The major outcome was a confidential industry report. By 2005, completed two sugarcane projects that radically changed the priorities and evaluation methods of Australian breeding programs such that the delivery of new varieties now happens 3 to 5 years earlier.Optimization of genotype evaluation methods in breeding programs With > 8500 citations, Prof Chapman is currently in the top 1% of authors cited in the ESI fields of Plant and Animal Sciences and in Agricultural Sciences.

Current projects include a US DoE project with Purdue University, and multiple projects with CSIRO, U Adelaide, La Trobe, INRA (France) and U Tokyo. He has led numerous research projects that impact local and global public and private breeding programs in wheat, sorghum, sunflower and sugarcane led a national research program on research in ‘Climate-Ready Cereals’ in the early 2010s and was one of the first researchers to deploy UAV technologies to monitor plant breeding programs. Building on an almost continuous collaboration with UQ over that time, including as an Adjunct Professor to QAAFI, Prof Chapman was jointly appointed (50%) as a Professor in Crop Physiology in the UQ School of Agriculture and Food Sciences from 2017 to 2020, and at 100% with UQ from Sep 2020.

Much of this research was undertaken with CSIRO since 1996.

In recent years, this work has expanded more generally into various applications in digital agriculture from work on canopy temperature sensing for irrigation decisions (CSIRO Entrepreneurship Award 2022) through to applications of deep-learning to imagery to assist breeding programs. Application of quantitative approaches (crop 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.

My career research has been around genetic and environment effects on physiology of field crops, particularly where drought dominates.This area is developing rapidly and across UQ, I am engaging with faculty in multiple schools (ITEE, Maths and Physics, Mining and Mech Engineering) as well as in the Research Computing Centre to develop new projects and training opportunities at the interface of field agriculture and these new digital analytics. Since 2020, with full-time appointment at UQ, my research portfolio has included multiple projects in applications of machine learning and artificial intelligence into the ag domain. My current research at UQ is as Professor in this School (teaching AGRC3040 Crop Physiology) and as an Affiliate Professor of QAAFI.

Deep Edge by R.J. Scott