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Crop Systems Biology
Xinyou Yin (Hrsg.), Paul C. Struik (Hrsg.)
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Springer International Publishing 
Naturwissenschaften, Medizin, Informatik, Technik / Landwirtschaft, Gartenbau
Beschreibung
The sequencing of genomes has been completed for an increasing number of crop species, and researchers have now succeeded in isolating and characterising many important QTLs/genes. High expectations from genomics, however, are waving back toward the recognition that crop physiology is also important for realistic improvement of crop productivity. Complex processes and networks along various hierarchical levels of crop growth and development can be thoroughly understood with the help of their mathematical description – modelling. The further practical application of these understandings also requires quantitative predictions. In order to better support design, engineering and breeding for new crops and cultivars for improving agricultural production under global warming and climate change, there is an increasing call for an interdisciplinary research approach, which combines modern genetics and genomics, traditional physiology and biochemistry, and advanced bioinformatics and modelling. Such an interdisciplinary approach has been practised in various research groups for many years. However, it does not seem to be fully covered in the format of book publications. We want to initiate a book project on crop systems biology - narrowing the gaps between genotypes and phenotypes and the gaps between crop modelling and genetics/genomics, for publication in 2013/2014. The book will be meant for those scientists and graduate students from fundamental plant biology and applied crop science who are interested in bridging the gap between these two fields. We have invited a group of scientists (who have very good track records in publishing excellent papers in this field or in a closely related area) to contribute chapters to this new book, and they have agreed to do so.
Kundenbewertungen
Genetic analysis and genomics, Genotype-phenotype gaps, Quantitative trait loci, Systems Biology, Crop improvement, Crop physiological modelling