Weather Conditions Influence on Hyssop Essential Oil Quality

被引:19
|
作者
Acimovic, Milica [1 ]
Pezo, Lato [2 ]
Zeremski, Tijana [1 ]
Loncar, Biljana [3 ]
Jeromela, Ana Marjanovic [1 ]
Jeremic, Jovana Stankovic [4 ]
Cvetkovic, Mirjana [4 ]
Sikora, Vladimir [1 ]
Ignjatov, Maja [1 ]
机构
[1] Inst Field & Vegetable Crops Novi Sad, Dept Plant Breeding, Dept Vegetable & Alternat Crops, Lab Soil & Agroecol, Maksima Gorkog 30, Novi Sad 21000, Serbia
[2] Univ Belgrade, Inst Gen & Phys Chem, Engn Dept, Studentski Trg 12-16, Belgrade 11000, Serbia
[3] Univ Novi Sad, Fac Technol, Bulevar Cara Lazara 1, Novi Sad 21000, Serbia
[4] Univ Belgrade, Inst Chem Technol & Met, Njegoseva 12, Belgrade 11000, Serbia
关键词
Hyssopus officinalis; essential oil; hydrodistillation; GC-MS; QSRR; artificial neural networks; OFFICINALIS L; CHEMICAL-COMPOSITION; ANTIFUNGAL ACTIVITY; BIOLOGICAL-ACTIVITY; PREDICTION; COMPONENTS; STRESS; QSRR; QSAR;
D O I
10.3390/pr9071152
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
This paper is a study of the chemical composition of Hyssopus officinalis ssp. officinalis grown during three years (2017-2019) at the Institute of Field and Vegetable Crops Novi Sad (Vojvodina Province, Serbia). Furthermore, comparisons with ISO standards during the years were also investigated, as well as a prediction model of retention indices of compounds from the essential oils. An essential oil obtained by hydrodistillation and analysed by GC-FID and GC-MS was isopinocamphone chemotype. The gathered information about the volatile compounds from H. officinalis was used to classify the samples using the unrooted cluster tree. The correlation analysis was applied to investigate the similarity of different samples, according to GC-MS data. The quantitative structure-retention relationship (QSRR) was also employed to predict the retention indices of the identified compounds. A total of 74 experimentally obtained retention indices were used to build a prediction model. The coefficient of determination for the training cycle was 0.910, indicating that this model could be used for the prediction of retention indices for H. officinalis essential oil compounds.
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页数:18
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