H. Meshkat; F. Sharifian; A. Hosainpour; A. Mohammad Nilkbakht
Abstract
In recent years, research on medicinal plants as therapeutic supplements has increased dramatically. Lavender (Lavandula stricta Del.) extract due to its special therapeutic properties is widely used in natural products. Due to the importance of physical quality of powder extract produced from medicinal ...
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In recent years, research on medicinal plants as therapeutic supplements has increased dramatically. Lavender (Lavandula stricta Del.) extract due to its special therapeutic properties is widely used in natural products. Due to the importance of physical quality of powder extract produced from medicinal plants in the food and pharmaceutical industry, in this research the performance of spray dryer in powder production of lavender extract at three levels of input temperatures including 150, 180, and 210 °C, three levels of input air flow rate including 6, 8, and 10 L min-1 and the ratios of 0, 25, and 50% maltodextrin drying aid to the dry matter mass of the extract were studied using the response surface method and physical properties of the produced powder were investigated. The moisture content, aqueous activity, bulk density, particle density, and porosity of powder samples varied in the range of 5.10-8.70%, 0.26-0.30%, 0.45-0.60 g mL-1, 0.99-2.50 g mL-1, and 47-87%, respectively. The maximum dryer yield in the production of lavender powder was determined to be 89% at a temperature of 210 °C and an air flow rate 8 L min-1 and a mass ratio 50% of dryer aid. Taking into account all the physical factors evaluated, the optimum point in processing lavender extract was obtained at input air temperature of 177.29 °C and input air flow rate of 10 L min-1, and ratio of maltodextrin to dry matter mass of extract of 67, in which moisture content, aqueous activity, bulk density, particle density, and powder porosity were 6.6%, 0.28, 0.58 g mL-1, 1.46 g mL-1, and 60.95%, respectively.
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.