Monitoring of plant development in controlled environment with machine vision

Information acquisition is the foremost requirement for the control and continued operation of any complex system. This is especially true when a plant production system is used as a major component in a sustainable life support system. The plant production system not only provides food and fiber but is a means of providing critically needed life supporting elements such as O2 and purified H2O. The success of the plant production system relies on close monitoring and control of the production system. Machine vision technology was evaluated for the monitoring of plant health and development and showed promising results. Spectral and morphological characteristics of a model plant were studied under various artificially induced stress conditions. From the spectroscopic studies, it was found that the stresses can be determined from visual and non-visual symptoms. The development of the plant can also be quantified using a video image analysis base approach. The correlations between the qualities of the model plant and machine vision measured spectral features were established. The success of the research has shown a great potential in building an automated, closed-loop plant production system in controlled environments.