QAAFI Early Career, Research Fellow
Overview
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
Qualifications
- Doctor of Philosophy of Environmental Management
Publications
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Journal Article: Sowing summer grain crops early in late winter or spring: effects on root growth, water use, and yield
Zhao, Dongxue, deVoil, Peter, Rognoni, Bethany G., Wilkus, Erin, Eyre, Joseph X., Broad, Ian and Rodriguez, Daniel (2024). Sowing summer grain crops early in late winter or spring: effects on root growth, water use, and yield. Plant and Soil. doi: 10.1007/s11104-024-06648-0
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Journal Article: Optimizing the ecological network of resource-based cities to enhance the resilience of regional ecological networks
Zhao, Yuxi, Zhang, Ming, Zhao, Dongxue, Duo, Linghua and Lu, Chunyang (2024). Optimizing the ecological network of resource-based cities to enhance the resilience of regional ecological networks. Environmental Science and Pollution Research, 31 (11), 17182-17205. doi: 10.1007/s11356-024-32271-8
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Journal Article: The response of ecosystem vulnerability to climate change and human activities in the Poyang lake city group, China
Chen, Yaoyao, Duo, Linghua, Zhao, Dongxue, Zeng, Yi and Guo, Xiaofei (2023). The response of ecosystem vulnerability to climate change and human activities in the Poyang lake city group, China. Environmental Research, 233 116473, 1-13. doi: 10.1016/j.envres.2023.116473
Grants
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Root structure and function traits: Overcoming the root phenotyping bottleneck in cereals
(2024–2027) PROC-9176895 Phenomics methods and tools to enable improved resource capture efficiency in grain crops
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Drought tolerance in sorghum: the roots of the solution
(2023–2026) ARC Early Career Industry Fellowships
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A proof of concept for the proximal 3D sensing of plant available water capacity
(2023–2024) Grains Research & Development Corporation
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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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.
Publications
Book Chapter
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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
Journal Article
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Zhao, Dongxue, deVoil, Peter, Rognoni, Bethany G., Wilkus, Erin, Eyre, Joseph X., Broad, Ian and Rodriguez, Daniel (2024). Sowing summer grain crops early in late winter or spring: effects on root growth, water use, and yield. Plant and Soil. doi: 10.1007/s11104-024-06648-0
-
Zhao, Yuxi, Zhang, Ming, Zhao, Dongxue, Duo, Linghua and Lu, Chunyang (2024). Optimizing the ecological network of resource-based cities to enhance the resilience of regional ecological networks. Environmental Science and Pollution Research, 31 (11), 17182-17205. doi: 10.1007/s11356-024-32271-8
-
Chen, Yaoyao, Duo, Linghua, Zhao, Dongxue, Zeng, Yi and Guo, Xiaofei (2023). The response of ecosystem vulnerability to climate change and human activities in the Poyang lake city group, China. Environmental Research, 233 116473, 1-13. doi: 10.1016/j.envres.2023.116473
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Gu, Ruili, Duo, Linghua, Guo, Xiaofei, Zou, Zili and Zhao, Dongxue (2023). Spatiotemporal heterogeneity between agricultural carbon emission efficiency and food security in Henan, China. Environmental Science and Pollution Research, 30 (17), 49470-49486. doi: 10.1007/s11356-023-25821-z
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Xiao, Sheng, Duo, Linghua, Guo, Xiaofei, Zou, Zili, Li, Yanan and Zhao, Dongxue (2023). Research on the coupling coordination and driving role of urbanization and ecological resilience in the middle and lower reaches of the Yangtze River. PeerJ, 11 e15869, e15869. doi: 10.7717/peerj.15869
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Zhao, Xueyu, Wang, Jie, Zhao, Dongxue and Triantafilis, John (2023). Soil organic carbon prediction by multi-digital data fusion for nitrogen management in a sugarcane field. Nutrient Cycling in Agroecosystems, 127 (1), 119-136. doi: 10.1007/s10705-022-10233-1
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Zhao, Xueyu, Wang, Jie, Zhao, Dongxue, Sefton, Michael and Triantafilis, John (2022). Mapping Cation Exchange Capacity (CEC) across sugarcane fields with different comparisons by using DUALEM data. Journal of Environmental and Engineering Geophysics, 27 (4), 191-205. doi: 10.32389/jeeg22-002
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3D characterization of crop water use and the rooting system in field agronomic research
Zhao, Dongxue, Eyre, Joseph X., Wilkus, Erin, de Voil, Peter, Broad, Ian and Rodriguez, Daniel (2022). 3D characterization of crop water use and the rooting system in field agronomic research. Computers and Electronics in Agriculture, 202 107409, 1-14. doi: 10.1016/j.compag.2022.107409
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Zhao, Xueyu, Zhao, Dongxue, Wang, Jie and Triantafilis, John (2022). Soil organic carbon (SOC) prediction in Australian sugarcane fields using Vis–NIR spectroscopy with different model setting approaches. Geoderma Regional, 30 e00566, 1-13. doi: 10.1016/j.geodrs.2022.e00566
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Dynamic change of vegetation index and its influencing factors in Alxa League in the arid area
Zhou, Peng, Zhao, Dongxue, Liu, Xiao, Duo, Linghua and He, Bao-Jie (2022). Dynamic change of vegetation index and its influencing factors in Alxa League in the arid area. Frontiers in Ecology and Evolution, 10 922739, 1-14. doi: 10.3389/fevo.2022.922739
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Duo, Linghua, Li, Yanan, Zhang, Ming, Zhao, Yuxi, Wu, Zhenhua and Zhao, Dongxue (2022). Spatiotemporal pattern evolution of urban ecosystem resilience based on “Resistance-Adaptation-Vitality”: a case study of Nanchang City. Frontiers in Earth Science, 10 902444, 1-20. doi: 10.3389/feart.2022.902444
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He, Bao-Jie, Zhao, Dongxue, Dong, Xin, Xiong, Ke, Feng, Chi, Qi, Qianlong, Darko, Amos, Sharifi, Ayyoob and Pathak, Minal (2022). Perception, physiological and psychological impacts, adaptive awareness and knowledge, and climate justice under urban heat: a study in extremely hot-humid Chongqing, China. Sustainable Cities and Society, 79 103685, 1-15. doi: 10.1016/j.scs.2022.103685
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Clay content mapping and uncertainty estimation using weighted model averaging
Zhao, Dongxue, Wang, Jie, Zhao, Xueyu and Triantafilis, John (2022). Clay content mapping and uncertainty estimation using weighted model averaging. CATENA, 209 (Part 2) 105791, 1-14. doi: 10.1016/j.catena.2021.105791
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Wang, Jie, Zhao, Dongxue, Zare, Ehsan, Sefton, Michael and Triantafilis, John (2022). Unravelling drivers of field-scale digital mapping of topsoil organic carbon and its implications for nitrogen practices. Computers and Electronics in Agriculture, 193 106640, 1-15. doi: 10.1016/j.compag.2021.106640
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Will individuals visit hospitals when suffering heat-related illnesses? Yes, but…
He, Bao-Jie, Zhao, Dongxue, Dong, Xin, Zhao, Ziqi, Li, Liguang, Duo, Linghua and Li, Jing (2022). Will individuals visit hospitals when suffering heat-related illnesses? Yes, but…. Building and Environment, 208 108587. doi: 10.1016/j.buildenv.2021.108587
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Li, Nan, Zhao, Dongxue, Arshad, Maryem, Sefton, Michael and Triantafilis, John (2022). Comparison of a digital soil map and conventional soil map for management of topsoil exchangeable sodium percentage. Soil Use and Management, 38 (1), 121-134. doi: 10.1111/sum.12666
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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. doi: 10.1016/j.still.2020.104618
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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
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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
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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. doi: 10.3390/s19183936
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
Other Outputs
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Early sorghum 2019-2022 data set
Rodriguez, Daniel and Zhao, Dongxue (2023). Early sorghum 2019-2022 data set. The University of Queensland. (Dataset) doi: 10.48610/7924c5e
Grants (Administered at UQ)
-
Root structure and function traits: Overcoming the root phenotyping bottleneck in cereals
(2024–2027) PROC-9176895 Phenomics methods and tools to enable improved resource capture efficiency in grain crops
-
Drought tolerance in sorghum: the roots of the solution
(2023–2026) ARC Early Career Industry Fellowships
-
A proof of concept for the proximal 3D sensing of plant available water capacity
(2023–2024) Grains Research & Development Corporation
-
Frost and Heat Management Analytics (GRDC Grant administered by CSIRO)
(2022–2026) CSIRO
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(2022–2025) CSIRO
PhD and MPhil Supervision
Current Supervision
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Digital farm tweens in agriculture
Doctor Philosophy — Associate Advisor
Other advisors:
Possible Research Projects
Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.
-
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.
-
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.
-
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.
