Electronic Nose Applications in the Food Industry

Mallikarjunan, P.

doi:10.1002/9780470388310.ch10

Cited by 4 publications

(17 citation statements)

References 63 publications

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“…Teknik ini bertujuan untuk menentukan apakah sampel-sampel sama atau tidak dan dapat dipisahkan dalam grup yang homogen. Teknik ini juga dapat menentukan variabel mana yang terhubung dan derajat korelasinya [7]. PCA mentransformasikan data ke dalam koordinat baru.…”

Section: Pendahuluanunclassified

The Method of Baseline Manipulation to Overcome the Sensor Drift on Gas Sensor Test for Herbal Drinks Discrimination

Agustika

Triyana

2017

JSD

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AbstrakSistem Sensor gas banyak digunakan untuk pendeteksian aroma. Permasalahan utama dalam sistem ini adalah adanya sensor drift yang membuat buruknya reprodusibilitas sensor. Reprodusibilitas sensor dapat ditingkatkan dengan menerapkan seleksi ciri pada respon luaran sensor dan manipulasi baseline. Penelitian ini difokuskan untuk menenentukan metode yang dapat mengurangi adanya sensor dift dengan tahapan manipulasi baseline dan memilih jenis manipulasi baseline yang optimal saat sistem sensor gas mendeteksi tiga jenis jamu yang berbeda. Data yang telah diseleksi ciri kemudian diterapkan tiga jenis manipulasi baseline yang berbeda (diferensial, relatif dan fraksional) dan dimasukkan ke sistem pengenalan pola Principal Component Analysis (PCA). Dari hasil analisis PCA manipulasi baseline yang meberikan hasil optimal adalah diferensial dengan nilai PC1 82,71%. Hal ini menunjukkan manipulasi baseline diferensial efektif dalam mereduksi terjadinya sensor drift.Kata kunci: electronic nose, sensor gas, manipulasi baseline, seleksi ciri AbstractGas sensor system is widely used for the detection of aroma. The main problem in this system is the sensor drift that makes poor reproducibility of the sensor. The reproducibility of the sensor can be improved by applying the feature selection of the sensor's output response and baseline manipulation. This research focused on determining methods that can reduce the dift sensor of gas sensor by using basaeline manipulation and selecting the optimal type of baseline manipulation when gas sensor system detects three different types of herbal drinks. The data that have been feature selected were then applied to three different types of baseline manipulation (differential, relative and fractional)

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Section: Pendahuluanunclassified

The Method of Baseline Manipulation to Overcome the Sensor Drift on Gas Sensor Test for Herbal Drinks Discrimination

Agustika

Triyana

2017

JSD

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“…Each sensor type has a greater or lesser affinity for a particular chemical class or group of compounds. The adsorption of volatiles on the sensor surface causes a physical or chemical change in the sensor, allowing a specific pattern or "smellprint" of the volatiles (Mallikarjunan 2005). Using chemometric techniques and multivariate statistical analysis, it is possible to distinguish among groups of samples and, depending on the type of ENose, identify individual sample components.…”

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confidence: 99%

“…Each sensor is comprised of a different conductive material such as polypyrrole, polythiophene, polyaniline, polyacetylene, and polyindole, with a range of properties to allow discrimination among different types of volatiles, although cross-selectivity can occur (Mallikarjunan 2005, Pinheiro et al 2002. Sensor responses are stored as smellprints and compared with the present readings during identification (Cyrano Sciences Inc., manufacturer guidelines, 2000).…”

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confidence: 99%

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Monitoring Effects of Ethanol Spray on Cabernet franc and Merlot Grapes and Wine Volatiles Using Electronic Nose Systems

Zoecklein¹,

Devarajan²,

Mallikarjunan³

et al. 2011

Am. J. Enol. Vitic.

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Abstract:The ability of two electronic nose systems (conducting polymer and surface acoustic wave-based) to differentiate volatiles of grapes and wines treated with an aqueous ethanol spray (5% v/v) at veraison was evaluated. Ethanol spray induced fruit ethylene production immediately posttreatment, which then declined progressively. The electronic nose evaluations of grape volatiles were compared with Cabernet franc and Merlot physicochemistry and with wine gas chromatographic and aroma sensory data. Canonical discriminant and principal component analysis found that both electronic nose systems and the physicochemical measures (Brix, TA, pH, color intensity and hue, total phenols, glycosides, and berry weight) were able to discriminate between ethanol-treated and untreated grapes and wines for both cultivars. Grape physicochemical treatment differences were due mainly to variations in hue, phenolic-free glycosides, and total phenols. Aroma sensory evaluations using a consumer panel differentiated between ethanol treatments and controls for Merlot, but not for Cabernet franc wines.

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“…In addition, it may be difficult to relate individual aroma and flavor compounds to a sensory response or attribute in a complex matrix such as wine (Genovese et al 2005). Traditional volatile analytical methods such as GC and GC-MS are time-consuming and require extensive sample preparation and training (Mallikarjunan 2005). Therefore, there is interest in an alternative simple and efficient method for analyzing volatile compounds.…”

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confidence: 99%

Electronic Nose Analysis of Cabernet Sauvignon (Vitis viniferaL.) Grape and Wine Volatile Differences during Cold Soak and Postfermentation

Gardner¹,

Zoecklein²,

Mallikarjunan³

2010

Am. J. Enol. Vitic.

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Cold soak is a prefermentation maceration process at cold temperatures, traditionally used to enhance red wine color. This study monitored changes in Vitis vinifera L. cv. Cabernet Sauvignon volatiles using a commercial conducting polymer electronic nose (ENose) during a five-day cold soak and postfermentation. Principal component analysis (PCA) of juice volatiles detected by the ENose during cold soak showed PC1 accounted for 95.7% of the variation. Various volatile associations were made with specific ENose sensors. In comparison, PCA of must chemistries had 52.4% of the variation accounted for by PC1. The PCA of wine volatiles detected by GC-MS showed PC1 accounted for 97.1% of the variation between control and cold soak treatment, where control wine volatiles were associated with several ethyl esters, while cold soak wine volatiles were associated with diethyl succinate, isovaleric acid, benzyl alcohol, 3-methyl butanol, cis-3-hexenol, γ-nonalactone, benzaldehyde, 2-methyl propanol, phenethyl acetate, 1-octanol, β-damascenone, terpinene-4-ol, γ-butyrolactone, ethyl acetate, hexanoic acid, citronellol, phenethyl alcohol, and n-butanol. Comparatively, PC1 accounted for 100% of the total variance when using the ENose to measure volatile composition. Sensory evaluation did not demonstrate significant differences in aroma between control and cold soak wines. This study demonstrates differences in volatile chemistry between control and cold soak wines, as well as the ability to use a conducting polymer ENose as a simple tool for analysis of volatiles.

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Electronic Nose Applications in the Food Industry

Cited by 4 publications

References 63 publications

The Method of Baseline Manipulation to Overcome the Sensor Drift on Gas Sensor Test for Herbal Drinks Discrimination

The Method of Baseline Manipulation to Overcome the Sensor Drift on Gas Sensor Test for Herbal Drinks Discrimination

Monitoring Effects of Ethanol Spray on Cabernet franc and Merlot Grapes and Wine Volatiles Using Electronic Nose Systems

Electronic Nose Analysis of Cabernet Sauvignon (Vitis viniferaL.) Grape and Wine Volatile Differences during Cold Soak and Postfermentation

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