DNA barcode trnH-psbA is a promising candidate for efficient identification of forage legumes and grasses.

Clicks: 442
ID: 83234
2020
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #8 of 169 articles by views in BMC research notes

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 169 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Grasslands are widespread ecosystems that fulfil many functions. Plant species richness (PSR) is known to have beneficial effects on such functions and monitoring PSR is crucial for tracking the effects of land use and agricultural management on these ecosystems. Unfortunately, traditional morphology-based methods are labor-intensive and cannot be adapted for high-throughput assessments. DNA barcoding could aid increasing the throughput of PSR assessments in grasslands. In this proof-of-concept work, we aimed at determining which of three plant DNA barcodes (rbcLa, matK and trnH-psbA) best discriminates 16 key grass and legume species common in temperate sub-alpine grasslands.Barcode trnH-psbA had a 100% correct assignment rate (CAR) in the five analyzed legumes, followed by rbcLa (93.3%) and matK (55.6%). Barcode trnH-psbA had a 100% CAR in the grasses Cynosurus cristatus, Dactylis glomerata and Trisetum flavescens. However, the closely related Festuca, Lolium and Poa species were not always correctly identified, which led to an overall CAR in grasses of 66.7%, 50.0% and 46.4% for trnH-psbA, matK and rbcLa, respectively. Barcode trnH-psbA is thus the most promising candidate for PSR assessments in permanent grasslands and could greatly support plant biodiversity monitoring on a larger scale.
Reference Key
loerasnchez2020dnabmc Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Loera-Sánchez, Miguel;Studer, Bruno;Kölliker, Roland;
Journal BMC research notes
Year 2020
DOI
10.1186/s13104-020-4897-5
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.