Evidence map›Paper›PMID 40895042›Full record

ArticlePeerJ2025

Utilizing E-nose for detection of mealybug infestation and ripeness of durian.

Chun-I Chiu, Thanchanok Yosen, Supatchaya Nampila, Jetsada Posom, Piyawan Suttiprapan, Yuwatida Sripontan

Abstract read
In one paragraph

Article in PeerJ, 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

6 authors.

Chun-I ChiuDepartment of Entomology and Plant Pathology, Faculty of Agriculture, Chiang Mai University, Chiang Mai, Thailand.ORCID 0000-0002-1603-0736
Thanchanok YosenCentral Laboratory, Faculty of Agriculture, Chiang Mai University, Chiang Mai, Thailand.ORCID 0000-0001-6284-862X
Supatchaya NampilaDepartment of Horticulture, Faculty of Agriculture, Khon Kaen University, Khon Kaen, Thailand.
Jetsada PosomDepartment of Agricultural Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen, Thailand.
Piyawan SuttiprapanDepartment of Entomology and Plant Pathology, Faculty of Agriculture, Chiang Mai University, Chiang Mai, Thailand.
Yuwatida SripontanDepartment of Entomology and Plant Pathology, Faculty of Agriculture, Khon Kaen University, Khon Kaen, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Mealybugs are major pests that cause sap loss and can significantly reduce the quality and market value of durian fruits. Early detection is essential for effective pest management. This study explores the impact of mealybug infestation on volatile emissions and evaluates the application of a low-cost electronic nose (E-nose) system for early infestation detection and ripeness monitoring. Methods: A prototype electronic nose (E-nose), equipped with four Grove Multichannel Gas Sensor V2 (GM) series sensors selected from a sensitivity survey of 13 sensors, was developed and tested on "Monthong" and "Kradum Thong" durians under outdoor and indoor conditions. Fruit odor signals were analyzed, and linear discriminant analysis (LDA) was used to assess classification performance. Results: The E-nose effectively differentiated odor profiles between infested and uninfested fruits and ripeness stages. Infested fruits exhibited a different trend of odor changes during ripening, likely due to stress-induced physiological responses. Discussion: This is the first study demonstrating the use of an E-nose for durian pest detection and ripeness monitoring. The E-nose shows strong potential as a cost-effective, non-destructive tool for early pest detection and postharvest quality control. Future work will focus on scaling the technology with robotic platforms for large-scale monitoring in farms and storage facilities.

Indexed as

Electronic NoseFruitHemipteraOdorantsAnimalsVolatile Organic CompoundsVolatile Organic CompoundsAgricultural technologyDurian fruitElectronic noseMealybug infestationPest detection

Identifiers

PMID40895042
PMCPMC12393072

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LicenceCC BY
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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.