Spectral response to early detection of stressed oil palm seedlings using near-infrared reflectance spectra at region 900-1000 nm

Raypah, Muna E. and Muhammad Imran, Mohd Nasru and Muhammad Hazeem Hasnol, Nazim and Ahmad Fairuz, Omar and Siti Anis Dalila, Muhammad Zahir and Mohd Faizal, Jamlos and Muncan, Jelena S. (2023) Spectral response to early detection of stressed oil palm seedlings using near-infrared reflectance spectra at region 900-1000 nm. Infrared Physics & Technology, 135 (104984). pp. 1-12. ISSN 1350-4495. (Published)

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DOI/Official URL: https://doi.org/10.1016/j.infrared.2023.104984

Abstract

A method was developed based on spectral analysis and classification models for early detection of water stress level in the leaves of oil palm seedlings. The healthy (well-watered: D0) and water-stressed (subjected to water stress for five days: D1-D5) leaves of oil palm seedlings were investigated to identify and classify the stress levels. The stress levels were grouped as light, moderate, and severe. The region 900–1000 nm was selected because it is highly correlated with water content, particularly in terms of first and second derivatives. The measured reflectance spectra at 900–1000 nm were pre-processed using smoothing, standard normal variate (SNV), and first and second Savitzky-Golay (SG) derivatives. Principal component analysis (PCA) was performed on several transformed datasets to reduce the reflectance spectral dimension and derive the principal components (PCs). Support vector machine (SVM) and linear discriminant analysis (LDA) classification models were employed to the scores of PCs to achieve six classification levels of water stress. Classification accuracy was assessed using the overall accuracy and confusion matrix of testing datasets. The SVM and PCA-LDA classification models predicted the water stress levels with high average overall classification accuracy of 92 % and 94 % using the smoothed + SNV + first derivative and smoothed + SNV spectral dataset, respectively. The findings confirmed the potential of 900–1000 nm region to distinguish the different levels of water stress in oil palm seedlings.

Item Type:	Article
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Classification; Near-infrared Spectroscopy; Oil Palm Seedlings; Principal Component Analysis; Water Stress
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division:	Institute of Postgraduate Studies Centre of Excellence for Artificial Intelligence & Data Science Faculty of Electrical and Electronic Engineering Technology
Depositing User:	Mrs Norsaini Abdul Samat
Date Deposited:	03 Jul 2024 06:44
Last Modified:	03 Jul 2024 06:44
URI:	http://umpir.ump.edu.my/id/eprint/41791
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