Identification of tissular origin of particles based on autofluorescence multispectral image analysis at the macroscopic scale

Mathias Corcel,Cécile Barron,Marie-Françoise Devaux,Fabienne Guillon

doi:10.1051/epjconf/201714005012

Abstract

Powders produced from plant materials are heterogeneous in relation to native plant heterogeneity, and during grinding, dissociation often occurred at the tissue scale. The tissue composition of powdery samples could be modified through dry fractionation diagrams and impact their end-uses properties. If tissue identification is often made on native plant structure, this characterization is not straightforward in destructured samples such powders. Taking advantage of the autofluorescence properties of cell wall components, multispectral image acquisition is envisioned to identify the tissular origin of particles. Images were acquired on maize stem sections and ground tissues isolated from the same stem by hand dissection. The variability in fluorescence intensity profiles was analysed using principal component analysis. The correspondence between fluorescence profiles and the different tissues observed in maize sections was assessed based on histology or known compositional heterogeneity. Similar variability was encountered in fluorescence profiles extracted from powder leading to the potential ability to predict tissular origin based on this autofluorescence multispectral signal.

Highlights

Plants are heterogeneous materials made up of organs which are themselves made up of various tissues including different cell types
We propose to calibrate multivariate maps using data coming from the multispectral images of tissue sections and to validate the maps by projecting reference powders data issued from pure plant tissues
Emission light was recovered through long pass filters and, taking advantage of the RGB channels of the colour camera (DSRiI, Nikon, Japan), each image were split in three channels and stack all together to obtain a 12 channels multispectral image (Fig. 2)

Summary

Introduction

Plants are heterogeneous materials made up of organs (stem, grains, leaves...) which are themselves made up of various tissues including different cell types. To be applicable to plant particles analysis, the spectral imaging must deal with: low sample preparation (eg avoid sample section), a fine resolution (

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Methods

Results