Opportunities abound to integrate digital agricultural systems such as instrument-free sensing and diagnostics; smart food production with tailored flavor, yield and nutrition; and systems engineering of economic models and market data. Many research projects will be pursued at Cornell, and these individual projects can be categorized as systems analytics, digital innovations, and discovery and design.
Systems analytics for improved decision-making
Systems 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, analyze and interpret them and extract information as the basis for decision-making. Systems analytics will be used to unleash the power of artificial intelligence (AI), data analytics and networked resources to develop policy and risk analytics, improve sustainability and inform enhanced decision-making for producers, distributors, consumers and policy-makers.
Systems analytics will do the following:
- Develop systems that can reason autonomously and support robots and humans to cooperate safely and securely in real time.
- Support development of real-time, high-resolution yield forecasting, and 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 and 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, and controlled environment, ecosystem, distribution network and market.
Digital innovations will do the following:
- 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 and digital as well as hardware and 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 and design tools that couple genetics, development and physiology in response to biotic and abiotic stresses, accounting for ecosystem-scale interactions. It will accelerate the development of climate-ready varieties and adaptation techniques and will discover the biological mechanisms that explain genotype to phenotype relationships in complex managed environments.
Discovery and design will do the following:
- 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 is to educate and support the world’s farmers via our extension and outreach 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.