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Using Simulation Modeling of Root Growth and Function as an Aid in Breeding for Increased Water- and Nutrient-Use Efficiency
A root system is considered efficient if it supplies optimal amounts of water and nutrients at minimal cost in photosynthates to the plant. This chapter explores the potential for simulation modeling to aid in identifying and breeding efficient root systems.
There are several soil-related stresses with the potential to adversely affect plant growth through limited supply of water and nutrients, physical constraints, toxicity, or by other pathways. A common strategy to reduce these stresses is to alter the soil environment through addition of amendments, tillage, or in other ways. An alternative strategy is to grow cultivars that are tolerant to soil-related stresses, a solution that is potentially economically and environmentally favorable and does not require a change in agricultural practices (and thus is most readily adopted by farmers) (Rengel 2005). Indeed, the capacity of genotypes to tolerate nutrient deficiencies has been identified as one of the crucial missing links in adaptation of crops to soil environments (Lynch 1998), especially in the face of changing climate (Lynch & St. Clair 2004). The successful crop genotypes of the future will be more efficient at capturing water and nutrient resources from challenging soils (Gregory & George 2011; Richardson et al. 2011).
By their very nature, root systems are difficult to observe. This has limited progress in understanding their structure and function and their interaction with the soil environment (Pierret et al. 2006). Indeed, the soil environment is always heterogeneous (e.g., Doussan et al. 2003; Valizadeh et al. 2003; Hodge 2004), and root systems interact in complex ways with it, being influenced by nutrient and water supply, temperature, soil structure, soil biological activity, and other factors varying in time and space. Knowledge of how individual factors influence the behavior of root systems is continually increasing (Gregory 2006; Richards et al. 2010; Nord et al. 2011; Palta et al. 2011; Richardson et al. 2011), but a more fundamental understanding of the impact that these factors have on the functional efficiency of root systems is needed to fully realize the potential of modern genetics.
Root properties are dependent on specific genes (e.g., in Arabidopsis, Loudet et al. 2005) and are therefore subject to genetic improvement through breeding. In contrast to Arabidopsis, the links between genes and root traits are not well known for most crops. However, modern breeding efforts combine bottom-up (gene to phenotype) and top-down (phenotype to gene) approaches, both of which require the knowledge of functional genomics driving discovery of genes for specific traits based on diverse genetic resources and excellent phenotyping capacity. However, utilizing the power of genomic approaches in crop improvement is hindered by a major gap in understanding the desired phenotypic traits in the field and linking these traits to relevant genes through genomics (cf. Ishitani et al. 2004; Richards et al. 2010). Indeed, it has been proposed that incorporating quantitative genetics into mechanistic models of root structure and function is required for understanding crop adaptation to soil environments (Lynch & St. Clair 2004).
Genetic marker technology provides the ability to screen large numbers of genotypes for particular rooting traits (e.g., Casson & Lindsey 2003; Loudet et al. 2005), allowing direct selection for specific characteristics of root systems (e.g., De Dorlodot et al. 2005), as has been demonstrated in common bean (Liao et al. 2004; Yan et al. 2004; Beebe et al. 2006; Ochoa et al. 2006) and maize (Zhu & Lynch 2004; Zhu et al. 2005a, b, 2006). Yet, it is still unknown which phenotypic traits are desirable in achieving increased efficiency of water and nutrient capture from the drying soil environments or how individual root traits influence crop productivity (Dunbabin et al. 2003a; Walk et al. 2006).
Publication titleImproving Water and Nutrient-Use Efficiency in Food Production Systems
Department/SchoolTasmanian Institute of Agriculture (TIA)
Place of publicationOxford, United Kingdom
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