Evidence map›Paper›PMID 38256795›Full record

ArticlePlants (Basel, Switzerland)2024

Metabolomics Analysis of Different Quinoa Cultivars Based on UPLC-ZenoTOF-MS/MS and Investigation into Their Antioxidant Characteristics.

Shufang Wang, Guannan Liu, Chong Xie, You Zhou, Runqiang Yang, Jirong Wu, Jianhong Xu, Kang Tu

Abstract read
In one paragraph

Article in Plants (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Comparative Metabolomic Analysis ofInternational journal of molecular sciences · 2024
    Article
  4. Review
  5. Multi Omics Applications in Biological Systems.Current issues in molecular biology · 2024
    Review
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

8 authors.

Shufang WangCollege of Food Science and Technology, Whole Grain Food Engineering Research Center, Nanjing Agricultural University, Nanjing 210095, China.
Guannan LiuCollege of Food Science and Technology, Whole Grain Food Engineering Research Center, Nanjing Agricultural University, Nanjing 210095, China.
Chong XieCollege of Food Science and Technology, Whole Grain Food Engineering Research Center, Nanjing Agricultural University, Nanjing 210095, China.ORCID 0000-0002-7790-4986
You ZhouJiangsu Key Laboratory for Food Quality and Safety-State Key Laboratory Cultivation Base, Ministry of Science and Technology/Key Laboratory for Control Technology and Standard for Agro-Product Safety and Quality, Ministry of Agriculture and Rural Affairs/Key Laboratory for Agro-Product Safety Risk Evaluation (Nanjing), Ministry of Agriculture and Rural Affairs/Collaborative Innovation Center for Modern Grain Circulation and Safety/Institute of Food Safety and Nutrition, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China.ORCID 0000-0003-2458-0946
Runqiang YangCollege of Food Science and Technology, Whole Grain Food Engineering Research Center, Nanjing Agricultural University, Nanjing 210095, China.ORCID 0000-0002-0191-6315
Jirong WuJiangsu Key Laboratory for Food Quality and Safety-State Key Laboratory Cultivation Base, Ministry of Science and Technology/Key Laboratory for Control Technology and Standard for Agro-Product Safety and Quality, Ministry of Agriculture and Rural Affairs/Key Laboratory for Agro-Product Safety Risk Evaluation (Nanjing), Ministry of Agriculture and Rural Affairs/Collaborative Innovation Center for Modern Grain Circulation and Safety/Institute of Food Safety and Nutrition, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China.
Jianhong XuCollege of Food Science and Technology, Whole Grain Food Engineering Research Center, Nanjing Agricultural University, Nanjing 210095, China.
Kang TuCollege of Food Science and Technology, Whole Grain Food Engineering Research Center, Nanjing Agricultural University, Nanjing 210095, China.ORCID 0000-0003-4314-2896

Funding

Jiangsu Agricultural Science and Technology Innovation Fund CX(22)2013
6 · The paper itself

Abstract

In recent years, quinoa, as a nutritious and sustainable food material, has gained increasing popularity worldwide. To investigate the diversity of nutritional characteristics among different quinoa cultivars and explore their potential health benefits, metabolites of five quinoa cultivars (QL-1, SJ-1, SJ-2, KL-1 and KL-2) were compared by non-targeted metabolomics analysis based on UPLC-ZenoTOF-MS/MS in this study. A total of 248 metabolites across 13 categories were identified. Although the metabolite compositions were generally similar among the different quinoa cultivars, significant variations existed in their respective metabolite contents. Among the identified metabolites, amino acids/peptides, nucleosides, saponins and phenolic acids were the most abundant. Notably, SJ-1 exhibited the most distinct metabolite profile when compared to the other cultivars. Amino acids/peptides and nucleosides were found to be crucial factors contributing to the unique metabolite profile of SJ-1. Collectively, these aforementioned metabolites accounted for a substantial 60% of the total metabolites observed in each quinoa variety. Additionally, a correlation between the DPPH radical scavenging activity and the free phenolic content of quinoa was observed. Variations in phenolic content resulted in different antioxidant capacities among the quinoa cultivars, and SJ-1 exhibited lower phenolic levels and weaker antioxidant activity than the others. These results can provide important information for the development of quinoa resources.

Indexed as

antioxidant propertiesmetabolomicsquinoaUPLC-ZenoTOF-MS/MSvariance analysis

Identifiers

PMID38256795
PMCPMC10819959

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