英文论文
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文献类型
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Journal article (JA)
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题名
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Auto-classification of biomass through characterization of their pyrolysis behaviors using thermogravimetric analysis with support vector machine algorithm: case study for tobacco
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作者
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Yin, Chao; Deng, Xiaohua; Yu, Zhiqiang; Liu, Zechun; Zhong, Hongxiang; Chen, Ruting; Cai, Guohua; Zheng, Quanxing; Liu, Xiucai; Zhong, Jiawei; Ma, Pengfei; He, Wei; Lin, Kai; Li, Qiaoling; Wu, Anan
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作者单位
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[Yin, Chao; Chen, Ruting; Wu, Anan] Xiamen Univ, Coll Chem & Chem Engn, Fujian Prov Key Lab Theoret & Computat Chem, Xiamen 361005, Fujian, Peoples R China. [Deng, Xiaohua; Yu, Zhiqiang; Liu, Zechun; Zhong, Hongxiang; Cai, Guohua; Zheng, Quanxing; Liu, Xiucai; Zhong, Jiawei; Ma, Pengfei; He, Wei; Lin, Kai; Li, Qiaoling] China Tobacco Fujian Ind Co Ltd, Technol Ctr, Xiamen 361021, Fujian, Peoples R China.
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通讯作者地址
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Xiamen Univ, Coll Chem & Chem Engn, Fujian Prov Key Lab Theoret & Computat Chem, Xiamen 361005, Fujian, Peoples R China.; China Tobacco Fujian Ind Co Ltd, Technol Ctr, Xiamen 361021, Fujian, Peoples R China.
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Email
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lql10684@fjtic.cn; ananwu@xmu.edu.cn
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ResearchID
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ORCID
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期刊名称
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Biotechnology for Biofuels
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出版社
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BioMed Central Ltd
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ISSN
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1754-6834
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出版信息
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2021-12, 14 (1):.
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JCR
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2
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影响因子
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ISBN
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基金
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National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [21773193]; fundamental research Funds for the Central UniversitiesFundamental Research Funds for the Central Universities [20720160031]
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会议名称
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会议地点
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会议开始日期
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会议结束日期
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关键词
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Biomass; Bioproducts; Chemical analysis; Classification (of information); Infrared devices; Near infrared spectroscopy; Pyrolysis; Smoke; Support vector machines; Tobacco
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摘要
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Background During the biomass-to-bio-oil conversion process, many studies focus on studying the association between biomass and bio-products using near-infrared spectra (NIR) and chemical analysis methods. However, the characterization of biomass pyrolysis behaviors using thermogravimetric analysis (TGA) with support vector machine (SVM) algorithm has not been reported. In this study, tobacco was chosen as the object for biomass, because the cigarette smoke (including water, tar, and gases) released by tobacco pyrolysis reactions decides the sensory quality, which is similar to biomass as a renewable resource through the pyrolysis process. Results SVM algorithm has been employed to automatically classify the planting area and growing position of tobacco leaves using thermogravimetric analysis data as the information source for the first time. Eighty-eight single-grade tobacco samples belonging to four grades and eight categories were split into the training, validation, and blind testing sets. Our model showed excellent performances in both the training and validation set as well as in the blind test, with accuracy over 91.67%. Throughout the whole dataset of 88 samples, our model not only provides precise results on the planting area of tobacco leave, but also accurately distinguishes the major grades among the upper, lower, and middle positions. The error only occurs in the classification of subgrades of the middle position. Conclusions From the case study of tobacco, our results validated the feasibility of using TGA with SVM algorithm as an objective and fast method for auto-classification of tobacco planting area and growing position. In view of the high similarity between tobacco and other biomasses in the compositions and pyrolysis behaviors, this new protocol, which couples the TGA data with SVM algorithm, can potentially be extrapolated to the auto-classification of other biomass types.
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一级学科
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Biotechnology & Applied Microbiology; Energy & Fuels
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WOS入藏号
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WOS:000644833600001
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EI收录号
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20211810281052
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DOI
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10.1186/s13068-021-01942-w
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ESI
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收录于
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SCIE, EI
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