Iranian Journal of Medicinal and Aromatic Plants Research

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Investigation of electronic nose system in classification of Rosa damascena Mill. essential oil by artificial neural network

Document Type : Research Paper

Authors

1 Department of Mechanical Engineering of Biosystem, Faculty of Agriculture, Urmia University, Urmia, Iran

2 Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran

3 Department of Mechanical Engineering of Biosystem, Faculty of Agriculture, Shahrekord University, Shahrekord, Iran

Abstract

Due to the increased use of medicinal plants, the qualitative classification is inevitable. Rosa damascena Mill. with a high value of essential oil and its unique properties in the health, food and pharmaceutical industries is of one of these plants. In this study, after essential oil extraction from nine genotypes of Rosa, the essential oil components were identified by GC and GC-MS analysis. The genotypes were divided in three classes (C1, C2, C3) based on total percentage of six most important compounds, having major role in essential oil quality (phenyl ethyl alcohol, trans rose oxide, citronellol, nerol, geraniol, geranial).Then, the classes were tested by an electronic nose (EN) system designed based on metal oxide semiconductor (MOS) sensors. Sensors response pattern was recorded and analyzed by chemometrics methods in next step. Results of principal components analysis (PCA) showed that 85% of data variance was explained by two first principal components (PC1, PC2). Artificial neural network based on back propagation multilayer perceptron (Bp-MLP) was performed and classification accuracy achieved 100% and 96% for training and test sets, respectively. These results showed that EN could be used as a quick, easy, accurate and inexpensive system to classify Rosa damascene Mill essential oil.

Keywords

References
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Iranian Journal of Medicinal and Aromatic Plants Research
Volume 33, Issue 3 - Serial Number 83
August 2017
Pages 339-349
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