From major crops to sugarcane: Rethinking nitrogen use efficiency for a sustainable future

Nitrogen is a key nutrient for plant growth and a major fertilizer input in agriculture. However, the average nitrogen use efficiency (NUE) of most crops remains below 50%, reflecting not only excessive fertilizer application but also the limited capacity of cropping systems to efficiently convert nitrogen inputs into stable biomass and yield. This increases production costs and leads to environmental pollution and ecological imbalance. Therefore, enhancing NUE has become a crucial objective for sustainable agricultural development. So far, although advanced tools such as high-throughput phenotyping and next-generation sequencing have facilitated NUE breeding, several challenges persist. These include accurate phenotyping of complex traits, the development of molecular markers, and the execution of quantitative trait locus (QTL) mapping, which is complicated by genomic diversity and genotype-by-environment interactions. Recently, major crops such as wheat, rice, and maize have progressively advanced from physiological studies to molecular dissection and breeding integration. It also highlighted recent progress in understanding nitrogen efficiency regulatory networks in sugarcane, molecular marker-assisted breeding, and optimized fertilization practices. Nevertheless, these findings remain insufficiently integrated into breeding pipelines and production systems. This review summarizes advances in crop NUE research and discusses their implications for sugarcane, highlighting key challenges and emerging opportunities for improving NUE and supporting sustainable crop production. • Summarizes NUE advances in rice, wheat and maize—gene identification, QTLs, mechanisms. • Highlights sugarcane-specific NUE insights—novel genes, microbiome interactions, and optimized fertilization. • Analyzes sugarcane NUE challenges—complex phenotypes, polyploidy, and unstable traits. • Proposes future NUE strategies: gene editing, multi-omics, and precision agriculture.