Project Grant 20175118126825

This project grant, awarded by the U.S. Department of Agriculture's National Institute of Food and Agriculture under the Agriculture and Food Research Initiative (CFDA 10.310), provides $612,113 to Washington State University to develop and evaluate non-invasive, real-time sensing techniques to detect and manage post-harvest potato storage diseases. The key products and services to be delivered include: Objective 1: Develop and evaluate ion mobility spectrometry and optical sensing systems for...

This Project Grant award from the National Science Foundation's Office of International Science and Engineering (CFDA 47.079) provides $400,000.00 to Cornell University to develop advanced methods for high-throughput, non-destructive evaluation of yield and quality in three key horticultural crops: tomato, onion, and strawberry. The project will apply imaging, machine learning, and multi-omic data analysis to create faster and more precise ways to measure traits like fruit count, size, and...

The University of Florida (UF) Division of Sponsored Research has been awarded a $720,797 Project Grant from the U.S. Department of Agriculture's Agriculture and Food Research Initiative (AFRI) program. The funding will support a 4-year research project focused on developing heat-tolerant potato varieties and integrating crop growth models with genomic prediction to accelerate potato breeding. The key products and services to be delivered under this grant include: Creation and evaluation of a...

Advanced Growing Resources Inc. was awarded a $255,786 National Science Foundation Project Grant under the NSF Technology, Innovation, and Partnerships program to develop a novel handheld spectroscopy device for early detection of crop afflictions. The one-year award will support the design of an affordable imaging spectrometer integrated with precision optics to bridge gaps in existing technologies. The device will be deployed to collect spectral data from grapes, a high-value crop...

The University of Nebraska was awarded a $591,306 Project Grant from the USDA's Agriculture and Food Research Initiative (AFRI) program to develop a tool called DeepYield. DeepYield uses artificial intelligence and deep learning techniques to predict sugar beet yields for farmers based on various data inputs. The project aims to help farmers manage their land more effectively by providing tailored insights on factors influencing yields. The University is partnering with the Western Sugar...

This Project Grant award from the U.S. Department of Agriculture's Institute of Food Production and Sustainability (CFDA 10.212 - Small Business Innovation Research (SBIR) Program / Small Business Technology Transfer (STTR) Program) will develop a plant-by-plant, precision fertilization capability for cool season vegetable crops. The $600,000 award to Geovisual Technologies Inc. aims to increase harvest yields while reducing overall fertilizer application through innovative precision targeting...

This $720,462 Project Grant was awarded by the USDA National Institute of Food and Agriculture (NIFA) under the Agriculture and Food Research Initiative (AFRI) on July 1, 2024 to the University of Wisconsin System. The project aims to develop new methods and software to overcome technical obstacles in using genomic selection for breeding potato and blueberry crops. The key products to be delivered include: New computational methods and user-friendly software to calculate genomic inbreeding rates...

The U.S. Department of Agriculture's Organic Agriculture Research and Extension Initiative (CFDA 10.307) awarded a $1,999,277 Project Grant to Oregon State University to identify essential oil blends for suppressing premature potato tuber sprouting in storage and develop microencapsulation methods for delivering the optimal products. The 4-year project aims to: (1) discover and develop essential oil blends that effectively suppress potato sprouting; (2) microencapsulate the most effective blends...

This $324,213 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of a novel AI infrastructure to integrate multi-scale sensing data and 3D modeling for enhanced crop monitoring and assessment. The key products to be delivered include: An AI system that integrates satellite, drone, and in-situ sensor data to accurately model 3D crop structures, including both above- and below-ground...

This Project Grant award from the U.S. Department of Agriculture's National Institute of Food and Agriculture (CFDA 10.519 - Equipment Grants Program) provides $498,100 to Washington State University to acquire a new multi-camera robotic plant phenotyping instrument and supporting infrastructure. The advanced phenotyping platform will enable non-invasive automated monitoring of plant traits like photosynthesis, fluorescence, shoot anatomy, leaf temperature, transpiration, and biomass across a...