Reflectance spectra for identifying stress in different parts of leaf: a case study on oil palm seedlings-Reference-Cited by-同舟云学术

Reflectance spectra for identifying stress in different parts of leaf: a case study on oil palm seedlings

Published:2024-01-28 Issue:3 Volume:45 Page:954-980
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Raypah Muna E.¹,Imran Mohd Nasru Muhammad²,Hazeem Hasnol Nazim Muhammad²,Omar Ahmad Fairuz²^ORCID,Muncan Jelena³,Muhammad Zahir Siti Anis Dalila⁴,Jamlos Mohd Faizal¹⁴,Mahmod Jasim Haider⁵

Affiliation:

1. Centre of Excellence for Artificial Intelligence & Data Science, Universiti Malaysia Pahang Al-Sultan Abdullah, Gambang, Malaysia

2. School of Physics, Universiti Sains Malaysia, Pulau Pinang, Malaysia

3. Aquaphotomics Research Department, Faculty of Agriculture, Kobe University, Kobe, Japan

4. Faculty of Electrical & Electronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, Pekan, Malaysia

5. School of Biological Sciences, Al-Muthanna University, Samawah, Iraq

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2024.2305626

Reference84 articles.

1. Anatomical feature of royal palm leaf sheath

2. Early Detection of Ganoderma Basal Stem Rot of Oil Palms Using Artificial Neural Network Spectral Analysis

3. Close-range hyperspectral image analysis for the early detection of stress responses in individual plants in a high-throughput phenotyping platform

4. Identification of a Suitable Machine Learning Model for Detection of Asymptomatic Ganoderma boninense Infection in Oil Palm Seedlings Using Hyperspectral Data

5. Oil palm leaves and roots differ in physiological response, antioxidant enzyme activities and expression of stress-responsive genes upon exposure to drought stress

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