In collaboration with Scientific Association of Iranian Medicinal Plants

Document Type : Research Paper

Authors

1 M.Sc. student, Mechanical Engineering of Biosystem Department, Razi University, Kermanshah, Iran

2 Mechanical Engineering of Biosystem Department, Razi University, Kermanshah, Iran

3 Ph.D. graduate of Mechanical Engineering of Biosystems, University of Tehran, Tehran, Iran

4 Plant Protection Department, Razi University, Kermanshah, Iran

Abstract

Summer savory (Satureja hortensisL.) is a fragrant herb in the Lamiaceae family with many medicinal properties. Today, urea fertilizer is used for growing this plant which has a great impact on its performance. However, the unnecessary use of urea fertilizer threatens consumer health. Therefore, in this research, the harvested savory plants were classified based on the amount of urea consumed by an olfactory machine. The urea was added to soil at four levels (0, 50, 100 and 150 kg ha-1). Plants were grown in experimental plots under greenhouse conditions. The fragrance of the samples was evaluated using the electronic nose system. In order to optimize the output signals of the electronic nose, the data were normalized by the fractional method. Principal component analysis (PCA) and artificial neural network (ANN) were used respectively to combine the features and classifying them. Based on the results, TGS822 sensorshowed the best response in the range of urea fertilizer tested. Based on the results of PCA, PC1 and PC2 accounted for 93% of the variance. Also, the confusion matrix showed a 100% correct classification rate by the best ANN structure. 

Keywords

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