Arrays of Bio/Chemical Sensors: Uses and Strategies for Their Application

A special issue of Chemosensors (ISSN 2227-9040). This special issue belongs to the section "Applied Chemical Sensors".

Deadline for manuscript submissions: 30 April 2026 | Viewed by 122

Special Issue Editor

Special Issue Information

Dear Colleagues,

The development of chemical sensors has been a topic of great interest in recent decades. However, most systems rely on selective sensors for the determination of a particular parameter. A different strategy consists of the use of sensor arrays that allow us to measure different parameters at the same time or develop detection strategies based on pattern recognition. At the hardware level, this strategy allows for working with simpler, more versatile and lower-cost systems. At the software level, it benefits from the enormous development in data analytics and artificial intelligence observed in recent years. The development of noses and electronic languages among others is noteworthy. This Special Issue will provide a forum for the latest research activities in the field sensor arrays, their implementation, data analysis and applications. Both review articles and original research papers are solicited.

Dr. Jose V. Ros-Lis
Guest Editor

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Keywords

  • arrays
  • sensors
  • pattern recognition
  • data analysis
  • e-nose

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Published Papers (1 paper)

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Research

17 pages, 1079 KB  
Article
Early Detection of Monilinia laxa in Nectarine (Prunus persica var. nectarina) Using Electronic Nose Technology: A Non-Destructive Diagnostic Approach
by Ana Martínez, Alejandro Hernández, Patricia Arroyo, Jesús Lozano, Alberto Martín and María de Guía Córdoba
Chemosensors 2025, 13(11), 391; https://doi.org/10.3390/chemosensors13110391 - 7 Nov 2025
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 [...] Read more.
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. Full article
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