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Digital Agriculture - Research Highlights
- Imaging and analyzing of leafy plant diseases: 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.
Researcher: Sarah Pethybridge
- 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.
Researcher: Terry Bates
Follow the team's podcast for grape growers
- Managing nitrogen and yield in field crops utilizing drone NDVI imaging: 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
- Proximal NDVI sensors to increase N use efficiency: 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.
Researcher: Quirine Ketterings
- Ag-Analytics – tools for farmers, researchers and policy makers: this platform offers tools to help farmers understand their crop insurance options to better manage risks. The team also host an open source/open data system that integrates economic and environmental data, and translate complex research into user-friendly web tools for researchers, farmers and policy makers.
Researcher: Joshua Woodard
- Using drone imagery to guide selective harvest in vineyards: 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.
Researcher: Justine Vanden Heuvel
- Improving dairy cow health and reducing labor cost: 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.
Researcher: Julio Giordano
- Improving apple grower profitability through precision management smart app: 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.
Researchers: Jaume Lordan Sanahuja and Poliana Francescatto
- The Adapt-N tool is a web-based nitrogen recommendation tool for corn crops, providing precise N fertilizer recommendations that account for the effects of seasonal conditions and field-specific information on crop and soil management.
Researcher: Harold van Es
- Facilitating access to climate and weather data: 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. ACIS provides researchers and programmers with webservice data access and facilitates the development of an array of stakeholder-driven decision tools and products by NRCC staff.
Researcher: Arthur DeGaetano