Evidence map›Paper›PMID 42041006›Full record

ArticlePlant phenomics (Washington, D.C.)2025

Structural parameter determination and pruning pattern analysis of pear tree shoots for dormant pruning.

Jiaqi Li, Hao Sun, Gengchen Wu, Hu Xu, Shutian Tao, Wei Guo, Kaijie Qi, Hao Yin, Shaoling Zhang, Seishi Ninomiya and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Plant phenomics (Washington, D.C.), 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

11 authors.

Jiaqi LiAcademy for Advanced Interdisciplinary Studies, Collaborative Innovation Center for Modern Crop Production Co-Sponsored by Province and Ministry, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China.
Hao SunAcademy for Advanced Interdisciplinary Studies, Collaborative Innovation Center for Modern Crop Production Co-Sponsored by Province and Ministry, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China.
Gengchen WuAcademy for Advanced Interdisciplinary Studies, Collaborative Innovation Center for Modern Crop Production Co-Sponsored by Province and Ministry, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China.
Hu XuAcademy for Advanced Interdisciplinary Studies, Collaborative Innovation Center for Modern Crop Production Co-Sponsored by Province and Ministry, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China.
Shutian TaoSanya Institute, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China.
Wei GuoGraduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Midori-cho, Tokyo, 188-0002, Japan.
Kaijie QiSanya Institute, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China.
Hao YinSanya Institute, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China.
Shaoling ZhangSanya Institute, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China.
Seishi NinomiyaAcademy for Advanced Interdisciplinary Studies, Collaborative Innovation Center for Modern Crop Production Co-Sponsored by Province and Ministry, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China.
Yue MuAcademy for Advanced Interdisciplinary Studies, Collaborative Innovation Center for Modern Crop Production Co-Sponsored by Province and Ministry, State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Nanjing Agricultural University, Nanjing, 210095, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The comprehensive understanding of the dormant pruning patterns in pear trees, along with the accurate identification of shoots suitable for pruning, is essential for implementing automated pruning and fruit production. Due to the complexity of tree architecture, previous descriptions of pruning strategies were qualitative summaries based on experience. In this study, we proposed a high-precision shoot extraction pipeline through point cloud alignment at different times, enabling a quantitative analysis of the pruning patterns. The structural parameters of 126 full bearing period pear trees, encompassing two cultivars and three architectures, were characterized, including the shoot number, single shoot angle and length, as well as shoot length density. The validation results demonstrated that the method attained an

Indexed as

3D structure analysisAutomated pruningPear tree pruningShoot characters

Identifiers

PMID42041006
PMCPMC13109299

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.