A. Gorji Chakespari; A. Mohammad Nilbakht; F. Sefidkon; M. Ghasemi Varnamkhasti
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 ...
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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.
H. Zeinali; S.R. Tabaei Aghdaei; M. Asgarzadeh; A. Kiyanipor; M. Abtahi
Volume 23, Issue 2 , August 2007, , Pages 195-203
Abstract
In order to evaluate the relationship of flower yield per plant and yield components in Rosa damascene Mill., an experiment was conducted in a Complete Randomized Block Design with three replications and with 35 genotypes of Rosa damascena, in Kashan dry land and desert research station. Fourteen characters ...
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In order to evaluate the relationship of flower yield per plant and yield components in Rosa damascene Mill., an experiment was conducted in a Complete Randomized Block Design with three replications and with 35 genotypes of Rosa damascena, in Kashan dry land and desert research station. Fourteen characters of morphological and yielding were measured. Flower yield per plant exhibited a significant positive correlation with fresh weight of flower, flower yield per branch, number of flower per branch and plant height, but with bud length had a significant negative correlation. Result of stepwise regression analysis for flower yield per plant showed that fresh weight per flower and number of flower per plant entered the model, respectively, and justified 90 percent of total variation of flower yield per plant. Factor analysis revealed 5 factors which justified 83.2 percent of the total variation among characters. In the first factor, traits of number of flowers per branch, flower yield per branch, canopy diameter, number of flower per plant, length of receptacle and flowering time had greater loadings and was named flower yielding factor. Path analysis showed that number of flower per plant, fresh weight of flower and flower yield per stem had the highest direct effects on flower yield per plant, therefore, this research suggest the number of flowers per plant, fresh weight per flower and number of flowers per branch can be good selection criteria for improving flower yield per plant in Rosa damascene.
F. Sefidkon; Z. Akbari; M.H. Assareh; Gh. Bakhshi Khaniki
Volume 22, Issue 4 , February 2007, , Pages 351-365
Abstract
Rosa damascena Mill is one of the important Rose species for production of aromatic compounds. The oil and distilled water of Rose are used vastly in medicinal, hygienic-cosmetic and food industries. In Iran, there are vast gardens of Rosa damascena in Kashan, Kerman, Tabriz, Sahand and Fars province. ...
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Rosa damascena Mill is one of the important Rose species for production of aromatic compounds. The oil and distilled water of Rose are used vastly in medicinal, hygienic-cosmetic and food industries. In Iran, there are vast gardens of Rosa damascena in Kashan, Kerman, Tabriz, Sahand and Fars province. In this research, the effect of different extraction methods on yield and chemical composition of four Rosa damascena samples (two samples from national botanical garden of Iran with source of Kashan and Oskou, one sample from Kashan and one sample from Chaloos road) were examined. The aromatic compounds were obtained by four extraction methods consisted of two distillation methods (hydro-distillation and water & steam distillation), extraction with organic solvents (by use of hexane and petroleum ether, individually). The yields of essential oils (from distillation methods) and concrete and absolute (from solvent extraction) were calculated. The oils and absolutes were analyzed by GC and GC/MS. The result showed (except Oskou sample) there is no significant difference between oil and absolute yield, but for all samples, the yield of concrete was higher than the yield of oil and absolute, significantly. Distillation methods produced higher percentage of citronellol and sometimes geraniol, but the valuable compound, phenyl ethyl alcohol, was not found in the oils or exist in very little amount. In solvent extraction methods, the percentage of phenyl ethyl alcohol was considerably high and citronellol and also geraniol were found in the absolutes, of course in lower amounts. There were also some differences between the minor components.
