Connecting agricultural data across scales to maintain food supply

Professor Scott Chapman, School of Agriculture and Food Sustainability, The University of Queensland

For more than 10 000 years, farmers have used local knowledge of their soils, climates and ecologies to guide the production of food, and to create new varieties of crops and ways to manage them in sustainable ways. Modern methods of production are efficient in terms of resource-use and we continue to try to refine the genetics and management of crops to feed the world.

Over the last 150 years or so, weather monitoring systems became part of quantifying environments, while in the last 30 years, the mapping of DNA in crop genomes now allows plant breeders to develop more adaptable varieties of crops. In our research, we study how varieties of crops adapt to climate across the entire wheatbelt. In doing this, we are utilising many sensing methodologies – using weather stations, imaging from phones and drones and satellites, and building computer models of how crops grow in current and future climates. New methods of deep learning and artificial intelligence contribute to gathering and building solutions to maintain food production under challenging conditions like increased heat and drought due to climate change.

Biography
After completing studies at UQ in the early 1990s, Scott went to Mexico for 4 years, working at CIMMYT – the home of the Green Revolution where dwarf wheats were invented in the 1960s averting massive food crises in East Asia. On returning to Australia, he worked for UQ and then for CSIRO for 24 years. Scott's career research has been around genetic and environment effects on physiology of field crops, particularly where drought dominates. Application of quantitative approaches (computer simulation and statistical methods) and phenotyping (aerial imaging, canopy monitoring) to integrate the understanding of interactions of genetics, growth and development and the bio-physical environment on crop yield. As a Professor at UQ since 2020, his research portfolio now includes multiple projects in applications of machine learning and artificial intelligence into the ag domain. This area is developing rapidly and, across UQ, he is engaging with faculty in multiple schools (ITEE, Maths and Physics, Mining and Mech Engineering) and with national and international partners to develop new projects and training opportunities at the interface of field agriculture and these new digital analytics.

Please note: If you have registered to attend the lecture via Zoom, the lecture link will be emailed to all registrants closer to the lecture date. This lecture may be recorded. If you have any questions, please email us at info@rgsq.org.au.