Laser & Optoelectronics Progress, Volume. 58, Issue 8, 0830001(2021)

Quantitative Analysis of Chlorophyll Content in Tea Leaves by Fluorescence Spectroscopy

Yande Liu*, Xiaodong Lin, Haigen Gao, Xue Gao, and Sun Wang
Author Affiliations
  • Institute of Optics Mechanics Electronics Technology and Application, East China Jiaotong University, Nanchang, Jiangxi 330013, China
  • show less

    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.

    Tools

    Get Citation

    Copy Citation Text

    Yande Liu, Xiaodong Lin, Haigen Gao, Xue Gao, Sun Wang. Quantitative Analysis of Chlorophyll Content in Tea Leaves by Fluorescence Spectroscopy[J]. Laser & Optoelectronics Progress, 2021, 58(8): 0830001

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Spectroscopy

    Received: Jul. 30, 2020

    Accepted: Sep. 10, 2020

    Published Online: Apr. 22, 2021

    The Author Email: Liu Yande (jxliuyd@163.com)

    DOI:10.3788/LOP202158.0830001

    Topics