Investigation of electronic nose system in classification of Rosa damascena Mill. essential oil by artificial neural network
Author(s):
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:
Language:
Persian
Published:
Iranian Journal of Medical and Aromatic Plants, Volume:33 Issue: 3, 2017
Pages:
339 to 349
magiran.com/p1730496
دانلود و مطالعه متن این مقاله با یکی از روشهای زیر امکان پذیر است:
اشتراک شخصی
با عضویت و پرداخت آنلاین حق اشتراک یکساله به مبلغ 1,390,000ريال میتوانید 70 عنوان مطلب دانلود کنید!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی نامحدود همه کاربران به متن مطالب تهیه نمایند!
توجه!
- حق عضویت دریافتی صرف حمایت از نشریات عضو و نگهداری، تکمیل و توسعه مگیران میشود.
- پرداخت حق اشتراک و دانلود مقالات اجازه بازنشر آن در سایر رسانههای چاپی و دیجیتال را به کاربر نمیدهد.
In order to view content subscription is required
Personal subscription
Subscribe magiran.com for 70 € euros via PayPal and download 70 articles during a year.
Organization subscription
Please contact us to subscribe your university or library for unlimited access!