Overview
Background
Dr Dongxue Zhao is a Research Fellow within the Queensland Alliance for Agriculture and Food Innovation at The University of Queensland, Australia. Her research aims to contribute to sustainable gains in crop productivity by improving our understanding of how crop-soil interactions determine crop and root growth, water and nutrient uptake, and final yield. In her research, she combines innovative proximal and remote sensing techniques of crops, soils and roots, with predictive modelling and artificial intelligence tools. These include integrating electromagnetic induction (EMI) techniques, and drone and satellite imagery to monitor crop root growth and water use dynamics over time; 3D mapping of soil properties and sub-soil constraints to map resource constraints; time-lapse imaging of soil wetting and drying cycles for applications in irrigated cropping; developing new hyperspectral libraries for the rapid estimation of plant, crop and soil properties; data fusion and machine learning in the landscape mapping of soil carbon, plant water and nutrients availability.
Research Interests
- Phenotyping crop rooting systems in the field
- 3D characterization of soil water content and crop water use
- Developing new spectral databases for measuring and monitoring soil and plant properties
Availability
- Dr Dongxue Zhao is:
- Available for supervision
Qualifications
- Doctor of Philosophy of Environmental Management, The University of New South Wales
Works
Search Professor Dongxue Zhao’s works on UQ eSpace
2018
Journal Article
Sensitivity analysis of wind pressure coefficients on CAARC standard tall buildings in CFD simulations
Meng, Fan-Qin, He, Bao-Jie, Zhu, Jin, Zhao, Dong-Xue, Darko, Amos and Zhao, Zi-Qi (2018). Sensitivity analysis of wind pressure coefficients on CAARC standard tall buildings in CFD simulations. Journal of Building Engineering, 16, 146-158. doi: 10.1016/j.jobe.2018.01.004
2017
Journal Article
Effects of architectural shapes on surface wind pressure distribution: case studies of oval-shaped tall buildings
Zhao, Dong-Xue and He, Bao-Jie (2017). Effects of architectural shapes on surface wind pressure distribution: case studies of oval-shaped tall buildings. Journal of Building Engineering, 12, 219-228. doi: 10.1016/j.jobe.2017.06.009
2017
Journal Article
Numerical simulation of the effects of building dimensional variation on wind pressure distribution
Mou, Ben, He, Bao-Jie, Zhao, Dong-Xue and Chau, Kwok-Wing (2017). Numerical simulation of the effects of building dimensional variation on wind pressure distribution. Engineering Applications of Computational Fluid Mechanics, 11 (1), 293-309. doi: 10.1080/19942060.2017.1281845
2016
Journal Article
Comparative research on tillable properties of diatomite-improved soils in the Yangtze River Delta region, China
Qu, Ji-Li and Zhao, Dong-Xue (2016). Comparative research on tillable properties of diatomite-improved soils in the Yangtze River Delta region, China. Science of the Total Environment, 568, 480-488. doi: 10.1016/j.scitotenv.2016.06.056
2016
Journal Article
Stabilising the cohesive soil with palm fibre sheath strip
Qu, Jili and Zhao, Dongxue (2016). Stabilising the cohesive soil with palm fibre sheath strip. Road Materials and Pavement Design, 17 (1), 87-103. doi: 10.1080/14680629.2015.1064010
2015
Journal Article
The green school project: a means of speeding up sustainable development?
Zhao, Dong-Xue, He, Bao-Jie and Meng, Fan-Qin (2015). The green school project: a means of speeding up sustainable development?. Geoforum, 65, 310-313. doi: 10.1016/j.geoforum.2015.08.012
2015
Journal Article
Social problems of green buildings: from the humanistic needs to social acceptance
Zhao, Dong-Xue, He, Bao-Jie, Johnson, Christine and Mou, Ben (2015). Social problems of green buildings: from the humanistic needs to social acceptance. Renewable and Sustainable Energy Reviews, 51 4675, 1594-1609. doi: 10.1016/j.rser.2015.07.072
2015
Journal Article
Effect of random inclusion of palm fibers on strength characteristics of Shanghai cohesive soil
Qu, Ji Li, Zhao, Dong Xue and Li, Bei Bei (2015). Effect of random inclusion of palm fibers on strength characteristics of Shanghai cohesive soil. Advanced Materials Research, 1096, 572-581. doi: 10.4028/www.scientific.net/amr.1096.572
Supervision
Availability
- Dr Dongxue Zhao is:
- Available for supervision
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Available projects
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Drought tolerance in sorghum: the roots of the solution
Droughts are a major constraint to dryland agriculture worldwide. Climate change is amplifying the frequency and intensity of droughts, making the need to increase crop resilience urgent. Plant breeding programs are developing new genotypes of improved drought tolerance, but progress is slow. The development of improved plant genotypes (G) relies on the ability to screen large numbers of experimental lines for favourable traits (phenotyping) across contrasting growing environments. Agronomists instead build drought tolerance by identifying optimum combinations of G and agronomic managements (M) that best fit site and expected environmental conditions. Under drought, the crop rooting system, its architecture, size, and activity, determine the capacity of the crop to take up water for photosynthesis and yield, underpinning agricultural productivity. Identifying desirable root phenotypes directly in the field would be the short route to help identify and incorporate traits that enhance drought tolerance in breeding programs, and to inform more resilient crop managements. In this project we aim to develop a new, repeatable, inexpensive, quick, and accurate method for phenotyping rooting systems in the field. The approach will integrate the use of proximal electromagnetic induction (EMI) sensing of soils, drone imagery and crop ecophysiological principles. The key objectives of this fellowship are to: 1. Develop and test a proof-of-concept root phenotyping method in collaboration with a sorghum breeding company to screen root traits in large numbers of G, and GxM combinations. 2. Develop a ready-to-use data acquisition platform, data pipeline, and analysis method for root phenotyping in collaboration with a service provider of digital agriculture products. This will allow breeding companies to accelerate genetic progress and build drought resilience into their genotypes; agronomists to identify more resilient combinations of genotype and management practices, and digital agriculture businesses offer new products and services to breeding companies and agronomists.
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Matching pulse crop designs to site and expected seasonal conditions to maximise yield and profit: a crop ecophysiology approach (GRDC project administered by CSIRO)
Chickpeas can increase profits, diversify income, and increase sustainability. Megatrends in global food markets favour consumption of plant-based protein. However, significant productivity gaps remain, driven by lack of understanding of pulse physiology and agronomy. As part of a collaborative effort between UQ-QAAFI Centre for Crop Sciences and CSIRO, this project aims to improve our understanding of the impact of different water availabilities and temperature relationships on chickpea growth, development, and yield potential. The student will join a team of field agronomists, crop modellers, and crop physiologist that are conducting on-farm and on-research station trials to research the impacts of water availability and temperature regimes during critical periods of biomass partitioning and yield formation for chickpeas. The focus of the trials is to improve our understanding of the dynamics of yield formation under contrasting stresses. The student will be trained on the use of proximal root and canopy sensing technologies in the phenotyping of canopies and rooting systems using drones and DualEM sensors. Field, trials will be conducted during at least two seasons to improve and validate the APSIM model that will be used to assess yield and risks associated to contrasting GxExM combinations. Frequent travelling to the field and working outdoors in farmers’ fields will be required.
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Proximal 3D sensing of plant available water capacity
Plant available water capacity (PAWC) is the main soil property required to assess the amount and distribution of plant available water (PAW), used to inform pre planting, planting, and in-crop management decisions. Having access to reliable spatial maps of PAWC and PAW can also help inform cost-benefit analyses of investments in precision agriculture technologies and their applications. Previous attempts to map PAWC and PAW included the use of inverse crop modelling approaches to link maps of crop yield and vegetation indices with soil PAWC using crop models. The approach assumes that the observed yield is only affected by PAWC, it tends to only produce accurate representations of the total plant available water rather than its distribution in the soil profile and is unable to be applied to the fields without multiple seasons of yield maps. Another approach has taken advantage of the existing soil-landscape maps and PAWC information in the APSoil database. However, not all areas across Australia have been covered by the database and soil-landscape maps, and the data in APSoil can be highly imprecise, and highly specific to particular point locations, limiting the capability of this approach to account for spatial variations of PAWC for a target field. Here we propose a new conceptual approach to map PAWC and PAW rapidly and cost-effectively that combines 3D proximal sensing of permanent soil properties with the characterisation of transient site conditions using 3D maps of root growth and activity (Zhao, et al., 2022), and APSIM modelling. The student will be trained on the use of proximal sensing technologies and crop modeling for 3D characterizing soil moisture dynamics.
Supervision history
Current supervision
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Doctor Philosophy
Overcoming the root phenotyping bottleneck in cereals
Principal Advisor
Other advisors: Dr Alison Kelly, Professor David Jordan, Professor Daniel Rodriguez
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Doctor Philosophy
Investigating root-shoot dynamics to improve water-use efficiency of barley
Associate Advisor
Other advisors: Dr Alex Wu, Associate Professor Karine Chenu, Dr Hannah Robinson, Dr Millicent Smith, Professor Lee Hickey
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Doctor Philosophy
Designing Farming Systems with Whole Farm Models
Associate Advisor
Other advisors: Professor Hamish McGowan, Professor Daniel Rodriguez
Media
Enquiries
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