Evidence map›Paper›PMID 37836223›Full record

ReviewPlants (Basel, Switzerland)2023

Trends in Seed Priming Research in the Past 30 Years Based on Bibliometric Analysis.

Yu Tian, Nalin Suranjith Gama-Arachchige, Ming Zhao

Open access · goldAbstract readReview
In one paragraph

Review in Plants (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
4.4field-weighted citation impact, top 6% of its field
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

4 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
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

3 authors at 3 institutions in 2 countries.

Yu TianJilin Provincial Key Laboratory of Tree and Grass Genetics and Breeding, College of Forestry and Grassland Science, Jilin Agricultural University, Changchun 130118, China.ORCID 0000-0002-2319-4325
Nalin Suranjith Gama-ArachchigeDepartment of Botany, Faculty of Science, University of Peradeniya, Peradeniya 20400, Sri Lanka.
Ming ZhaoState Key Laboratory of Vegetation & Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China.
Chinese Academy of Sciences · CNJilin Agricultural University · CNUniversity of Peradeniya · LK

Funding

Jilin Province Science and Technology Development Program 20220402056GHScience and technology research project of Education Department of Jilin Province JJKH20220370KJ
6 · The paper itself

Abstract

Seed priming (SP) treatments are widely used in agriculture and restoration to improve seed germination and seedling vigor. Although there exists a considerable amount of scientific literature on SP, it has seldom undergone visual and quantitative analyses. To gain insights into the patterns observed in SP research over the last three decades, we conducted a bibliometric analysis using the Science Citation Index-Expanded (SCI-E) database, aiming to minimize the similarity score in plagiarism detection. This analysis offers a thorough examination of yearly publications, temporal patterns in keyword usage, the top-performing journals, authors, institutions, and countries within the field of SP. Our research findings suggest a steady annual increase of 10.59% in the volume of SP publications, accompanied by a significant upward trajectory in the average citations received per paper annually. According to the analysis of keywords, it was found that "priming" and "germination" emerged as the most frequently used terms in the field of SP research. Seed

Indexed as

bibliometric analysisgerminationinternational collaborationseedseed priming

Identifiers

PMID37836223
PMCPMC10575273
OpenAlexW4387369863

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.