Crop simulation modelling

Activity: Scholarly activities in Learning and Teaching reflectionPeer reviewed publication reflection

Description

The subject AGR203 (Production Analysis and Optimisation) has two components: Experimental Design and Decision Support (simulation Modelling). I am teaching the second part of this subject (simulation modelling). If the students are only being told the theoretical background of simulation modelling, it does not make much sense to them. However, if they see theoretical concepts are applied in practical situations, it makes better sense for the students.
For this I use the Agricultural Production Systems Simulation (APSIM), the second most popular, only next to DESSAT, crop simulation model in the word. As it is a public domain (free license for academic/research use) software, students can download it to their computer. This is also the software I am using for my research and I have published more than 10 peer reviewed articles using this software. So I use my research data and papers in teaching this part of the subject. My research involves field experiment and computer simulation. So 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 the same as 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 data for different future climate scenarios and the impact on crop yield. To see the adaptation to climate change, students run the computer program for different sowing dates and short-season and long-season varieties. This enables 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 different crop seeds and different times of sowing to see the impacts of these on emergence. These latter tests could have not been practically done with the experimental method as it would take long time and requires resources. However, students could do these with simulation modelling. A proposal to assess students learning using these two methods could not be approved by the Ethics Committee although several iterations were made because of the committee’s unreasonable, in my opinion, demand for such simple projects. However, students were asked to reflect on their learning and the pros and cons of the two approaches. It was very pleasing to see what the students did with the simulation modelling and the level of engagement. They 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 (like black box method). In this simulation, we could click on many factors and see how they interact and affect emergence which could not be done with the experimental approach. They now better understand what affects affect emergence. We could set the sowing dates at different times and see crop emergence date. We would have not been able to do this with experimental approach as we have only limited time of few weeks. We could create and analyse several scenarios. We could even see how seeds sown too deep could not even emerge. We could see why small seeded crops need to be sown shallow. Simulation modelling helped us to understand all these.
Period01 Jan 2021
Held atAgricultural, Environmental and Veterinary Sciences
Degree of RecognitionInternational