Models for navigating biological complexity in breeding improved crop plants.
about
Adapting wheat in Europe for climate changeUse of crop simulation modelling to aid ideotype design of future cereal cultivarsConnecting Biochemical Photosynthesis Models with Crop Models to Support Crop ImprovementA generic model to simulate air-borne diseases as a function of crop architectureA framework for evolutionary systems biologyGenetic and physiological bases for phenological responses to current and predicted climates.Breeding for the future: what are the potential impacts of future frost and heat events on sowing and flowering time requirements for Australian bread wheat (Triticum aestivium) varieties?Barley: a translational model for adaptation to climate change.A mixed-model quantitative trait loci (QTL) analysis for multiple-environment trial data using environmental covariables for QTL-by-environment interactions, with an example in maizeRoot growth models: towards a new generation of continuous approaches.Interlocking feedback loops govern the dynamic behavior of the floral transition in Arabidopsis.Genetic analysis of vegetative branching in sorghum.Identifying target traits and molecular mechanisms for wheat breeding under a changing climate.Integrating omic approaches for abiotic stress tolerance in soybean.Brief history of agricultural systems modelingTowards a new generation of agricultural system data, models and knowledge products: Design and improvement.Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science.A common genetic determinism for sensitivities to soil water deficit and evaporative demand: meta-analysis of quantitative trait Loci and introgression lines of maize.Any trait or trait-related allele can confer drought tolerance: just design the right drought scenario.A gene regulatory network model for floral transition of the shoot apex in maize and its dynamic modeling.A functional-structural model of rice linking quantitative genetic information with morphological development and physiological processes.Integrating Crop Growth Models with Whole Genome Prediction through Approximate Bayesian Computation.In silico system analysis of physiological traits determining grain yield and protein concentration for wheat as influenced by climate and crop management.Velocity of temperature and flowering time in wheat - assisting breeders to keep pace with climate change.Assessment of the Potential Impacts of Wheat Plant Traits across Environments by Combining Crop Modeling and Global Sensitivity Analysis.Phenotyping for drought tolerance of crops in the genomics era.Multiple abiotic stimuli are integrated in the regulation of rice gene expression under field conditions.Barley genomics: An overview.Plant response to environmental conditions: assessing potential production, water demand, and negative effects of water deficit.When parameters in dynamic models become phenotypes: a case study on flesh pigmentation in the chinook salmon (Oncorhynchus tshawytscha).Using a model-based framework for analysing genetic diversity during germination and heterotrophic growth of Medicago truncatulaIn-silico analysis of water and carbon relations under stress conditions. A multi-scale perspective centered on fruit.Simulating the yield impacts of organ-level quantitative trait loci associated with drought response in maize: a "gene-to-phenotype" modeling approach.Leaf Segmentation and Tracking in Arabidopsis thaliana Combined to an Organ-Scale Plant Model for Genotypic Differentiation.Functional-structural plant modelling: a new versatile tool in crop science.Gene expression analysis, proteomics, and network discovery.Adapting APSIM to model the physiology and genetics of complex adaptive traits in field crops.Yield-trait performance landscapes: from theory to application in breeding maize for drought tolerance.Plant systems biology: network matters.Plant hormone interactions: innovative targets for crop breeding and management.
P2860
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P2860
Models for navigating biological complexity in breeding improved crop plants.
description
2006 nî lūn-bûn
@nan
2006年の論文
@ja
2006年論文
@yue
2006年論文
@zh-hant
2006年論文
@zh-hk
2006年論文
@zh-mo
2006年論文
@zh-tw
2006年论文
@wuu
2006年论文
@zh
2006年论文
@zh-cn
name
Models for navigating biological complexity in breeding improved crop plants.
@ast
Models for navigating biological complexity in breeding improved crop plants.
@en
type
label
Models for navigating biological complexity in breeding improved crop plants.
@ast
Models for navigating biological complexity in breeding improved crop plants.
@en
prefLabel
Models for navigating biological complexity in breeding improved crop plants.
@ast
Models for navigating biological complexity in breeding improved crop plants.
@en
P2093
P1476
Models for navigating biological complexity in breeding improved crop plants.
@en
P2093
Bruce Walsh
Dean Podlich
François Tardieu
Fred van Eeuwijk
Graeme Hammer
Mark Cooper
Scott Chapman
Stephen Welch
P304
P356
10.1016/J.TPLANTS.2006.10.006
P577
2006-11-07T00:00:00Z