Chromatographic Profiling with Machine Learning Discriminates the Maturity Grades of Nicotiana tabacum L. Leaves
Abstract
:1. Introduction
2. Materials and Methods
2.1. Materials and Reagents
2.2. Sample Preparation
2.3. LC-MS Analysis
2.4. Data Preprocessing
2.5. Machine Learning Models of Maturity Grades
2.6. Identification of Metabolites
3. Results
3.1. Development of the Analytical Method
3.1.1. Extraction Solvent Optimization
3.1.2. Extraction Time Selection
3.1.3. Investigation of UPLC/IT-TOF MS Parameters
3.2. Validation of the Analytical Method
3.3. Classification of the Leaves from Different Maturity Grades
3.4. Identification of Metabolites from Different Maturity Grades
4. Discussions
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Maturity Grade | Producing Area | Variety | Growth Period | HARVEST PERIOD | Number of Samples |
---|---|---|---|---|---|
Unripe sample | Yunnan, China | K326 | April to August, 2020 | Transplanted for 70 days | 15 |
Ripe sample | Yunnan, China | K326 | April to August, 2020 | Transplanted for 80 days | 15 |
Overripe sample | Yunnan, China | K326 | April to August, 2020 | Transplanted for 90 days | 15 |
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Chen, Y.; Tian, M.; Zhao, G.; Lu, H.; Zhang, Z.; Zou, C. Chromatographic Profiling with Machine Learning Discriminates the Maturity Grades of Nicotiana tabacum L. Leaves. Separations 2021, 8, 9. https://doi.org/10.3390/separations8010009
Chen Y, Tian M, Zhao G, Lu H, Zhang Z, Zou C. Chromatographic Profiling with Machine Learning Discriminates the Maturity Grades of Nicotiana tabacum L. Leaves. Separations. 2021; 8(1):9. https://doi.org/10.3390/separations8010009
Chicago/Turabian StyleChen, Yi, Miao Tian, Gaokun Zhao, Hongmei Lu, Zhimin Zhang, and Congming Zou. 2021. "Chromatographic Profiling with Machine Learning Discriminates the Maturity Grades of Nicotiana tabacum L. Leaves" Separations 8, no. 1: 9. https://doi.org/10.3390/separations8010009