Predictive characterization of crop wild relatives and landraces: technical guidelines version 1 - Thormann, I.; Endresen, D.T.F.; Rubio-Teso, M.L.; Iriondo, M.J.; Maxted, Nigel; Parra-Quijano, M. (Bioversity International, 2014)
Predictive characterization methods use ecogeographical and climatic data derived from the specific location of a collecting or observation site, to predict characteristics of accessions and populations that can inform conservation and use options. The predictive characterization methods presented in these technical guidelines for crop wild relatives (CWR) and landraces (LR) aim to enhance the use of CWR and LR through identification of sets of accessions or occurrences that have a higher likelihood of harbouring genetic diversity for specific adaptive traits than a set selected at random. The methods presented are the ecogeographical filtering and the calibration method. These are two of the various methods that implement the Focused Identification of Germplasm Strategy (FIGS). The guidelines were developed within the framework of the EU funded project PGR Secure ‘Novel characterization of crop wild relative and landrace resources as a basis for improved crop breeding’.