Crop outlook - Queensland Alliance for Agriculture and Food Innovation

Summer and winter cropping forecasts for Queensland’s wheat and sorghum cropping industries are produced by QAAFI’s experts in the complex integration of spatial production modelling and climate forecasting. These crop outlooks are available for free to view and download by growers.

Wheat outlook (winter)

QAAFI’s OZ-Wheat regional wheat yield forecasts are developed from climate data and modelling, remote sensing and historical data showing likely yield outcomes. They cover Queensland and northern New South Wales. The Oz-Wheat model is run from 1 October the year before sowing in order to account for the influence of the summer fallow on starting soil moisture conditions.

The current winter crop outlook for the state as a whole indicates a predicted median crop yield well below the long‐term expectation (19th percentile ranking relative to all years). This incorporates current soil water conditions and the seasonal rainfall outlook based on the southern oscillation index. There is however some variation within the state’s cropping region. While most parts of QLD’s cropping region have a very much reduced chance of this year’s wheat crop being above the long‐term median, some parts of CQ have an increased chance for an above median crop. This early in the season, widespread above average rainfall is needed across all parts of the state’s cropping region during the next couple of months. This will induce late planting opportunities and is needed to improve the current below average wheat crop expectations across most of QLD.

Sorghum outlook (summer)

QAAFI’s regional sorghum crop outlooks cover Queensland and northern New South Wales and are based on cropping after winter fallow, sorghum modelling, actual climate data, up to the forecasting date and projected climate data.

This late in the 2018/19 sorghum cropping season, predicted average crop yield for north-eastern Australia’s (NEAUS) summer cropping region has converged to 2.38 t/ha, which is close to the lowest on record (1st percentile) over the long-term. Very little variation exists across almost the entire NEAUS region with all regions having a forecast median yield falling in the bottom 5th percentile relative to all years. The recent very much below average rainfall recorded during February in the entire summer cropping region has further diminished crop yield prospects to very much below or lowest on record for some shires for the 2018/19 sorghum cropping season. The exception is for parts of southern NNSW, which have a close to average crop yield expectation. This crop outlook is based on a crop-free (short fallow) practice through the winter season and therefore areas with longer fallow practices are likely to have better yield prospects.

Paddock watch

Paddock Watch allows producers to directly input crop locations on their properties each season, to be used inside an automated prediction framework. Computer simulation and satellite imagery is then used to map crop production estimates at a regional scale across the State.

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About the researcher

QAAFI’s Dr Andries Potgeiter produces regular seasonal outlooks for sorghum and wheat producers in Queensland. Dr Potgieter (left) obtained a Bachelor of Science (Hons, MSc) in Mathematical Statistics at the University of the Orange Free State in 1991 and completed his PhD in the use of remote-sensing technologies, discriminating between specific and total winter cropping areas across regions and seasons, at the University of Southern Queensland, Australia in 2009. Before coming to QAAFI in 2010, Dr Potgeiter worked for the Queensland Government for more than 11 years as a senior research scientist. His main research interest is in the complex integration of spatial production modelling, climate forecasting and remotely sensed systems at a regional scale. In particular, his interest targets agricultural research that enhances the protifability and sustainability of spatial production systems through a better understanding of the linkages and interactions of such systems across a range of spatial (e.g. field, farm, catchment and national), and temporal (i.e. seasons to decades) scales.