  In this paper, system identification approach has been adopted to develop a
novel dynamical model for describing the relationship between light as an
environmental stimulus and the electrical response as the measured output for a
bay leaf (Laurus nobilis) plant. More specifically, the target is to predict
the characteristics of the input light stimulus (in terms of on-off timing,
duration and intensity) from the measured electrical response - leading to an
inverse problem. We explored two major classes of system estimators to develop
dynamical models - linear and nonlinear - and their several variants for
establishing a forward and also an inverse relationship between the light
stimulus and plant electrical response. The best class of models are given by
the Nonlinear Hammerstein-Wiener (NLHW) estimator showing good data fitting
results over other linear and nonlinear estimators in a statistical sense.
Consequently, a few set of models using different functional variants of NLHW
has been developed and their accuracy in detecting the on-off timing and
intensity of the input light stimulus are compared for 19 independent plant
datasets (including 2 additional species viz. Zamioculcas zamiifolia and
Cucumis sativus) under similar experimental scenario.
