Real-Time Root Growth Monitoring of Hydroponic Tomato Plants

Hydroponic farming is a prime alternative to traditional agriculture, as it uses far less space and water when comparing the two methods by yield, pound for pound. One problem in this area is the current inspection techniques for root health and growth. Current phenology monitoring techniques require a worker to remove the plant from the medium, which can stress the plant and lead to further complications. Therefore, we are developing an imaging system capable of capturing root images in situ in the growing environment, alleviating the above problems with the practices of the status quo. This system consists of an inner transparent dome structure and an outer PVC tube in which the hydroponic tomato plant, in a 6 inch net pot, is placed upon. The outer tube is filled with the growing solution mixture, and inside the dome structure is a camera capable of 360 degree imaging. This system is capable of processing root images using computer vision algorithms to measure the length, thickness, and growth rate of primary and capillary roots. One application is timing when the root-tips begin to swell, which is indicative of Al-toxicity. From this data we will use machine learning algorithms to further analyze the data for correlations and other predictive factors that would otherwise not be found with traditional analysis techniques. We plan to create benchmark growth tables that will be made available to the community, improving the quality of food production and sustainability.