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Focused identification of germplasm strategy (FIGS) detects wheat stem rust resistance linked to environmental variables

December 17, 2011

Genetic Resources and Crop EvolutionAbdallah Bari, Kenneth Street, Michael Mackay, Dag Terje Filip Endresen, Eddy De Pauw and Ahmed Amri (2012). Focused identification of germplasm strategy (FIGS) detects wheat stem rust resistance linked to environmental variables. Genetic Resources and Crop Evolution (Published Online 3 December 2011), pp. 1-17. doi:10.1007/s10722-011-9775-5

This new FIGS study follows the same principles and uses the same stem rust trait dataset from USDA GRIN as our previous study published in Crop Science (Endresen et al., 2011; doi: 10.2135/cropsci2010.12.0717). The predictive computer models are however calibrated using other methods such as Artificial Neural Networks (ANN), Support Vector Machines (SVM), Random Forests (RF), Principal Component Logistic Regression (PCLR) and Generalized Partial Least Squares (GPLS). My colleague Abdallah Bari from ICARDA based in Aleppo, Syria was conducting the data analysis. In particular the non-linear methods ANN and SVM seems suitable for this dataset. The results from this new study provides support for the results from our previous study where the data analysis was conducted by me.

See also:
http://icardanews.wordpress.com/2011/10/31/research-team-for-figs-opens-global-consultation/
http://icardablog.wordpress.com/2011/10/20/figs-a-new-targeted-approach-to-mining-gene-banks/
http://www.mendeley.com/groups/502321/trait-mining-figs/papers/
http://www.slideshare.net/group/trait-mining/slideshows
http://code.google.com/p/trait-mining/
http://www.rustopedia.org/traction?type=single&proj=references&rec=1627

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