Crop modelling can play an important role in guiding the increase in global food production capacity necessary to meet the impending shortfall.
In a recently published Editorial, Professor Graeme Hammer from the Centre for Crop Science at The University of Queensland explores what is needed to improve the future practice of plant modelling to support crop improvement.
“The biological understanding contained in dynamic plant growth and development models can be harnessed for prediction. The predictive capabilities enable simulation of scenarios to help advance crop adaptation and plant improvement,” says Hammer.
In his piece, Hammer identifies two practices necessary for effective modelling: (1) model and modeller credibility and (2) transdisciplinarity.
Hammer describes how model and modeller credibility can be tested. Models must have biological realism in their functions with grounding in solid experimental and theoretical evidence. The accessibility of code and underpinning logic and theory contained in the model is required for full transparency. Modellers must have clarity on what a model can and cannot sensibly do.
Transdisciplinarity addresses the need to capture the nexus between molecular and ecophysiological understanding and concepts that are central in the adaptive responses of complex plant/crop systems. Multiscale modeling is central to enhancing awareness of the interdependence among disciplinary specialisations. Hammer calls for on-going effort to improve connectivity among molecular, plant and crop level scientific effort. “I urge researchers to read papers and seek dialogue beyond the strict confines of their disciplinary base.”
The virtual conference, FSPM2020: Toward Computable Plants, to be held October 5-9, 2020, will provide an excellent opportunity to make broad-based connections without the cost or time of travel.
For ideas on how to connect with other researchers virtually, read “in silico Plants Maximizes the Visibility of Your Paper.”