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基于荧光光谱的鲜茶叶片叶绿素含量定量分析 被引量:3

Quantitative Analysis of Chlorophyll Content in Tea Leaves by Fluorescence Spectroscopy
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摘要 茶叶叶片叶绿素含量的准确监测对茶树的营养状况和生长态势具有重要意义,为此基于叶绿素荧光光谱技术提出一种快速无损检测叶片叶绿素含量的方法。利用叶绿素荧光采集装置对茶叶叶片进行光谱采集,并测量叶绿素相对含量。采用S-G(Savitzky-Golay)平滑法对光谱进行预处理,可以消除大量的噪声信号;对所提方法与传统方法进行比较。实验结果表明,采用所提方法能够有效消除无关变量,对模型的优化可以得到较好的效果;简化变量后所建立的偏最小二乘模型在预测集上的相关系数为0.96,方均根误差为0.87,在建模集上的相关系数为0.96,方均根误差为0.95;荧光光谱结合化学计量学方法可以为茶叶叶片叶绿素含量的定量分析提供一种快速简便的分析方法。 Accurate monitoring of the chlorophyll content of tea leaves is of great significance to the nutritional status and growth of tea trees.Thus,a method for rapid and nondestructive detection of chlorophyll content of leaves is proposed on the basis chlorophyll fluorescence spectroscopy technology.The chlorophyll fluorescence collection device is used to collect the spectrum of tea leaves and measure the relative chlorophyll content.The Savitzky-Golay(S-G)smoothing method is used to preprocess the spectrum,which can eliminate a large number of noise signals.The proposed method is compared with the traditional method.Experimental results show that the proposed method can effectively eliminate irrelevant variables,and the optimization of the model can achieve better results.The partial least square model established after simplifying the variables has a correlation coefficient of 0.96 on the prediction set,and a root mean square error of 0.87.The correlation coefficient on the model set is 0.96,and the root mean square error is 0.95.The fluorescence spectroscopy and chemometric methods can provide a quick and easy analysis method for the quantitative analysis of tea leaf chlorophyll content.
作者 刘燕德 林晓东 高海根 高雪 王舜 Liu Yande;Lin Xiaodong;Gao Haigen;Gao Xue;Wang Sun(Institute of Optics Mechanics Electronics Technology and Application,East China Jiaotong University,Nanchang,Jiangxi 330013,China)
出处 《激光与光电子学进展》 CSCD 北大核心 2021年第8期444-453,共10页 Laser & Optoelectronics Progress
基金 国家自然科学基金(31760344) 江西省教育厅科学技术研究项目(GJJ190306)。
关键词 光谱学 荧光光谱 连续投影算法 后向区间偏最小二乘法 叶绿素 spectroscopy fluorescence spectroscopy successive projections algorithm backward interval partial least squares chlorophyll
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