Controlled Environment Agriculture in Metropolitan Areas
Jan 18, 2018
Controlled environment agriculture (CEA), such as greenhouses, plant factories, and vertical farms, may be a viable alternative to conventional field-based production of vegetables for supplying metropolitan areas. This project will develop tools to assess the economic viability and sustainability of CEA operations, and guide their development in urban areas. Researchers: Neil Mattson, Miguel Gomez, Anusuya Rangarajan
Using Touch Sensitive Soft Robots to Improve Vineyard Management
Jul 7, 2017
This project aims to develop an automated vineyard system to accurately determine vine yield, leaf area to fruit ratio, and cluster integrity based on touch-sensitive soft robots (rather than the industry standard of computer vision), accurately estimating grape vine yields prior to harvest. Researchers: Kirstin Petersen, Justine Vanden Heuvel.
E-synch: Improving Cattle Reproductive Management
Jul 6, 2017
The easy-to-use E-synch device will reduce the hassle of reproductive management of dairy cows, using sensors to closely monitor individual animals and customize the protocols for their reproductive cycle in real-time. An electronically controlled, reusable device will deliver reproductive hormones automatically. This project aims to help balance and optimize the productivity and health of millions of cows around the world. Researchers: Julio Giordano, David Erickson
Using Micro Water Sensor to Manage Irrigation in Apple Orchards
Jul 5, 2017
This project is developing an integrated digital solution for optimizing irrigation in apple orchards, using a micro water stress sensor technology - the microtensiometer - recently developed by Cornell. This tiny and inexpensive chip combined with smart technology systems collecting and interpreting the data it provides, will serve as a foundation for the next generation of automated irrigation systems, delivering water only where it is needed. Researchers: Abraham Stroock, Lailiang Cheng, Alan Lakso
What Keeps Farmers from Adopting Digital Agriculture?
Jul 4, 2017
This study aims to uncover the concerns farmers might have when deciding to adopt new precision agriculture technologies, focusing on how novel forms of data collection and information flow have raised questions about privacy and the distribution of the resulting economic benefits. Researchers: Solon Barocas, Harold Van Es, Karen Levy.
Smart Agriculture Through Big Data-driven Optimization
Jul 3, 2017
The connections between agriculture, economics and sustainability are complex, and so are the ever-increasing streams of available data. This project aims to advance climate-smart farming, optimize crop insurance and promote conservation agriculture by combining data-driven optimization and advanced machine learning techniques with digital agriculture data. Researcher: Fengqi You.
Facilitating Access to Complex Climate and Weather Data
Jul 2, 2017
The Northeast Regional Climate Center (NRCC) has developed the Applied Climate Information System (ACIS) that allows users to easily access a wide range of weather observations, climate projections and weather forecasts. NRCC staff is developing an array of decision tools, including a database of past weather forecasts to allow researchers and users to assess and improve the accuracy of forecasts. The team focuses on improving resolution of data and regional relevance. Researchers: Arthur DeGaetano, Madeleine Udell More information
Intelligent Lighting Systems in Greenhouses
Mar 21, 2017
The Greenhouse Lighting and Systems Engineering (GLASE) consortium is advancing LED light engineering, plant photobiology, carbon dioxide enrichment and systems control to create intelligent systems that can dramatically reduce the energy cost and carbon footprint of horticultural lighting. Researcher: Neil Mattson. Read more
Using Drone NDVI Imaging to Manage Nitrogen and Yield
Mar 20, 2017
This project is evaluating the use of drone-generated NDVI (normalized difference vegetation index) maps as tools for predicting yield and nitrogen needs of corn and forage sorghum. The team is developing a standard operating procedure for using drones to collect NDVI imagery to ensure consistent, actionable data under changing light and growing condition. Researchers: Quirine Ketterings and Elson Shields. More information