Computational Models
The model bean? Computational modelling of Coffea growth
The model can reproduce the measured data, and so opens up avenues for applying this original procedure to other experimental data.
Computational Models
Modelling practices that support crop improvement
Credibility and transdisciplinarity play crucial roles in modelling to advance crop adaptation and plant improvement.
Computational Models
Modelling rice roots reveals how to pick up phosphorus
Combining experimentally measured single root phene datasets with a 3D continuum multiscale soilroot model enhances the mechanistic insights in soil-root processes that are important for water and P uptake.
Computational Models
Key Eucalyptus traits for high yield under climate change identified
Global sensitivity analysis was used to identify key traits for Eucalyptus adaptation to climate variability and change in Brazil.
Computational Models
Individual variation in plant dispersal and fecundity increases rates of spatial spread
The highest increases in spread rates occur when variation in dispersal positively co-varies with fecundity.
Computational Models
You get a better model of the forest when you look at the individual trees
The computing principle GIGO states that if the data you put into a model is garbage, then the output will be too. Jie Yang and colleagues
Computational Models
From computer to field: can in silico modelling can help us to optimise rice for possible droughts?
Advances in computational models may allow us to quickly predict responses of important food crops to environmental stresses in the field, and to identify the genetic basis of these.
Computational Models
Going nuts: simulating macadamia’s carbon allocation in Australia
Study proposes a new computer model for simulating macadamia tree carbon allocation.
Computational Models
Positions matter: drones using nadir and oblique photography on maize fields
Study reveals that more detailed 3D point clouds can be produced using oblique photography.
Computational Models
Plant-mSubP: a machine learning tool to predict single- and multi-target protein subcellular localisation
Plant cells are three-dimensional spaces composed of several compartments, each with its own physicochemical environment and function. The subcellular localisation of proteins, the cell’s
Computational Models
V-Mango model: an intricate 3D simulation of the King of Fruits
The computer-modelled mangoes could identify when their real-life counterparts were most at risk from mango blossom gall midge.
Computational Models
Pattern-oriented modelling a useful tool for FSP models when experimental data is lacking
POM parameter estimation led to a model that converged on manual parameterization.