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Jan 26, 2021 - Système d'Information
Pichot, Christian; Clastre, Philippe; Fiocca, Amélie; Evtimova, Mariya; Jaillet, Benjamin; Ozcan, Aytac; Benard, Alain; Benedet, Fabrice; Bouvet, Alain; Cailly, Priscilla; Courbet, François; Deleuze, Christine; Ginisty, Christian; Herault, Bruno; Maurice, Damien; Meredieu, Celine; Michotey, Celia; Mirlyaz, Wulfran; Orazio, Christophe; Paillassa, Eric; Perrier, Celine; Plinio Sist; Pozzi, Tiffani; Renaud, Jean-Pierre; Saint-Andre, Laurent; Said, Sonia, 2021, "Documentation Système d'Information IN-SYLVA France", https://doi.org/10.15454/ELXRGY, Portail Data INRAE, V5
Ensemble des documents élaborés dans le cadre du développement du Système d'Information (SI) IN-SYLVA France. Cette publication comporte plusieurs document élaboré au cours du projet. (i) in-sylva_cahier_des_charges: cahier des charges pour le développement du SI (format pdf). (i...
application/pdf - 712.8 KB - MD5: 2fd80316bc7aa73a1657d32b61db10cc
Standard de métadonnées pour le système d'information IN-SYLVA
EABX data(INRAE - French National Research Institute for Agriculture, Food and Environment)
Jan 25, 2021eabx
application/rdf+xml - 1.4 MB - MD5: 79f3d950a6db169905d554c1657ee459
Thésaurus: référentiels internes pour le système d'Information IN-SYLVA
Jan 22, 2021 - Chemometrics-Chemhouse
Mallet, Alexandre; Pérémé, Margaud; Charnier, Cyrille; Roger, Jean-Michel; Steyer, Jean-Philippe; Latrille, Eric; Bendoula, Ryad, 2021, "On-site substrate characterization in the anaerobic digestion context: a dataset of near infrared spectra acquired with four different optical systems on freeze-dried and ground organic wastes", https://doi.org/10.15454/SQQTUU, Portail Data INRAE, V1
The near infrared spectra of thirty-three freeze-dried and ground organic waste samples of various biochemical composition were collected on four optical systems, including a laboratory spectrometer (Buchi FT-NIR NirFlex N-500), a transportable spectrometer (ARCoptix FT-NIR Rocke...
text/x-python - 6.3 KB - MD5: cf9e5db2f45fe9b354906026a4af2d7f
A python script to read the dataset elements, and show the training (via cross-validation) of a PLS-R to predict the biochemical characteristics.
text/tsv - 1.6 MB - MD5: 71a80d89981e88c7df9176b4605882eb
Reflectance spectra (in nm) from the polarized system PoLis : total back-scattered signal (Rbs)
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