JOURNAL ARTICLE
DIVERSITY OF HERBACEOUS ANGIOSPERMS IN SOUTH KAMRUP OF KAMRUP DISTRICT, ASSAM, INDIA.
Published In: Journal of Economic & Taxonomic Botany (Scientific Publishers), 2025, v. 49, n. 3. P. 159 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Das, Karuna Kanta 3 of 3
Abstract
The study of diversity of herbaceous angiosperms in South Kamrup area, Kamrup district of Assam, India revealed the presence of 457 species belonging to 316 genera, 78 families and 32 orders as per APG IV classification. The most populous orders are Poales (73), Lamiales (50), Asterales (43), Fabales (33), Caryophyllales (32), Asparagales (31), Alismatales (28), Solanales (21), Zingiberales (17) and Cucurbitales (16), which constitute 75.27% of the total herbaceous flora of the study area. The Poaceae are the most dominant family, followed by Asteraceae, Fabaceae, Orchidaceae, Araceae, Cyperaceae, Cucurbitaceae, Lamiaceae, Malvaceae and Amaranthaceae. The naturally occurring (wild) species are 76.4% (349 spp.) while 23.6% (108 spp.) are cultivated herbs. Amongst these are 137 IUCN threat assessed as of the LC category. Of the other species whose conservation status in the study area outside the IUCN assessment is 17 Edangered, two Critically Endangered, nine Vulnerable (VL) and three Rare (R). Most of herbaceous angiosperms are terrestrial (273; 59.73%), which are followed by geophytes (73; 15.97%), climbers (47; 10.28%), hydrophytes (20; 4.37%), epiphytes (19; 4.15%), helophytes (17; 3.71%), lianas (9; 1.96%), succulents (3; 0.65%), parasites ((3; 0.65%) and lithophytes (1; 0.2%). [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Economic & Taxonomic Botany (Scientific Publishers). 2025/09, Vol. 49, Issue 3, p159
- Document Type:Article
- Subject Area:Anatomy and Physiology
- Publication Date:2025
- ISSN:0250-9768
- DOI:10.61080/JETB/V49/i3/2025/159-178
- Accession Number:191094810
- Copyright Statement:Copyright of Journal of Economic & Taxonomic Botany (Scientific Publishers) is the property of Scientific Publishers India and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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