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Estimation of chlorophyll content in pepper leaves using spectral transmittance red-edge parameters

文献类型: 外文期刊

作者: Huang, Shuai 1 ; Wu, You 1 ; Wang, Qinglan 1 ; Liu, Jingli 2 ; Han, Qingyan 2 ; Wang, Jianfeng 2 ;

作者机构: 1.Jilin Acad Agr Sci, Changchun 130033, Peoples R China

2.Jilin Acad Vegetable & Flower Sci, Key Lab Facil Vegetable Jilin Prov, Changchun 130119, Peoples R China

3.Jilin Acad Vegetable & Flower Sci, Key Lab Facil Vegetable, Changchun, Jilin, Peoples R China

关键词: pepper leaf; chlorophyll content; red -edge parameters; ridge regression

期刊名称:INTERNATIONAL JOURNAL OF AGRICULTURAL AND BIOLOGICAL ENGINEERING ( 影响因子:1.885; 五年影响因子:2.232 )

ISSN: 1934-6344

年卷期: 2022 年 15 卷 5 期

页码:

收录情况: SCI

摘要: The objective of this work was to monitor the growth status of pepper and provide precise guidance on fertilization through non-destructive detection methods for chlorophyll content based on spectral transmittance. The analysis of the narrower red-edge spectral region (680-760 nm) reduced the requirements for light sources and light detection sensors, and provided a simpler and more accurate method of data acquisition for the process of developing instruments for estimating chlorophyll content in leaves. The red-edge region of spectral transmittance was demonstrated to be closely related to chlorophyll content. Regression models for estimating chlorophyll content with seven different methods were developed using the four red-edge parameters extracted from the red-edge region. The problems of multicollinearity of red-edge parameters and errors in model coefficients were solved by the ridge regression method in the process of building a multivariate regression model. The results indicated that the ridge regression method reduces the errors of the model coefficients and constant terms while improving the detection accuracy, thus the ridge regression model could estimate the leaf chlorophyll content more accurately and repeatedly.

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