SIHM: A high-resolution hyperspectral microscope for plant diagnostics

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Authors: Maria Merin Antony, C. S. Suchand Sandeep, Murukeshan Vadakke Matham
Cited by: 0
References: 32

Abstract

Plant diagnostics plays a key role in optimizing plant nutrition and improving overall crop yield. For a reliable plant diagnosis, it is important to analyse both cell structure and pigment level changes to understand the stress type and the mechanisms involved. However, most of the existing techniques are unable to simultaneously visualize both changes, and some of the techniques are destructive in nature and lack sensitivity. High-resolution hyperspectral microscopy offers the capability to analyse the spectral characteristics of biological tissues, yet its application in plant diagnostics remains limited, particularly for probing deeper leaf layers. In addition, accurate characterization of different leaf layers requires high optical sectioning capability, which is lacking in conventional hyperspectral microscopes. In this context, a Structured Illumination Hyperspectral Microscope (SIHM) is developed, combining optical sectioning and hyperspectral imaging capabilities to enable layer-specific structural and spectral characterization of intact plant tissues. Sinusoidally modulated structured illumination patterns are projected onto the region of interest on the sample, and spectral images are captured using a hyperspectral imager. The developed microscope offers a spectral resolution of 1.3 nm, an optical sectioning ability of ~5.2 μm, and a spatial resolution of ~586 nm. The system's ability for non-destructive plant diagnostics is demonstrated through the characterization of pigment changes associated with chlorosis and necrosis, highlighting its potential for the assessment of plant health and physiology.

Fields of Study & Subjects

Leaf Properties and Growth Measurement Remote Sensing in Agriculture Spectroscopy and Chemometric Analyses

Publication details

Journal / source
Information Processing in Agriculture
Publisher
Elsevier BV
Publication date
1 July 2026
Language
EN