Chapter Six - Optimizing crop nitrogen use efficiency: Integrating root performance and machine learning into nutrient management.

Nitrogen (N) is an essential nutrient for plant healthy growth and development, determining crop performance and yield outcomes. However, less than 50% of the N fertilizer applied in modern agricultural systems is effectively utilized by crops in the year of planting, causing resource waste and environmental harm. To improve N use efficiency (NUE), it is crucial to prioritize root performance as it primarily controls the plants' ability to absorb and utilize soil nutrients. The robustness of the root system is also closely related to crop lodging, which is an important factor that hinders the absorption, assimilation, translocation and distribution of N in major field crops. This review attempts to comprehensively summarize recent advances in plant root biology in the context of climate change, emphasizing its important role in soil nutrient dynamics and crop lodging risk, as well as its comprehensive impact on NUE of field grain crops. We discussed the importance of balanced and precision nutrient management to improve NUE and highlighted the innovative role of machine learning in modern agriculture, including root phenotyping, crop lodging detection and nutrient management decisions. Overall, combining machine learning with root biology, along with other practices such as crop rotation, cover cropping, use of biostimulants, and balanced nutrient supply, can reduce lodging risk and promote N uptake and utilization, thereby simultaneously improving NUE, crop productivity and agroecosystem sustainability. This helps ultimately secure our food supply while minimizing the negative impact of N on the environment facing unprecedent climate change. [ABSTRACT FROM AUTHOR]