Evidence map›Paper›PMID 40648452›Full record

ArticleSensors (Basel, Switzerland)2025

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

Tianyang Lu, Adam D Fletcher, Richard John Colgan, Michael D O'Toole

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Tianyang LuDepartment of Electronic and Electrical Engineering, University of Manchester, Manchester M13 9PL, UK.ORCID 0009-0006-4861-6084
Adam D FletcherDepartment of Electronic and Electrical Engineering, University of Manchester, Manchester M13 9PL, UK.ORCID 0000-0002-2285-2090
Richard John ColganNatural Resources Institute, University of Greenwich, Medway Campus, Central Avenue Chatham Maritime, Kent ME4 4TB, UK.ORCID 0000-0002-0653-5845
Michael D O'TooleDepartment of Electronic and Electrical Engineering, University of Manchester, Manchester M13 9PL, UK.ORCID 0000-0001-6397-7431

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

FruitPerseaSpectrum AnalysisElectric Conductivityavocado fruit assessmentbioimpedance (BIS)dispersioneddy-currentmagnetic induction spectroscopy (MIS)non-contact testingpermittivity membrane behavior

Identifiers

PMID40648452
PMCPMC12252501

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.