ArticleACS omega2022
Quantitative Analysis of Routine Chemical Constituents of Tobacco Based on Thermogravimetric Analysis.
Article in ACS omega, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 16 citations in OpenAlex.
- Construction of a sensory quality evaluation model for tobacco leaves from Henan Province and its application in tobacco quality assessment.Frontiers in plant science · 2026Article
- Effects of moisture-preserving yellowing process optimization on cell physiology and post-curing chemical composition.BMC plant biology · 2025Article
- Review
- A model for tobacco growing area classification based on time series features of thermogravimetric analysis.Biotechnology for biofuels and bioproducts · 2025Article
- Insights into tobacco leaf quality deterioration under long-term storage by investigating dynamic phytochemical and metabolite profile variations.BMC plant biology · 2025Article
- Microbial community succession during tobacco fermentation reveals a flavor-improving mechanism.Frontiers in bioengineering and biotechnology · 2025Article
- Article
- Quantitative analysis of pyrolysis characteristics and chemical components of tobacco materials based on machine learning.Frontiers in chemistry · 2024Article
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As the most basic indexes to evaluate the quality of tobacco, the contents of routine chemical constituents in tobacco are mainly detected by continuous-flow analysis at present. However, this method suffers from complex operation, time consumption, and environmental pollution. Thus, it is necessary to establish a rapid accurate detection method. Herein, different from the ongoing research studies that mainly chose near-infrared spectroscopy as the information source for quantitative analysis of chemical components in tobacco, we proposed for the first time to use the thermogravimetric (TG) curve to characterize the chemical composition of tobacco. The quantitative analysis models of six routine chemical constituents in tobacco, including total sugar, reducing sugar, total nitrogen, total alkaloids, chlorine, and potassium, were established by the combination of TG curve and partial least squares algorithm. The accuracy of the model was confirmed by the value of root mean square error for prediction. The models can be used for the rapid accurate analysis of compound contents. Moreover, we performed an in-depth analysis of the chemical mechanism revealed by the result of the quantitative model, namely, the regression coefficient, which reflected the correlation degree between the six chemicals and different stages of the tobacco thermal decomposition process.
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Registered trials
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.