Inovativní technologie pro efektivní hydroponické pěstování

The aim of the project will be to develop a machine-learning model that will be able to predict the deterioration of hydroponic media quality during pathogenic plant infection based on data obtained from inexpensive sensors. This project aims at efficient water management in relation to maintaining the quality of the grown material, considering the limitation of the biocides application. The project will install a hydroponic unit in a climate chamber where experiments with selected plant species will be carried out under controlled conditions. This unit will allow the repeated collection of information from selected sensors, which will be compared with data obtained from laboratory measurements. Simultaneously, the accuracy of low-cost sensors and their durability will be evaluated.