Evidence map›Paper›PMID 38231858›Full record

ArticleFoods (Basel, Switzerland)2023

Leaf Mustard (

Awraris Derbie Assefa, Seong-Hoon Kim, Ho Chul Ko, Nayoung Ro, Parthiban Subramanian, Yun-Jo Chung, Yong-Hyuk Lee, Bum-Soo Hahn, Ju-Hee Rhee

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Variations of Major Glucosinolates in Diverse Chinese Cabbage (International journal of molecular sciences · 2024
    Article
  3. Unveiling Glucosinolate Diversity inAntioxidants (Basel, Switzerland) · 2024
    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

9 authors.

Awraris Derbie AssefaNational Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of Korea.ORCID 0000-0002-2289-1436
Seong-Hoon KimNational Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of Korea.ORCID 0000-0003-3244-4266
Ho Chul KoNational Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of Korea.
Nayoung RoNational Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of Korea.
Parthiban SubramanianNational Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of Korea.ORCID 0000-0002-4797-5791
Yun-Jo ChungNational Creative Research Laboratory for Ca2+ Signaling Network, Jeonbuk National University Medical School, Jeonju 54896, Republic of Korea.
Yong-Hyuk LeeAgricultural Technology Center of Yeosu, Yeosu 59633, Republic of Korea.
Bum-Soo HahnNational Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of Korea.ORCID 0000-0002-1747-1875
Ju-Hee RheeNational Agrobiodiversity Center, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of Korea.

Funding

Rural Development Administration PJ01423001
6 · The paper itself

Abstract

Leaf mustard, characterized by its purple/red/green leaves with a green/white midrib, is known for its thick, tender, and spicy leaves with a unique taste and flavor. There were only a few studies reported on leaf mustard for its morphological and biochemical traits from Korea. A total of 355 leaf mustard accessions stored at the GenBank of the National Agrobiodiversity Center were evaluated for 25 agro-morphological traits and seven intact glucosinolates (GSLs). The accessions showed a wide variation in terms of most of the traits. The quantitative agro-morphological traits varied from 16.0 (leaf length) to 48.7% (petiole width) of the coefficient of variation (CV). The highest variation was observed in glucoiberin (299.5%, CV), while the total GSL showed a CV of 66.1%. Sinigrin, followed by gluconapin and gluconasturtiin, was the most abundant GSL, accounting for as high as 75% of the total GSLs, while glucobrassicanapin and glucoiberin were the least abundant, contributing 0.7% and 0.1% on average, respectively. Sinigrin had a positive significant correlation with all GSLs but gluconasturtiin, while glucobarbarin and gluconasturtiin were highly positively correlated to each other, but least correlated with other GSLs. The leaf length was negatively correlated with sinigrin and glucoiberin. The width of the petiole showed a positive correlation with gluconapin, glucobrassicanapin, and glucobrassicin, while the length of the petiole had a negative correlation with sinigrin, glucobrassicanapin, glucoiberin, glucobrassicin, and the total GSLs. A higher width of the midrib was associated with higher contents of gluconapin, glucobrassicanapin, and glucobrassicin. A PCA analysis based on the agro-morphological traits showed that the first and second principal components accounted for 65.2% of the overall variability. Accessions that form a head tend to exhibit a longer leaf length, a larger plant weight, a thicker midrib, and higher widths of the midrib, petiole, and leaf. The GSLs showed inconsistent inter-and intra-leaf variation. Accessions that identified for various traits in their performance, such as, for example, Yeosu66 and IT259487 (highest total glucosinolates) and IT228984 (highest plant weight), would be promising lines for developing new varieties.

Indexed as

agro-morphological charactersdiversityglucosinolatesleaf mustard

Identifiers

PMID38231858
PMCPMC10706673

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.