Dr Chloe Lai
| Name | Dr Chloe Lai |
|---|---|
| Email Address | chloe.lai@unisq.edu.au |
| Job Title | Research Fellow (Soil and Crop Modelling) |
| Qualifications | BEnvMan Qld, PhD Qld |
| Department | Centre for Sustainable Agricultural Systems (Research) |
| Centre for Sustainable Agricultural Systems (Operations) | |
| ORCID | https://orcid.org/0000-0002-7135-7520 |
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Employment
| Position | Organisation | From | To |
|---|---|---|---|
| Research Fellow | University of Southern Queensland | 2019 |
Expertise
My research develops practical solutions for spatially explicit, timely, data-driven farm management by modelling the interactions between soil constraints, crop production, and management practices. I specialise in integrating agricultural systems models, machine learning, and geostatistics to understand and connect processes at different scales. I work closely with industry partners to address specific challenges related to soil constraint management.
Teaching
AGR3304 Soil Science
Fields of Research
- 300206. Agricultural spatial analysis and modelling
- 300207. Agricultural systems analysis and modelling
- 410699. Soil sciences not elsewhere classified
Professional Membership
| Professional Membership | Year |
|---|---|
| Soil Science Australia | |
| International Union of Soil Science |
BEnvMan
Qld
2014
PhD
Qld
2021
Current Supervisions
| Research Title | Supervisor Type | Level of Study | Commenced |
|---|---|---|---|
| Understanding impacts of microplastics on soil structure and plant performance | Associate Supervisor | Doctoral | 2022 |
Completed Supervisions
| Research Title | Supervisor Type | Level of Study | Completed |
|---|---|---|---|
| Modelling soil physical and chemical properties using existing datasets across grain-growing regions of Australia | Associate Supervisor | Doctoral | 2024 |
| Project title | Details | Year |
|---|---|---|
| Knowledge-guided machine-learning optimisation of soil constraint management | This project aims to find the best ways to manage multiple soil constraints such as sodicity, acidity, and salinity to help farmers make informed soil management decisions to maximise productivity and profitability. While there are different ways to manage constraints in isolation, it is difficult to know which method to use and when due to high variability in the responsiveness of soils to ameliorants where multiple soil constraints exist. To tackle this challenge, the project proposes a computer-based approach (a knowledge-guided machine-learning framework) that incorporates scientific understanding and learns from existing data to predict which combinations of soil management will work best for a particular soil affected by multiple constraints under specific weather and farming conditions. | 2023 |
| Pipeline for quantification of climate risk on crop productivity of dominant soil types in Queensland, under future climate change scenarios | This project aims to establish a pipeline that quantifies climate risks on crop productivity for dominant soil types in Queensland under future climate change scenarios. By integrating Earth observations and a process-based agricultural systems model (APSIM), the project will evaluate crop performance over time, analyze emerging impacts on agronomic practices, and quantify climate risks through scenario modeling based on dominant crops and soil types. This will allow the evaluation of climate risks and development of targeted management interventions to mitigate the impact of climate change on crop production. | 2023 |
| Evaluating novel approaches for drought resilience through capitalising on an established network of long-term trials | This project focuses on enhancing the resilience of Australian farming systems and soils, enabling them to withstand and recover from frequent and extreme weather events. This resilience is crucial for the financial health and sustainability of farms, as well as for the well-being of rural communities. Utilizing the Soil CRC's resources, which include seven established field trials and a network of research and grower groups, the project aims to showcase the effectiveness of innovative practices in improving drought resilience. By analyzing up to eight years of field data from New South Wales, Victoria, and Western Australia, the project will refine APSIM model to assess the impact of new treatments, such as cover crops and soil amendments, on soil water retention, crop water use efficiency, and crop yield consistency. The ultimate goal is to demonstrate how these practices can reduce long-term financial risks for farmers. Grower groups will then disseminate these drought-mitigation strategies through their networks, promoting more resilient farming practices. | 2023 |
| Scoping study of the requirements for the development of CaneMAPPs | This study scopes the development of CaneMAPPS, a digital platform aimed at enhancing sugarcane farming productivity, profitability, and environmental sustainability. It will assess the feasibility and requirements for CaneMAPPS to serve as a central hub for comprehensive farm data management, analysis, and reporting. The platform is intended to facilitate the adoption of best practices and compliance with regulations by offering paddock-specific to industry-wide insights. This study will focus on integrating industry-best practices with advanced, cost-effective digital technologies, ensuring CaneMAPPS is fit-for-purpose and supports sustainable farming transitions. | 2021 |
| Diagnosis frameworks for multiple and complex soil constraints | This project addresses the challenge that 77% of Australian agricultural soils face productivity limitations due to various soil constraints, which are difficult to diagnose and manage due to their complex interactions. Traditionally, identifying these constraints involves costly and extensive soil sampling. The project aims to create and test new methods that leverage existing data (such as crop yields and basic soil tests) and public information (like national soil grids and satellite imagery) to identify soil issues more affordably. It will combine recent progress in biophysical soil modeling with artificial intelligence and statistical techniques to provide scalable and adaptive solutions for land managers. | 2021 |
| A conceptual framework for the modelling of sodicity constraints to crops | This project aims to improve our understanding of how soil constraints, which adversely affect crop yields, interact with plant physiological processes. The project will develop a conceptual model that integrates both biophysical and biogeochemical processes, focusing on how soil constraints, particularly sodicity, impact crop growth. Sodicity is chosen for its dual physical and geochemical challenges to crops. By interfacing this model with existing crop models, the project intends to facilitate future research across disciplines, aiding in the discovery of new soil management strategies and enhancing our mechanistic comprehension of soil-plant interactions within cropping systems. | 2021 |
| Date | Name | Awarding organisation | Underpinning research |
|---|---|---|---|
| 2022 | Silver overall in International Soil Judging Competition as a member of the Australian Team | World Congress of Soil Science | |
| 2022 | Postgraduate award for excellence in soil science | Queensland Branch of Soil Science Australia | |
| 2021 | Finalist of the Brian Chambers international award for early career researchers in crop nutrition | International Fertiliser Society | |
| 2021 | Finalist of Cooperative Research Australia Early Career Research Competition | Cooperative Research Australia | |
| 2021 | Winner (1st) of Individual Australian Soil Judging Competition | Soil Science Australia | |
| 2021 | Capacity Building Grant | University of Southern Queensland | |
| 2022 | Panelist for Industry-Research Collaboration in 2051: Voices from the future | Collaborate Innovate Conference |