Botany Seminar on trait data mining using FIGS, Copenhagen (25 Feb 2011)


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Predictive link between crop traits and eco-climatic description of the original collecting site. Presented at the Botany Seminar series ( on 25 February 2011 at the Department of Agriculture and Ecology, Faculty of Life Sciences, Copenhagen University, Denmark. URL:

Endresen, D.T.F. (2010). Predictive association between trait data and ecogeographic data for Nordic barley landraces. Crop Sci. 50(6):2418-2430. doi: 10.2135/cropsci2010.03.0174

Endresen, D.T.F., K. Street, M. Mackay, A. Bari, and E. De Pauw (2011). Predictive Association between Biotic Stress Traits and Eco-Geographic Data for Wheat and Barley Landraces. Crop Science 51 (5): 2036-2055. doi: 10.2135/cropsci2010.12.0717

Endresen, D.T.F., K. Street, M. Mackay, A. Bari, A. Amri, E. De Pauw, K. Nazari, and A. Yahyaoui (2012). Sources of Resistance to Stem Rust (Ug99) in Bread Wheat and Durum Wheat Identified Using Focused Identification of Germplasm Strategy (FIGS). Crop Science [Online first] doi: 10.2135/cropsci2011.08.0427; Published online 8 Dec. 2011.

Endresen, D.T.F. (2011). Utilization of Plant Genetic Resources: A Lifeboat to the Gene Pool [PhD Thesis]. Copenhagen University, Faculty for Life Sciences, Department of Agriculture and Ecology. Available at: (PDF 37 MB). ISBN: 978-91-628-8268-6.

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  • Image: Wheat at Alnarp June 2010 by Dag Endresen,
  • NOTE that the countries are colored by the distribution of accessions:: while the red dots are the georeferenced collecting places.Dynamic maps live to SESTO, created with UMN Mapserver (Dag Endresen, 2009)
  • Statsbygg (2008). Svalbard Global Seed Vault, Longyearbyen, Svalbard, new construction. Ferdigmelding nr 671/2008, Project no 11098. Statsbygg, Oslo, Norway. 28 p. Available at, verified 18 Jan 2011.
  • Integration of GBIF-mediated occurrence data with other applications like the openModeller generates a probability distribution using the Envelope Score Algorithm.
  • GBIF-MAPA Mapping and Analysis Portal Application []The survey gap analysis (SGA) tool helps you design a biodiversity survey that will best complement the existing survey effort by identifying those areas least well surveyed in terms of environmental conditions.Photo:
  • Illustration of trait mining with ecoclimatic GIS layers. GIS layers included in the illustration are from the ICARDA ecoclimatic database, average: annual temperature (front), annual precipitation (middle), and winter precipitation (back) (De Pauw, 2003)
  • Photo: Dag Endresen.Field of sugar beet (Beta vulgaris L.) at Alnarp (June 2005). URL:
  • Modern agriculture uses advanced plant varieties based on the most productive genetics. The original land races and wild forms produce lower yields, but their greater genetic variation contains a higher diversity in e.g. resistance to disease. High-yielding modern crops are therefore vulnerable when a new disease arises.
  • Illustration traditional cattle farming: (USAID, Public Domain)
  • The WorldClim dataset is described in: Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978NOAA GHCN-Monthly version 2: stations, precipitation: 20590;temperature:7280
  • We often divide the data for a simulation model project in three equal parts: one set for initial model calibration or training, one set for further calibration or fine tuning; and one test set for validation on the model.
  • GRIN database (USDA-ARS, National Plant Germplasm System, Germplasm Resources Information Network, online USDA GRIN, trait data online:
  • GRIN database (USDA-ARS, National Plant Germplasm System, Germplasm Resources Information Network, online USDA GRIN, trait data online: Harold Bockelman extracted the trait data (C&E)
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