Haley Schuhl

This paper uses UAS to measure tef growth and lodging, showing early height can predict lodging and that low-cost UAS can accurately measure lodging severity.

PlantCV v4 improves usability and functionality for plant phenotyping by adding new image types and tutorials for non-coding researchers.

The paper demonstrates a smartphone-based image capture system and two image analysis pipelines for efficient and accurate plant phenotyping in large field experiments.

The paper uses seed color and morphology data from image scans to predict germination traits in perennial crops, showing improved prediction accuracy when combining HSV color features with morphology.

The paper develops a phytomeric growth model integrated with high-throughput phenotyping to better estimate water use efficiency and identify genetic factors influencing plant size and drought response in Setaria.