AFFILIATION : Sydney University - Australia
THEME : Modelling and forecasting crop yield with Big Data – applications in cotton and grains
SUMMARY We are now in the age of Big Data in agriculture, and with this comes many opportunities. In broadacre cropping systems there is often an abundance of data collected on-farm, including yield monitor data, ECa surveys, soil test results, and management data. In addition, publicly-available datasets that can be used to interpret the crop-growing environment are increasing in quantity and quality, including satellite remote sensing imagery and climate data. Combining this wealth of data across many fields and farms, and many seasons can provide significant value in understanding our cropping systems. It allows the development of empirical models to forecast crop yield at fine spatial scales, as well as the identification of yield gaps, and the detection of possible yield constraints. These outputs can be invaluable in assisting farmers to improve their management decisions. This presentation covers case studies from the cotton and grains industries, and uses data from a suite of large farms across Australia. BIOGRAPHY

Patrick Filippi is a researcher in the School of Life and Environmental Sciences and Sydney Institute of Agriculture. His research interests are in precision agriculture, and helping growers to make more informed and precise management decisions. This is done through utilising an abundance of agricultural and environmental data sources, and combining this with advanced modelling techniques. Patrick completed a Bachelor of Science in Agriculture (Hons) at USyd in 2013, with a major in agronomy. He also completed his PhD in 2017 at USyd, which was focused on monitoring, modelling, and mapping spatio-temporal changes in soil properties in an irrigated cotton-growing region. This research had a particular emphasis on the role of agricultural practices and environmental shifts on soil condition.