2 resultados para adaptive functioning

em eResearch Archive - Queensland Department of Agriculture


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The objectives of this project over a 3 years study period are: 1) validation and on-farm adoption of improved root growth and functioning for managing cotton production under limited water and nitrogen nutrition; and 2) Delivering improved understanding of enhancing root growth and functioning to about 50% cotton growers in the regions leading towards a better adaptation to future climate driven challenges, particularly limited water availability in Queensland and New South Wales. The research is expected to be supported through cash and/or in-kind contributions by CRDC and Agri-Science Queensland (DEEDI).

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Progress in crop improvement is limited by the ability to identify favourable combinations of genotypes (G) and management practices (M) in relevant target environments (E) given the resources available to search among the myriad of possible combinations. To underpin yield advance we require prediction of phenotype based on genotype. In plant breeding, traditional phenotypic selection methods have involved measuring phenotypic performance of large segregating populations in multi-environment trials and applying rigorous statistical procedures based on quantitative genetic theory to identify superior individuals. Recent developments in the ability to inexpensively and densely map/sequence genomes have facilitated a shift from the level of the individual (genotype) to the level of the genomic region. Molecular breeding strategies using genome wide prediction and genomic selection approaches have developed rapidly. However, their applicability to complex traits remains constrained by gene-gene and gene-environment interactions, which restrict the predictive power of associations of genomic regions with phenotypic responses. Here it is argued that crop ecophysiology and functional whole plant modelling can provide an effective link between molecular and organism scales and enhance molecular breeding by adding value to genetic prediction approaches. A physiological framework that facilitates dissection and modelling of complex traits can inform phenotyping methods for marker/gene detection and underpin prediction of likely phenotypic consequences of trait and genetic variation in target environments. This approach holds considerable promise for more effectively linking genotype to phenotype for complex adaptive traits. Specific examples focused on drought adaptation are presented to highlight the concepts.