A first attempt to combine NIRS and plenoptic cameras for the assessment of grasslands functional diversity and species composition

Grassland represents more than half of the agricultural land. Numerous metrics (biomass, functional trait, species composition) can be used to describe grassland vegetation and its multiple functions. The measures of these metrics are generally destructive and laborious. Indirect measurements using optical tools are a possible alternative. Some tools have high spatial resolutions (digital camera), and others have high spectral resolutions (Near Infrared Spectrometry NIRS). A plenoptic camera is a multifocal camera that produces clear images at different depths in an image. The objective of this study was to test the interest of combining plenoptic images and NIRS data to characterize different descriptors of two Mediterranean legumes mixtures. On these mixtures, we measured biomass, species biomass, and functional trait diversity. NIRS and plenoptic images were acquired just before the field measurements. The plenoptic images were analyzed using Trainable Weka Segmentation ImageJ to evaluate the percentage of each species in the image. We calculated the average and standard deviation of the different colors (red, green, blue reflectance) in the image. We assessed the percentage of explanation of outputs of the images and NIRS analyses using variance partition and partial least squares. The biomass Trifolium michelianum and Vicia sativa were predicted with more than 50% variability explained. For the other descriptors, the variability explained was lower but nevertheless significant. The percentage variance explained was nevertheless quite low, and further work is required to produce a useable tool, but this work already demonstrates the interest in combining image analysis and NIRS.

Saved in:
Bibliographic Details
Main Authors: Taugourdeau, Simon, Dionisi, Mathilde, Lascoste, Mylène, Lesnoff, Matthieu, Capron, Jean-Marie, Borne, Frédéric, Borianne, Philippe, Julien, Lionel
Format: article biblioteca
Language:eng
Subjects:biomasse, Vicia sativa, couverture végétale, mesure (activité), herbage, mauvaise herbe, http://aims.fao.org/aos/agrovoc/c_926, http://aims.fao.org/aos/agrovoc/c_8222, http://aims.fao.org/aos/agrovoc/c_25409, http://aims.fao.org/aos/agrovoc/c_4668, http://aims.fao.org/aos/agrovoc/c_3366, http://aims.fao.org/aos/agrovoc/c_8347, http://aims.fao.org/aos/agrovoc/c_3081,
Online Access:http://agritrop.cirad.fr/600980/
http://agritrop.cirad.fr/600980/1/agriculture-12-00704.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id dig-cirad-fr-600980
record_format koha
spelling dig-cirad-fr-6009802024-01-29T19:05:57Z http://agritrop.cirad.fr/600980/ http://agritrop.cirad.fr/600980/ A first attempt to combine NIRS and plenoptic cameras for the assessment of grasslands functional diversity and species composition. Taugourdeau Simon, Dionisi Mathilde, Lascoste Mylène, Lesnoff Matthieu, Capron Jean-Marie, Borne Frédéric, Borianne Philippe, Julien Lionel. 2022. Agriculture (Basel), 12 (5):704, 16 p.https://doi.org/10.3390/agriculture12050704 <https://doi.org/10.3390/agriculture12050704> A first attempt to combine NIRS and plenoptic cameras for the assessment of grasslands functional diversity and species composition Taugourdeau, Simon Dionisi, Mathilde Lascoste, Mylène Lesnoff, Matthieu Capron, Jean-Marie Borne, Frédéric Borianne, Philippe Julien, Lionel eng 2022 Agriculture (Basel) biomasse Vicia sativa couverture végétale mesure (activité) herbage mauvaise herbe http://aims.fao.org/aos/agrovoc/c_926 http://aims.fao.org/aos/agrovoc/c_8222 http://aims.fao.org/aos/agrovoc/c_25409 http://aims.fao.org/aos/agrovoc/c_4668 http://aims.fao.org/aos/agrovoc/c_3366 http://aims.fao.org/aos/agrovoc/c_8347 France http://aims.fao.org/aos/agrovoc/c_3081 Grassland represents more than half of the agricultural land. Numerous metrics (biomass, functional trait, species composition) can be used to describe grassland vegetation and its multiple functions. The measures of these metrics are generally destructive and laborious. Indirect measurements using optical tools are a possible alternative. Some tools have high spatial resolutions (digital camera), and others have high spectral resolutions (Near Infrared Spectrometry NIRS). A plenoptic camera is a multifocal camera that produces clear images at different depths in an image. The objective of this study was to test the interest of combining plenoptic images and NIRS data to characterize different descriptors of two Mediterranean legumes mixtures. On these mixtures, we measured biomass, species biomass, and functional trait diversity. NIRS and plenoptic images were acquired just before the field measurements. The plenoptic images were analyzed using Trainable Weka Segmentation ImageJ to evaluate the percentage of each species in the image. We calculated the average and standard deviation of the different colors (red, green, blue reflectance) in the image. We assessed the percentage of explanation of outputs of the images and NIRS analyses using variance partition and partial least squares. The biomass Trifolium michelianum and Vicia sativa were predicted with more than 50% variability explained. For the other descriptors, the variability explained was lower but nevertheless significant. The percentage variance explained was nevertheless quite low, and further work is required to produce a useable tool, but this work already demonstrates the interest in combining image analysis and NIRS. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/600980/1/agriculture-12-00704.pdf text cc_by info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ https://doi.org/10.3390/agriculture12050704 10.3390/agriculture12050704 info:eu-repo/semantics/altIdentifier/doi/10.3390/agriculture12050704 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.3390/agriculture12050704
institution CIRAD FR
collection DSpace
country Francia
countrycode FR
component Bibliográfico
access En linea
databasecode dig-cirad-fr
tag biblioteca
region Europa del Oeste
libraryname Biblioteca del CIRAD Francia
language eng
topic biomasse
Vicia sativa
couverture végétale
mesure (activité)
herbage
mauvaise herbe
http://aims.fao.org/aos/agrovoc/c_926
http://aims.fao.org/aos/agrovoc/c_8222
http://aims.fao.org/aos/agrovoc/c_25409
http://aims.fao.org/aos/agrovoc/c_4668
http://aims.fao.org/aos/agrovoc/c_3366
http://aims.fao.org/aos/agrovoc/c_8347
http://aims.fao.org/aos/agrovoc/c_3081
biomasse
Vicia sativa
couverture végétale
mesure (activité)
herbage
mauvaise herbe
http://aims.fao.org/aos/agrovoc/c_926
http://aims.fao.org/aos/agrovoc/c_8222
http://aims.fao.org/aos/agrovoc/c_25409
http://aims.fao.org/aos/agrovoc/c_4668
http://aims.fao.org/aos/agrovoc/c_3366
http://aims.fao.org/aos/agrovoc/c_8347
http://aims.fao.org/aos/agrovoc/c_3081
spellingShingle biomasse
Vicia sativa
couverture végétale
mesure (activité)
herbage
mauvaise herbe
http://aims.fao.org/aos/agrovoc/c_926
http://aims.fao.org/aos/agrovoc/c_8222
http://aims.fao.org/aos/agrovoc/c_25409
http://aims.fao.org/aos/agrovoc/c_4668
http://aims.fao.org/aos/agrovoc/c_3366
http://aims.fao.org/aos/agrovoc/c_8347
http://aims.fao.org/aos/agrovoc/c_3081
biomasse
Vicia sativa
couverture végétale
mesure (activité)
herbage
mauvaise herbe
http://aims.fao.org/aos/agrovoc/c_926
http://aims.fao.org/aos/agrovoc/c_8222
http://aims.fao.org/aos/agrovoc/c_25409
http://aims.fao.org/aos/agrovoc/c_4668
http://aims.fao.org/aos/agrovoc/c_3366
http://aims.fao.org/aos/agrovoc/c_8347
http://aims.fao.org/aos/agrovoc/c_3081
Taugourdeau, Simon
Dionisi, Mathilde
Lascoste, Mylène
Lesnoff, Matthieu
Capron, Jean-Marie
Borne, Frédéric
Borianne, Philippe
Julien, Lionel
A first attempt to combine NIRS and plenoptic cameras for the assessment of grasslands functional diversity and species composition
description Grassland represents more than half of the agricultural land. Numerous metrics (biomass, functional trait, species composition) can be used to describe grassland vegetation and its multiple functions. The measures of these metrics are generally destructive and laborious. Indirect measurements using optical tools are a possible alternative. Some tools have high spatial resolutions (digital camera), and others have high spectral resolutions (Near Infrared Spectrometry NIRS). A plenoptic camera is a multifocal camera that produces clear images at different depths in an image. The objective of this study was to test the interest of combining plenoptic images and NIRS data to characterize different descriptors of two Mediterranean legumes mixtures. On these mixtures, we measured biomass, species biomass, and functional trait diversity. NIRS and plenoptic images were acquired just before the field measurements. The plenoptic images were analyzed using Trainable Weka Segmentation ImageJ to evaluate the percentage of each species in the image. We calculated the average and standard deviation of the different colors (red, green, blue reflectance) in the image. We assessed the percentage of explanation of outputs of the images and NIRS analyses using variance partition and partial least squares. The biomass Trifolium michelianum and Vicia sativa were predicted with more than 50% variability explained. For the other descriptors, the variability explained was lower but nevertheless significant. The percentage variance explained was nevertheless quite low, and further work is required to produce a useable tool, but this work already demonstrates the interest in combining image analysis and NIRS.
format article
topic_facet biomasse
Vicia sativa
couverture végétale
mesure (activité)
herbage
mauvaise herbe
http://aims.fao.org/aos/agrovoc/c_926
http://aims.fao.org/aos/agrovoc/c_8222
http://aims.fao.org/aos/agrovoc/c_25409
http://aims.fao.org/aos/agrovoc/c_4668
http://aims.fao.org/aos/agrovoc/c_3366
http://aims.fao.org/aos/agrovoc/c_8347
http://aims.fao.org/aos/agrovoc/c_3081
author Taugourdeau, Simon
Dionisi, Mathilde
Lascoste, Mylène
Lesnoff, Matthieu
Capron, Jean-Marie
Borne, Frédéric
Borianne, Philippe
Julien, Lionel
author_facet Taugourdeau, Simon
Dionisi, Mathilde
Lascoste, Mylène
Lesnoff, Matthieu
Capron, Jean-Marie
Borne, Frédéric
Borianne, Philippe
Julien, Lionel
author_sort Taugourdeau, Simon
title A first attempt to combine NIRS and plenoptic cameras for the assessment of grasslands functional diversity and species composition
title_short A first attempt to combine NIRS and plenoptic cameras for the assessment of grasslands functional diversity and species composition
title_full A first attempt to combine NIRS and plenoptic cameras for the assessment of grasslands functional diversity and species composition
title_fullStr A first attempt to combine NIRS and plenoptic cameras for the assessment of grasslands functional diversity and species composition
title_full_unstemmed A first attempt to combine NIRS and plenoptic cameras for the assessment of grasslands functional diversity and species composition
title_sort first attempt to combine nirs and plenoptic cameras for the assessment of grasslands functional diversity and species composition
url http://agritrop.cirad.fr/600980/
http://agritrop.cirad.fr/600980/1/agriculture-12-00704.pdf
work_keys_str_mv AT taugourdeausimon afirstattempttocombinenirsandplenopticcamerasfortheassessmentofgrasslandsfunctionaldiversityandspeciescomposition
AT dionisimathilde afirstattempttocombinenirsandplenopticcamerasfortheassessmentofgrasslandsfunctionaldiversityandspeciescomposition
AT lascostemylene afirstattempttocombinenirsandplenopticcamerasfortheassessmentofgrasslandsfunctionaldiversityandspeciescomposition
AT lesnoffmatthieu afirstattempttocombinenirsandplenopticcamerasfortheassessmentofgrasslandsfunctionaldiversityandspeciescomposition
AT capronjeanmarie afirstattempttocombinenirsandplenopticcamerasfortheassessmentofgrasslandsfunctionaldiversityandspeciescomposition
AT bornefrederic afirstattempttocombinenirsandplenopticcamerasfortheassessmentofgrasslandsfunctionaldiversityandspeciescomposition
AT boriannephilippe afirstattempttocombinenirsandplenopticcamerasfortheassessmentofgrasslandsfunctionaldiversityandspeciescomposition
AT julienlionel afirstattempttocombinenirsandplenopticcamerasfortheassessmentofgrasslandsfunctionaldiversityandspeciescomposition
AT taugourdeausimon firstattempttocombinenirsandplenopticcamerasfortheassessmentofgrasslandsfunctionaldiversityandspeciescomposition
AT dionisimathilde firstattempttocombinenirsandplenopticcamerasfortheassessmentofgrasslandsfunctionaldiversityandspeciescomposition
AT lascostemylene firstattempttocombinenirsandplenopticcamerasfortheassessmentofgrasslandsfunctionaldiversityandspeciescomposition
AT lesnoffmatthieu firstattempttocombinenirsandplenopticcamerasfortheassessmentofgrasslandsfunctionaldiversityandspeciescomposition
AT capronjeanmarie firstattempttocombinenirsandplenopticcamerasfortheassessmentofgrasslandsfunctionaldiversityandspeciescomposition
AT bornefrederic firstattempttocombinenirsandplenopticcamerasfortheassessmentofgrasslandsfunctionaldiversityandspeciescomposition
AT boriannephilippe firstattempttocombinenirsandplenopticcamerasfortheassessmentofgrasslandsfunctionaldiversityandspeciescomposition
AT julienlionel firstattempttocombinenirsandplenopticcamerasfortheassessmentofgrasslandsfunctionaldiversityandspeciescomposition
_version_ 1792500350503092224