Comparison of UV and visible autofluorescence of wheat grain tissues in macroscopic images of cross-sections and particles

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

doi:10.1016/j.compag.2016.06.016

Cited by 17 publications

(23 citation statements)

References 24 publications

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“…The quantitative features obtained from histological staining can also be related to the chemical composition of the tissues, such as the lignin content [ 31 ]. Acquisition devices such as confocal microscopy or microspectroscopy can provide more detailed information about the chemical content of plant tissues [ 13 – 15 ]. The field of view is however limited to several dozen cells.…”

Section: Discussionmentioning

confidence: 99%

“…The continuous development of imaging techniques has led to promising ways for investigating the chemical composition of plant tissues. Fluorescence imaging techniques allow for the localisation of specific proteins, polysaccharides and phenolic compounds [ 13 , 14 ]. Vibrational microspectroscopies such as infra-red or Raman spectroscopies provide complementary information about the molecular composition of the observed materials [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

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Histological quantification of maize stem sections from FASGA-stained images

et al. 2017

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BackgroundCrop species are of increasing interest both for cattle feeding and for bioethanol production. The degradability of the plant material largely depends on the lignification of the tissues, but it also depends on histological features such as the cellular morphology or the relative amount of each tissue fraction. There is therefore a need for high-throughput phenotyping systems that quantify the histology of plant sections.ResultsWe developed custom image processing and an analysis procedure for quantifying the histology of maize stem sections coloured with FASGA staining and digitalised with whole microscopy slide scanners. The procedure results in an automated segmentation of the input images into distinct tissue regions. The size and the fraction area of each tissue region can be quantified, as well as the average coloration within each region. The measured features can discriminate contrasted genotypes and identify changes in histology induced by environmental factors such as water deficit.ConclusionsThe simplicity and the availability of the software will facilitate the elucidation of the relationships between the chemical composition of the tissues and changes in plant histology. The tool is expected to be useful for the study of large genetic populations, and to better understand the impact of environmental factors on plant histology.Electronic supplementary materialThe online version of this article (doi:10.1186/s13007-017-0225-z) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Histological quantification of maize stem sections from FASGA-stained images

et al. 2017

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“…We conducted several studies on the fluorescence properties of wheat grain tissues [19,27] in which we noticed another remarkable feature of the cavity content: it appeared to fluoresce under UV excitation. Examples of fluorescence imaging of wheat grain sections is given in Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Fluorescence emission was valued based on the grey scale intensity of pixels. Pseudospectra were obtained from the multispectral images: pixels were manually selected in targeted structures and their intensity profile was extracted using a home-made function in Matlab [27].…”

Section: J O U R N a L P R E -P R O O Fmentioning

confidence: 99%

The endosperm cavity of wheat grains contains a highly hydrated gel of arabinoxylan

et al. 2021

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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“…4. If the structural state (powder vs section) was shown to have no impact on tissues extracted from wheat grain [7], this must be further investigated on maize stem in order to understand this discrepancy. The impact of particle size and thickness on fluorescence recovery should be integrated in the data exploration.…”

Section: Fluorescence Profiles Variability Encountered In Maize Powdementioning

confidence: 99%

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

et al. 2017

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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.

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Comparison of UV and visible autofluorescence of wheat grain tissues in macroscopic images of cross-sections and particles

Cited by 17 publications

References 24 publications

Histological quantification of maize stem sections from FASGA-stained images

Histological quantification of maize stem sections from FASGA-stained images

The endosperm cavity of wheat grains contains a highly hydrated gel of arabinoxylan

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

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