Following advances in genetics, genomics, and phenotyping, trait selection in breeding is limited by our ability to understand interactions within the plant and with the environment, and to identify traits of most relevance to the target population of environments. We propose an integrated approach that combines insights from crop modelling, physiology, genetics, and breeding to characterize traits valuable for yield gain in the target population of environments, develop relevant high-throughput phenotyping platforms, and identify genetic controls and their value in production environments. This paper uses transpiration efficiency (biomass produced per unit of water used) as an example of a complex trait of interest to illustrate how the approach can guide modelling, phenotyping, and selection in a breeding programme. We believe that this approach, by integrating insights from diverse disciplines, can increase the resource use efficiency of breeding programmes for improving yield gains in target populations of environments.

In sorghum, the growth angle of nodal roots is a major component of root system architecture. It strongly influences the spatial distribution of roots of mature plants in the soil profile, which can impact drought adaptation. However, selection for nodal root angle in sorghum breeding programs has been restricted by the absence of a suitable high throughput phenotyping platform. The aim of this study was to develop a phenotyping platform for the rapid, non-destructive and digital measurement of nodal root angle of sorghum at the seedling stage. The phenotyping platform comprises of 500 soil filled root chambers (50 × 45 × 0.3 cm in size), made of transparent perspex sheets that were placed in metal tubs and covered with polycarbonate sheets. Around 3 weeks after sowing, once the first flush of nodal roots was visible, roots were imaged in situ using an imaging box that included two digital cameras that were remotely controlled by two android tablets. Free software (openGelPhoto.tcl) allowed precise measurement of nodal root angle from the digital images. The reliability and efficiency of the platform was evaluated by screening a large nested association mapping population of sorghum and a set of hybrids in six independent experimental runs that included up to 500 plants each. The platform revealed extensive genetic variation and high heritability (repeatability) for nodal root angle. High genetic correlations and consistent ranking of genotypes across experimental runs confirmed the reproducibility of the platform. This low cost, high throughput root phenotyping platform requires no sophisticated equipment, is adaptable to most glasshouse environments and is well suited to dissect the genetic control of nodal root angle of sorghum. The platform is suitable for use in sorghum breeding programs aiming to improve drought adaptation through root system architecture manipulation.

Photosynthetic manipulation provides new opportunities for enhancing crop yield. However, understanding and quantifying the importance of individual and multiple manipulations on the seasonal biomass growth and yield performance of target crops across variable production environments is limited. Using a state‐of‐the‐art cross‐scale model in the APSIM platform we predicted the impact of altering photosynthesis on the enzyme‐limited (A_c) and electron transport‐limited (A_j) rates, seasonal dynamics in canopy photosynthesis, biomass growth, and yield formation via large multiyear‐by‐location crop growth simulations. A broad list of promising strategies to improve photosynthesis for C₃ wheat and C₄ sorghum were simulated. In the top decile of seasonal outcomes, yield gains were predicted to be modest, ranging between 0% and 8%, depending on the manipulation and crop type. We report how photosynthetic enhancement can affect the timing and severity of water and nitrogen stress on the growing crop, resulting in nonintuitive seasonal crop dynamics and yield outcomes. We predicted that strategies enhancing A_c alone generate more consistent but smaller yield gains across all water and nitrogen environments, A_j enhancement alone generates larger gains but is undesirable in more marginal environments. Large increases in both A_c and A_j generate the highest gains across all environments. Yield outcomes of the tested manipulation strategies were predicted and compared for realistic Australian wheat and sorghum production. This study uniquely unpacks complex cross‐scale interactions between photosynthesis and seasonal crop dynamics and improves understanding and quantification of the potential impact of photosynthesis traits (or lack of it) for crop improvement research.

Summary: Tillering determines the plant size of sorghum (Sorghum bicolor) and an understanding of its regulation is important to match genotypes to prevalent growing conditions in target production environments. The aim of this study was to determine the physiological and environmental regulation of variability in tillering among sorghum genotypes, and to develop a framework for this regulation. Diverse sorghum genotypes were grown in three experiments with contrasting temperature, radiation and plant density to create variation in tillering. Data on phenology, tillering, and leaf and plant size were collected. A carbohydrate supply/demand (S/D) index that incorporated environmental and genotypic parameters was developed to represent the effects of assimilate availability on tillering. Genotypic differences in tillering not explained by this index were defined as propensity to tiller (PTT) and probably represented hormonal effects. Genotypic variation in tillering was associated with differences in leaf width, stem diameter and PTT. The S/D index captured most of the environmental effects on tillering and PTT most of the genotypic effects. A framework that captures genetic and environmental regulation of tillering through assimilate availability and PTT was developed, and provides a basis for the development of a model that connects genetic control of tillering to its phenotypic consequences.

Water availability can limit maize (Zea mays L.) yields, and root traits may enhance drought adaptation if they can moderate temporal patterns of soil water extraction to favour grain filling. Root system efficiency (RSE), defined as transpiration per unit leaf area per unit of root mass, represents the functional mass allocation to roots to support water capture relative to the allocation to aerial mass that determines water demand. The aims of this study were to identify the presence of hybrid variation for RSE in maize, determine plant attributes that drive these differences and illustrate possible links of RSE to drought adaptation via associations with water extraction patterns. Individual plants for a range of maize hybrids were grown in large containers in shadehouses in Queensland, Australia. Leaf area, shoot and root mass, transpiration, root distribution and soil water were measured in all or selected experiments. Significant hybrid differences in RSE existed. High RSE was associated with reduced dry mass allocation to roots and more efficient water capture per unit of root mass. It was also weakly negatively associated with total plant dry mass, reducing preanthesis water use. This could increase grain yield under drought. RSE provides a conceptual physiological framework to identify traits for high-throughput phenotyping in breeding programs.