Evidence map›Paper›PMID 40805749›Full record

ArticlePlants (Basel, Switzerland)2025

Comparative Metabolomics Analysis of Four Pineapple (

Ping Zheng, Jiahao Wu, Denglin Li, Shiyu Xie, Xinkai Cai, Qiang Xiao, Jing Wang, Qinglong Yao, Shengzhen Chen, Ruoyu Liu and 5 more

Abstract read
In one paragraph

Article in Plants (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Metabolomics Analysis of Different Varieties ofFoods (Basel, Switzerland) · 2026
    Article
  2. 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

15 authors.

Ping ZhengFujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science andTechnology, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.ORCID 0000-0002-1236-9038
Jiahao WuFujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science andTechnology, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.ORCID 0009-0006-9365-3597
Denglin LiFujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science andTechnology, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Shiyu XieFujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science andTechnology, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Xinkai CaiFujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science andTechnology, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.ORCID 0009-0001-1313-7765
Qiang XiaoFujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science andTechnology, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Jing WangFujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science andTechnology, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.ORCID 0009-0000-8535-2272
Qinglong YaoFujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science andTechnology, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Shengzhen ChenFujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science andTechnology, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Ruoyu LiuPingtan Science and Technology Research Institute, College of Marine Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.ORCID 0000-0003-0853-9863
Yuqin LiangXiamen Botanical Garden, Xiamen 361000, China.
Yangmei ZhangYunnan Institute of Tropical Crops, Jinghong City, Xishuangbanna 666100, China.
Biao DengHorticulture Research Institute, Guangxi Academy of Agricultural Sciences, Nanning Investigation Station of South Subtropical Fruit Trees, Ministry of Agriculture, Nanning 530004, China.ORCID 0000-0003-3780-7986
Yuan QinFujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science andTechnology, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Xiaomei WangFujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science andTechnology, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.

Funding

Construction Funds for the Key Core Technology of Biological Breeding at the Institute of Future Technology, Fujian Agriculture and Forestry University 72202202307Special Fund for Tropical Crop Science and Technology Innovation Project of Yunnan RF2024-8The project of Guangxi featured fruit innovation team pineapple Nanning Integrated test station post under the national modern agricultural industry technology system nycytxgxcxtd-2024-17-10the Research Funds on Breeding Technology Innovation for Characteristic Fruit Trees of Yunnan KH230435Athe Science and Technology Major Project of Guangxi Gui Ke AA22068096
6 · The paper itself

Abstract

Understanding the metabolic characteristics of pineapple varieties is crucial for market expansion and diversity. This study performed comparative metabolomic analysis on the "Comte de Paris" (BL) and three Taiwan-introduced varieties: "Tainong No. 11" (XS), "Tainong No. 23" (MG), and "Tainong No. 13" (DM). A total of 551 metabolites were identified across the four varieties, with 231 metabolites exhibiting no significant differences between all varieties. This included major sugars such as sucrose, glucose, and fructose, as well as key acids like citric, malic, and quinic acids, indicating that the in-season maturing fruits of different pineapple varieties can all achieve good sugar-acid accumulation under suitable conditions. The differentially accumulated metabolites (DAMs) that were identified among the four varieties all primarily belonged to several major subclasses, including phenolic acids, flavonoids, amino acids and derivatives, and alkaloids, but the preferentially accumulated metabolites in each variety varied greatly. Specifically, branched-chain amino acids (L-leucine, L-isoleucine, and L-valine) and many DAMs in the flavonoid, phenolic acid, lignan, and coumarin categories were most abundant in MG, which might contribute to its distinct and enriched flavor and nutritional value. XS, meanwhile, exhibited a notable accumulation of aromatic amino acids (L-phenylalanine, L-tryptophan), various phenolic acids, and many lignans and coumarins, which may be related to its unique flavor profile. In DM, the dominant accumulation of jasmonic acid might contribute to its greater adaptability to low temperatures during autumn and winter, allowing off-season fruits to maintain good quality. The main cultivar BL exhibited the highest accumulation of L-ascorbic acid and many relatively abundant flavonoids, making it a good choice for antioxidant benefits. These findings offer valuable insights for promoting different varieties and advancing metabolome-based pineapple improvement programs.

Indexed as

comparative analysisfruit qualitymetabolomepineapple

Identifiers

PMID40805749
PMCPMC12349519

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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.