A team of biologists and computer scientists has adopted a time-based machine-learning approach to deduce the temporal logic of nitrogen signaling in plants from genome-wide expression data. The work potentially offers new ways to monitor and enhance crop growth using less nitrogen fertilizer, which would benefit human nutrition and the environment.