APSIM NextGen Canola model – new flexibility and functionality

Dr Julianne Lilley1, Dr Jeremy Whish2, Dr Neil Huth3, Dean Holzworth3, Neville Herrmann1 

1CSIRO, Canberra, Australia,

2CSIRO, St Lucia, Australia,

3CSIRO, Toowoomba, Australia

 

The Agricultural Production Systems sIMulator (APSIM) consists of a suite of models developed to simulate the soil, crop and management interactions of farming systems. The canola model was developed in the late 1990s and has been used to investigate different aspects of canola production across Australia ever since. More recently the APSIM Initiative has been building the next generation of APSIM to create a simulation framework that can run larger and more complex simulations at multiple temporal and spatial scales. The Plant Modelling Framework for APSIM NextGen is more versatile and the efficiency of capturing our understanding of crop processes within the model is improved. For example, new routines describing genetic parameters, or the physiological response to new traits or events such as abiotic or biotic stress are readily incorporated, modified and tested.

The new APSIM Next Gen Canola model has been validated against an extensive set of detailed phenology observations (n>400) and yield observations (n>1000) from field experiments that include a wide range of cultivars, locations, seasons and agronomic treatments. A feature of the new model includes improved phenology prediction by better accounting for response to vernalisation and thermal time with parameters to describe new cultivar phenotypes. This allows the evaluation of a novel phenology type in the farming system and improved prediction of canola development beyond the traditional growing regions.


Biography:

Dr Julianne Lilley is Team Leader of the Integrated Agric Modelling & Decisions team within Agriculture and Food which develops and uses soil, crop, pasture and livestock models in a farming systems context for application in agricultural research across Australia and internationally. Julianne is a crop scientist with over 25 years research experience in crop physiology. Her research has included climate change impacts, crop root system function, crop water-use efficiency, dual-purpose cropping, whole-farm productivity and resource protection. She applies crop physiological understanding embedded within crop simulation models to greatly expand the outcomes of experiments and draw robust conclusions about the impacts of agricultural management decisions.

She is currently leads research investigating farm management practices which optimise profitability of canola, understanding environmental triggers and the underlying genetic control of flowering in canola, and developing the Yield Gap Australia website, a tool developed at CSIRO to inform policy makers and grain producers of the gap between potential and actual yields from local to national scale.

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