Evidence map›Paper›PMID 41415157›Full record

ArticlePlant phenomics (Washington, D.C.)2025

Determination of optimal sampling time of grape embryo rescue based on near infrared spectroscopy combined with machine learning.

Fuqiang Wang, Lu Bian, Zhanzhan Zhan, Yao Chen, Chendong Ling, Han Guo, Yueqi Gai, Guotian Liu, Tengfei Xu, Yuejin Wang and 2 more

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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.

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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

12 authors.

Fuqiang WangState Key Laboratory for Crop Stress Resistance and High-Efficiency Production, Northwest A&F University, Yangling, 712100, China.
Lu BianState Key Laboratory for Crop Stress Resistance and High-Efficiency Production, Northwest A&F University, Yangling, 712100, China.
Zhanzhan ZhanState Key Laboratory for Crop Stress Resistance and High-Efficiency Production, Northwest A&F University, Yangling, 712100, China.
Yao ChenState Key Laboratory for Crop Stress Resistance and High-Efficiency Production, Northwest A&F University, Yangling, 712100, China.
Chendong LingCollege of Information Engineering, Northwest A&F University, Yangling, 712100, China.
Han GuoCollege of Horticulture, Northwest A&F University, Yangling, 712100, China.
Yueqi GaiCollege of Horticulture, Northwest A&F University, Yangling, 712100, China.
Guotian LiuState Key Laboratory for Crop Stress Resistance and High-Efficiency Production, Northwest A&F University, Yangling, 712100, China.
Tengfei XuState Key Laboratory for Crop Stress Resistance and High-Efficiency Production, Northwest A&F University, Yangling, 712100, China.
Yuejin WangState Key Laboratory for Crop Stress Resistance and High-Efficiency Production, Northwest A&F University, Yangling, 712100, China.
Yan XuState Key Laboratory for Crop Stress Resistance and High-Efficiency Production, Northwest A&F University, Yangling, 712100, China.
Yingqiu HuoKey Laboratory for Agricultural Internet of Things, Ministry of Agriculture and Rural Affairs, Yangling, 712100, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Grape embryo rescue technology is currently the primary method for breeding new seedless grape cultivars. The timing of berry sampling directly impacts the efficacy of this technique. Therefore, achieving efficient, accurate, and non-destructive determination of the optimal sampling time for seedless grape embryo rescue breeding has long been a challenge. This study collected near-infrared spectral data and data on 19 physiological indicators from 2940 grape berries of six grape cultivars at six sampling times to construct a baseline dataset. Remarkably, it was discovered for the first time that pericarp puncture hardness (PPH) is closely associated with the embryo development rate of seedless grape. Subsequently, the optimal sampling times for 'Flame Seedless', 'Ruby Seedless', and 'Jingzaojing' were determined when their PPH reached 720 ​± ​20 ​g, 990 ​± ​20 ​g and 633 ​± ​20 ​g, respectively. Then, a total of 840 models for PPH recognition were established and assessed based on their coefficient of determination (

Indexed as

Machine learningNear infrared spectroscopyPericarp puncture hardnessSampling timeSeedless grape

Identifiers

PMID41415157
PMCPMC12709896

What Socratic 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 Socratic graph.