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Calibration of a Sensor Array (an Electronic Tongue) for Identification and Quantification of Odorants from Livestock Buildings
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PubMed Central
ABSTRACT
This contribution serves a dual purpose. The first purpose was to investigate the possibility of using a sensor array (an electronic tongue) for on-line identification and quantification of key odorants representing a variety of chemical groups at two different acidities, pH 6 and 8. The second purpose was to simplify the electronic tongue by decreasing the number of electrodes from 14, which was the number of electrodes in the prototype. Different electrodes were used for identification and quantification of different key odorants. A total of eight electrodes were sufficient for identification and quantification in micromolar concentrations of the key odorants n-butyrate, ammonium and phenolate in test mixtures also containing iso-valerate, skatole and p-cresolate. The limited number of electrodes decreased the standard deviation and the relative standard deviation of triplicate measurements in comparison with the array comprising 14 electrodes. The electronic tongue was calibrated using 4 different test mixtures, each comprising 50 different combinations of key odorants in triplicates, a total of 600 measurements. Back propagation artificial neural network, partial least square and principal component analysis were used in the data analysis. The results indicate that the electronic tongue has a promising potential as an online sensor for odorants absorbed in the bioscrubber used in livestock buildings. No MeSH data available. |
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f13-sensors-07-00103: Calibration curve (18 samples) of n-butyrate in test mixtures of key odorants containing p-cresolate at pH 8. BPNN used 6, 9, 1 nodes. Mentions: Figure 12 shows that samples with high n-butyrate concentration (5 × 10-4 - 10-3 M) in the mixture, can be monitored using PLS-1 score plot. PLS-1 and full cross validation were used and six electrodes (no. 2, 5, 6, 7, 8, 9) were sufficient. It was possible to model n-butyrate from 5 × 10-5 to 10-3 M. Twenty-nine samples in triplicates (87samples) were split into 48, 21 and 18 as train, test and validation sets, respectively. The BPNN used 6, 9, 1 nodes. Six electrodes were sufficient (no. 2, 5, 6, 7, 8, 9). Slope, correlation, RMSEP and RPD of the calibration curve were 0.83, 0.97, 0.14 and 3.22, respectively (Fig. 13). |
View Article: PubMed Central
This contribution serves a dual purpose. The first purpose was to investigate the possibility of using a sensor array (an electronic tongue) for on-line identification and quantification of key odorants representing a variety of chemical groups at two different acidities, pH 6 and 8. The second purpose was to simplify the electronic tongue by decreasing the number of electrodes from 14, which was the number of electrodes in the prototype. Different electrodes were used for identification and quantification of different key odorants. A total of eight electrodes were sufficient for identification and quantification in micromolar concentrations of the key odorants n-butyrate, ammonium and phenolate in test mixtures also containing iso-valerate, skatole and p-cresolate. The limited number of electrodes decreased the standard deviation and the relative standard deviation of triplicate measurements in comparison with the array comprising 14 electrodes. The electronic tongue was calibrated using 4 different test mixtures, each comprising 50 different combinations of key odorants in triplicates, a total of 600 measurements. Back propagation artificial neural network, partial least square and principal component analysis were used in the data analysis. The results indicate that the electronic tongue has a promising potential as an online sensor for odorants absorbed in the bioscrubber used in livestock buildings.
No MeSH data available.
