Description
The subject AGR203 (Production Analysis and Optimisation) has two components: Experimental Design and Decision Support (Simulation Modelling). I teach the second part of this subject (simulation modelling). What I observed while teaching this subject is that if the students are only told the theoretical background of simulation modelling, it does not make much sense to them. However, if they see theoretical concepts as applied in practical situations, they are more engaged and interested in the subject.I used the Agricultural Production SIMulation (APSIM), an Australian model and the second most popular crop simulation model in the world. As it is a public domain (free license for academic/research use) software, students can download it to their computer. This is also the program I am using for my research and I have published more than 10 peer reviewed articles using this program. So I used my research data and papers in teaching this part of the subject. My research involves field experiment and computer simulation. By showing them how both approaches (of field experiment and simulation) can be used to study Genetic x Environment x Management, I give them the opportunity to compare the two approaches and specially how simulation modelling can be cost and time effective and helps to predict, what cannot be done using field experimental approach.
In this program, different parameters can be varied and the effect on resource use and crop yield investigated. This is similar to doing field experiment (for example different sowing dates) and see the effect on crop yield. In the simulation program, these changes can be done just by a click on the key-board or computer screen. The students were able to makes the changes in soil type, crop sowing dates, crop variety, different amounts of fertiliser, different amount of irrigation and see how it affects crop yield.
In the paper submitted as artifact, the students were given different climate data and investigate the impact on crop yield. To see the adaptation to climate change, students ran the computer program for different sowing dates and short-season and long-season varieties. This enabled them to see how it is possible to reduce yield loss due to climate change by adjusting sowing dates and crop varieties.
In the first part of this subject (experimental design part), students do an assessment task where they plant crop seeds at different depths and see seedling emergence date. The same exercise was done using simulation modelling. But they also simulated the effect of different crop seeds and times of sowing on emergence. These latter tests could have not been practically done with the experimental method as it would take long time and requires resources. The students were asked to reflect on their learning and the pros and cons of the two approaches. Their response to the comparison of the two approaches was that the simulation modelling enabled them to see what could have not been seen in the experimental method (which is like black box). The students were able to set the sowing dates at different times and see crop emergence date which could have not been done with experimental approach as we have only limited time of few weeks. They were able to see how seeds sown too deep could not even emerge and why small-seeded crops need to be sown shallow.
Period | 01 Jan 2021 |
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Held at | Agricultural, Environmental and Veterinary Sciences |
Degree of Recognition | International |
Related content
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Research Outputs
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Simulating agronomic adaptation strategies to mitigate the impacts of climate change on wheat yield in south-eastern Australia
Research output: Contribution to journal › Article › peer-review