Peaceful Ntshangase is currently conducting MSc research focused on drought stress detection in eucalyptus seedlings using advanced digital phenotyping and machine learning approaches. The study investigates the physiological and structural responses of different eucalyptus genotypes under both well-watered and drought-stressed conditions within a controlled glasshouse environment.

The research makes use of the PlantEye F600 multispectral 3D scanner to capture a range of growth and health-related traits, including plant height, digital biomass, leaf area, NDVI, chlorophyll-associated indices, and canopy structure. In addition, physiological measurements such as stomatal conductance, photosynthetic activity, and soil moisture content are collected using the LI-600 porometer/fluorometer and HydroSense sensor.

By integrating high-throughput phenotyping data with machine learning techniques, the project aims to determine whether drought stress in eucalyptus seedlings can be identified before severe visible symptoms develop. The broader goal of the research is to contribute towards more climate-resilient forestry systems and support the development of precision phenotyping tools for future forestry and plant science applications.


