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Full-Text Articles in Engineering
Seabem: An Artificial Intelligence Powered Web Application To Predict Cover Crop Biomass, Aime Christian Tuyishime, Andrea Basche
Seabem: An Artificial Intelligence Powered Web Application To Predict Cover Crop Biomass, Aime Christian Tuyishime, Andrea Basche
Honors Theses
SEABEM, the Stacked Ensemble Algorithms Biomass Estimator Model, is a web application with a stacked ensemble of Machine Learning (ML) algorithms running on the backend to predict cover crop biomass for locations in Sub-Saharan. The SEABEM model was developed using a previously developed database of crop growth and yield that included site characteristics such as latitude, longitude, soil texture (sand, silt, and clay percentages), temperature, and precipitation. The goal of SEABEM is to provide global farmers, mainly small-scale African farmers, the knowledge they need before practicing and benefiting from cover crops while avoiding the expensive and time-consuming operations that come …
Dynamic Classification Of Moisture Stress Using Canopy And Leaf Temperature Responses To A Step Changes Of Incident Radiation, Erin E. Stevens, George E. Meyer, Ellen T. Paparozzi
Dynamic Classification Of Moisture Stress Using Canopy And Leaf Temperature Responses To A Step Changes Of Incident Radiation, Erin E. Stevens, George E. Meyer, Ellen T. Paparozzi
Honors Theses
Environmental conditions affect plant productivity and understanding how plants respond to drought stress can be measured in different ways. This study focused on measuring leaf response time to induced water stress. Leaf response time to a step increase and step decrease in radiation was computed for four species of well-watered and water-stressed plants in a controlled environment. The canopy temperature was measured with an infrared thermometer and a thermal imaging camera. Thermal images were analyzed to determine the average temperature of a selected single, unobstructed leaf at the top of the canopy. Both the canopy response time and the single …