The effect of various extraction techniques on the quality of sage (Salvia officinalis L.) essential oil, expressed by chemical composition, thermal properties and biological activity

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Názov: The effect of various extraction techniques on the quality of sage (Salvia officinalis L.) essential oil, expressed by chemical composition, thermal properties and biological activity
Autori: Đurović, Saša, Micić, Darko, Pezo, Lato, Radić, Danka, Bazarnova, Julia, Smyatskaya, Yulia A., Blagojević, Stevan
Zdroj: Food Chem X
Food Chemistry: X, Vol 13, Iss, Pp 100213-(2022)
Food Chemistry-X
Informácie o vydavateľovi: Elsevier BV, 2022.
Rok vydania: 2022
Predmety: Artificial neural network, 0106 biological sciences, Thermal properties, Nutrition. Foods and food supply, Biological activity, Chemical composition, 04 agricultural and veterinary sciences, TP368-456, Sage, 01 natural sciences, Food processing and manufacture, 6. Clean water, 0104 chemical sciences, 3. Good health, Article(s) from the Special Issue on Advances in Tea Chemistry, Flavor, Safety and Health by Dr. Xu and Dr. Yin, Extraction techniques, 0404 agricultural biotechnology, Essential oil quality, Extraction conditions, TX341-641
Popis: In this study, influence of the extraction techniques on the quality of the sage essential oil was investigated. Obtained samples were analyzed for chemical composition by GC/MS, thermal properties by thermogravimetric analysis (TGA), and for biological activity: antioxidant (DPPH, CUPRAC, FRAP, ABTS, HRSA and TBARS), microbiological (Staphylococcus aureus, Escherichia coli, Bacillus subtilis, Pseudomonas aeruginosa, Candida albicans, and Aspergillus niger), and cytotoxic (HeLa, LS-174, A549 and MRC-5) activities. Chemical composition showed that viridiflorol was principal compound in all samples followed by camphor, thujones, and verticiol. MWD 400 W was the most potent antioxidant agent, D 200 W and MWD 400 W antimicrobial agents, while hydrodistallates (D 200 W and D 400 W) were the most potent cytotoxic agents. An artificial neural network model was developed for the antioxidant activity anticipation of analyzed samples. These models showed good prediction properties (the r2 value during training cycle for output variables was 0.998).
Druh dokumentu: Article
Other literature type
Jazyk: English
ISSN: 2590-1575
DOI: 10.1016/j.fochx.2022.100213
Prístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/35498992
https://doaj.org/article/aa791a28d68f47aea3349315f5eff142
https://riofh.iofh.bg.ac.rs/handle/123456789/894
Rights: CC BY
Prístupové číslo: edsair.doi.dedup.....809e07a9ddd4a8b31c3b1355dbda3a8d
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  Data: The effect of various extraction techniques on the quality of sage (Salvia officinalis L.) essential oil, expressed by chemical composition, thermal properties and biological activity
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  Data: Food Chem X<br />Food Chemistry: X, Vol 13, Iss, Pp 100213-(2022)<br />Food Chemistry-X
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  Data: Elsevier BV, 2022.
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– Name: Abstract
  Label: Description
  Group: Ab
  Data: In this study, influence of the extraction techniques on the quality of the sage essential oil was investigated. Obtained samples were analyzed for chemical composition by GC/MS, thermal properties by thermogravimetric analysis (TGA), and for biological activity: antioxidant (DPPH, CUPRAC, FRAP, ABTS, HRSA and TBARS), microbiological (Staphylococcus aureus, Escherichia coli, Bacillus subtilis, Pseudomonas aeruginosa, Candida albicans, and Aspergillus niger), and cytotoxic (HeLa, LS-174, A549 and MRC-5) activities. Chemical composition showed that viridiflorol was principal compound in all samples followed by camphor, thujones, and verticiol. MWD 400 W was the most potent antioxidant agent, D 200 W and MWD 400 W antimicrobial agents, while hydrodistallates (D 200 W and D 400 W) were the most potent cytotoxic agents. An artificial neural network model was developed for the antioxidant activity anticipation of analyzed samples. These models showed good prediction properties (the r2 value during training cycle for output variables was 0.998).
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  Data: 2590-1575
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  Data: 10.1016/j.fochx.2022.100213
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