Evidence map›Paper›PMID 37628823›Full record

ReviewInternational journal of molecular sciences2023

Application of Multi-Perspectives in Tea Breeding and the Main Directions.

Haozhen Li, Kangkang Song, Xiaohua Zhang, Di Wang, Shaolin Dong, Ying Liu, Long Yang

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. ddRAD sequencing of 1076Plant diversity · 2026
    Article
  2. Article
  3. 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

7 authors.

Haozhen LiCollege of Plant Protection and Agricultural Big-Data Research Center, Shandong Agricultural University, Tai'an 271018, China.
Kangkang SongCollege of Plant Protection and Agricultural Big-Data Research Center, Shandong Agricultural University, Tai'an 271018, China.
Xiaohua ZhangCollege of Plant Protection and Agricultural Big-Data Research Center, Shandong Agricultural University, Tai'an 271018, China.
Di WangCollege of Plant Protection and Agricultural Big-Data Research Center, Shandong Agricultural University, Tai'an 271018, China.
Shaolin DongCollege of Plant Protection and Agricultural Big-Data Research Center, Shandong Agricultural University, Tai'an 271018, China.
Ying LiuCollege of Plant Protection and Agricultural Big-Data Research Center, Shandong Agricultural University, Tai'an 271018, China.
Long YangCollege of Plant Protection and Agricultural Big-Data Research Center, Shandong Agricultural University, Tai'an 271018, China.ORCID 0000-0002-9990-8398

Funding

Special Funds for Local Scientific and Technological Development Guided by the Central Government YDZX2022123The Foundation of Innovation Team Project for Modern Agricultural Industrious Technology System of Shandong Province SDAIT-25-01
6 · The paper itself

Abstract

Tea plants are an economically important crop and conducting research on tea breeding contributes to enhancing the yield and quality of tea leaves as well as breeding traits that satisfy the requirements of the public. This study reviews the current status of tea plants germplasm resources and their utilization, which has provided genetic material for the application of multi-omics, including genomics and transcriptomics in breeding. Various molecular markers for breeding were designed based on multi-omics, and available approaches in the direction of high yield, quality and resistance in tea plants breeding are proposed. Additionally, future breeding of tea plants based on single-cellomics, pangenomics, plant-microbe interactions and epigenetics are proposed and provided as references. This study aims to provide inspiration and guidance for advancing the development of genetic breeding in tea plants, as well as providing implications for breeding research in other crops.

Indexed as

Camellia sinensisPlant BreedingCrops, AgriculturalCytoplasmTeaTeaapplicationsbreedinggermplasmomicstea

Identifiers

PMID37628823
PMCPMC10454712

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.