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

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.

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Electronic Nose Technologies in Monitoring Black Tea Manufacturing Process

Journal of Sensors ◽

10.1155/2020/3073104 ◽

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.

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

Sensors ◽

10.3390/s19112646 ◽

2019 ◽

Vol 19 (11) ◽

pp. 2646 ◽

Cited By ~ 8

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.

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Electronic nose based on metal oxide semiconductor sensors and pattern recognition techniques: characterisation of vegetable oils

Analytica Chimica Acta ◽

10.1016/s0003-2670(01)01355-1 ◽

2001 ◽

Vol 449 (1-2) ◽

pp. 69-80 ◽

Cited By ~ 72

Author(s):

Yolanda González Martı́n ◽

M.Concepción Cerrato Oliveros ◽

José Luis Pérez Pavón ◽

Carmelo Garcı́a Pinto ◽

Bernardo Moreno Cordero

Keyword(s):

Pattern Recognition ◽

Metal Oxide ◽

Vegetable Oils ◽

Electronic Nose ◽

Metal Oxide Semiconductor ◽

Oxide Semiconductor ◽

Pattern Recognition Techniques ◽

Semiconductor Sensors

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Weight Update Generation Circuit Utilizing Phase Noise of Integrated Complementary Metal–Oxide–Semiconductor Ring Oscillator for Memristor Crossbar Array Neural Network‐Based Stochastic Learning

Advanced Intelligent Systems ◽

10.1002/aisy.202000011 ◽

2020 ◽

Vol 2 (5) ◽

pp. 2000011

Author(s):

Woorham Bae ◽

Kyung Jean Yoon

Keyword(s):

Neural Network ◽

Metal Oxide ◽

Phase Noise ◽

Complementary Metal Oxide Semiconductor ◽

Metal Oxide Semiconductor ◽

Ring Oscillator ◽

Oxide Semiconductor ◽

Crossbar Array ◽

Stochastic Learning ◽

Memristor Crossbar

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Metal Oxide Semiconductor Based Electronic Nose as Classification and Prediction Instrument for Nicotine Concentration in Unflavoured Electronic Juice

2018 4th International Conference on Science and Technology (ICST) ◽

10.1109/icstc.2018.8528686 ◽

2018 ◽

Author(s):

Tisna Julian ◽

Shidiq Nur Hidayat ◽

Kuwat Triyana

Keyword(s):

Metal Oxide ◽

Electronic Nose ◽

Metal Oxide Semiconductor ◽

Oxide Semiconductor ◽

Nicotine Concentration

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Development Of Portable Electronic Nose Device For Perfume Odour Classification

Jurnal Teknologi ◽

10.11113/jt.v54.798 ◽

2012 ◽

Cited By ~ 2

Author(s):

Fauzan Khairi Che Harun ◽

Nur Atiqah Ibrahim ◽

Mohd Ariffanan Mohd Basri

Keyword(s):

Metal Oxide ◽

Gas Sensor ◽

Electronic Nose ◽

Current Source ◽

Metal Oxide Semiconductor ◽

Oxide Semiconductor ◽

Constant Current ◽

Constant Current Source ◽

Body Shop ◽

National Instrument

Artikel ini membentangkan pembangunan sebuah hidung elektronik (e–Hidung) mudah alih berdasarkan kad perolehan data National Instrument dan LabView. Kajian ini merangkumi rekabentuk litar e–Hidung yang terdiri daripada pelbagai jenis semikonduktor oksida logam daripada FIGARO sebagai sensor gas. Rintangan dari setiap sensor gas diukur melalui litar arus tetap yang dikawal melalui LabView. Sumber arus tetap digunakan sebagai antara muka elektronik bolehubah yang membolehkan pemetaan voltan keluaran sensor untuk profil rintangan sensor dilakukan secara tepat. Rintangan dari setiap sensor dikira secara tepat dan dipaparkan oleh LabView. Keputusan kajian menunjukkan bahawa e – Hidung yang dihasilkan boleh mengesan dan mengklasifikasikan antara dua jenama terkenal iaitu Body Shop dan Avon. Kaedah analisis komponen utama (PCA) yang digunakan menunjukkan diskriminasi besar iaitu 99.53% untuk bau tersebut. Ini menunjukkan bahawa sistem yang dihasilkan mampu membezakan baud an akan digunakan untuk tugas yang lebih kompleks pada masa akan datang. Kata kunci: Hidung elektronik; semikonduktor oksida logam; sensor gas; pengecaman corak; This paper presents the development of a portable electronic nose (e–Nose) based on a National Instrument data acquisition card and LabView. The study includes the design of e–Nose circuits that consist of different types of metal oxide semiconductor from FIGARO as gas sensors. The resistances of each gas sensor are measured through a constant current circuit controlled via LabView. The constant current source is used as an adaptive electronic interface that allows the accurate mapping of the sensor’s voltage output to sensor resistance profiles. The resistance of each sensor is accurately computed and displayed by LabView. The result of the study showed that the created e – Nose can detect and classify between two famous brands Body Shop and Avon. The applied principal component analysis (PCA) method shows great discrimination of 99.53% for the mentioned odour. This suggests that the system is able to discriminate between simple odours and will be use for a more complex task in the future. Key words: Electronic Nose: metal oxide semiconductor; gas sensor; pattern recognition; PCA

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Sensor array optimization and discrimination of apple juices according to variety by an electronic nose

Analytical Methods ◽

10.1039/c6ay02610a ◽

2017 ◽

Vol 9 (6) ◽

pp. 921-928 ◽

Cited By ~ 23

Author(s):

Hao Wu ◽

TianLi Yue ◽

Zhijiao Xu ◽

Chen Zhang

Keyword(s):

Metal Oxide ◽

Electronic Nose ◽

Chemical Sensors ◽

Apple Juice ◽

Sensor Array ◽

Metal Oxide Semiconductor ◽

Oxide Semiconductor ◽

Array Optimization ◽

Semiconductor Type

An electronic nose (PEN3) containing 10 metal oxide semiconductor type chemical sensors was used to discriminate between eight varieties of apple juice.

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