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Updated: Jul 16, 2026

Fruit Volatile Analysis Using an Electronic Nose
Published on: March 30, 2012
Electrical Impedance Spectroscopy and Tomography for Fruit Quality Monitoring: A State-of-the-Art Analysis and
Giovanni Chiorboli1, Nicola Delmonte1, Andrea Toscani1
1Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy.
None:
Non-invasive Electrical Impedance Tomography (EIT) and Electrical Impedance Spectroscopy (EIS) are emerging as promising techniques for real-time monitoring and quality assessment in food processing and agri-food applications. This study reviews recent advances in impedance-based sensing for fruit characterization and investigates the experimental implementation of multi-electrode impedance measurements for tomographic imaging. Particular attention is devoted to electrode configurations, electrode polarization effects, and equivalent circuit modeling. Experimental measurements were performed on yellow honeydew melon samples using a four-electrode configuration and a impedance analyzer Keysight E4990 (Keysight Technologies, Santa Rosa, USA) over the frequency range from 20 Hz to 1 MHz. The impedance spectra were validated through Kramers-Kronig consistency tests and interpolated using several fractional-order equivalent circuit models, including single-Cole, double-Cole, and Hayden-based models. The results show that four-electrode measurements are less sensitive to electrode-sample interface artifacts than conventional two-electrode approaches, thereby providing a more reliable estimate of the sample impedance, particularly at low frequencies. Among the tested models, the double-Cole model provided the best interpolation accuracy, while the fractional Hayden models effectively described the temporal evolution of extracellular resistance and membrane-related parameters. Preliminary EIT reconstructions further demonstrate the feasibility of non-destructive tomographic imaging for fruit monitoring. These findings support the potential of EIS and EIT as low-cost, portable, and non-invasive tools for smart food quality assessment and precision agriculture applications.

