光谱学与光谱分析, 2017, 37 (7): 2046, 网络出版: 2017-08-30  

应用近红外光谱和多算法融合方法分析烤烟的香型风格特征

Analysis of Flue-Cured Tobacco Flavor Style Features Using Near-Infrared Spectroscopy and Multiple Algorithms Fusion
作者单位
1 中国农业大学信息与电气工程学院, 北京 100083
2 中国农业大学, 教育部现代精细农业系统集成研究重点实验室, 北京 100083
3 上海烟草集团有限责任公司, 上海 200082
摘要
以全国17个主要烤烟产地省份中收集的3 914个烟叶样品的近红外光谱为实验对象, 其中浓香型、 中间香型、 清香型烟叶光谱分别865条、 1 403条、 1 646条, 应用近红外光谱和多算法融合方法分析其香型风格特征。 在以产地进行初步划分烟叶香型以及认可过渡型和非典型香型类型的基础上, 选取基于主成分及Fisher准则的投影法(PPF)、 偏最小二乘判别(DPLS)、 支持向量机(SVM)作为单分类器, 得到各个算法第1和2判别分析结果; 应用PPF-DPLS-SVM融合和各算法第1和2判别分析结果, 将预测验证样品的分析结果详细划分为典型、 过渡型、 非典型香型样品(分别为493, 392, 115个); 其中典型香型烟叶样品的判别准确率达到927%, 较未进行典型样品划分时PPF, DPLS, SVM单算法的识别准确率分别提高了302%, 154%, 166%。 样品数据来源于全国主要烤烟产地, 数据量大, 代表性较好, 分析结果具有一定普遍性; 提出的多算法融合分析方法大幅度提高了通过客观数据判别烤烟香型的准确率; 同时, 将烤烟香型细划分为典型、 过渡型和非典型香型的方式, 对烤烟烟叶原料的科学合理利用以及烟叶原料的模块化工业加工等有指导作用。
Abstract
In this paper, 3 914 near infrared spectrums of flue-cured tobacco samples was tested. These tobacco samples were collected in 17 provincial origins, including the NONG (Luzhou) flavor 865 cartons, Intermediate flavor 1 646 cartons and QING flavor (Fen) 1 646 cartons. We used near-Infrared spectroscopy and multiple algorithms fusion to analyze flue-cured tobacco flavor style features. Based on the preliminary classification of tobacco flavor according to different origins, accepting transitional and atypical flavor, tobacco flavor classification models of PPF (Projection of Basing on Principal Component and Fisher Criterion), DPLS (Partial least squares discriminant) and SVM (Support vector machine) were established respectively; and 1st and 2nd discriminant results of each algorithm can be known. Using PPF-DPLS-SVM fusion and discriminant results (1st and 2nd) of each algorithm, prediction results can be refined into typical, transitional and atypical flavor. The numbers of three flavors were 493, 392 and 115, respectively. The discriminant accuracy rate of typical flavor was improved to 927%. And it was improved 302%, 154% and 166% to compared with those achieved using PPF, DPLS and SVM, respectively. The tested samples were collected in main origins of China, which were abundant with great representativeness, therefore, the analysis result had practical application. The analysis method presented greatly improved the discriminant accuracy rate of flue-cured tobacco flavor, which was better than that of the classification according to objective data. The method refining flue-cured tobacco into typical, transitional and atypical flavor, provided guidance to the scientific application and module industrial processing of raw flue-cured tobacco.

栾丽丽, 王宇恒, 胡文雁, 杨凯, 束茹欣, 李军会, 赵龙莲, 张晔晖. 应用近红外光谱和多算法融合方法分析烤烟的香型风格特征[J]. 光谱学与光谱分析, 2017, 37(7): 2046. LUAN Li-li, WANG Yu-heng, HU Wen-yan, YANG Kai, SHU Ru-xin, LI Jun-hui, ZHAO Long-lian, ZHANG Ye-hui. Analysis of Flue-Cured Tobacco Flavor Style Features Using Near-Infrared Spectroscopy and Multiple Algorithms Fusion[J]. Spectroscopy and Spectral Analysis, 2017, 37(7): 2046.

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