In This Issue
Summer Bridge on Smart Agriculture
June 15, 2022 Volume 52 Issue 2
People everywhere rely on agriculture in one form or another – for food, animal feed, fiber, and other necessities. The summer 2022 articles describe precision indoor farming and alternative protein food systems, advances in food processing, genome editing, digitalization, sustainable and regenerative agriculture, the role of a circular economy, and the important role of policy.

Digital Biology to Enable Sustainable and Resilient Agriculture

Tuesday, June 14, 2022

Author: The CROPPS Research Community

Progress in understanding and production of crops requires transdisciplinary collaboration and innovation.

Preparing for a future of resilient and sustainable agriculture that produces nutritious calories for the globe’s growing population requires a deeper understanding of the biology of plants, their associated organisms, and their responses to a changing climate. The discovery and translation of this knowledge will require the intensive collaboration of engineers and computer scientists with life scientists. The resulting technical innovations will have implications beyond plant science and agriculture, and the biological discoveries will have impacts on other branches of the life sciences.

CROPPS.gifBecause the practice and outputs of agriculture affect all people, this effort must involve the social sciences and be informed by strong engagement with stakeholders along the agrifood value chain, including farmers, consumers, and public and private organizations. This transdisciplinary effort represents a new form of “digital biology” and calls for the intentional cross-training of life scientists, engineers, computer scientists, and social scientists to lead discovery, innovation, and responsible translation in this critical area.

Agriculture as a Complex System

The practice of crop-based agriculture, like that of medicine, involves developing and deploying interventions to influence the behavior of an extraordinarily complex system that is still incompletely understood. For crops, this system involves

  • the plants themselves as highly differentiated, multicellular, eukaryotic organisms;
  • a local environment that spans from the atmosphere to below ground—the soil in particular presents massive physical, chemical, and biological complexity;
  • local ecologies that include microbes, insects, and other plants, each of which can present benefits and costs for a crop; and
  • human contexts, in the form of farm management of cultivars, inputs, labor, and markets as well as consideration of the preferences, health, and economics of consumers.

Progress toward a more complete understanding of crop systems and the ability to interact with them in more sophisticated ways will help secure a healthy future for people and the planet. This pursuit also presents diverse scientific and technical challenges, with strong potential to advance other areas of science and technology, and provides a richly multidisciplinary context in which to train life scientists and engineers.

Challenges in Agricultural R&D and Practice

Through the 10,000-year history of agriculture, humans’ ability to learn from and innovate in their interaction with plants has provided a foundation—in calories, nutrition, fuel, and fiber—for population growth and stable societies. Discoveries in the study of plants, such as evolution (Darwin) and genetics (Mendel and McClintock), are landmarks in the history of science. Innovations in crop agriculture have enhanced environmental modeling and measurement and provide some of the earliest examples of self-driving vehicles and applications of genetically engineered organisms.

Yet despite important advances in both biological understanding and technology, there remain critical limitations in the speed, precision, and robustness of approaches, in both research and development (R&D) and on-farm practices. Following are some important examples of these limitations:

  • In the R&D context of breeding new cultivars for increased yield, nutritional value, resource efficiency, and resilience, the development cycle requires most of a decade, a span of time over which both climate and market conditions can change dramatically. Visions for accelerating this cycle, such as the use of gene editing to move useful gene variants rapidly into high-performance genetic lines, require a deeper understanding of the biology of, for example, gene regulation as well as breakthroughs in the throughput, versatility, and precision of emerging tools for gene editing (Varshney et al. 2020).
  • Characterizing plant-microbe interactions in the soil is a challenging frontier in crop sciences, with enormous potential benefits from the capture of native symbioses or design of new beneficial interactions to lower dependence on external inputs and increase resilience and sustainability (Arif et al. 2020). Lack of tools to navigate, study, and model the complex and poorly accessible ecosystem formed by plants and microbes in the soil has hindered both science and application in this area.
  • On the farm, management of inputs such as water and nitrogen, detection of and response to disease and pests, and mitigation of extreme climatic conditions remain limited in precision and speed. For example, crops make use of only about one third of the nitrogen delivered by fertilization, and the rest is lost via leaching and gaseous releases (Omara et al. 2019). Lack of access to high-frequency or real-time information about plants’ internal biological states and processes hinders discovery, the development of predictive models, and, in turn, farmers’ ability to manage these challenges.

Lack of real-time information about plants’ internal biological states hinders the development of predictive models and farmers’ ability to manage challenges.

A common theme in these examples is the interconnection between tools and knowledge in efforts to achieve important outcomes in crop-based agriculture: acquiring understanding requires tools, and the development of tools requires understanding.

CROPPS figure 1.gif
FIGURE 1 Illustration of the vision pursued in the Center for Research on Programmable Plant Systems (CROPPS), which is developing a suite of technologies to allow plants to serve as nodes on an Internet of Living Things (IoLT). This IoLT will enable multiscale understanding based on efficient two-way exchange of information with plants, above and below ground, across genetically diverse populations, and in changing environments. The center pursues its science and engineering in cycles (design-build-test-learn) that are continuously informed by public engagement and a commitment to education, ethical practices, and positive societal outcomes.

The Center for Research on Programmable Plant Systems (CROPPS)

Colleagues at Cornell University, the University of Illinois at Urbana-Champaign, the University of Arizona, and the Boyce Thompson Institute are pursuing a research program that fosters close, multifaceted collaborations among life scientists, engineers, computer scientists, and social scientists. In the newly established Center for Research on Programmable Plant Systems (CROPPS), a Science and Technology Center of the National Science Foundation, we aim to define a new kind of transdisciplinary digital biology in which experts in these areas collaborate to create technology that supports discoveries that inform and inspire new technologies and applications.

In CROPPS, we are pursuing a vision focused on developing new modes of interaction with plants’ internal biological processes to decode the rules of living systems. We will use this newly acquired knowledge to improve outcomes in both the research pipeline and practice of agriculture.

An Internet of Living Things

The CROPPS vision builds on advances in embedded systems, edge and cloud computing, and communication systems that have inspired the concepts of Industry 4.0, the Internet of Things, and digital agriculture (Chandra et al. 2022; Schueller and Reid 2022). We extend these developments to the tight coupling of living systems—plants—in a network of information flow to form an Internet of Living Things (IoLT; figure 1).

In developing the IoLT, we aim to create a virtuous cycle of discovery, refinement, and optimization. In the context of research, this cycle involves access to new data, in planta and in relevant environments, that feed the development and maturation of multiscale models; predictions from these models, in turn, inform the design of new technologies and experiments to access further data and insights.

In parallel with advancing understanding of plant systems, this research cycle serves as an incubator of innovations in engineering and computer science. A critical goal of this research phase is to assess, through cycles of design-build-test-learn, the robustness, effectiveness, and safety of prototypes of hardware, software, and plants to foster their adoption in agricultural R&D and crop production. In assessment cycles, we prioritize engagement of stakeholders from across the agricultural sector—growers from both large and small farms, and representatives of private, governmental, and nongovernmental organizations—as well as the general public to inform our visions and approaches with their perspectives and concerns.

The realization of our vision of digital biology and an IoLT will require a richness of interconnected innovations across biology, engineering, and computing. The following sections present examples focused on opening new pathways to exchange physical, chemical, and biological information with plant systems.

Biotechnology and Synthetic Biology

Genetic engineering and gene editing are powerful approaches for defining the flow of information to and from plants’ inner biology and for programming changes in plant function, as in the introduction of genetic variants (gain and loss of function) and gene-encoded sensors, reporters, and inducers. With the emergence of synthetic biology, one can now look toward more complicated functions for gene circuits with logic elements and multiple inputs and outputs.

Realizing the full potential of these approaches will require integrated advances to address bottlenecks in plant transformation related to (i) the efficiency and versatility of gene delivery technologies; (ii) slow, labor-intensive processes such as cell and tissue manipulation and diagnostics for quality control; and (iii) the design of robust gene circuits to enable, for example, new mechanisms of bidirectional transduction (Altpeter et al. 2016). The pursuit of these advances presents interesting opportunities for collaboration between molecular biologists, biomolecular engineers, roboticists, optical engineers, and computer scientists for computations ranging from machine vision to molecular simulation.

Synthetic biology also provides a particularly rich context for learning across disciplinary boundaries with, for example, biologists benefiting from the powerful conceptual tools of circuit design and engineers gaining access to a vast diversity of new functional elements (Wurtzel et al. 2019).

Robotics and Automation

Robotics and automation have a long history of contributing to agriculture, in both R&D and production contexts. They have enabled, for example, self-driving tractors, platforms for high-throughput screening of plants for breeding (“phenotyping”), and increased in-field autonomy with rovers and aerial vehicles (Shamshiri et al. 2018).

Digital biology and the IoLT present new challenges for robotics, calling on them to mediate communications with plants’ inner biology via mechanical, chemical, and optical interactions. An important frontier for these engagements is the development of autonomous tools for exploration of the belowground realm of plant systems, in which kilometers of roots are interspersed with the highly heterogeneous, biologically active environment of the soil.

The multifunctional and dexterous actuators emerging in the area of soft robotics present promising opportunities to address these challenges (e.g., Zhao et al. 2016).

Sensing and Actuation

Micro- and nanoengineered systems have proven valuable in biomedicine in contexts from drug delivery to imaging, glucose sensing, and pacemakers. Injectable or implantable systems can similarly play important roles in opening access to internal states and dynamics in plants and enabling tailorable modes of transduction into digitizable signals.

Plants present challenges distinct from mammals for the design of such tools with respect to, for example, gaining access through tough external tissues and selective membranes and controlling the translocation of materials once they have passed these barriers. Device function must also be informed by specific physiological contexts, such that the transfer of strategies directly from biomedical technologies is often not possible.

In synthetic biology, biologists benefit from the tools of circuit design and engineers gain access to
new functional elements.

Members of the CROPPS team have collaborated on the successful design of a nanoparticle that reports local water stress in leaves as easily readable changes in fluorescence spectrum. This development involved iterations of design to achieve the necessary responsiveness and compatibility with delivery to and operation in the microscopic spaces in leaves (Jain et al. 2021). Engineering of these systems requires consideration of both biological and environmental appropriateness relative to toxicity, degradation processes, and potential for retrieval and reuse.

Computing and Modeling

Innovations in computing can both contribute to an IoLT of plant systems and benefit from the unprecedented data streams that this infrastructure will create. For instance, the IoLT will enable the creation of digital twins of every plant in the cloud, and such a detailed dataset will help drive artificial intelligence models that were not possible until now.

We focus on the vast challenges and opportunities of building predictive models of the multiscale processes—from molecules, cells, and tissues to the whole organism and its local environment—that define a plant’s growth, resource use, response to stress, and productivity. This effort needs to define new ways to combine the mechanistic approaches of systems biology with the data-driven approaches of bioinformatics. Such hybrid approaches can exploit the robustness to extrapolation of mechanistic models across environmental and other conditions, while data-driven models provide scalability to manage, for example, full genome-scale analyses. Such approaches are emerging as accelerators of plant breeding (Wang et al. 2020).

These modeling contexts present interesting targets for innovation in data science and machine learning with resources such as massive datasets (genomic, transcriptomic, proteomic, and metabolic) between which bridges must be built (Cheng et al. 2021). As models mature, the IoLT provides a context in which strategies from systems engineering will need to be developed to make their predictive power useful in defining optimal interactions with plants to support both continued research discoveries and improved crop management.

Digital Biologists and the Public Interest

In closing, we emphasize the human dimensions of our vision of digital biology for discovery and translation in crop-based agriculture. Food and other products produced by plants touch everyone, and the environment in which plants are grown belongs to all.

The success of the CROPPS vision depends on the cultivation of true digital biologists who pursue their innovations with humble awareness of the need to engage seriously with the public, reflect continuously on the implications of their work, and be adaptive in updating approaches to target outcomes that benefit people and this planet.


We appreciate the thoughtful comments of three evaluators of our manuscript and support from the National Science Foundation under Grant No. DBI-2019674.


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About the Author:The Center for Research on Programmable Plant Systems (CROPPS; is an NSF Science and Technology Center partnership of Cornell University, University of Illinois Urbana-Champaign, University of Arizona, and Boyce Thompson Institute.