Rate My Professor Scott Chapman

Professor Scott Chapman serves as Professor in Crop Physiology in the School of Agriculture and Food Sustainability at the University of Queensland, holding an affiliate professorship with the Queensland Alliance for Agriculture and Food Innovation. He obtained a Bachelor with Honours and a Doctor of Philosophy from the University of Queensland, completing his PhD in 1990 on the effects of drought during reproductive development on groundnut yields. Chapman's professional trajectory features long-term collaboration with CSIRO since 1996, a joint 50% appointment as Professor in Crop Physiology at UQ from 2017 to 2020, and a full-time role since September 2020. He instructs the course AGRC3040 Crop Physiology and contributes to numerous funded projects, including GRDC initiatives on analytics for grains, reducing lodging in sorghum, and salinity tolerance in taro.

Chapman's research examines genetic and environmental influences on field crop physiology, emphasizing drought-prone conditions, through crop simulation, statistical analyses, and phenotyping via aerial imaging and canopy monitoring. His innovations extend to machine learning, artificial intelligence, IoT, UAVs, and remote sensing for digital agriculture, such as canopy temperature for irrigation scheduling and deep learning for breeding imagery analysis. Notable impacts include reshaping Australian sugarcane and wheat breeding priorities for faster variety delivery, devising the internationally adopted 'environment characterization' methodology for drought-stable varieties, and developing the Pheno-Copter autonomous aerial phenotyping platform at CSIRO. He has garnered over 29,500 citations, placing him in the top 1% of cited authors in Plant and Animal Sciences and Agricultural Sciences per Essential Science Indicators, and received the CSIRO Entrepreneurship Award in 2022 for canopy sensing work, alongside 2024 Clarivate Highly Cited Researcher status in Cross-Field. Select publications encompass 'Molecular breeding for complex adaptive traits: how integrating crop ecophysiology and modelling can enhance efficiency' (Hammer et al., 2016), 'Visible, near infrared, and thermal spectral radiance on-board UAVs for high-throughput phenotyping' (Chapman et al., 2018), and contributions to sorghum modelling (Hammer et al., 2016).