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41 to 50 of 116 Results
Jun 10, 2020 - Frimouss Project
Roch, Léa; Prigent, Sylvain; Klose, Holger; Cakpo, Coffi-Belmys; Beauvoit, Bertrand; Deborde, Catherine; Fouillen, Laetitia; van Delft, Pierre; Jacob, Daniel; Usadel, Björn; Dai, Zhanwu; Génard, Michel; Vercambre, Gilles; Colombié, Sophie; Moing, Annick; Gibon, Yves, 2020, "Frimouss project", https://doi.org/10.15454/1KQBTM, Portail Data INRAE, V1, UNF:6:0J0yUOtSfMB1bt+qlqbtTg== [fileUNF]
Fruit features : Fruit growth has been measured from anthesis to harvest on plants with regular crop load. The anthesis date have been observed in order to describe the data collected according to days and degree-days from anthesis. Fruit growth has been monitored using non-destr...
Frimouss Project(INRAE, Institut National de la Recherche pour l’Agriculture, l’Alimentation et l’Environement)
Jun 10, 2020PMB Metabolomics
Frimouss Integrative fruit modeling for a unified selection system - ANR Project https://anr.fr/Projet-ANR-15-CE20-0009
Jun 4, 2020 - GAFL
Causse, Mathilde, 2020, "Dataset for QTL detection in a Tomato MAGIC population analysed in a multi-environment experiment", https://doi.org/10.15454/UVZTAV, Portail Data INRAE, V1, UNF:6:nkco+yhSh6cfkeykQFbMGw== [fileUNF]
Description of the data The data described here were produced from the ANR projects ADAPTOM (ANR-13-ADAP-0013) and TomEpiSet (ANR-16-CE20-0014). An 8-way tomato MAGIC population was phenotyped over 12 environments including three geographical location (France, Israel and Morocco)...
May 14, 2020 - Experimental - Observation - Simulation Dataverse
Laurent, Benoit, 2020, "Microhaplotype genotyping-by-sequencing of 98 highly polymorphic markers in three chestnut tree species", https://doi.org/10.15454/PNBEAM, Portail Data INRAE, V5, UNF:6:vfR+Xz1fRgxgxhqS02yR2g== [fileUNF]
Chestnut species have large ecological, cultural and economic importance. Developing genetic markers for these species is of interest for conservation, breeding or evolutionary studies. We designed 192 primer pairs targeting microsatellites detected in the Castanea mollissima ref...
May 13, 2020 - Experimental - Observation - Simulation Dataverse
Rincent, Renaud, 2020, "Robert et al. Combining crop growth modelling with trait-assisted prediction improved the prediction of genotype by environment interactions", https://doi.org/10.15454/TKMGCQ, Portail Data INRAE, V2, UNF:6:TSvPO2jAaj2OqvykPlBLqA== [fileUNF]
Genotyping data, Phenotyping data (Heading date and Grain Yield) used in the study of Robert et al. (220 wheat varieties and 16 environments as well as 139 environmental covariates describing each environment).
May 12, 2020 - Experimental - Observation - Simulation Dataverse
Gay, Laurene, 2020, "Medicago truncatula SNP temporal data from: "Power and limits of selection genome scans on temporal data from a selfing population"", https://doi.org/10.15454/TYQDGP, Portail Data INRAE, V1, UNF:6:nt7te5W6j1eifPoBiuCDgQ== [fileUNF]
SNP data from a population located in Cape Corsica (42°58.406’ North, 9°22,015’ East, 362 m.a.s.l.), collected in 1987 (64 plants) and 2009 (96 plants).Genotyping was performed using two SNP chips specifically developed for M. truncatula (Loridon et al. 2013 Molecular Ecology Res...
Apr 6, 2020 - Experimental - Observation - Simulation Dataverse
Boureau, Tristan, 2020, "PHENOTIC Platform", https://doi.org/10.15454/U2BWFJ, Portail Data INRAE, V1
The PHENOTIC platform gathers services for plant production and high-throughput phenotyping of plant material. The PHENOTIC platform develops approaches for phenotyping plants at two complementary scales: seeds and aerial parts of plants. Therefore, the purpose of the PHENOTIC pl...
Apr 1, 2020
Beral, Aurore, 2020, "Bread wheat phenotyping data UMR 1095 GDEC", https://doi.org/10.15454/5MR0EI, Portail Data INRAE, V1
This dataset supports the study of Beral et al. (2020) including phenotyping data for two experiments conducted at INRA, Clermont-Ferrand in 2015/2016 and 2016/2017 using the Pheno3C high-throughput, field-phenotyping platform. Two genetic panels of winter wheat genotypes were in...
Feb 28, 2020 - URGI Plant and Fungi Dataverse
Papoutsoglou, Evangelia A.; Faria, Daniel; Arend, Daniel; Arnaud, Elizabeth; Athanasiadis, Ioannis N.; Chaves, Inês; Coppens, Frederik; Cornut, Guillaume; Costa, Bruno V.; Ćwiek-Kupczyńska, Hanna; Droesbeke, Bert; Finkers, Richard; Gruden, Kristina; Junker, Astrid; King, Graham J.; Krajewski, Paweł; Lange, Matthias; Laporte, Marie-Angélique; Michotey, Célia; Oppermann, Markus; Ostler, Richard; Poorter, Hendrik; Ramı́rez-Gonzalez, Ricardo; Ramšak, Živa; Reif, Jochen C.; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Scholz, Uwe; Tardieu, François; Uauy, Cristobal; Usadel, Björn; Visser, Richard G.F.; Weise, Stephan; Kersey, Paul J.; Miguel, Célia M.; Adam-Blondon, Anne-Françoise; Pommier, Cyril, 2020, "Enabling reusability of plant phenomic datasets with MIAPPE 1.1 - Supplementary dataset", https://doi.org/10.15454/1YXVZV, Portail Data INRAE, V1
Exemplar dataset demonstrating the use of MIAPPE as described in "Enabling reusability of plant phenomic datasets with MIAPPE 1.1". Enabling data reuse and knowledge discovery is increasingly critical in modern science, and requires an effort towards standardizing data publicatio...
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