scholarly journals Discriminatory power assessment of the sensor array of an electronic nose system for the detection of non alcoholic beer aging

2012 ◽  
Vol 30 (No. 3) ◽  
pp. 236-240 ◽  
Author(s):  
M. Ghasemi-Varnamkhasti ◽  
S.S. Mohtasebi ◽  
M. Siadat ◽  
S.H. Razavi ◽  
H. Ahmadi ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Electronic Nose ◽  
High Stability ◽  
Sensor Array ◽  
Principal Component ◽  
Discriminatory Power ◽  
Chemical Changes ◽  
Brewing Process ◽  
Electronic Nose System ◽  
And Control

Many chemical changes in beer aroma occur during storage (aging), and monitoring these changes could give guidelines to the brewers how to manage and control the brewing process to obtain the final product with a high stability in flavour after packaging. In this regard, our laboratory aimed at a research into the application of an electronic nose in order to get the fingerprint of the change of non alcoholic beer aroma during aging. Th discriminatory power of the sensor array of this system was evaluated. Principal Component Analysis (PCA) and Soft Independent Modelling of Class Analogy (SIMCA) techniques were used for this purpose. The results obtained can direct us to performing other parts of our project. Considering the discriminatory power of the sensor array used, we can develop the application of a specific electronic nose system by picking up the most effective sensors or ignoring the redundant sensors.

Differentiation between Cerebrospinal Fluid and Serum with Electronic Nose

2005 ◽  
Vol 133 (1) ◽  
pp. 16-19 ◽  
Author(s):  
Anna Aronzon ◽  
C. William Hanson ◽  
Erica R. Thaler
Keyword(s):  
Principal Component Analysis ◽  
Cerebrospinal Fluid ◽  
Electronic Nose ◽  
Clinical Setting ◽  
Sensor Array ◽  
Low Cost ◽  
Principal Component ◽  
Rapid Diagnosis ◽  
Novel Method ◽  
Csf Leaks

OBJECTIVE: The study investigates the ability of the electronic nose to differentiate between cerebrospinal fluid (CSF) and serum and to identify an unknown specimen as CSF or serum. STUDY DESIGN AND SETTING: CSF and serum specimens were heated and tested with an organic semiconductor-based Cyranose 320 electronic nose (Cyrons Sciences, Pasadena, CA). Data from the 32-element sensor array were subjected to principal component analysis to depict differences in odorant patterns. RESULTS: The electronic nose was able to distinguish between CSF and serum isolates with Mahalanobis distance >5. Furthermore, the electronic nose was able to place unknown specimens in the appropriate class of CSF or serum. CONCLUSIONS: The electronic nose is a novel method that may allow rapid, low cost, and reliable distinction between CSF and serum in a clinical setting. SIGNIFICANCE: Because the results are available almost immediately, the electronic nose is a powerful tool that in the future may allow for rapid diagnosis of CSF leaks in the office setting.

Development of Chemical Sensor Array for Rice Aroma Detection

2015 ◽  
Vol 1103 ◽  
pp. 15-20
Author(s):  
Panida Lorwongtragool ◽  
Teerakiat Kerdcharoen
Keyword(s):  
Electronic Nose ◽  
Sensor Array ◽  
Chemical Sensor ◽  
Principal Component ◽  
Sample Temperature ◽  
Rice Grain ◽  
Milled Rice ◽  
The Matrix ◽  
Electronic Nose System ◽  
Rice Aroma

Gas sensor array based on polymer/multi-walled carbon nanotubes (polymer/MWCNTs) composites prepared by screen printing technique was examined for rice aroma detection. The sensor array consists of two sets of three different sensors, i.e., MWCNTs dispersed in the matrix of poly (2-Acrylamido-2-methyl-1-propanesulfonic acid-co-acrylonitrile (S1-S2), polyvinyl alcohol (S3-S4) and poly (styreneco-maleic acid) partial isobutyl/methyl mixed ester (S5-S6). Sample temperature, which is one of the important parameters, has been found to influence the releasing rate of the volatiles from rice grain when needed to operate on the electronic nose system. In this case, the fabricated sensor array installed within a lab-made electronic nose system with optimum sample temperature at 70°C could provide rapid and best responses to the volatiles released from the milled rice sample. Moreover, the responsive signals could be recovered to original state as well within four minutes by only purging with fresh air at room temperature. Based on the principal component analysis (PCA) pattern recognition, it was shown that the electronic nose can discriminate six rice samples based on the content of aroma.

scholarly journals Discrimination between Alternative Herbal Medicines from Different Categories with the Electronic Nose

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2936 ◽  
Author(s):  
Xianghao Zhan ◽  
Xiaoqing Guan ◽  
Rumeng Wu ◽  
Zhan Wang ◽  
You Wang ◽  
...  
Keyword(s):  
Herbal Medicine ◽  
Electronic Nose ◽  
Nearest Neighbor ◽  
Herbal Medicines ◽  
Principal Component ◽  
Support Vector ◽  
Linear Discriminant ◽  
Convenient Means ◽  
Electronic Nose System ◽  
Insight Into

As alternative herbal medicine gains soar in popularity around the world, it is necessary to apply a fast and convenient means for classifying and evaluating herbal medicines. In this work, an electronic nose system with seven classification algorithms is used to discriminate between 12 categories of herbal medicines. The results show that these herbal medicines can be successfully classified, with support vector machine (SVM) and linear discriminant analysis (LDA) outperforming other algorithms in terms of accuracy. When principal component analysis (PCA) is used to lower the number of dimensions, the time cost for classification can be reduced while the data is visualized. Afterwards, conformal predictions based on 1NN (1-Nearest Neighbor) and 3NN (3-Nearest Neighbor) (CP-1NN and CP-3NN) are introduced. CP-1NN and CP-3NN provide additional, yet significant and reliable, information by giving the confidence and credibility associated with each prediction without sacrificing of accuracy. This research provides insight into the construction of a herbal medicine flavor library and gives methods and reference for future works.

scholarly journals Deteksi Formalin Pada Buah Tomat (Lycopersicum esculentum Mill) Dengan Teknologi Hidung Elektronik (Electronic Nose)

2019 ◽  
Vol 4 (2) ◽  
pp. 359-366
Author(s):  
Irfan Maibriadi ◽  
Ratna Ratna ◽  
Agus Arip Munawar
Keyword(s):  
Principal Component Analysis ◽  
Electronic Nose ◽  
Principal Component ◽  
Component Analysis ◽  
Lycopersicum Esculentum ◽  
Olfactory Ability ◽  
Pca Method ◽  
The Difference ◽  
Electronic Nose Technology

Abstrak,  Tujuan dari penelitian ini adalah mendeteksi kandungan dan kadar formalin pada buah tomat dengan menggunakan instrument berbasis teknologi Electronic nose. Penelitian ini menggunakan buah tomat yang telah direndam dengan formalin dengan kadar 0.5%, 1%, 2%, 3%, 4%, dan buah tomat tanpa perendaman dengan formalin (0%). Jumlah sampel yang digunakan pada penelitian ini adalah sebanyak 18 sampel. Pengukuran spektrum beras menggunakan sensor Piezoelectric Tranducer. Klasifikasi data spektrum buah tomat menggunakan metode Principal Component Analysis (PCA) dengan pretreatment nya adalah Gap Reduction. Hasil penelitian ini diperoleh yaitu: Hidung elektronik mulai merespon aroma formalin pada buah tomat pada detik ke-8.14, dan dapat mengklasifikasikan kandungan dan kadar formalin pada buah tomat pada detik ke 25.77. Hidung elektronik yang dikombinasikan dengan metode principal component analysis (PCA) telah berhasil mendeteksikandungan dan kadar formalin pada buah tomat dengan tingkat keberhasilan sebesar 99% (PC-1 sebesar 93% dan PC-2 sebesar 6%). Perbedaan kadar formalin menjadi faktor utama yang menyebabkan Elektronik nose mampu membedakan sampel buah tomat yang diuji, karena semakin tinggi kadar formalin pada buah tomat maka aroma khas dari buah tomat pun semakin menghilang, sehingga Electronic nose yang berbasis kemampuan penciuman dapat membedakannya.Detect Formaldehyde on Tomato (Lycopersicum esculentum Mill) With Electronic Nose TechnologyAbstract, The purpose of this study is to detect the contents and levels of formalin in tomatoes by using instruments based on Electronic nose technology. This study used tomatoes that have been soaked in formalin with a concentration of 0.5%, 1%, 2%, 3%, 4%, 5% and tomatoes without soaking with formalin (0%). The samples in this study were 18 samples. The measurements of the intensity on tomatoes aroma were using Piezoelectric Transducer sensors. The classification of tomato spectrum data was using the Principal Component Analysis (PCA) method with Gap Reduction pretreatment. The results of this study were obtained: the Electronic nose began to respond the smell of formalin on tomatoes at 8.14 seconds, and it could classify the content and formalin levels in tomatoes at 25.77 seconds. Electronic nose combined with the principal component analysis (PCA) method have successfully detected the content and levels of formalin in tomatoes with a success rate at 99% (PC-1 of 93% and PC-2 of 6%). The difference of grade formalin levels is the main factor that causes Electronic nose to be able to distinguish the tomato samples tested, because the higher of formalin content in tomatoes, the distinctive of tomatoes aroma is increasingly disappearing. Thereby, the Electronic nose based on  the olfactory ability can distinguish them. 

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