Evaluation of experiments for estimation of dynamical crop model parameters

Planned experiments are usually expected to provide maximal benefits within limited costs. However, there are known difficulties in optimal design of experiments. They are related to the case when only limited number of parameters could be estimated, because available experiments are noninformative. The useful method for this case is considered based on the dominant parameters selection procedure (DPS). The methodology is illustrated here with data from five planned experiments related to the NICOLET lettuce growth model. The maximal number and the list of estimated parameters are determined while the conditional number of the information Fisher matrix (modified E-criterion) is kept below a given upper constraint.