Evidence map›Paper›PMID 40270798›Full record

ArticleEcology and evolution2025

A Novel Approach for Pollen Identification and Quantification Using Hybrid Capture-Based DNA Metabarcoding.

D Kireta, K-J van Dijk, S Crotty, A Malik, K Bell, K Hogendoorn, A J Lowe

Abstract read
In one paragraph

Article in Ecology and evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

D KiretaSchool of Biological Sciences The University of Adelaide Adelaide South Australia Australia.ORCID https://orcid.org/0000-0001-8957-3400
K-J van DijkSchool of Biological Sciences The University of Adelaide Adelaide South Australia Australia.
S CrottySchool of Computer and Mathematical Sciences The University of Adelaide Adelaide South Australia Australia.
A MalikSchool of Biological Sciences The University of Adelaide Adelaide South Australia Australia.
K BellNew South Wales Department of Primary Industries Wagga Wagga New South Wales Australia.ORCID https://orcid.org/0000-0002-4445-4026
K HogendoornSchool of Agriculture, Food and Wine The University of Adelaide Adelaide South Australia Australia.
A J LoweSchool of Biological Sciences The University of Adelaide Adelaide South Australia Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pollen identification (ID) and quantification is important in many fields, including pollination ecology and agricultural sciences, and efforts to explore optimal molecular methods for identifying low concentrations of DNA from plant mixtures are increasing, but quantifying mixture proportions remains challenging. Traditional pollen ID using microscopy is time-consuming, requires expertise and has limited accuracy and throughput. Molecular barcoding approaches being explored offer improved accuracy and throughput. The common approach, amplicon sequencing, employs PCR amplification to isolate DNA barcodes, but introduces significant bias, impairing downstream quantification. We apply a novel molecular hybrid capture approach to artificial pollen mixtures to improve upon current taxon ID and quantification methods. The method randomly fragments DNA and uses RNA baits to capture DNA barcodes, which allows for PCR duplicate removal, reducing downstream quantification bias. Four reference databases were used to explore identification and quantification. A restricted

Indexed as

hybrid capturepollen identificationpollen metabarcodingpollen quantificationtarget enrichment

Identifiers

PMID40270798
PMCPMC12017898

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.