Evidence map›Paper›PMID 41481617›Full record

ArticlePloS one2026

Effects of drying processes on the chemical and physical properties of safflower: Towards a multidimensional quality evaluation model.

Juan Li, Rui Wang, Cuiping Chen, Xulong Huang, Bin Xian, Tang Lv, Chaoxiang Ren, Qinghua Wu, Feiyan Wen, Jie Yan and 1 more

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
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

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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

11 authors.

Juan LiChinese Medicine Germplasm Resources Innovation and Effective Uses Key Laboratory of Sichuan Province, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Rui WangCollege of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Cuiping ChenChinese Medicine Germplasm Resources Innovation and Effective Uses Key Laboratory of Sichuan Province, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Xulong HuangCollege of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Bin XianChinese Medicine Germplasm Resources Innovation and Effective Uses Key Laboratory of Sichuan Province, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Tang LvCollege of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Chaoxiang RenCollege of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Qinghua WuChinese Medicine Germplasm Resources Innovation and Effective Uses Key Laboratory of Sichuan Province, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Feiyan WenCollege of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Jie YanChinese Medicine Germplasm Resources Innovation and Effective Uses Key Laboratory of Sichuan Province, Chengdu University of Traditional Chinese Medicine, Chengdu, China.ORCID https://orcid.org/0000-0002-9694-8722
Jin PeiChinese Medicine Germplasm Resources Innovation and Effective Uses Key Laboratory of Sichuan Province, Chengdu University of Traditional Chinese Medicine, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The drying process is a critical step in determining the quality of safflower (Carthamus tinctorius L.). This study aims to systematically evaluate the effects of different drying methods on the chemical composition, color, morphology, odor, and microstructure of safflower dried petals, and to establish a comprehensive quality evaluation model for safflower based on machine learning. The results showed that drying methods significantly altered the chemical composition of safflower. Freeze-dried samples exhibited significantly higher levels of the active components hydroxysafflower yellow pigment A and anhydrosafflower yellow pigment B compared to other methods (p < 0.05), presenting a bright orange color and a mild odor. Microscopic structure and morphological analysis indicate that freeze-dried safflower effectively preserves its morphological characteristics, with a clear arrangement of cells and lower overall shrinkage. Based on nineteen quality parameters, nine quality evaluation models for safflower were constructed. The multiclassification decision forest model achieved a prediction accuracy of 89.1%. The importance analysis of quality parameters revealed that the B, G, and R color features in the RGB color mode are the most critical indicators for evaluating safflower quality. This study provides key basis for optimizing the drying process of safflower. The comprehensive evaluation model established provides a technical foundation for intelligent evaluation and standardized control of safflower quality, which is of significant practical value for improving safflower quality and promoting the standardized development of the industry.

Indexed as

Carthamus tinctoriusDesiccationColorFlowersFreeze DryingMachine LearningOdorants

Identifiers

PMID41481617
PMCPMC12758763

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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.