| Title: | Classification of the fragrant styles and evaluation of the aromatic quality of flue-cured tobacco leaves by machine-learning methods |
| Author(s): | Gu L; Xue L; Song Q; Wang F; He H; Zhang Z; |
| Address: | "* Institute of Tobacco Science and Technology, Fujian Agriculture and Forestry University, Fuzhou 350002, China. dagger Research Institute of Plateau Ecological, Agriculture and Animal Husbandry College, Tibet University, Linzhi 860000, China. double dagger College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China" |
| DOI: | 10.1142/S0219720016500335 |
| ISSN/ISBN: | 1757-6334 (Electronic) 0219-7200 (Linking) |
| Abstract: | "During commercial transactions, the quality of flue-cured tobacco leaves must be characterized efficiently, and the evaluation system should be easily transferable across different traders. However, there are over 3000 chemical compounds in flue-cured tobacco leaves; thus, it is impossible to evaluate the quality of flue-cured tobacco leaves using all the chemical compounds. In this paper, we used Support Vector Machine (SVM) algorithm together with 22 chemical compounds selected by ReliefF-Particle Swarm Optimization (R-PSO) to classify the fragrant style of flue-cured tobacco leaves, where the Accuracy (ACC) and Matthews Correlation Coefficient (MCC) were 90.95% and 0.80, respectively. SVM algorithm combined with 19 chemical compounds selected by R-PSO achieved the best assessment performance of the aromatic quality of tobacco leaves, where the PCC and MSE were 0.594 and 0.263, respectively. Finally, we constructed two online tools to classify the fragrant style and evaluate the aromatic quality of flue-cured tobacco leaf samples. These tools can be accessed at http://bioinformatics.fafu.edu.cn/tobacco" |
| Keywords: | *Algorithms Gas Chromatography-Mass Spectrometry/methods *Machine Learning Odorants/*analysis Plant Leaves/*chemistry Support Vector Machine Tobacco/*chemistry Volatile Organic Compounds/*analysis Tobacco aromatic quality classification and evaluation fra; |
| Notes: | "MedlineGu, Li Xue, Lichun Song, Qi Wang, Fengji He, Huaqin Zhang, Zhongyi eng Singapore 2016/10/05 J Bioinform Comput Biol. 2016 Dec; 14(6):1650033. doi: 10.1142/S0219720016500335. Epub 2016 Sep 9" |
