Remarkable advances in food and agricultural sciences over the past century demonstrate how public support for research can enable talented U.S. scientists to contribute to improving food and agriculture (NRC, 2014b). Much has been accomplished, yet much remains to be done. Food and agricultural research will need to respond to and address some of the looming contingencies that threaten the resiliency of our food system. The United States is facing resource scarcities in some regions (such as water shortages in the High Plains), increased variability in weather conditions, and other rapid transformations in the agricultural sector that may be difficult to reverse. For some crops (such as soybeans), it is no longer possible to continue increasing inputs to maximize yields or maintain nutritional value without sacrificing other resources (such as the contamination and depletion of water and soil). In animal agriculture, imported animals and animal products endanger our national herds and flocks through the potential introduction of diseases that would decimate our resources (such as avian influenza and foot-and-mouth disease). Further innovations in management are needed to reduce waste and greenhouse gas emissions per animal. Food loss and waste remains at an estimated 30-40 percent, with key resources lost primarily at the retail and consumer stages (Buzby et al., 2014). Therefore, there is a need to find new methods, processes, and systems to better handle and preserve our food supply and to optimize and better utilize existing ones. Diversifying our approaches will be key to strengthening and improving the resiliency of our food supply.
In the past decade, the United States has lost its status as the top global performer of public agricultural research and development (R&D) to China (Clancy et al., 2016). Unless the United States reverses this trend and invests, the most promising innovations to enhance productivity and expand the food supply are likely to come from other countries, and the United States will fall behind other countries in terms of agricultural growth. There is an urgent need to facilitate the convergence of disciplines and science breakthroughs to address the “wicked” problems1 facing U.S. food and agriculture. Tackling these challenges will require a leveraging of capabilities across the scientific and technological enterprise. In addition, talent from allied disciplines, such as behavioral and economic sciences, will be indispensable to help solve these problems. In some cases, new tools (e.g., CRISPR) are available, but knowledge is still lacking as to how to effectively deploy those tools (e.g., in developing more resilient crops and better food quality and nutritional characteristics) and how to effectively gain producer and consumer acceptance. In other cases, it appears that there are promising opportunities in allied fields such as data science and sensors, but it remains unclear how researchers from these disparate disciplines will be enticed to collaborate on research programs to provide solutions that benefit food and agriculture. For instance, data will be essential for accurate predictions or assessments, and the opportunities appear endless in how big data and analytics can be used to increase efficiencies across the food and agricultural spectrum (e.g., to optimize breeding and improve food handling and distribution).
Food and agricultural research will play a critical role in meeting the food needs in the United States and elsewhere in a sustainable manner in the upcoming decade. Now is the time to develop a strategy that would harness emerging scientific advances to transform agricultural systems for greater efficiency, resiliency, and sustainability. Given the generational time from bench to field, investments are needed today to provide future benefits. Much can be accomplished in 10 years.
This report proposes a strategic path forward by first examining the solutions to problems through the concept of convergence and then by providing recommendations for carrying out such a strategy through 2030. For the United States to maintain its global leadership in food and agricultural
1 A “wicked” problem is an intractable problem with many interdependent factors that make it difficult to define and solve (Rittel and Webber, 1973; Crowley and Head, 2017). The term “wicked” is used not to indicate that a problem is ethically deplorable, but it instead refers to the challenging nature of the problem. Wicked problems are too complex to be solved using conventional linear approaches, and instead require rationale systematic processes for solutions. The concept was first introduced by Rittel and Webber (1973) to address social concerns and has since been widely applied to address problems with a social component such as environmental degradation and climate change.
research, it will be critical to invest both public and private resources to achieve scientific breakthroughs and to develop the critical scientific workforce that can address the multifaceted challenges. A better understanding of the food system itself can help better manage the overall system and its impacts.
The food system is vast and complex, making it challenging to comprehensively address all of the issues included in food production. In the past, it has been more common to examine these problems in a defined space or discipline for reasons related to practicality and greater ease of management, and that approach has been effective at addressing distinct issues that require specific knowledge in a domain. However, the so-called wicked problems of the future will require a radically different approach to understand the issues and uncover solutions that can only be found when explored beyond the traditional boundaries of food and agricultural disciplines.
Convergence is described as
an approach to problem solving that cuts across disciplinary boundaries [and] integrates knowledge, tools, and ways of thinking from life and health sciences, physical, mathematical, and computational sciences, engineering disciplines, and beyond to form a comprehensive synthetic framework for tackling scientific and societal challenges that exist at the interfaces of multiple fields. (NRC, 2014a; p. 1)
The National Science Foundation (NSF) has identified convergence research as one of the 10 big ideas for future investments (NSF, 2018). Food and agricultural research would greatly benefit from incorporating convergent approaches, as convergence merges diverse areas of expertise to stimulate innovation ranging from basic science discoveries to translational scientific applications (NRC, 2014a).
The next decade will be a critical juncture for food and agricultural research. For instance, the emergence of a digital world has given rise to the ability to collect, share, and analyze information much more easily and readily than in the past. It will be important to harness the opportunities that data have to offer in order to integrate and harmonize data so that they are usable and accessible. Boxes 9-1 and 9-2 provide examples of specific problems that will require convergence to address the various issues within the broader system.
3.1 Major Goals
To achieve the major goals of efficiency, resiliency, and sustainability, improvements are needed to address the most challenging issues across the food system. The key research challenges identified by the committee include (1) increasing nutrient use efficiency in crop production systems, (2) reducing soil loss and degradation, (3) mobilizing genetic diversity for crop improvement, (4) optimizing water use in agriculture, (5) improving food animal genetics, (6) developing precision livestock production systems, (7) early and rapid detection and prevention of plant and animal diseases, (8) early and rapid detection of foodborne pathogens, and (9) reducing food loss and waste throughout the supply chain.
In addressing these challenges, the committee identified important research directions by disciplines or categories that encompass the overarching and interrelated goals of efficiency, resiliency, and sustainability. The recommended research directions in the preceding chapters are important opportunities because of new scientific developments that make them possible in the near term.
3.2 Science Breakthroughs and Recommendations
Solving the most vexing problems in the next decade will require a strategy that promotes convergent problem-solving approaches and scientific and technological breakthroughs that span across disciplines. The previous chapters identified challenges and opportunities by research disciplines and recommended specific research directions in those fields. Five
critical breakthrough opportunities emerged in the study that the committee found to be applicable across many different disciplines. Some of these are in the early stages of development, and others are on the cusp for widespread application to food and agriculture. The five areas identified as the most promising science breakthroughs for food and agricultural research are intended to facilitate the recommended research directions and serve the overarching goals of efficiency, resiliency, and sustainability. The recommendations that follow will require a shift in how the research community approaches its work, and initiatives for each of the breakthroughs will require robust support.
Transdisciplinary Research and Systems Approach
Breakthrough 1: A systems approach to understand the nature of interactions among the different elements of the food and agricultural system can be leveraged to increase overall system efficiency, resilience, and sustainability. Progress in meeting major goals is only able to occur when the scientific community begins to more methodically integrate science, technology, human behavior, economics, and policy into biophysical and empirical models. For example, there is the need to integrate the rate and determinants of adopting new technologies, practices, products, and processing innovations into food and agricultural system models. This approach is required to properly quantify the shifts in resource use, market effects, and response (including the effects of scale), as well as to determine benefits that
are achievable from the scientific and technological breakthroughs (Khanna and Zilberman, 2017; Perry et al., 2017; Taylor and Zilberman, 2017). Considerations of these system interactions is critical for finding holistic solutions to the food and agricultural challenges that threaten our security and competitiveness.
Recommendation 1: Transdisciplinary science and systems approaches should be prioritized to solve agriculture’s most vexing problems. Solving the most challenging problems in agriculture will require convergence and systems thinking to address the issues; in the absence of both, enduring solutions may not be achievable. Transdisciplinary problem-based collaboration (team science) will need to be facilitated because for some, it is difficult to professionally gravitate to scientific fields outside of their expertise. Such transitions will require learning to work in transdisciplinary teams. Enticing and enabling researchers from disparate disciplines to work effectively together on food and agricultural issues will require incentives in support of the collaboration. The use of convergent approaches will also facilitate new collaborations that may not have occurred when approached by researchers operating in disciplines in separate silos. Transdisciplinary problem-based collaborations will enable engagement of a new or diverse set of stakeholders and partners and benefit the food and agriculture sector (NRC, 2014a). Leadership is key to making team science successful, as scientific directors need a unique set of skills that includes openness to different perspectives, the ability to conceptualize the big picture, and perhaps most importantly, a talent for uniting people around a common mission. These qualities are not always natural for scientists, so providing professional development opportunities to foster leadership in the transdisciplinary model is critical.
There are many examples of programs that already require transdisciplinary work: for example, grants provided by NSF’s Innovations at the Nexus of Food, Energy and Water Systems (INFEWS) and the request for proposals outlined in the 2018 Sustainable Agricultural Systems competitive grants program administered through the U.S. Department of Agriculture’s Agricultural and Food Research Initiative (USDA-AFRI). The NSF INFEWS and most recent USDA grants on Sustainable Agricultural Systems have relatively larger budgets that can support convergent team science. However, many of the standard grants requiring “transdisciplinary” approaches do not provide enough funding needed to support team science so incentives for transdisciplinary science are still lacking. For convergence to truly be productive, financial incentives are needed to encourage grant applicants to step outside of their comfort zones and to establish deep connections among subject matter experts from a variety of arenas.
Making the food system more sustainable and resilient can only be achieved through a better understanding of the system and its function. This is because the elements of the food system are highly interconnected,
contain many complicated feedback loops, and are spatially and temporally heterogeneous. The biophysical elements of the food system are also tightly coupled with natural ecosystems, the built environment, and with human behaviors. Despite the fact that the food system will be inherently indeterminate at large scales, there are likely to be several critical nodes where a better understanding of the linkages would lead to significant improvement in overall system efficiency. The research community needs to come together to better define the food system, determine the barriers to successful development of integrated systems models of the food system, and identify approaches needed to overcome those barriers. These would need to be differentiated from other drivers of inefficiency, such as ineffective policies or undervaluation of natural resources. Such systems incorporate spatial and dynamic complexities and allow for synthesis of model outcomes and evaluation of trade-offs to alternative model and policy specifications (IOM and NRC, 2015). This greater understanding at the systems level can be translated into systems models to direct future research needs, or to determine which measurements are required to lower uncertainty in model parameters or formulations (e.g., feedback loops), or to identify policy interventions that could have the greatest overall system benefits. Given the complexity of the food system, it is desirable to conduct a decadal survey of modeling tools and databases to identify where progress has been made and where the greatest uncertainties remain.
A multidimensional systems approach will be essential for addressing policy and regulation. A systems approach can be used to consider the design and assess the effects of proposed agricultural policies and incentives to influence human behaviors that can support the desired systems-level sustainability outcomes (such as eliminating groundwater mining or mitigating nutrient loading to receiving streams). A systems approach will help to avoid unanticipated negative consequences to the environment or to humans from interventions in the food system. A systems approach will likely require a paradigm shift at all levels that encourages systems-based thinking and convergent approaches to problem solving.
Encouraging convergent research and improving our systems-level understanding of the food system will require changes in the way research is funded. NSF, USDA, the U.S. Department of Energy (DOE), and the U.S. Agency for International Development (USAID) are examples of four federal agencies with areas relevant to food and agriculture. There are already some examples of joint funding calls (e.g., NSF/USDA INFEWS) and requests for “convergence” research (e.g., 2018 USDA-AFRI grants on Sustainable Agricultural Systems and USDA/DOE/NASA-ROSES [National Aeronautics and Space Administration, Research Opportunities in Space and Earth Sciences] grants). Expanding these types of programs and deepening the connections between stakeholders and researchers from a wide
range of disciplines—from physical and biological sciences to social and behavioral sciences to engineering—will promote the convergence required. Creating large, long-term (10 years or more), highly transdisciplinary research centers focused on a particular agriculture problem would also significantly promote convergence. Some examples of successful centers aimed at addressing a particular issue and constructed on integrated and collaborative approaches include USAID’s Global Development Laboratory for Innovation, NSF’s Long-Term Ecological Research Program, and NSF’s Engineering Research Centers.
Most improvements in food system modeling will also require changes in the agri-food data cyberinfrastructure. Computational models depend on input data for development, validation, and application. The data requirements for integrated food systems models can be as intense as the food system under study is rich. All the inputs needed and outputs generated at each step involved in the process of growing, harvesting, processing, packaging, transporting, marketing, consuming, and disposing of food items within a social, political, economic, and environmental context are of interest. Experimental basic research provides essential data that otherwise do not exist. Making existing data findable, accessible, interoperable, and reuseable and encouraging open data (or other approaches to sharing proprietary data) is paramount to accelerating food system models.
Breakthrough 2: The development and validation of precise, accurate, field-deployable sensors and biosensors will enable rapid detection and monitoring across various food and agricultural disciplines. Historically, sensors and sensing technology have been widely used in agriculture, food production, and distribution systems to provide point measurements for certain characteristics of interest (e.g., temperature). But the ability to monitor several characteristics at once is the key to understanding both what and how it is happening in the target system. Scientific and technological developments in materials science and nanotechnology are poised to enable the creation of novel nano- and biosensors to continuously monitor and detect levels and conditions of environmental stimuli and biotic and abiotic stresses. The next generation of sensors may also revolutionize the ability to detect disease prior to the onset of symptoms in plants and animals, to identify human pathogens before they enter the food distribution chain, and to monitor and make decisions in near real time.
Recommendation 2: Create initiatives to more effectively employ existing sensing technologies and to develop new sensing technologies across all areas of food and agriculture. These initiatives would lead to transdisciplinary research, development, and application across the food system.
The attributes of the sensor (e.g., shape, size, material, in situ or in planta, mobile, wired or wireless, and biodegradable) would depend on the purpose, application, duration, and location of the sensors. For example, in situ soil and crop sensors may provide continuous data feed and may alert the farmer when moisture content in soil and turgor pressure in plants fall below a critical level to initiate site-specific irrigation to a group of plants, eliminating the need to irrigate the entire field. Likewise, in planta sensors may quantify biochemical changes in plants caused by an insect pest or a pathogen, alerting and enabling the producer to plan and deploy immediate site-specific control strategies before infestation occurs or damage is visible. Biosensors for food products could indicate product adulteration or spoilage and could alert distributors and consumers to take necessary action.
Collaboration among scientists across various disciplines will be essential for developing the right set of characteristics for sensors. For instance, mobile sensors or wearable devices could transmit data to smartphones or other devices, and sensors would need to be developed that would be scale and target appropriate (nanoscale sensors for individual organisms [plants, animals] versus large-scale sensors for detecting soil characteristics). Sensing technologies would also need to be affordable to be implemented on a large scale and have the capability to be disposable even after single use at retail and consumer phases. The consideration of these various factors will require a convergence of disciplines (such as computer science, materials science, agronomy, food science, and animal sciences) to develop sensors that would be useful for field use and easily integrated into models and databases.
To facilitate progress, online or face-to-face platforms need to be developed that allow scientists from the various arenas (soil, plant, and animal) to become current on the latest technologies. Sharing across disciplines will spur new developments. Whether this is done through the institution of consortia, semiannual transdisciplinary meetings, or some other platform can be left to the researcher and policy community, again with stakeholder input.
One possibility might be to model sharing of sensor information and development on the European Viral Archive project, in which scientists from government and university laboratories from multiple countries worked together to create a virtual archive that would be available for the next emerging viral disease outbreak. After several years of collaboration and cooperation, an archive was available at the time of the Zika virus outbreak, and the archive allowed scientists from all over the world to make rapid progress on disease diagnosis and control.
Data Science and Agri-Food Informatics
Breakthrough 3: The application and integration of data science, software tools, and systems models will enable advanced analytics for
managing the food and agricultural system. Development of inexpensive field-deployable sensors, remote sensing capabilities, and omics techniques have resulted in the collection of enormous amounts of data, but the right tools have yet to be employed for using such data effectively. Data generated in research laboratories and in the field have been maintained in an unconnected manner, preventing the ability to generate insights from their integration. Advances and applications of data science and analytics have been highlighted as an important opportunity to elevate food and agricultural research and the application of knowledge. The ability to more quickly collect, analyze, store, share, and integrate highly heterogeneous datasets will create opportunities to vastly improve our understanding of the complex food system, and ultimately to the widespread use of near-real-time, data-driven management approaches.
Recommendation 3: Establish initiatives to nurture the emerging area of agri-food informatics and to facilitate the adoption and development of information technology, data science, and artificial intelligence in food and agricultural research. Data science and analytics are essential for addressing the most important challenges facing the food system. For example, data analytics that can rapidly link genotypes to phenotypes will help to provide the linkages required to select for desired traits in plants and animals, and will enable nutrigenomics research. Data-driven approaches and blockchain technologies that instantly transfer product data along the food supply chain can be employed to increase food quality and safety through real-time detection of pathogens. These same technologies can also be used to promote animal health, welfare, and productivity. Better analytics of disparate data sources will enable precision agriculture by using real-time data from distributed ground and remote sensing of soil moisture and nutrient levels, accurate weather predictions, plant and soil microbiome, and plant health data. Data collected at high spatial and temporal resolutions will enable scientists to better explore, model, and ultimately optimize the interactions between and functioning of complex systems.
Maximizing the knowledge and utility that can be gained from large research datasets requires strategic efforts to provide better data access, data harmonization, and data analytics in food and agricultural systems. The challenges of handling massive datasets that are highly heterogeneous across space and time need to be addressed. Data standards need to be established and the vast array of data need to be more findable, interoperable, and reuseable. There is a need to increase data processing speeds, develop methods to quickly assess data veracity, and provide support for the development and dissemination of agri-food informatics capabilities, including tools for modeling real-time applications in dynamically changing conditions.
Blockchain and artificial intelligence, including machine-learning algorithms, are promising technologies for the unique needs of the food and
agricultural system that have yet to be fully developed. Development of advanced analytic approaches, such as machine-learning algorithms for automated rapid phenotyping, will require better platforms for studying how various components in the food system interact. Application of these approaches will require investment in infrastructure to house massive numbers of records and a means by which those records can be integrated and effectively used for decision-making purposes. A convergence of expertise from many disciplines will be needed to realize the potential of these opportunities.
Genomics and Precision Breeding
Breakthrough 4: The ability to carry out routine gene editing of agriculturally important organisms will allow for precise and rapid improvement of traits important for productivity and quality. Gene editing—aided by recent advances in omics (e.g., genomics, transcriptomics, proteomics, and metabolomics)—is poised to accelerate breeding to generate traits in plants, microbes, and animals that improve efficiency, resilience, and sustainability. Comparing hundreds of genotypes using omics technologies can speed the selection of alleles to enhance productivity, disease or drought resistance, nutritional value, and palatability. For instance, the tomato metabolome was effectively modified for enhanced taste, nutritional value, and disease resistance, and the swine genome was effectively targeted with the successful introduction of resistance to porcine reproductive and respiratory syndrome virus. This capability opens the door to domesticating new crops and soil microbes, developing disease-resistant livestock, controlling organisms’ response to stress, and mining biodiversity for useful genes.
Recommendation 4: Establish initiatives to exploit the use of genomics and precision breeding to genetically improve traits of agriculturally important organisms. Genetic improvement programs in crops and animals are an essential component of agricultural sustainability. With the advent of gene-editing technologies, targeted genetic improvements can be applied to plant and animal improvement in a way that traditional methods of modification were unable to achieve. There are opportunities to accelerate genetic improvement by incorporating genomic information, advanced breeding technologies, and precision breeding methods into conventional breeding and selection programs. Encouraging the acceptance and adoption of some of these breakthrough technologies requires insight gained from social science and related education and communication efforts with producers and the public.
Gene editing could be used to both expand allelic variation introduced from wild relatives into crops and remove undesirable linked traits, thereby increasing the value of genetic variation available in breeding programs.
Similarly, incorporating essential micronutrients or other quality-related traits in crops through gene-editing tools offers an opportunity to increase food quality and shelf life, enhance nutrition, and decrease food loss and food waste. These technologies are similarly applicable to food animals, and possible targets of genetic improvements include enhanced fertility, removal of allergens, improved feed conversion, disease resistance, and animal welfare.
Genome sequencing and other omics technologies may enable diagnosis of unknown pathogens as well as pinpointing the disease-causing organism from a tissue sample, in a needle-in-a-haystack manner, all in real time. Further advances in this technology could enable rapid testing in the field and at low cost. Such a technology could markedly decrease the time to diagnose transboundary animal diseases and save millions (if not billions) of dollars over the current system of diagnostics.
More in-depth knowledge of omics and how they vary between organisms will be essential in devising robust strategies for detection. Especially in the realm of food safety, the ability to identify extremely small quantities of pathogens and the ability to determine strains could significantly enhance public health by identifying causes of foodborne outbreaks at the earliest possible moment. Detecting miniscule amounts of volatile materials—production of chemicals associated with spoilage—could lead to decreased food loss and waste and prompt preemptive removal to chilled conditions.
Breakthrough 5: Understand the relevance of the microbiome to agriculture, and harness this knowledge to improve crop production, transform feed efficiency, and increase resilience to stress and disease. Emerging accounts of research on the human microbiome provide tantalizing reports of the effect of resident microbes on the body’s health. In comparison, a detailed understanding of the microbiomes in agriculture—animals, plants, and soil—is markedly more rudimentary, even as their functional and critical roles have been recognized for each at a fundamental level. A better understanding of molecular-level interactions between the soil, plant, and animal microbiomes could revolutionize agriculture by improving soil structure, increasing feed efficiency and nutrient availability, and boosting resilience to stress and disease. It is too early to draw conclusions about the relevance and potential applications of microbiomes across ecosystems of relevance to food and agriculture. However, with increasingly sophisticated tools to probe agricultural microbiomes, the next decade of research promises to bring increasing clarity to their role in agricultural productivity and resiliency.
Recommendation 5: Establish initiatives to increase the understanding of the animal, soil, and plant microbiomes and their broader applications across the food system. Transdisciplinary efforts focused on obtaining a
better understanding of the various agriculturally relevant microbiomes and the complex interactions among them would create opportunities to modify and improve numerous aspects of the food and agricultural continuum. For example, understanding the microbiome in animals could help to more precisely tailor nutrient rations and increase feed efficiency. Knowing which microbes or consortia of organisms might be protective against infections could decrease disease incidence and/or severity and therefore lower losses. Research efforts are already under way to characterize the food microbiome in an effort to produce a reference database for microbes upon which rapid identification of human pathogens can be based. In plant sciences, research priorities are being established that focus on engineering various microbiomes to promote better disease control, drought resistance, and yield enhancement. Characterization of interactions between the soil and plant microbiomes (phytobiome) is critical. The soil microbiome is responsible for cycling of carbon, nitrogen, and many other key nutrients that are required for crop productivity, and carries out several other key ecosystem functions impacted in largely unknown ways by a changing climate. Enhanced understanding of the basic microbiome components and the roles they play in nutrient cycling is likely to be critical for ensuring continuing and sustainable crop production globally.
The science breakthroughs alone cannot transform food and agricultural research, as there are other factors that contribute to the success of food and agricultural research. Such factors include the research infrastructure, funding, and the scientific workforce. Other considerations include the social, economic, and political outcomes of various approaches.
4.1 Research Infrastructure Considerations
Conclusion 1: Investments are needed for tools, equipment, facilities, and human capital to conduct cutting-edge research in food and agriculture. Addressing agriculture’s most vexing problems in a convergent manner will require investments in research infrastructure that facilitate convergence of disciplines on food and agricultural research. These could include physical infrastructure for experimentation as well as cyber infrastructure that enables sharing of ideas, data, models, and knowledge. Investments in our knowledge infrastructure are needed to develop a workforce capable of working in transdisciplinary teams and in a convergent manner. Mechanisms are also needed to facilitate building private–public partnerships and engaging the public in food and agricultural research. Some important infrastructure needs include
- Funded experimental facilities for crop, animal, agriculture, and food sciences where teams of scientists, engineers, companies, and other stakeholders can converge to test new methods and models and to engage the public at all steps of the process;
- Funding to encourage team science and to develop new educational programs that support convergence thinking and problem solving;
- Data platforms that are findable, accessible, interoperable, and reuseable and facilitate open access;
- Models that are open access and available to the whole research community; and
- Highly spatially and temporally resolved weather forecasting.
Conclusion 2: The Agricultural Experiment Station Network and the Cooperative Extension System deserve continued support because they are vital for basic and applied research and are needed to effectively translate research to achieve impactful results in the food and agricultural sectors. The agricultural sciences are grounded in the basic sciences but have an eye toward the applied; this has historically been facilitated by state agricultural experiment stations, as well as by extension and outreach efforts. Personnel and facilities with these functions allow scientists to translate laboratory-based findings into real-world products and processes that are most relevant, ultimately reaching key stakeholders and end users. Those stakeholders include industry, regulatory agencies, farmers and ranchers, and the general public. The recognition that scientists need to collaborate with stakeholders and translate basic research into useful and applicable results for the good of society is a fundamental value of the agricultural sciences. Recognizing and reinforcing that value through the provision of resources is essential for integrating agricultural scientific breakthroughs into the fabric of everyday life.
4.2 Funding Considerations
Conclusion 3: Current public and private funding for food and agricultural research is inadequate to address critical breakthrough areas over the next decade. There is a rapidly emerging need for food security and health to merit national priority and receive the funding needed to address the complex challenges in the next decade. If a robust food system is critical for securing the nation’s health and well-being, then funding in both the public and private sectors ought to reflect this as a priority.
In the past century, public funding for food and agricultural research has been essential for enabling talented U.S. scientists to conduct basic scientific research and provide innovative solutions for improving food and agriculture. Agricultural R&D by the public sector provides benefits
that accrue to both farmers as well as consumers and is estimated to have a median rate of return of 40 percent (Clancy et al., 2016). Waning U.S. public investments will slow innovation and growth and would jeopardize the ability of the United States to remain competitive in a global economy, potentially undermining U.S. food and nutrition security (NRC, 2014b). As previously mentioned, since 2009, China has surpassed the United States as the top global performer of agricultural R&D (Clancy et al., 2016). In fiscal year (FY) 2017, the National Institutes of Health (NIH) allocated $18.2 billion for competitive research grants compared to USDA, which was appropriated only $325 million for competitive research grants (less than 2 percent of the NIH’s amount), a budget that was less than half of the congressionally authorized amount (HHS, 2017; USDA, 2017). The current level of federal funding for food and agricultural research has thus been inadequate. Breakthrough science needed to assist the food and agricultural enterprise to thrive in the future will require a significant investment. More will be required to sustain the level of coordination and collaboration needed to address the increasingly integrative, expansive, and visionary research required to ensure future security and competitiveness.
The current political climate suggests that it may be difficult to increase public funding for food and agricultural research to the levels needed. Although private R&D is not a substitute for public R&D funding, private foundations and industry can provide some research funding that is complementary to public funding in the U.S. agricultural innovation system. Innovative business models can be more widely employed for engaging researchers. For example, venture capital funding for start-up companies, which are well known in the tech industry, are providing record sources of investment in food and agricultural research (The Context Network, 2017; Cosgrove, 2018; Rausser et al., 2018). There are new institutions and mechanisms of financing research and of implementing innovations induced by research that offer the potential to expand funding. For instance, the Foundation for Food and Agriculture Research was established by Congress in the Agricultural Act of 2014 (known as the 2014 Farm Bill) to increase investment in cutting-edge research by leveraging public funds with matching nonfederal dollars (including industry and nonprofit organizations) and thus expand the total funding available to support research. Other examples of new institutions include the Agricultural Technology Innovation Partnership Foundation formed to develop public–private collaborations around USDA research discoveries technology transfer, including linkage to venture capital and business expertise. However, these sources alone are insufficient to achieve the goals laid out in this report. In order for the U.S. agricultural enterprise to capitalize on the integrative, expansive, and visionary tools of research now being actively pursued by many other industries (e.g., sensing technologies, wireless communication, and machine
learning), a commitment to a major investment is needed now to ensure their relevant application to food and agriculture.
4.3 Education and Scientific Workforce
Conclusion 4: Efforts to renew interest in food and agriculture will need to be made to engage nonagricultural professionals and to excite the next generation of students. Vast opportunities are available for non-traditional agriculture professionals to be involved in food and agriculture. However, there may be barriers to their involvement, such as misperceptions about the sophistication of agricultural technology and the lack of sustained funding for building transdisciplinary agricultural research teams that include non-agricultural professionals and scientists from other disciplines to work in food and agricultural sciences.
A robust workforce for food and agricultural research will require talented individuals who are proficient in the challenges facing the food system along with an understanding of the opportunities to think outside the box for innovative approaches. Recruiting talented individuals into food and agricultural research will require a demonstration and shift in perception that food and agriculture can be innovative. There are efforts under way to merge traditional agricultural disciplines with other areas of expertise to bring about convergent approaches, such as the new undergraduate program in computer science and crop sciences at the University of Illinois at Urbana-Champaign beginning in fall 2018 (UIUC, 2017).
4.4 Socioeconomic Contributions and Other Considerations
Conclusion 5: A better understanding of linkages between biophysical sciences and socioeconomic sciences is needed to support more effective policy design, producer adoption, and consumer acceptance of innovation in the food and agricultural sectors. The successful application of scientific innovation in the field depends on the willingness and ability of stakeholders to successfully apply and use new products and processes; it also depends on whether they view high-tech, site-specific approaches as economically or ecologically beneficial. There is a critical need to better understand the best means and methods for effective technology development and integration in production processes, with input from both the public and private sectors. Better understanding of the political economy, behavioral and choice processes related both to adoption and use of the technological innovation, and acceptance and perception of new products will be required to support the effective design of policies and application of the research innovation (Herring and Paarlberg, 2016; Clancy and Moschini, 2018). For example, digital information from remote sensing devices may be used in new deci-
sion support systems to assist agricultural workers in making choices about field practices or animal handling. However, workers will need sufficient training and motivation to respond to expected and unexpected outcomes and uncertainty (e.g., animal response to treatment or extreme weather events). Lessons from behavioral sciences (e.g., “nudges” or defaults) may help support behavioral change and training requirements. An example of “nudges” or defaults is in the reduced costs of adoption and use of water conservation practices (Ferraro et al., 2017). Attention to the political economy and socioeconomic context highlights the challenge of distributional aspects as well. Small-scale operators may be limited in their ability to take advantage of newer technologies because of cost considerations or capital requirements. Some consumers may be limited in food choices by lack of access to product variety or innovative data applications in their local food outlets and environment. However, to allow more rapid diffusion of the technological advances and offer an important way to address issues of potential scale bias in some of the new technologies, innovations are needed in scaling the available technologies and in the market for services that provide user friendly access to data services for small-scale producers or consumers through devices and apps.
The successful implementation of scientific advances also requires other important considerations to be taken into account. Policies on land or input use, environmental impact, animal welfare, and food-handling practices can have significant near- and long-term impacts on agricultural and food sustainability. Some policy or technology changes may have unintended consequences in the system and require closer examination of system interactions, including human behaviors related to adoption and use of new inputs, products, and processes. Insights from behavioral sciences can help inform policy designs and reduce the costs of change, inform technological adoption in the field (e.g., design of conservation or tillage applications, or provision of product information to consumers), and address issues of product acceptance and consumer trust in the food system (Lusk and McCluskey, 2018).
At this pivotal time in history with an expanding global population requiring more from an increasingly fragile natural resource base, science breakthroughs are needed now more than ever. As the world’s greatest agricultural producer, the United States bears the tremendous responsibility of implementing scientific advances to support our nation’s well-being and security, and perhaps even global stability. Promising research opportunities include integrating agriculture and food systems to sustainably meet human and animal health needs, providing yield stability and economic value under
variable and uncertain environmental pressures, and reducing inputs and negative environmental impacts. Realizing this vision requires a holistic systems approach that combines scientific discovery, technological innovation, and incentives to revolutionize our food and agricultural systems to ensure greater food security and human and environmental health. Implementing this vision requires a bolder approach to research that integrates scientific insight from various disciplines to bring promising breakthroughs to fruition and to ensure U.S. competitiveness and food security. The food system of tomorrow will depend on how well we are able to prepare for resiliency today and how well we are able to build our capacity for the future. The U.S. scientific enterprise is willing to rise to address such challenges; the tools and resources identified in this report can ensure its success.
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