Evidence map›Paper›PMID 36844088›Full record

ArticleFrontiers in plant science2023

Integrative analysis of sensory evaluation and non-targeted metabolomics to unravel tobacco leaf metabolites associated with sensory quality of heated tobacco.

Lu Zhao, Shanzhai Shang, Yongfeng Tian, Yulong Gao, Zhongbang Song, Lijuan Peng, Zhuolin Li, Bingwu Wang

Abstract read
In one paragraph

Article in Frontiers in plant science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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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3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

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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.

Lu ZhaoNational Tobacco Genetic Engineering Research Center, Yunnan Academy of Tobacco Agricultural Sciences, Kunming, Yunnan, China.
Shanzhai ShangResearch and Development Center, China Tobacco Yunnan Industrial Co., Ltd., Kunming, Yunnan, China.
Yongfeng TianResearch and Development Center, China Tobacco Yunnan Industrial Co., Ltd., Kunming, Yunnan, China.
Yulong GaoNational Tobacco Genetic Engineering Research Center, Yunnan Academy of Tobacco Agricultural Sciences, Kunming, Yunnan, China.
Zhongbang SongNational Tobacco Genetic Engineering Research Center, Yunnan Academy of Tobacco Agricultural Sciences, Kunming, Yunnan, China.
Lijuan PengLaboratory of Tobacco Chemistry, Yunnan Tobacco Quality Supervision and Test Station, Kunming, Yunnan, China.
Zhuolin LiDepartment of Technical Support, Malong Branch of Qujing Tobacco Company, Qujing, Yunnan, China.
Bingwu WangNational Tobacco Genetic Engineering Research Center, Yunnan Academy of Tobacco Agricultural Sciences, Kunming, Yunnan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Heated tobacco ( Methods: In present study, five tobacco varieties were evaluated as heated tobacco for sensory quality by an expert panel and the volatile and non-volatile metabolites were analyzed by non-targeted metabolomics profiling. Results: The five tobacco varieties had distinct sensory qualities and can be classified into higher and lower sensory rating classes. Principle component analysis and hierarchical cluster analysis showed that leaf volatile and non-volatile metabolome annotated were grouped and clustered by sensory ratings of heated tobacco. Orthogonal projections to latent structures discriminant analysis followed by variable importance in projection and fold-change analysis revealed 13 volatiles and 345 non-volatiles able to discriminate the tobacco varieties with higher and lower sensory ratings. Some compounds such as β-damascenone, scopoletin, chlorogenic acids, neochlorogenic acids, and flavonol glycosyl derivatives had strong contribution to the prediction of sensory quality of heated tobacco. Several Discussion: Taken together, these discriminating volatile and non-volatile metabolites support the role of leaf metabolites in affecting the sensory quality of heated tobacco and provide new information on the types of leaf metabolites that can be used to predict applicability of tobacco varieties for heated tobacco products.

Indexed as

discriminating metabolitesheated tobacco productsnon-targeted metabolomics profilingorthogonal projections to latent structures discriminant analysissensory evaluation

Identifiers

PMID36844088
PMCPMC9944805

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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.