Plant stem tissue modeling and parameter identification using metaheuristic optimization algorithms

Abstract

Bio-impedance non-invasive measurement techniques usage is rapidly increasing in the agriculture industry. These measured impedance variations reflect tacit biochemical and biophysical changes of living and non-living tissues. Bio-impedance circuit modeling is an effective solution used in biology and medicine to fit the measured impedance. This paper proposes two new fractional-order bio-impedance plant stem models. These new models are compared with three commonly used bio-impedance fractional-order circuit models in plant modeling (Cole, Double Cole, and Fractional-order Double-shell). The two proposed models represent the characterization of the biological cellular morphology of the plant stem. Experiments are conducted on two samples of three different medical plant species from the family Lamiaceae, and each sample is measured at two inter-electrode spacing distances. Bio-impedance measurements are done using an electrochemical station (SP150) in the range of 100 Hz to 100 kHz. All employed models are compared by fitting the measured data to verify the efficiency of the proposed models in modeling the plant stem tissue. The proposed models give the best results in all inter-electrode spacing distances. Four different metaheuristic optimization algorithms are used in the fitting process to extract all models parameter and find the best optimization algorithm in the bio-impedance problems.

Plant impedance spectroscopy: a review of modeling approaches and applications

“…The optimal EEC parameters for the considered circuit are argmin κ F(κ). The Levenberg-Marquart algorithm ( Marquardt, 1963 ) is commonly used to solve this optimization problem, although many alternative algorithms have been proposed for bioimpedance analysis ( Yousri et al., 2019 ; Gadallah et al., 2022 ; Ghoneim et al., 2022 ). Most plant EIS studies use the above method for circuit parameter identification, typically through commercial or freely available software, such as LEVM/LEVMW ( MacDonald, 2013 ), EIS Spectrum Analyzer ( Bondarenko and Ragoisha, 2005 ), LabView ( Kodosky, 2020 ), or ZView ( Johnson, 2000 ).…”

A Mini-Review on Recent Fractional Models for Agri-Food Problems

“…The search process revealed a few different studies in the agri-food context that we cite here for the sake of completeness. In such studies, the adjective "fractional" is related to types of machine learning algorithms [10,11], regression models [12] or empirical models [13,14].…”

Plant Tissue Modelling Using Power-Law Filters

“…Despite that, the double-shell model did not provide efficient fitting results at low frequencies [ 13 ]. The Cole-Cole model was extended to the double dispersion impedance model to improve the accuracy over a wide range of frequencies [ 14 , 15 ]. By adding a Constant Phase Element (CPE) to the aforementioned models, better accuracy can be obtained.…”

“…Similar models were also proposed for modelling the electrode/tissue interface based in [ 20 , 21 ]. Plant stem was characterized through two fractional-order-based models in [ 15 ]. Fractional-order mathematical functions such as the Mittag-Leffler function were used in [ 22 ] to model the macroscale properties of complex and heterogeneous biological systems.…”

“…Some new algorithms such as the Flower pollination algorithm (FPA) and the Moth Flame optimization were also considered in [ 11 ]. The Water Cycle Algorithm (WCA) was deployed to extract equivalent plant stem model parameters in [ 15 ] and compared with other optimization algorithms.…”