Advances in Water and Nitrogen Management for Smart Agriculture

Water and nitrogen are the key macro inputs for ensuring agricultural production and productivity. Deficiency of these inputs during crop growth period or at critical growth stages can reduce yield up to 50-70%. Sustainable management of these inputs needs assessment of their availability in soil and plant. Agriculture 4.0 consisting remote sensing (i.e. multispectral and hyperspectral remote sensing), use of sensors, computer vision techniques and data science and analytics aid in early detection and prediction of these deficiencies. Different plant and soil parameter sensors, UAVs (unmanned aerial vehicles) and UGVs (unmanned ground vehicles), and internet of things further improve stress detection and monitoring. By integrating real-time data with AI powered solutions, farmers can decide application of irrigation and fertilizers more efficiently, targeting only the site specific areas. This will optimize input application, reduce resource waste, minimizes negative environmental impact, and boosts economic returns. As climate variability continues to challenge agriculture, developing robust monitoring systems for water and nitrogen stress is essential for developing crop resilience. Evolution and application of advanced tools and techniques especially artificial intelligence, computer vision have enabled the researchers to identify, classify, quantify and predict such stresses more precisely.Agricultural systems face increasing pressure from climate variability, water scarcity, and inefficient nutrient management, which threaten sustainable food production. In many regions, irrigation and nitrogen fertilizer applications are still based on generalized recommendations rather than real-time crop needs, leading to excessive input use, nutrient losses, environmental pollution, and higher greenhouse gas emissions. These challenges hinder progress toward key Sustainable Development Goals, particularly SDG 2 (Zero Hunger), SDG 12 (Responsible Consumption and Production), and SDG 13 (Climate Action). To address this, precision agriculture technologies such as soil and plant sensors, IoT-based monitoring, remote sensing, and data-driven decision support systems enable early detection of crop water and nitrogen stress. These tools support site-specific irrigation and nutrient management, improving resource-use efficiency, reducing environmental impacts, and enhancing resilience to climate-related stresses.This Research Topic focuses on recent advancements in computer vision techniques and data analytics for sustainable water and nitrogen management in crops for diverse agroecosystems. With increasing climate variability and resource constraints, innovative digital tools are essential for early detection and management of abiotic stresses. The Research Topic aims to bring together studies utilizing technologies such as remote sensing, UAV imagery, IoT-based sensors, machine learning, and advanced data analytics to improve decision-making in crop management. Researchers worldwide are invited to contribute original research and review articles that involve diverse tools and techniques for solving a multitude of problems related to abiotic factors under the changing climate from different parts of the globe together at a single platform. Topic editors: Yogesh Anand Rajwade, Vinay Nangia, Sahila Beegum, Mukesh Kumar Tiwari, Narendra Chandel, Sachinkumar Nandgude Source: https://www.frontiersin.org/research-topics/79417/advances-in-water-and-nitrogen-management-for-smart-agriculture