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Cornell Institute for Digital Agriculture

The worldwide food system faces a formidable challenge - to feed an estimated global population of 10 billion people by 2050. To meet this challenge, we must re-envision the way food is produced, processed and distributed, the way natural resources are used, recycled and replenished, and the way our agricultural systems interact with both the human and the natural world to sustain the health of individuals, communities and the environment. Digital Agriculture (DA) is the application of

computational and information technologies coupled with nanotechnology, biology, systems engineering and economics to both the research and operational sides of agriculture and food production. Digital agriculture will enable more efficient use of resources, more effective management, and better design of food systems, thereby helping to meet the challenge.

The Cornell Digital Agriculture Initiative includes researchers from the College of Agriculture and Life Sciences, the College of Engineering, Computing and Information Sciences, the College of Veterinary Medicine, and the S.C. Johnson College of Business. We bring together world-class scientists and practitioners from academia, industry, and government to develop disruptive innovations that couple computing, agro-ecologies, robots and humans to solve these agricultural challenges. We aim to advance three complementary components of the future of agriculture: Scalable Analytics, Digital Innovations and Discovery and Design.

Scalable Analytics for improved decision-making - Scalable analytics underlies work to capture, curate, interpret and disseminate diverse data sets and will form a backbone of operational DA systems. Platforms will be developed to collect data and translate this data to information for decision making. Scalable analytics will be used to unleash the power of artificial intelligence A student operates a drone in a field.(AI), data analytics, and networked resources. From here, we can develop policy and risk analytics to improve sustainability and inform enhanced decision-making for producers, distributors,
consumers and policy makers.

More specifically, Scalable Analytics will:

  • Develop systems that can reason autonomously and support robots and humans to optimally cooperate safely and securely in real-time.
  • Support development of real-time, high-resolution yield forecasting, disease and practice modeling utilizing AI, spatial statistics, and machine learning approaches.
  • Develop methodologies to manage and deploy disparate, complex data structures and streams (climate, local weather, soil, plant/animal, machine, human).
  • Examine how attitudes, education, social and business relationships impact digital agriculture adoption, and how adoption may disrupt existing local social and economic relationships.

Digital Innovations for measurement and control - Digital innovations will invent and deploy new secure, private and reliable communication channels and local or edge computing. Tools will be developed for pervasive sensing and automation in agricultural practices, from the molecular and cellular level to the scale of the field/barn/controlled environment, ecosystem, distribution network, and market.

More specifically, Digital Innovations will:

  • Expand the Cloud to the edge of the farm, the Edge Cloud, thereby providing seamless and continuous computation and communication despite limited energy and sparse cellular connectivity.
  • Reconcile the modes and idiosyncrasies of a highly heterogeneous, highly granular collection of analog + digital and hardware + software components.
  • Design nano-bio-sensors to “measure the immeasurable.”
  • Engineer smart, autonomous machines that can evaluate and treat individuals with minimal invasion.

Discovery and Design of the next generation of food systems - Discovery and design will develop systems models A microchip smaller than a grapeand design tools that couple genetics, development and physiology to biotic and abiotic stresses with accounting for ecosystem-scale interactions. It will accelerate the development of climate-ready varieties, adaptation techniques and discover the biology that connects genotype to phenotype in complex managed environments.

More specifically Discovery and Design will:

  • Exploit new data streams to advance genetics, phenology, and breeding for health, pathogen resistance, stress mitigation and local adaptation.
  • Develop and deploy micro-, nano-, and molecular technologies for the transmission of biological information from organisms to computing systems in real-time.
  • Provide robust predictions that allow for design and optimization in uncertain environments.

As we make progress addressing these three complementary components, an overarching goal of this Initiative and our land grant mission will be to educate and support the world’s farmers via our extension programs, and to create unique cross-disciplinary, cross-college curriculum and research interactions that will train a generation of Cornell students for productive careers in digital agriculture. As momentum and energy increases around the Cornell Digital Agriculture Initiative, there is a growing interest to consider launching a more formal Institute.

Goals for a Cornell Institute for Digital Agriculture

  • Advance the three complimentary components of digital agriculture and serve as an internal and external focal point for Cornell University
  • Address training and communication needs of faculty and students (e.g., facilitate integrated coursework, internships and student projects; organize on-campus events and seminars)
  • Work with liaisons in the constituent colleges and relevant university centers to seek private and public sector involvement and support (corporations, foundations, government)
  • Facilitate faculty-to-faculty collaboration and joint grant applications
  • Serve as a high-level advisory team for industry and government
  • Work with Cornell technology licensing and entrepreneurship offices to promote commercialization activities