scholarly journals Electronic Nose Technologies in Monitoring Black Tea Manufacturing Process

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Tharaga Sharmilan ◽  
Iresha Premarathne ◽  
Indika Wanniarachchi ◽  
Sandya Kumari ◽  
Dakshika Wanniarachchi
Keyword(s):  
Neural Network ◽  
Electronic Nose ◽  
Gas Sensors ◽  
Black Tea ◽  
Quality Parameters ◽  
Polyphenolic Compounds ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
Optimum Level ◽  
Fermentation Stage

“Tea” is a beverage which has a unique taste and aroma. The conventional method of tea manufacturing involves several stages. These are plucking, withering, rolling, fermentation, and finally firing. The quality parameters of tea (color, taste, and aroma) are developed during the fermentation stage where polyphenolic compounds are oxidized when exposed to air. Thus, controlling the fermentation stage will result in more consistent production of quality tea. The level of fermentation is often detected by humans as “first” and “second” noses as two distinct smell peaks appear during fermentation. The detection of the “second” aroma peak at the optimum fermentation is less consistent when decided by humans. Thus, an electronic nose is introduced to find the optimum level of fermentation detecting the variation in the aroma level. In this review, it is found that the systems developed are capable of detecting variation of the aroma level using an array of metal oxide semiconductor (MOS) gas sensors using different statistical and neural network techniques (SVD, 2-NM, MDM, PCA, SVM, RBF, SOM, PNN, and Recurrent Elman) successfully.

scholarly journals A Prototype to Detect the Alcohol Content of Beers Based on an Electronic Nose

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2646 ◽  
Author(s):  
Henike Guilherme Jordan Voss ◽  
José Jair Alves Mendes Júnior ◽  
Murilo Eduardo Farinelli ◽  
Sergio Luiz Stevan
Keyword(s):  
Metal Oxide ◽  
Electronic Nose ◽  
Gas Sensors ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
Alcohol Content ◽  
Electronic Noses

Due to the emergence of new microbreweries in the Brazilian market, there is a need to construct equipment to quickly and accurately identify the alcohol content in beverages, together with a reduced marketing cost. Towards this purpose, the electronic noses prove to be the most suitable equipment for this situation. In this work, a prototype was developed to detect the concentration of ethanol in a high spectrum of beers presents in the market. It was used cheap and easy-to-acquire 13 gas sensors made with a metal oxide semiconductor (MOS). Samples with 15 predetermined alcohol contents were used for the training and construction of the models. For validation, seven different commercial beverages were used. The correlation (R2) of 0.888 for the MLR (RMSE = 0.45) and the error of 5.47% for the ELM (RMSE = 0.33) demonstrate that the equipment can be an effective tool for detecting the levels of alcohol contained in beverages.

scholarly journals Characterization of Unpleasant Odors in Poultry Houses Using Metal Oxide Semiconductor-Based Gas Sensor Arrays and Pattern Recognition Methods

2021 ◽  
Vol 5 (1) ◽  
pp. 52
Author(s):  
Mohammed Moufid ◽  
Carlo Tiebe ◽  
Nezha El Bari ◽  
Matthias Bartholmai ◽  
Benachir Bouchikhi
Keyword(s):  
Electronic Nose ◽  
Gas Sensors ◽  
Sensor Arrays ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
Pattern Recognition Methods ◽  
Poultry Farms ◽  
Odor Emissions ◽  
The Impact

In this study, the ability of an electronic nose developed to analyze and monitor odor emissions from three poultry farms located in Meknes (Morocco) and Berlin (Germany) was evaluated. Indeed, the potentiality of the electronic nose (e-nose) to differentiate the concentration fractions of hydrogen sulfide, ammonia, and ethanol was investigated. Furthermore, the impact change of relative humidity values (from 15% to 67%) on the responses of the gas sensors was reported and revealed that the effect remained less than 0.6%. Furthermore, the relevant results confirmed that the developed e-nose system was able to perfectly classify and monitor the odorous air of poultry farms.

scholarly journals Practical discrimination of good and bad cooked food using metal oxide semiconductor odour sensor

2013 ◽  
pp. 39-47 ◽  
Author(s):  
Ima Essiet ◽  
Ado Dan-Isa
Keyword(s):  
Neural Network ◽  
Metal Oxide ◽  
Success Rate ◽  
Electronic Nose ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
Test Results ◽  
Direct Proportion ◽  
Cooked Food ◽  
Average Success Rate

An increasing concentration of ammonia in cooked food is in direct proportion to the extent of decay. This fact is used to design an electronic nose (e-nose) based on metal oxide semiconductor odour sensor circuit capable of discriminating good and bad cooked food. On the basis of the data produced by the e-nose circuit, a feedforward multilayer neural network is designed and trained to recognize varying concentrations of ammonia in the food. Test results of the prototype e-nose system show that it is capable of classifying cooked food as being good or bad with over 92% average success rate.

scholarly journals Mixed Odor Classification for QCM Sensor Data by Neural Network

2013 ◽  
Vol 1 (2) ◽  
pp. 43-48
Author(s):  
Sigeru Omatu ◽  
Hideo Araki ◽  
Toru Fujinaka ◽  
Mitsuaki Yano ◽  
Michifumi Yoshioka ◽  
...  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Metal Oxide ◽  
Gas Sensors ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
Sensor Data ◽  
The Neural Network ◽  
Odor Classification ◽  
Semiconductor Gas Sensors

Compared with metal oxide semiconductor gas sensors, quarts crystal microbalance (QCM) sensors are sensitive for odors. Using an array of QCM sensors, we measure mixed odors and classify them into an original odor class beforemixing based on neural networks. For simplicity we consider the case that two kinds of odor are mixed since more than two becomes too complex to analyze the classification results. We have used eight sensors and four kinds of odor are used as the original odors. The neural network used here is a conventional layered neural network. The classification is acceptable although the perfect classification could not been achieved.

A hybrid electronic nose system for discrimination of pathogenic bacterial volatile compounds

2020 ◽  
Vol 12 (47) ◽  
pp. 5671-5683
Author(s):  
Thara Seesaard ◽  
Chadinee Thippakorn ◽  
Teerakiat Kerdcharoen ◽  
Sumana Kladsomboon
Keyword(s):  
Metal Oxide ◽  
Volatile Compounds ◽  
Electronic Nose ◽  
Gas Sensors ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
Semiconductor Gas Sensors ◽  
Electronic Nose System

Self-built hybrid electronic nose prototypes equipped with organic–inorganic nanocomposite gas sensors and metal-oxide semiconductor gas sensors for bacterial discrimination.

scholarly journals Field Study of Metal Oxide Semiconductor Gas Sensors in Temperature Cycled Operation for Selective VOC Monitoring in Indoor Air

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 647
Author(s):  
Tobias Baur ◽  
Johannes Amann ◽  
Caroline Schultealbert ◽  
Andreas Schütze
Keyword(s):  
Air Quality ◽  
Metal Oxide ◽  
Gas Sensor ◽  
Gas Sensors ◽  
Indoor Air ◽  
Ambient Air ◽  
Quantitative Agreement ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
High Temporal Resolution

More and more metal oxide semiconductor (MOS) gas sensors with digital interfaces are entering the market for indoor air quality (IAQ) monitoring. These sensors are intended to measure volatile organic compounds (VOCs) in indoor air, an important air quality factor. However, their standard operating mode often does not make full use of their true capabilities. More sophisticated operation modes, extensive calibration and advanced data evaluation can significantly improve VOC measurements and, furthermore, achieve selective measurements of single gases or at least types of VOCs. This study provides an overview of the potential and limits of MOS gas sensors for IAQ monitoring using temperature cycled operation (TCO), calibration with randomized exposure and data-based models trained with advanced machine learning. After lab calibration, a commercial digital gas sensor with four different gas-sensitive layers was tested in the field over several weeks. In addition to monitoring normal ambient air, release tests were performed with compounds that were included in the lab calibration, but also with additional VOCs. The tests were accompanied by different analytical systems (GC-MS with Tenax sampling, mobile GC-PID and GC-RCP). The results show quantitative agreement between analytical systems and the MOS gas sensor system. The study shows that MOS sensors are highly suitable for determining the overall VOC concentrations with high temporal resolution and, with some restrictions, also for selective measurements of individual components.

scholarly journals Synthesis of Metal Oxide Semiconductor Nanostructures for Gas Sensors

Gas Sensors ◽  
2020 ◽  
Author(s):  
Nazar Abbas Shah ◽  
Majeed Gul ◽  
Murrawat Abbas ◽  
Muhammad Amin
Keyword(s):  
Metal Oxide ◽  
Gas Sensors ◽  
Semiconductor Nanostructures ◽  
Metal Oxide Semiconductor ◽  
Oxide Semiconductor
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