Visible and near-infrared spectroscopic determination of sugarcane chlorophyll content using a modified wavelength selection method for multivariate calibration

Spectroscopy in the visible and near-infrared region (Vis-NIR) region has proven to be an effective technique for quantifying the chlorophyll contents of plants, which serves as an important indicator of their photosynthetic rate and health status. However, the Vis-NIR spectroscopy analysis confro...

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Main Authors: Ong, Pauline, Jian, Jinbao, Li, Xiuhua, Yin, Jianghua, Ma, Guodong
Format: Article
Language:English
Published: Elsevier 2024
Subjects:
Online Access:http://eprints.uthm.edu.my/11676/1/J16735_1feb4b8c010a4cf527ff4d0347961933.pdf
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author Ong, Pauline
Jian, Jinbao
Li, Xiuhua
Yin, Jianghua
Ma, Guodong
author_facet Ong, Pauline
Jian, Jinbao
Li, Xiuhua
Yin, Jianghua
Ma, Guodong
author_sort Ong, Pauline
collection UTHM
description Spectroscopy in the visible and near-infrared region (Vis-NIR) region has proven to be an effective technique for quantifying the chlorophyll contents of plants, which serves as an important indicator of their photosynthetic rate and health status. However, the Vis-NIR spectroscopy analysis confronts a significant challenge concerning the existence of spectral variations and interferences induced by diverse factors. Hence, the selection of characteristic wavelengths plays a crucial role in Vis-NIR spectroscopy analysis. In this study, a novel wavelength selection approach known as the modified regression coefficient (MRC) selection method was introduced to enhance the diagnostic accuracy of chlorophyll content in sugarcane leaves. Experimental data comprising spectral reflectance measurements (220–1400 nm) were collected from sugarcane leaf samples at different growth stages, including seedling, tillering, and jointing, and the corresponding chlorophyll contents were measured. The proposed MRC method was employed to select optimal wavelengths for analysis, and subsequent partial least squares regression (PLSR) and Gaussian process regression (GPR) models were developed to establish the relationship between the selected wavelengths and the measured chlorophyll contents. In comparison to full-spectrum modelling and other commonly employed wavelength selection techniques, the proposed simplified MRC-GPR model, utilizing a subset of 291 selected wavelengths, demonstrated superior performance. The MRC-GPR model achieved higher coefficient of determination of 0.9665 and 0.8659, and lower root mean squared error of 1.7624 and 3.2029, for calibration set and prediction set, respectively. Results showed that the GPR model, a nonlinear regression approach, outperformed the PLSR model.
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spelling uthm.eprints-116762024-11-14T00:00:49Z http://eprints.uthm.edu.my/11676/ Visible and near-infrared spectroscopic determination of sugarcane chlorophyll content using a modified wavelength selection method for multivariate calibration Ong, Pauline Jian, Jinbao Li, Xiuhua Yin, Jianghua Ma, Guodong SB183 -317 Field crops Including cereals, forage crops, grasses, legumes, root crops, sugar plants, textile plants, alkaloidal plants, medicinal plants Spectroscopy in the visible and near-infrared region (Vis-NIR) region has proven to be an effective technique for quantifying the chlorophyll contents of plants, which serves as an important indicator of their photosynthetic rate and health status. However, the Vis-NIR spectroscopy analysis confronts a significant challenge concerning the existence of spectral variations and interferences induced by diverse factors. Hence, the selection of characteristic wavelengths plays a crucial role in Vis-NIR spectroscopy analysis. In this study, a novel wavelength selection approach known as the modified regression coefficient (MRC) selection method was introduced to enhance the diagnostic accuracy of chlorophyll content in sugarcane leaves. Experimental data comprising spectral reflectance measurements (220–1400 nm) were collected from sugarcane leaf samples at different growth stages, including seedling, tillering, and jointing, and the corresponding chlorophyll contents were measured. The proposed MRC method was employed to select optimal wavelengths for analysis, and subsequent partial least squares regression (PLSR) and Gaussian process regression (GPR) models were developed to establish the relationship between the selected wavelengths and the measured chlorophyll contents. In comparison to full-spectrum modelling and other commonly employed wavelength selection techniques, the proposed simplified MRC-GPR model, utilizing a subset of 291 selected wavelengths, demonstrated superior performance. The MRC-GPR model achieved higher coefficient of determination of 0.9665 and 0.8659, and lower root mean squared error of 1.7624 and 3.2029, for calibration set and prediction set, respectively. Results showed that the GPR model, a nonlinear regression approach, outperformed the PLSR model. Elsevier 2024 Article PeerReviewed text en http://eprints.uthm.edu.my/11676/1/J16735_1feb4b8c010a4cf527ff4d0347961933.pdf Ong, Pauline and Jian, Jinbao and Li, Xiuhua and Yin, Jianghua and Ma, Guodong (2024) Visible and near-infrared spectroscopic determination of sugarcane chlorophyll content using a modified wavelength selection method for multivariate calibration. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 305. pp. 1-15. https://doi.org/10.1016/j.saa.2023.123477
spellingShingle SB183 -317 Field crops Including cereals, forage crops, grasses, legumes, root crops, sugar plants, textile plants, alkaloidal plants, medicinal plants
Ong, Pauline
Jian, Jinbao
Li, Xiuhua
Yin, Jianghua
Ma, Guodong
Visible and near-infrared spectroscopic determination of sugarcane chlorophyll content using a modified wavelength selection method for multivariate calibration
title Visible and near-infrared spectroscopic determination of sugarcane chlorophyll content using a modified wavelength selection method for multivariate calibration
title_full Visible and near-infrared spectroscopic determination of sugarcane chlorophyll content using a modified wavelength selection method for multivariate calibration
title_fullStr Visible and near-infrared spectroscopic determination of sugarcane chlorophyll content using a modified wavelength selection method for multivariate calibration
title_full_unstemmed Visible and near-infrared spectroscopic determination of sugarcane chlorophyll content using a modified wavelength selection method for multivariate calibration
title_short Visible and near-infrared spectroscopic determination of sugarcane chlorophyll content using a modified wavelength selection method for multivariate calibration
title_sort visible and near infrared spectroscopic determination of sugarcane chlorophyll content using a modified wavelength selection method for multivariate calibration
topic SB183 -317 Field crops Including cereals, forage crops, grasses, legumes, root crops, sugar plants, textile plants, alkaloidal plants, medicinal plants
url http://eprints.uthm.edu.my/11676/1/J16735_1feb4b8c010a4cf527ff4d0347961933.pdf
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