Parameter Estimation of a Dynamic Growth Model for Lettuce in an Adaptive Vertical Farm

We introduce the adaptive vertical farm (AVF), an innovative and sustainable vertical farming technology, and investigate parameter estimation for a dynamic crop growth model of lettuce. The goal is to tune parameters for accurate height prediction based on dry mass production. We numerically study the identifiability of the parameters of the growth model starting from information collected on the field, and then use the identified model to forecast the growth of plants using real-world measurements. Parameter estimation is performed by solving an optimization problem that aims at minimizing the difference between the measured and predicted dry mass over a given temporal window. Preliminary numerical results demonstrate the effectiveness of the proposed approach using both synthetic and real-world datasets.