Evidence map›Paper›PMID 31991919›Full record

ArticleMetabolites2020

Changes in Metabolome and Nutritional Quality of

Yajun Wang, Xiaojie Liang, Yuekun Li, Yunfang Fan, Yanlong Li, Youlong Cao, Wei An, Zhigang Shi, Jianhua Zhao, Sujuan Guo

Abstract read
In one paragraph

Article in Metabolites, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Article
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  11. Article
  12. Discrimination for geographical origin ofFood science & nutrition · 2023
    Article
  13. Comparative Analysis of Polyphenols inMolecules (Basel, Switzerland) · 2023
    Article
  14. Quality Consistency of Herbal Products: Chemical Evaluation.Progress in the chemistry of organic natural products · 2023
    Article
  15. Authenticating the geographic origins ofFrontiers in plant science · 2023
    Article
  16. Article
  17. Potentially suitable habitats ofFrontiers in plant science · 2023
    Article
  18. Pepino (Metabolites · 2022
    Article
  19. Comparative Analysis of the Phenolic Profile ofMolecules (Basel, Switzerland) · 2022
    Article
  20. 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

10 authors.

Yajun WangKey Laboratory for Silviculture and Conservation, Ministry of Education, Beijing Forestry University, Beijing 100083, China.
Xiaojie LiangNational Wolfberry Engineering Research Center, Yinchuan 750002, China.
Yuekun LiNational Wolfberry Engineering Research Center, Yinchuan 750002, China.
Yunfang FanNational Wolfberry Engineering Research Center, Yinchuan 750002, China.
Yanlong LiNational Wolfberry Engineering Research Center, Yinchuan 750002, China.
Youlong CaoNational Wolfberry Engineering Research Center, Yinchuan 750002, China.
Wei AnNational Wolfberry Engineering Research Center, Yinchuan 750002, China.
Zhigang ShiNingxia Academy of Agriculture and Forestry Sciences, Yinchuan 750002, China.
Jianhua ZhaoNational Wolfberry Engineering Research Center, Yinchuan 750002, China.
Sujuan GuoKey Laboratory for Silviculture and Conservation, Ministry of Education, Beijing Forestry University, Beijing 100083, China.

Funding

Agro-Technical Independent Innovation Special Project of Ningxia Hui Autonomous Region, China QCYL-2018-04National Natural Science Foundation of China 31460211
6 · The paper itself

Abstract

This study aimed at assessing the climatic factors influencing the wolfberry fruit morphology, and the composition of its nutritious metabolites. The cultivar Ningqi1, widely grown in Northwest China was collected from three typical ecological growing counties with contrasting climatic conditions: Ningxia Zhongning (NF), Xinjiang Jinghe (XF) and Qinghai Nomuhong (QF). During the ripening period, 45 fruits from different plantations at each location were sampled. A total of 393 metabolites were detected in all samples through the widely targeted metabolomics approach and grouped into 19 known classes. Fruits from QF were the biggest followed by those from XF and NF. The altitude, relative humidity and light intensity had negative and strong correlations with most of the metabolites, suggesting that growing wolfberry in very high altitudes and under high light intensity is detrimental for the fruit nutritional quality. Soil moisture content is highly and negatively correlated with vitamins, organic acids and carbohydrates while moderately and positively correlated with other classes of metabolites. In contrast, air and soil temperatures exhibited positive correlation with majority of the metabolites. Overall, our results suggest high soil and air temperatures, low altitude and light intensity and moderate soil moisture, as the suitable conditions to produce

Indexed as

bioactive compoundsecological factorshealth benefitsmetabolic profilingwolfberry

Identifiers

PMID31991919
PMCPMC7073637

What OpenQuestion holds

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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.