Future technologies and systemic innovation are critical for the profound transformation the food system needs. These innovations range from food production, land use and emissions, all the way to improved diets and waste management. Here, we identify these technologies, assess their readiness and propose eight action points that could accelerate the transition towards a more sustainable food system. We argue that the speed of innovation could be significantly increased with the appropriate incentives, regulations and social license. These, in turn, require constructive stakeholder dialogue and clear transition pathways. Main To date, the future sustainability of food systems, the role of changing diets, reducing waste and increasing agricultural productivity have been mainly studied through the lens of existing technologies. Regarding the latter, for example, a common research question concerns what level of yield gain could be achieved through new crop varieties, livestock breeds, animal feeds, or changes in farming practices and the diffusion of technologies such as irrigation and improved management 7-13. Yet, as studies have shown, even with wide adoption of existing agricultural technologies,

The development of pedotransfer functions offers a potential means of alleviating cost and labour burdens associated with bulk‐density determinations. As a means of incorporating a priori knowledge into the model‐building process, we propose a conceptual model for predicting soil bulk density from other more regularly measured properties. The model considers soil bulk density to be a function of soil mineral packing structures (ρm) and soil structure (Δρ). Bulk‐density maxima were found for soils with approximately 80% sand. Bulk densities were also observed to increase with depth, suggesting the influence of over‐burden pressure. Residuals from the ρm model, hereby known as Δρ, correlated with organic carbon. All models were trained using Australian soil data, with limits set at bulk densities between 0.7 and 1.8 g cm−3 and containing organic carbon levels below 12%. Performance of the conceptual model (r2 = 0.49) was found to be comparable with a multiple linear regression model (r2 = 0.49) and outperformed models developed using an artificial neural network (r2 = 0.47) and a regression tree (r2 = 0.43). Further development of the conceptual model should allow the inclusion of soil morphological data to improve bulk‐density predictions.

The Soil and Landscape Grid of Australia (SLGA) is the first continental version of the GlobalSoilMap concept and the first nationally consistent, fine spatial resolution set of continuous soil attributes with Australia-wide coverage. The SLGA relies on digital soil mapping methods and integrates historical soil data, new measurement with spectroscopic sensors, novel spatial modelling and a web-service delivery architecture. The SLGA provides soil, regolith and landscape estimates at the centre point of 3 arcsecond grid cells (~90 × 90 m) across Australia. At each point, there are estimates of 11 soil attributes and confidence intervals for each estimate to a depth of 2 m or less, depth of regolith and a set of terrain descriptors. The information system also includes a library of mid-infrared spectra, an inference engine that allows estimation of additional soil parameters and an information model that enables users to access the system via web services. The explicit mapping of depth, bulk density and coarse fragments allows estimation of material stores and fluxes on a volumetric basis. The SLGA therefore has immediate applications in carbon, nitrogen and water process modelling. The map of regolith depth will find immediate application to studies of vadose zone processes, including solute transport, groundwater and nutrient fluxes beyond the root zone. Landscape attributes at 1 and 3 arcseconds are useful for a wide spectrum of ecological, hydrological and broader environmental applications. The SLGA can be accessed at no cost from www.csiro.au/soil-and-landscape-grid. It is managed and delivered as part of the Australian Soil Resource Information System (ASRIS).

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