Evidence map›Paper›PMID 39456309›Full record

ArticleFoods (Basel, Switzerland)2024

Ultrasound as a Physical Elicitor to Improve Texture in Blueberry Fruit: Physiological Indicator and Transcriptomic Analysis.

Yuanyuan Hou, Yinggang Ge, Ailikemu Mulati, Yuting Yang, Jiayi Wang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Foods (Basel, Switzerland), 2024. 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

5 authors.

Yuanyuan HouNational Demonstration Center for Experimental Biology Education, Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science & Technology, Xinjiang University, Urumqi 830046, China.
Yinggang GeNational Demonstration Center for Experimental Biology Education, Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science & Technology, Xinjiang University, Urumqi 830046, China.ORCID 0000-0002-8336-3768
Ailikemu MulatiNational Demonstration Center for Experimental Biology Education, Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science & Technology, Xinjiang University, Urumqi 830046, China.
Yuting YangNational Demonstration Center for Experimental Biology Education, Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science & Technology, Xinjiang University, Urumqi 830046, China.
Jiayi WangNational Demonstration Center for Experimental Biology Education, Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science & Technology, Xinjiang University, Urumqi 830046, China.

Funding

Autonomous Region Universities Basic Research Funds Research Projects-cultivation Projects No. XJEDU2022P007Key Research and Development Program in Xinjiang Uygur Autonomous Region No. 2023B02042-2Student Research Training Program No. 202310755071
6 · The paper itself

Abstract

Ultrasound (US) washing has been verified to improve the quality of postharvest blueberry fruit. However, its physiological and molecular mechanisms remain largely unknown. In the present study, an US with a frequency of 25 kHz and a power density of 400 W for 2 min was performed to investigate its role in impacting the quality of blueberries. The results showed that US washing improved the quality of blueberries, with a higher firmness and lignin content (

Indexed as

blueberry fruitfruit qualitylignin biosynthesistranscriptomeultrasound washing

Identifiers

PMID39456309
PMCPMC11508173

What OpenQuestion holds

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Registered trials

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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.