Faculty Mentor Information
John Shovic, University of Idaho
Additional Funding Sources
This project was funded thanks to an Office of Undergraduate Research SURF grant in the summer of 2023.
Presentation Date
7-2023
Abstract
Remote sensing systems for precision agriculture allow for technology and automation to improve the profitability and sustainability of modern farms. The adoption of these systems in the United States has been slow, due to the high cost of and difficulty using them. The University of Idaho, in collaboration with Laurel Grove Wine Farm in Winchester, Virginia, has been in the process of developing a remote sensing system which has been designed to be low-cost and flexible in its agricultural applications. This new system lacks deterministic testing results for (1) reliability, (2) overall cost, and (3) usability by farmers. This research project aims to test the system’s performance in a new application domain: a heritage apple orchard at Sandpoint Organic Agriculture Center. This project will test the performance, cost, and usability of the remote sensing system to determine its viability of use in other agricultural settings.
Precision Agriculture Adoption and Integration Case Study
Remote sensing systems for precision agriculture allow for technology and automation to improve the profitability and sustainability of modern farms. The adoption of these systems in the United States has been slow, due to the high cost of and difficulty using them. The University of Idaho, in collaboration with Laurel Grove Wine Farm in Winchester, Virginia, has been in the process of developing a remote sensing system which has been designed to be low-cost and flexible in its agricultural applications. This new system lacks deterministic testing results for (1) reliability, (2) overall cost, and (3) usability by farmers. This research project aims to test the system’s performance in a new application domain: a heritage apple orchard at Sandpoint Organic Agriculture Center. This project will test the performance, cost, and usability of the remote sensing system to determine its viability of use in other agricultural settings.