ELECTRONIC NOSE CHEMICAL SENSOR FEASIBILITY STUDY FOR THE DIFFERENTIATION OF APPLE CULTIVARS

2005 ◽  
Vol 48 (5) ◽  
pp. 1995-2002 ◽  
Author(s):  
W. N. Marrazzo ◽  
P. H. Heinemann ◽  
R. E. Crassweller ◽  
E. LeBlanc
Keyword(s):  
Feasibility Study ◽  
Electronic Nose ◽  
Chemical Sensor ◽  
Apple Cultivars

ELECTRONIC NOSE CHEMICAL SENSOR VERSUS GAS CHROMATOGRAPHY: A FEASIBILITY STUDY FOR THE DIFFERENTIATION OF APPLE FLAVORS AND ESSENCES

2005 ◽  
Vol 48 (5) ◽  
pp. 2003-2006 ◽  
Author(s):  
W. N. Marrazzo ◽  
P. H. Heinemann ◽  
R. A. Saftner ◽  
R. E. Crassweller ◽  
E. Leblanc
Keyword(s):  
Gas Chromatography ◽  
Feasibility Study ◽  
Electronic Nose ◽  
Chemical Sensor

scholarly journals Identification and Quantification of Olive Oil Quality Parameters Using an Electronic Nose

Agriculture ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 674
Author(s):  
Nawaf Abu-Khalaf
Keyword(s):  
Olive Oil ◽  
Electronic Nose ◽  
Chemical Sensor ◽  
Chemical Constituents ◽  
Oil Quality ◽  
Quality Parameters ◽  
Signal Acquisition ◽  
Good Precision ◽  
Olive Oil Quality ◽  
Quality Categories

An electronic nose (EN), which is a kind of chemical sensor, was employed to check olive oil quality parameters. Fifty samples of olive oil, covering the four quality categories extra virgin, virgin, ordinary virgin and lampante, were gathered from different Palestinian cities. The samples were analysed chemically using routine tests and signals for each chemical were obtained using EN. Each signal acquisition represents the concentration of certain chemical constituents. Partial least squares (PLS) models were used to analyse both chemical and EN data. The results demonstrate that the EN was capable of modelling the acidity parameter with a good performance. The correlation coefficients of the PLS-1 model for acidity were 0.87 and 0.88 for calibration and validation sets, respectively. Furthermore, the values of the standard error of performance to standard deviation (RPD) for acidity were 2.61 and 2.68 for the calibration and the validation sets, respectively. It was found that two principal components (PCs) in the PLS-1 scores plot model explained 86% and 5% of EN and acidity variance, respectively. PLS-1 scores plot showed a high performance in classifying olive oil samples according to quality categories. The results demonstrated that EN can predict/model acidity with good precision. Additionally, EN was able to discriminate between diverse olive oil quality categories.

Feasibility study of doped SnO2 nanomaterial for electronic nose towards sensing biomarkers of lung cancer

2020 ◽  
Vol 31 (18) ◽  
pp. 15751-15763
Author(s):  
Zeenat Khatoon ◽  
H. Fouad ◽  
H. K. Seo ◽  
Mohamed Hashem ◽  
Z. A. Ansari ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Feasibility Study ◽  
Electronic Nose

scholarly journals Detecting recurrent head and neck cancer using electronic nose technology: A feasibility study

Head & Neck ◽  
2019 ◽  
Vol 41 (9) ◽  
pp. 2983-2990 ◽  
Author(s):  
Rens M. G. E. Goor ◽  
Joey C. A. Hardy ◽  
Michel R. A. Hooren ◽  
Bernd Kremer ◽  
Kenneth W. Kross
Keyword(s):  
Head And Neck Cancer ◽  
Head And Neck ◽  
Feasibility Study ◽  
Neck Cancer ◽  
Electronic Nose ◽  
Electronic Nose Technology ◽  
Recurrent Head

scholarly journals Temperature effect of electronic nose sampling for classifying mixture of beef and pork

2020 ◽  
Vol 19 (3) ◽  
pp. 1626
Author(s):  
Sinarring Azi Laga ◽  
Riyanarto Sarno
Keyword(s):  
Food Safety ◽  
Random Forest ◽  
Temperature Effect ◽  
Electronic Nose ◽  
Chemical Sensor ◽  
Temperature Sensors ◽  
Classification Method ◽  
Effect Of Temperature ◽  
Random Forest Method ◽  
Gas Interactions

Strong demand and strong price of raw foodstuffs like beef was commonly used in conventional markets by beef dealers to commit fraud in order to gain larger income. The fraud has been in the form of combining beef and pork. In Indonesia, this has been a issue of food health in recent years. Via scent, some food safety concerns can be expected. By using electronic nose that is equipped with electrochemical and air sensors  such as temperature sensors, strain, and humidity to find the pure beef or mixed beef. According to its selectivity, the sensor can detect gas to make small icurrents that are the result of chemical sensor and gas interactions with oxygen .In this study, the classification method k-NN, SVM, Naïve Bayes, and Random Forest was used in 5 different meat variations with a ratio of 0%, 10%, 50%, 90% and 100% with temperatures of -22°C, Room Temp., And 55 ° C. The results showed the effect of temperature on increasing the accuracy, which is at a temperature of -22 ° C. The lower the temperature, the more stable the value obtained by electronic nose. At a temperature of -22 ° C, the method that produces the highest accuracy is the Random Forest method.

scholarly journals A Novel Wearable Electronic Nose for Healthcare Based on Flexible Printed Chemical Sensor Array

Sensors ◽  
2014 ◽  
Vol 14 (10) ◽  
pp. 19700-19712 ◽  
Author(s):  
Panida Lorwongtragool ◽  
Enrico Sowade ◽  
Natthapol Watthanawisuth ◽  
Reinhard Baumann ◽  
Teerakiat Kerdcharoen
Keyword(s):  
Electronic Nose ◽  
Sensor Array ◽  
Chemical Sensor ◽  
Chemical Sensor Array ◽  
Wearable Electronic

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.

Investigation of Different Apple Cultivars by High Resolution Magic Angle Spinning NMR. A Feasibility Study

2011 ◽  
Vol 59 (24) ◽  
pp. 12784-12793 ◽  
Author(s):  
Martina Vermathen ◽  
Mattia Marzorati ◽  
Daniel Baumgartner ◽  
Claudia Good ◽  
Peter Vermathen
Keyword(s):  
High Resolution ◽  
Feasibility Study ◽  
Magic Angle Spinning ◽  
Magic Angle ◽  
Apple Cultivars ◽  
Angle Spinning
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