Skip to main content
Featured Dataverses

In order to use this feature you must have at least one published dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Find Advanced Search

1 to 10 of 88 Results
Nov 26, 2020 - GisSol Dataverse
Saby, Nicolas P.A.; Lemercier, Blandine; Arrouays, Dominique; Walter, Christian; Gouny, Laetitia; Swidersky, Chloé; Toutain, Benoît; Bispo, Antonio, 2019, "Statistiques spatio-temporelles sur les propriétés agronomiques des sols agricoles en France issues de la Base de Données d'Analyses de Terre (BDAT)", https://doi.org/10.15454/SVDTOU, Portail Data INRAE, V3, UNF:6:SIZoeWPXnrTjOmmku4l4Jg== [fileUNF]
In France, farmers commission about 250,000 soil-testing analyses per year to assist them managing soil fertility. The number and diversity of origin of the samples make these analyses an interesting and original information source regarding cultivated topsoil variability. Moreov...
Nov 25, 2020 - AMAP ECOPICS
Weemstra, Monique, 2020, "Species plots: Soil and Climate data", https://doi.org/10.15454/JKZAPX, Portail Data INRAE, V1, UNF:6:UqItE8dlQm02DOllAiyZxg== [fileUNF]
The soil and climate data stored here are collected at 5 replicate plots (but pooled per altitude) every 100 m increase in altitude between 1400 and 2400 m a.s.l. at the Belledonne Massif, FR.
Nov 3, 2020 - AMAP ECOPICS
Merino-Martin, Luis, 2020, "Monolith Aggregate Stability", https://doi.org/10.15454/UOU4TO, Portail Data INRAE, V1
Soil aggregate stability on samples from topsoil and subsoil at six altitudes along an elevational gradient at the Massif de Belledonne, France
Nov 3, 2020 - AMAP ECOPICS
Beatriz Eugenia Marín Castro, 2020, "Description of Soil Profiles", https://doi.org/10.15454/ZTCHEG, Portail Data INRAE, V1, UNF:6:j1cpdW9qmiGYja5TGdUpog== [fileUNF]
Evaluation of soil types at Massif de Belledonne, France
Nov 3, 2020 - AMAP ECOPICS
Stokes, Alexia, 2020, "Stable State Infiltration", https://doi.org/10.15454/PWWMYV, Portail Data INRAE, V1, UNF:6:TL8619x+qZv034gHydyQRw== [fileUNF]
Water infiltration into soil along an elevational gradient at Massif de Belledonne, France
Oct 26, 2020 - LandmarkH2020 Dataverse
Saby, Nicolas P.A.; Chenu, Jean-Philippe; Szergi, Tamas; Csorba, Adam; Bertuzzi, Patrick; Toutain, Benoît; Picaud, Calypso; Gay, Laura; Creamer, R., 2020, "French RMQS soil profile and monitoring dataset with related management practices data", https://doi.org/10.15454/AIQ9WS, Portail Data INRAE, V1, UNF:6:HfeFeHIMAWpeh4m/FkViWw== [fileUNF]
This dataset corresponds to a datamart produced by the WP2 team of the Landmark H2020 project. 2 tables provided by France are available: One table of fact-gathering the results of the chemical and physical analyses of the soil profiles and monitoring. One table of fact-gathering...
AMAP ECOPICS(INRA - Institut National de la Recherche Agronomique)
Oct 8, 2020AMAP
Oct 6, 2020 - Vocabulaires Ouverts
Denis Baize, 2020, "Petit Lexique de Pédologie", https://doi.org/10.15454/5FIPVE, Portail Data INRAE, V1
Ce lexique présente plus de 1.000 concepts utiles du vocabulaire francophone et des systèmes typologiques contemporains.
Oct 5, 2020 - GisSol Dataverse
Saby, Nicolas; Bertouy, Benoit; Boulonne, Line; Bispo, Antonio; Ratié, Céline; Jolivet, Claudy, 2019, "Statistiques sommaires issues du RMQS sur les données agronomiques et en éléments traces des sols français de 0 à 50 cm", https://doi.org/10.15454/BNCXYB, Portail Data INRAE, V5
Ce jeu de données fournit des statistiques sommaires sur les concentrations en éléments traces et propriétés pédologiques issues des résulats d'analyses du RMQS pour deux profondeurs. Le réseau RMQS repose sur le suivi de 2200 sites répartis uniformément sur le territoire françai...
Jul 29, 2020 - LandmarkH2020 Dataverse
Vrebos Dirk; Schulte, Rogier; Jones, Arwyn; Staes, Jan; O’Sullivan, Lilian; Lugato, Emanuele; Schröder, Jaap; Meire, Patrick, 2020, "Bayesian networks to evaluate soil functions of agricultural land in Europe", https://doi.org/10.15454/YA4OSH, Portail Data INRAE, V1
This dataset is part of both deliverable 4.2 and 4.3 and was produced by the WP4 team of the Landmark H2020 project. It contains the Bayesian networks for the following crops: Barley Silage maize Grain maize Intensive grasslands - hay Intensive grasslands - grazed Extensive grass...
Add Data

Sign up or log in to create a dataverse or add a dataset.

Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.

Contact Portail Data INRAE Support

Portail Data INRAE Support

Please fill this out to prove you are not a robot.

+ =