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Extraction methods and bioautography for evaluation of medicinal plant antimicrobial activity

Nostro, A., Germano, M.P., D'Angelo, V., Marino, A., Cannatelli, M.A.·2000·Letters in Applied Microbiology

Abstract

A comparative study on the antimicrobial properties of extracts from medicinal plants obtained by two different methods was carried out. The screening of the antimicrobial activity of extracts from six plants was conducted by a disc diffusion test against Gram-positive, -negative and fungal organisms. The most active extracts (inhibition diameter >/=12 mm) were assayed for the minimum inhibitory concentration and submitted to phytochemical screening by thin-layer chromatography and bioautography. The results obtained indicate that the diethyl ether extracts were the most efficient antimicrobial compounds. The activity was more pronounced against Gram-positive and fungal organisms than against Gram-negative bacteria. Bioautography showed that the antimicrobial activity was probably due to flavonoids and terpenes.

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Metadata

Authors
Nostro, A., Germano, M. P., D'Angelo, V., Marino, A., & Cannatelli, M. A.
Venue
Letters in Applied Microbiology
Published
2000-05
Volume
30
Issue
5
Pages
379-384
ISSN
  • 0266-8254 (ISSN-L)
  • 1365-2673
OpenAlex
W2000362546
Cited by
858
References
1
FWCI
4.77
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Extraction methods and bioautography for evaluation of medicinal plant antimicrobial activity. https://app.cochat.ai/papers/10.1046/j.1472-765x.2000.00731.x
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Nostro, A., Germano, M. P., D'Angelo, V., Marino, A., & Cannatelli, M. A. (2000). Extraction methods and bioautography for evaluation of medicinal plant antimicrobial activity. Letters in Applied Microbiology. https://doi.org/10.1046/j.1472-765x.2000.00731.x

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.