UAV Image-Based Crop Growth Analysis of 3D-Reconstructed Crop Canopies.

Plant growth rate is an essential phenotypic parameter for quantifying potential crop productivity. Under field conditions, manual measurement of plant growth rate is less accurate in most cases. Image-based high-throughput platforms offer great potential for rapid, non-destructive, and objective estimation of plant growth parameters.

Phenotyping Flowering in Canola ( L.) and Estimating Seed Yield Using an Unmanned Aerial Vehicle-Based Imagery.

Phenotyping crop performance is critical for line selection and variety development in plant breeding. Canola ( L.) flowers, the bright yellow flowers, indeterminately increase over a protracted period.

High-Throughput UAV Image-Based Method Is More Precise Than Manual Rating of Herbicide Tolerance.

The traditional visual rating system is labor-intensive, time-consuming, and prone to human error. Unmanned aerial vehicle (UAV) imagery-based vegetation indices (VI) have potential applications in high-throughput plant phenotyping. The study objective is to determine if UAV imagery provides accurate and consistent estimations of crop injury from herbicide application and its potential as an alternative to visual ratings.