| Affiliations: | Genetics & Genomics Research Leadership |
| Project Leader: | Aaron DeSalvio aarondesalvio@tamu.edu |
| Faculty Mentor: | Seth Murray, Ph.D. |
|
Meeting Times:
|
TBA |
|
Team Size:
|
3
|
| Open Spots: | 0 |
|
Special Opportunities:
|
Students that become proficient in image analysis and data processing will be eligible for co-authorship on publications stemming from this project. |
|
Team Needs:
|
Team members must be proficient with data organization, use of Microsoft products, and must be willing to learn how to use GIS software such as QGIS and Agisoft Metashape. |
|
Description:
|
Phenomics, which is the study of spectral signatures of plants using data generally obtained from unoccupied aerial vehicles (UAVs, or drones), is an emerging method of data analysis aimed at predicting economically relevant agronomic traits in crops. Until now, phenomics has focused on whole plot-based image analysis, where many plants are grown in a plot within an agricultural experiment and spectral data are extracted that represent an average value for the entire plot. However, significant plant-to-plant variation is often observed within a plot, and it is likely that condensing the spectral data into a single average value results in overlooked phenotypic differences between plants. This project seeks to characterize single plant differences and potentially identify outliers or mutants at the single plant level. This could enable early-generation selection of plants and potentially help identify better-adapted plants by advancing only individuals that display desired characteristics, such as higher grain yield or disease resistance. |