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Classification of Mixtures of Odorants from Livestock Buildings by a Sensor Array (an Electronic Tongue)

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ABSTRACT

An electronic tongue comprising different numbers of electrodes was able to classify test mixtures of key odorants characteristic of bioscrubbers of livestock buildings (n-butyrate, iso-valerate, phenolate, p-cresolate, skatole and ammonium). The classification of model solutions indicates that the electronic tongue has a promising potential as an online sensor for characterization of odorants in livestock buildings. Back propagation artificial neural network was used for classification. The average classification rate was above 80% in all cases. A limited, but sufficient number of electrodes were selected by average classification rate and relative entropy. The sufficient number of electrodes decreased standard deviation and relative standard deviation compared to the full electrode array.

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PLS-1 score plot of all samples in test mixtures of key odorants containing ammonium at pH 6 (to right) and at pH 8 (to left). Full cross validation, PLS-DA was used and eight electrodes were sufficient.
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f4-sensors-07-00129: PLS-1 score plot of all samples in test mixtures of key odorants containing ammonium at pH 6 (to right) and at pH 8 (to left). Full cross validation, PLS-DA was used and eight electrodes were sufficient.

Mentions: BPNN classification models were superior to linear classification methods, e.g. partial least square – discriminant analysis (PLS-DA) [11]. This was explained by the non-linear response of electrodes [25], which results from interferences between ions in the test mixtures [26]. However, PLS-DA showed a complete agreement with BPNN in some cases. PLS-DA was carried out for classification of the last three test mixtures of key odorants shown in Table 3. In these cases, the two test mixtures were easily separated in the PLS score plots, as shown in Fig. 3, 4 and Fig. 5. Electrodes no. 1, 2, 5, 6, 7, 8, 9, 11 were sufficient.


Classification of Mixtures of Odorants from Livestock Buildings by a Sensor Array (an Electronic Tongue)
PLS-1 score plot of all samples in test mixtures of key odorants containing ammonium at pH 6 (to right) and at pH 8 (to left). Full cross validation, PLS-DA was used and eight electrodes were sufficient.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3756716&req=5

f4-sensors-07-00129: PLS-1 score plot of all samples in test mixtures of key odorants containing ammonium at pH 6 (to right) and at pH 8 (to left). Full cross validation, PLS-DA was used and eight electrodes were sufficient.
Mentions: BPNN classification models were superior to linear classification methods, e.g. partial least square – discriminant analysis (PLS-DA) [11]. This was explained by the non-linear response of electrodes [25], which results from interferences between ions in the test mixtures [26]. However, PLS-DA showed a complete agreement with BPNN in some cases. PLS-DA was carried out for classification of the last three test mixtures of key odorants shown in Table 3. In these cases, the two test mixtures were easily separated in the PLS score plots, as shown in Fig. 3, 4 and Fig. 5. Electrodes no. 1, 2, 5, 6, 7, 8, 9, 11 were sufficient.

View Article: PubMed Central

ABSTRACT

An electronic tongue comprising different numbers of electrodes was able to classify test mixtures of key odorants characteristic of bioscrubbers of livestock buildings (n-butyrate, iso-valerate, phenolate, p-cresolate, skatole and ammonium). The classification of model solutions indicates that the electronic tongue has a promising potential as an online sensor for characterization of odorants in livestock buildings. Back propagation artificial neural network was used for classification. The average classification rate was above 80% in all cases. A limited, but sufficient number of electrodes were selected by average classification rate and relative entropy. The sufficient number of electrodes decreased standard deviation and relative standard deviation compared to the full electrode array.

No MeSH data available.


Related in: MedlinePlus