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Home / Regular Issue / JST Vol. 31 (6) Oct. 2023 / JST-4022-2022


A Review on Analysis Method of Proximal Hyperspectral Imaging for Studying Plant Traits

Jian Wen Lin, Mohd Shahrimie Mohd Asaari, Haidi Ibrahim, Mohamad Khairi Ishak dan Abdul Sattar Din

Pertanika Journal of Science & Technology, Volume 31, Issue 6, October 2023


Keywords: Deep learning, hyperspectral imaging, machine learning, spatial information, spectral information

Published on: 12 October 2023

Understanding the response of plant traits towards different growing conditions is crucial to maximizing crop yield and mitigating the effect of the food crisis. At present, many imaging techniques are being explored and utilized within plant science to solve problems in agriculture. One of the most advanced imaging methods is hyperspectral imaging (HSI), as it carries the spectral and spatial information of a subject. However, in most plant studies that utilized HSI, the focus was given to performing an analysis of spectral information. Even though a satisfactory performance was achieved, there is potential for better performance if spatial information is given more consideration. This review paper (1) discusses the potential of the proximal HSI analysis methods for plant traits studies, (2) presents an overview of the acceptance of hyperspectral imaging technology for plant research, (3) presents the basic workflow of hyperspectral imaging in proximal settings concerning the image acquisition settings, image pre-processing, spectral normalization, and spectral analysis, (4) discusses the analysis methods that utilize spatial information, and (5) addresses some technical challenges related to implementing hyperspectral imaging in proximal settings for plant traits analysis.

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