Sorghum Crop Modeling and Its Utility in Agronomy and Breeding

Crop models are simplified mathematical representations of the interacting biological and environmental components of the dynamic soil–plant–environment system. Sorghum crop modeling has evolved in parallel with crop modeling capability in general, since its origins in the 1960s and 1970s. Here we briefly review the trajectory in sorghum crop modeling leading to the development of advanced models. We then (i) overview the structure and function of the sorghum model in the Agricultural Production System sIMulator (APSIM) to exemplify advanced modeling concepts that suit both agronomic and breeding applications, (ii) review an example of use of sorghum modeling in supporting agronomic management decisions, (iii) review an example of the use of sorghum modeling in plant breeding, and (iv) consider implications for future roles of sorghum crop modeling. Modeling and simulation provide an avenue to explore consequences of crop management decision options in situations confronted with risks associated with seasonal climate uncertainties. Here we consider the possibility of manipulating planting configuration and density in sorghum as a means to manipulate the productivity–risk trade-off. A simulation analysis of decision options is presented and avenues for its use with decision-makers discussed. Modeling and simulation also provide opportunities to improve breeding efficiency by either dissecting complex traits to more amenable targets for genetics and breeding, or by trait evaluation via phenotypic prediction in target production regions to help prioritize effort and assess breeding strategies. Here we consider studies on the stay-green trait in sorghum, which confers yield advantage in water-limited situations, to exemplify both aspects. The possible future roles of sorghum modeling in agronomy and breeding are discussed as are opportunities related to their synergistic interaction. The potential to add significant value to the revolution in plant breeding associated with genomic technologies is identified as the new modeling frontier.

Estimating production costs and profitability of strawberry genotypes in southeast Queensland using plant traits

In Queensland the subtropical strawberry (Fragaria ×ananassa) breeding program aims to combine traits into new genotypes that increase production efficiency. The contribution of individual plant traits to cost and income under subtropical Queensland conditions has been investigated. The study adapted knowledge of traits and the production and marketing system to assess the economic impact (gross margin) of new cultivars on the system, with the overall goal of improving the profitability of the industry through the release of new strawberry cultivars. Genotypes varied widely in their effect on gross margin, from 48% above to 10% below the base value. The advantage of a new genotype was also affected by the proportion of total area allocated to the new genotype. The largest difference in gross margin between that at optimum allocation (8% increase in gross margin) and an all of industry allocation (20% decrease in gross margin) of area to the genotype was 28%. While in other cases the all of industry allocation was also the optimum allocation, with one genotype giving a 48% benefit in gross margin.