Applications of Machine Learning in Breeding for Stress Tolerance in Maize
作者： Leonardo Ornella , Gerardo Cervigni , Elizabeth Tapia
DOI: 10.1007/978-94-007-2220-0_5
关键词:
摘要: Corn is one of the world’s most important cereals and a major source calories for humanity, along with rice wheat. Climate change use marginal land crop production require development genotypes adapted to stressful environments, particularly drought tolerant plants. Among new technologies currently available accelerate releasing there an emerging discipline called Machine Learning (ML). A primary goal ML algorithms automatically learn recognize complex patterns make intelligent decisions based on data. This work reviews several strategic applications in maize breeding. Quantitative trait loci mapping, heterotic group assignment popular genome-wide selection are some key areas addressed by literature. Results encouraging propose as valuable alternative traditional statistical techniques applied maize, even more recently introduced linear mixed models.
springer.com
sci-hub.st 参考文章(115)
Elhan S. Ersoz, Jianming Yu, Edward S. Buckler, Applications of Linkage Disequilibrium and Association Mapping in Maize Springer, Berlin, Heidelberg. pp. 173- 195 ,(2009) , 10.1007/978-3-540-68922-5_13
Sally Jo Cunningham, Machine learning and statistics: a matter of perspective University of Waikato, Department of Computer Science. ,(1995)
Huan Liu, Hiroshi Motoda, None, Computational Methods of Feature Selection Chapman and Hall/CRC. ,(2007) , 10.1201/9781584888796
J. A. Hartigan, A failure of likelihood asymptotics for normal mixtures Proceedings of the Berkeley Conference in Honor of Jerzy Neyman and Jack Kiefer, 1985. ,vol. 2, pp. 807- 810 ,(1985)
Marianne Bänziger, Jose-Luis Araus, Recent Advances in Breeding Maize for Drought and Salinity Stress Tolerance Springer, Dordrecht. pp. 587- 601 ,(2007) , 10.1007/978-1-4020-5578-2_23
M. N. S. Swamy, Ke-Lin Du, Neural networks in a softcomputing framework ,(2006)
Molecular Genetic Approaches to Maize Improvement Springer. ,(2009) , 10.1007/978-3-540-68922-5
Quantitative genetics, genomics and plant breeding Plant Breeding. ,vol. 39, ,(2001) , 10.1079/9780851996011.0000
Arnel R. Hallauer, J. B. Miranda Filho, Quantitative Genetics in Maize Breeding ,(2011)
Advanced Lectures on Machine Learning ML Summer Schools 2003. ,(2004) , 10.1007/B100712