8th International Triticeae Symposium

Dag Endresen from GBIF Norway was invited to present a key note on using GBIF-mediated data for predictive characterization at the 8th International Triticeae Symposium 2017 (8ITS) in Wernigerode Germany.


8th International Triticeae Symposium 2017

The International Triticeae Symposium is an interdisciplinary conference organized by the International Triticeae Consortium. The 8th International Triticeae Symposium 2017 (8ITS) was organized by the Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung (IPK Gatersleben) in Wernigerode Germany from 11th to 16th June 2017.

"Triticeae is the economically most important tribe in the grass family (Poaceae). It contains the major cereal crops and forage grasses such as wheat, barley and rye. It also includes important fodder grasses in genera such as Agropyron, Elymus, Leymus, and Psathyrostachys. Because of their economic importance, plants in Triticeae are commonly used for applied and theoretical research and compared with other tribes in Poaceae" (cited from the conference home page).

Predictive characterization and Focused Identification of Germplasm Strategy (FIGS) is a machine learning approach for selecting plant material for a target phenotypic trait for the purpose of crop improvement. A predictive machine leaning model is calibrated using training data for living specimens (of traditional cultivars of crop wild relatives) together with climate and other environmental data from their original locations of origin. The Global Biodiversity Information Facility (GBIF) provide open and free access to the relevant occurrence data (including Triticeae). And work is in progress to provide also access to the respective crop trait evaluation data based on recent extensions to Darwin Core and new application data profiles to the GBIF Integrated data Publishing Toolkit (IPT).



GBIF (2017) Triticeae occurrences published in GBIF. GBIF.org accessed 9 June 2017. doi:10.15468/dl.3z2bmo

Endresen, DTF (2017) Predictive characterization of wheat and barley landraces - using GBIF-mediated data. 8th International Triticeae Symposium 2017, 2017-06-12 to 2017-06-16 at Wernigerode, Germany, Volume: 8. [Slides: PPTX, PDF]

Thormann, I; Parra-Quijano, M; Endresen, DTF; Rubio-Teso, ML; Iriondo, JM; & Maxted, N (2014). Predictive characterization of crop wild relatives and landraces: Technical guidelines, version 1. Bioversity International. ISBN 978-92-9255-004-2. 40 pp. doi:10.13140/RG.2.1.1359.0487

Tags: GBIF, Agrobiodiversity, Data modelling, research data By Dag Endresen
Published June 12, 2017 9:56 PM - Last modified June 13, 2017 11:11 PM