光谱学与光谱分析, 2015, 35 (6): 1654, 网络出版: 2015-06-11   

估测田间烟叶色素含量的光谱模型研究

The Study of the Spectral Model for Estimating Pigment Contents of Tobacco Leaves in Field
作者单位
1 中国农业大学现代精细农业系统集成教育部重点实验室, 北京 100083
2 云南省烟草农业科学研究院, 云南 昆明 650021
3 中国农业大学资源与环境学院, 北京 100193
摘要
田间烟叶色素含量的光谱无损快速测量, 对烟草营养生长期的营养诊断与长势监测、 成熟期的烟叶品质评判具有重要的生产指导意义。 该研究的目的是利用烟叶田间光谱估测烟叶的叶绿素和类胡萝卜素含量。 研究采集了营养生长期和成熟期烟叶田间反射光谱, 测量了样品烟叶的色素含量, 利用支持向量机(SVM)和光谱指数法, 对营养生长期和成熟期烟叶样品用分期建模和混合建模两种方法建立色素含量估测模型, 并对模型的预测性能进行比较。 研究结果表明, 分期建模和混合建模对于烟叶色素含量的估测效果差异不显著。 对于叶绿素含量, SVM和光谱指数法均有较好的估测效果; 对于类胡萝卜素含量, SVM方法比光谱指数法具有更高的估测精度。 采用SVM方法对烟叶样品的叶绿素含量分期建模得到的估测决定系数和均方根误差分别为0.862 9和0.015 5, 对叶绿素含量混合建模得到的估测决定系数和均方根误差分别为0.898 5和0.012 3; 采用SVM方法对烟叶样品类胡萝卜素含量分期建模得到的估测决定系数和均方根误差分别为0.873 0和0.002 4, 对类胡萝卜素含量混合建模得到的估测决定系数和均方根误差分别为0.852 7和0.002 4。 该研究的创新点是通过支持向量机和光谱指数法采用分期建模以及混合建模的方式建立了烟叶样品色素含量的估测模型, 为烟草田间生产的质量控制、 烟叶的采收品质保证提供科学依据和技术支持。
Abstract
Fast and non-destructive measurements of tobacco leaf pigment contents by spectroscopy in situ in the field has great significance in production guidance for nutrient diagnosis and growth monitoring of tobacco in vegetative growth stage, and it is also very important for the quality evaluation of tobacco leaves in mature stage. The purpose of this study is to estimate the chlorophyll and carotenoid contents of tobacco leaves using tobacco leaf spectrum collected in the field. Reflectance spectrum of tobacco leaves in vegetative growth stage and mature stage were collected in situ in the field and the pigment contents of tobacco leaf samples were measured in this study, taking the tobacco leaf samples collected in each and both stages as modeling sets respectively, and using the methods of support vector machine (SVM) and spectral indice to establish the pigment content estimation models, and then compare the prediction performance of the models built by different methods. The study results indicated that the difference of estimation performance by each stage or mixed stages is not significant. For chlorophyll content, SVM and spectral indice modeling methods can both have a well estimation performance, while for carotenoid content, SVM modeling method has a better estimation performance than spectral indice. The coefficient of determination and the root mean square error of SVM model for estimating tobacco leaf chlorophyll content by each stage were 0.867 6 and 0.014 7, while the coefficient of determination and the root mean square error of SVM model for estimating tobacco leaf chlorophyll content by mixed stages were 0.898 6 and 0.012 3; The coefficient of determination and the root mean square error for estimating tobacco leaf carotenoid content by each stage were 0.861 4 and 0.002 5, while the coefficient of determination and the root mean square error of SVM model for estimating tobacco leaf carotenoid content by mixed stages were 0.839 9 and 0.002 5. The innovation point of this study is that on the basis of support vector machine and spectral indice, models established by each stage and mixed stages for estimating the pigment contents of tobacco leaf samples can provide scientific basis and technical support for quality control of tobacco leaf production in field and the ensurance of tobacco leaf recovery quality.

任晓, 劳彩莲, 徐照丽, 晋艳, 郭焱, 李军会, 杨宇虹. 估测田间烟叶色素含量的光谱模型研究[J]. 光谱学与光谱分析, 2015, 35(6): 1654. REN Xiao, LAO Cai-lian, XU Zhao-li, JIN Yan, GUO Yan, LI Jun-hui, YANG Yu-hong. The Study of the Spectral Model for Estimating Pigment Contents of Tobacco Leaves in Field[J]. Spectroscopy and Spectral Analysis, 2015, 35(6): 1654.

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