TY - JOUR
T1 - Evaluation of a commercial electronic nose system coupled with universal gas sensing chamber for sensing indicator compounds associated with meat safety
AU - Mohapatra, Punyatoya
AU - Panigrahi, Suranjan
AU - Amamcharla, Jayendra
N1 - Publisher Copyright:
© 2014, Springer Science+Business Media New York.
PY - 2015/6/1
Y1 - 2015/6/1
N2 - This study was conducted to evaluate the performance of a commercial electronic nose (Cyranose 320™) for sensing indicator compounds (ethanol and acetic acid) associated with spoiled beef. The present study reported the sensitivity of an array of 32 sensors to ethanol and acetic acid. Different vapor concentrations of ethanol (37, 100, 250 and 500 ppm) and acetic acid (38, 75, 100, 200 and 300 ppm) were tested to evaluate the performance of the commercial system. An in-house designed universal gas sensing and characterization system was coupled with the electronic nose system to generate the desired gas concentration. The raw smell print patterns were obtained and analyzed for individual and multiple detectors. Tukey’s multiple comparison technique was performed to analyze the response of individual detectors. Area above and below the baseline were selected as two features for pair wise comparison of the detectors. Different sensors showed different responses between various concentrations of gases. Analysis of multiple detectors was performed using linear and quadratic discriminant analysis (LDA and QDA) along with bootstrap. LDA along with bootstrap provided the highest total classification accuracies of 94.34 % between 100 and 200 ppm of acetic acid. QDA provided higher total classification accuracy of 89.69 % at lower concentration level of 38 and 75 ppm for acetic acid and 84.78 % between 37 and 100 ppm of ethanol. Hence, QDA was a better model of choice at lower concentrations. This study proved non-selective nature of sensors and showed that simultaneous use of multiple sensor information provided better classification accuracy for discriminating various gas concentrations as compared to using individual sensor output.
AB - This study was conducted to evaluate the performance of a commercial electronic nose (Cyranose 320™) for sensing indicator compounds (ethanol and acetic acid) associated with spoiled beef. The present study reported the sensitivity of an array of 32 sensors to ethanol and acetic acid. Different vapor concentrations of ethanol (37, 100, 250 and 500 ppm) and acetic acid (38, 75, 100, 200 and 300 ppm) were tested to evaluate the performance of the commercial system. An in-house designed universal gas sensing and characterization system was coupled with the electronic nose system to generate the desired gas concentration. The raw smell print patterns were obtained and analyzed for individual and multiple detectors. Tukey’s multiple comparison technique was performed to analyze the response of individual detectors. Area above and below the baseline were selected as two features for pair wise comparison of the detectors. Different sensors showed different responses between various concentrations of gases. Analysis of multiple detectors was performed using linear and quadratic discriminant analysis (LDA and QDA) along with bootstrap. LDA along with bootstrap provided the highest total classification accuracies of 94.34 % between 100 and 200 ppm of acetic acid. QDA provided higher total classification accuracy of 89.69 % at lower concentration level of 38 and 75 ppm for acetic acid and 84.78 % between 37 and 100 ppm of ethanol. Hence, QDA was a better model of choice at lower concentrations. This study proved non-selective nature of sensors and showed that simultaneous use of multiple sensor information provided better classification accuracy for discriminating various gas concentrations as compared to using individual sensor output.
KW - Acetic acid
KW - Conducting polymers
KW - Cyranose 320™
KW - Electronic nose
KW - Ethanol
KW - Sensor
KW - Universal gas sensing and characterization system
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U2 - 10.1007/s11694-014-9200-9
DO - 10.1007/s11694-014-9200-9
M3 - Article
AN - SCOPUS:84939962552
SN - 2193-4126
VL - 9
SP - 121
EP - 129
JO - Journal of Food Measurement and Characterization
JF - Journal of Food Measurement and Characterization
IS - 2
ER -