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Lincoln University (2021)

Modelling approaches for lucerne growth and development under dryland conditions

Liu Jian

Titre : Modelling approaches for lucerne growth and development under dryland conditions

Auteur : Liu Jian

Université de soutenance : Lincoln University

Grade : Masters of Agricultural Science 2021

Lucerne is an ideal plant for east coast sheep and beef farmers to integrate on-farm to cope with a dry and drying climate. Expanded use of lucerne on-farm leads to on-farm questions around feed supply, environmental impacts and farm resilience. Many of these questions can only be answered with process-based models. These have been helping researchers, policy makers and farmers to make informed decisions about farm practices worldwide. However, the current lucerne model in the Agricultural production system simulator next generation (APSIMX) is not designed for simulating lucerne responses to dryland conditions. Hence, this study aimed to incorporate previous knowledge obtained from dryland experiments from Lincoln University into the APSIMX-Lucerne mode. New equations were introduced to the model to constraint the growth and development processes including leaf area expansion rate, radiation use efficiency and phyllochron under water-limited conditions. Secondly, this study investigated an alternative approach for increasing the efficiency and reliabilities of model parameter estimation. The reproducibility of the study was addressed as the third objective by adapting data science concepts and state-of-art tools. A literature review of lucerne responding to water stress (water deficiencies) laid out the physiological knowledge to design the mechanism of the APSIMX-Lucerne model. The thesis initially documents previous experiments, the APSIMX framework and data science tools. The conventional approach for APSIMX model development was conducted to gain experience and understanding of the structure and operation of the APSIMX-Lucerne model, verify the implementation of the lucerne model in the APSIMX framework and identify major issues with current model implementation to guide subsequent improvements. An alternative approach was applied via the R programme and a workflow manager to implement an optimisation procedure for estimating nine water-related parameters in a simple APSIMX water balance model.


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