基于可见-近红外光谱技术预测茶鲜叶全氮含量

doi:10.3964/j.issn.1000-0593(2008)12-2821-05

CORC > 北京大学 > 地球与空间科学学院

	基于可见-近红外光谱技术预测茶鲜叶全氮含量; Determination of Total Nitrogen Content in Fresh Tea Leaf Using Visible-Near Infrared Spectroscopy
	胡永光 ; 李萍萍 ; 母建华 ; 毛罕平 ; 吴才聪 ; 陈斌
刊名	光谱学与光谱分析
	2008
关键词	可见-近红外光谱偏最小二乘回归茶鲜叶全氮含量预测 Visible-near infrared spectroscopy Partial least squares regression Fresh tea leaf Total nitrogen content
DOI	10.3964/j.issn.1000-0593(2008)12-2821-05
英文摘要	为快速无损监测茶树氮素营养及其生长状况,基于可见-近红外光谱技术建立了茶鲜叶全氮含量的预测模型。以茶鲜叶为对象,田间试验使用便携式光谱仪采集叶片漫反射光谱信息,通过不同预处理和统计分析,建立茶鲜叶全氮含量预测的光谱模型。试验共采集111个样品,其中86个样品作校正集,25个样品作预测集。通过一阶导数与滑动平均滤波相结合的预处理方法,用7个主成分建立的偏最小二乘模型最好,其校正集均方根误差(RMSEC)为0.0973,预测集的相关系数为0.8881,预测均方根误差(RMSEP)为0.1304,预测的平均相对误差为4.339%。研究结果表明,利用可见-近红外光谱技术可以很好地预测茶鲜叶全氮含量,对...; To monitor tea tree growth and nitrogen nutrition in tea leaves, visible-near infrared spectroscopy was used to determine total nitrogen content. One hundred eleven fresh tea leaves of different nitrogen levels were sampled according to different tea type, plant age, leaf age, leaf position and soil nutrients, which covered a wide range of nitrogen content. Visible-near infrared reflectance spectra were scanned under the sunlight with a portable spectroradiometer (ASD FieldSpec 3) in field. The software of NIRSA developed by Jiangsu University was used to establish the calibration models and prediction models, which included spectra data editing, preprocessing, sample analysis, spectrogram comparison, calibration model and prediction model, analysis reporting and system configuration. Eighty six samples were used to establish the calibration model with the preprocessing of first/second-order derivative plus moving average filter and the algorithm of PLS regression, stepwise regression, principal component regression, PLS regression plus artificial neural network and so on. The result shows that the PI-S regression calibration model with 7 principal component factors after the preprocessing of first-order derivative plus moving average filter is the best and correspondingly the root mean square error of calibration is 0.973. Twenty five unknown samples were used to establish the prediction model and the correlation coefficient between predicted values and real values is 0.8881, while the root mean square error of prediction is 0.1304 with the mean relative error of 4.339%. Therefore, visible-near infrared spectroscopy has a huge potential for the determination of total nitrogen content in fresh tea leaves in a rapid and nondestructive way. Consequently, the technique can be significant to monitoring the tea tree growth and fertilization management.; SCI(E); EI; 中文核心期刊要目总览(PKU); 中国科技核心期刊(ISTIC); 3; 12; 2821-2825; 28
语种	中文
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/229337]
专题	地球与空间科学学院
推荐引用方式 GB/T 7714	胡永光,李萍萍,母建华,等. 基于可见-近红外光谱技术预测茶鲜叶全氮含量, Determination of Total Nitrogen Content in Fresh Tea Leaf Using Visible-Near Infrared Spectroscopy[J]. 光谱学与光谱分析,2008.
APA	胡永光,李萍萍,母建华,毛罕平,吴才聪,&陈斌.(2008).基于可见-近红外光谱技术预测茶鲜叶全氮含量.光谱学与光谱分析.
MLA	胡永光,et al."基于可见-近红外光谱技术预测茶鲜叶全氮含量".光谱学与光谱分析 (2008).