Evidence map›Paper›PMID 41699481›Full record

ArticleBMC plant biology2026

Comprehensive phenomics and vegetative yield analysis of global kale (Brassica oleracea var. acephala) germplasm in controlled environment agriculture.

Adrian Ming Jern Lee, Ting Xiang Neik, Shuang Song, Kwai Wei Chan, Seam Choon Law, Pei-Wen Ong, Ethan Tze Cherng Lim, Fook Tim Chew

Abstract read
In one paragraph

Article in BMC plant biology, 2026. 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
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0citing papers in PubMed
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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

8 authors.

Adrian Ming Jern LeeDepartment of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore, 117543, Singapore.
Ting Xiang NeikDepartment of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore, 117543, Singapore.
Shuang SongDepartment of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore, 117543, Singapore.
Kwai Wei ChanDepartment of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore, 117543, Singapore.
Seam Choon LawDepartment of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore, 117543, Singapore.
Pei-Wen OngDepartment of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore, 117543, Singapore.
Ethan Tze Cherng LimDepartment of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore, 117543, Singapore.
Fook Tim ChewDepartment of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore, 117543, Singapore. dbscft@nus.edu.sg.

Funding

Singapore Food Agency SFS_RND_SUFP_001_04
6 · The paper itself

Abstract

backgroundKale (Brassica oleracea var. acephala) is a high value leafy vegetable with an extensive domestication history and germplasm diversity, making it an ideal target for genetic improvement. To meet growing food security needs particularly with controlled environment agriculture (CEA) systems, specialized breeding strategies are required. The goal of this study was to survey the phenotypic architecture of a global kale germplasm collection under commercial CEA conditions. This study establishes a phenotypic baseline and serves as a hypothesis generating resource for future genetic and physiological studies in kale and other leafy vegetables grown under CEA.

resultsA total of 203 kale accessions were phenotyped for 113 quantitative traits using high-throughput phenotyping methods. Significant differentiation was observed across all traits, with coefficient of variation ranging from 2.5% to 180.7%, confirming broad genetic variability among accessions. Trait correlation networks and hierarchical clustering grouped phenotypes into seven biologically corresponding modules including leaf, stem and root morphology, plant architecture, hyperspectral indices, and seedling growth. These modules highlight coordinated phenotypic patterns among traits. Integrative yield analyses combining partial least squares variable importance in projection with differential trait analysis identified 28 phenotypes most strongly associated with total aboveground fresh weight, a robust proxy for CEA vegetative yield. Principal component analysis further distilled these traits into three orthogonal components explaining 87.1% of total yield variation. These components represented modules related to plant organ size, canopy structure, and density, emphasizing their biological contribution to harvestable biomass.

conclusionsThis study generates a foundational phenomics resource and comprehensive dissection of kale’s yield architecture under CEA conditions. The composition of traits identified constitutes a targeted set of breeding traits to be further validated for improved leafy vegetable yield. By integrating large-scale germplasm resources with phenomics, this work establishes the utility of a high-throughput phenotypic analysis for further leafy crop research and improvement.

Indexed as

BrassicaPhenomicsAgricultureEnvironment, ControlledGenetic VariationPhenotypePlant BreedingPlant LeavesBrassica oleracea var. acephalaHigh-throughput phenotypingIndoor farmingPhenomicsPlant breeding

Identifiers

PMID41699481
PMCPMC13014718

What Socratic holds

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LicenceCC BY
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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 Socratic graph.