dc.contributor.author | Chatterjee, SK | |
dc.contributor.author | Ghosh, S | |
dc.contributor.author | Das, S | |
dc.contributor.author | Manzella, V | |
dc.contributor.author | Vitaletti, A | |
dc.contributor.author | Masi, E | |
dc.contributor.author | Santopolo, L | |
dc.contributor.author | Mancuso, S | |
dc.contributor.author | Maharatna, K | |
dc.date.accessioned | 2018-01-19T14:21:16Z | |
dc.date.issued | 2014-03-04 | |
dc.description.abstract | 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. | en_GB |
dc.description.sponsorship | The work reported in this paper was supported by project PLants Employed As SEnsor Devices (PLEASED), EC grant agreement number 296582. | en_GB |
dc.identifier.citation | Vol. 53, pp. 101-116 | en_GB |
dc.identifier.doi | 10.1016/j.measurement.2014.03.040 | |
dc.identifier.uri | http://hdl.handle.net/10871/31095 | |
dc.language.iso | en | en_GB |
dc.publisher | Elsevier for International Measurement Confederation (IMEKO) | en_GB |
dc.relation.source | The data on experiments on lights are available in the PLEASED website at http://pleased-fp7.eu/?page_id=253. | en_GB |
dc.rights | Copyright © 2014 Elsevier Ltd. All rights reserved. | en_GB |
dc.subject | Dynamical modelling | en_GB |
dc.subject | Environment prediction | en_GB |
dc.subject | Inverse model | en_GB |
dc.subject | Plant electrical signal | en_GB |
dc.subject | Statistical estimators | en_GB |
dc.subject | System identification | en_GB |
dc.title | Forward and Inverse Modelling Approaches for Prediction of Light Stimulus from Electrophysiological Response in Plants | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2018-01-19T14:21:16Z | |
dc.description | This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record. | en_GB |
dc.identifier.journal | Measurement | en_GB |