Search Results

The primary objective of the investigation was to evaluate the effects of induced perturbations in air temperature on the development of the tomato plant, while correlating a plant feature for use with machine vision non-contact sensing technologies, and allow for eventual integration into a non-invasive plant-based environmental control system. Real-time information of plant growth responses to steady-state and changing air temperature regimes were measured (i.e. dry weight). There was a positive correlation of the profile machine vision images with dry weight. Therefore, machine vision could be used for plant developmental predictions and development of a control system for maintaining plant schedules.