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GRK 1070 SP 2.2: QTL analysis and optimization of breeding schemes for improved nitrogen-use efficiency of maize and wheat for sustainable cropping systems in the North China Plain

Project

Environment and ressource management

This project contributes to the research aim ' Environment and ressource management'. Which funding institutions are active for this aim? What are the sub-aims? Take a look:
Environment and ressource management


Project code: keine Angaben
Contract period: 01.01.2004 - 01.01.2013
Purpose of research: Basic research

In China, agriculture needs to be intensified by increasing the productivity per unit land. However, the possibility to improve yield by further increasing the amounts of input is very limited due to already very high input amounts of fertilizers and irrigation water in the present cropping system. Hence, the development and characterization of improved varieties, especially with regard to traits of utmost importance for sustainable resource use, such as nitrogen- (NUE) and water-use efficiency (WUE), is crucial for a sustainable agriculture in the North China Plain. The decision about the requirement of one common or two separate breeding programs for developing varieties adapted to low and high N fertilization strongly depends on an appropriate estimation of the correlation between yield at different fertilization levels. Therefore, maize and wheat varieties are evaluated in multiple locations in the North China Plain. Adopting novel breeding approaches based on doubled haploids (DH) can speed up the process of developing new varieties substantially and rapidly provides suitable cultivars for new cropping systems. Therefore, optimum breeding strategies for maize breeding are modeled and simulated to optimize alternative breeding schemes with respect to the optimum allocation of test resources using different optimization criteria. Modeling of production systems and material flows is a powerful tool to increase sustainable resource use by identifying cropping systems, which combine reduced inputs with high yields. However, an appropriate model requires knowledge about the genetics of crop growth and yield and its interaction with environmental factors. Therefore, maize and wheat populations developed by the Chinese partners in the first project phase are phenotyped in multi-location field trials and genotyped with molecular markers to map quantitative trait loci (QTL) for NUE.

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