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, unknown
Works
Search Professor Dongxue Zhao’s works on UQ eSpace
2021
Journal Article
Selecting optimal calibration samples using proximal sensing EM induction and γ-ray spectrometry data: an application to managing lime and magnesium in sugarcane growing soil
Wang, Jie, Zhao, Xueyu, Zhao, Dongxue and Triantafilis, John (2021). Selecting optimal calibration samples using proximal sensing EM induction and γ-ray spectrometry data: an application to managing lime and magnesium in sugarcane growing soil. Journal of Environmental Management, 296 113357, 1-14. doi: 10.1016/j.jenvman.2021.113357
2021
Journal Article
A systematic evaluation of multisensor data and multivariate prediction methods for digitally mapping exchangeable cations: a case study in Australian sugarcane field
Arshad, Maryem, Zhao, Dongxue, Khongnawang, Tibet and Triantafilis, John (2021). A systematic evaluation of multisensor data and multivariate prediction methods for digitally mapping exchangeable cations: a case study in Australian sugarcane field. Geoderma Regional, 25 e00400, 1-15. doi: 10.1016/j.geodrs.2021.e00400
2021
Journal Article
Scope to map available water content using proximal sensed electromagnetic induction and gamma-ray spectrometry data
Zare, Ehsan, Wang, Jie, Zhao, Dongxue, Arshad, Maryam and Triantafilis, John (2021). Scope to map available water content using proximal sensed electromagnetic induction and gamma-ray spectrometry data. Agricultural Water Management, 247 106705, 106705. doi: 10.1016/j.agwat.2020.106705
2021
Journal Article
Soil exchangeable cations estimation using Vis-NIR spectroscopy in different depths: Effects of multiple calibration models and spiking
Zhao, Dongxue, Arshad, Maryem, Wang, Jie and Triantafilis, John (2021). Soil exchangeable cations estimation using Vis-NIR spectroscopy in different depths: Effects of multiple calibration models and spiking. Computers and Electronics in Agriculture, 182 105990, 1-14. doi: 10.1016/j.compag.2021.105990
2021
Journal Article
The effect of trade openness on the relationship between agricultural technology inputs and carbon emissions: evidence from a panel threshold model
Xu, Xiaocang, Zhang, Na, Zhao, Dongxue and Liu, Chengjie (2021). The effect of trade openness on the relationship between agricultural technology inputs and carbon emissions: evidence from a panel threshold model. Environmental Science and Pollution Research, 28 (8), 9991-10004. doi: 10.1007/s11356-020-11255-4
2021
Journal Article
Predicting soil physical and chemical properties using vis-NIR in Australian cotton areas
Zhao, Dongxue, Arshad, Maryem, Li, Nan and Triantafilis, John (2021). Predicting soil physical and chemical properties using vis-NIR in Australian cotton areas. Catena, 196 104938, 104938. doi: 10.1016/j.catena.2020.104938
2021
Journal Article
Proximally sensed digital data library to predict topsoil clay across multiple sugarcane fields of Australia: applicability of local and universal support vector machine
Arshad, Maryem, Zhao, Dongxue, Zare, Ehsan, Sefton, Michael and Triantafilis, John (2021). Proximally sensed digital data library to predict topsoil clay across multiple sugarcane fields of Australia: applicability of local and universal support vector machine. Catena, 196 104934. doi: 10.1016/j.catena.2020.104934
2020
Journal Article
Reconnaissance scale mapping of salinity in three-dimensions using EM38 and EM34 data and inversion modelling
Wang, Jie, Zhao, Xueyu, Zhao, Dongxue, Arshad, Maryem, Zare, Ehsan and Triantafilis, John (2020). Reconnaissance scale mapping of salinity in three-dimensions using EM38 and EM34 data and inversion modelling. Land Degradation and Development, 31 (18), 2936-2951. doi: 10.1002/ldr.3684
2020
Journal Article
Two-dimensional time-lapse imaging of soil wetting and drying cycle using EM38 data across a flood irrigation cotton field
Zare, Ehsan, Arshad, Maryam, Zhao, Dongxue, Nachimuthu, Gunasekhar and Triantafilis, John (2020). Two-dimensional time-lapse imaging of soil wetting and drying cycle using EM38 data across a flood irrigation cotton field. Agricultural Water Management, 241 106383. doi: 10.1016/j.agwat.2020.106383
2020
Journal Article
Mapping cation exchange capacity using a quasi-3d joint inversion of EM38 and EM31 data
Zhao, Dongxue, Li, Nan, Zare, Ehsan, Wang, Jie and Triantafilis, John (2020). Mapping cation exchange capacity using a quasi-3d joint inversion of EM38 and EM31 data. Soil and Tillage Research, 200 104618, 104618. doi: 10.1016/j.still.2020.104618
2020
Book Chapter
Integration of Low-Carbon Eco-City, Green Campus and Green Building in China
He, Bao-Jie, Zhao, Dong-Xue and Gou, Zhonghua (2020). Integration of Low-Carbon Eco-City, Green Campus and Green Building in China. Green Building in Developing Countries: Policy, Strategy and Technology. (pp. 49-78) Cham, Switzerland: Springer. doi: 10.1007/978-3-030-24650-1_4
2019
Journal Article
Determining optimal digital soil mapping components for exchangeable calcium and magnesium across a sugarcane field
Li, Nan, Arshad, Maryem, Zhao, Dongxue, Sefton, Michael and Triantafilis, John (2019). Determining optimal digital soil mapping components for exchangeable calcium and magnesium across a sugarcane field. Catena, 181 104054. doi: 10.1016/j.catena.2019.04.034
2019
Journal Article
Comparing management zone maps to address infertility and sodicity in sugarcane fields
Arshad, Maryem, Li, Nan, Zhao, Dongxue, Sefton, Michael and Triantafilis, John (2019). Comparing management zone maps to address infertility and sodicity in sugarcane fields. Soil and Tillage Research, 193, 122-132. doi: 10.1016/j.still.2019.05.023
2019
Journal Article
Three-dimensional mapping of clay and cation exchange capacity of sandy and infertile soil using EM38 and inversion software
Khongnawang, Tibet, Zare, Ehsan, Zhao, Dongxue, Srihabun, Pranee and Triantafilis, John (2019). Three-dimensional mapping of clay and cation exchange capacity of sandy and infertile soil using EM38 and inversion software. Sensors, 19 (18) 3936, 3936. doi: 10.3390/s19183936
2019
Journal Article
Digital regolith mapping of clay across the Ashley irrigation area using electromagnetic induction data and inversion modelling
Zhao, Xueyu, Wang, Jie, Zhao, Dongxue, Li, Nan, Zare, Ehsan and Triantafilis, John (2019). Digital regolith mapping of clay across the Ashley irrigation area using electromagnetic induction data and inversion modelling. Geoderma, 346, 18-29. doi: 10.1016/j.geoderma.2019.01.033
2019
Journal Article
Co-benefits approach: Opportunities for implementing sponge city and urban heat island mitigation
He, Bao-Jie, Zhu, Jin, Zhao, Dong-Xue, Gou, Zhong-Hua, Qi, Jin-Da and Wang, Junsong (2019). Co-benefits approach: Opportunities for implementing sponge city and urban heat island mitigation. Land Use Policy, 86, 147-157. doi: 10.1016/j.landusepol.2019.05.003
2018
Journal Article
Promoting and implementing urban sustainability in China: an integration of sustainable initiatives at different urban scales
He, Bao-Jie, Zhao, Dong-Xue, Zhu, Jin, Darko, Amos and Gou, Zhong-Hua (2018). Promoting and implementing urban sustainability in China: an integration of sustainable initiatives at different urban scales. Habitat International, 82, 83-93. doi: 10.1016/j.habitatint.2018.10.001
2018
Journal Article
A Vis-NIR spectral library to predict clay in Australian cotton growing soil
Zhao, Dongxue, Zhao, Xueyu, Khongnawang, Tibet, Arshad, Maryem and Triantafilis, John (2018). A Vis-NIR spectral library to predict clay in Australian cotton growing soil. Soil Science Society of America Journal, 82 (6), 1347-1357. doi: 10.2136/sssaj2018.03.0100
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
Funding
Current funding
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
Designing Farming Systems with Whole Farm Models
Associate Advisor
Other advisors: Professor Hamish McGowan, 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
Media
Enquiries
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