Evidence map›Paper›PMID 41937755›Full record

SynthesisFrontiers in plant science2026

Scientific evolution and translational horizons of plant core germplasm: a global bibliometric synthesis and strategic insights.

Wenjun Wang, Hang Ma, Yaodong Qi, Jingxue Ye, Min Lu, Xueping Wei

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in plant science, 2026. 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

6 authors.

Wenjun WangFaculty of Agronomy, Jilin Agricultural University, Changchun, China.
Hang MaState Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Yaodong QiState Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Jingxue YeState Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Min LuFaculty of Agronomy, Jilin Agricultural University, Changchun, China.
Xueping WeiState Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The increasing volume of global plant germplasm resources has led to the complexity of plant germplasm resource management. Plant core germplasm collections demonstrate significant potential in improving the efficiency of germplasm resource management, promoting crop improvement, and maintaining biodiversity. Methods: This study conducted a comprehensive bibliometric analysis of 2,303 Chinese and English publications (2004-2024) sourced from the Web of Science (WoS) and China National Knowledge Infrastructure (CNKI), offering an integrated bilingual perspective on global research patterns and evolution. Results and Discussion: Results show sustained growth in the field, with China and the United States as the leading contributors and collaborative hubs. The research trajectory progressed through three distinct phases-foundational, consolidation, and predictive-driven by advances from phenotypic evaluation to high-throughput genomics and genome-wide association studies (GWAS). Keyword evolution reveals a clear paradigm shift from descriptive, phenotype-based management toward allele-driven, predictive breeding platforms. Persistent challenges include data fragmentation, limited sharing, and a strong taxonomic bias toward major cereal crops. Looking forward, we propose the integration of artificial intelligence to establish biodigital resource centers and the development of functionally designed core collections tailored to specific plant groups. These strategies will enhance precision breeding and support sustainable agriculture and global food security.

Indexed as

bibliometricsburst term analysiscore collectiongenetic diversitygenome-wide association studiesgermplasmmolecular marker

Identifiers

PMID41937755
PMCPMC13044095

What OpenQuestion holds

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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.