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.

Artificial olfaction system for on-site odour measurement

Odour impacts and concerns are an impediment to the growth of the Australian chicken meat industry. To manage these, the industry has to be able to demonstrate the efficacy of its odour reduction strategies scientifically and defensibly; however, it currently lacks reliable, cost effective and objective tools to do so. This report describes the development of an artificial olfaction system (AOS) to measure meat chicken farm odour. This report describes the market research undertaken to determine the demand for such a tool, the development and evaluation of three AOS prototypes, data analysis and odour prediction modelling, and the development of two complementary odour measurement tools, namely, a volatile organic compound (VOC) pre-concentrator and a field olfactometer. This report is aimed at investors in poultry odour research and those charged with, or interested in, assessment of odour on chicken farms, including farm managers, integrators, their consultants, regulators and researchers. The findings will influence the focus of future environmental odour measurement research.