Early detection of fish degradation by electronic nose

Zambotti, Giulia; Soprani, Matteo; Gobbi, Emanuela; Capuano, Rosamaria; Pasqualetti, Valentina; Natale, Corrado Di; Ponzoni, Andrea

doi:10.1109/isoen.2019.8823461

Cited by 17 publications

(13 citation statements)

References 4 publications

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“…In [40], quality grades of organic green teas was classified and evaluated by using electronic nose based on machine learning algorithms. In [41], the authors made early detection of fish degradation by electronic nose.…”

Section: The Related Applicationsmentioning

confidence: 99%

Using Recurrent Neural Network to Optimize Electronic Nose System with Dimensionality Reduction

Zou

2020

Electronics

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Electronic nose is an electronic olfactory system that simulates the biological olfactory mechanism, which mainly includes gas sensor, data pre-processing, and pattern recognition. In recent years, the proposals of electronic nose have been widely developed, which proves that electronic nose is a considerably important tool. However, the most recent studies concentrate on the applications of electronic nose, which gradually neglects the inherent technique improvement of electronic nose. Although there are some proposals on the technique improvement, they usually pay attention to the modification of gas sensor module and barely consider the improvement of the last two modules. Therefore, this paper optimizes the electronic nose system from the perspective of data pre-processing and pattern recognition. Recurrent neural network (RNN) is used to do pattern recognition and guarantee accuracy rate and stability. Regarding the high-dimensional data pre-processing, the method of locally linear embedding (LLE) is used to do dimensionality reduction. The experiments are made based on the real sensor drift dataset, and the results show that the proposed optimization mechanism not only has higher accuracy rate and stability, but also has lower response time than the three baselines. In addition, regarding the usage of RNN model, the experimental results also show its efficiency in terms of recall ratio, precision ratio, and F1 value.

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Section: The Related Applicationsmentioning

confidence: 99%

Using Recurrent Neural Network to Optimize Electronic Nose System with Dimensionality Reduction

Zou

2020

Electronics

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“…Para la detección temprana de la degradación de productos agroalimentarios se han desarrollado trabajos como el del caso de Zambotti y Dinatale, los cuales crearon un protocolo para medir y rastrear la contaminación microbiana en peces a través de la miniaturización de una Nariz Electrónica con bajo consumo de energía [13]. En otra investigación bajo la misma área, se realizó una evaluación de una matriz de ocho sensores diferentes de semiconductores de óxido de metal (MOS) para la detección rápida de la adulteración en el jarabe de uva.…”

Section: Aplicaciones De Los Sistemas De Olfato Electrónicounclassified

Análisis de volátiles en el proceso de fermentado de cacao, mediante una nariz electrónica para el control de calidad del producto en Norte de Santander-Cúcuta

2020

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El presente estudio consiste de una nariz electrónica compuesta de 10 sensores de gases de tipo MQ para la clasificación de muestras de CLON ICS-95 de cacao. El desarrollo de las pruebas fue de tipo cualitativo, obteniendo una huella digital que caracterizó cada clase, las cuales fueron: Fermentado deseado: 144 horas, sobre-fermentado y mala fermentación cacao infectado con monilia. Todos los sensores usados en las diferentes pruebas fueron de material de óxidos metálicos con capacidad de medir diversos tipos de gases, butanos, propanos, alcoholes, monóxido de carbono en diferentes concentraciones, donde al hacer contacto con los volátiles asociados producen una alteración en el voltaje de salida. Las señales se adquirieron mediante un sistema de adquisición de datos basado en tarjeta Arduino y uso del software Labview, permitiendo el almacenamiento de los datos. El algoritmo para la extracción de parámetros, pre-procesamiento y procesamiento de datos se realizó mediante el uso de software Python. Los resultados se analizaron implementando análisis de componente principales PCA y ejecución de dos métodos de pre-procesamiento de datos, como el centrado y escalado de datos, logrando un porcentaje de varianza en los componentes principales de 97.8% y con el método Manhattan se obtuvo un 93.8% del porcentaje de varianza en la componente principal PC1. Con estos resultados se logró observar que el sistema de olfato electrónico fue capaz de clasificar los datos de acuerdo a las clases definidas, fermentado deseado: 144 horas, sobre-fermentado y mala fermentación cacao infectado con monilia

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“…Conventionally, gas mixtures have been analysed using techniques such as gas chromatography (GC) [13], ion mobility spectrometry (IMS) [14], and proton-transfer-reaction mass spectrometry (PTR-MS) [15]. These approaches provide qualitative and quantitative analysis of vapours but require expert personnel and have high operational cost and time consuming sample preparation and analysis [16]. Furthermore, they are also bulky and need frequent calibration [2].…”

Section: Introductionmentioning

confidence: 99%

An Outlook of Recent Advances in Chemiresistive Sensor-Based Electronic Nose Systems for Food Quality and Environmental Monitoring

John

Murugappan

Nisbet

et al. 2021

Sensors

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An electronic nose (Enose) relies on the use of an array of partially selective chemical gas sensors for identification of various chemical compounds, including volatile organic compounds in gas mixtures. They have been proposed as a portable low-cost technology to analyse complex odours in the food industry and for environmental monitoring. Recent advances in nanofabrication, sensor and microcircuitry design, neural networks, and system integration have considerably improved the efficacy of Enose devices. Here, we highlight different types of semiconducting metal oxides as well as their sensing mechanism and integration into Enose systems, including different pattern recognition techniques employed for data analysis. We offer a critical perspective of state-of-the-art commercial and custom-made Enoses, identifying current challenges for the broader uptake and use of Enose systems in a variety of applications.

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Early detection of fish degradation by electronic nose

Cited by 17 publications

References 4 publications

Using Recurrent Neural Network to Optimize Electronic Nose System with Dimensionality Reduction

Using Recurrent Neural Network to Optimize Electronic Nose System with Dimensionality Reduction

Análisis de volátiles en el proceso de fermentado de cacao, mediante una nariz electrónica para el control de calidad del producto en Norte de Santander-Cúcuta

An Outlook of Recent Advances in Chemiresistive Sensor-Based Electronic Nose Systems for Food Quality and Environmental Monitoring

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