AI Based Solution to Optimize the Fertilizer Composition in Hydroponics Agriculture.

Precision agriculture is one of the trending research areas in the world. AI technologies have been applied to greenhouse hydroponics agriculture (which comes under precision agriculture) to control the requirements of the plants in greenhouse agriculture. Apart from the environmental conditions such as temperature, humidity, and light intensity, the optimum combination of the fertilizer components, EC, and pH value provided during the plants’ growth phase is vital to obtaining a higher yield during the harvesting period. However, finding the optimal fertilizer composition is challenging due to the fact that the required fertilizer composition is different for different plant types and the experimental cost is higher. Sparse data samples will be received in data-driven experiments because of the large search space (number of permutations) of the fertilizer combinations. This paper presents an experimental design and AI based solution to find the optimal fertilizer composition for the lettuce plants in hydroponics agriculture. Further, this paper presents preliminary ANOVA analysis results and the designed AI algorithm which is based on Bayesian Neural Network, kNN algorithm, and Particle Swarm Optimization algorithm.