A multi-site experiment in a network of European fields for assessing the maize yield response to environmental scenarios

  • Emilie Millet (Creator)
  • Cyril Pommier (Creator)
  • Melanie Buy (Creator)
  • A. Nagel (Creator)
  • Willem Kruijer (Creator)
  • Therese Welz-Bolduan (Creator)
  • Jeremy Lopez (Creator)
  • Cecile Richard (Creator)
  • Ferenc Racz (Creator)
  • Franco Tanzi (Creator)
  • Tamas Spitkot (Creator)
  • Maria-Angela Canè (Creator)
  • Sandra Negro (Creator)
  • Aude Coupel-Ledru (Creator)
  • Stéphane Nicolas (Creator)
  • Carine Palaffre (Creator)
  • Cyril Bauland (Creator)
  • Sebastien Praud (Creator)
  • Nicolas Ranc (Creator)
  • Thomas Presterl (Creator)
  • Zoltan Bedo (Creator)
  • Roberto Tuberosa (Creator)
  • Björn Usadel (Creator)
  • Alain Charcosset (Creator)
  • Fred van Eeuwijk (Creator)
  • Xavier Draye (Creator)
  • François Tardieu (Creator)
  • Claude Welcker (Creator)

Dataset

Description

This dataset comes from the European Union project DROPS (DROught-tolerant yielding PlantS). A panel of 256 maize hybrids was grown with two water regimes (irrigated or rainfed), in seven fields in 2012 and 2013, respectively, spread along a climatic transect from western to eastern Europe, plus one site in Chile in 2013. This resulted in 29 experiments defined as the combination of one year, one site and one water regime, with two and three repetitions for rainfed and irrigated treatments, respectively. A detailed environmental characterisation was carried out, with hourly records of micrometeorological data and soil water status, and associated with precise measurement of phenology. Grain yield and its components were measured at the end of the experiment. The main purpose of this dataset consists in using the environmental characterisation to quantify the genetic variability of maize grain yield in response to the environmental drivers for genotype-by-environment interaction. For instance, allelic effects at QTLs identified over the field network are consistent within a scenario but largely differ between scenarios.
Date made available27 Mar 2019
PublisherINRA
Temporal coverage2011 - 2013

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