Controlled Environment Agriculture in Metropolitan Areas – January 18, 2018
Neil Mattson, Associate Professor, College of Agriculture and Life Sciences (CALS), School of Integrative Plant Science (SIPS); Miguel Gomez, Associate Professor, SC Johnson College of Business (JCB), Charles H. Dyson School of Applied Economics and Management (Dyson); and Anusuya Rangarajan, Director, Cornell Small Farm Program, CALS, SIPS.
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.
Using Touch Sensitive Soft Robots to Improve Vineyard Management – JUL 7, 2017
Kirstin Petersen, Assistant Professor, College of Engineering (COE), Electrical and Computer Engineering (ECE); and Justine Vanden Heuvel, Associate Professor, CALS, SIPS.
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.
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.
Using Micro Water Sensor to Manage Irrigation in Apple Orchards – JUL 5, 2017
Lailiang Cheng, Professor, CALS, SIPS; Alan Lakso, Professor Emeritus, CALS, SIPS; and Abraham Stroock, ’95, Professor, COE, Chemical and Biomolecular Engineering (CBE).
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.
What Keeps Farmers from Adopting Digital Agriculture? – JUL 4, 2017
Solon Barocas, Assistant Professor, Computing and Information Science (CIS), Information Science (Info Sci); Karen Levy, CIS, Info Sci; and Harold van Es, CALS, SIPS.
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.
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.
Facilitating Access to Complex Climate and Weather Data – JUL 2, 2017
Arthur DeGaetano, Professor, CALS, Earth and Atmospheric Sciences (EAS); and Madeleine Udell, Assistant Professor, CIS, Statistics and Data Science (DSDS).
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.
Intelligent Lighting Systems in Greenhouses – MAR 21, 2017
Neil Mattson, Associate Professor, CALS, SIPS.
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.
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.
Smart Tools for Apple Growers to Protect Crops – MAR 19, 2017
Art DeGaetano, Professor, CALS, EAS.
Apple freeze-risk decision tool helps apple growers to protect their crops against spring freezes: When a frost hits after a warm spell, apple producers begin to see damage to the developing fruit. The easy-to-use, online tool considers the exact location, the apple variety, and the stage of bud/bloom development to assess the risk of freeze damage.
Freeze-risk decision tool
Sustaining NY Apple Production in an Age of Climate Change (video)
Leaf Doctor and Estimate, two new free apps, work with photo analysis of damaged leaves to determine plant disease severity and help growers and researchers to decide if and how to treat the plant. While Leaf Doctor analyzes photos users take, Estimate connects users to a database of diseased leaves to help determine damage.
Digital Mapping Technology for Grape Growers – MAR 17, 2017
Terry Bates, Senior Research Associate, CALS, SIPS at Cornell Lake Erie Research and Extension Laboratory, Portland, NY.
Digital mapping technology for grape growers: the project aims to bring precision viticulture technology to grape growers, by measuring conditions related to soil, canopy and crop, and using software developed by the research team to produce detailed digital maps.
Follow the team’s podcast for grape growers
Using Proximal NDVI Sensors to Increase N Use Efficiency – MAR 16, 2017
Quirine Ketterings, Professor, CALS, ANSC.
Algorithms convert NDVI measurements of hand-held or tractor mounted sensors into on-the-go N rate recommendations while in the field. This project evaluates which algorithms are most appropriate to use for corn grown for silage or grain in New York State.
Using Drone Imagery to Guide Selective Harvest in Vineyards – MAR 14, 2017
Justine Vanden Heuvel, Associate Professor, CALS, SIPS.
The practice of selective harvesting for different grades of fruit quality in wine grape vineyards is common among large producers. This project helps Finger Lakes wine grape growers to learn how to use drones to collect NDVI images of their vineyards, and use them to guide harvest plans and maximize the economic potential of their fruit.
Improving Dairy Cow Health and Reducing Labor Cost – MAR 13, 2017
Julio Giordano, Associate Professor, CALS, ANSC.
This project aims to better understand the behavioral, physiological, and productivity parameters during health and disease in dairy cows. The team’s experiments on dairy farms are designed to understand if automated health monitoring can promptly and accurately identify cows suffering from health disorders.
Improving Apple Grower Profitability Through Precision Management Smart App – MAR 12, 2017
Jaume Lordan Sanahuja; and Poliana Francescatto, post doc CALS, SIPS.
The aim of this project is to develop an innovative, fast and easy-to-use tool for growers, making the precision management practices of apple orchards easier to accomplish. A new app will provide data analysis and real-time guidance, and help boost grower productivity in an environmentally friendly way.
Adapt-N: Web-based Nitrogen Management Tool – MAR 11, 2017
Harold van Es, Professor, CALS, SIPS.
The Adapt-N provides precise N fertilizer recommendations to farmers for corn crops, accounting for the effects of seasonal conditions and field-specific information on crop and soil management. Adapt-N is now licensed to Yara International, and won the $1 million grand prize from the Tulane Nitrogen Reduction Challenge.