Evidence map›Paper›PMID 41350356›Full record

ArticleScientific reports2025

​ Uncovering associations between DUS test traits and biochemical composition in safflower germplasm​​.

Lianjia Zhao, Fan Wang, Zhongqing Li, Yundan Cong, Chaohong Deng, Jing Xiao, Guorong Yan, Ning Liu, Yanyan Yang, Shuran He and 4 more

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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
0cells of the map it votes in
0citing 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

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

14 authors.

Lianjia Zhao *Crop Research Institute, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China.
Fan Wang *Crop Research Institute, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China.
Zhongqing LiCrop Research Institute, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China.
Yundan CongCrop Research Institute, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China.
Chaohong DengCrop Research Institute, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China.
Jing XiaoCrop Research Institute, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China.
Guorong YanCrop Research Institute, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China.
Ning LiuCrop Research Institute, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China.
Yanyan YangCrop Research Institute, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China.
Shuran HeCrop Research Institute, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China.
Axiang GaoCrop Research Institute, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China.
Yue MaCrop Research Institute, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China.
Yu SongCrop Research Institute, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China. songyu150@163.com.
Wei WangCrop Research Institute, Xinjiang Academy of Agricultural Sciences, Urumqi, 830091, China. wangweiwlj@163.com.

Funding

Xinjiang Academy of Agricultural Sciences Young Science and Technology Backbone Innovation Capacity Training Project xjnkq-2023017Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences Stable Support Project xjnkywdzc-2025003-01-5-5
6 · The paper itself

Abstract

Safflower (Carthamus tinctorius L.), a globally valued medicinal and oilseed crop, exhibits geographically structured biochemical signatures critical for its nutraceutical quality. Our study reveals safflower nutrient blueprint through an integrated approach combining phylogeography, chemometrics, and machine learning. We identified: (1) Evidence suggestive of genetic bottlenecks​​ in Xinjiang germplasm driving biochemical homogenization; (2) ​​Geography-driven chemodiversity​​ where cationic mineral-amino acid complexes adapt accessions to regional soil geochemistry; (3) ​​Evolutionary tradeoffs​​ manifesting as systemic mineral-fatty acid antagonisms; and (4) ​​Machine learning-enabled trait prediction​​, with crude fiber content showing relatively higher predictability due to developmental hardwiring. We revealed that fiber deposition prioritizes morpho-developmental regulators, while calcium accumulation depends on amino acid-mediated transport. Our findings establish that geographical isolation conserves nutrient signatures through reduced gene flow, while metabolic constraints limit co-optimization of competing traits. Our work provides predictive frameworks for precision breeding of climate-resilient safflower with enhanced nutraceutical value.

Indexed as

Carthamus tinctoriusQuantitative Trait, HeritableSeedsMachine LearningPhylogeographyPlant BreedingSoilSoilChemodiversity​Machine learningNutrient signaturesPredictive breedingSafflower

Identifiers

PMID41350356
PMCPMC12796480

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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.