Fractional-Order Equivalent Circuit Representation of Kohlrabi Tissue Samples

In an effort to investigate the electrical impedance properties of kohlrabi (Brassica oleracea var. gongylodes L.) plants, the range/variability of kohlrabi impedance from a collection of 16 similarly sized samples were explored. The impedance data was collected in a bipolar configuration interfacing copper wires into discs of sliced kohlrabi plants. An optimization algorithm was used to fit the collected data to a fractional-order equivalent circuit model. The model used to represent the approximated data consisted of a fractional-order capacitor in series with a parallel CPE-R. The electrical impedance of all samples represented by this model had less than 10% deviation in the band from 40 Hz to 1 MHz. Despite having similar dimensions and electrode configurations (material, insertion depth, spacing), there was a high variability (up to 70%) between fractional-order model parameters of the samples.

I. Introduction

The electrical impedance of a biological tissue, or tissue bioimpedance, refers to the passive electrical properties of the tissue. This property can be measured by applying a voltage (V) across a tissue under test and measuring the current (I) that is induced. Knowing both voltage and current, the impedance is calculated as: = / J. The electrical impedance of a tissue is dependent on factors including the type of tissue, cellular fluid, cell membranes, and cell intercon-nections. Based on these underlying associations of impedance with tissue physiology, these measurements are being widely investigated as potential indicators to quantify the quality of fruits, vegetables, and other food products. Recent research has investigated tissue bioimpedance to detect damage resulting from freezing in potatoes [1], track the ripening of apples and bananas [2], and quantify quality defects in freeze-thawed meat [3], highlighting how this technique is being investigated in this field. Beyond direct measurements of food products, this technique is also being investigated to evaluate the associations between beverages and their chemical composition [4] and the potential identification of contaminants [5].