# Magnetic Induction Spectroscopy-Based Non-Contact Assessment of Avocado Fruit Condition

## TL;DR

This paper shows how a non-contact method called Magnetic Induction Spectroscopy can assess avocado ripeness by measuring electrical properties without touching the fruit.

## Contribution

The study introduces a non-contact MIS technique for avocado ripeness assessment, revealing distinct electrical changes during ripening stages.

## Key findings

- Avocado ripeness can be tracked through changes in conductivity and permittivity measured via MIS.
- Three ripening stages are identified based on spectral trends and normalized gradient analysis.
- Equivalent circuit modeling shows ripening involves weakened capacitive structures and increased extracellular conductivity.

## Abstract

This study demonstrates that the ripeness of avocado fruits can be analyzed using frequency-dependent electrical conductivity and permittivity through a non-invasive Magnetic Induction Spectroscopy (MIS) method. Utilizing an MIS system for conductivity and permittivity measurements of a large sample set (N=60) of avocado fruits across multiple frequencies from 100 kHz to 3 MHz enables clear observation of their dispersion behavior and the evolution of their spectra over ripening time in a completely non-contact manner. For the entire sample batch, the conductivity spectrum exhibits a general upward shift and spectral flattening over ripening time. To further quantify these features, normalized gradient analysis and equivalent circuit modeling were employed, and statistical analysis confirmed the correlations between electrical parameters and ripening stages. The trend characteristics of the normalized gradient parameter Py provide a basis for defining the three ripening stages within the 22-day period: early pre-ripe stage (0–5 days), ripe stage (5–15 days), and overripe stage (after 15 days). The equivalent circuit model, which is both physically interpretable and fitted to experimental data, revealed that the ripening process of avocado fruits is characterized by a weakening of capacitive structures and an increase in extracellular solution conductivity, suggesting changes in cellular integrity and extracellular composition, respectively. The results also highlight significant inter-sample variability, which is inherent to biological samples. To further investigate individual conductivity variation trends, Gaussian Mixture Model (GMM) clustering and Principal Component Analysis (PCA) was conducted for exploratory sample classification and visualization. Through this approach, the sample set was classified into three categories, each corresponding to distinct conductivity variation patterns.