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Functional–structural plant models (FSPMs) have been evolving for over 2 decades and their future development, to some extent, depends on the value of potential applications in crop science. To date, stabilizing crop production by identifying valuable traits for novel cultivars adapted to adverse environments is topical in crop science. Thus, this study will examine how FSPMs are able to address new challenges in crop science for sustainable crop production. FSPMs developed to simulate organogenesis, morphogenesis, and physiological activities under various environments and are amenable to downscale to the tissue, cellular, and molecular level or upscale to the whole plant and ecological level. In a modeling framework with independent and interactive modules, advanced algorithms provide morphophysiological details at various scales. FSPMs are shown to be able to: (i) provide crop ideotypes efficiently for optimizing the resource distribution and use for greater productivity and less disease risk, (ii) guide molecular design breeding via linking molecular basis to plant phenotypes as well as enrich crop models with an additional architectural dimension to assist breeding, and (iii) interact with plant phenotyping for molecular breeding in embracing three-dimensional (3D) architectural traits. This study illustrates that FSPMs have great prospects in speeding up precision breeding for specific environments due to the capacity for guiding and integrating ideotypes, phenotyping, molecular design, and linking molecular basis to target phenotypes. Consequently, the promising great applications of FSPMs in crop science will, in turn, accelerate their evolution and vice versa.

Limited-transpiration rate at high evaporative demand (‘LTR’ trait) has potential to improve drought adaptation, crop water productivity and food security. The quantification of the implications of LTR for water consumption, biomass accumulation and yield formation requires the use of dynamic crop modelling to simulate physiological and environmental processes and interactions in target environments. Here, a new transpiration module was developed for the Agricultural Production Systems sIMulator (APSIM NextGen) and used to simulate atmospheric and edaphic water stress on wheat crops. This module was parameterised with (i) data from a lysimeter experiment assessing genotypic variability in the LTR trait for four genotypes contrasting in transpiration efficiency, and with (ii) a more pronounced response to high evaporative demand. The potential of the LTR trait for improving crop productivity was investigated across the Australian wheatbelt over 1989-2018. The LTR trait was simulated to allow an increase in national yield by up to 2.6%, mostly due to shift in water use pattern, alleviation of water deficit during grain filling period and a higher harvest index. Greatest productivity gains were found in the northeast (4.9%, on average) where heavy soils allow the conserved water with the LTR trait to be available later at more critical stages. The effect of the LTR trait on yield was enhanced under the future climate scenario, particularly in the northeast. Limiting transpiration at high evaporative demands appears to be a promising trait for selection by breeders, especially in drought-prone environments where crops heavily rely on stored soil moisture.

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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 (Ac) and electron transport‐limited (Aj) 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 Ac alone generate more consistent but smaller yield gains across all water and nitrogen environments, Aj enhancement alone generates larger gains but is undesirable in more marginal environments. Large increases in both Ac and Aj 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.

There is high confidence that climate change has increased the probability of concurrent temperatureprecipitation extremes, changed their spatial-temporal variations, and affected the relationships between drivers of such natural hazards. However, the extent of such changes has been less investigated in Australia. Daily weather data (131 years, 1889-2019) at 700 grid cells (1• × 1•) across Australia was obtained to calculate annual and seasonal mean daily maximum temperature (MMT) and total precipitation (TPR). A nonparametric multivariate copula framework was adopted to estimate the return period of compound hotdry (CHD) events based on an 'And' hazard scenario (hotter than a threshold 'And' drier than a threshold). CHD extremes were defined as years with joint return periods of larger than 25 years. Mann-Kendall nonparametric tests was used to analyse trends in MMT and TPR as well as in the frequency of univariate and CHD extremes. A general cooling-wetting trend was observed over 1889-1989. Significant increasing trends were detected over 1990-2019 in the frequency and severity of hot extremes across the country while trends in dry extremes were mostly insignificant (and decreasing). Results showed a significant increase in the association between temperature and precipitation at various temporal scales. The frequency of CHD extremes was mostly stable over 1889-1989, but significantly increased between 1990 and 2019 at 44% of studied grid cells, mostly located in the north, south-east and south-west. Spatial homogeneity (i.e. connectedness) and propagation of extreme events from one grid cell to its neighbouring cells was investigated across Australia. It can be concluded that this connectedness has not significantly changed since 1889.

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