Nitika Sandhu, Aman Kumar, Jasneet Singh, Gaurav Augustine, Jaismeen Kaur, Muskan Gupta, Harsh Shukla, Ekta Kharche
The study explores genomic and molecular approaches to optimize Nitrogen Use Efficiency (NUE) in crops, focusing on genes, QTLs, root architecture, nitrate transporters, and nitrogen-responsive transcription factors. Optimizing NUE can mitigate greenhouse gas emissions and reduce the carbon footprint in agriculture. Genomic innovations can help breed climate-resilient varieties with enhanced NUE, contributing to food security and environmental sustainability.
Nitrogen (N) is a critical macronutrient for crop productivity, yet its inefficient utilization in agricultural systems contributes to environmental degradation and increased carbon emissions. Enhancing Nitrogen Use Efficiency (NUE) in crops is essential for sustainable food production under changing climatic conditions. This chapter explores genomic and molecular approaches to optimize NUE, integrating advances in genomic technologies, marker-assisted selection and gene-editing technologies. Key regulatory networks governing nitrogen uptake, assimilation and remobilization are examined, with a focus on genes and quantitative trait loci (QTLs) associated with improved NUE. The role of root architecture, nitrate transporters and nitrogen-responsive transcription factors in enhancing nutrient acquisition is highlighted. Additionally, the chapter discusses the interplay between nitrogen metabolism and carbon sequestration, emphasizing how optimizing NUE can mitigate greenhouse gas emissions. The chapter also addresses the challenges associated with enhancing NUE through genomic approaches, emphasizing the need for integrating these strategies with sustainable agronomic practices and policies to achieve long-term food security and environmental sustainability. By leveraging genomic innovations, this study provides insights into breeding climate-resilient varieties with enhanced NUE, reducing the carbon footprint while ensuring food security in a resource-constrained world.