The livelihood of humanity depends crucially on the growing and harvesting of crops, the processing of crops to produce the various foods that are eaten and the distribution of the
resulting products and produce to the various consumers. The underlying biological foundation on
which the success of this complex industrial hierarchy of activity rests is the success of the ongoing
process of plant breeding. Not only must plants be bred to ensure that the planned end-products,
such as bread, cakes, pasta and noodles, are of acceptable quality, they must, in order to minimize
crop failure and thereby ensure food security and supply, also be insect and/or disease resistant.
The success of such endeavours rests on the quality of the underlying science, which has become
highly sophisticated in recent years. Its utilization, in terms of the modern understanding of the
genetics of plant growth and the increasing sophistication of experimentation and instrumentation,
has greatly improved the speed and quality of plant breeding. The associated implementation of
these new plant breeding protocols is generating a need for improved quantication through the
utilization of mathematical modelling. In order to illustrate the diverse range of mathematics
required to support such quantification, this paper discusses some illustrative aspects connected
with the recent modelling of the flow and deformation of wheat-flour dough, information recovery
from spectroscopic data (e.g. such as the determination of the protein content in wheat), antiviral
resistance in plants and pattern formation in plants. Various aspects of the mathematics involved
are highlighted from a mathematical modelling perspective, with a key secondary goal, using the
discussion about these examples, of illustrating how applications impact on mathematics with the
resulting mathematical developments in turn contributing to the solution of other applications
with the process starting all over again.