Recent advances in sequencing technology have enabled the elucidation of entire genome sequences for a number of key organisms. The bioinformatics post-processing of these sequences revealed the complete set of molecular components involved in cellular biochemical activities. The next challenge for the emerging field of systems biology is to integrate this data into so-called genome-scale models (GEM) to describe and simulate whole-cell metabolism. Such computational models have immense potential to speed up the rate of discovery (while reducing the need for expensive lab work) by their ability to rapidly generate and test new hypotheses. In plant biology, metabolic network modelling can generate new knowledge for improving plant performance. This approach is particularly useful for metabolic engineering purposes, redicting the necessary changes needed in order to enhance the yield and nutritional value of a range of agricultural products.