Over the last several decades, increased agricultural production has been driven by improved agronomic practices and a dramatic increase in the use of nitrogen-containing fertilizers to maximize the yield potential of crops. To reduce input costs and to minimize the potential environmental impacts of nitrogen fertilizer that has been used to optimize yield, an increased understanding of the molecular responses to nitrogen under field conditions is critical for our ability to further improve agricultural sustainability. Using maize (Zea mays) as a model, we have characterized the transcriptional response of plants grown under limiting and sufficient nitrogen conditions and during the recovery of nitrogen-starved plants. We show that a large percentage (approximately 7%) of the maize transcriptome is nitrogen responsive, similar to previous observations in other plant species. Furthermore, we have used statistical approaches to identify a small set of genes whose expression profiles can quantitatively assess the response of plants to varying nitrogen conditions. Using a composite gene expression scoring system, this single set of biomarker genes can accurately assess nitrogen responses independently of genotype, developmental stage, tissue type, or environment, including in plants grown under controlled environments or in the field. Importantly, the biomarker composite expression response is much more rapid and quantitative than phenotypic observations. Consequently, we have successfully used these biomarkers to monitor nitrogen status in real-time assays of field-grown maize plants under typical production conditions. Our results suggest that biomarkers have the potential to be used as agronomic tools to monitor and optimize nitrogen fertilizer usage to help achieve maximal crop yields.

Breeding programs aim to improve crop yield and environmental stability for enhanced food security. The principal methodology in breeding for stable yield gain relies on the indirect selection of beneficial genetics by yield evaluation across diverse environmental conditions. This methodology requires substantial resources while delivering a slow pace of yield gain and environmental adaptation. Alternative methods are required to accelerate gain and adaptation, becoming even more imperative in a changing climate. New molecular tools and approaches can enable accelerated creation and deployment of multiple alleles of genes identified to control key traits. With the advent of tools that enable breeding by targeted allelic selection, identifying gene targets associated with an improved crop performance ideotype will become crucial. Previous studies have shown that altered photoperiod regimes increase yield in wheat (Triticum aestivum). In the current study, we have employed such treatments to study the resulting yield ideotype in five spring wheat cultivars. We found that the photoperiod treatment creates a yield ideotype arising from delayed spike establishment rates that are accompanied by increased early shoot expression of TARGET OF EAT1 (TaTOE1) genes. Genes identified in this way could be used for ideotype‐based improve crop performance through targeted allele creation and selection in relevant environments.