天津农业科学2024，Vol.30Issue(4)：82-90,9.DOI:10.3969/j.issn.1006-6500.2024.04.013
基于近红外光谱的醇化雪茄烟叶品种判别模型研究
Study on Discrimination Model of Alcoholized Cigar Tobacco Varieties Based on Near Infrared Spec-troscopy
摘要
Abstract
The aim of this study was to improve the discrimination accuracy of different post-alcoholised cigar tobacco varieties,pre-processing algorithms such as multiple scattering correction were used to denoise the spectral data in order to reduce the influence of experimental,environmental and instrumental noise on the data.Support vector machines,BP neural networks and random forests were combined to establish near-infrared spectral discrimination models for different varieties.The model performance was evaluated by ac-curacy and confusion matrix.The results showed that the model built with SNV+FD preprocessing algorithm and CARS feature wave-length selection algorithm was the most effective,and showed high accuracy in both training and prediction sets,which confirmed the feasibility of the use of NIR spectroscopy to quickly discriminate different varieties of post-alcoholisation cigar tobacco leaves.In sum-mary,the use of near infrared spectroscopy could realize the non-destructive and rapid discrimination of different varieties of alco-holized cigar tobacco,and further improve the industrial availability of cigar tobacco.关键词
雪茄烟叶/近红外光谱技术/品种判别/支持向量机/随机森林/BP神经网络Key words
cigar tobacco/near infrared spectroscopy/variety discrimination/support vector machine/random forest/BP neural network分类
农业科技引用本文复制引用
孙利,张毅,孟广云,余彦,高飞,王潞..基于近红外光谱的醇化雪茄烟叶品种判别模型研究[J].天津农业科学,2024,30(4):82-90,9.基金项目
中国烟草总公司云南省公司科技计划项目(2021530000242040) （2021530000242040）
