the dairy industry or agriculture in general. Over the last seven years, I have been lucky to attend numerous conferences that discuss research relevant to specific issues in the dairy industry, whether this be the adoption of a new technology or the modification of a testing procedure. However, I noticed absent from these discussions were relevant policy conversations or how the adoption of new technologies could enhance farm income. More so, there was little discussed as to what is happening in the global dairy sector and how global innovations and trends might impact dairy farmers and processors in the United States. I just assumed these conversations didn’t happen at conferences.

I learned that is not the case at the International Dairy Federation (IDF) World Dairy Summit, which I attended a few weeks ago in Chicago, Illinois. The meeting itself rotates to different countries each year, and it has been over 30 years since the United States hosted the World Dairy Summit. As someone who has recently shifted away from the dairy foods processing sector and into dairy policy and economics, I was excited to attend a conference where there appeared to be such a focus on dairy markets and policy. The World Dairy Summit itself hosted 1,200 participants from around the world to discuss the theme of the conference: “Boundless Potential, Endless Opportunities.”

High-level plenary sessions were held with global dairy industry leaders coupled with topic-specific concurrent sessions. Plenary sessions focused broadly on issues the global dairy industry is facing. However, there was a strong focus on sustainability and how the dairy industry can work toward a greener future. To contribute to this dialogue, global dairy industry leaders discussed how their companies and governments are working to achieve the global dairy industry’s goal of being carbon neutral by 2050. Furthermore, dairy industry leaders discussed how technology adoption and policies can intersect to fill the demand for dairy solids from a growing population. Importantly, leaders also discussed how this intersectionality can work to achieve a carbon-free dairy industry, without curtailing production. In the concurrent sessions, dairy industry leaders widely discussed how trade can be a tool to mutually benefit the global dairy industry, and how changing global consumer demand stands to impact U.S. dairy farmers.

Making New Connections

Although the plenary and concurrent sessions offered valuable information and insight from global dairy leaders, one of the most remarkable aspects of attending the IDF World Dairy Summit was networking with like-minded dairy professionals from around the United States and the globe. These conversations, whether in concurrent sessions or in one-on-one hallway conversations, were incredibly important to gaining valuable insights into dairy markets, policy, and future career opportunities. The connections I have made with farmers, members of the scientific community, and industry groups at IDF were numerous and have proven helpful in several instances since the conference. I hope to continue to cultivate these networks as I continue down the very narrow, but increasingly relevant, field of dairy economics.

Besides a plethora of new connections, friends, and colleagues, I returned to Arkansas with one other memento from the World Dairy Summit, a first-place trophy from the dairy marketing and economics poster session. Participants were invited to submit original research posters to one of seven major research categories. Those who placed first in the category returned home with a glass plaque with the IDF logo etched into it. The dairy markets and economics plaque now sits proudly on a shared bookshelf in our department’s Ph.D. office. In a research space as small as dairy markets and economics, receiving first place signified to me that our research had valid and broad implications for the entire dairy industry. Personally, I feel as though this award signifies I am making headway as an aspiring dairy economist.

Overall, the IDF annual meeting exceeded my expectations and offered an incredible experience of networking with like-minded dairy enthusiasts while thinking of new ideas on how my research can impact dairy farmers here in the U.S. The IDF meeting has truly expanded my personal network of global dairy industry stakeholders and fueled my commitment to contributing meaningfully to the dynamic and ever-evolving world of dairy.

I attended this conference as both a graduate student at the University of Arkansas and as a Farm Foundation Agricultural Scholar, and as such my attendance at this meeting would not have been possible without the commitment of Farm Foundation. As I reflect on this experience, I am incredibly grateful for Farm Foundation for affording me this incredible opportunity.

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Executive Summary

On September 13, 2023, the Farm Foundation and the U.S. Department of Agriculture hosted a one-day virtual conference, U.S. Farm Households’ Social and Economic Needs and the Future of U.S. Agriculture. The event brought together researchers, practitioners, and policymakers to discuss new interdisciplinary research at the intersection of farm household needs and the farm business and to exchange ideas to better support farm households and U.S. agriculture.

The presentations and discussions highlighted ways that farm household well-being directly influences farm business viability and decision-making. Participants noted that while household factors have not always been a focus of agricultural policy, they require consideration to support family farm production and encourage new farm entrants. Some presentations addressed particular social supports, including access to health insurance, childcare, and financial services that intersect with the goals of strengthening rural economies and communities more generally. Other themes that emerged included the need for data on both farm households and their businesses to study these linkages and the role of non-financial considerations in farm business decision-making. As the structure of agriculture has changed, the needs of farm households have grown increasingly diverse. However, the capacity of rural communities to provide services, such as health care and mental health services, childcare, and other social and economic supports, has often lagged. This conference brought together interested stakeholders to begin a conversation on a more holistic means of supporting U.S. agricultural production by considering household-level support. All authors presenting original research were invited to prepare manuscripts for a special issue of Agriculture and Human Values (a Springer journal) related to the conference theme, to be published in late 2024. 

Conference Overview

On September 13, 2023, the Farm Foundation and the U.S. Department of Agriculture hosted a one-day virtual conference focused on U.S. farm households’ socioeconomic needs. The event brought together a wide range of social science researchers, practitioners, and policymakers to discuss new research at the intersection of farm household needs and the farm business and to exchange ideas to better support farm households and U.S. agriculture. The day’s agenda, including research paper authors and their affiliations, can be found in Appendix A below.

The conference began with opening remarks from USDA Deputy Secretary Torres Small, highlighting the important but less studied need to support farm households in ways that go beyond programs focused on agricultural production and the farm business. A panel discussion among farmers and farm service providers offered concrete perspectives on how initiatives like strengthening rural communities, promoting mental health, access to childcare and healthcare support farm viability and recruiting new and diverse farmers.

The themes covered in the opening session were revisited throughout the day during research presentations and informal topical discussions among participants. All of the presentations spoke to the conference theme of linkages between farm households’ well-being and farm business success, but a presentation by Douglas Jackson-Smith was perhaps the most direct. He showed evidence that household shocks, including health changes, divorce, and death, were more predictive of farm survival and exit during the pandemic than farm-level financial shocks. A presentation by Renee Wiatt and Maria Marshall echoed these findings by showing that socioemotional wealth influences farm succession decisions in addition to farm financial health.

“Household shocks, including health changes, divorce, and death, were more predictive of farm survival and exit during the pandemic than farm-level financial shocks.”

Many presentations highlighted the role of communities and the rural economy in supporting farm households and businesses – a theme that members of the opening panel returned to repeatedly in their remarks. Analena Bruce discussed the importance of understanding the broader systems that farmers operate in to understand agricultural production and whether farming is viable. Farm viability depends on factors other than income generation, including mental and physical health. Bruce mentioned that low levels of farm income cause farm households to rely on off-farm income to meet health insurance and economic needs. This topic was addressed directly by Allie Bauman’s work showing that the expansion of Medicaid eligibility allowed beginning farmers to work less off-farm and more on-farm, which may increase farm survival rates. Florence Becot conducted a survey of farm households with children and showed that childcare costs and availability are challenges for 74 percent of farm households. While rural childcare is a community-wide issue, farm households indicated direct tradeoffs between caring for children and investing time and money in their farm businesses, suggesting the interplay between strong social supports for rural communities and the ability to make a living farming.

Another theme of the conference was the diversity of farm households in terms of characteristics, farm production, income, and needs. Mary Ahearn’s presentation outlined ways in which the profession has pursued better data collection on both the farm household and farm business as an essential input for assessing farm household economic needs and the linkages with farm business outcomes and agricultural policy. As an example of improved data, she talked about how women operators were not accounted for in official data, which once remedied reflected their large contributions to agricultural production. Two presentations made use of the contemporary USDA dataset Ahearn discussed covering both household and farm-level information. Katherine Lim used the Agricultural and Resource Management Survey (ARMS) to study older farm households’ income sources and retirement savings, finding that many older farm households rely heavily on social security income and private pensions, and that the majority have a private retirement account. Farm operators of color; however, have lower levels of retirement savings and lower levels of income overall. Tia McDonald combined ARMS with bank branch location data to show that being geographically closer to a physical bank branch was associated with increases in savings behavior among farm households again highlighting the intersection of strong rural communities with farm household well-being and farm operation financial performance.

This conference brought together stakeholders to study and address challenges faced by farm households. The throughline theme from the conference is that household needs directly affect farm business viability and decision-making. These linkages have not always been evident to researchers and therefore have not been a focus in the development and analysis of agricultural policy. Household social and economic needs intersect with non-agricultural policy and rural development more generally; however, farm households may face unique challenges associated with their status as agricultural producers. To better understand the challenges faced by the diverse population of farms and farm households, it would be beneficial to continue and expand collection of detailed qualitative and quantitative data.

Katherine Lim is a USDA ERS Agricultural Research Economist.

Appendix A: Conference Agenda

Wednesday, September 13, 2023

9:00 AM – 10:00 AM: Welcome Address & Panel Discussion

Welcome Address: 9:00 – 9:10 a.m.

Shoshanah Inwood, The Ohio State University

USDA Deputy Secretary of Agriculture Xochitl Torres Small

Moderated by:

Martha King, Farm Foundation 

Panel Discussion: 9:10 – 10:00 a.m.

Moderated by:

Matt Russell, USDA Farm Service Agency 

Panel Participants:

Dr. Gabrielle Roesch-McNally, American Farmland Trust

Adam Alson, Alson Farms and Appleseed Childhood Education

Mary Saunders Bulan, Rural Advancement Foundation International – USA

Graham Unangst-Rufenacht, Rural Vermont 

10:00 AM – 11:30 AM: Session One, Farm Families’ Persistence and Well Being

Farm Operator Household Well-Being Measurement And Analysis: The Past 50 Years And Future Directions. Mary Clare Ahearn, National Center for Agricultural Policy, and Ashok Mishra, University of Arizona.  

Factors Associated with Farm Survival and Exit During the COVID-19 Pandemic in Ohio. Douglas Jackson-Smith, Ohio State University, Tiffany Woods, Shoshannah Inwood, Julia Linder, and Lauren Gallander 

Discussion Moderator: Becca Jablonski, Colorado State University 

Break & Networking Lounge

Enjoy your lunch while making new connections, collaborations, and digging deeper into the issues with subject matter experts. Discussion tables will convene conference participants with government representatives, farmers, technical service providers, and researchers on specific social and economic needs and common ground issues.

Participants will be automatically assigned to a specific breakout room table topic. You can leave the room at any time and rejoin the lobby area to switch to a different table topic. 

12:30 PM – 2:00 PM: Session Two, Farm Viability in the Face of Social and Economic Needs

“A Farm is Viable If It Can Keep Its Head Above Water”; Farm Viability, Persistence, And The Sustainability Of Agriculture in New England. Analena Bruce (University of New Hampshire), Cindy Zheng, and Elise Neideker

The Impact of Expanded Health Care Coverage On U.S. Beginning Farmers And Ranchers. Allie Bauman (Colorado State University), and Becca Jablonski

Farm Families’ Challenges Meeting Their Social And Economic Needs And The Consequences On the Farm Business:  The Example of Childcare. Florence Becot (National Farm Medicine Center) and Shoshanah Inwood (Ohio State University) 

Discussion Moderator: Jessica Crowe, USDA-ERS

2:05 PM – 3:35 PM: Session Three, Overcoming Barriers to Meeting Farm Household and Farm Business Goals

Farm Households and Retirement:  Incomes Sources and Savings Behavior. Katherine Lim (USDA Economic Research Service) and Ashley Spalding

“Rich And Ready To Go Or Stay And Grow”?  A Succession Preparedness Study Of U.S. Farmers in the North Central Region. Authors: Renee Wiatt (Purdue University) and Maria I. Marshall

Distance To Commercial Banks And Farm Household Use of Financial Services. Tia McDonald (USDA, Economic Research Service) and Noah Miller 

Discussion Moderator:  Shoshanah Inwood, The Ohio State University 

3:35 PM – 4:00 PM, Closing Remarks

Panel of organizers reflecting on the conference, discussion questions, and concluding thoughts.

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