Evidence map›Paper›PMID 41210779›Full record

ArticleACS omega2025

Green Extraction Tree: A Novel Tool to Greenness Metric for Green Extraction of Natural Products.

Linhong Fan, Wenxiang Fan, Zhang Hui, Qian Zhang, Jinfa Tang, Zhengtao Wang, Li Yang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in ACS omega, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

7 authors.

Linhong FanState Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicines, The MOE Key Laboratory of Standardization of Chinese Medicines, Shanghai Key Laboratory of Compound Chinese Medicines, and SATCM Key Laboratory of New Resources and Quality Evaluation of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Wenxiang FanState Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicines, The MOE Key Laboratory of Standardization of Chinese Medicines, Shanghai Key Laboratory of Compound Chinese Medicines, and SATCM Key Laboratory of New Resources and Quality Evaluation of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Zhang HuiFirst Affiliated Hospital of Henan University of Chinese Medicine, Henan Province Engineering Research Center for Clinical Application, Evaluation and Transformation of Traditional Chinese Medicine, Henan Provincial Key Laboratory for Clinical Pharmacy of Traditional Chinese Medicine, Henan Province Engineering Research Center of Safety Evaluation and Risk Management of Traditional Chinese Medicine, Zhengzhou, Henan 450000, China.
Qian ZhangState Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicines, The MOE Key Laboratory of Standardization of Chinese Medicines, Shanghai Key Laboratory of Compound Chinese Medicines, and SATCM Key Laboratory of New Resources and Quality Evaluation of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Jinfa TangFirst Affiliated Hospital of Henan University of Chinese Medicine, Henan Province Engineering Research Center for Clinical Application, Evaluation and Transformation of Traditional Chinese Medicine, Henan Provincial Key Laboratory for Clinical Pharmacy of Traditional Chinese Medicine, Henan Province Engineering Research Center of Safety Evaluation and Risk Management of Traditional Chinese Medicine, Zhengzhou, Henan 450000, China.ORCID https://orcid.org/0000-0001-7786-0955
Zhengtao WangState Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicines, The MOE Key Laboratory of Standardization of Chinese Medicines, Shanghai Key Laboratory of Compound Chinese Medicines, and SATCM Key Laboratory of New Resources and Quality Evaluation of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.ORCID https://orcid.org/0000-0003-2797-4625
Li YangState Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicines, The MOE Key Laboratory of Standardization of Chinese Medicines, Shanghai Key Laboratory of Compound Chinese Medicines, and SATCM Key Laboratory of New Resources and Quality Evaluation of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A comprehensive and intuitive evaluation tool, termed the Green Extraction Tree (GET), has been developed to assess the greenness of the sample preparation process in the green extraction of natural products. The assessment criteria integrate the 10 principles of green sample preparation with the 6 principles of green extraction of natural products, encompassing the entire natural product extraction process, including samples, solvents and reagents, energy consumption, byproducts and waste, process risk, and extract quality. The GET employs a "tree" pictogram to classify and evaluate the greenness of various aspects of the natural product extraction process, using three different color markers (green, yellow, red) to represent three distinct levels of environmental impact (low, medium, high) across different processes. In terms of quantitative analysis, the values 2, 1 and 0 are assigned to green, yellow, and red respectively, the final scores are used to conduct a horizontal comparison of the greenness of different processes. The evaluation procedure was conducted using an open-access toolkit that generates the GET pictogram corresponding to each extraction method, facilitating a visual assessment of the greenness of natural product extraction methods. Through five different extraction methods as case studies, the difference of greenness and extraction process to be improved of each method were successfully identified by GET. Additionally, compared to the other representative green assessment tools, GET presents a unique novel perspective and exhibits greater applicability to the natural product green extraction process.

Identifiers

PMID41210779
PMCPMC12593995

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.