初烤完整烟叶总植物碱的近红外光谱测量方法研究

发布时间：2018-04-06 07:49

  本文选题：近红外光谱　切入点：完整烟叶　出处：《光谱学与光谱分析》2017年10期

【摘要】：为了探讨近红外光谱分析技术检测完整烟叶化学成分的可行性,利用近红外光谱分析技术,对初烤完整烟叶的光谱采集方式及总植物碱定量分析建模方法进行了研究。以云南省昆明市不同乡镇、不同品种的初烤烟叶为研究对象,分别采用烟叶的叶尖、叶中、叶基光谱及其平均光谱建立初烤完整烟叶总植物碱近红外偏最小二乘法(PLS)定量分析模型以选择出代表完整烟叶信息的建模光谱;分别用KS和SPXY方法对样品的校正集进行选择,采用向后区间偏最小二乘法(BiPLS)、无信息变量消除法(UVE)、竞争适应性重加权采样法(CARS)等选择特征变量,对模型进一步优化。研究结果表明,采用叶尖、叶中、叶基3个部位的平均光谱建立的模型相比单独每个部位光谱所建立模型的预测精度提高了8.5%~9.5%,与全光谱建模相比,用KS-BiPLS建立模型能明显改善模型的预测能力,模型的预测精度约提高了10%,模型的校正集决定系数和均方根误差分别为0.917 4和0.226 1,检验集决定系数和预测均方根误差分别为0.902 0和0.2007。本研究方法适用于完整的初烤烟叶,无需对样品进行预处理,对于大量的初烤烟叶,能够快速、无损测定烟叶总植物碱含量,可以节省大量的时间。同时,该研究为初烤烟叶分级、提高原料的品质提供技术支持,也将为卷烟生产的过程控制提供科学依据。
[Abstract]:In order to explore the feasibility of detecting the chemical components of intact tobacco leaves by near infrared spectroscopy (NIR), the spectral acquisition method and the quantitative analysis modeling method of total plant alkaloids were studied by using Near-infrared spectroscopy (NIR).The first baked tobacco leaves of different villages and towns in Kunming, Yunnan Province, were studied. The leaf tip and middle leaf of tobacco leaf were used respectively.The leaf base spectrum and its average spectrum were used to establish a quantitative analysis model of total alkaloids of the whole tobacco leaves, and to select the modeling spectrum representing the complete tobacco leaf information, and the calibration sets of the samples were selected by using KS and SPXY methods, respectively.The model is further optimized by using the backward interval partial least square method (BiPLS), the elimination of no information variables (UVEV), and the competitive adaptive re-weighted sampling method (CARSs).The results show that the prediction accuracy of the model based on the average spectra of the three parts of leaf tip, leaf and leaf base is 8.59.5than that of the model established by each part alone, which is compared with the full-spectrum model.The prediction ability of the model can be improved obviously by using KS-BiPLS. The prediction accuracy of the model is improved by about 10%. The calibration set decision coefficient and root mean square error of the model are 0.917 4 and 0.226 1 respectively, and the determination coefficient of test set and the prediction root mean square error are 0.902 0 and 0.2007 respectively.This method is suitable for the whole freshly baked tobacco leaves without pretreatment. For a large number of freshly baked tobacco leaves, it can be used to determine the total plant alkali content of tobacco leaves quickly and without damage, and can save a lot of time.At the same time, the research will provide technical support for the classification of freshly baked tobacco leaves and improve the quality of raw materials, as well as provide scientific basis for the process control of cigarette production.
【作者单位】： 中国农业大学现代精细农业系统集成研究教育部重点实验室;云南省烟草农业科学研究院;
【基金】：国家自然科学基金项目(61144012) 中国烟草总公司云南省公司项目(2015YN03)资助
【分类号】：O657.33;TS411
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本文编号：1718633