Evidence map›Paper›PMID 42181729›Full record

ArticleRSC advances2026

Prediction and visual analysis of flue-cured tobacco aroma types based on machine learning and feature derivation.

Zhiying Wang, Shouchen Yang, Xiaoting Wang, Jun Qiu, Jianmin Cao, Xianwei Hao

Abstract read
In one paragraph

Article in RSC advances, 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
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

6 authors.

Zhiying WangTobacco Research Institute of CAAS Qingdao 266101 China 821012450666@caas.cn caojianmin@caas.cn +86-532-88703386 +86-18375487707 +86-13864806225.ORCID https://orcid.org/0009-0005-9704-1910
Shouchen YangTechnology Center, China Tobacco Shandong Industry Co., Ltd Qingdao 266101 China.
Xiaoting WangTechnology Center, China Tobacco Shandong Industry Co., Ltd Qingdao 266101 China.
Jun QiuTobacco Research Institute of CAAS Qingdao 266101 China 821012450666@caas.cn caojianmin@caas.cn +86-532-88703386 +86-18375487707 +86-13864806225.
Jianmin CaoTobacco Research Institute of CAAS Qingdao 266101 China 821012450666@caas.cn caojianmin@caas.cn +86-532-88703386 +86-18375487707 +86-13864806225.ORCID https://orcid.org/0000-0002-9179-7726
Xianwei HaoTechnology Center, China Tobacco Zhejiang Industrial Co. Ltd Hangzhou 310000 China hxwzjzy2020@163.com +86-571-81188181 +86-15968175953.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study aimed to investigate the relationship between aroma types and chemical properties of flue-cured tobacco (FCT), and to explore the applicability of machine learning (ML) combined with feature derivation in the FCT industry. A total of 619 Sichuan FCT samples representing three aroma types (fresh-sweet, honey-sweet, and mellow-sweet) were utilized. Feature derivation was performed based on 51 raw chemical indices, followed by a three-tier key indicator selection process incorporating separability analysis, Random Forest (RF) importance ranking, and redundant feature elimination

Identifiers

PMID42181729
PMCPMC13191578

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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.