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Early Detection of Monilinia laxa in Nectarine (Prunus persica var. nectarina) Using Electronic Nose Technology: A Non-Destructive Diagnostic Approach

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Title: Early Detection of Monilinia laxa in Nectarine (Prunus persica var. nectarina) Using Electronic Nose Technology: A Non-Destructive Diagnostic Approach
Authors: Ana Martínez, Alejandro Hernández, Patricia Arroyo, Jesús Lozano, Alberto Martín, María de Guía Córdoba
Source: Chemosensors, Vol 13, Iss 11, p 391 (2025)
Publisher Information: MDPI AG, 2025.
Publication Year: 2025
Collection: LCC:Biochemistry
Subject Terms: E-nose, volatile profile, early decay, nectarine, Monilinia laxa, Biochemistry, QD415-436
Description: This study evaluates the application of an electronic nose (E-nose) system as a non-destructive tool for the early detection of Monilinia laxa infection in yellow nectarines (Prunus persica var. nectarine, cv. “Kinolea”) through the analysis of volatile organic compounds (VOCs). Two experimental groups were established: a control group of healthy fruit and a treatment group inoculated with the pathogen. The VOCs emitted by both groups were identified and quantified using gas chromatography-mass spectrometry (GC-MS). Simultaneously, the responses of the E-nose were recorded at three critical stages of fungal development: early, intermediate, and advanced. The electronic nose used consists of a set of 11 commercial metal oxide semiconductor (MOX) sensors. The signals from these sensors showed a strong correlation with the VOC profiles associated with fungal deterioration. Linear discriminant analysis (LDA) models based on E-nose data successfully distinguished between healthy and infected samples with 97% accuracy. Furthermore, the system accurately classified samples into three stages of contamination—control, early infection, and advanced infection—with 96% classification accuracy. These findings demonstrate that E-nose technology is an effective, rapid, and non-invasive method for the real-time monitoring of post-harvest fungal contamination in nectarines, offering significant potential for improving quality control during storage and distribution.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2227-9040
Relation: https://www.mdpi.com/2227-9040/13/11/391; https://doaj.org/toc/2227-9040
DOI: 10.3390/chemosensors13110391
Access URL: https://doaj.org/article/7f8d4646e6604b8da2f5cc2d54386cec
Accession Number: edsdoj.7f8d4646e6604b8da2f5cc2d54386cec
Database: Directory of Open Access Journals
Description
Abstract:This study evaluates the application of an electronic nose (E-nose) system as a non-destructive tool for the early detection of Monilinia laxa infection in yellow nectarines (Prunus persica var. nectarine, cv. “Kinolea”) through the analysis of volatile organic compounds (VOCs). Two experimental groups were established: a control group of healthy fruit and a treatment group inoculated with the pathogen. The VOCs emitted by both groups were identified and quantified using gas chromatography-mass spectrometry (GC-MS). Simultaneously, the responses of the E-nose were recorded at three critical stages of fungal development: early, intermediate, and advanced. The electronic nose used consists of a set of 11 commercial metal oxide semiconductor (MOX) sensors. The signals from these sensors showed a strong correlation with the VOC profiles associated with fungal deterioration. Linear discriminant analysis (LDA) models based on E-nose data successfully distinguished between healthy and infected samples with 97% accuracy. Furthermore, the system accurately classified samples into three stages of contamination—control, early infection, and advanced infection—with 96% classification accuracy. These findings demonstrate that E-nose technology is an effective, rapid, and non-invasive method for the real-time monitoring of post-harvest fungal contamination in nectarines, offering significant potential for improving quality control during storage and distribution.
ISSN:22279040
DOI:10.3390/chemosensors13110391